A Novel Deep Model for Biopsy Image Grading
Gang Zhang, Zhaohui Liang, Huadong Lai, Yiyu Lin, Dong Liang Lin, Ziping Li · 2016
We propose in this paper a deep learning model based on convolutional neural network (CNN) for biopsy image grading. The model outputs a vector of scores indicating presence or severity of the target histopathological characteristics. Within the model, we first design a 7-layer CNN for feature representation and high level concept extraction. Each biopsy image is expressed as a feature vector through our CNN processor. We then place a sigmoid function into the output layer so as to generate a score for each target characteristic. The proposed model is evaluated on a benchmark dataset and a real biopsy image dataset to show its effectiveness.