4 papers · 1 filter
BagShift: Measuring How Patch Selection Changes the Evidence Seen by Whole-Slide MIL
Ruicheng Yuan, Zhenxuan Zhang, Liwei Hu +4
Whole-slide multiple-instance learning (MIL) observes only the patches admitted by its selector. Deployment can alter this selector through compute limits, tissue masking, or regio…
HiPath: Hierarchical Vision-Language Alignment for Structured Pathology Report Prediction
Ruicheng Yuan, Zhenxuan Zhang, Anbang Wang +5
Pathology reports are structured, multi-granular documents encoding diagnostic conclusions, histological grades, and ancillary test results across one or more anatomical sites; yet…
MedSapiens: Taking a Pose to Rethink Medical Imaging Landmark Detection
Marawan Elbatel, Anbang Wang, Keyuan Liu +6
This paper does not introduce a novel architecture; instead, it revisits a fundamental yet overlooked baseline: adapting human-centric foundation models for anatomical landmark det…
Geometric-Guided Few-Shot Dental Landmark Detection with Human-Centric Foundation Model
Anbang Wang, Marawan Elbatel, Keyuan Liu +4
Accurate detection of anatomic landmarks is essential for assessing alveolar bone and root conditions, thereby optimizing clinical outcomes in orthodontics, periodontics, and impla…