Development of 3-stage hybrid computer aided design (3-HCAD) system for multi-modal medical images to identify brain tumor

Ashok Vajravelu; K. S. Tamilselvan; Muhammad Mahadi; Wan Suhaimizan Bin Wan Zaki; K. S. Suresh; Gowtham G. Iyer

doi:10.53730/ijhs.v6nS6.11392

Authors

Ashok Vajravelu Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Malaysia
K. S. Tamilselvan
kstamilselvan@gmail.com
Department of ECE, KPR Institute of Engineering and Technology, Anna University, Coimbatore, India
Muhammad Mahadi Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Malaysia
Wan Suhaimizan Bin Wan Zaki Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Malaysia
K. S. Suresh Head (Technology Extension Division), Centre for Development of Imaging Technology (C-DIT), Thiruvananthapuram, India
Gowtham G. Iyer PhD Scholar (GE210002), Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Malaysia

Keywords:

hybrid computer aided design, magnetic resonance imaging, computed tomography, dual tree complex wavelet transform, nonsubsampled contourlet transform

Abstract

The latest developments in medical imaging and computer-aided solutions for image processing problems attract attention of various researchers to impart their research in the medical imaging field. Designing and developing efficient algorithms to present the medical information effectively have become critical areas of research in this field. A 3-Stage Hybrid Computer Aided Design system is introduced to identify Brain tumor in earlier stages by extracting meaningful information from multimodal medical images. The preferred multi-modality images is Magnetic Resonance Imaging (MRI) and Computed Tomography (CT). The CAD system proposed in this paper can eliminate the dependency on human operators as it is an efficient software-based system. The first stage in this model consists of image pre-processing with Wavelet and Curvelet transforms. The second stage of the CAD system is an image segmentation process, which involves a combination of Wavelet Transform and Watershed Technique. The third stage involves image fusion, where the individually segmented CT and MRI images are fused together to obtain an integrated complementary information from two different images. This is followed by decomposing CT and MRI images using the Dual Tree Complex Wavelet Transform (DTCWT) and Nonsubsampled Contourlet Transform (NSCT).

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