Abstract

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IMAGE PROCESSING BASED ABNORMAL BLOOD CELLS DETECTION

Deepika N. Patil and Uday P. Khot


This paper deals with an image processing technique used for detecting the abnormalities of blood cells in less time. The proposed image processing technique also helps in counting and segregating the blood cells in different categories based on the form factor. Image processing techniques are widely used in the domain of medical sciences for detecting various diseases, infections, tumors, cell abnormalities, and various cancers. Detecting and curing a disease on time is very important in the field of medicine for protecting and saving human life. Mostly in case of high severity, diseases where the mortality rates are more, the waiting time of patients for their reports such as blood test, MRI is more. The time taken for generation of any of the test is from 2-8 days. In high risk diseases like Hepatitis B, it is recommended that the patient’s waiting time should be as less as possible and the treatment should be started immediately. The current system used by the pathologists for identification of blood parameters is costly and the time involved in generation of the reports is also more sometimes leading to loss of patient’s life. Also the pathological tests are expensive, which are sometimes not affordable by the patient. The proposed method gives 83% accuracy in counting the number of blood cells and 29% variation in observed values of detected abnormalities.