GC-EnC: A Copula based Ensemble of CNNs for Malignancy Identification in Breast Histopathology and Cytology Images

This is the official code release for the paper titled -

"GC-EnC: A Copula based Ensemble of CNNs for Malignancy Identification in Breast Histopathology and Cytology Images"

Copyright 2022, Soumyajyoti Dey, Shyamali Mitra, Sukanta Chakraborty, Debashri Mondal, Mita Nasipuri and Nibaran Das, All rights reserved.

Abstract of the Paper

In the present work, we have explored the potential of Copula-based ensemble of CNNs over individual classifiers for malignancy identification in histopathology and cytology images. The Copula-based model that integrates three best performing CNN architectures, namely, DenseNet-161/201, ResNet- 101/34, InceptionNet-V3 is proposed. Also, the limitation of small dataset is circumvented using a Fuzzy template based data augmentation technique that intelligently selects multiple region of interests (ROIs) from an image. The proposed framework of data augmentation amalgamated with the ensemble technique showed a gratifying performance in malignancy prediction surpassing the individual CNN’s performance on breast cytology and histopathology datasets. The proposed method has achieved accuracies of 84.37%, 97.32%, 91.67% on the JUCYT, BreakHis and BI datasets respectively. This automated technique will serve as a useful guide to the pathologist in delivering the appropriate diagnostic decision in reduced time and effort.

Dataset Folder Organization

Dataset_Name
   |-- Original
       |-- Train
           |-- Benign
           |-- Malignant
       |-- Test
           |-- Benign
           |-- Malignant
       |-- Validation
           |-- Benign
           |-- Malignant
   |-- Mask
       |-- Train
           |-- Benign
           |-- Malignant
       |-- Test
           |-- Benign
           |-- Malignant
       |-- Validation
           |-- Benign
           |-- Malignant
   |-- ROI
       |-- Train
           |-- Benign
           |-- Malignant
       |-- Test
           |-- Benign
           |-- Malignant
       |-- Validation
           |-- Benign
           |-- Malignant

External Packages Required

• Numpy 1.14.2
• PIL 5.0.0
• Scipy 1.0.0
• Matplotlib 2.1.2
• Pytorch 0.4.0
• MATLAB-2018b