Beyond the LUMIR challenge: The pathway to foundational registration models [0.03%]
超越LUMIR挑战：基础注册模型的发展路径
Junyu Chen,Shuwen Wei,Joel Honkamaa et al.
Junyu Chen et al.
Medical image challenges have played a transformative role in advancing the field, catalyzing innovation and establishing new performance benchmarks. Image registration, a foundational task in neuroimaging, has similarly advanced through th...
Annotation-efficient medical image segmentation via cross-latent graphs and vector-quantized memory [0.03%]
基于交叉潜在图和向量量化记忆的注解高效医学图像分割方法
Yanyu Xu,Menghan Zhou,Xinxing Xu et al.
Yanyu Xu et al.
Medical image segmentation plays a vital role in computer-assisted diagnosis, yet the heavy reliance on large-scale pixel-level annotations limits its scalability in real-world clinical applications. To alleviate this bottleneck, we propose...
HyperCOCO: Multi-sensory HyperCOgnitive COmputing for learning population level brain connectivity [0.03%]
超感知超越认知计算：用于学习人群水平大脑连接性的方法
Mayssa Soussia,Mohamed Ali Mahjoub,Islem Rekik
Mayssa Soussia
Learning a high-order connectional brain template (CBT) endowed with cognitive capacities such as visual or auditory memory is crucial for identifying cognition-related biomarkers and distinguishing between control and clinical populations....
PANTHER Challenge Report: Cross-Domain Pancreatic Tumor Segmentation in Magnetic Resonance Imaging [0.03%]
PAIP 2019挑战报告：磁共振胰腺肿瘤分割比赛
Amparo S Betancourt Tarifa,Marcel Verheij,René Monshouwer et al.
Amparo S Betancourt Tarifa et al.
Accurate delineation of pancreatic tumors on Magnetic Resonance Imaging (MRI) is important for diagnosis, radiotherapy treatment planning, and outcome assessment, but remains challenging due to complex anatomy and subtle tumor appearance. I...
DGCD-3D: Difference-guided conditional diffusion model for low-field 3D MRI enhancement to assist stroke assessment [0.03%]
基于差异引导的条件扩散模型，用于低场3D磁共振图像增强以辅助卒中评估
Hao Li,Ziyang Liu,Yu Zhou et al.
Hao Li et al.
Low-field (LF) magnetic resonance imaging (MRI) plays a crucial role in assisting clinicians with rapid stroke diagnosis. However, its inherent limitations, such as low signal-to-noise ratio (SNR) and suboptimal image quality, make accurate...
Leveraging modality-guided pre-training for dual-prompt-driven multi-cancer PET-CT segmentation [0.03%]
基于模式引导的预训练在双提示驱动的多癌症PET-CT分割中的应用研究
Xinglong Liang,Jiaju Huang,Tianyu Zhang et al.
Xinglong Liang et al.
PET-CT lesion segmentation remains challenging due to heterogeneous lesion appearance, small and dispersed lesions, physiological FDG uptake, and limited annotations. Existing self-supervised methods are mostly designed for unimodal imaging...
MICLEAR: Intelligent molecular cytology for intraoperative margin assessment of pancreatic ductal adenocarcinoma [0.03%]
MICLEAR：智能分子细胞病理学在胰腺导管腺癌术中切缘评估中的应用
Tinghe Fang,Daoning Liu,Xun Chen et al.
Tinghe Fang et al.
Pancreatic ductal adenocarcinoma (PDAC) is a highly mortal cancer whose only potentially curative treatment is surgical resection. Intraoperative assessment of its surgical margins is vital for patient survival. Frozen section biopsy is rou...
Rethinking the detail-preserved completion of complex tubular structures based on point cloud: A dataset and a benchmark [0.03%]
基于点云的复杂管状结构精细补全：数据集和基准测试方法
Yaolei Qi,Yikai Yang,Wenbo Peng et al.
Yaolei Qi et al.
Complex tubular structures are essential in medical imaging and computer-assisted diagnosis, where their integrity enhances anatomical visualization and lesion detection. However, existing segmentation algorithms struggle with structural di...
Accurate full segmentation of organs-at-risk in head and neck cancer based on multimodal point cloud fusion [0.03%]
基于多模态点云融合的头颈部肿瘤高精度危重器官全分割
Pengfei Xu,Xinyu Zhou,Jie Wang et al.
Pengfei Xu et al.
Accurate segmentation of multiple organs is essential for the diagnosis and treatment of head and neck cancer. However, the intricate anatomical structure and dense organ distribution in the head and neck region pose significant challenges ...
Adaptive distribution-aware transformer for multi-scale visual representation learning on imbalanced and low-resolution data [0.03%]
一种基于不平衡和低分辨率数据的自适应分布感知变压器多尺度视觉表征学习方法
Sakib Ahammed,Xia Cui,Wenqi Lu et al.
Sakib Ahammed et al.
Deep learning models often struggle with class imbalance and low-resolution medical images, where critical spatial details and minority-class features are underrepresented. We introduce the Adaptive Distribution-aware Vision Transformer (Ad...