Share Email Print

Proceedings Paper

Segmentation of knee cartilage by using a hierarchical active shape model based on multi-resolution transforms in magnetic resonance images
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Knee osteoarthritis (OA) is characterized by the morphological degeneration of cartilage. Efficient segmentation of cartilage is important for cartilage damage diagnosis and to support therapeutic responses. We present a method for knee cartilage segmentation in magnetic resonance images (MRI). Our method incorporates the Hermite Transform to obtain a hierarchical decomposition of contours which describe knee cartilage shapes. Then, we compute a statistical model of the contour of interest from a set of training images. Thereby, our Hierarchical Active Shape Model (HASM) captures a large range of shape variability even from a small group of training samples, improving segmentation accuracy. The method was trained with a training set of 16- MRI of knee and tested with leave-one-out method.

Paper Details

Date Published: 19 November 2013
PDF: 8 pages
Proc. SPIE 8922, IX International Seminar on Medical Information Processing and Analysis, 892214 (19 November 2013); doi: 10.1117/12.2035534
Show Author Affiliations
Madeleine León, Univ. Nacional Autónoma de México (Mexico)
Boris Escalante-Ramirez, Univ. Nacional Autónoma de México (Mexico)

Published in SPIE Proceedings Vol. 8922:
IX International Seminar on Medical Information Processing and Analysis
Jorge Brieva; Boris Escalante-Ramírez, Editor(s)

© SPIE. Terms of Use
Back to Top