[A multi-scale supervision and residual feedback optimization algorithm for improving optic chiasm and optic nerve segmentation accuracy in nasopharyngeal carcinoma CT images].

The proposed deep learning segmentation algorithm can effectively enhance feature representation to achieve accurate segmentation of the optic chiasm and optic nerves in CT images of NPC.

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Publication Details

Journal
PubMed
Published
2025-03-20
DOI
https://doi.org/10.12122/j.issn.1673-4254.2025.03.21
Primary Topic
Brain Tumor Detection and Classification
Type
article
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[A multi-scale supervision and residual feedback optimization algorithm for improving optic chiasm and optic nerve segmentation accuracy in nasopharyngeal carcinoma CT images].

Shujun Liang, Jinyu Liu, Yu Zhang
PubMed
Brain Tumor Detection and Classification
article

[A multi-scale supervision and residual feedback optimization algorithm for improving optic chiasm and optic nerve segmentation accuracy in nasopharyngeal carcinoma CT images].

Shujun Liang, Jinyu Liu, Yu Zhang
article en

Abstract

The proposed deep learning segmentation algorithm can effectively enhance feature representation to achieve accurate segmentation of the optic chiasm and optic nerves in CT images of NPC.

PubMedVol. 45(3)
Southern Medical University (CN)
Brain Tumor Detection and Classification
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[A multi-scale supervision and residual feedback optimization algorithm for improving optic chiasm and optic nerve segmentation accuracy in nasopharyngeal carcinoma CT images]. — Shujun Liang, Jinyu Liu, et al. · PubMed (2025) | TGRS Research Map | TGRS