Background The variation in articular cartilage thickness (ACT) in healthy knees is difficult to
quantify and therefore poorly documented. Our aims are to (1) define how machine learning …

Purpose Software-based image analysis is important for studies of cartilage changes in
knee osteoarthritis (OA). This study describes an evaluation of a semi-automated cartilage …

OBJECTIVE: The primary goal of this study was to describe and evaluate conditions that
could influence the precision and accuracy of measuring in vivo cartilage thickness in the …

Objective. Accurate automated segmentation of cartilage should provide rapid reliable
outcomes for both epidemiological studies and clinical trials. We aimed to assess the …

OBJECTIVE: Quantitative magnetic resonance imaging (qMRI) of knee cartilage morphology
is a powerful research tool but relies on expensive and often inaccessible 1.5 T whole-body …

Background Establishing clinically accessible measures of cartilage health is critical for
assessing effectiveness of protocols to reduce risk of osteoarthritis (OA) development and …

OBJECTIVE: To assess the reliability and accuracy of manual and semi-automated
segmentation methods for quantifying knee cartilage thickness. This study employed both …

OBJECTIVE: Validation of a new fast software technique to segment the cartilage on knee
magnetic resonance (MR) acquisitions. Large studies of knee osteoarthritis (OA) will require …

The objective of this work was to develop a methodology for measuring cartilage thickness
in anatomically based subregions in the tibial and in the central weight-bearing femoral …

Background The purpose of this study was to retrospectively investigate whether the
average cartilage thickness calculated by magnetic resonance imaging (MRI) three …