Effects of Compression Algorithms and Identification of Cancer cell using CT Coronel View Lung Image
1Pandian R, Electronics and Instrumentation, Sathyabama Institute of Science and Technology, India.
2Lalitha Kumari S, Electronics and Instrumentation, Sathyabama Institute of Science and Technology, India.
Manuscript received on July 13, 2021. | Revised Manuscript received on August 05, 2021. | Manuscript published on August 30, 2021. | PP: 103-105 | Volume-8 Issue-6, August 2019. | Retrieval Number: 100.1/ijitee.B5552128218| DOI: 10.35940/ijeat.B5552.088619
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Modern radiology techniques provide crucial medical information for radiologists to diagnose diseases and determine appropriate treatments. Hence dealing with medical image compression needs to compromise on good perceptual quality (i.e. diagnostically lossless) and high compression rate. The objective also includes finding out an optimum algorithm for medical image compression algorithm. The objective is also focused towards the selection of the developed image compression algorithm, which do not change the characterization behavior of the image.
Keywords: CT lung Coronel, Wavelet, Encoding, features, GLCM and Classification.