Seed point selection for seed-based region growing in segmenting microcalcifications

Author

Malek, A.A. ; Rahman, W.E.Z.W.A. ; Yasiran, S.S. ; Jumaat, A.K. ; Jalil, U.M.A.

Author_Institution

Fac. of Comput. & Math. Sci., Univ. Teknol. MARA Negeri Sembilan Branch, Kuala Pilah, Malaysia

fYear

2012

fDate

10-12 Sept. 2012

Firstpage

1

Lastpage

5

Abstract

Seed-based region growing (SBRG) has been widely used as a segmentation method for medical images. The selection of initial seed point in SBRG is the crucial part before the segmentation process is carried out. Most of the region growing methods identify the seed point manually which involve human interaction and require prior information about the image. In this paper, an automated initial seed point selection for SBRG algorithm is proposed. The proposed method is tested on 50 mammogram images confirmed by a radiologist to consist microcalcifications. The performance is evaluated using Receiving Operator Curve (ROC) based on level of detection. Experimental results show that the method has successfully segmented the microcalcifications with 0.98 accuracy.

Keywords

image segmentation; mammography; medical image processing; SBRG algorithm; detection level; human interaction; mammogram images; medical image segmentation method; receiving operator curve; region growing methods; seed point selection; seed-based region growing; segmenting microcalcifications; Breast; Feature extraction; Image segmentation; Lesions; Morphology; Shape; Ultrasonic imaging; Mammogram; Microcalcifications; Seed-based region growing; segmentation;

fLanguage

English

Publisher

ieee

Conference_Titel

Statistics in Science, Business, and Engineering (ICSSBE), 2012 International Conference on

Conference_Location

Langkawi

Print_ISBN

978-1-4673-1581-4

Type

conf

DOI

10.1109/ICSSBE.2012.6396580

Filename

6396580