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

• Published in: International journal of health sciences pp. 7576 - 7590
• Main Authors: Vajravelu, Ashok, Tamilselvan, K. S., Mahadi, Muhammad, Zaki, Wan Suhaimizan Bin Wan, Suresh, K. S., Iyer, Gowtham G.
• Format: Journal Article
• Language: English
• Published: 01.08.2022
• DOI: 10.53730/ijhs.v6nS6.11392
• ISSN: 2550-6978

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).