An Ensemble Approach for Classification of Breast Histopathology Images

Abstract

This paper presents an approach to classify breast histopathology images based on the mitotic count. An ensemble of handcrafted features, a bag of features (BoF), and convolutional neural network (CNN) are done for mitosis detection. Initially, mitotic regions are segmented followed by extraction of handcrafted features, BoF, and CNN-learned features from the candidate region. A non-linear support vector machine with Gaussian radial basis function kernel is used for the classification of each feature set independently. The proposed work utilizes the main tissue components of the images in an ensemble style to correctly classify the input histopathology image into benign or malignant. It also enables to maximize the performance by leveraging the disconnected feature set. Publicly available ICPR 2012 and 2014 mitosis dataset of is used for evaluation. The proposed ensemble method yielded a much improved F1 score. Better accuracy and fewer computing resources of our approach make it feasible for clinical use.

KEYWORDS:

• Bag of features
• Breast histopathology
• Convolutional neural network
• Ensemble
• Handcrafted features
• Mitosis
• Segmentation

Additional information

Notes on contributors

P. Dhivya

P Dhivya received her BE degree from Arulmigu Kalasalingam College of Engineering, Srivilliputur, under Anna University and obtained her ME degree from Meenakshi College of Engineering, Chennai, under Anna University, Tamil Nadu, India. She is currently pursuing her full-time PhD in medical image processing at Anna University. She has published over 10 technical papers in international/national conferences. Corresponding author. Email: [email protected]

S. Vasuki

S Vasuki completed her PhD, from Anna University, Chennai, Tamil Nadu. She is presently working as head of Electronics and Communication Department, Velammal College of Engineering and Technology, Madurai, Tamil Nadu. She is a Life Member of Indian Society for Technical Education and Institution of Electronics and Telecommunication Engineers. She has been doing continuous research and guiding 12 research scholars in the discipline of computer vision, image processing, texture analysis, character recognition, etc.

She has published 30 technical papers in reputed international journals and presented 120 technical papers in international/national conferences. Email: [email protected]