7 citations · 28 across the 24 of their papers we have counts for
8 papers · 1 filter
SAME++: A Self-supervised Anatomical eMbeddings Enhanced medical image registration framework using stable sampling and regularized transformation
Lin Tian, Zi Li, Fengze Liu +7
Image registration is a fundamental medical image analysis task. Ideally, registration should focus on aligning semantically corresponding voxels, i.e., the same anatomical locatio…
Anatomy-Aware Lymph Node Detection in Chest CT using Implicit Station Stratification
Ke Yan, Dakai Jin, Dazhou Guo +5
Finding abnormal lymph nodes in radiological images is highly important for various medical tasks such as cancer metastasis staging and radiotherapy planning. Lymph nodes (LNs) are…
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…
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…
SAMConvex: Fast Discrete Optimization for CT Registration using Self-supervised Anatomical Embedding and Correlation Pyramid
Zi Li, Lin Tian, Tony C. W. Mok +8
Estimating displacement vector field via a cost volume computed in the feature space has shown great success in image registration, but it suffers excessive computation burdens. Mo…
Accurate Airway Tree Segmentation in CT Scans via Anatomy-aware Multi-class Segmentation and Topology-guided Iterative Learning
Puyang Wang, Dazhou Guo, Dandan Zheng +8
Intrathoracic airway segmentation in computed tomography (CT) is a prerequisite for various respiratory disease analyses such as chronic obstructive pulmonary disease (COPD), asthm…
Continual Segment: Towards a Single, Unified and Accessible Continual Segmentation Model of 143 Whole-body Organs in CT Scans
Zhanghexuan Ji, Dazhou Guo, Puyang Wang +9
Deep learning empowers the mainstream medical image segmentation methods. Nevertheless current deep segmentation approaches are not capable of efficiently and effectively adapting…
CancerUniT: Towards a Single Unified Model for Effective Detection, Segmentation, and Diagnosis of Eight Major Cancers Using a Large Collection of CT Scans
Jieneng Chen, Yingda Xia, Jiawen Yao +22
Human readers or radiologists routinely perform full-body multi-organ multi-disease detection and diagnosis in clinical practice, while most medical AI systems are built to focus o…