Robust segmentation and measurements techniques of white cells in blood microscope images

The analysis and the count of blood cell in microscope image can provide useful information concerning the health of the patients. In particular, morphological analysis of white cell deformations can effectively detect important diseases such as the Acute Lymphoblastic Leukemia. Blood images obtained by microscopes coupled with a digital camera are simple to obtain and can be more simply transmitted to clinical centers than liquid blood samples. Automatic measurement systems for white cells in blood microscope image can greatly help blood experts that typically inspect blood films manually. Unfortunately, the analysis made by human experts is not rapid and it presents a not standardized accuracy due to the operator’s capabilities and tiredness. The presented paper shows how that it is effectively possible to accurately measure the white cells properties in order to allow, at a second stage, the leukemia identification. In particular, the paper presents how to suitably enhance the microscope image by removing the undesired microscope background and a new segmentation strategy to robustly identify white cells permitting to better extract their features for subsequent automatic diagnosis of diseases.