Confident Learning-Based Label Correction for Retinal Image Segmentation

Confident Learning-Based Label Correction for Retinal Image Segmentation

<b>Background/Objectives:</b> In automatic medical image analysis, particularly for diabetic retinopathy, the accuracy of labeled data is crucial, as label noise can significantly complicate the analysis and lead to diagnostic errors. To tackle the issue of label noise in retinal image s...

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Bibliographic Details
Main Authors: Tanatorn Pethmunee, Supaporn Kansomkeat, Patama Bhurayanontachai, Sathit Intajag
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Diagnostics
Subjects:
labeling error
label noise correction
confident learning
semantic segmentation
retinal images
dataset refinement
Online Access:https://www.mdpi.com/2075-4418/15/14/1735
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