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Nuclei Segmentation in Histopathology Images Using Structure-Preserving Color Normalization Based Ensemble Deep Learning Frameworks

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Computers, Materials & Continua 2023年第12期77卷 3077-3094页

作者： Manas Ranjan Prusty Rishi Dinesh hariket sukesh kumar sheth Alapati Lakshmi Viswanath Sandeep kumar Satapathy Centre for Cyber-Physical Systems Vellore Institute of TechnologyChennai600127India School of Computer Science and Engineering Vellore Institute of TechnologyChennai600127India Centre for Advanced Data Science Vellore Institute of TechnologyChennai600127India

This paper presents a novel computerized technique for the segmentation of nuclei in hematoxylin and eosin(H&E)stained histopathology *** purpose of this study is to overcome the challenges faced in automated nuclei segmentation due to the diversity of nuclei structures that arise from differences in tissue types and staining protocols,as well as the segmentation of variable-sized and overlapping *** this extent,the approach proposed in this study uses an ensemble of the UNet architecture with various Convolutional Neural Networks(CNN)architectures as encoder backbones,along with stain normalization and test time augmentation,to improve segmentation ***,this paper employs a Structure-Preserving Color Normalization(SPCN)technique as a preprocessing step for stain *** proposed model was trained and tested on both single-organ and multi-organ datasets,yielding an F1 score of 84.11%,mean Intersection over Union(IoU)of 81.67%,dice score of 84.11%,accuracy of 92.58%and precision of 83.78%on the multi-organ dataset,and an F1 score of 87.04%,mean IoU of 86.66%,dice score of 87.04%,accuracy of 96.69%and precision of 87.57%on the single-organ *** findings demonstrate that the proposed model ensemble coupled with the right pre-processing and post-processing techniques enhances nuclei segmentation capabilities.

关键词： Nuclei segmentation image segmentation ensemble U-Net deep learning histopathology image convolutional neural networks

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Risk factors of thrombosis in abdominal veins

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World Journal of Gastroenterology 2008年第28期14卷 4518-4522页

作者： Amit kumar Dutta Ashok Chacko Biju George Joseph Anjilivelil Joseph sukesh Chandran Nair Vikram Mathews Department of Gastrointestinal Sciences Christian Medical College & HospitalVellore 632 004India Department of Clinical Pathology Christian Medical College & HospitalVellore 632 004India Department of Hematology Christian Medical College & HospitalVellore 632 004India

AIM: To estimate the prevalence of inherited and acquired thrombophilic risk factors in patients with abdominal venous thrombosis and to compare the risk factor profiles between Budd-Chiari syndromes (BCS) and splanchnic vein thrombosis (SVT). METHODS: In this retrospective study, 36 patients with abdominal venous thrombosis were studied. The patients were divided into Budd-Chiari group (hepatic vein, IVC thrombosis) and splanchnic venous thrombosis group (portal, splenic, superior mesenteric veins) based on the veins involved. Hereditary and acquired thrombophilic risk factors were evaluated in all patients. RESULTS: Twenty patients had SVT, 14 had BCS, and 2 had mixed venous thrombosis. Ten patients (28%) had hereditary and 10 patients (28%) acquired thrombophilic risk factors. The acquired risk factors were significantly more common in the SVT group (SVT vs BCS: 45% vs 7%, χ2 = 5.7, P = 0.02) while hereditary risk factors did not show significant differences between the two groups (SVT vs BCS: 25% vs 36%, χ2 = 0.46, P = 0.7). Multiple risk factors were present in one (7%) patient with BCS and in 3 patients (15%) with SVT. No risk factors were identified in 57% of patients with BCS and in 45% of patients with SVT. CONCLUSION: Hereditary and acquired risk factors play an important role in the etiopathogenesis of abdominal venous thrombosis. Acquired risk factorsare significantly more common in SVT patients while hereditary factors are similar in both groups.

关键词： Budd Chiari syndrome Splanchnic vein thrombosis Risk factors Hereditary Risk comparison

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Structure Based Pharmacophore Modeling and Virtual Screening for Identification of Novel Inhibitor for Cyclooxygenase-2

Structure Based Pharmacophore Modeling and Virtual Screening...

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International Conference on Bioscience, Biochemistry and Bioinformatics（ICBBB 2011）

作者： Saranyah K. sukesh.K. Dinesh kumar K. Lilly M.Saleena Department of Bioinformatics School of BioengineeringSRM UniversityKattankulathurTamil Nadu.India 603203 Assistant Professor Department of BioinformaticsSchool of BioengineeringSRM UniversityKattankulathurTamil Nadu.India 603203

Chronic inflammation is a first-rate example of a disease that symbolizes turmoil in normal host defense ***-2,an isoform of COX family,is highly inducible in response to proinflammatory stimuli,cytokines and consequential in exaggerated prostaglandin *** pharmacophore of known inhibitor S-58 screened with more than 100,000 ligands from Asinex Phase Database using *** best five ligands showed good orientation with the known inhibitor S-58 and further taken for the drug likeness analysis.

关键词： Cyclooxygenase,Inhibitors,Structure based Pharmacophore

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