Authors: G. Malu; Elizabeth Sherly; Sumod Mathew Koshy
Addresses: University of Kerala, Thiruvananthapuram, Kerala 695 581, India ' Indian Institute of Information Technology and Management – Kerala, Technopark, Thiruvananthapuram, Kerala, 695581, India ' Dept. of Imageology, Regional Cancer Centre, Thiruvananthapuram, Kerala, 695011, India
Abstract: Breast cancer is one of the most common cancers found in women around the world. Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) is nowadays used in many suspected cases that may not be visible in a mammogram. This work concentrates on algorithmic development for segmentation of lesions, automating region of interest (ROI), and to delineate the malignancy on DCE-MRI. This has been tested against the intensity time kinetic curve method. The curve pattern and its distribution shows the likelihood of malignancy, which can be automatically coloured based on the assessment. The system helps to compute volume rendering by forming a 3D structure of the lesion area. The proposed system enables doctors to improve the diagnostic accuracy. The development is carried out using graphic processing unit (GPU) based high end parallel computing with NVIDIA CUDA software, which enables to process more than 5000 images of a single patient with better speed and managed memory.
Keywords: dynamic MRI; contrast enhancement; MRI-CAE system; intensity time kinetic graphs; volume rendering; GPU-based CUDA system; breast cancer; magnetic resonance imaging; mammograms; image segmentation; lesions; lesion identification; region of interest; ROI automation.
International Journal of Computer Applications in Technology, 2015 Vol.51 No.1, pp.23 - 30
Published online: 01 Apr 2015 *Full-text access for editors Access for subscribers Purchase this article Comment on this article