Deep learning for retinal vessel segmentation: a systematic review of techniques and applications [0.03%]
视网膜血管分割的深度学习：技术及应用的系统性回顾
Zhihui Liu,Mohd Shahrizal Sunar,Tian Swee Tan et al.
Zhihui Liu et al.
Ophthalmic diseases are a leading cause of vision loss, with retinal damage being irreversible. Retinal blood vessels are vital for diagnosing eye conditions, as even subtle changes in their structure can signal underlying issues. Retinal v...
TongueTransUNet: toward effective tongue contour segmentation using well-managed dataset [0.03%]
TongueTransUNet：使用管理良好的数据集实现有效的舌轮廓分割
Khalid Al-Hammuri,Fayez Gebali,Awos Kanan
Khalid Al-Hammuri
In modern telehealth and healthcare information systems medical image analysis is essential to understand the context of the images and its complex structure from large, inconsistent-quality, and distributed datasets. Achieving desired resu...
Drug repositioning based on mutual information for the treatment of Alzheimer's disease patients [0.03%]
基于互信息的药物重新定位以治疗阿尔茨海默病患者
Claudia Cava,Isabella Castiglioni
Claudia Cava
Computational drug repositioning approaches should be investigated for the identification of new treatments for Alzheimer's patients as a huge amount of omics data has been produced during pre-clinical and clinical studies. Here, we investi...
Rapid wall shear stress prediction for aortic aneurysms using deep learning: a fast alternative to CFD [0.03%]
使用深度学习对主动脉瘤进行快速的壁剪应力预测：CFD的快速替代方案
Md Ahasan Atick Faisal,Onur Mutlu,Sakib Mahmud et al.
Md Ahasan Atick Faisal et al.
Aortic aneurysms pose a significant risk of rupture. Previous research has shown that areas exposed to low wall shear stress (WSS) are more prone to rupture. Therefore, precise WSS determination on the aneurysm is crucial for rupture risk a...
Precise dental caries segmentation in X-rays with an attention and edge dual-decoder network [0.03%]
具有注意力和边缘双解码器网络的X射线精准牙龋分割
Feng Huang,Jiaxing Yin,Yuxin Ma et al.
Feng Huang et al.
Caries segmentation holds significant clinical importance in medical image analysis, particularly in the early detection and treatment of dental caries. However, existing deep learning segmentation methods often struggle with accurately seg...
InspirationOnly: synthesizing expiratory CT from inspiratory CT to estimate parametric response map [0.03%]
仅吸气：从吸气CT合成呼气CT以估计参数响应图
Tiande Zhang,Haowen Pang,Yanan Wu et al.
Tiande Zhang et al.
Chronic obstructive pulmonary disease (COPD) is a highly heterogeneous disease with various phenotypes. Registered inspiratory and expiratory CT images can generate the parametric response map (PRM) that characterizes phenotypes' spatial di...
Integrating multi-scale information and diverse prompts in large model SAM-Med2D for accurate left ventricular ejection fraction estimation [0.03%]
通过在大型模型SAM-Med2D中整合多尺度信息和多样化提示实现准确的左心室射血分数估算
Yagang Wu,Tianli Zhao,Shijun Hu et al.
Yagang Wu et al.
Left ventricular ejection fraction (LVEF) is a critical indicator of cardiac function, aiding in the assessment of heart conditions. Accurate segmentation of the left ventricle (LV) is essential for LVEF calculation. However, current method...
Improved segmentation of hepatic vascular networks in ultrasound volumes using 3D U-Net with intensity transformation-based data augmentation [0.03%]
基于强度变换的数据增强在三维U形网络肝血管分割中的应用研究
Yukino Takahashi,Takaaki Sugino,Shinya Onogi et al.
Yukino Takahashi et al.
Accurate three-dimensional (3D) segmentation of hepatic vascular networks is crucial for supporting ultrasound-mediated theranostics for liver diseases. Despite advancements in deep learning techniques, accurate segmentation remains challen...
Unsupervised cross-modality domain adaptation via source-domain labels guided contrastive learning for medical image segmentation [0.03%]
基于源域标签引导的对比学习的无监督跨模态领域适应方法在医学图像分割中的应用研究
Wenshuang Chen,Qi Ye,Lihua Guo et al.
Wenshuang Chen et al.
Unsupervised domain adaptation (UDA) offers a promising approach to enhance discriminant performance on target domains by utilizing domain adaptation techniques. These techniques enable models to leverage knowledge from the source domain to...
Improving movement decoding performance under joint constraints based on a neural-driven musculoskeletal model [0.03%]
基于神经驱动的生物力学模型下的联合约束下改善运动解码性能
Lizhi Pan,Xingyu Yan,Shizhuo Yue et al.
Lizhi Pan et al.
Electromyography-driven musculoskeletal model (E-DMM) connects the user's control commands with the joint positions from a physiological perspective. However, features extracted directly from the surface EMG signals may be affected by signa...