Leukemia detection using digital image processing in MATLAB
Date of Publication
2010
Document Type
Bachelor's Thesis
Degree Name
Bachelor of Science in Electronics and Communications Engineering
College
Gokongwei College of Engineering
Department/Unit
Electronics and Communications Engineering
Thesis Adviser
Miguel O. Gutierrez
Defense Panel Chair
Enrique M. Manzano
Defense Panel Member
Rodrigo S. Jamisola, Jr.
Edwin Sybingco
Abstract/Summary
Leukemia is a form of cancer that affects the normal production of blood cells particularly white blood cells or leukocytes. Early detection of the disease is necessary for proper treatment management. The study presents an algorithm for detection and classification of Leukemia through Digital Image Processing.
An algorithm that uses various digital image processing techniques capable of extracting morphological features and classifying the blood sample as acute or chronic leukemia or negative for leukemia was devised. The algorithm used features such as size, blood count, and the roundness ratio of the nucleus to determine whether the white blood cell is a blast or a mature leukocyte. Blood count was also considered to compare the concentration of leukocytes.
Based on the data gathered, the algorithm was able to achieve 92% accuracy in the detection and classification of Leukemia in 100 blood samples. To get more accurate results and be able to classify specific types of leukemia such as hairy cell leukemia, type of diagnosis such as flow cytometry and immunophenotyping should be explored.
Abstract Format
html
Language
English
Format
Accession Number
TU15534
Shelf Location
Archives, The Learning Commons, 12F, Henry Sy Sr. Hall
Physical Description
124, [28] leaves : ill. (some col) ; 28 cm.
Keywords
Leukemia; Digital image processing
Recommended Citation
Dimayuga, R. A., Ong, G. T., Perez, R. S., Siy, G. O., & Sohrabi Langroudi, S. C. (2010). Leukemia detection using digital image processing in MATLAB. Retrieved from https://animorepository.dlsu.edu.ph/etd_bachelors/14642