Linear Contrast Enhancement Research Articles

Hybrid Wavelet‐Deep Learning Framework for Fluorescence Microscopy Images Enhancement

ABSTRACTFluorescence microscopy is a powerful tool for visualizing cellular structures, but it faces challenges such as noise, low contrast, and autofluorescence that can hinder accurate image analysis. To address these limitations, we propose a novel hybrid image enhancement method that combines wavelet‐based denoising, linear contrast enhancement, and convolutional neural network‐based autofluorescence correction. Our automated method employs Haar wavelet transform for noise reduction and a series of adaptive linear transformations for pixel value adjustment, effectively enhancing image quality while preserving crucial details. Furthermore, we introduce a semantic segmentation approach using CNNs to identify and correct autofluorescence in cellular aggregates, enabling targeted mitigation of unwanted background signals. We validate our method using quantitative metrics, such as signal‐to‐noise ratio (SNR) and peak signal‐to‐noise ratio (PSNR), demonstrating superior performance compared to both mathematical and deep learning‐based techniques. Our method achieves an average SNR improvement of 8.5 dB and a PSNR increase of 4.2 dB compared with the original images, outperforming state‐of‐the‐art methods such as BM3D and CLAHE. Extensive testing on diverse datasets, including publicly available human‐derived cardiosphere and fluorescence microscopy images of bovine endothelial cells stained for mitochondria and actin filaments, showcases the flexibility and robustness of our approach across various acquisition conditions and artifacts. The proposed method significantly improves fluorescence microscopy image quality, facilitating more accurate and reliable analysis of cellular structures and processes, with potential applications in biomedical research and clinical diagnostics.

Diagnostic significance of peritumoral enhancement in distinguishing between muscle-invasive and non-muscle-invasive bladder cancer.

The aim of this study was to assess the prevalence of peritumoral enhancement (PTE) in patients with muscle-invasive bladder cancer (MIBC) and non-MIBC (NMIBC) and to propose a modified diagnostic criterion for Vesical Imaging Reporting and Data System (VI-RADS) that incorporates PTE. This retrospective study included 95 patients with bladder cancer (age, 72 ± 11; 77 men; 36 MIBCs and 59 Non-MIBCs) who underwent multiparametric MRI in our referral center between 2011 and 2023. The images were interpreted by four radiologists. The readers classified the possibility of muscle layer invasion into categories 1-5, based on the VI-RADS categorical diagnostic criterion. PTE was defined as a linear contrast enhancement observed at the edge of tumor invasion which is convex outward from the normal bladder wall and contrasts more than the normal muscle layer and tumor. A modified VI-RADS that upgrades the final VI-RADS category to 4 if PTE is present when the original VI-RADS category is 3 or less was proposed. The frequency of PTE in the MIBC and NMIBC groups was compared using the Fisher's exact test. Sensitivity and specificity for the diagnosis of MIBC were compared with the original VI-RADS using McNemar test. Pathologic diagnosis was used as the reference standard. PTE was present in 70-81% (25/36-29/36) of MIBC and absent in 92-98% (54/59-58/59) of non-MIBC. For all readers, the PTE was significantly more frequent (p < 0.001) in the MIBC group than the NMIBC group. The sensitivities of modified VI-RADS (75.0-86.1%) were significantly higher than those of original VI-RADS (41.7-55.6%) (p = 0.002-0.008). The specificity of modified VI-RADS (91.5-98.3%) were not statistically different from original VI-RADS (98.3-100%). In conclusion, PTE is a highly specific finding for MIBC. modified VI-RADS incorporating PTE increases sensitivity for MIBC.

Unveiling Distinctive MRI Characteristics in the Diagnosis of GFAP Astrocytopathy: A Rare Autoimmune Neuroinflammatory Disorder.

Glial fibrillary acidic protein (GFAP) astrocytopathy is a rare autoimmune inflammatory disorder affecting the central nervous system, involving the meninges, brain parenchyma, and spinal cord. The distinctive radiologic feature observed on magnetic resonance imaging (MRI) is characterized by periventricular radial and linear contrast enhancement. This case report details a 45-year-old male who initially exhibited constitutional symptoms, followed by encephalitis, lower limb weakness, and urinary retention. The MRI findings revealed meningoencephalitis with longitudinal extensive myelitis. Notably, the cerebrospinal fluid analysis confirmed the presence of anti-GFAP antibodies.

NTRK-rearranged spindle cell neoplasm: Initial observation of imaging appearance and clinicopathologic correlation

ObjectiveTo explore pre-treatment imaging findings of neurotrophic tyrosine receptor kinase (NTRK)-rearranged spindle cell neoplasm, an emerging group of molecularly defined soft tissue tumors and summarize the clinical course, including TRK inhibitor therapy response. Materials and methodsThis retrospective study included 8 women and 4 men with NTRK-rearranged spindle cell neoplasm (median age, 35.5 years, range, 0–66). Available pre-treatment MRI, CT, PET, and US imaging were reviewed. Tumor histology and the patients' clinical course were reviewed. ResultsPrimary tumors were located within the soft tissue, lungs, kidney, and breast with soft tissue being the most prevalent site (n = 6). Pre-treatment MRI (n = 4) revealed linear hypointense signal foci and contrast enhancement in all patients with hemorrhage in half of the tumors. A tail sign (n = 1) and fluid levels (n = 1) were less frequent. Ultrasound showed well-marginated hypoechoic masses with internal flow. Primary tumors were all non-calcified on CT (4/4). Metastases were FDG-avid (4/4). Among the 8 patients who developed metastasis, 7 developed pulmonary metastases. All four patients who received NTRK inhibitor therapy showed an initial decrease in tumor size or FDG uptake. ConclusionNTRK-rearranged neoplasms may occur as enhancing masses with linear hypointense signal foci on MRI and FDG avid metastases on PET. Pulmonary metastases were frequent in our study. Initial treatment response is observed in most patients.

Acute Reversible Encephalopathy with Neuronal Intranuclear Inclusion Disease Diagnosed by a Brain Biopsy: Inferring the Mechanism of Encephalopathy from Radiological and Histological Findings.

A 75-year-old man presented with headache and disturbance of consciousness. Magnetic resonance imaging revealed edema localized mainly in the cortex and linear contrast enhancement. A brain biopsy revealed numerous astrocytes with inclusion, and genetic testing demonstrated prolonged GGC repeats in NOTCH2NLC. The present case provided two novel insights into the mechanism underlying encephalopathy associated with neuronal intranuclear inclusion disease. First, the histological findings at a site with contrast enhancement on magnetic resonance imaging did not demonstrate any organic association, such as the presence of inflammation or ischemic changes. Second, the imaging and cerebrospinal fluid findings demonstrated increased cerebral blood flow and opening of the blood-brain barrier, indicating the cause of the cerebral swelling.

Carotid Artery Thrombus in Antiphospholipid Antibody Syndrome.

HomeRadiologyRecently Published PreviousNext Reviews and CommentaryFree AccessImages in RadiologyCarotid Artery Thrombus in Antiphospholipid Antibody SyndromeZongli Han, Hui Qi Zongli Han, Hui Qi Author AffiliationsFrom the Department of Neurosurgery, Peking University Shenzhen Hospital, 1120 Lianhua Rd, Shenzhen 518036, PR China.Address correspondence to H.Q. (email: [email protected]).Zongli HanHui Qi Published Online:Mar 14 2023https://doi.org/10.1148/radiol.221836MoreSectionsPDF ToolsImage ViewerAdd to favoritesCiteTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinked In A 23-year-old previously healthy woman presented with sudden-onset right-sided hemiparesis and paresthesia. Brain MRI scan demonstrated acute left frontal lobe embolic infarcts. High-spatial-resolution vessel wall MRI scan revealed an isointense peripherally enhancing lesion in the left common carotid artery with resultant severe luminal narrowing, compatible with an intraluminal thrombus (Figure, A–C). Contrast-enhanced US image confirmed free-floating thrombus with proximal attachment to the vessel wall (Figure, D). Endarterectomy was performed, and an organized thrombus was confirmed with pathologic process. Antibody serology tests were positive for anticardiolipin immunoglobulin G, β-2 glycoprotein immunoglobulin G, and lupus anticoagulants. The diagnosis of antiphospholipid antibody syndrome was established according to the Miyakis criteria (1,2). The patient was treated with warfarin and showed no signs of clinical or radiologic relapse at 1-year follow-up.Images in a 23-year-old woman with sudden-onset right-sided hemiparesis and paresthesia. (A–C) T1-weighted three-dimensional isotropic variable flip-angle fast spin echo MRI scans with black-blood technique with a 3-T clinical scanner (uMR 780; United Imaging Healthcare) show vessel walls. (A) Axial and (B) coronal T1-weighted images without contrast material show an intraluminal T1 isointense lesion within the left common carotid artery with resultant severe luminal narrowing (arrows). (C) Coronal contrast-enhanced T1-weighted image shows peripheral linear contrast enhancement of the thrombus (arrow). (D) Contrast-enhanced US image demonstrates a free-floating thrombus with microbubbles between the thrombus and the carotid vessel (*) with proximal attachment to the vessel wall (arrowhead).Download as PowerPointOpen in Image Viewer Antiphospholipid antibody syndrome is an autoimmune disease characterized by recurrent arterial or venous thrombosis, pathologic pregnancy, and positive antiphospholipid antibodies (3). Neurologic manifestations, especially cerebral ischemia, are frequently present; however, presentation with carotid thrombus is uncommon (4).Disclosures of conflicts of interest: Z.H. No relevant relationships. H.Q. No relevant relationships.AcknowledgmentsThe authors thank Hui Zhang from the Department of Radiology, who helped with the interpretation of the high-resolution MRI. They also thank Liya Wei from the Department of Ultrasound, who helped with the interpretation of the contrast-enhanced US image.

Analysis and Comparison of Image Enhancement Technique for Improving PSNR of Lung Images by Linear Contrast Enhancement Technique over Histogram Equalization Technique

Aim: The aim of this study is to compare and analyze linear contrast enhancement algorithm for lung image enhancement over novel histogram equalization technique. Material and Methods: In this research, different sources of lung images collected from the kaggle website were used. Samples were considered as (N=30) for linear contrast filter and (N=30) for novel histogram equalization technique with total sample size calculated using clinical.com. As a result the total number of samples was calculated to be 60. Using SPSS Software and a standard data set, the PSNR was obtained. Both linear contrast filter and novel histogram equalization technique image enhancement were implemented on lung images through Matlab coding and also PSNR values of each image were extracted. Then through SPSS software comparison and analysis has been made. Result: In the final output of image enhancement, novel histogram equalization technique shows better performance in improving PSNR of lung images than linear contrast filter. Comparison of PSNR values are done by independent sample test using IBM-SPSS software. There is a statistical difference between histogram technique and linear contrast filter. The novel histogram equalization technique showed higher results of PSNR (65.9197dB) with (p=0.04) in comparison with linear contrast filter (36.1190dB). Conclusion: Within this research study the histogram equalization image enhancement technique has greater PSNR value of lung images than in linear contrast enhancement technique.

Linear Contrast Enhancement Network for Low-Illumination Image Enhancement

Images captured under low-illumination conditions usually suffer from severe degradations, such as fading and low contrast, drastically affecting the performance of systems relying on images under low-illumination conditions. To address such problems, this study proposes a linear contrast enhancement network (LCENet) for low-illumination image enhancement. It consists of three subnets: two encoder–decoder-based subnets for gradient map restoration and brightness enhancement, respectively, and a backbone network for adaptive brightness and contrast adjustment. In addition, a linear contrast enhancement adaptive instance normalization (LCEAIN) module with linear contrast enhancement ability is proposed in the backbone network, which can avoid the problem of ignoring contrast enhancement when enhancing image brightness. Considerable evaluations on both synthetic and real low-illumination images show that the proposed method performs favorably against other existing similar methods. Moreover, our method can handle complex low-illuminance conditions and has good generalization for low-illuminance scenes with backlighting, night scenes with light sources, as well as underwater scenes with low illuminance. Code: <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/zhouzhaorun/LCENet</uri> .

Aggressive Mantle Cell Lymphoma with Neurolymphomatosis and Cutaneous Infiltration: First Case Report and Review of Literature

Mantle cell lymphoma accounts for 5-10% of cases of non-Hodgkin's lymphoma. Neurolymphomatosis(NL) and Cutaneous involvement of mantle cell lymphoma has been rarely described. When present, they are indicators of high-grade disease and poor prognosis. We present the first reported case of Neurolymphomatosis and concurrent cutaneous mantle cell lymphoma. A 73-year-old man with a recent diagnosis of mantle cell lymphoma presented with progressive weakness of the upper and lower extremities that began one month after his first round of chemotherapy. The Dermatologic exam revealed red-violaceous, edematous papules and plaques on the head, trunk, and upper extremities. Prior work-up including MRI brain and cervical spine, lumbar puncture and cytology were unremarkable. He received treatment with dexamethasone and PLEX with no improvement. MRI lumbar spine revealed abnormal linear and nodular contrast enhancement in the dural sac along the lumbosacral nerves with associated soft tissue thickening in epidural spaces, consistent with NL. Skin biopsy showed medium to large cells with atypical nuclei throughout the dermis. Immunohistochemical stains for CD20, CD5, and cyclin D1 were positive, while CD3 and CD23 were negative. These findings were consistent with cutaneous mantle cell lymphoma. MR-CHOP therapy was promptly initiated however the patient developed pancytopenia with worsening swallowing dysfunction and died of aspiration pneumonia and sepsis. We identified 13 cases of Mantle cell Neurolymphomatosis in the literature, including our case. Mean age on presentation was 57.5 with male predominance. Six cases had neuronal involvement on primary presentation. Most common symptom was painful sensorimotor neuropathy. Cranial nerve involvement was seen in four cases and leptomeningeal involvement was seen in two of the cases. Diagnosis was established with MRI in eight cases with 100% positivity. Seven cases had PET-CT on presentation, of which five were positive. Most cases were treated with systemic chemotherapy with R-CHOP and high dose Methotrexate. One case received stem cell transplant which was followed by relapse. One case reported successful treatment with CAR-T brexu-cel infusion with no evidence of relapse on 2-month follow up. Most patients died of progression of disease although survival data was not available for all cases. Rapid, aggressive infiltration of both the nerve roots and skin by mantle cell lymphoma represents unusually high-grade disease. This case highlights the importance of clinical suspicion of NL in any subtype of lymphoma showing aggressive features. There is a narrow window for treatment to prevent fatal outcomes. MRI is the diagnostic modality of choice, which was instrumental in establishing diagnosis in our case and further workup was not felt necessary. Novel CART-cell therapy and consolidative therapies such as high dose chemotherapy followed by stem cell transplant (HDC- ASCT) should be considered in appropriate cases, as we intended in our case after disease stabilization. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Xanthogranuloma of the Sellar Region: A Comprehensive Review of Neuroimaging in a Rare Inflammatory Entity.

Xanthogranuloma of the sellar region is a rare chronic inflammatory lesion resulting from secondary hemorrhage, inflammation, infarction, and necrosis of an existing Rathke’s cleft cyst, craniopharyngioma, or pituitary adenoma. Sellar xanthogranulomas are challenging to differentiate from other cystic lesions preoperatively due to the lack of characteristic imaging features. We performed a literature overview of the clinical and paraclinical features, treatment options, and long-term outcomes of patients with sellar xanthogranuloma, focusing on the preoperative radiological diagnosis. The hyperintense signal in both T1- and T2-weighted sequences, cystic or partially cystic morphology, ovoid shape, sellar epicenter, intra- and suprasellar location, intratumoral calcifications, linear rim contrast enhancement, and the absence of cavernous sinus invasion suggest xanthogranuloma in the preoperative differential diagnosis. An endoscopic endonasal gross total resection without radiotherapy is the preferred first-line treatment. Given the low rate of recurrence rate and low chance of endocrinological recovery, a mass reduction with decompression of the optic apparatus may represent an appropriate surgical goal. Identifying the xanthogranulomas’ mutational profile could complement histopathological diagnosis and give insight into their histo-pathogenesis. A better preoperative neuroimagistic diagnosis of sellar xanthogranulomas and differentiation from lesions with a poorer prognosis, such as craniopharyngioma, would result in an optimal personalized surgical approach.

Variational Anisotropic Gradient-Domain Image Processing.

Gradient-domain image processing is a technique where, instead of operating directly on the image pixel values, the gradient of the image is computed and processed. The resulting image is obtained by reintegrating the processed gradient. This is normally done by solving the Poisson equation, most often by means of a finite difference implementation of the gradient descent method. However, this technique in some cases lead to severe haloing artefacts in the resulting image. To deal with this, local or anisotropic diffusion has been added as an ad hoc modification of the Poisson equation. In this paper, we show that a version of anisotropic gradient-domain image processing can result from a more general variational formulation through the minimisation of a functional formulated in terms of the eigenvalues of the structure tensor of the differences between the processed gradient and the gradient of the original image. Example applications of linear and nonlinear local contrast enhancement and colour image Daltonisation illustrate the behaviour of the method.

An improved algorithm using weighted guided coefficient and union self‐adaptive image enhancement for single image haze removal

The visibility of outdoor images is usually significantly degraded by haze. Existing dehazing algorithms, such as dark channel prior (DCP) and colour attenuation prior (CAP), have made great progress and are highly effective. However, they all suffer from the problems of dark distortion and detailed information loss. This paper proposes an improved algorithm for single-image haze removal based on dark channel prior with weighted guided coefficient and union self-adaptive image enhancement. First, a weighted guided coefficient method with sampling based on guided image filtering is proposed to refine the transmission map efficiently. Second, the k-means clustering method is adopted to calibrate the original image into bright and non-bright colour areas and form a transmission constraint matrix. The constraint matrix is then marked by connected-component labelling, and small bright regions are eliminated to form an atmospheric light constraint matrix, which can suppress the halo effect and optimize the atmospheric light. Finally, an adaptive linear contrast enhancement algorithm with a union score is proposed to optimize restored images. Experimental results demonstrate that the proposed algorithm can overcome the problems of image distortion and detailed information loss and is more efficient than conventional dehazing algorithms.

Symptoms: Sudden Hearing Loss and Facial Paralysis

Symptoms: Sudden Hearing Loss and Facial Paralysis

Motion Planning Algorithm for a Mobile Robot with a Smart Machine Vision System

This study is devoted to the challenges of motion planning for mobile robots with smart machine vision systems. Motion planning for mobile robots in the environment with obstacles is a problem to deal with when creating robots suitable for operation in real-world conditions. The solutions found today are predominantly private, and are highly specialized, which prevents judging of how successful they are in solving the problem of effective motion planning. Solutions with a narrow application field already exist and are being already developed for a long time, however, no major breakthrough has been observed yet. Only a systematic improvement in the characteristics of such systems can be noted. The purpose of this study: develop and investigate a motion planning algorithm for a mobile robot with a smart machine vision system. The research subject for this article is a motion planning algorithm for a mobile robot with a smart machine vision system. This study provides a review of domestic and foreign mobile robots that solve the motion planning problem in a known environment with unknown obstacles. The following navigation methods are considered for mobile robots: local, global, individual. In the course of work and research, a mobile robot prototype has been built, capable of recognizing obstacles of regular geometric shapes, as well as plan and correct the movement path. Environment objects are identified and classified as obstacles by means of digital image processing methods and algorithms. Distance to the obstacle and relative angle are calculated by photogrammetry methods, image quality is improved by linear contrast enhancement and optimal linear filtering using the Wiener-Hopf equation. Virtual tools, related to mobile robot motion algorithm testing, have been reviewed, which led us to selecting Webots software package for prototype testing. Testing results allowed us to make the following conclusions. The mobile robot has successfully identified the obstacle, planned a path in accordance with the obstacle avoidance algorithm, and continued moving to the destination. Conclusions have been drawn regarding the concluded research.

Microfabricated Vapor Cells with Reflective Sidewalls for Chip Scale Atomic Sensors.

We investigate the architecture of microfabricated vapor cells with reflective sidewalls for applications in chip scale atomic sensors. The optical configuration in operation is suitable for both one-beam and two-beam (pump & probe) schemes. In the miniaturized vapor cells, the laser beam is reflected twice by the aluminum reflectors on the wet etched 54.7° sidewalls to prolong the optical length significantly, thus resulting in a return reflectance that is three times that of bare silicon sidewalls. To avoid limitations faced in the fabrication process, a simpler, more universal and less constrained fabrication process of microfabricated vapor cells for chip scale atomic sensors with uncompromised performance is implemented, which also decreases the fabrication costs and procedures. Characterization measurements show that with effective sidewall reflectors, mm3 level volume and feasible hermeticity, the elongated miniature vapor cells demonstrate a linear absorption contrast improvement by 10 times over the conventional micro-electro-mechanical system (MEMS) vapor cells at ~50 °C in the rubidium D1 absorption spectroscopy experiments. At the operating temperature of ~90 °C for chip scale atomic sensors, a 50% linear absorption contrast enhancement is obtained with the reflective cell architecture. This leads to a potential improvement in the clock stability and magnetometer sensitivity. Besides, the coherent population trapping spectroscopy is applied to characterize the microfabricated vacuum cells with 46.3 kHz linewidth in the through cell configuration, demonstrating the effectiveness in chip scale atomic sensors.

Local patterns in the copy-move detection problem solution

Embedding of duplicates is one of commonly used methods of image forgery. During this process, an image fragment is copied and pasted to another position in the same image. This is performed to conceal some important part of the image. A copy-move forgery detection algorithm aims to recognize duplicated areas in the image. This algorithm is based on calculating the characteristics in a sliding or overlapping window. In this paper, we compare the performance of copy-move detection algorithms that utilize a local binary pattern, a local ternary pattern, a local derivative pattern, and some extensions thereof. A distinctive feature of the used characteristics is their resistance to distortions inserted into the copy, such as linear contrast enhancement and impulse noise. This method also has low computational complexity.

Primary Central Nervous System Vasculitis Mimicking a Cortical Brain Tumor: A Case Report.

We report a case of primary central nervous system vasculitis (PCNSV) mimicking a cortical brain tumor. A 25-year-old woman presented with a 2-week history of headache and transient right hemiparesis. Brain magnetic resonance imaging (MRI) revealed a cortical-involving lesion on the left frontal lobe. The 6-cm sized lesion showed low signal intensity on T1-weighted images and high signal intensity on T2-weighted images. The lesion had continual linear enhancement on the subcortical white matter and leptomeninges. There was no evidence of hemorrhage on susceptibility-weighted images and no diffusion restriction on diffusion-weighted images. The regional cerebral blood volume was decreased on the MR perfusion images, and spectroscopy showed increased lactate and lipid peaks. The symptoms were aggravated by fever and seizures. Biopsy was performed to rule out tumorous or inflammatory lesions. Pathologically, lymphocytes were infiltrated on the vessels, and the arachnoid membrane was thickened with inflammatory cells. The patient did not have any underlying diseases, including immune disorders. After high-dose steroid administration, her symptoms improved. Two months later, brain MRI showed a reduction in the infiltration of the T2 hyperintensity lesion with subtle subcortical enhancement. We present a case of PCNSV involving the left frontal lobe, showing vasogenic edema, mass effect, and subcortical linear contrast enhancement without hemorrhage or infarction.

A new copy-move forgery detection algorithm using image preprocessing procedure

One of the simplest ways of digital image forgery is a copy-move attack. The copy-move process consists of three stages: copy selected image fragment from one place, transform it using some image processing algorithm and paste it to another place of the same image. Two main approaches to copy-move detection exist nowadays: feature-based and hash-based. Most of the algorithms are developed according to the feature-based approach, whereas the hash-based approach is used only for plain copy-move detection (when the copied image fragment is not transformed). However, the main advantage of hash-based algorithms is low computational complexity. In this paper, we propose a new hash-based copy-move detection algorithm that can be applied to transformed duplicates detection due to a special preprocessing procedure. This procedure implements initial image transformation to incorporate the changes (affine transforms are not considered in this paper), produced by a transform algorithm on the second stage. Several preprocessing procedures are compared during experiments: image intensity range reduction, gradient calculation, expansion in orthonormal basis, adaptive linear contrast enhancement and local binary pattern.

Early Stage of Hyperintense Acute Reperfusion Marker on Contrast-Enhanced FLAIR Images in Patients With Acute Stroke.

Hyperintense acute reperfusion marker (HARM) is defined as delayed CSF enhancement on FLAIR images in patients with acute stroke and was observed in follow-up FLAIR images after initial MRI with contrast material administration. We hypothesized that different imaging findings of HARM could be present depending on the timing of FLAIR imaging after contrast material administration. Of 218 consecutive patients with acute stroke or transient ischemic attack over 3 months, 12 with linear contrast enhancement on the cortical surface in initial FLAIR images underwent serial FLAIR imaging. Initial FLAIR images were obtained 5 minutes after contrast material administration, and follow-up unenhanced FLAIR images were obtained 2.5-29 hours (mean, 13.2 hours) after initial FLAIR imaging. The enhancement patterns between initial and follow-up FLAIR images were compared. In all 12 patients, initial contrast-enhanced FLAIR images showed focal or multifocal linear contrast enhancement along the cortical surface near acute infarctions. On follow-up unenhanced FLAIR images, initial cortical enhancement spread diffusely and filled the subarachnoid space. HARM in acute stroke can be detected earlier than previously reported on initial contrast-enhanced FLAIR images. Different imaging findings of HARM depend on the timing of FLAIR imaging after contrast material administration.

Illumination - Invariant Facial Components Extraction Using Adaptive Contrast Enhancement Methods

The process of accurate localization of the basic components of human faces (i.e., eyebrows, eyes, nose, mouth, etc.) from images is an important step in face processing techniques like face tracking, facial expression recognition or face recognition. However, it is a challenging task due to the variations in scale, orientation, pose, facial expressions, partial occlusions and lighting conditions. In the current paper, a scheme includes the method of three-hierarchal stages for facial components extraction is presented; it works regardless of illumination variance. Adaptive linear contrast enhancement methods like gamma correction and contrast stretching are used to simulate the variance in light condition among images. As testing material a subset consists of 1150 images belong to 91 different subjects was taken from Cohn-Kanade AU coded dataset (CK); the subjects images hold different facial expressions. The test results show the effectiveness of the proposed automated localization scheme in different illuminations conditions; it gave accuracy of about 95.7%.