Analysis of Parameters' Effects in Semi-Automated Knee Cartilage Segmentation Model

dc.contributor.author	Gan, Hong-Seng
dc.contributor.author	Ahmad Helmy Abdul Karim
dc.contributor.author	Khairil Amir Sayuti
dc.contributor.author	Tan, Tian-Swee
dc.contributor.author	Mohammed Rafiq Abdul Kadir
dc.contributor.author	UniKL BMI
dc.date.accessioned	2016-09-23T02:07:38Z
dc.date.available	2016-09-23T02:07:38Z
dc.date.issued	2016-09-23
dc.identifier.uri	http://ir.unikl.edu.my/jspui/handle/123456789/14392
dc.description	UniKL BMI	en_US
dc.description.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.	en_US
dc.language.iso	en	en_US
dc.title	Analysis of Parameters' Effects in Semi-Automated Knee Cartilage Segmentation Model	en_US
dc.type	Working Paper	en_US
dc.conference.name	International Conference on Mathematics Engineering & Industrial Applications	en_US
dc.conference.year	2016	en_US