A fuzzy based classifier for diagnosis of acute lymphoblastic leukemia using blood smear image processing

2017 ◽  
Author(s):  
M. A. Khosrosereshki ◽  
M. B. Menhaj
Keyword(s):  
Image Processing ◽  
Acute Lymphoblastic Leukemia ◽  
Blood Smear ◽  
Lymphoblastic Leukemia ◽  
Blood Smear Image

A CLINICOPATHOLOGICAL STUDY OF ACUTE AND CHRONIC LEUKEMIA IN A TERTIARY CARE HOSPITAL

2021 ◽  
pp. 72-74
Author(s):  
Sarat Das ◽  
Prasanta Kr. Baruah ◽  
Sandeep Khakhlari ◽  
Gautam Boro
Keyword(s):  
Acute Myeloid Leukemia ◽  
Acute Lymphoblastic Leukemia ◽  
Peripheral Blood ◽  
Myeloid Leukemia ◽  
Blood Smear ◽  
Lymphoblastic Leukemia ◽  
Peripheral Blood Smear ◽  
Care Hospital ◽  
Cytochemical Study ◽  
Acute Myeloid

Introduction: Leukemias are neoplastic proliferations of haematopoietic stem cells and form a major proportion of haematopoietic neoplasms that are diagnosed worldwide. Typing of leukemia is essential for effective therapy because prognosis and survival rate are different for each type and sub-type Aims: this study was carried out to determine the frequency of acute and chronic leukemias and to evaluate their clinicopathological features. Methods: It was a hospital based cross sectional study of 60 patients carried out in the department of Pathology, JMCH, Assam over a period of one year between February 2018 and January 2019. Diagnosis was based on peripheral blood count, peripheral blood smear and bone marrow examination (as on when available marrow sample) for morphology along with cytochemical study whenever possible. Results: In the present study, commonest leukemia was Acute myeloid leukemia (AML, 50%) followed by Acute lymphoblastic leukemia (ALL 26.6%), chronic myeloid leukemia (CML, 16.7%) and chronic lymphocytic leukemia (CLL, 6.7%). Out of total 60 cases, 36 were male and 24 were female with Male:Female ratio of 1.5:1. Acute lymphoblastic leukemia was the most common type of leukemia in the children and adolescents. Acute Myeloid leukemia was more prevalent in adults. Peripheral blood smear and bone Conclusion: marrow aspiration study still remains the important tool along with cytochemistry, immunophenotyping and cytogenetic study in the diagnosis and management of leukemia.

scholarly journals IDENTIFICATION OF MEGALOBLASTIC ANEMIA CELLS THROUGH THE USE OF IMAGE PROCESSING TECHNIQUES

2018 ◽  
Vol 4 (3) ◽  
pp. 1-5 ◽  
Author(s):  
Asaad Babker ◽  
Vyacheslav Lyashenko
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Blood Smear ◽  
Color Image ◽  
Megaloblastic Anemia ◽  
Cell Structure ◽  
Color Space ◽  
Image Processing Techniques ◽  
Processing Techniques ◽  
Blood Smear Image

Objective: Our aim is to show the possibility of using different image processing techniques for blood smear analysis. Also our aim is to determine the sequence of image processing techniques to identify megaloblastic anemia cells. Methods: We consider blood smear image. We use a variety of image processing techniques to identify megaloblastic anemia cells. Among these methods, we distinguish the modification of the color space and the use of wavelets. Results: We developed a sequence of image processing techniques for blood smear image analysis and megaloblastic anemia cells identification. As a characteristic feature for megaloblastic anemia cells identification, we consider neutrophil image structure. We also use the morphological methods of image analysis in order to reveal the nuclear lobes in neutrophil structure. Conclusion: We can identify the megaloblastic anemia cells. To do this, we use the following sequence of blood smear image processing: color image modification, change of the image contrast, use of wavelets and morphological analysis of the cell structure. 

scholarly journals Acute Lymphoblastic Leukemia Presenting as Fanconi Syndrome

2018 ◽  
Vol 11 (1) ◽  
pp. 63-67
Author(s):  
Tatsunori Yoshida ◽  
Hiroshi Tsujimoto ◽  
Takayuki Ichikawa ◽  
Shinji Kounami ◽  
Hiroyuki Suzuki
Keyword(s):  
Acute Lymphoblastic Leukemia ◽  
Renal Tubular Acidosis ◽  
Fanconi Syndrome ◽  
Blood Smear ◽  
Lymphoblastic Leukemia ◽  
Peripheral Blood Smear ◽  
Leukemic Cells ◽  
Laboratory Examinations ◽  
Renal Tubular ◽  
Electrolyte Abnormalities

Acute lymphoblastic leukemia (ALL) presenting as Fanconi syndrome (FS) is extremely rare. Here, we report a case of ALL presenting as bilateral nephromegaly following FS. A 2-year-old girl was unexpectedly diagnosed with bilateral nephromegaly. After 2 weeks, she developed general fatigue, thirst, and polyuria. Laboratory examinations revealed renal tubular acidosis, hypokalemia, hypophosphatemia, and aminoaciduria, and FS was diagnosed. Replacement of bicarbonate and potassium did not improve her condition. Two weeks after the onset of FS, leukemic cells appeared on a peripheral blood smear, and the patient was diagnosed with precursor B-cell ALL presenting as nephromegaly and FS. Chemotherapy brought about a prompt resolution of acidosis and electrolyte abnormalities, without renal dysfunction. The patient remains well 4 years after the onset of the disease. Although extremely rare, FS should be recognized as one of the emerging renal complications of ALL.

scholarly journals Segmentation of White Blood Cells and Lymphoblast Cells Using Moving K-Means

2018 ◽  
Vol 8 (2) ◽  
pp. 211
Author(s):  
Ika Candradewi ◽  
Reno Ghaffur Bagasjvara
Keyword(s):  
Image Processing ◽  
Acute Lymphoblastic Leukemia ◽  
Digital Image Processing ◽  
Digital Image ◽  
Blood Cells ◽  
Lymphoblastic Leukemia ◽  
White Blood Cells ◽  
Image Processing Technique ◽  
Cell Segmentation ◽  
Lymphoblast Cells

One of the diagnosis procedures for acute lymphoblastic leukemia is screening for blood cells by expert operator using microscope. This process is relatively long and will slow healing process of this disease which need fast treatment. Another way to screen this disease is by using digital image processing technique in microscopic image of blood smears to detect lymphoblast cells and types of white blood cells. One of essential step in digital image processing is segmentation because this process influences the subsequent process of detecting and classifying Acute Lymphoblastic Leukemia disease. This research performed segmentation of white blood cells using moving k-means algorithm. Some process are done to remove noise such as red blood cells and reduce detection errors such as white blood cells and/or lymphoblastic cell  that’s appear overlap. Postprocessing are performed to improve segmentation quality and to separate connected white blood cell. The dataset in this study has been validated with expert clinical pathologists from Sardjito Regional General Hospital, Yogyakarta, Indonesia. This research produces systems performance with results in sensitivity of 85.6%, precision 82.3%, Fscore of 83,9% and accuracy of 72.3%. Based on the results of the testing process with a much larger number of datasets on the side of the variations level of cell segmentation difficulties both in terms of illumination and overlapping cell, the method proposed in this study was able to detect or segment overlapping white blood cells better.

Sign in / Sign up

Export Citation Format

Share Document