51 citations · 58 across the 6 of their papers we have counts for
6 papers
Matching in the Wild: Learning Anatomical Embeddings for Multi-Modality Images
Xiaoyu Bai, Fan Bai, Xiaofei Huo +10
Radiotherapists require accurate registration of MR/CT images to effectively use information from both modalities. In a typical registration pipeline, rigid or affine transformatio…
Lesion Segmentation and RECIST Diameter Prediction via Click-driven Attention and Dual-path Connection
Youbao Tang, Ke Yan, Jinzheng Cai +6
Measuring lesion size is an important step to assess tumor growth and monitor disease progression and therapy response in oncology image analysis. Although it is tedious and highly…
Weakly-Supervised Universal Lesion Segmentation with Regional Level Set Loss
Youbao Tang, Jinzheng Cai, Ke Yan +6
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 univer…
SAM: Self-supervised Learning of Pixel-wise Anatomical Embeddings in Radiological Images
Ke Yan, Jinzheng Cai, Dakai Jin +7
Radiological images such as computed tomography (CT) and X-rays render anatomy with intrinsic structures. Being able to reliably locate the same anatomical structure across varying…
Encoding Metal Mask Projection for Metal Artifact Reduction in Computed Tomography
Yuanyuan Lyu, Wei-An Lin, Haofu Liao +2
Metal artifact reduction (MAR) in computed tomography (CT) is a notoriously challenging task because the artifacts are structured and non-local in the image domain. However, they a…
Combining Pyramid Pooling and Attention Mechanism for Pelvic MR Image Semantic Segmentaion
Ting-Ting Liang, Satoshi Tsutsui, Liangcai Gao +2
One of the time-consuming routine work for a radiologist is to discern anatomical structures from tomographic images. For assisting radiologists, this paper develops an automatic s…