MetaCOVID: A Siamese neural network framework with contrastive loss for n-shot diagnosis of COVID-19 patients [0.03%]
MetaCOVID：用于n-shot诊断COVID-19患者的具有对比损失的Siamese神经网络框架
Mohammad Shorfuzzaman,M Shamim Hossain
Mohammad Shorfuzzaman
Various AI functionalities such as pattern recognition and prediction can effectively be used to diagnose (recognize) and predict coronavirus disease 2019 (COVID-19) infections and propose timely response (remedial action) to minimize the s...
Automatically discriminating and localizing COVID-19 from community-acquired pneumonia on chest X-rays [0.03%]
胸部X光片中COVID-19与社区获得性肺炎的自动区分和定位
Zheng Wang,Ying Xiao,Yong Li et al.
Zheng Wang et al.
The COVID-19 outbreak continues to threaten the health and life of people worldwide. It is an immediate priority to develop and test a computer-aided detection (CAD) scheme based on deep learning (DL) to automatically localize and different...
Three-Dimensional Krawtchouk Descriptors for Protein Local Surface Shape Comparison [0.03%]
三维Krawtchouk描述符在蛋白质局部表面形状比较中的应用
Atilla Sit,Woong-Hee Shin,Daisuke Kihara
Atilla Sit
Direct comparison of three-dimensional (3D) objects is computationally expensive due to the need for translation, rotation, and scaling of the objects to evaluate their similarity. In applications of 3D object comparison, often identifying ...
Weighted Graph Regularized Sparse Brain Network Construction for MCI Identification [0.03%]
加权图正则化稀疏脑网络构建用于MCI识别
Renping Yu,Lishan Qiao,Mingming Chen et al.
Renping Yu et al.
Brain functional networks (BFNs) constructed from resting-state functional magnetic resonance imaging (rs-fMRI) have been widely applied to the analysis and diagnosis of brain diseases, such as Alzheimer's disease and its prodrome, namely m...
Strength and Similarity Guided Group-level Brain Functional Network Construction for MCI Diagnosis [0.03%]
基于功能连接强度和相似性的轻量级MCIdiagnosis脑网络模型构建方法研究
Yu Zhang,Han Zhang,Xiaobo Chen et al.
Yu Zhang et al.
Sparse representation-based brain functional network modeling often results in large inter-subject variability in the network structure. This could reduce the statistical power in group comparison, or even deteriorate the generalization cap...
Accurate vessel extraction via tensor completion of background layer in X-ray coronary angiograms [0.03%]
基于张量补全背景层的X线冠状动脉造影中的精确血管提取
Binjie Qin,Mingxin Jin,Dongdong Hao et al.
Binjie Qin et al.
This paper proposes an effective method for accurately recovering vessel structures and intensity information from the X-ray coronary angiography (XCA) images of moving organs or tissues. Specifically, a global logarithm transformation of X...
A New Design in Iterative Image Deblurring for Improved Robustness and Performance [0.03%]
一种新的迭代图像去模糊设计用于提升稳健性和性能
Taihao Li,Huai Chen,Min Zhang et al.
Taihao Li et al.
In many applications, image deblurring is a pre-requisite to improve the sharpness of an image before it can be further processed. Iterative methods are widely used for deblurring images but care must be taken to ensure that the iterative p...
Texture Analysis for Muscular Dystrophy Classification in MRI with Improved Class Activation Mapping [0.03%]
基于改进类激活映射的肌营养不良MRI图像分类纹理分析
Jinzheng Cai,Fuyong Xing,Abhinandan Batra et al.
Jinzheng Cai et al.
The muscular dystrophies are made up of a diverse group of rare genetic diseases characterized by progressive loss of muscle strength and muscle damage. Since there is no cure for muscular dystrophy and clinical outcome measures are limited...
Polyp detection during colonoscopy using a regression-based convolutional neural network with a tracker [0.03%]
基于回归的卷积神经网络结肠镜多发息肉检测算法研究
Ruikai Zhang,Yali Zheng,Carmen C Y Poon et al.
Ruikai Zhang et al.
A computer-aided detection (CAD) tool for locating and detecting polyps can help reduce the chance of missing polyps during colonoscopy. Nevertheless, state-of-the-art algorithms were either computationally complex or suffered from low sens...
Structured sparsity regularized multiple kernel learning for Alzheimer's disease diagnosis [0.03%]
基于结构稀疏正则化的多核学习在阿尔茨海默病诊断中的应用研究
Jialin Peng,Xiaofeng Zhu,Ye Wang et al.
Jialin Peng et al.
Multimodal data fusion has shown great advantages in uncovering information that could be overlooked by using single modality. In this paper, we consider the integration of high-dimensional multi-modality imaging and genetic data for Alzhei...