Publication Type : Conference Paper
Publisher : IEEE
Source : 2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI), IEEE, Tirunelveli, India (2019)
Url : https://ieeexplore.ieee.org/document/8862696
Campus : Amritapuri
School : School of Engineering
Department : Electronics and Communication
Year : 2019
Abstract : Image segmentation plays a vital role in medical image processing. Different pre-processing methods yield different results. The pre-processing methods such as histogram stretching with erosion and dilation, average filter and median filter along with histogram stretching is applied to the four different segmentation algorithms which are Otsu's thresholding, Watershed based segmentation, Canny edge detection and K-mean clustering. These algorithms are used to segment Acute Lymphoblastic Leukemia datasets and the parameters such as precision, accuracy and sensitivity of the results are calculated so as to find a better algorithm which is suitable for segmentation of the leukemic cells.
Cite this Research Publication : T. Bhagya, Anand, K., Kanchana, D. S., and Remya Ajai A. S., “Analysis of Image Segmentation Algorithms for the Effective Detection of Leukemic Cells”, in 2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI), Tirunelveli, India, 2019.