Image Based Analysis for Bone Marrow Cancer Detection using Soft Computing Techniques: A Review
Keywords:
Leukemia, classification, detection, segmentation, featureAbstract
Bone marrow is a vital component of the human body, as it contains stem cells that form blood cells and immune system cells. Bone marrow cancer is due to hematologic disorders that affect the blood and can affect the bone marrow, white blood cells, platelets, and red blood cells. Every year, many people are diagnosed with bone marrow cancer. Bone marrow cancer can be detected by extracting features of a white blood cell. White blood cell classification is challenging for hematologists. Hematologists can identify malignant white blood cells by examining a peripheral blood smear under a microscope. However, the process is time-consuming, difficult, and expensive. Image processing and soft computing play a significant role in identifying early indicators of bone marrow cancer. The proposed study aims to investigate the existing cancer detection systems and their components. Further, this study majorly focuses on showing critical analysis of bone marrow cancer detection using image processing that includes enhancement, segmentation, feature extraction, classification, and accuracy which may help hematologists and oncologists to detect bone marrow cancer at early stages. Further, the paper also foresees the future aspects in the area of bone marrow cancer recognition systems. In comparison to manual detection techniques, these soft computing techniques are precise, trustworthy, and quick.
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