9 papers
SemiSAM-O1: Pushing the Boundary of Annotation-Efficient Medical Image Segmentation with Generalist Knowledge Fusion
Yichi Zhang, Le Xue, Bichun Xu +6
Semi-supervised learning (SSL) has become a promising solution to alleviate the annotation burden of deep learning-based medical image segmentation models. While recent advances in…
Developing Foundation Models for Universal Segmentation from 3D Whole-Body Positron Emission Tomography
Yichi Zhang, Le Xue, Wenbo Zhang +16
Positron emission tomography (PET) is a key nuclear medicine imaging modality that visualizes radiotracer distributions to quantify in vivo physiological and metabolic processes, p…
SegAnyPET: Universal Promptable Segmentation from Positron Emission Tomography Images
Yichi Zhang, Le Xue, Wenbo Zhang +5
Positron Emission Tomography (PET) is a powerful molecular imaging tool that plays a crucial role in modern medical diagnostics by visualizing radio-tracer distribution to reveal p…
PET-F2I: A Comprehensive Benchmark and Parameter-Efficient Fine-Tuning of LLMs for PET/CT Report Impression Generation
Yuchen Liu, Wenbo Zhang, Liling Peng +6
PET/CT imaging is pivotal in oncology and nuclear medicine, yet summarizing complex findings into precise diagnostic impressions is labor-intensive. While LLMs have shown promise i…
Rethinking Intracranial Aneurysm Vessel Segmentation: A Perspective from Computational Fluid Dynamics Applications
Feiyang Xiao, Yichi Zhang, Xigui Li +7
The precise segmentation of intracranial aneurysms and their parent vessels (IA-Vessel) is a critical step for hemodynamic analyses, which mainly depends on computational fluid dyn…
PET2Rep: Towards Vision-Language Model-Drived Automated Radiology Report Generation for Positron Emission Tomography
Yichi Zhang, Wenbo Zhang, Zehui Ling +12
Positron emission tomography (PET) is a cornerstone of modern oncologic and neurologic imaging, distinguished by its unique ability to illuminate dynamic metabolic processes that t…