Efficient Region of Interest Extraction Methods for Multiple Medical Images
B. P. Santosh Kumar1, K. Venkata Ramanaiah2
1B. P. Santosh Kumar*, Department of Electronics and Communication Engineering, YSR Engineering College of Yogi Vemana University, Proddatur, India.
2Dr. K. Venkata Ramanaiah, Department of Electronics and Communication Engineering, YSR Engineering College of Yogi Vemana University, Proddatur, India.
Manuscript received on October 12, 2019. | Revised Manuscript received on 22 October, 2019. | Manuscript published on November 10, 2019. | PP: 1554-1559 | Volume-9 Issue-1, November 2019. | Retrieval Number: A4526119119/2019©BEIESP | DOI: 10.35940/ijitee.A4526.119119
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Abstract: Medical images do contain important and unimportant spatial regions. Compression methods which are capable of reconstructing the image with high quality are required to compress the medical images. For these images, only a portion of it is useful for diagnosis hence a region based coding techniques are significant for compressing and transmission. Extracting a significant region is of great demand since a slighter mistake may leads to wrong diagnosis. This paper is focused on investigating multiple image processing algorithms for medical images. All the images may not contain the same region of interest, so different approaches are supposed to apply for different images. In this three types of medical images were considered like magnetic resonance (MR) brain images, computer tomography (CT) abdomen images and X-ray lung images. In this paper three automatic region of interest extraction algorithms were proposed for different types of images.
Keywords: Medical Image Compression, Region of Interest, CT, MRI, Abdominal Image Compression
Scope of the Article: Image Processing and Pattern Recognition