Search Results for author: Yufan He

Found 19 papers, 10 papers with code

Aorta Segmentation from 3D CT in MICCAI SEG.A. 2023 Challenge

1 code implementation6 Oct 2023 Andriy Myronenko, Dong Yang, Yufan He, Daguang Xu

In this work, we describe our solution to the Segmentation of the Aorta (SEG. A. 231) from 3D CT challenge.

Segmentation

Automated 3D Segmentation of Kidneys and Tumors in MICCAI KiTS 2023 Challenge

1 code implementation6 Oct 2023 Andriy Myronenko, Dong Yang, Yufan He, Daguang Xu

Kidney and Kidney Tumor Segmentation Challenge (KiTS) 2023 offers a platform for researchers to compare their solutions to segmentation from 3D CT.

Segmentation Tumor Segmentation

Deformable Cross-Attention Transformer for Medical Image Registration

no code implementations10 Mar 2023 Junyu Chen, Yihao Liu, Yufan He, Yong Du

Transformers have recently shown promise for medical image applications, leading to an increasing interest in developing such models for medical image registration.

Image Registration Medical Image Registration

Spatially-varying Regularization with Conditional Transformer for Unsupervised Image Registration

no code implementations10 Mar 2023 Junyu Chen, Yihao Liu, Yufan He, Yong Du

In the past, optimization-based registration models have used spatially-varying regularization to account for deformation variations in different image regions.

Unsupervised Image Registration

Automated head and neck tumor segmentation from 3D PET/CT

1 code implementation22 Sep 2022 Andriy Myronenko, Md Mahfuzur Rahman Siddiquee, Dong Yang, Yufan He, Daguang Xu

Head and neck tumor segmentation challenge (HECKTOR) 2022 offers a platform for researchers to compare their solutions to segmentation of tumors and lymph nodes from 3D CT and PET images.

Segmentation Tumor Segmentation

Automated segmentation of intracranial hemorrhages from 3D CT

no code implementations21 Sep 2022 Md Mahfuzur Rahman Siddiquee, Dong Yang, Yufan He, Daguang Xu, Andriy Myronenko

Intracranial hemorrhage segmentation challenge (INSTANCE 2022) offers a platform for researchers to compare their solutions to segmentation of hemorrhage stroke regions from 3D CTs.

Segmentation

Automated ischemic stroke lesion segmentation from 3D MRI

no code implementations20 Sep 2022 Md Mahfuzur Rahman Siddique, Dong Yang, Yufan He, Daguang Xu, Andriy Myronenko

Ischemic Stroke Lesion Segmentation challenge (ISLES 2022) offers a platform for researchers to compare their solutions to 3D segmentation of ischemic stroke regions from 3D MRIs.

Ischemic Stroke Lesion Segmentation Lesion Segmentation +2

TransMorph: Transformer for unsupervised medical image registration

1 code implementation19 Nov 2021 Junyu Chen, Eric C. Frey, Yufan He, William P. Segars, Ye Li, Yong Du

Recently Vision Transformer architectures have been proposed to address the shortcomings of ConvNets and have produced state-of-the-art performances in many medical imaging applications.

Image Registration Medical Image Registration

ViT-V-Net: Vision Transformer for Unsupervised Volumetric Medical Image Registration

1 code implementation13 Apr 2021 Junyu Chen, Yufan He, Eric C. Frey, Ye Li, Yong Du

However, the performances of ConvNets are still limited by lacking the understanding of long-range spatial relations in an image.

Image Classification Image Registration +3

DiNTS: Differentiable Neural Network Topology Search for 3D Medical Image Segmentation

1 code implementation CVPR 2021 Yufan He, Dong Yang, Holger Roth, Can Zhao, Daguang Xu

In this work, we focus on three important aspects of NAS in 3D medical image segmentation: flexible multi-path network topology, high search efficiency, and budgeted GPU memory usage.

Image Segmentation Medical Image Segmentation +3

Self domain adapted network

1 code implementation7 Jul 2020 Yufan He, Aaron Carass, Lianrui Zuo, Blake E. Dewey, Jerry L. Prince

However, training a model for each target domain is time consuming and computationally expensive, even infeasible when target domain data are scarce or source data are unavailable due to data privacy.

Self-Supervised Learning Unsupervised Domain Adaptation

Finding novelty with uncertainty

2 code implementations11 Feb 2020 Jacob C. Reinhold, Yufan He, Shizhong Han, Yunqiang Chen, Dashan Gao, Junghoon Lee, Jerry L. Prince, Aaron Carass

Medical images are often used to detect and characterize pathology and disease; however, automatically identifying and segmenting pathology in medical images is challenging because the appearance of pathology across diseases varies widely.

Segmentation

Validating uncertainty in medical image translation

1 code implementation11 Feb 2020 Jacob C. Reinhold, Yufan He, Shizhong Han, Yunqiang Chen, Dashan Gao, Junghoon Lee, Jerry L. Prince, Aaron Carass

Medical images are increasingly used as input to deep neural networks to produce quantitative values that aid researchers and clinicians.

Translation

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