Please use this identifier to cite or link to this item:
http://hdl.handle.net/2080/2727
Title: | GLRLM based Feature Extraction for Acute Lymphoblastic Leukemia(ALL) Detection |
Authors: | Mishra, Sonali Majhi, Banshidhar Sa, Pankaj Kumar Siddiqui, Faiza |
Keywords: | Acute Lymphoblastic Leukemia Grey level run length Marker-based watershed segmentation CAD system |
Issue Date: | Jun-2017 |
Publisher: | Springer |
Citation: | 5th International Conference on Advanced Computing, Networking, and Informatics(ICACNI), NIT Goa, India,1-3 June 2017 |
Abstract: | This paper proposes a gray level run length matrix (GLRLM) based feature extraction technique for the detection of Acute Lymphoblas-tic Leukemia (ALL). ALL could be a fatal hematopoietic ailment which might cause death if it's not treated at the early stage. The GLRL matrix is a method for extraction of statistical textural features from the nucleus of the lymphocyte image. The extracted features are then supplied to the Support Vector Machine (SVM) for classi_cation. The experiments are performed on an publicly available dataset ALL-IDB1. The accuracy of the proposed scheme is found to be 96.97% for SVM classifier |
Description: | Copyright for this paper belongs to proceeding publisher |
URI: | http://hdl.handle.net/2080/2727 |
Appears in Collections: | Conference Papers |
Files in This Item:
File | Description | Size | Format | |
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2017_ICACNI_SMishra_GLRLM.pdf | 554 kB | Adobe PDF | View/Open |
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