Application of CNN in blood smeared images: A Review
Dilip Kumar Baruah · Revista Electronica de Veterinaria · 2024
Disorders such as malaria, leukemia, thrombocytopenia, sickle cell anemia, and many others cause morphological and physiological changes in the blood cells which can be used as an indicator in the diagnosis process of such diseases. Blood smear analysis is a routine work carried out in laboratories to diagnose a disease. Microscopic evaluation is one of the widely used techniques for blood smear analysis. However, the diagnostic result may vary depending on the skill and experience of the technician, instruments and methods used to analyze the blood sample. Manual microscopic examination is time consuming and is less repeatability. The advent of digital imaging taken using Light microscopy has enhanced diagnostic role. In recent years several technological innovations in the field of image processing and Convolutional Neural Networks (CNN) are employed in automated medical diagnosis. This paper focuses on the recent works reported in the field of automated disease diagnosis from blood-smeared images.