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Proceedings Paper

Segmentation of humeral head from axial proton density weighted shoulder MR images
Author(s): Aysun Sezer; Hasan Basri Sezer; Songul Albayrak
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Paper Abstract

The purpose of this study is to determine the effectiveness of segmentation of axial MR proton density (PD) images of bony humeral head. PD sequence images which are included in standard shoulder MRI protocol are used instead of T1 MR images. Bony structures were reported to be successfully segmented in the literature from T1 MR images. T1 MR images give more sharp determination of bone and soft tissue border but cannot address the pathological process which takes place in the bone. In the clinical settings PD images of shoulder are used to investigate soft tissue alterations which can cause shoulder instability and are better in demonstrating edema and the pathology but have a higher noise ratio than other modalities. Moreover the alteration of humeral head intensity in patients and soft tissues in contact with the humeral head which have the very similar intensities with bone makes the humeral head segmentation a challenging problem in PD images. However segmentation of the bony humeral head is required initially to facilitate the segmentation of the soft tissues of shoulder. In this study shoulder MRI of 33 randomly selected patients were included. Speckle reducing anisotropic diffusion (SRAD) method was used to decrease noise and then Active Contour Without Edge (ACWE) and Signed Pressure Force (SPF) models were applied on our data set. Success of these methods is determined by comparing our results with manually segmented images by an expert. Applications of these methods on PD images provide highly successful results for segmentation of bony humeral head. This is the first study to determine bone contours in PD images in literature.

Paper Details

Date Published: 28 January 2015
PDF: 6 pages
Proc. SPIE 9287, 10th International Symposium on Medical Information Processing and Analysis, 928715 (28 January 2015); doi: 10.1117/12.2073494
Show Author Affiliations
Aysun Sezer, Yildiz Technical Univ. (Turkey)
Hasan Basri Sezer, Sisli Hamidiye Etfal Training and Research Hospital (Turkey)
Songul Albayrak, Yildiz Technical Univ. (Turkey)

Published in SPIE Proceedings Vol. 9287:
10th International Symposium on Medical Information Processing and Analysis
Eduardo Romero; Natasha Lepore, Editor(s)

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