POPAR: Patch Order Prediction and Appearance Recovery for Self-supervised Medical Image Analysis

Pang Jiaxuan; Haghighi Fatemeh; Ma DongAo; Islam Nahid Ul; Hosseinzadeh Taher Mohammad Reza; Gotway Michael B.; Liang Jianming

doi:10.5281/zenodo.7102247

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Published September 21, 2022 | Version 1

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POPAR: Patch Order Prediction and Appearance Recovery for Self-supervised Medical Image Analysis

1. Arizona State University
2. Mayo Clinic

Pre-trained Models for POPAR: Patch Order Prediction and Appearance Recovery for Self-supervised Medical Image Analysis

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Name	Size
POPAR_Swin_448.pth md5:363cbd5eecaee1ed6d604565ad16e6a2	1.5 GB	Download
POPAR_ViT_224.pth md5:514221da50cb92457ee7311241f2bc54	691.2 MB	Download

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DOI

Resource type

Other

Publisher

Zenodo

Conference

International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2022); Domain Adaptation and Representation Transfer (DART2022) (MICCAI 2022; DART 2022)

License: Creative Commons Attribution 4.0 International

The Creative Commons Attribution license allows re-distribution and re-use of a licensed work on the condition that the creator is appropriately credited. Read more

Technical metadata

Created: September 22, 2022
Modified: April 30, 2023

POPAR: Patch Order Prediction and Appearance Recovery for Self-supervised Medical Image Analysis

Authors/Creators

Description

Files

Files (2.1 GB)