SinGAN-Seg: Synthetic training data generation for medical image segmentation

SinGAN-Seg: Synthetic training data generation for medical image segmentation

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Analyzing medical data to find abnormalities is a time-consuming and costly task, particularly for rare abnormalities, requiring tremendous efforts from medical experts. Therefore, artificial intelligence has become a popular tool for the automatic processing of medical data, acting as a supportive...

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Bibliographic Details
Main Authors: Vajira Thambawita, Pegah Salehi, Sajad Amouei Sheshkal, Steven A. Hicks, Hugo L. Hammer, Sravanthi Parasa, Thomas de Lange, Pål Halvorsen, Michael A. Riegler
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2022-01-01
Series:PLoS ONE
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9060378/?tool=EBI

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https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9060378/?tool=EBI

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