Identification and Segmentation of Liver Tumour Cells Using HPBSB Model

  • V. Suresh kumar, M. Rajesh Khanna, P.Vijayanand
Keywords: Liver tumour, Probability model, feature extraction, Gabor filtration

Abstract

Image processing is most important and basic part in several fields of biomedical research, for example, tumour identification, consequently deciding the heart chamber volume, screening lung checks for potential ailments. Various systems for identifying the location of liver tumour include different processes such as image acquisition, segmentation, classification using neural network and optimization, and identification of tumour type. This paper presents another way to deal with identification and segmentation of liver tumours. The identification and segmentation of tumours in liver can be formulized as identification by utilizing Hybrid Probability Based Straightened Bound Segmentation model. The fundamental target of the proposed strategy is to decisively distinguish the nearness of tumour cells in liver images as an early sign of dangerous cells that may cause to the end of patients.

Published
2021-09-10
How to Cite
P.Vijayanand, V. S. kumar, M. R. K. (2021). Identification and Segmentation of Liver Tumour Cells Using HPBSB Model. Design Engineering, 7260-7270. Retrieved from http://thedesignengineering.com/index.php/DE/article/view/4213
Section
Articles