Sparse Representation Based Class Level Dictionary Learning Approach for Histopathology Image Classification

摘要

This paper presents histopathology image analysis methods for classification. Histopathology images contain large number diverse feature and rich geometrical structure. Automated histology image classification plays a vital role in computer-aided diagnosis. In this paper we have proposed class level dictionary learning approach which reduces the workload of pathologist. The algorithm has achieved significant performance on various histopathological image datasets. The strength of this model provides an efficient model for histopathology image classification. From the experimental results, it is clear that this methodology has better results than previous methods.