most citedTransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

4k citations · 4k across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20212 cited

Sequential Learning on Liver Tumor Boundary Semantics and Prognostic Biomarker Mining

Jieneng Chen, Ke Yan, Yu-Dong Zhang +9

The boundary of tumors (hepatocellular carcinoma, or HCC) contains rich semantics: capsular invasion, visibility, smoothness, folding and protuberance, etc. Capsular invasion on tu…

eess.IV202135 cited

SpecTr: Spectral Transformer for Hyperspectral Pathology Image Segmentation

Boxiang Yun, Yan Wang, Jieneng Chen +3

Hyperspectral imaging (HSI) unlocks the huge potential to a wide variety of applications relied on high-precision pathology image segmentation, such as computational pathology and…

cs.CV20214k cited

TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

Jieneng Chen, Yongyi Lu, Qihang Yu +6

Medical image segmentation is an essential prerequisite for developing healthcare systems, especially for disease diagnosis and treatment planning. On various medical image segment…

cs.CV20197 cited

Deep Distance Transform for Tubular Structure Segmentation in CT Scans

Yan Wang, Xu Wei, Fengze Liu +5

Tubular structure segmentation in medical images, e.g., segmenting vessels in CT scans, serves as a vital step in the use of computers to aid in screening early stages of related d…

cs.AI2019

Towards Brain-inspired System: Deep Recurrent Reinforcement Learning for Simulated Self-driving Agent

Jieneng Chen, Jingye Chen, Ruiming Zhang +1

An effective way to achieve intelligence is to simulate various intelligent behaviors in the human brain. In recent years, bio-inspired learning methods have emerged, and they are…