Based On The Blood Cells Of The Bp Neural Network Of Automatic Identification Technology

With the development of computer technology, computers are widely used in medical study field. Among all these applications, computer assisted diagnosis are getting more and more attention, especially the processing of medical microscopic images. The work is very tiring with low efficiency in the traditional methods. So the members of the examination often have subjective observation errors and are requested to have higher technique level. Images can only be recorded by microscopic photograph however can not be processed, saved, and delivered long-distance by the network, so it isn't fit for the new request of development. Now we can get the digital medical microscopic images with the modern light-electricity conversion, hardware of the computer, data and image processing software etc. To reduce work intension and assist diagnosis for doctor, the blood cells need to be recognized by the specific request and analyzed on the quantitative colors and morphology in the computer.The paper is based on BP neural network method in digital image processing. Based on the method, the cells auto-counting system is developed by VC++. Firstly, we introduce the basic concepts and expound several familiar models about artificial neural network in detail, then make overall discussion on the BP neural network. Secondly, we introduce basic theories of digital image processing such as image smoothing, histogram threshold segmentation, thinning, gradient enhancement, mathematical morphology. The application of these knowledge and its results are also introduced. Thirdly, we use the BP neural network to classify the kind of cells with the extracted characteristic, and count the number of cells to give proof for medical diagnosis. At Last, we review the entire work and suggest the direction for future research.This paper provides theoretical proof for medical diagnosis and improves efficiency and accuracy for identifying more kinds of cells.