Pramit Ghosh

Pramit Ghosh, Debotosh Bhattacharjee, Mita Nasipuri et al.

The analysis and counting of blood cells in a microscope image can provide useful information concerning to the health of a person. In particular, morphological analysis of red blood cells deformations can effectively detect important disease like malaria. Blood images, obtained by the microscope, which is coupled with a digital camera, are analyzed by the computer for diagnosis or can be transmitted easily to clinical centers than liquid blood samples. Automatic analysis system for the presence of Plasmodium in microscopic image of blood can greatly help pathologists and doctors that typically inspect blood films manually. Unfortunately, the analysis made by human experts is not rapid and not yet standardized due to the operators capabilities and tiredness. The paper shows how effectively and accurately it is possible to identify the Plasmodium in the blood film. In particular, the paper presents how to enhance the microscopic image and filter out the unnecessary segments followed by the threshold based segmentation and recognize the presence of Plasmodium. The proposed system can be deployed in the remote area as a supporting aid for telemedicine technology and only basic training is sufficient to operate it. This system achieved more than 98 percentage accuracy for the samples collected to test this system.

Pramit Ghosh, Debotosh Bhattacharjee, Mita Nasipuri et al.

Blood related invasive pathological investigations play a major role in diagnosis of diseases. But in India and other third world countries there are no enough pathological infrastructures for medical diagnosis. Moreover, most of the remote places of those countries have neither pathologists nor physicians. Telemedicine partially solves the lack of physicians. But the pathological investigation infrastructure can not be integrated with the telemedicine technology. The objective of this work is to automate the blood related pathological investigation process. Detection of different white blood cells has been automated in this work. This system can be deployed in the remote area as a supporting aid for telemedicine technology and only high school education is sufficient to operate it. The proposed system achieved 97.33 percent accuracy for the samples collected to test this system.