Research Article | Open Access
Enhancing Segmentation Approaches from Super Pixel Division Algorithm to Hidden Markov Random Fields with Expectation Maximization (HMRF-EM)
Christo Ananth,S. Amutha,K. Niha,
Pages: 2400-2410
Abstract
In surgical planning and cancer treatment, it is crucial to segment and measure a
liver tumor's volume accurately. Because it would involve automation, standardisation, and the incorporation of complete volumetric information, accurate automatic liver tumor segmentation would substantially affect the processes for therapy planning and follow-up reporting. Based on the Hidden Markov random field, Automatic liver tumor detection in CT scans is possible using hidden Markov random fields (HMRF-EM)
Keywords
Hidden Markov Random Field, CT Scan, Adaptive K Means.