3D Fractal Analysis of Gd-EOB-DTPA-MRI for Vessels Encapsulating Tumor Clusters Prediction in Hepatocellular Carcinoma [0.03%]
基于3D分形分析的Gd-EOB-DTPA-MRI对肝细胞癌肿瘤团块包绕血管预测价值的研究
Miaomiao Wang,Yinzhong Wang,Ya Shen et al.
Miaomiao Wang et al.
This study aims to evaluate the potential role of 3-dimensional (3D) fractal analysis derived from Gd-EOB-DTPA-MRI in predicting vessels encapsulating tumor clusters (VETC) pattern in patients with hepatocellular carcinoma (HCC). This retro...
Mandibular Angle Bone Appositions in Bruxism: A Deep Learning-Based Detection and Staging Study [0.03%]
咬肌骨附着部位在磨牙症中的深度学习检测与分级研究
Fatma Yuce,Muhammet Üsame Öziç
Fatma Yuce
This study aims to automatically detect, classify, and stage bone apposition changes in the mandibular angle region associated with bruxism using panoramic radiographs. The deep learning-based YOLO11x architecture was implemented to identif...
Technical Developments in Radiology: Enhancing Research Workflows with PACScrawler [0.03%]
放射科技术的发展：利用PACScrawler增强科研工作流
Joshy Cyriac,Ashraya Kumar Indrakanti,Jakob Wasserthal et al.
Joshy Cyriac et al.
Efficiently identifying and retrieving imaging studies to create research cohorts is often hindered by the segregated storage of medical imaging data and radiological reports. To address this, we developed PACScrawler, an open-source tool d...
Prediction of Whole-Body Tissue Composition from Regional Sub-Body CT Scans [0.03%]
基于区域亚全身CT扫描的全身影像组学模型及其对体组成成分的预测研究
Morteza Golzan,Hyunwoo Lee,Vincent Chow et al.
Morteza Golzan et al.
Accurate assessment of body composition is essential for understanding human physiology and health risks and developing personalized medical strategies. Traditional approaches, such as single-slice segmentation at the L3 vertebra, often fai...
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 ...