Study Of Pulse Coupled Neural Network In Biomedical Image Processing

Study of modern image processing indicates that the processing techniques must be of high speed, high quality and intelligence, and can also simulate the biologic vision system. "The Third-generation Neural Network"-- Pulse Coupled Neural Network (PCNN) is a new artificial neural network which comes from the research of small mammals' visual properties, namely, the synchronous pulse burst phenomenon of cat's visual cortex. PCNN is more similar to the course of vision system processes images because it is the accurate simulation of mammals' vision system. Especially, its nonlinear modulation characteristic has wide application in biomedical image processing. In this paper, the following works have been done according to the latest research in PCNN:(1) The research of plant body cell needs to account the content of macromolecules such as cellular protein, nucleic acid and starch as well as distributions of enzyme and calcium ion in different develop stages. Noise reduction is a crucial step in the whole quantitative analysis processing. In cell slice image, cell and background are similar, and their intensities are less different. Traditional methods can reduce image noise, but they would blur details at the same time. In this paper, a novel mixed noise removal algorithm for slice images of plant cell based on PCNN is proposed for the first time.(2) Image compression algorithms with effective storage and high quality of restoration are needed to meet large numbers of data and real-time multimedia techniques. The traditional image compression techniques, including Run-length Coding, Huffman Coding, Arithmetic Coding, and so on, make a deep research on decreasing the linear pertinence of images, and aim at reducing the statistical redundancy of originals, such as entropy redundancy and dimensional redundancy. Irregular Regions Image Coding (IRIC) algorithm is presented in this paper. Firstly, the original image is segmented into two kinds of parts by PCNN, one is the contours and textures sensitive to human vision system, and the other is smooth regions. Then they are coded by different methods. Experimental results indicate that IRIC not only can get a high compression ratio, but also protect image details. It is a recommendable technique in modern image compression.(3) Ultrasonic images are usually characterized by complexity, low contrast and all kinds of speckle, making ultrasonic image processing very difficult. PCNN was introduced into the field of ultrasonic image processing, and image enhancement algorithm and edge detection algorithm are proposed in this paper for the first time. Simulations indicate that PCNN is an excellent processing tool for ultrasonic images.