Youngjin Yoo

Revisiting 2D Foundation Models for Scalable 3D Medical Image Classification

3D medical image classification is essential to modern clinical workflows. Medical foundation models (FMs) have emerged as a promising approach for scaling to new tasks, yet current research suffers from three critical pitfalls: data-regime bias, suboptimal adaptation, and insufficient task coverage