%0 Journal Article %1 noauthororeditor %A Manimaran, Azarudeen Shariff | Md Hasan Raja | Mohamed Faseeh | S. %D 2023 %J CENTRAL ASIAN JOURNAL OF THEORETICAL AND APPLIED SCIENCE %K ALL, AML, Automated Blood CLL, CML Cancer Cell, Cells Diagnosis, Microscopy, %N 7 %P 19-35 %T Automated Blood Cancer Diagnosis with Microscopy and Cell Counting of ALL, AML, CLL, and CML Cells %U https://cajotas.centralasianstudies.org/index.php/CAJOTAS/article/view/1238/1298 %V 4 %X White blood cell (WBC) cancer, often known as leukaemia, can cause irreparable harm to the body's blood and bone marrow. If not caught early enough, it can be fatal. Manual diagnosis of malignant neoplastic disease cells is typically performed using complete blood count (CBC) or morphological image analysis. These approaches are labor-intensive and can result in less-than-perfect mounting. In this research, we propose an automatic method for the analysis of microscopic blood images for the diagnosis of leukemias such as acute lymphocytic leukaemia (ALL), acute myeloid leukaemia (AML), chronic lymphocytic leukaemia (CLL), and chronic myeloid leukaemia (CML). White blood cells, red blood cells, and platelets are initially separated from the image using this method. Lymphocytes are then isolated from the rest of the white blood cells. Next, an SVM classifier is fed information about the lymphocytes' shape and colour to determine if they are conventional or blast cells. After that, the white blood cell count is taken to ensure a proper diagnosis. This automated approach for the detection of malignant neoplasms was superior to traditional methods of diagnosis in terms of convenience, speed, and accuracy.

@article{noauthororeditor, abstract = {White blood cell (WBC) cancer, often known as leukaemia, can cause irreparable harm to the body's blood and bone marrow. If not caught early enough, it can be fatal. Manual diagnosis of malignant neoplastic disease cells is typically performed using complete blood count (CBC) or morphological image analysis. These approaches are labor-intensive and can result in less-than-perfect mounting. In this research, we propose an automatic method for the analysis of microscopic blood images for the diagnosis of leukemias such as acute lymphocytic leukaemia (ALL), acute myeloid leukaemia (AML), chronic lymphocytic leukaemia (CLL), and chronic myeloid leukaemia (CML). White blood cells, red blood cells, and platelets are initially separated from the image using this method. Lymphocytes are then isolated from the rest of the white blood cells. Next, an SVM classifier is fed information about the lymphocytes' shape and colour to determine if they are conventional or blast cells. After that, the white blood cell count is taken to ensure a proper diagnosis. This automated approach for the detection of malignant neoplasms was superior to traditional methods of diagnosis in terms of convenience, speed, and accuracy.}, added-at = {2024-02-23T07:18:16.000+0100}, author = {Manimaran, Azarudeen Shariff | Md Hasan Raja | Mohamed Faseeh | S.}, biburl = {https://www.bibsonomy.org/bibtex/2a52d88e5b0cad664fb08719df89d734b/centralasian_20}, interhash = {ca336b9c43ce414ecf4c9ee4277d4d47}, intrahash = {a52d88e5b0cad664fb08719df89d734b}, issn = {2660-454X}, journal = {CENTRAL ASIAN JOURNAL OF THEORETICAL AND APPLIED SCIENCE}, keywords = {ALL, AML, Automated Blood CLL, CML Cancer Cell, Cells Diagnosis, Microscopy,}, language = {english}, month = {July}, number = 7, pages = {19-35}, timestamp = {2024-02-23T07:18:16.000+0100}, title = {Automated Blood Cancer Diagnosis with Microscopy and Cell Counting of ALL, AML, CLL, and CML Cells}, url = {https://cajotas.centralasianstudies.org/index.php/CAJOTAS/article/view/1238/1298}, volume = 4, year = 2023 }