Correction: Raymann, J.; Rajalakshmi, R. GAR-Net: Guided Attention Residual Network for Polyp Segmentation from Colonoscopy Video Frames. Diagnostics 2023, 13, 123

Joel Raymann; Ratnavel Rajalakshmi

doi:10.3390/diagnostics14090900

and

¹

Faculty of Mathematics, University of Waterloo, Waterloo, ON N2L 3G1, Canada

²

School of Computer Science and Engineering, Vellore Institute of Technology, Chennai 600127, India

^*

Author to whom correspondence should be addressed.

Diagnostics2024, 14(9), 900;https://doi.org/10.3390/diagnostics14090900

This article belongs to the Section Machine Learning and Artificial Intelligence in Diagnostics

Version Notes

Order Reprints

There was an error in the original publication [1]. Section 2. Related Works contains paragraphs from the journal’s template.

A correction has been made by removing the last three paragraphs of Section 2. Related Works.

The authors state that the scientific conclusions are unaffected. This correction was approved by the Academic Editor. The original publication has also been updated.

Reference

Raymann, J.; Rajalakshmi, R. GAR-Net: Guided Attention Residual Network for Polyp Segmentation from Colonoscopy Video Frames. Diagnostics 2023, 13, 123. [Google Scholar] [CrossRef] [PubMed]

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© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Correction: Raymann, J.; Rajalakshmi, R. GAR-Net: Guided Attention Residual Network for Polyp Segmentation from Colonoscopy Video Frames. Diagnostics 2023, 13, 123

Reference

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