TY - GEN
T1 - Survey of Leukemia Cancer Cell Detection Using Image Processing
AU - Devi, Tulasi Gayatri
AU - Patil, Nagamma
AU - Rai, Sharada
AU - Philipose, Cheryl Sarah
N1 - Funding Information:
Supported by National Institute of Technology Karnataka.
Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - Cancer is the development of abnormal cells that divide at an abnormal pace, uncontrollably. Cancerous cells have the ability to destroy other normal tissues and can spread throughout the body. Cancer cells can develop in various parts of the body. The paper focuses on leukemia which is a type of blood cancer. Blood cancer usually start in the bone marrow where the blood is produced in the body. The types of blood cancer are: Leukemia, Non-Hodgkin lymphoma, Hodgkin lymphoma, and Multiple myeloma. Leukemia is a type of blood cancer that originates in the bone marrow. Leukemia is seen when the body produces an abnormal amount of white blood cells that hinder the bone marrow from creating red blood cells and platelets. Several detection methods to identify the cancerous cells have been proposed. Identification of the cancer cells through cell image processing is very complex. The use of computer aided image processing allows the images to be viewed in 2D and 3D making it easier to identify the cancerous cells. The cells have to undergo segmentation and classification in order to identify the cancerous tumours. Several papers propose segmentation methods, classification methods and some propose both. The purpose of this survey is to review various papers that use either conventional methods or machine learning methods to detect the cells as cancerous and non-cancerous.
AB - Cancer is the development of abnormal cells that divide at an abnormal pace, uncontrollably. Cancerous cells have the ability to destroy other normal tissues and can spread throughout the body. Cancer cells can develop in various parts of the body. The paper focuses on leukemia which is a type of blood cancer. Blood cancer usually start in the bone marrow where the blood is produced in the body. The types of blood cancer are: Leukemia, Non-Hodgkin lymphoma, Hodgkin lymphoma, and Multiple myeloma. Leukemia is a type of blood cancer that originates in the bone marrow. Leukemia is seen when the body produces an abnormal amount of white blood cells that hinder the bone marrow from creating red blood cells and platelets. Several detection methods to identify the cancerous cells have been proposed. Identification of the cancer cells through cell image processing is very complex. The use of computer aided image processing allows the images to be viewed in 2D and 3D making it easier to identify the cancerous cells. The cells have to undergo segmentation and classification in order to identify the cancerous tumours. Several papers propose segmentation methods, classification methods and some propose both. The purpose of this survey is to review various papers that use either conventional methods or machine learning methods to detect the cells as cancerous and non-cancerous.
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U2 - 10.1007/978-3-031-11346-8_41
DO - 10.1007/978-3-031-11346-8_41
M3 - Conference contribution
AN - SCOPUS:85135005131
SN - 9783031113451
T3 - Communications in Computer and Information Science
SP - 468
EP - 488
BT - Computer Vision and Image Processing - 6th International Conference, CVIP 2021, Revised Selected Papers
A2 - Raman, Balasubramanian
A2 - Murala, Subrahmanyam
A2 - Chowdhury, Ananda
A2 - Dhall, Abhinav
A2 - Goyal, Puneet
PB - Springer Science and Business Media Deutschland GmbH
T2 - 6th International Conference on Computer Vision and Image Processing, CVIP 2021
Y2 - 3 December 2021 through 5 December 2021
ER -
