212 citations · 216 across the 4 of their papers we have counts for
5 papers
HERO: Histology Encoder for Robust Representation in Oncology
Zhi Li, Eghbal Amidi, Yating Cheng +12
Foundation models trained on large pathology image corpora now provide strong, transferable representations for computational pathology. Over the past few years a series of such mo…
ESICA: A Scalable Framework for Text-Guided 3D Medical Image Segmentation
Yu Xin, Gorkem Can Ates, Jun Ma +5
Text guided 3D medical image segmentation offers a flexible alternative to class based and spatial prompt based models by allowing users to specify regions of interest directly in…
Med3DVLM: An Efficient Vision-Language Model for 3D Medical Image Analysis
Yu Xin, Gorkem Can Ates, Kuang Gong +1
Vision-language models (VLMs) have shown promise in 2D medical image analysis, but extending them to 3D remains challenging due to the high computational demands of volumetric data…
DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions
Gorkem Can Ates, Yu Xin, Kuang Gong +1
Vision-language models (VLMs) have been widely applied to 2D medical image analysis due to their ability to align visual and textual representations. However, extending VLMs to 3D…
Dual Cross-Attention for Medical Image Segmentation
Gorkem Can Ates, Prasoon Mohan, Emrah Celik
We propose Dual Cross-Attention (DCA), a simple yet effective attention module that is able to enhance skip-connections in U-Net-based architectures for medical image segmentation.…