Research Progress on Semantic Segmentation in Lumbar Degenerative Diseases.

Authors

Yu-Tong Ji, Chuan-Tao Wang, Hai-Liang Xia, Ji-Liang Zhai

Published in

Zhongguo yi xue ke xue yuan xue bao. Acta Academiae Medicinae Sinicae. Sep 14, 2026. Epub Sep 14, 2026.

Abstract

With the continuous advancement of medical imaging technologies,deep learning-based semantic segmentation has emerged as a key methodology in medical image analysis,achieving substantial progress in recent years.In particular,these techniques have demonstrated remarkable effectiveness in the automated identification and segmentation of lumbar spine-related diseases.This review provides a comprehensive overview of widely used deep learning-based semantic segmentation methods and systematically summarizes their recent applications in intervertebral disc segmentation,detection and classification of lumbar degenerative disorders,and quantitative analysis of lumbar intervertebral discs.Furthermore,the major challenges associated with current approaches in clinical and practical settings are discussed,and potential directions for future research and methodological improvements are highlighted.

PMID:
42733950
Bibliographic data and abstract were imported from PubMed on 14 Sep 2026.

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