ABUS-ResMask-Net: ABUS Lesion Classification Network Design with ResMask Module and BI-RADS Content-Awareness Auxiliary Tasks [0.03%]
基于具有ResMask模块和BI-RADS意识辅助任务的病变分类网络的设计的ABUS-ResMask-Net方法
Wen Li,Yinglan Kuang,Huajia Wang et al.
Wen Li et al.
This study aims to develop a 2.5D deep learning model with shape and margin as auxiliary tasks to improve the diagnostic performance of benign-malignant classification of breast lesions in automated breast ultrasound system (ABUS) images. I...
Physics-Informed Multiscale Decoding of Tissue Microstructure: The Gray Level Affinity Metrics (GLAM) Framework [0.03%]
基于物理的组织微结构多尺度解码：灰度亲和度计量(GLAM)框架
Ahmad Pour Rashidi,Laetitia Perronne,Chase Krumpelman et al.
Ahmad Pour Rashidi et al.
Drawing inspiration from statistical mechanics, which provides a rigorous framework for understanding how microscopic interactions give rise to macroscopic structures, we propose a novel family of physics-inspired texture descriptors termed...
Development of a Deep Learning Model for Automated Measurement of Skeletal Muscle Volume in 18F-FDG PET/CT [0.03%]
开发一种深度学习模型用于自动测量18F-FDG PET/CT中的骨骼肌体积
Ryusuke Nakamoto,Koji Fujimoto,Ryo Sakamoto et al.
Ryusuke Nakamoto et al.
To develop a deep learning-based automated trunk muscle volumetry method using whole-body CT from PET/CT and evaluate its performance against bioelectrical impedance analysis (BIA). In this retrospective study, an nnU-Net-based segmentation...
LCRE-Net: A Lightweight Cross-Scale Residual Enhancement Network for Lung Segmentation in CT Images [0.03%]
轻量级跨尺度残差增强网络在CT图像中进行肺部分割的研究
Ju-Rong Ding,Jie Wang,Xia Li et al.
Ju-Rong Ding et al.
Accurate segmentation of lung and lesion regions from CT images is crucial for the diagnosis and quantitative assessment of lung diseases. Existing methods for lung CT segmentation suffer from limitations such as insufficient effective rece...
ADF-Net: Adaptive Directional Feature Fusion Network for OCTA Vessel Segmentation [0.03%]
自适应方向特征融合网络在OCTA血管分割中的应用
Suxin Li,Idowu Paul Okuwobi
Suxin Li
Optical Coherence Tomography Angiography (OCTA) enables high-resolution visualization of the retinal vascular network. However, retinal vessels exhibit complex multi-scale and multi-directional patterns, particularly in thin vessels, bifurc...
FS-DANet: Dual-Domain Signal Enhancement and Dynamic Spatial Calibration for Gastric Ultrasound Artifact Mitigation [0.03%]
用于胃超声伪像抑制的双域信号增强和动态空间校准方法
Yuyi Bai,Yanmin Luo,Zhikui Chen et al.
Yuyi Bai et al.
Accurate automatic segmentation of gastric cancer in ultrasound images is crucial for early diagnosis and treatment. However, this task remains challenging due to severe speckle noise, tissue deformation, and the high computational cost of ...
DIFNet: A Dual-Branch Interactive Fusion Network for Femoral Nerve Segmentation in Ultrasound Images [0.03%]
基于双分支交互融合的股神经分割网络DIFNetBar铛铛endphp
Junbo Gao,Yujie He,Wei Sun et al.
Junbo Gao et al.
Accurate femoral nerve (FN) segmentation in ultrasound images is crucial for nerve blocks but remains challenging due to its tortuous structure, large-scale variations, and low-contrast boundaries with the closely adjacent femoral artery. E...
An ROI-Guided Imaging Informatics Framework for Image-Language Differentiation of Tuberculous and Pyogenic Spondylitis on MRI [0.03%]
基于ROI的影像信息框架在MRI上指导图-语言区分椎体结核和化脓性脊柱炎
Xuming Jiang,Yang Liu,Xinyi Li et al.
Xuming Jiang et al.
This study aims to develop and validate an MRI-based image-language collaborative framework for differentiating tuberculous spondylitis (TB) from pyogenic spondylitis (PS) at the patient level. This retrospective two-center study included 3...
Artificial Intelligence in Ischemic Stroke Lesion Segmentation: A Narrative Review of Deep Learning Methods, Clinical Utility, and Future Directions [0.03%]
缺血性卒中病变分割的人工智能方法：深度学习、临床应用及未来方向的故事性综述
Taofeeq Oluwatosin Togunwa,Theophilus Olayiwola,Halleluyah Darasinmi Oludele et al.
Taofeeq Oluwatosin Togunwa et al.
Ischemic stroke management is time-sensitive, and lesion segmentation supports treatment selection, prognostication, and reproducible quantification. Deep learning (DL) aims to accelerate and standardize lesion delineation to augment neuroi...
Neoadjuvant Chemoradiotherapy on Postoperative Complications of Rectal Cancer: A Retrospective Study Integrating MRI Radiomics and Deep Learning [0.03%]
结合MRI影像组学和深度学习的术前同步放化疗对直肠癌术后并发症的影响：回顾性研究
Yuchen Bu,Liuping Zhu,Zhonghua Ning et al.
Yuchen Bu et al.
Neoadjuvant chemoradiotherapy (nCRT) is standard for locally advanced rectal cancer but increases postoperative complication (POC) risks due to tissue fibrosis and immunosuppression. Existing models based on clinical parameters overlook nCR...