Zobrazeno 1 - 10
of 171 639
pro vyhledávání: '"Multi-organ"'
Autor:
Robert S. D. Higgins, Juan Sanchez
Advances in the science of immunology have improved the success rate of organ transplantations since the mid twentieth century. Organ transplantation is now a lifesaving medical procedure for thousands of patients around the world with end-organ dise
Pathological cell semantic segmentation is a fundamental technology in computational pathology, essential for applications like cancer diagnosis and effective treatment. Given that multiple cell types exist across various organs, with subtle differen
Externí odkaz:
http://arxiv.org/abs/2412.02978
Multi-organ diseases present significant challenges due to their simultaneous impact on multiple organ systems, necessitating complex and adaptive treatment strategies. Despite recent advancements in AI-powered healthcare decision support systems, ex
Externí odkaz:
http://arxiv.org/abs/2409.04224
Autor:
Tian, Weiwei, Huang, Xinyu, Hou, Junlin, Ren, Caiyue, Jiang, Longquan, Zhao, Rui-Wei, Jin, Gang, Zhang, Yuejie, Geng, Daoying
Owing to a large amount of multi-modal data in modern medical systems, such as medical images and reports, Medical Vision-Language Pre-training (Med-VLP) has demonstrated incredible achievements in coarse-grained downstream tasks (i.e., medical class
Externí odkaz:
http://arxiv.org/abs/2409.02418
Autor:
Zhao, Haochen, Meng, Hui, Yang, Deqian, Xie, Xiaozheng, Wu, Xiaoze, Li, Qingfeng, Niu, Jianwei
Semi-supervised multi-organ medical image segmentation aids physicians in improving disease diagnosis and treatment planning and reduces the time and effort required for organ annotation.Existing state-of-the-art methods train the labeled data with g
Externí odkaz:
http://arxiv.org/abs/2408.04914
Autor:
Hornung, Eden1 (AUTHOR), Achanta, Sirisha1 (AUTHOR), Moss, Alison1 (AUTHOR), Schwaber, James S.1 (AUTHOR) rajanikanth.vadigepalli@jefferson.edu, Vadigepalli, Rajanikanth1 (AUTHOR) james.schwaber@jefferson.edu
Publikováno v:
PLoS ONE. 11/8/2024, Vol. 19 Issue 11, p1-28. 28p.
Vision language models (VLM) have achieved success in both natural language comprehension and image recognition tasks. However, their use in pathology report generation for whole slide images (WSIs) is still limited due to the huge size of multi-scal
Externí odkaz:
http://arxiv.org/abs/2409.15574
AFFSegNet: Adaptive Feature Fusion Segmentation Network for Microtumors and Multi-Organ Segmentation
Autor:
Zheng, Fuchen, Chen, Xinyi, Chen, Xuhang, Li, Haolun, Guo, Xiaojiao, Liu, Weihuang, Pun, Chi-Man, Zhou, Shoujun
Medical image segmentation, a crucial task in computer vision, facilitates the automated delineation of anatomical structures and pathologies, supporting clinicians in diagnosis, treatment planning, and disease monitoring. Notably, transformers emplo
Externí odkaz:
http://arxiv.org/abs/2409.07779
Partially-supervised multi-organ medical image segmentation aims to develop a unified semantic segmentation model by utilizing multiple partially-labeled datasets, with each dataset providing labels for a single class of organs. However, the limited
Externí odkaz:
http://arxiv.org/abs/2409.03228