Automated segmentation of the healed anterior cruciate ligament from T₂ * relaxometry MRI scans.

ABSTRACT: Collagen organization of the anterior cruciate ligament (ACL) can be evaluated using T₂ * relaxometry. However, T₂ * mapping requires manual image segmentation, which is a time-consuming process and prone to inter- and intra- segmenter variability. Automating segmentation would address these challenges. A model previously trained using Constructive Interference in Steady State (CISS) scans was applied to T₂ * segmentation via transfer learning. It was hypothesized that there would be no significant differences in the model's segmentation performance between T₂ * and CISS, structural measures versus ground truth manual segmentation, and reliability versus independent and retest manual segmentation. Transfer learning was conducted using 54 T_2<

SUBMITTER: Flannery SW 

PROVIDER: S-EPMC9708947 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature