Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/425944
Title: | Automated Detection And Identification Of White Blood Cell And The Diagnosis Of Its Disorders Using Blood Micrograph |
Researcher: | Roy, Reena M |
Guide(s): | P M, Ameer |
Keywords: | Engineering and Technology Engineering Engineering Electrical and Electronic Electronics and Communication |
University: | National Institute of Technology Calicut |
Completed Date: | 2022 |
Abstract: | Medical imaging has become an essential tool for visualization and interpretation newlinein biology and medicine over the last decade. In haematology, a branch newlineof medicine concerned with the study of blood and hematopoietic tissue illnesses, newlinemedical image processing holds a prominent position. For pathological newlinestudies, the number of erythrocytes, leukocytes, platelets, and other blood newlinecells is critical for detecting anaemia, malaria, leukaemia, lymphoma, and newlineother infectious diseases. Leukocyte count is crucial in determining the body s newlineimmunity among these blood cell parameters. It is essential to know the types newlineand numbers of leukocytes to diagnose blood type diseases. newlineThe visual examination of a blood smear using a microscope is an essential newlinestep in blood cancer detection and its classification. The analysis of white newlineblood cells allows the detection of lymphoma and leukaemia that, if untreated, newlineare fatal. It is most challenging to determine the white blood cells (WBCs) newlinefrom a blood smear. Currently, skilled operators perform morphological newlineanalysis of blood cells manually. As a result, the method is time-consuming, newlineand errors frequently occur, necessitating the assistance of experts. Hence, newlinean automated blood cell recognition system is critical for diagnosing diseases newlineearly and classifying disease kinds for optimal treatment. newlineLymphoma and leukaemia grow more slowly than other cancers and are newlineeasier to cure if found early. Lymphoma is caused by the uncontrolled growth of newlinewhite blood cells called lymphocytes, whereas leukaemia is because white cell newlinecount increases with immature blast cells (lymphoid or myeloid). Automatic newlinerecognition and classification of leukocytes help medical practitioners to newlinediagnose these disorders by analyzing their percentages. newline |
Pagination: | |
URI: | http://hdl.handle.net/10603/425944 |
Appears in Departments: | Department of Electronics and Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 232.33 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 1.02 MB | Adobe PDF | View/Open | |
03_content.pdf | 110.78 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 97.76 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 1.34 MB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 98.8 kB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 6.74 MB | Adobe PDF | View/Open | |
08_ chapter 4.pdf | 1.54 MB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 1.68 MB | Adobe PDF | View/Open | |
10_chapter 6.pdf | 1.07 MB | Adobe PDF | View/Open | |
11_annexures.pdf | 160.7 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 237.7 kB | Adobe PDF | View/Open |
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