most cited3D TransUNet: Advancing Medical Image Segmentation through Vision Transformers

38 citations · 38 across the 5 of their papers we have counts for

collaborators

5 papers

q-bio.QM2026

A vision foundation model for single-cell biology via spatial gene cartography

Ridvan Yesiloglu, Sakib Mostafa, James Zou +5

Most single-cell foundation models are adapted from language models, representing each cell as a sequence of gene tokens. This discards the relationships among genes and often the…

cs.LG2026

Knowledge Graph Modulated Deep Learning for Limited-Sample Clinical Data Analysis

Yuwei Xue, Sakib Mostafa, James Zou +5

Biological systems are governed by structured molecular interactions, where pathways, regulatory circuits, and functional gene relationships shape cellular behavior and disease pro…

cs.LG2026

Toward a universal foundation model for graph-structured data

Sakib Mostafa, Lei Xing, Md. Tauhidul Islam

Graphs are a central representation in biomedical research, capturing molecular interaction networks, gene regulatory circuits, cell--cell communication maps, and knowledge graphs.…

cs.LG2026

Vision-based Deep Learning Analysis of Unordered Biomedical Tabular Datasets via Optimal Spatial Cartography

Sakib Mostafa, Tarik Massoud, Maximilian Diehn +2

Tabular data are central to biomedical research, from liquid biopsy and bulk and single-cell transcriptomics to electronic health records and phenotypic profiling. Unlike images or…

cs.CV2023★ 38 cited

3D TransUNet: Advancing Medical Image Segmentation through Vision Transformers

Jieneng Chen, Jieru Mei, Xianhang Li +12

Medical image segmentation plays a crucial role in advancing healthcare systems for disease diagnosis and treatment planning. The u-shaped architecture, popularly known as U-Net, h…