NDLI: Improved image segmentation algorithms for detecting types of acute lymphatic leukaemia

Content Provider	IET Digital Library
Author	Tahhan, F. E. Al Sakr, Ali A. Aladle, Doaa A. Fares, M. E.
Abstract	A modified digital image processing technique is presented to accurately investigate the types of the acute lymphatic leukaemia (ALL). In this technique, three complementary steps are performed. In the first one, a colour segmentation procedure is used to obtain images including only the white blood cell. In the second step, the histogram equalisation and linear contrast stretching procedures are utilised to obtain images for the nucleus. In the third step, images for the cytoplasm only may be reconstructed from which the vacuoles may be detected. For accurate detection for ALL types, significant and discriminative parameters are introduced such as geometric shape of nucleus membrane, equivalent sizes for the nucleus and cytoplasm and their ratio when the shapes of nucleuses are regular or irregular. This method is applied to a blood smear images for real cases of ALL. To validate the present technique, a comparison is made between present results with their counterparts obtained by expert (manual) technique. Another assessment is performed by comparing the average accuracy of the present technique and the average accuracy of different image processing techniques in the literature. The assessment confirms the high efficiency of the present technique in detecting all types of ALL.
Starting Page	2595
Ending Page	2603
Page Count	9
ISSN	17519659
Volume Number	13
e-ISSN	17519667
Issue Number	Issue 13, Nov (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/13/13
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2018.6515
Journal	IET Image Processing
Publisher Date	2019-09-04
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Acute Lymphatic Leukaemia ALL Types Biology And Medical Computing Biomedical Measurement And Imaging Blood Blood Smear Image Cellular Biophysics Colour Segmentation Procedure Complementary Steps Computer Vision And Image Processing Technique Different Image Discriminative Parameter Expert Technique Geometric Shape Health Physics Histogram Equalisation Image Colour Analysis Image Enhancement Image Processing Image Segmentation Improved Image Segmentation Algorithm Linear Contrast Medical And Biomedical Uses of Field Medical Image Processing Modified Digital Image Processing Technique Nucleus Cytoplasm Nucleus Membrane Optical, Image And Video Signal Processing Patient Diagnostic Method And Instrumentation Radiations Radioactivity Significant Parameter White Blood Cell
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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