BCNet: A Deep Convolutional Neural Network for Breast Cancer Grading

07/11/2021
by   Pouya Hallaj Zavareh, et al.
71

Breast cancer has become one of the most prevalent cancers by which people all over the world are affected and is posed serious threats to human beings, in a particular woman. In order to provide effective treatment or prevention of this cancer, disease diagnosis in the early stages would be of high importance. There have been various methods to detect this disorder in which using images have to play a dominant role. Deep learning has been recently adopted widely in different areas of science, especially medicine. In breast cancer detection problems, some diverse deep learning techniques have been developed on different datasets and resulted in good accuracy. In this article, we aimed to present a deep neural network model to classify histopathological images from the Databiox image dataset as the first application on this image database. Our proposed model named BCNet has taken advantage of the transfer learning approach in which VGG16 is selected from available pertained models as a feature extractor. Furthermore, to address the problem of insufficient data, we employed the data augmentation technique to expand the input dataset. All implementations in this research, ranging from pre-processing actions to depicting the diagram of the model architecture, have been carried out using tf.keras API. As a consequence of the proposed model execution, the significant validation accuracy of 88

READ FULL TEXT

page 1

page 2

page 6

page 7

page 8

page 9

12/22/2021

Convolutional neural network based on transfer learning for breast cancer screening

Breast cancer is the most common cancer in the world and the most preval...
07/06/2018

Data Augmentation for Detection of Architectural Distortion in Digital Mammography using Deep Learning Approach

Early detection of breast cancer can increase treatment efficiency. Arch...
11/16/2017

Hybrid Approach of Relation Network and Localized Graph Convolutional Filtering for Breast Cancer Subtype Classification

Network biology has been successfully used to help reveal complex mechan...
03/20/2013

Bayesian Networks Aplied to Therapy Monitoring

We propose a general Bayesian network model for application in a wide cl...
04/18/2022

Application of Transfer Learning and Ensemble Learning in Image-level Classification for Breast Histopathology

Background: Breast cancer has the highest prevalence in women globally. ...
08/12/2020

An Efficient Confidence Measure-Based Evaluation Metric for Breast Cancer Screening Using Bayesian Neural Networks

Screening mammograms is the gold standard for detecting breast cancer ea...