4 citations · 8 across the 5 of their papers we have counts for
5 papers
A Continual Learning-driven Model for Accurate and Generalizable Segmentation of Clinically Comprehensive and Fine-grained Whole-body Anatomies in CT
Dazhou Guo, Zhanghexuan Ji, Yanzhou Su +31
Precision medicine in the quantitative management of chronic diseases and oncology would be greatly improved if the Computed Tomography (CT) scan of any patient could be segmented,…
Towards a Comprehensive, Efficient and Promptable Anatomic Structure Segmentation Model using 3D Whole-body CT Scans
Heng Guo, Jianfeng Zhang, Jiaxing Huang +6
Segment anything model (SAM) demonstrates strong generalization ability on natural image segmentation. However, its direct adaptation in medical image segmentation tasks shows sign…
Parse and Recall: Towards Accurate Lung Nodule Malignancy Prediction like Radiologists
Jianpeng Zhang, Xianghua Ye, Jianfeng Zhang +8
Lung cancer is a leading cause of death worldwide and early screening is critical for improving survival outcomes. In clinical practice, the contextual structure of nodules and the…
Med-Query: Steerable Parsing of 9-DoF Medical Anatomies with Query Embedding
Heng Guo, Jianfeng Zhang, Ke Yan +2
Automatic parsing of human anatomies at the instance-level from 3D computed tomography (CT) is a prerequisite step for many clinical applications. The presence of pathologies, brok…
A New Probabilistic V-Net Model with Hierarchical Spatial Feature Transform for Efficient Abdominal Multi-Organ Segmentation
Minfeng Xu, Heng Guo, Jianfeng Zhang +2
Accurate and robust abdominal multi-organ segmentation from CT imaging of different modalities is a challenging task due to complex inter- and intra-organ shape and appearance vari…