UNETR: Transformers for 3D Medical Image Segmentation-Reference-Cited by-同舟云学术

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UNETR: Transformers for 3D Medical Image Segmentation

Published:2022-01 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
language:
Short-container-title:

Author:

Hatamizadeh Ali¹,Tang Yucheng²,Nath Vishwesh¹,Yang Dong¹,Myronenko Andriy¹,Landman Bennett²,Roth Holger R.¹,Xu Daguang¹

Affiliation:

1. NVIDIA

2. Vanderbilt University

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9706406/9706408/09706678.pdf?arnumber=9706678

Reference55 articles.

1. High-resolution 3D abdominal segmentation with random patch network fusion

2. Multiclass semantic segmentation and quantification of traumatic brain injury lesions on head CT using deep learning: an algorithm development and multicentre validation study

3. V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation

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