Sofian, H. and Muhammad, S. and Ming, J. T. C. and Noor, N. M. (2016) Lumen coronary artery border detection using texture and Chi-square classification. In: 2015 International Conference on Image and Vision Computing New Zealand, IVCNZ 2015, 23 November 2015 through 24 November 2015, New Zealand.
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Abstract
In this paper, we present the lumen coronary artery border detection using intravascular ultrasound (IVUS) images. The approach make used of texture analysis based on Binary Robust Independent Elementary Features (BRIEF) and Chi-square classification. This proposed method can detect the boundary and calculate the area within the lumen coronary artery border. This method was tested on thirty samples of IVUS images which were obtained from Computer Vision Centre, Bellaterra, Dept. Matemàtica Aplicada i Anàlisi, Universitat de Barcelona, Barcelona. The Bland Altman plot is used to show the variation between the proposed automatic segmentation method and ground truth when three different threshold were used. The segmentation performance of the proposed method is measured using Jaccard Index (JI), Hausdorff Distance (HD), Area Overlap Error (AOE), Percentage Area Difference (PAD) and Dice Similarity Index (DI). In this study, the results show that the border detection is better when threshold TH5 is used.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Uncontrolled Keywords: | Binary Robust Independent Elementary Features, Coronary Artery Disease, Intravascular Ultrasound, Lumen Boundary, Texture Analysis |
| Subjects: | T Technology > T Technology (General) |
| Divisions: | Razak School of Engineering and Advanced Technology |
| ID Code: | 72952 |
| Deposited By: | Muhammad Atiff Mahussain |
| Deposited On: | 27 Nov 2017 09:02 |
| Last Modified: | 27 Nov 2017 09:02 |
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