The Detection and Classification of blast cell in Leukaemia Acute Promyelocytic Leukaemia ( AML M3) blood using Simulated Annealing and Neural Network
Dublin Core
Title
The Detection and Classification of blast cell in Leukaemia Acute Promyelocytic Leukaemia ( AML M3) blood using Simulated Annealing and Neural Network
Subject
Leukaemia
Description
This paper presents a method for the detection and classification of blast cells in M3 with others sub-types using simulated annealing and neural networks. In this paper, we increased our test result from 10 images to 20 images. We performed Hill Climbing, Simulated Annealing and Genetic Algorithms for detecting the blast cells. As a result, simulated annealing is the “best” heuristic search for detecting the leukaemia cells. From the detection, we performed features extraction on the blast cells and we classifying based on M3 and other sub-types using neural networks. We received convincing result which has targeting around 97% in classifying of M3 with other sub-types. Our results are based on real world image data from a Haematology Department.
Creator
Waidah Ismail, Rosline Hassan, Annette Payne, Stephen Swift
Source
Faculty Science and Technology
Publisher
Universiti Sains Islam Malaysia
Contributor
Bhg Koleksi Khas dan Keusahawanan
Format
Paper
Language
English
Type
Article
Files
Collection
Citation
Waidah Ismail, Rosline Hassan, Annette Payne, Stephen Swift, “ The Detection and Classification of blast cell in Leukaemia Acute Promyelocytic Leukaemia ( AML M3) blood using Simulated Annealing and Neural Network,” Digital Kelantan Collection, accessed March 30, 2023, http://digitalkelantancollection.umk.edu.my/koleksikelantan/items/show/458.