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Lymphocyte image segmentation using functional link neural architecture for acute leukemia detection

Lymphocyte image segmentation using functional link neural architecture for acute leukemia detection Biomed Eng Lett (2012) 2:100-110 DOI 10.1007/s13534-012-0056-9 ORIGINAL ARTICLE Lymphocyte Image Segmentation Using Functional Link Neural Architecture for Acute Leukemia Detection Subrajeet Mohapatra, Dipti Patra, Sunil Kumar and Sanghamitra Satpathy Received: 11 April 2012 / Revised: 31 May 2012 / Accepted: 5 June 2012 © The Korean Society of Medical & Biological Engineering and Springer 2012 Abstract Keywords Leukocyte segmentation, Lab color model, Purpose Microscopic examination of stained blood slides is Neural networks, Pixel classification, Functional expansion, Tanimoto index an indispensable technique for hematological disease recognition. Diagnosis based on human visual interpretation is often subjected to inter and intra observer variations, slowness, tiredness and operator experience. Accurate and INTRODUCTION authentic diagnosis of hematological neoplasia is essential in the planning of suitable surgery and chemotherapy. This Cellular components of the blood are considered important paper aims at proposing a fast and simple framework for as the blood cells are easily accessible indicators of disturbances lymphocyte image segmentation. in their organs of origin or degradation which are much less Methods Accurate segmentation of lymphocyte is essential accessible for diagnosis. Thus, changes in the erythrocyte, as it facilitates automated leukemia detection in blood leukocytes, and platelets allow important inference to be microscopic http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Biomedical Engineering Letters Springer Journals

Lymphocyte image segmentation using functional link neural architecture for acute leukemia detection

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References (56)

Publisher
Springer Journals
Copyright
Copyright © 2012 by Korean Society of Medical and Biological Engineering and Springer
Subject
Engineering; Biomedicine general; Biomedical Engineering; Biophysics and Biological Physics; Medical and Radiation Physics
ISSN
2093-9868
eISSN
2093-985X
DOI
10.1007/s13534-012-0056-9
Publisher site
See Article on Publisher Site

Abstract

Biomed Eng Lett (2012) 2:100-110 DOI 10.1007/s13534-012-0056-9 ORIGINAL ARTICLE Lymphocyte Image Segmentation Using Functional Link Neural Architecture for Acute Leukemia Detection Subrajeet Mohapatra, Dipti Patra, Sunil Kumar and Sanghamitra Satpathy Received: 11 April 2012 / Revised: 31 May 2012 / Accepted: 5 June 2012 © The Korean Society of Medical & Biological Engineering and Springer 2012 Abstract Keywords Leukocyte segmentation, Lab color model, Purpose Microscopic examination of stained blood slides is Neural networks, Pixel classification, Functional expansion, Tanimoto index an indispensable technique for hematological disease recognition. Diagnosis based on human visual interpretation is often subjected to inter and intra observer variations, slowness, tiredness and operator experience. Accurate and INTRODUCTION authentic diagnosis of hematological neoplasia is essential in the planning of suitable surgery and chemotherapy. This Cellular components of the blood are considered important paper aims at proposing a fast and simple framework for as the blood cells are easily accessible indicators of disturbances lymphocyte image segmentation. in their organs of origin or degradation which are much less Methods Accurate segmentation of lymphocyte is essential accessible for diagnosis. Thus, changes in the erythrocyte, as it facilitates automated leukemia detection in blood leukocytes, and platelets allow important inference to be microscopic

Journal

Biomedical Engineering LettersSpringer Journals

Published: Jul 11, 2012

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