Diagnosis Evaluation and Interpretation of Qualitative Abnormalities in Peripheral Blood Smear Images—A Review

The computer and the digital camera have given proven opportunities to improve the hematology research and education with patient service. Peripheral Blood Smear (PBS) images of high quality can be obtained quickly and smoothly from the Peripheral Blood Smear with the help of a modern, high resolution digital camera and a high quality microscope. A PBS or blood film is a thin layer of blood coated on a microscope slide. PBS are usually examined to analyze the blood related problems and occasionally, to find parasites within the blood. PBS image examination is a part of the daily work of every testing laboratory. The manual examination of these images is difficult, takes more time and faces human intervention and observation error. This has motivated researchers to develop different algorithms and methods to automate peripheral blood smear image analysis. The interest of computer aided decision making has been identified in many medical applications such as automatic detection, classification and analysis of objects in hematological cytology. Image analysis itself consists of a sequence of steps consisting of image segmentation, features extraction and selection and pattern classification. The aim of this review article is to summarize the qualitative abnormalities of the blood cells, viz., Red Blood Cell, White blood Cell and Platelets. This aids the researcher, for ease interpretation and common diagnosis of the peripheral blood smear images. Also, this helps the researchers to propose more relevant image processing and machine learning tools for developing a complete automated PBS analysis system that can reduce the time spent for slide examination.