Tissue Processing, Staining And Image Processing Of Pathological Cancer Images: A Review
U. Rajyalakshmi1, K. Satya Prasad2, S. Koteswara Rao3
1U. Rajyalakshmi, ECE Dept, JNT University Kakinada, Kakinada, India.
2K. Satya Prasad, ECE Dept, JNT University Kakinada, Kakinada, India.
3S. Koteswara Rao, Vignan’s Institute of Information Technology, Vishakapatnam, India.
Manuscript received on January 25, 2014. | Revised Manuscript received on February 15, 2014. | Manuscript published on February 28, 2014. | PP: 10-15 | Volume-3, Issue-3, February 2014. | Retrieval Number: C2520023314/2013©BEIESP
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© 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: Digital image processing enables synthesis of images for characterisation of properties. Image segmentation is the most critical functions in image analysis and processing. Fundamentally segmentation results affect all the subsequent processes of image analysis such as object representation and description, feature measurement, and higher level tasks such as object classification. Cancer, at early stage, detection can be possible only with micro image processing. Processing and staining of Cancer tissues for pathological examination through micro images is a difficult task. The study intends to compare the set of image segmentation and edge detection algorithms that can be employed in the image segmentation process. Review of current methodologies of image segmentation using automated algorithms, which are accurate and require little user interaction, is possible especially for pathological medical images. In this paper we project the study of processing, straining and capturing of the pathological images for processing to detect cancer early.
Keywords: Image processing, Pathological Images, Edge detection, Image segmentation, Tissue processing, staining, cancer.