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  • 47.Cnf-1130
EngiTek Congresses with Published Papers
EngiTek 2020, Irbid
2
Papers Published at EngiTek 2020
All 2 Papers
IDAuthors and TitlePages
51.Cnf-17 Mr. Ameer Mubaslat
Mr. Ahmad Al Haj
Prof. Saud Khashan
Simulation assisted leak detection in pressurized systems using machine learning
1-6
51.Cnf-1062 Dr. Aqeed M. Chyad
Dr. Osama Abudayyeh
Dr. Maha Alkasisbeh
A Nonlinear Regression-Based Machine Learning Model for Predicting Concrete Bridge Deck Condition
7-11
47.Cnf-1130 Paper View Page
Title Automatic Detection of Acute Lymphoblastic Leukemia Using Machine Learning
Authors Ms. Lamis Bany Issa, Jordan University of Science and Technology, Irbid, Jordan
Dr. Areen Al-Bashir, Jordan University of Science and Technology, Irbid, Jordan
Abstract The identification of acute leukaemia blast cells in coloured microscopic images is a challenging task. Usually it is performed by visual assessment for microscopic images of blood samples. However, considering the quick advances in utilizing different image processing techniques; rapid and more accurate assessment can be achieved. Therefore, this paper proposed an enhanced automatic method to detect Acute Lymphoblastic Leukemia (ALL) utilizing microscopic blood sample images. Our proposed methodology includes; Colour-based segmentation using K-Means clustering technique together with morphological operations and feature extraction algorithms and finally cell classification. The proposed method was tested on blood microscopic images from ALL-IDB1 database, University of Milano, Italy. ALL_IDB1 comprises of 108 blood cells images (healthy and leukaemia) in which the lymphocytes are lapelled by expert oncologists. The accuracy achieved was 96.3%. this relatively high accuracy suggests that the Colour-based method for segmentation was more efficient and acceptable compared to the traditional thresholding methods and the methods that not considered the overlapped cells.
Track BME: Biomedical Engineering
Conference 1st International Conference on Electrical Engineering and Technologies (ElectriTek 2020)
Congress International Congress on Engineering Technologies (EngiTek 2020), 16-18 June 2020 (Remotely), Irbid, Jordan
Pages --1
Topics Biomedical Signal Processing
Biomedical Imaging Systems
ISSN 2227-331X
DOI
BibTeX @inproceedings{1130EngiTek2020,
title={Automatic Detection of Acute Lymphoblastic Leukemia Using Machine Learning},
author={Lamis Bany Issa, and Areen Al-Bashir},
booktitle={International Congress on Engineering Technologies (EngiTek 2020)},
year={2020},
pages={--1},
doi={}},
organization={Mosharaka for Research and Studies} }
Paper Views 505 Paper Views Rank 133/525
Paper Downloads 171 Paper Downloads Rank 144/525
EngiTek 2020 Visits: 19102||ElectriTek 2020 Visits: 10439||BME Track Visits: 1764