Image Enhancement

Recently, many researchers have directed their attention to methods of predicting shorelines by the use of multispectral images. Thus, a simple and optimised method using image enhancements is proposed to improve the low contrast of the Satellite pour l'Observation de la Terre-5 (SPOT-5) images in the detection of shorelines. The near-infrared (NIR) channel is important in this study to ensure the contrast of the vegetated area and sea classification, due to the high reflectance of leaves in the near infrared wavelength region. This study used five scenes of interest to show the different results in shoreline detection. The results demonstrated that the proposed method performed in an enhanced manner as compared to current methods when dealing with the low contrast ratio of SPOT-5 images. As a result, by utilising the near-infrared histogram equalization (NIR-HE), the contrast of all datasets was efficiently restored, producing a higher efficiency in edge detection, and achieving higher overall accuracy. The improved filtering method showed significantly better shoreline detection results than the other filter methods. It was concluded that this method would be useful for detecting and monitoring the shoreline edge in Tanjung Piai.

Time-resolved contrast-enhanced magnetic resonance angiography of the brain is challenging due to the need for rapid imaging and high spatial resolution. Moreover, the significant dispersion of the intravenous contrast bolus as it passes through the heart and lungs increases the overlap between arterial and venous structures, regardless of the acquisition speed and reconstruction window. An innovative technique is presented that divides a single dose contrast into two injections. Initially a small volume of contrast material (2-3 mL) is used to acquiring timeresolved weighting images with a high frame rate (2 frames/s) during the first pass of the contrast agent. The remaining contrast material is used to obtain a high resolution whole brain contrastenhanced (CE) magnetic resonance angiography (0.57 × 0.57 × 1 mm 3 ) that is used as the spatial constraint for Local Highly Constrained Projection Reconstruction (HYPR LR) reconstruction. After HYPR reconstruction, the final dynamic images (HYPR CE) have both high temporal and spatial resolution. Furthermore, studies of contrast kinetics demonstrate that the shorter bolus length from the reduced contrast volume used for the first injection significantly improves the arterial and venous separation.

Encephalitis is generally diagnosed by clinical symptoms, cerebrospinal fluid examination, and imaging studies including CT, MR imaging and perfusion single photon emission tomography (SPECT). However, the role of positron emission tomography (PET) in diagnosis of encephalitis remains unclear. A 49-year-old woman presenting with coma and elevated inflammatory reaction was diagnosed as having encephalitis according to slow activity on electroencephalogram, broad cortical lesion in MR fluid attenuated inversion recovery image, and increased blood flow demonstrated by SPECT. PET revealed increased accumulation of 11 C-methionine (MET) in the affected brain tissues. After the symptom had improved two months later, the accumulation of MET as well as the abnormal findings of MR imaging and SPECT was normalized. This case indicated that MET PET may monitor the activity of encephalitis.

A novel temporal correlation technique was used to map the first-pass transit of iodinated contrast agents through the brain. Transit profiles after bolus injections were measured with dynamic computed tomography (CT) scanning (1 image/s over 50 s). A rabbit model of focal cerebral ischemia (n = 6) was used, and dynamic CT scans were performed at 30, 60, 90, and 120 min postocclusion. Within the ischemic core, no bolus transit was detectable, demonstrating that complete ischemia was present after arterial occlusion. In the periphery of the ischemic distribution, transit dynamics showed smaller peaks, broadened profiles, and overall delay in bolus transit. A cross-correlation method was used to generate maps of delays in ischemic transit profiles compared with normal transit profiles from the contralateral hemisphere. These maps showed that penumbral regions surrounding the ischemic core had significantly delayed bolus transit profiles. Enlargement of the ischemic core over time (fro...

Background and purpose: MR contrast media are commonly used but do not have evidence-based guidelines for their application. This investigation seeks to define specific methodological problems in the MR contrast media literature and to suggest guidelines for an improved study design. Methods: To evaluate the reported clinical efficacy of MR contrast media in neuroimaging, we performed a critical review of the literature. From 728 clinical studies retrieved via MEDLINE, we identified 108 articles that evaluated contrast media efficacy for a minimum of 20 patients per study. The articles were randomly assigned to four readers (a fifth reader reviewed all of the articles) who were blinded to article titles, authors, institutions, and journals of publication. The readers applied objective, well-established methodological criteria to assign each article a rating of A, B, C, or D. Results: One hundred one of 108 articles received a D rating, six received a C rating, and one received a B rating. In general, the Methods sections of the evaluated articles did not contain details that would allow the reader to calculate reliable measures of diagnostic accuracy, such as sensitivity and specificity. Specifically, a common problem was failure to establish and uniformly apply an acceptable standard of reference. In addition, images were not always interpreted independently from the reference standard. Radiologists and clinicians need to determine the applicability of any published study to their own practices. Unfortunately, the studies we reviewed commonly lacked clear descriptions of patient demographics, the spectrum of symptomatology, and the procedure for assembling the study cohort. Finally, small sample sizes with inadequate controls were presented in almost all of the articles. Conclusion: Although MR contrast media are widely used and play an essential role in lesion detection and confidence of interpretation, no rigorous studies exist to establish valid sensitivity and specificity estimates for their application. On the basis of this review, we herein describe basic methods to document improvements in technology. Such studies are essential to devise measures of diagnostic accuracy, which can form the basis for further studies that will assess diagnostic and therapeutic impact and, ultimately, patient outcomes.

MR contrast media are commonly used but do not have evidence-based guidelines for their application. This investigation seeks to define specific methodological problems in the MR contrast media literature and to suggest guidelines for an improved study design. To evaluate the reported clinical efficacy of MR contrast media in neuroimaging, we performed a critical review of the literature. From 728 clinical studies retrieved via MEDLINE, we identified 108 articles that evaluated contrast media efficacy for a minimum of 20 patients per study. The articles were randomly assigned to four readers (a fifth reader reviewed all of the articles) who were blinded to article titles, authors, institutions, and journals of publication. The readers applied objective, well-established methodological criteria to assign each article a rating of A, B, C, or D. One hundred one of 108 articles received a D rating, six received a C rating, and one received a B rating. In general, the Methods sections of...

Unilateral solid kidney tumor of fetus is an extremely rare phenomenon in day to day obstetric practice. Antenatal diagnosis of it is also very unusual. Only few cases of it diagnosed by prenatal ultrasound have so far been reported in world literature. Although, Clinical suspicion of kidney disease arises with poly/oligohydramnios, sonographic confirmation of type of kidney lesion is very rare. However, on the basis of this imaging evidence ultimate management is planned. In this case, congenital renal tumor of baby was first diagnosed on the basis of sonographic report. It suggested clearly that it was a unilateral solid parenchymal tumor. Caesarean delivery was advocated on maternal request, keeping in mind the safe delivery of preterm baby. After managing immediate neonatal problem baby was referred to paediatric-surgery unit. There he was operated upon two weeks after delivery. Gradually, the baby was recovered from right nephrectomy and followed up for 6 months.

Directed graph representations of brain networks are increasingly being used to indicate the direction and level of influence among brain regions. Most of the existing techniques for directed graph representations are based on time series analysis and the concept of causality, and use time lag information in the brain signals. These time lag-based techniques can be inadequate for functional magnetic resonance imaging (fMRI) signal analysis due to the limited time resolution of fMRI as well as the low frequency hemodynamic response. The aim of this paper is to present a novel measure of necessity that uses asymmetry in the joint distribution of brain activations to infer the direction and level of interaction among brain regions. We present a mathematical formula for computing necessity and extend this measure to partial necessity, which can potentially distinguish between direct and indirect interactions. These measures do not depend on time lag for directed modeling of brain interactions and therefore are more suitable for fMRI signal analysis. The necessity measures were used to analyze resting state fMRI data to determine the presence of hierarchy and asymmetry of brain interactions during resting state. We performed ROI-wise analysis using the proposed necessity measures to study the default mode network. The empirical joint distribution of the fMRI signals was determined using kernel density estimation, and was used for computation of the necessity and partial necessity measures. The significance of these measures was determined using a one-sided Wilcoxon rank-sum test. Our results are consistent with the hypothesis that the posterior cingulate cortex plays a central role in the default mode network.

Purpose-To enable high-quality correction of susceptibility-induced geometric distortion artifacts in diffusion MRI images without increasing scan time. Theory and Methods-A new method for distortion correction is proposed based on subsampling a generalized version of the state-of-the-art reversed-gradient distortion correction method. Rather than acquire each q-space sample multiple times with different distortions (as in the conventional reversed-gradient method), we sample each q-space point once with an interlaced sampling scheme that measures different distortions at different q-space locations. Distortion correction is achieved using a novel constrained reconstruction formulation that leverages the smoothness of diffusion data in q-space. Results-The effectiveness of the proposed method is demonstrated with simulated and in vivo diffusion MRI data. The proposed method is substantially faster than the reversed-gradient method, and can also provide smaller intensity errors in the corrected images and smaller errors in derived quantitative diffusion parameters. The proposed method enables state-of-the-art distortion correction performance without increasing data acquisition time.

First unequal error protection (UEP) proposals date back to the 1960's (Masnick and Wolf; 1967), but now with the introduction of scalable video, UEP develops to a key concept for the transport of multimedia data. The paper presents an overview of some new approaches realizing UEP properties in physical transport, especially multicarrier modulation, or with LDPC and Turbo codes. For multicarrier modulation, UEP bit-loading together with hierarchical modulation is described allowing for an arbitrary number of classes, arbitrary SNR margins between the classes, and arbitrary number of bits per class. In Turbo coding, pruning, as a counterpart of puncturing is presented for flexible bit-rate adaptations, including tables with optimized pruning patterns. Bit- and/or check-irregular LDPC codes may be designed to provide UEP to its code bits. However, irregular degree distributions alone do not ensure UEP, and other necessary properties of the parity-check matrix for providing UEP are...

The field of signal or image processing naturally deals with the image de-noising. The image may be corrupted by a noise and/or poor illumination and/or high temperature, and/or transmission. The ability of capturing the energy of signal provides us the better solution towards de-noising of a natural images corrupted by Gaussian noise using multi-wavelet techniques. Multi-wavelet can gratify with symmetry and asymmetry which are very imperative characteristics in signal processing. The image will be highly de-noised if and only if the degree of the noise is lesser. Normally, its energy is dispersed over low frequency band while both its noise and details are dispersed over high frequency band. Corresponding hard threshold used in various scale high frequency sub-bands. In this paper proposed to indicate the aptness of various wavelets and multi-wavelet based and a size of different neighborhood on the performance of image de-noising algorithm in terms of PSNR value. Finally it compa...

Image enhancement is one of the most critical subjects in computer vision and image processing fields. It can be considered as means to enrich the perception of images for human viewers. All kinds of images typically suffer from different problems such as weak contrast and noise. The primary purpose of image enhancement is to change an image's visual appearance. Many algorithms have recently been proposed for enhancing medical images. Image enhancement is still deemed a challenging task. In this paper, the fuzzy c means clustering (FCM) technique is utilized to enhance the medical images. The method of enhancement consists of two stages. The proposed algorithm conducts a cluster test on the image pixels. It then increases the difference of gray level between the diverse objects to accomplish the enhancement purpose of the medical images. The experimental results have been tested using various images. The algorithm enhanced the small target of the image to a reasonable limit and revealed favorable performance. The results of image enhancement techniques were evaluated by using terms of different criteria such as peak signal to noise ratio (PSNR), mean square error (MSE) and average information contents (AIC), showing promising performance.

The purpose of this study was to compare sulfur hexafluoride microbubble (SonoVue)-enhanced myocardial contrast echocardiography (MCE) with single-photon emission computed tomography (SPECT) relative to coronary angiography (CA) for assessment of coronary artery disease (CAD). Small-scale studies have shown that myocardial perfusion assessed by SonoVue-enhanced MCE is a viable alternative to SPECT for CAD assessment. However, large multicenter studies are lacking. Patients referred for myocardial ischemia testing at 34 centers underwent rest/vasodilator SonoVue-enhanced flashreplenishment MCE, standard 99m Tc-labeled electrocardiography-gated SPECT, and quantitative CA within 1 month. Myocardial ischemia assessments by 3 independent, blinded readers for MCE and 3 readers for SPECT were collapsed into 1 diagnosis per patient per technique and were compared to CA (reference standard) read by 1 independent blinded reader. Of 628 enrolled patients who received SonoVue (71% males; mean age: 64 years; >1 cardiovascular [CV] risk factor in 99% of patients) 516 patients underwent all 3 examinations, of whom 161 (31.2%) had !70% stenosis (131 had single-vessel disease [SVD]; 30 had multivessel disease), and 310 (60.1%) had !50% stenosis. Higher sensitivity was obtained with MCE than with SPECT (75.2% vs. 49.1%, respectively; p < 0.0001), although specificity was lower (52.4% vs. 80.6%, respectively; p < 0.0001) for !70% stenosis. Similar findings were obtained for patients with !50% stenosis. Sensitivity levels for detection of SVD and proximal disease for !70% stenosis were higher for MCE (72.5% vs. 42.7%, respectively; p < 0.0001; 80% vs. 58%, respectively; p ¼ 0.005, respectively). SonoVue-enhanced MCE demonstrated superior sensitivity but lower specificity for detection of CAD compared to SPECT in a population with a high incidence of CV risk factors and intermediate-high prevalence of CAD. (A phase III study to compare SonoVueÒ enhanced myocardial echocardiography [MCE] to single photon emission computerized tomography [ECG-GATED SPECT], at rest and at peak of low-dose Dipyridamole stress test, in the assessment of significant coronary artery disease [CAD] in patients with suspect or known CAD using Coronary Angiography as Gold Standard-SonoVue MCE vs SPECT; EUCTR2007-003492-39-GR) (

MRI remains the premier method for non-invasive imaging of soft-tissue. Since the first demonstration of ULF MRI the trend has been towards ever higher magnetic fields. This is because the signal, and efficiency of Faraday detectors, increases with ever higher magnetic fields and corresponding Larmor frequencies. Nevertheless, there are many compelling reasons to continue to explore MRI at much weaker magnetic fields, the so-called ultra-low field or (ULF) regime. In the past decade many excellent proof-of-concept demonstrations of ULF MRI have been made. These include combined MRI and magnetoencephalography, imaging in the presence of metal, unique tissue contrast, and implementation in situations where a high magnetic field is simply impractical. These demonstrations have routinely used pulsed pre-polarization (at magnetic fields from $10 to 100 mT) followed by read-out in a much weaker (1-100 lT) magnetic fields using the ultra-sensitive Superconducting Quantum Interference Device (SQUID) sensor. Even with pre-polarization and SQUID detection, ULF MRI suffers from many challenges associated with lower magnetization (i.e. signal) and inherently long acquisition times compared to conventional >1 T MRI. These are fundamental limitations imposed by the low measurement and gradient fields used. In this review article we discuss some of the techniques, potential applications, and inherent challenges of ULF MRI.

As a starting point of this paper we present a problem from mammographic image processing. We show how it can be formulated as an optimal control problem for PDEs and illustrate that it leads to penalty terms which are non-standard in the theory of optimal control of PDEs. To solve this control problem we use a generalization of the conditional gradient method which is especially suitable for non-convex problems. We apply this method to our control problem and illustrate that this method also covers the recently proposed method of surrogate functionals from the theory of inverse problems.

continue to emphasize that neonatal EDH is an uncommon diagnosis despite increasing use of neuroimaging . Most neonatal EDH cases are related to birth trauma. Reported obstetric risk factors include prolonged or obstructed labor, cephalopelvic disproportion, nulliparity, instrumental delivery with forceps or vacuum extraction, and excessive external compression or fundal pressure during delivery. Although definitions of prolonged labor vary across obstetric guidelines, the primary contributing factor in our case appeared to be intense maternal straining together with the application of fundal pressure rather than prolonged labor itself. In addition, a few cases have been described after accidental falls at the

The largest organ in the body is the liver and primarily helps in metabolism and detoxification. Liver segmentation is a crucial step in liver cancer detection in computer vision-based biomedical image analysis. Liver segmentation is a critical task and results in under-segmentation and over-segmentation due to the complex structure of abdominal computed tomography (CT) images, noise, and textural variations over the image. This paper presents liver segmentation in abdominal CT images using marker-based watershed transforms. In the pre-processing stage, a modified double stage gaussian filter (MDSGF) is used to enhance the contrast, and preserve the edge and texture information of liver CT images. Further, marker controlled watershed transform is utilized for the segmentation of liver images from the abdominal CT images. Liver segmentation using suggested MDSGF and marker-based watershed transform help to diminish the under-segmentation and over-segmentation of the liver object. The...

Ischemic heart disease continues to rank as the leading cause of death and disability worldwide and it remains the most prevalent underlying cause of cardiomyopathy and heart failure. In a pooled analysis of 13 major multicenter heart failure trials, ischemic cardiomyopathy (ICM) was responsible for nearly 70% of all heart failure cases. 2 Clinically, ICM is defined by impaired left ventricular (LV) systolic function in the setting of significant coronary artery disease. 2 Despite significant progress in pharmacotherapy, devicebased treatments, and revascularization techniques, ICM still imposes a heavy global health burden. Mortality rates hover around 16% at one year and can climb to nearly 40% by five years in both the U.S. and Europe. These figures underscore the urgent need for early, accurate diagnosis,

In clinical applications where structural asymmetries between homologous shapes have been correlated with pathology, the questions of definition and quantification of "asymmetry" arise naturally. When not only the degree but the position of deformity is thought relevant, asymmetry localization must also be addressed. Asymmetries between paired shapes have already been formulated in terms of (nonrigid) diffeomorphisms between the shapes. For the infinity of such maps possible for a given pair, we define optimality as the minimization of deviation from isometry under the constraint of piecewise deformation homogeneity. We propose a novel variational formulation for segmenting asymmetric regions from surface pairs based on the minimization of a functional of both the deformation map and the segmentation boundary, which defines the regions within which the homogeneity constraint is to be enforced. The functional minimization is achieved via a quasi-simultaneous evolution of the map and the segmenting curve, conducted on and between two-dimensional surface parametric domains. We present examples using both synthetic data and pairs of left and right hippocampal structures and demonstrate the relevance of the extracted features through a clinical epilepsy classification analysis.

The presence of BOLD contrast in M R I studies has been shown to interfere with least squares motion correction algorithms. We derive a theoretical expression for the error that activation contributes to least squares motion correction. These estimates match errors generated by motion correction experiments done on a simulated fMRl dataset. The analysis is not specific to activation related errors, and can be used to study the effect of any expected difference between two volumes being registered.

Materials and Methods: Case Report with Review of Literature Results: We report a case of bilateral primary lipoma in a 21year old Nigerian which initially posed a diagnostic dilemma due to its similarity with the testes, both in size, shape and appearance on ultrasound scan. Diagnosis was then made with the aid of Magnetic resonance imaging and the patient was managed with surgical excision and biopsy with no resultant post op complication. It is therefore recommended that for proper evaluation of patients with scrotal masses, radiological imaging modalities as well as histology are useful in aiding diagnosis. Background: Primary scrotal lipoma is a very rare clinical entity where tumour of mature adipocytes arise from the subcutaneous tissue of scrotal sac. Accurate clinical diagnosis is important to exclude possible differential diagnosis.

The automatic retinal disease diagnosis by artificial intelligent is an interesting and challenging topic in the medical field. It requires an appropriate image enhancement technique and a sufficient training dataset for the specific retina conditions. The aim of this study was to design an automatic diagnosis convolutional neural network (CNN) model which does not require a large training dataset to specifically identify diabetic retinopathy symptoms, which are cotton wool, exudates spots, and red lesion in colour fundus pictures. A novel framework comprised image enhancement method by using upgraded contrast limited adaptive histogram equalization (UCLAHE) filter and transferred pre-trained networks was developed to classify the retinal diseases regarding to the symptoms. The performance of the proposed framework was evaluated based on accuracy, sensitivity, and specificity metrics. The collected results have proven the robustness of the proposed framework in offering good accuracy in retina diseases diagnosis.

Segmentation of the human cerebral cortex from MRI has been subject of much attention during the last decade. Methods based on active surfaces for representing and extracting the cortical boundaries have shown promising results. We present an active surface method, that extracts the inner and outer cortical boundaries using a combination of different vector fields and a local weighting method based on the intrinsic properties of the deforming surface. Our active surface model deforms polygonal meshes to fit the boundaries of the cerebral cortex using a force balancing scheme. As a result of the local weighting strategy and a self-intersection constraint, the method is capable of modelling tight sulci where the image edge is missing or obscured. The performance of the method is evaluated using both real and simulated MRI data.

This paper does not study a drug or a molecular pathway, but rather an oncologic decision problem: in oral squamous cell carcinoma with a clinically negative neck (cN0), is it better to observe, perform elective neck dissection, irradiate, or use more refined staging techniques such as sentinel lymph node biopsy (SLNB)? The review's answer goes in a fairly clear direction: neck dissection appears superior to a "wait and see" strategy, and SLNB appears superior to USgFNAC as a staging tool for the cN0 neck.

Purpose: To develop a method for high-resolution cardiac T1 mapping. Methods: A new method, accelerated and navigator-gated look-locker imaging for cardiac T1 estimation (ANGIE), was developed. An adaptive acquisition algorithm that accounts for the interplay between navigator gating and undersampling patterns well-suited for compressed sensing was used to minimize scan time. Computer simulations, phantom experiments, and imaging of the left ventricle (LV) were used to optimize and evaluate ANGIE. ANGIE's high spatial resolution was demonstrated by T1 mapping of the right ventricle (RV). Comparisons were made to modified Look-Locker imaging (MOLLI). Results: Retrospective reconstruction of fully sampled datasets demonstrated the advantages of the adaptive algorithm. For the LV, ANGIE measurements of T1 were in good agreement with MOLLI. For the RV, ANGIE achieved a spatial resolution of 1.2 × 1.2 mm 2 with a scan time of 157±53 s per slice, and measured RV T1 values of 980±96 ms versus 1076±157 ms for lowerresolution MOLLI. ANGIE provided lower intrascan variation in the RV T1 estimate compared with MOLLI (P<0.05). ANGIE enables high-resolution cardiac T1 mapping in clinically reasonable scan times. ANGIE opens the prospect of quantitative T1 mapping of thin cardiovascular structures such as the RV wall.

To determine the frequency of appearance of various MR signs in mesial temporal sclerosis, to determine the optimal scanning planes for their visualization, and to propose a histologic explanation for the diminished demarcation between gray and white matter in the temporal lobe, a frequent MR finding in patients with mesial temporal sclerosis. MR scans of 14 surgically treated patients with epilepsy and histologically proven mesial temporal sclerosis were assessed for the presence of six features: feature 1, high signal intensity in the hippocampus; 2, reduced hippocampal size; 3, ipsilateral atrophy of the hippocampal collateral white matter; 4, enlarged temporal horn; 5, reduced gray-white matter demarcation in the temporal lobe; and 6, decreased temporal lobe size. Feature 1 was present in 14 patients and was best appreciated on the T2-weighted images in planes parallel to the long axes of the hippocampi. Feature 2, present in 12 patients, and feature 6, present in 9 patients, we...

Purpose: To evaluate the relative enhancement of liver, pancreas, focal nodular hyperplasia (FNH), pancreas-toliver index, and FNH-to-liver index in the hepatic arterial dominant phase (HADP) after injection of hepatocyte-specific MRI contrast agents, gadoxetic acid and gadobenate dimeglumine, on 3 and 1.5 Tesla (T) MRI in the same patient. The MRI database was retrospectively searched to identify consecutive patients who underwent abdominal MRI at 3T and 1.5T systems, using both 0.025 mmol/kg gadoxetic acid-enhanced and 0.05 mmol/kg gadobenate dimeglumine-enhanced MRI at the same magnetic strength field system. 22 patients were identified, 10 were scanned at 3T system and 12 at 1.5T system. The enhancement of liver, pancreas, and FNH was evaluated quantitatively on MR images. The relative enhancement of liver in HADP in the gadobenate dimeglumine-enhanced group in all subjects was significantly higher than that in gadoxetic acidenhanced group (P ¼ 0.023). The gadobenate dimeglumine-enhanced group in HADP had better relative enhancement of pancreas and FNH, pancreas-to-liver index, and FNH-to-liver index than gadoxetic acidenhanced group, but the difference was not statistically significant. The 0.05 mmol/kg gadobenate dimeglumine-enhanced abdominal MRI studies at 3T and 1.5T MR systems are superior in relative enhancement of the liver in HADP to 0.025 mmol/kg gadoxetic acid-enhanced MRI. This type of assessment may provide comparative effectiveness data.

ABSTRACT

Intraventricular hemorrhage (IVH) is a type of bleeding in newborns that occurs after germinal matrix hemorrhage. The  aim of this report is to determine the causes and pathologies associated with HIV and the postoperative outcomes with conventional or surgical management, based on bleeding findings through neurographic diagnostic means and care in  the intensive care unit (ICU) during the development of the disease. A spontaneously born premature infant at 27 weeks  gestation, delivered in cephalic presentation, was admitted to the emergency department with ruptured membranes and  two umbilical cord entanglements. There was no spontaneous breathing. Resuscitation was performed in the delivery
room with mask ventilation for 1 minute and intubation for 2 minutes. Surfactant replacement therapy was administered  with positive results. The Apgar score was 3/4/5, and weight was 1190 g. The infant was transferred to the NICU for further care and monitoring. A premature infant was transferred to the neonatal unit at 1 month and 14 days of age (33
weeks  gestation)  in  moderate  condition  due  to  respiratory  distress;  oxygen  dependence  due  to  bronchopulmonary  dysplasia  (BPD);  neurological  symptoms,  including  central  nervous  system  depression  syndrome  due  to  hypoxic- hemorrhagic CNS damage; and ventriculomegaly.

PurposeTo design, fabricate, characterize, and in vivo assay clinically viable magnetic particles for MRI‐based cell tracking.MethodsPoly(lactide‐co‐glycolide) (PLGA) encapsulated magnetic nano and microparticles were fabricated. Multiple biologically relevant experiments were performed to assess cell viability, cellular performance, and stem cell differentiation. In vivo MRI experiments were performed to separately test cell transplantation and cell migration paradigms, as well as in vivo biodegradation.ResultsHighly magnetic nano (∼100 nm) and microparticles (∼1–2 µm) were fabricated. Magnetic cell labeling in culture occurred rapidly achieving 3–50 pg Fe/cell at 3 h for different particles types, and &gt;100 pg Fe/cell after 10 h, without the requirement of a transfection agent, and with no effect on cell viability. The capability of magnetically labeled mesenchymal or neural stem cells to differentiate down multiple lineages, or for magnetically labeled immune cells to release c...

We describe an algorithm for finding particle images in cryo-EM micrographs. The algorithm starts from a crude 3D map of the target particle, computed from a relatively small number of manually picked images, and then projects the map in many different directions to give synthetic 2D templates. The templates are clustered and averaged and then cross-correlated with the micrographs. A probabilistic model of the imaging process then scores cross-correlation peaks to produce the final picks. We give quantitative results on two quite different target particles: keyhole limpet hemocyanin and p97 AAA ATPase. On these particles our automatic particle picker shows human performance level, as measured by the Fourier shell correlations of 3D reconstructions.

The task of creating detailed three dimensional virtual worlds for interactive entertainment software can be simplified by using Constructive Solid Geometry (CSG) techniques. CSG allows artists to combine primitive shapes, visualized through polygons, into complex and believable scenery. Constructive Volume Geometry (CVG) is a super-set of CSG that operates on volumetric data, which consists of values recorded at constant intervals in three dimensions of space. To allow volumetric data to be integrated into existing frameworks, indirect visualization is performed by constructing and visualizing polygon meshes corresponding to the implicit surfaces in the volumetric data. The Indirect CVG (ICVG) algebra, which provides constructive volume geometry operators appropriate to volumetric data that will be indirectly visualized is introduced. ICVG includes operations analogous to the union, difference, and intersection operators in the standard CVG algebra, as well as new operations. Additionally, a series of volumetric primitives well suited to indirect visualization is defined.

Many deep neural networks are built by using stacked convolutional layers of fixed and single size (often 3×3) kernels. This paper describes a method for training the size of convolutional kernels to provide varying size kernels in a single layer. The method utilizes a differentiable, and therefore backpropagation-trainable Gaussian envelope which can grow or shrink in a base grid. Our experiments compared the proposed adaptive layers to ordinary convolution layers in a simple two-layer network, a deeper residual network, and a U-Net architecture. The results in the popular image classification datasets such as MNIST, MNIST-CLUTTERED, CIFAR-10, Fashion, and "Faces in the Wild" showed that the adaptive kernels can provide statistically significant improvements on ordinary convolution kernels. A segmentation experiment in the Oxford-Pets dataset demonstrated that replacing a single ordinary convolution layer in a Ushaped network with a single 7×7 adaptive layer can improve its learning performance and ability to generalize.

Intraoperative brain retraction leads to a misalignment between the intraoperative positions of the brain structures and their previous positions, as determined from preoperative images. In vitro swine brain sample uniaxial tests showed that the mechanical response of brain tissue to compression and extension could be described by the hyper-viscoelasticity theory. The brain retraction caused by the mechanical process is a combination of brain tissue compression and extension. In this paper, we first constructed a hyper-viscoelastic framework based on the extended finite element method (XFEM) to simulate intraoperative brain retraction. To explore its effectiveness, we then applied this framework to an in vivo brain retraction simulation. The simulation strictly followed the clinical scenario, in which seven swine were subjected to brain retraction. Our experimental results showed that the hyper-viscoelastic XFEM framework is capable of simulating intraoperative brain retraction and ...

Plaque assaying, measurement of the number, diameter, and area of plaques in a Petri dish image, is a standard procedure gauging the concentration of phage in biology. This paper presented a novel and effective method for implementing automatic plaque assaying. The method was mainly comprised of the following steps: In the training stage, after pre-processing the images for noise suppression, an initial training set was readied by sampling positive (with a plaque at the center) and negative (plaque-free) patches from the training images, and extracting the HOG features from each patch. The linear SVM classifier was trained in a self-learnt supervised learning strategy to avoid possible missing detection. Specifically, the training set which contained positive and negative patches sampled manually from training images was used to train the preliminary classifier which exhaustively searched the training images to predict the label for the unlabeled patches. The mislabeled patches were...

A new method to measure rotating frame relaxation and to create contrast for MRI is introduced. The technique exploits relaxation along a fictitious field (RAFF) generated by amplitude‐ and frequency‐modulated irradiation in a subadiabatic condition. Here, RAFF is demonstrated using a radiofrequency pulse based on sine and cosine amplitude and frequency modulations of equal amplitudes, which gives rise to a stationary fictitious magnetic field in a doubly rotating frame. According to dipolar relaxation theory, the RAFF relaxation time constant (TRAFF) was found to differ from laboratory frame relaxation times (T1 and T2) and rotating frame relaxation times (T1ρ and T2ρ). This prediction was supported by experimental results obtained from human brain in vivo and three different solutions. Results from relaxation mapping in human brain demonstrated the ability to create MRI contrast based on RAFF. The value of TRAFF was found to be insensitive to the initial orientation of the magneti...

PurposeMRI relaxation measurements are performed in the presence of a fictitious magnetic field in the recently described technique known as RAFF (Relaxation Along a Fictitious Field). This method operates in the 2nd rotating frame (rank n = 2) by using a nonadiabatic sweep of the radiofrequency effective field to generate the fictitious magnetic field. In the present study, the RAFF method is extended for generating MRI contrasts in rotating frames of ranks 1 ≤ n ≤ 5. The developed method is entitled RAFF in rotating frame of rank n (RAFFn).Theory and MethodsRAFFn pulses were designed to generate fictitious fields that allow locking of magnetization in rotating frames of rank n. Contrast generated with RAFFn was studied using Bloch‐McConnell formalism together with experiments on human and rat brains.ResultsTolerance to B0 and B1 inhomogeneities and reduced specific absorption rate with increasing n in RAFFn were demonstrated. Simulations of exchange‐induced relaxations revealed en...

The loss of dopaminergic (DA) neurons in the substantia nigra pars compacta (SNc) is well characterized in Parkinson's disease (PD). Recent developments in magnetic resonance imaging (MRI) techniques have provided the opportunity to evaluate for changes in cellular density. Longitudinal relaxation measurements in the rotating frame (T 1ρ ) provide a unique magnetic resonance imaging (MRI) contrast in vivo. Due to the specificity of T 1ρ to water-protein interactions, the T 1ρ MRI method has strong potential to be used as a non-invasive method for quantification of neuronal density in the brain. Recently introduced adiabatic T 1ρ magnetic resonance imaging (MRI) mapping methods provide a tool to assess molecular motional regimes with high sensitivity due to utilization of an effective magnetic field sweep during adiabatic pulses. In this work, to investigate the sensitivity of T 1ρ to alterations in neuronal density, adiabatic T 1ρ MRI measurements were employed in vivo on itx3-homeobox gene-deficient aphakia mice in which the deficit of DA neurons in the SNc is well established. The theoretical analysis of T 1ρ maps in the different areas of the brain of aphakia mouse suggested variation of the 1 H 2 O rotational correlation times, τ c . This suggests τ c to be a sensitive indicator for neuronal loss during neurological disorders. The results manifest significant dependencies of the T 1ρ relaxations on the cell densities in the SNc, suggesting T 1ρ MRI method as a candidate for detection of neuronal loss in neurological disorders.

In the present study we derive a solution for two site fast exchange-induced relaxation in the presence of a fictitious magnetic field as generated by amplitude and frequency modulated RF pulses. This solution provides a means to analyze data obtained from relaxation experiments with the method called RAFFn (Relaxation Along a Fictitious Field of rank n), in which a fictitious field is created in a coordinate frame undergoing multi-fold rotation about n axes (rank n). The RAFF2 technique is relevant to MRI relaxation methods that provide good contrast enhancement for tumor detection. The relaxation equations for n=2 are derived for the fast exchange regime using density matrix formalism. The method of derivation can be further extended to obtain solutions for n&gt;2.

Widefield deconvolution epifluorescence microscopy (WDEM) combined with fluorescence in situ hybridization (FISH) was performed to identify and characterize single bacterial cells within sections of the mediterranean sponge Chondrosia reniformis. Sponges were embedded in paraffin wax or plastic prior to the preparation of thin sections, in situ hybridization and microscopy. Serial digital images generated by widefield epifluorescence microscopy were visualized using an exhaustive photon reassignment deconvolution algorithm and three-dimensional rendering software. Computer processing of series of images taken at different focal planes with the deconvolution technique provided deblurred three-dimensional images with high optical resolution on a submicron scale. Results from the deconvolution enhanced widefield microscopy were compared with conventional epifluorescent microscopical images. By the application of the deconvolution algorithm on digital image data obtained with widefield epifluorescence microscopy after FISH, the occurrence and spatial arrangement of Desulfovibrionaceae closely associated with micropores of Chondrosia reniformis could be visualized.

This work describes a novel process for the fabrication of hybrid nanostructured particles showing intense tunable photoluminescence and a simultaneous ferromagnetic behavior. The fabrication process involves the synthesis of nanostructured porous silicon (NPSi) by chemical anodization of crystalline silicon and subsequent in pore growth of Co nanoparticles by electrochemically-assisted infiltration. Final particles are obtained by subsequent sonication of the Co-infiltrated NPSi layers and conjugation with poly(ethylene glycol) aiming at enhancing their hydrophilic character. These particles respond to magnetic fields, emit light in the visible when excited in the UV range, and internalize into human mesenchymal stem cells with no apoptosis induction. Furthermore, cytotoxicity in in-vitro systems confirms their biocompatibility and the viability of the cells after incorporation of the particles. The hybrid nanostructured particles might represent powerful research tools as cellular trackers or in cellular therapy since they allow combining two or more properties into a single particle.

A long standing problem in computer vision is the extraction of meaningful features from images. This paper describes a method of detecting circular arcs in images based on a recursive algorithm that first analyses lists of connected edge points and finds a polygonal description, and then analyses this description fitting arcs to groups of connected lines. The result is a description of image edges consisting of circular arcs and lines. The algorithm uses no thresholding. Instead the best option is chosen at each decision stage.

Experiments were carried out to investigate the possibility of training cellular automata to to perform processing. Currently, only binary images are considered, but the space of rule sets is still very large. Various objective functions were considered, and sequential floating forward search used to select good rule sets for a range of tasks, namely: noise filtering, thinning, and convex hulls. Several modifications to the standard CA formulation were made (the B-rule and 2-cycle CAs) which were found to improve performance.

Relevance feedback (RF) is an interactive process which refines the retrievals to a particular query by utilizing the user's feedback on previously retrieved results. Most researchers strive to develop new RF techniques and ignore the advantages of existing ones. In this paper, we propose an image relevance reinforcement learning (IRRL) model for integrating existing RF techniques in a content-based image retrieval system. Various integration schemes are presented and a long-term shared memory is used to exploit the retrieval experience from multiple users. Also, a concept digesting method is proposed to reduce the complexity of storage demand. The experimental results manifest that the integration of multiple RF approaches gives better retrieval performance than using one RF technique alone, and that the sharing of relevance knowledge between multiple query sessions significantly improves the performance. Further, the storage demand is significantly reduced by the concept digesting technique. This shows the scalability of the proposed model with the increasing-size of database.

This paper depicts a projection and camera model for fisheye lens. It also presents results of the calibration of fisheye lens made on two test fields. It was shown in this experiment that place of calibration performance (laboratory or terrain) is not important when modern calibration methods are used. It makes full using of these lens in close range photogrammetry possible. Calibration of fisheye lens camera system was made with application an software created by our team in matlab on one image. There was used camera with 14 mega pixels in this experiment.

High-quality Papanicolaou (Pap) smear images are essential for reliable early detection of cervical cancer, yet low contrast and noise often hinder accurate interpretation. This study introduces spider monkey optimization (SMO)-contrast-limited adaptive histogram equalization (CLAHE), an optimized CLAHE framework guided by the SMO algorithm. A novel signal contrast (SC) objective function is proposed, combining perceptual enhancement contrast enhancement-based image quality (CEIQ) with fidelity preservation peak signal-to-noise ratio (PSNR) to adaptively tune CLAHE parameters. Experiments on the publicly available SIPaKMeD and Mendeley LBC datasets demonstrate that SMO-CLAHE consistently outperforms manual settings and flower pollination algorithm (FPA)-based optimization, and achieves performance comparable to pelican optimization algorithm (POA) across key quality metrics including entropy, structural similarity index (SSIM), PSNR, enhancement measure estimation (EME), root mean square contrast (RMSC), standard deviation (STD-DEV), and CEIQ. Furthermore, downstream evaluation using a MobileNetV3-S classifier shows that the enhanced images lead to improved cervical cancer classification performance. These results highlight SMO-CLAHE as a robust and clinically relevant preprocessing framework, offering a new perspective for Pap smear image enhancement and diagnostic support.

Compressed sensing (CS) has been widely applied in magnetic resonance imaging (MRI) to accelerate the image acquisition without significantly reducing its image quality. In Cartesian MRI, acquisition time can be reduced by skipping phase-encoding steps for faster data acquisition. However, the balance between random under-sampling and Nyquist sampling at the k-space center strongly determines image quality. In this study, we systematically evaluate the impact of different random-to-Nyquist sampling ratios for both single-coil (CS-MRI) and multi-coil (CS-pMRI) reconstructions. Simulation results reveal that dense Nyquist sampling around the k-space center is essential for maintaining image fidelity, whereas reconstruction quality deteriorates sharply when random sampling exceeds approximately 60% of the total under-sampled data. Moreover, CS-pMRI consistently outperforms CS-MRI under equivalent under-sampling factors, benefiting from additional coil sensitivity information that improves resilience against aliasing and noise. These findings provide practical guidelines for hybrid under-sampling design, emphasizing that sufficient Nyquist sampling coverage of central k-space is crucial for achieving highquality reconstructions while enabling high acceleration in CS-MRI.

Purpose-To extend the previously developed Temporally Constrained Reconstruction (TCR) algorithm to allow for real-time availability of 3D temperature maps capable of monitoring MRguided high intensity focused ultrasound (MRgHIFU) applications. Methods-A real-time TCR (RT-TCR) algorithm is developed that only uses current and previously acquired undersampled k-space data from a 3D segmented EPI pulse sequence, with the image reconstruction done in a GPU implementation to overcome computation burden. Simulated and experimental data sets of HIFU heating are used to evaluate the performance of the RT-TCR algorithm. Results-The simulation studies demonstrate that the RT-TCR algorithm has sub-second reconstruction time and can accurately measure HIFU-induced temperature rises of 20 °C in 15 seconds for 3D volumes of 16 slices (RMSE = 0.1 °C), 24 slices (RMSE = 0.2 °C), and 32 slices (RMSE = 0.3 °C). Experimental results in ex vivo porcine muscle demonstrate that the RT-TCR approach can reconstruct temperature maps with 192 × 162 × 66 mm 3D volume coverage, 1.5 × 1.5 × 3.0 mm resolution, and 1.2 second scan time with an accuracy of +/-0.5°C. The RT-TCR algorithm offers an approach to obtaining large coverage 3D temperature maps in real-time for monitoring MRgHIFU treatments.

Diffuse optical tomographic image reconstruction uses advanced numerical models that are computationally costly to be implemented in the real time. The graphics processing units (GPUs) offer desktop massive parallelization that can accelerate these computations. An open-source GPU-accelerated linear algebra library package is used to compute the most intensive matrix-matrix calculations and matrix decompositions that are used in solving the system of linear equations. These open-source functions were integrated into the existing frequency-domain diffuse optical image reconstruction algorithms to evaluate the acceleration capability of the GPUs (NVIDIA Tesla C 1060) with increasing reconstruction problem sizes. These studies indicate that single precision computations are sufficient for diffuse optical tomographic image reconstruction. The acceleration per iteration can be up to 40, using GPUs compared to traditional CPUs in case of threedimensional reconstruction, where the reconstruction problem is more underdetermined, making the GPUs more attractive in the clinical settings. The current limitation of these GPUs in the available onboard memory (4 GB) that restricts the reconstruction of a large set of optical parameters, more than 13,377.