: A Segmentation process is labeling an image used for obtaining more meaningful information. In biomedical images, it plays has an
important role in helping pathologist for conducting advanced analysis. After the Graphical Processing Unit (GPU) introduced not only for
graphical necessary but also for general computing, segmentation process which is computationally expensive can be potentially improved. The
good accuracy detection and segmentation result provides morphological information for the pathologist. Consequently, more advanced
approaches were developed to ensure the good performance of detection and segmentation such as deep learning approach. The Convolutional
Neural Network (CNN) is one of deep learning architecture with complex computation. This paper presents an overview of utilization of
Convolutional Neural Network as prominent deep learning architecture under Graphical Processing Unit platform and proposes an approach of
using GPU as potential further parallel techniques in CNN.
Keywords: Image segmentation; deep learning; convolutional neural network; medical image, GPU speed.: