4 citations · 8 across the 8 of their papers we have counts for
8 papers
AI-Driven Automated Tool for Abdominal CT Body Composition Analysis in Gastrointestinal Cancer Management
Xinyu Nan, Meng He, Zifan Chen +3
The incidence of gastrointestinal cancers remains significantly high, particularly in China, emphasizing the importance of accurate prognostic assessments and effective treatment s…
PAM: A Propagation-Based Model for Segmenting Any 3D Objects across Multi-Modal Medical Images
Zifan Chen, Xinyu Nan, Jiazheng Li +9
Volumetric segmentation is important in medical imaging, but current methods face challenges like requiring lots of manual annotations and being tailored to specific tasks, which l…
Large Language Models Illuminate a Progressive Pathway to Artificial Healthcare Assistant: A Review
Mingze Yuan, Peng Bao, Jiajia Yuan +8
With the rapid development of artificial intelligence, large language models (LLMs) have shown promising capabilities in mimicking human-level language comprehension and reasoning.…
propnet: Propagating 2D Annotation to 3D Segmentation for Gastric Tumors on CT Scans
Zifan Chen, Jiazheng Li, Jie Zhao +5
**Background:** Accurate 3D CT scan segmentation of gastric tumors is pivotal for diagnosis and treatment. The challenges lie in the irregular shapes, blurred boundaries of tumors,…
Devil is in the Queries: Advancing Mask Transformers for Real-world Medical Image Segmentation and Out-of-Distribution Localization
Mingze Yuan, Yingda Xia, Hexin Dong +13
Real-world medical image segmentation has tremendous long-tailed complexity of objects, among which tail conditions correlate with relatively rare diseases and are clinically signi…
Region-Aware Metric Learning for Open World Semantic Segmentation via Meta-Channel Aggregation
Hexin Dong, Zifan Chen, Mingze Yuan +5
As one of the most challenging and practical segmentation tasks, open-world semantic segmentation requires the model to segment the anomaly regions in the images and incrementally…
Multi-Scale Context-Guided Lumbar Spine Disease Identification with Coarse-to-fine Localization and Classification
Zifan Chen, Jie Zhao, Hao Yu +2
Accurate and efficient lumbar spine disease identification is crucial for clinical diagnosis. However, existing deep learning models with millions of parameters often fail to learn…
Composite Localization for Human Pose Estimation
ZiFan Chen, Xin Qin, Chao Yang +1
The existing human pose estimation methods are confronted with inaccurate long-distance regression or high computational cost due to the complex learning objectives. This work prop…