Parallel Image Processing Using Neural Networks: Applications in Contrast Enhancement of Medical Images

This paper describes the implementation of a parallel image processing algorithm, the aim of which is to give good contrast enhancement in real time, especially on the boundaries of an object of interest defined by a grey homogeneity (for example, an object of medical interest having a functional or morphologic homogeneity, like a bone or tumor). The implementation of a neural network algorithm which does this contrast enhancement has been done on a SIMD massively parallel machine (a MasPar of 8192 processors) and the communication between its processors has been optimized.