MatConvNet-Based Fast Method for Cervical MR Images Classification

The deep convolutional neural network (CNN) has been successfully used to obtain high-level representation in various applications of computer vision problems. However, in the field of medical imaging there are not sufficient images available to train a deep CNN. Therefore, we have used a pre-trained deep CNN model for classification of cervical cancer MR images. In this paper, we have proposed MatConvNet-based CNN model to extract features from pre-trained CNN for classification. The vgg-f architecture is deployed to extract the image features. We have evaluated our proposed system with benchmark cervical cancer database obtained from Tumor Cancer Imaging Archive (TCIA). We got the promising result with 98.9% accuracy that is beyond the methods reported in the literature.

[1]  Andrew Zisserman,et al.  Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.

[2]  J. Kahng,et al.  [Clinical efficacy of HPV DNA chip test in the era of HPV vaccination: 1,211 cases, a single institution study]. , 2008, The Korean journal of laboratory medicine.

[3]  V. Nicolet,et al.  MR imaging of cervical carcinoma: a practical staging approach. , 2000, Radiographics : a review publication of the Radiological Society of North America, Inc.

[4]  Ho-Jin Choi,et al.  Diagnosing cervical cell images using pre-trained convolutional neural network as feature extractor , 2017, 2017 IEEE International Conference on Big Data and Smart Computing (BigComp).

[5]  Stefan Holban,et al.  Segmentation of bone structure in X-ray images using convolutional neural network , 2013 .

[6]  Malay Kumar Kundu,et al.  Pap smear image classification using convolutional neural network , 2016, ICVGIP '16.

[7]  Lubomir M. Hadjiiski,et al.  Deep-learning convolution neural network for computer-aided detection of microcalcifications in digital breast tomosynthesis , 2016, SPIE Medical Imaging.

[8]  Luiz Eduardo Soares de Oliveira,et al.  Breast cancer histopathological image classification using Convolutional Neural Networks , 2016, 2016 International Joint Conference on Neural Networks (IJCNN).

[9]  Naoufel Werghi,et al.  Classification of Cervical-Cancer Using Pap-Smear Images: A Convolutional Neural Network Approach , 2017, MIUA.

[10]  Selim Aksoy,et al.  Unsupervised segmentation and classification of cervical cell images , 2012, Pattern Recognit..

[11]  Geoffrey E. Hinton,et al.  ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.

[12]  Tao Xu,et al.  Multimodal Deep Learning for Cervical Dysplasia Diagnosis , 2016, MICCAI.

[13]  Hayit Greenspan,et al.  Chest pathology detection using deep learning with non-medical training , 2015, 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI).