activity
20222026
most citedUNesT: Local Spatial Representation Learning with Hierarchical Transformer for Efficient Medical Segmentation

4 citations · 15 across the 18 of their papers we have counts for

collaborators
Showing 2022Show all

5 papers · 1 filter

eess.IV2022★ 1 cited

Time-distance vision transformers in lung cancer diagnosis from longitudinal computed tomography

Thomas Z. Li, Kaiwen Xu, Riqiang Gao +5

Features learned from single radiologic images are unable to provide information about whether and how much a lesion may be changing over time. Time-dependent features computed fro…

eess.IV2022★ 4 cited

UNesT: Local Spatial Representation Learning with Hierarchical Transformer for Efficient Medical Segmentation

Xin Yu, Qi Yang, Yinchi Zhou +12

Transformer-based models, capable of learning better global dependencies, have recently demonstrated exceptional representation learning capabilities in computer vision and medical…

eess.IV2022★ 1 cited

Body Composition Assessment with Limited Field-of-view Computed Tomography: A Semantic Image Extension Perspective

Kaiwen Xu, Thomas Li, Mirza S. Khan +6

Field-of-view (FOV) tissue truncation beyond the lungs is common in routine lung screening computed tomography (CT). This poses limitations for opportunistic CT- based body composi…

cs.CV2022★ 2 cited

A Comparative Study of Confidence Calibration in Deep Learning: From Computer Vision to Medical Imaging

Riqiang Gao, Thomas Li, Yucheng Tang +7

Although deep learning prediction models have been successful in the discrimination of different classes, they can often suffer from poor calibration across challenging domains inc…

eess.IV2022★ 4 cited

Characterizing Renal Structures with 3D Block Aggregate Transformers

Xin Yu, Yucheng Tang, Yinchi Zhou +10

Efficiently quantifying renal structures can provide distinct spatial context and facilitate biomarker discovery for kidney morphology. However, the development and evaluation of t…