Automated method of fracture detection in CT brain images

Author

Zaki, W. Mimi Diyana W ; Fauzi, M. Faizal Ahmad ; Besar, Rosli

Author_Institution

Dept. of Electr., Electron. & Syst., Univ. Kebangsaan Malaysia, Bangi, Malaysia

Volume

1

fYear

2008

fDate

17-19 Nov. 2008

Firstpage

1156

Lastpage

1160

Abstract

This paper presents a novel approach to automatically detect the fracture of skull in CT images. The approach consists of 5 steps: 1) skull segmentation, 2) skull extraction, 3) edge detection, 4) noise removal and, 5) image classification. Experiments show that the recognition rate is 99% for 100 images that are randomly chosen from a medical image database contributed by Hospital Putrajaya, Malaysia. This approach is simple and fast, but yet gives reliable results and high recognition rate. Due to this fact, it can provide a very strong basis of content-based medical image retrieval for medical training or diagnosis.

Keywords

brain; computerised tomography; content-based retrieval; edge detection; feature extraction; image classification; image denoising; image retrieval; image segmentation; medical image processing; CT brain images; computerised tomography; content-based medical image retrieval; edge detection; fracture detection; image classification; medical diagnosis; medical image database; medical training; noise removal; skull extraction; skull segmentation; Biomedical imaging; Brain; Computed tomography; Image classification; Image databases; Image edge detection; Image recognition; Image segmentation; Medical diagnostic imaging; Skull;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent System and Knowledge Engineering, 2008. ISKE 2008. 3rd International Conference on

Conference_Location

Xiamen

Print_ISBN

978-1-4244-2196-1

Electronic_ISBN

978-1-4244-2197-8

Type

conf

DOI

10.1109/ISKE.2008.4731105

Filename

4731105