Wei-Lun Huang,Minghao Xue,Zhiyou Liu et al.
Wei-Lun Huang et al.
Melanoma is the most deadly form of skin cancer. Tracking the evolution of nevi and detecting new lesions across the body is essential for the early detection of melanoma. Despite prior work on longitudinal tracking of skin lesions in 3D to...
DDTracking: A diffusion model-based deep generative framework with local-global spatiotemporal modeling for diffusion MRI tractography [0.03%]
基于扩散模型的深度生成框架DDTracking：具有局部-全局时空建模的弥散加权成像纤维束追踪方法
Yijie Li,Wei Zhang,Xi Zhu et al.
Yijie Li et al.
Diffusion MRI (dMRI) tractography is an advanced technique that uniquely enables in vivo mapping of brain fiber pathways. Traditional methods rely on tissue modeling to estimate fiber orientations for streamline propagation, which are compu...
Multimodal sparse fusion transformer network with spatio-temporal decoupling for breast tumor classification [0.03%]
基于时空解耦的多模态稀疏融合Transformer网络乳腺肿瘤分类方法
Jiahao Xu,Shuxin Zhuang,Yi He et al.
Jiahao Xu et al.
Accurate analysis of tumor morphology, vascularity, and tissue stiffness under multimodal ultrasound imaging plays a critical role in the diagnosis of breast cancer. However, manual interpretation across multiple modalities is time-consumin...
ESM-AnatTractNet: Advanced deep learning model of true positive eloquent white matter tractography to improve preoperative evaluation of pediatric epilepsy surgery [0.03%]
基于深度学习的eloquent白质束成像模型提高儿童癫痫手术术前评估能力
Min-Hee Lee,Bohan Xiao,Soumyanil Banerjee et al.
Min-Hee Lee et al.
Accurate preoperative identification of true positive white matter pathways involved in critical eloquent functions such as motor, language, and vision plays a vital role in minimizing the risk of postoperative functional deficits and impro...
Xin You,Ming Ding,Minghui Zhang et al.
Xin You et al.
Accurate boundary segmentation of volumetric images is a critical task for image-guided diagnosis and computer-assisted intervention. It is challenging to address the boundary confusion with explicit constraints. Existing methods of refinin...
A navigation-guided 3D breast ultrasound scanning and reconstruction system for automated multi-lesion spatial localization and diagnosis [0.03%]
一种用于自动多病灶空间定位和诊断的导航引导式三维乳腺超声扫描与重建系统
Yi Zhang,Yulin Yan,Kun Wang et al.
Yi Zhang et al.
Handheld ultrasound (HHUS) is indispensable for breast cancer screening but remains compromised by operator-dependent acquisition, subjective 2D interpretation and clock-face annotation. Existing spatial tracking systems for HHUS typically ...
MADAT: Missing-aware dynamic adaptive transformer model for medical prognosis prediction with incomplete multimodal data [0.03%]
基于不完整多模态数据的医学预后预测的缺失感知动态自适应变换器模型
Jianbin He,Guoheng Huang,Xiaochen Yuan et al.
Jianbin He et al.
Multimodal medical prognosis prediction has shown great potential in improving diagnostic accuracy by integrating various data types. However, incomplete multimodality, where certain modalities are missing, poses significant challenges to m...
Reliable uncertainty quantification for 2D/3D anatomical landmark localization using multi-output conformal prediction [0.03%]
基于多输出共形预测的二维/三维解剖标志定位的可靠不确定性量化方法
Jef Jonkers,Frank Coopman,Luc Duchateau et al.
Jef Jonkers et al.
Automatic anatomical landmark localization in medical imaging requires not just accurate predictions but reliable uncertainty quantification for effective clinical decision support. Current uncertainty quantification approaches often fall s...
Fundus image quality assessment in retinopathy of prematurity via multi-label graph evidential network [0.03%]
早产儿视网膜病变的基金us图像质量评估的多标签图证据网络方法研究
Donghan Wu,Wenyue Shen,Lu Yuan et al.
Donghan Wu et al.
Retinopathy of Prematurity (ROP) is a leading cause of childhood blindness worldwide. In clinical practice, fundus imaging serves as a primary diagnostic tool for ROP, making the accurate quality assessment of these images critically import...
DPFR: Semi-supervised gland segmentation via density perturbation and feature recalibration [0.03%]
基于密度扰动和特征重标定的半监督腺体分割方法
Jiejiang Yu,Yu Liu
Jiejiang Yu
In recent years, semi-supervised methods have attracted considerable attention in gland segmentation of histopathological images, as they can substantially reduce the annotation data burden for pathologists. The most widely adopted approach...