The examination of peripheral blood films is time consuming, requires highly trained staff and remains subject to significant statistical variance and also a human visual error. In the past decades, efforts have been made to develop automated morphological analysis systems. The automated analysis of blood cell images was first described by Prewitt and Mendlesohn in 1966. Subsequently, other authors showed that digital image processing can be used for automated leucocyte recognition. In this work , we develope an automated blood cells image analysis based on external morphologocal properties of the erythrocyted and leukocytes (RBC and WBC) cells.
The differential counting of blood cells is an important diagnostic tool for successful treatment and management of patients. Additionally, the blood cells smear films need precise histological preperation to gain a good microscopic results. The reliable and efficient analysis of patient samples is therefore crucial. Current automated cell counters are based on laser-light scatter and flow-cytochemical principles, and offer a leukocyte, red cell and platelet count, including a five-part leucocyte differential and a panel for screening red blood cell (erythrocyte) abnormalities. A drawback of automated cell counters is that they offer very limited morphological information and are unable to reliably classify immature and abnormal cells. When abnormalities are suspected in a sample, results are automatically marked. In these cases or when quantification of the pathological cells is needed, a blood film is prepared for microscopical examination and cell classification. The optical microscopically review rate is about 23% of all processed blood samples, resulting in a huge amount of laboratory-intensive work.
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