Complex-valued Multi-scale Hybrid Attention Network for Fast MRI via Sparsified Data Learning [0.03%]
基于稀疏数据学习的快速MRI复杂值多尺度混合注意力网络
Yongchun Ma,Yuanzhen Tang,Zhaoyang Jin
Yongchun Ma
This study proposes a complex-valued multi-scale attention U-Net framework (SCMAU-Net) for accelerated MRI (magnetic resonance imaging) reconstruction from undersampled k-space data. The method employs a complex-valued difference transform ...
Automatic Phase and Sequence Identification in Gd-EOB-DTPA-Enhanced Liver MRI Using Deep Convolutional and Sequential Learning [0.03%]
基于深度卷积和序列学习的Gd-EOB-DTPA增强肝MRI的自动相位和序列识别
Tomomi Takenaga,Shouhei Hanaoka,Yukihiro Nomura et al.
Tomomi Takenaga et al.
The purpose of this study is to develop and validate a deep learning model for automatic identification of acquisition sequences (including T1-weighted sequences with various dynamic contrast-enhanced phases and other auxiliary sequences) i...
Ultrasound-Based AI in Predicting Hormone Receptor Status in Breast Cancer: Is "Digital Biopsy" Possible [0.03%]
基于超声的AI在预测乳腺癌激素受体状态中的应用：“数字活检”可能吗？
Beyza Nur Kuzan,Can Ilgin,Murat Emeç et al.
Beyza Nur Kuzan et al.
Accurate and rapid determination of tumor histopathological features and molecular subtypes is critical for breast cancer prognosis and treatment strategies. This study evaluates the feasibility of a "digital biopsy" approach that uses mach...
OpenDicomViewer: A Lightweight Open-Source DICOM Viewer for macOS Built with Swift [0.03%]
OpenDicomViewer：一个用Swift编写的轻量级开源DICOM图像浏览器应用程序
JoonNyung Heo,Daeseong Kim,Kunhee Kim et al.
JoonNyung Heo et al.
Digital Imaging and Communications in Medicine (DICOM) viewers are essential tools in clinical practice, yet established open-source macOS viewers such as Horos rely on legacy Objective-C and C++ source trees. In the public Horos repository...
Multimodal Large Language Model for Zero-Shot L3 Body Composition Segmentation on CT: Improved Accuracy via Automated Candidate Selection [0.03%]
多模态大型语言模型在CT图像中进行零样本L3身体组成分割的自动候选选择改进准确度研究
Haruto Sugawara,Akiyo Takada,Shimpei Kato
Haruto Sugawara
The purpose of the study is to evaluate zero-shot L3 body composition segmentation on computed tomography (CT) using a general-purpose multimodal large language model (MLLM) and to assess whether automated candidate selection improves segme...
Scalable Left Ventricular ROI Annotation for Stress Perfusion Cardiac MRI using Deep Learning with Visual Refinement [0.03%]
基于深度学习的心肌灌注MRI的左心室感兴趣区域标注及视觉优化方法
Mahsa Pourhossein Kalashami,Mohamed Elshibly,Simran Shergill et al.
Mahsa Pourhossein Kalashami et al.
Accurate extraction of the left ventricular (LV)-centred region of interest (ROI) in stress perfusion cardiovascular magnetic resonance (CMR) remains challenging due to low signal-to-noise ratio (SNR), motion artefacts, high-dimensional ima...
RE-LIG: A Faithfulness-Driven Layer Integrated Gradients Framework for Explainable Medical Visual Question Answering [0.03%]
基于信仰驱动的层集成梯度框架的解释性医学视觉问答研究
Esra Balık,İrfan Aygün,Mehmet Kaya
Esra Balık
Medical Visual Question Answering (Med-VQA) systems have the potential to support medical image interpretation and clinical decision-making processes. However, the "black-box" nature of existing systems and low-resolution constraints limit ...
Bridging Parallel Disciplines: An Integrated Workshop for Clinical and Imaging Informatics Training [0.03%]
融合学科壁垒：临床与影像信息学培训综合研讨会
James Whitfill,Kayla Berigan,Ankit A Modi et al.
James Whitfill et al.
Medical informatics training consists of two types of fellowship programs: clinical informatics (CI) and imaging informatics (II). Historically, there has been little collaborative learning between these fellowships despite significant over...
CRAF-Net: A Fine-Grained Cross-Channel Attention Network for Preoperative Microvascular Invasion Grading in Hepatocellular Carcinoma via DCE-MRI [0.03%]
基于DCE-MRI的肝细胞癌术前微血管侵犯分级的细粒度跨通道注意力网络(CRAF-Net)
Zebang Zhong,Xiao Luo,Daoying Geng et al.
Zebang Zhong et al.
To address the clinical challenge of preoperative microvascular invasion (MVI) grading in hepatocellular carcinoma (HCC), this paper proposes a cross-channel attention fine-grained Network (CRAF-Net) using dynamic contrast-enhanced magnetic...
Reasoning Model-Assisted Second-Reader Quality Control of Chinese-Language Ultrasound Reports: A Retrospective Imaging Informatics Study [0.03%]
基于推理模型的中国超声报告二级质控研究性影像信息学研究
Zhenqi Zhang,Zirui Jiang,Yihan Qi et al.
Zhenqi Zhang et al.
The purpose of this study is to evaluate whether the reasoning model DeepSeek-R1 can function as a second-reader quality control (QC) tool for Chinese-language ultrasound reports. In this retrospective diagnostic-accuracy study with a paral...