Cross-Cohort Automatic Knee MRI Segmentation With Multi-Planar U-Nets.

ABSTRACT:

Background

Segmentation of medical image volumes is a time-consuming manual task. Automatic tools are often tailored toward specific patient cohorts, and it is unclear how they behave in other clinical settings.

Purpose

To evaluate the performance of the open-source Multi-Planar U-Net (MPUnet), the validated Knee Imaging Quantification (KIQ) framework, and a state-of-the-art two-dimensional (2D) U-Net architecture on three clinical cohorts without extensive adaptation of the algorithms.

Study type

Retrospective cohort study.

Subjects

A total of 253 subjects (146 females, 107 males, ages 57 ± 12 years) from three knee osteoarthritis (OA) studies (Center for Clinical and Basic Research [CCBR], Osteoarthritis Initiative [OAI], and Prevention of OA in Overweight Fe

SUBMITTER: Perslev M 

PROVIDER: S-EPMC9106804 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature