Paper
12 March 2010 Surface smoothness: cartilage biomarkers for knee OA beyond the radiologist
Sudhakar Tummala, Erik B. Dam
Author Affiliations +
Abstract
Fully automatic imaging biomarkers may allow quantification of patho-physiological processes that a radiologist would not be able to assess reliably. This can introduce new insight but is problematic to validate due to lack of meaningful ground truth expert measurements. Rather than quantification accuracy, such novel markers must therefore be validated against clinically meaningful end-goals such as the ability to allow correct diagnosis. We present a method for automatic cartilage surface smoothness quantification in the knee joint. The quantification is based on a curvature flow method used on tibial and femoral cartilage compartments resulting from an automatic segmentation scheme. These smoothness estimates are validated for their ability to diagnose osteoarthritis and compared to smoothness estimates based on manual expert segmentations and to conventional cartilage volume quantification. We demonstrate that the fully automatic markers eliminate the time required for radiologist annotations, and in addition provide a diagnostic marker superior to the evaluated semi-manual markers.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sudhakar Tummala and Erik B. Dam "Surface smoothness: cartilage biomarkers for knee OA beyond the radiologist", Proc. SPIE 7623, Medical Imaging 2010: Image Processing, 762323 (12 March 2010); https://doi.org/10.1117/12.844115
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Cited by 3 scholarly publications.
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KEYWORDS
Cartilage

Diagnostics

Magnetic resonance imaging

Statistical analysis

Bone

Image segmentation

Radiography

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