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LM-CartSeg pipeline automates knee MRI cartilage and bone segmentation for radiomics

Researchers have developed LM-CartSeg, an automated pipeline for segmenting knee MRI scans to analyze cartilage and subchondral bone. This system uses two 3D nnU-Net models and geometric rules for accurate compartmentalization and radiomics feature extraction. The pipeline demonstrated strong performance in classifying osteoarthritis, outperforming models that only considered size-related features. AI

Summary written by gemini-2.5-flash-lite from 1 source. How we write summaries →

IMPACT Provides a robust, automated foundation for multi-center knee osteoarthritis radiomics studies.

RANK_REASON Academic paper detailing a new automated segmentation pipeline for medical imaging analysis.

Read on arXiv cs.CV →

COVERAGE [1]

  1. arXiv cs.CV TIER_1 · Tongxu Zhang, Zongpan Li, Aaron Kam Lun Leung, Siu Ngor Fu ·

    LM-CartSeg: Automated Segmentation of Lateral and Medial Cartilage and Subchondral Bone for Radiomics Analysis

    arXiv:2512.03449v3 Announce Type: replace Abstract: Background and Objective: Radiomics of knee MRI requires robust, anatomically meaningful regions of interest (ROIs) that jointly capture cartilage and subchondral bone. Most existing work relies on manual ROIs and rarely reports…