1 citations · 1 across the 3 of their papers we have counts for
4 papers
Knee3DVLM: Dual-Sequence Full-Volume Vision-Language Modeling for Comprehensive Knee MRI Assessment
Maryam Baizhigitova, Andrew Seohwan Yu, Po-Hao Chen +7
Vision-language models (VLMs) are increasingly being applied to three-dimensional medical imaging, but their application to knee MRI remains limited, particularly for interpreting…
Medical Image Spatial Grounding with Semantic Sampling
Andrew Seohwan Yu, Mohsen Hariri, Kunio Nakamura +3
Vision language models (VLMs) have shown significant promise in visual grounding for images as well as videos. In medical imaging research, VLMs represent a bridge between object d…
Forte : Finding Outliers with Representation Typicality Estimation
Debargha Ganguly, Warren Morningstar, Andrew Yu +1
Generative models can now produce photorealistic synthetic data which is virtually indistinguishable from the real data used to train it. This is a significant evolution over previ…
Novel adaptation of video segmentation to 3D MRI: efficient zero-shot knee segmentation with SAM2
Andrew Seohwan Yu, Mohsen Hariri, Xuecen Zhang +3
Intelligent medical image segmentation methods are rapidly evolving and being increasingly applied, yet they face the challenge of domain transfer, where algorithm performance degr…