The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON SYSTEMS
Transactions ID Number: 52-608
Full Name: Hum Yan Chai
Position: Ph.D. Candidate
Age: ON
Sex: Male
Address: 26,jalan pulai 12 ,81300 , skudai
Country: MALAYSIA
Tel: 016-4377906
Tel prefix:
Fax:
E-mail address: ychum2@live.utm.my
Other E-mails: yanchai33@hotmail.com
Title of the Paper: Gray-Level Co-occurrence Matrix Bone Fracture Detection
Authors as they appear in the Paper: Hum Yan Chai ,Lai Khin Wee,Tan Tian Swee ,Sheikh Hussain
Email addresses of all the authors: ychum2@live.utm.my, kwlai2@live.utm.my, tantswee@utm.my,hussain@fkbsk.utm.my
Number of paper pages: 10
Abstract: Fractures of bone are a common affliction in orthopedic wards at any given time. Trained radiologists generally identify abnormal pathologies including fractures with a relatively high level of accuracy. However studies examining reader accuracy have shown that in some cases the miss rate can be as high when reading x-rays containing multiple abnormalities. Accurate diagnosis of fractures is vital to the effective management of patient injuries. As a result, detection of long-bone fractures is an important orthopedics and radiologic problem, and it is proposed that a novel computer aided detection system could help lowering the miss rate. This paper examines the development of such a system, for the detection of long-bone fractures. This project fully employed MATLAB 7.8.0 (.r2009a) as the programming tool for loading image, image processing and user interface development. Results obtained demonstrate the performance of the femur‟s long bone fracture detectio!
n system with some limitations
Keywords: Texture analysis,Bone fracture, Classification, Gray-level co-occurrence matrix, Image processing
EXTENSION of the file: .pdf
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Organizer of the Session:
How Did you learn about congress: Image Processing,Bone fracture detection , Fracture detection Classifier,Gray-level co-occurence Matrix
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