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Title: Analysis of Parameters' Effects in Semi-Automated Knee Cartilage Segmentation Model
Authors: Gan, Hong-Seng
Ahmad Helmy Abdul Karim
Khairil Amir Sayuti
Tan, Tian-Swee
Mohammed Rafiq Abdul Kadir
Issue Date: 23-Sep-2016
Abstract: Unlike automated segmentation, the accuracy of semi-automated segmentation is affected by pertinent parameters such as observer, type of methods and type of cartilage. In this paper, we investigated the effect of these parameters on segmentation results. based on Dice similarity index obtained from fifteen normal and ten diseased magnetic resonance images, a parameter estimation model was constructed to study the impact of each parameter.
Description: UniKL BMI
Appears in Collections:Conference Papers

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