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2019 | OriginalPaper | Chapter

Review on Image Segmentation Techniques Incorporated with Machine Learning in the Scrutinization of Leukemic Microscopic Stained Blood Smear Images

Authors : Duraiswamy Umamaheswari, Shanmugam Geetha

Published in: Proceedings of the International Conference on ISMAC in Computational Vision and Bio-Engineering 2018 (ISMAC-CVB)

Publisher: Springer International Publishing

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Abstract

This paper is a contemplated work of N-different methods that have been employed in the area of revealing and classifying leukocytes and leukoblast cells. Blood cell images obtained through digital microscopes are taken as input to the algorithms reviewed. In bringing out the nucleus and cytoplasm of White Blood Cells (WBCs), the images have been undergone by a variety of image segmentation techniques along with filtering, enhancement, edge detection, feature extraction, classification, and image recognition steps. Apart from image processing, the analysis and categorization of the leukemic images are handled using some other machine learning techniques of computer science discipline. Assessment of accuracy and correctness of the proposals were done by applying texture, color, contour, morphological, geometrical, and statistical features.

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Title: Review on Image Segmentation Techniques Incorporated with Machine Learning in the Scrutinization of Leukemic Microscopic Stained Blood Smear Images
Authors: Duraiswamy Umamaheswari
Shanmugam Geetha
Publisher: Springer International Publishing
Book: Proceedings of the International Conference on ISMAC in Computational Vision and Bio-Engineering 2018 (ISMAC-CVB)
Print ISBN: 978-3-030-00664-8

Electronic ISBN: 978-3-030-00665-5

Copyright Year: 2019
DOI: https://doi.org/10.1007/978-3-030-00665-5_163

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