An Image Processing Application for Diagnosing Acute Lymphoblastic Leukemia (ALL)

Abstract

Leukemia, simply called “Blood cancer” is a fatal disease where the white blood cells (WBC) increases in bone marrow and peripheral blood. Acute lymphoblastic leukemia (ALL) is one of the most common types of leukemia aroused by accumulation and overproduction of immature and cancerous cells known as lymphoblasts. Presently, the diagnosis of ALL includes performing a full blood count, blood picture, bone marrow biopsy, cytochemical stain, immunophenotyping and cytogenetics. These techniques are highly tedious, costly, requires expertise of hematologists and available only in few hospitals. Therefore, as an alternative, use of image processing to diagnose ALL would become an effective solution. Although, several research groups have employed image processing to identify ALL, recognition and splitting of overlapping red blood cells (RBC) with WBC has yet been a challenging issue. This paper is about an application which includes an image processing algorithm to diagnose ALL while attempting to solve the above mentioned issue of overlapping cells. The algorithm is also extended to detect the quality devastation in blood films in terms of storing them for prolonged period. The inputs for this application are microscopic peripheral blood images of ALL patients obtained from Department of Pathology Clinic at Faculty of Medicine, University of Colombo. Then, image processing techniques; image enhancement, segmentation, feature extraction and classification are performed. For the detection and diagnosis of leukemia, segmentation using morphological operations in OpenCV Python and classification using KNearest Neighbour and Support vector machine implementations has been proposed in this research. It is observed that the proposed algorithm has led to a high accuracy in diagnosing ALL. The system also includes a PHP based web application that serves hematologists, doctors and patients to log in to their specific user accounts and make records, insert details and view diagnosing reports.