Coronary artery calcification segmentation with sparse annotations in intravascular OCT: Leveraging self-supervised learning and consistency regularization [0.03%]
基于自我监督学习和一致性正则化的稀疏注释下血管内OCT影像中冠状动脉钙化分割
Chao Li,Zhifeng Qin,Zhenfei Tang et al.
Chao Li et al.
Assessing coronary artery calcification (CAC) is crucial in evaluating the progression of atherosclerosis and planning percutaneous coronary intervention (PCI). Intravascular Optical Coherence Tomography (OCT) is a commonly used imaging too...
Enhancing intracranial vessel segmentation using diffusion models without manual annotation for 3D Time-of-Flight Magnetic Resonance Angiography [0.03%]
利用扩散模型改进无手动注释的3D时间飞跃磁共振血管造影颅内血管分割效果
Jonghun Kim,Inye Na,Jiwon Chung et al.
Jonghun Kim et al.
Intracranial vessel segmentation is essential for managing brain disorders, facilitating early detection and precise intervention of stroke and aneurysm. Time-of-Flight Magnetic Resonance Angiography (TOF-MRA) is a commonly used vascular im...
Twin-ViMReg: DXR driven synthetic dynamic Standing-CBCTs through Twin Vision Mamba-based 2D/3D registration [0.03%]
基于双视锥蛇的2D/3D注册的双ViMReg：通过DXR合成动态数字站立CBCT
Jiashun Wang,Hao Tang,Zhan Wu et al.
Jiashun Wang et al.
Medical imaging of the knee joint under physiological weight bearing is crucial for diagnosing and analyzing knee lesions. Existing modalities have limitations: Standing Cone-Beam Computed Tomography (Standing-CBCT) provides high-resolution...
Deep learning for automatic vertebra analysis: A methodological survey of recent advances [0.03%]
深度学习在自动腰椎分析中的应用：近期研究方法综述
Zhuofan Xie,Zishan Lin,Enlong Sun et al.
Zhuofan Xie et al.
Automated vertebra analysis (AVA), encompassing vertebra detection and segmentation, plays a critical role in computer-aided diagnosis, surgical planning, and postoperative evaluation in spine-related clinical workflows. Despite notable pro...
Collect vascular specimens in one cabinet: A hierarchical prompt-guided universal model for 3D vascular segmentation [0.03%]
一站式的血管分割：分层提示引导的通用模型
Yinuo Wang,Cai Meng,Zhe Xu
Yinuo Wang
Accurate segmentation of vascular structures in volumetric medical images is critical for disease diagnosis and surgical planning. While deep neural networks have shown remarkable effectiveness, existing methods often rely on separate model...
SA2Net: Scale-adaptive structure-affinity transformation for spine segmentation from ultrasound volume projection imaging [0.03%]
尺度自适应结构亲和变换的脊柱分割算法-SA2Net
Hao Xie,Zixun Huang,Yushen Zuo et al.
Hao Xie et al.
Spine segmentation, based on ultrasound volume projection imaging (VPI), plays a vital role for intelligent scoliosis diagnosis in clinical applications. However, this task faces several significant challenges. Firstly, the global contextua...
A self-attention model for robust rigid slice-to-volume registration of functional MRI [0.03%]
一种鲁棒的刚性切片到体积配准的自注意力模型（功能磁共振成像）
Samah Khawaled,Onur Afacan,Simon K Warfield et al.
Samah Khawaled et al.
Functional Magnetic Resonance Imaging (fMRI) is vital in neuroscience, enabling investigations into brain disorders, treatment monitoring, and brain function mapping. However, head motion during fMRI scans, occurring between shots of slice ...
Mamba-based context-aware local feature network for vessel detail enhancement [0.03%]
基于响尾蛇的上下文感知局部特征网络用于血管细节增强
Keyi Han,Anqi Xiao,Jie Tian et al.
Keyi Han et al.
Objective: Blood vessel analysis is essential in various clinical fields. Detailed vascular imaging enables clinicians to assess abnormalities and make timely, effective interventions. Near-infrared-II (NIR-II, 1000-1700 ...
SGRRG: Leveraging radiology scene graphs for improved and abnormality-aware radiology report generation [0.03%]
SGRRG：利用放射科场景图改进并具有异常意识的放射科报告生成
Jun Wang,Lixing Zhu,Abhir Bhalerao et al.
Jun Wang et al.
Radiology report generation (RRG) methods often lack sufficient medical knowledge to produce clinically accurate reports. A scene graph provides comprehensive information for describing objects within an image. However, automatically genera...
A segmentation-based hierarchical feature interaction attention model for gene mutation status identification in colorectal cancer [0.03%]
一种基于分段的层次特征交互注意力模型，用于结直肠癌基因突变状态识别
Yu Miao,Sijie Song,Lin Zhao et al.
Yu Miao et al.
Precise identification of Kirsten Rat Sarcoma (KRAS) gene mutation status is critical for both qualitative analysis of colorectal cancer and formulation of personalized therapeutic regimens. In this paper, we propose a Segmentation-based Hi...