Advances in medical image segmentation: A comprehensive survey with a focus on lumbar spine applications [0.03%]
基于腰椎应用的医学图像分割进展综述
Ahmed Kabil,Ghada Khoriba,Mina Yousef et al.
Ahmed Kabil et al.
Medical Image Segmentation (MIS) stands as a cornerstone in medical image analysis, playing a pivotal role in precise diagnostics, treatment planning, and monitoring of various medical conditions. This paper presents a comprehensive and sys...
ExF-SVM: Exhaustive feature selection with support vector machine algorithm for brain stroke prediction [0.03%]
基于支持向量机算法的脑卒中预测属性选择方法研究
Prasannavenkatesan Theerthagiri,A Usha Ruby,George Chellin Chandran J
Prasannavenkatesan Theerthagiri
Predicting brain strokes requires decision-making, and over the past few decades, artificial intelligence (AI) based technologies have greatly improved disease diagnosis. Even with their potential, hospital environments continue to lack tru...
A systematic review on automatic segmentation of renal tumors and cysts using various convolutional neural network architectures in radiological images [0.03%]
基于放射影像的肾脏肿瘤和囊肿自动分割的各种卷积神经网络架构系统综述
Chintam Anusha,Kunjam Nageswara Rao,T Lakshmana Rao
Chintam Anusha
Premature diagnosis of kidney cancer is crucial for saving lives and enabling better treatment. Medical experts utilize radiological images, such as CT, MRI, US, and histopathological analysis, to identify kidney tumors and cysts, providing...
Spatially Aware GCNs for efficient, high-accuracy cancer grading: Mitigating oversmoothing via frequency analysis [0.03%]
基于频谱分析缓解过度平滑的空间感知GCN高效精准肿瘤分级方法研究
Luke Johnston,Zhangsheng Yu
Luke Johnston
We present a Spatially Aware Graph Convolutional Network (SA-GCN) for classifying colorectal and non-small cell lung cancer grades, with a focus on preserving high-resolution spatial features and leveraging frequency information in histopat...
Correlated latent space learning for structural differentiation modeling in single cell RNA data [0.03%]
单细胞RNA数据的结构分化模型的相关潜在空间学习
Zeyu Fu,Chunlin Chen
Zeyu Fu
Single-cell RNA sequencing (scRNA-seq) enables high-resolution analysis of cellular differentiation, yet many existing methods have difficulty modeling its continuous, coupled, and noise-prone dynamics. We present CODEVAE (Correlated Ordina...
Breast cancer prediction using mammography exams for real hospital settings [0.03%]
基于乳房X线摄影的乳腺癌预测研究及医院真实场景应用探索
Shreyasi Pathak,Jörg Schlötterer,Jeroen Geerdink et al.
Shreyasi Pathak et al.
Breast cancer prediction models for mammography assume that annotations are available for individual images or regions of interest (ROIs), and that there is a fixed number of images per patient. These assumptions do not hold in real hospita...
Machine learning based prediction of single-frequency viscoelastic brain white matter - A data science framework [0.03%]
基于机器学习的单频粘弹性脑白质预测-一种数据科学框架
M Agarwal,Assimina A Pelegri
M Agarwal
Characterizing brain white matter (BWM) using in vivo Magnetic Resonance Elastography (MRE) and Diffusion Tensor Imaging (DTI) is a costly, time-intensive process. Numerical modeling approaches, such as finite element models (FEMs), also fa...
Graph theory analysis based on cross frequency coupling methods in major depressive disorder: A resting state EEG study [0.03%]
基于交叉频率耦合方法的图论分析在抑郁症患者静息态脑电中的应用研究
Sepideh Baghernezhad,Parisa Raouf,Vahid Shalchyan et al.
Sepideh Baghernezhad et al.
Major depressive disorder (MDD) is a common and debilitating mental disorder that affects the personal and social activities of individuals. Conventional diagnostic approaches are based on the validity of the information provided by the pat...
Revised NMS-driven pipeline for heart valve regurgitation and Kawasaki disease coronary aneurysm localization [0.03%]
基于NMS的管道修订版，用于心脏瓣膜反流和川崎病冠状动脉瘤定位
Shih-Hsin Chen,Ho-Chang Kuo,Ken-Pen Weng et al.
Shih-Hsin Chen et al.
Object detection in echocardiography is still uncommon, yet precise localization of pediatric valvular regurgitation and Kawasaki-related coronary aneurysms is critical. We introduce two lightweight variants of non-maximum suppression, rNMS...
A rationally designed multi-epitope vaccine candidate targeting conserved FiuA for broad Pseudomonas aeruginosa protection [0.03%]
一种针对铜绿假单胞菌广谱保护的理性设计的多抗原表位疫苗候选者FiuA
Anahita Hessami,Mona Moosavi,Fatemeh Rahim et al.
Anahita Hessami et al.
Pseudomonas aeruginosa is a significant opportunistic pathogen, and developing a broadly protective vaccine has been hindered by its antigenic variability and immune evasion mechanisms. This study presents a rationally designed multi-epitop...