14 citations · 31 across the 19 of their papers we have counts for
9 papers · 1 filter
SAMRI-3D: Adapting SAM2 for 3D MRI Segmentation with Global Volume Tokens
Zhao Wang, Wei Dai, Hongfu Sun +2
Foundation models such as Segment Anything Model 2 (SAM2) have transformed natural-image and video segmentation, and recent work has begun adapting them to medical imaging. These a…
Anatomical grounding pre-training for medical phrase grounding
Wenjun Zhang, Shakes Chandra, Aaron Nicolson
Medical Phrase Grounding (MPG) maps radiological findings described in medical reports to specific regions in medical images. The primary obstacle hindering progress in MPG is the…
TriFormer: A Multi-modal Transformer Framework For Mild Cognitive Impairment Conversion Prediction
Linfeng Liu, Junyan Lyu, Siyu Liu +3
The prediction of mild cognitive impairment (MCI) conversion to Alzheimer's disease (AD) is important for early treatment to prevent or slow the progression of AD. To accurately pr…
Evidence-aware multi-modal data fusion and its application to total knee replacement prediction
Xinwen Liu, Jing Wang, S. Kevin Zhou +2
Deep neural networks have been widely studied for predicting a medical condition, such as total knee replacement (TKR). It has shown that data of different modalities, such as imag…
Towards Trustable Skin Cancer Diagnosis via Rewriting Model's Decision
Siyuan Yan, Zhen Yu, Xuelin Zhang +5
Deep neural networks have demonstrated promising performance on image recognition tasks. However, they may heavily rely on confounding factors, using irrelevant artifacts or bias w…
Skin Lesion Recognition with Class-Hierarchy Regularized Hyperbolic Embeddings
Zhen Yu, Toan Nguyen, Yaniv Gal +7
In practice, many medical datasets have an underlying taxonomy defined over the disease label space. However, existing classification algorithms for medical diagnoses often assume…