S<sup>3</sup>-TTA: Scale-Style Selection for Test-Time Augmentation in Biomedical Image Segmentation-Reference-Cited by-同舟云学术

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S³-TTA: Scale-Style Selection for Test-Time Augmentation in Biomedical Image Segmentation

Published:2024-05-27 Issue: Volume:abs/1508.06576 Page:1-5
ISSN:
Container-title:2024 IEEE International Symposium on Biomedical Imaging (ISBI)
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Author:

Xie Kangxian¹,Huang Siyu²,Ordonez Sebastian Cajas³,Pfister Hanspeter³,Wei Donglai⁴

Affiliation:

1. Boston University

2. Clemson University

3. Harvard University

4. Boston College

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10635099/10635102/10635833.pdf?arnumber=10635833

Reference19 articles.

1. nucleAIzer: A Parameter-free Deep Learning Framework for Nucleus Segmentation Using Image Style Transfer

2. Style-Invariant Cardiac Image Segmentation with Test-Time Augmentation

3. Test-time augmentation for deep learning-based cell segmentation on microscopy images

4. Cellpose: a generalist algorithm for cellular segmentation

5. Mask R-CNN

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