Using Computer Vision to Identify and Count Blood Cells helps in medical diagnosis

Identification and quantification of complete blood cells (CBCs) is often an essential clinical test to monitor a patient’s health. The conventional method suffers from time-consuming and erroneous procedures, is dependent on the skill of clinical laboratorians, and is affected by the quality and precision of laboratory equipment. This paper introduces a “you only look once” (YOLO) object detection and classification algorithm to automate CBC identification and quantification.