A Survey on Automated Leukemia Detection and Classification: Exploring Image Processing and Gene Expression Analysis Approaches
Priyush Panwar, Dimple Mehta · International Journal of Computer Applications · 2023
Leukemia is a haematological disorder which affects blood and bone marrow.Automated leukemia detection is significant for facilitating timely diagnoses and increasing the chances of successful treatment outcomes.Further, the classification of leukemia is crucial because each type demands a distinct treatment strategy.Deep learning and machine learning techniques are being used by computer aided diagnosis systems for their high precision in identifying leukemia from microscopic blood smear images using image processing techniques and gene microarray data using gene expression analysis techniques.However, automation of this task using image processing techniques is challenging due to the uneven structure and overlapping of cells.The large number of genes in microarray data makes the classification challenging, which is accomplished by applying a variety of feature selection techniques.In this study, recent developments in automated leukemia detection and classification employing image processing and gene expression analysis methods are explored.Furthermore, the paper compares and contrasts various techniques to provide a comprehensive overview that can assist in the continuous refinement of the detection and classification process.