IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

HE Stain Image Segmentation Using an Innovative Type-2 Fuzzy Set-Based Approach

HE Stain Image Segmentation Using an Innovative Type-2 Fuzzy Set-Based Approach
View Sample PDF
Author(s): Dibya Jyoti Bora (Kaziranga University, India)
Copyright: 2019
Pages: 24
Source title: Histopathological Image Analysis in Medical Decision Making
Source Author(s)/Editor(s): Nilanjan Dey (Techno India College of Technology, India), Amira S. Ashour (Tanta University, Egypt), Harihar Kalia (Seemantha Engineering College, India), R.T. Goswami (Techno India College of Technology, India) and Himansu Das (KIIT University, India)
DOI: 10.4018/978-1-5225-6316-7.ch012

Purchase

View HE Stain Image Segmentation Using an Innovative Type-2 Fuzzy Set-Based Approach on the publisher's website for pricing and purchasing information.

Abstract

HE stain images are widely used in medical diagnosis and often considered a gold standard for histology and pathology laboratories. A proper analysis is needed to have a critical decision about the status of the diagnosis of the concerned patient. Segmentation is always considered as an advanced stage of image analysis where objects of similar properties are put in one segment. But segmentation of HE stain images is not an easy task as these images involve a high level of fuzziness with them mainly along the boundary edges. So, traditional techniques like hard clustering techniques are not suitable for segmenting these images. So, a new approach is proposed in this chapter to deal with this problem. The proposed approach is based on type-2 fuzzy set and is new. The experimental results prove the superiority of the proposed technique.

Related Content

Amy Moy. © 2022. 19 pages.
Kristen L. Kerber. © 2022. 11 pages.
Kristen L. Kerber. © 2022. 12 pages.
Gayathri Srinivasan. © 2022. 23 pages.
Jacky K. W. Kong. © 2022. 19 pages.
Iason Mantagos. © 2022. 11 pages.
M. H. Esther Han. © 2022. 29 pages.
Body Bottom