Authors: Mahnoor Rasheed; Ishtiaq Ahmad; Sumbal Zahoor; Muhammad Nasir Khan
Addresses: Department of Electrical and Electronic System, The University of Lahore, Lahore, Pakistan ' Department of Electrical Engineering, The University of Lahore, Lahore, Pakistan ' Department of Electrical Engineering, The University of Lahore, Lahore, Pakistan ' Department of Electrical Engineering, The University of Lahore, Lahore, Pakistan
Abstract: Major progress in image processing allows us to make large-scale use of medical imaging data to provide better detection and treatment of several diseases. Cancer is one of them that cause around 1.7 million deaths every year. Advanced and precise detection of cancer can prevent the severe complications. Tongue cancer is relatively rare that takes the consideration of medical field groups in recent time. In this research work, an efficient tongue cancer detection system is proposed that carried out in two phases. Initially, advanced filtering techniques are used to remove the noise content of microscopic images of tissue cultures from the body of the subject to be diagnosed. Image information is enhanced in pre-processing step that squeezes undesirable contortion and enhances some picture highlights for less demanding and faster assessment. In next phase, the image is segmented in a manner that abstracts significant material and characteristics of the image. The detection of the affected part is performed using the Otsu thresholding, k-means clustering and marker controlled watershed segmentation techniques. The performance and limitations of these schemes are compared and discussed. The simulation results show the marker controlled watershed offers best segmentation and detection.
Keywords: tongue cancer detection; k-means clustering; marker controlled watershed segmentation; Otsu thresholding.
International Journal of Biomedical Engineering and Technology, 2020 Vol.34 No.4, pp.391 - 412
Received: 04 Oct 2017
Accepted: 27 Feb 2018
Published online: 05 Jan 2021 *