Textural analysis of bio-images for aid in the detection of abnormal blood cells

Bouzid-Daho, Abdellatif; Boughazi, Mohamed; Tanougast, Camel; Medjahed, Oussama Benali

doi:10.1504/ijbet.2017.10007479

Cited by 5 publications

(3 citation statements)

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“…To perform our approach, we consider for study purpose a public supervised image datasets (http://www.hematocell.univ-angers.fr/index.php/banque-images) of blood cells provided from the hematology service of the CHU Hospital, Angers, France. This database gives typical blood microscope images obtained from the microscope inspection of blood slides which provides important qualitative and quantitative information concerning the presence of hematological pathologies (Bouzid-Daho et al, 2017b). Our work will be based on a blood smear images of a subject with CLL.…”

Section: Databasementioning

confidence: 99%

Detection of abnormal blood cells by segmentation and classification

Bouzid-Daho

Boughazi

Petit

2019

IJMEI

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Leukaemia is a cancer of the hematopoietic cells. The detection of abnormal blood cells before cancer degeneration is a medical problem. The aim of our work is to obtain maximum recognition rate of leukaemia. We propose the development of a system based on mathematical morphology and k-means methods capable of segmentation, classification, and detection of the cancerous blood cells. This allows the characterisation and the description the cancerous region, which is an important task in the interpretation and diagnosis of pathologies present in blood. The segmentation was carried out using an efficient and fast algorithmic processing. It turns out that the proposed system shows to better segmentation and classification for tested images. The obtained experimental results are very encouraging which help hematologists for identification of abnormal blood cells.

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Section: Databasementioning

confidence: 99%

Detection of abnormal blood cells by segmentation and classification

Bouzid-Daho

Boughazi

Petit

2019

IJMEI

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“…The type of microscopic medical images is the blood cells [11], which represents pathology [12]. In this case our goal in algorithmic processing is to segment the set of bio-images based on the relevant element color and texture [13][14].…”

Section: B Medical Contextmentioning

confidence: 99%

Segmentation of Abnormal Blood Cells for Biomedical Diagnostic Aid

Bouzid-Daho¹,

Boughazi²

2018

IJIGSP

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The aim of our work is to obtain a maximum rate of recognition of abnormal (cancerous) blood cells. We propose the development of a system based on kmeans methods, after an RGB channel decomposition by applying the algorithm which can segment our microscopic medical images. It turns out that the proposed system shows better segmentation and classification for the identification and detection of leukemia. The experimental results obtained are very encouraging, which helps hematologists to monitor the evolution of cancerous blood cells and make a good diagnosis.

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“…The structuring element is a geometric figure simple to form known or arbitrary which can be a circle, a segment, a square or a triangle. The Form and the dimension of the structuring element noted , allow you to extract specific forms when it is contained in a part of the whole or of its complement (9). By convention, it affects : 1) Value if the point is ignored ; 2) Value if the point is taken into account ; 3) : for the center.…”

Section: Mathematical Morphologymentioning

confidence: 99%

Segmentation of Abnormal Blood Cells to Aid Leukemia Detection

Bouzid-Daho¹,

Boughazi²,

Tanougas³

2016

Acta Healthmedica

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The field of biomedical diagnosis has become very important in the evolution of medicine, and especially for the detection of cancer cells. In this paper, we will develop an algorithmic treatment by segmentation, using elements of mathematical morphology. The aim of our work is to obtain a maximum rate of recognition of leukemia. Our algorithmic diagram can segment, detect, characterize and describe cancerous blood cells (leukemia). This proposal is an important task in the interpretation and diagnosis of pathologies for hematologists. The experimental results applied on our microscopic medical images are encouraging for the identification of abnormal blood cells generally, and the distinction of leukemia especially, which shows the efficiency and rapidity of our algorithmic system.

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Textural analysis of bio-images for aid in the detection of abnormal blood cells

Cited by 5 publications

References 0 publications

Detection of abnormal blood cells by segmentation and classification

Detection of abnormal blood cells by segmentation and classification

Segmentation of Abnormal Blood Cells for Biomedical Diagnostic Aid

Segmentation of Abnormal Blood Cells to Aid Leukemia Detection

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