1 code implementation • 25 Nov 2023 • Xiaoyu Bai, Fan Bai, Xiaofei Huo, Jia Ge, JingJing Lu, Xianghua Ye, Ke Yan, Yong Xia
They use self-supervised learning to acquire a discriminative embedding for each voxel within the image.
no code implementations • 7 Jul 2023 • Xiaoyu Bai, Fan Bai, Xiaofei Huo, Jia Ge, Tony C. W. Mok, Zi Li, Minfeng Xu, Jingren Zhou, Le Lu, Dakai Jin, Xianghua Ye, JingJing Lu, Ke Yan
We then use this SAM to identify corresponding regions on paired images using robust grid-points matching, followed by a point-set based affine/rigid registration, and a deformable fine-tuning step to produce registered paired images.
no code implementations • 5 May 2021 • YouBao Tang, Ke Yan, Jinzheng Cai, Lingyun Huang, Guotong Xie, Jing Xiao, JingJing Lu, Gigin Lin, Le Lu
PDNet learns comprehensive and representative deep image features for our tasks and produces more accurate results on both lesion segmentation and RECIST diameter prediction.
no code implementations • 3 May 2021 • YouBao Tang, Jinzheng Cai, Ke Yan, Lingyun Huang, Guotong Xie, Jing Xiao, JingJing Lu, Gigin Lin, Le Lu
Accurately segmenting a variety of clinically significant lesions from whole body computed tomography (CT) scans is a critical task on precision oncology imaging, denoted as universal lesion segmentation (ULS).
1 code implementation • 4 Dec 2020 • Ke Yan, Jinzheng Cai, Dakai Jin, Shun Miao, Dazhou Guo, Adam P. Harrison, YouBao Tang, Jing Xiao, JingJing Lu, Le Lu
We introduce such an approach, called Self-supervised Anatomical eMbedding (SAM).