Abstract:

Cancer diagnosis and treatment has a great significance due to the prevalent episodes of the diseases, high death rate and cancer stands in the fifth position which causes death. Among the various cancers, liver cancer stands in the third position. Liver cancer is generally diagnosed by three different test like blood test, image test and biopsy. To make the task of detecting the liver cancer simpler, less time consuming, an effective and efficient approach is adopted for the same. In this analysis, a computer aided diagnostic system for detecting liver cancer is put forward. The proposed detection methodology makes use of MRI, CT and USG scan imagery. K means clustering technique is adopted so as to segment the images in order to capture the region of interest. Later, Haar wavelet transform is considered to compute the threshold values for the of interest. Hence, this analysis, gave an better accuracy, reducing the time complexity and computational complexity of the test.

Description:

Haar wavelet transform, Image processing, K-means clustering, Liver cancer