Proceedings ArticleDOI
Automatic Approach for Cervical Cancer Detection Based on Deep Belief Network (DBN) Using Colposcopy Data
Dian Candra Rini Novitasari,Ahmad Zoebad Foeady,Muhammad Thohir,Ahmad Zaenal Arifin,Khoirun Niam,Ahmad Hanif Asyhar +5 more
- pp 415-420
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TLDR
This paper can be an alternative to help medical authorities in detecting cervical cancer with the help of the Computer-Aided Diagnosis (CAD) System and results obtained from the identification process of cervical cancer using the DBN method is 84%.Abstract:
Cervical cancer is one of the diseases with the highest mortality rate. In the world, cervical cancer is ranked as the fourth most dangerous disease. Based on these problems, this paper can be an alternative to help medical authorities in detecting cervical cancer with the help of the Computer-Aided Diagnosis (CAD) System. CAD System used has two processes, such as preprocessing and classification. Preprocessing is useful to improve the image so that it is easier to do the process of identifying features. Preprocessing used is greyscale, histogram equalization, and median filter. Preprocessing results will be formed into a vector matrix using the reshaping process. The final step is the process of classifying data using the Deep Belief Network method. The best accuracy results obtained from the identification process of cervical cancer using the DBN method is 84%. Based on the results of accuracy, is expected to help reduce the number of deaths from cervical cancer with early detection.read more
Citations
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Backpropagation을 이용한 악보인식
TL;DR: Song et al. as mentioned in this paper used back propagation network to recognize music symbols and music notes by preprocessing such as binarization, slope correction, staff line removing, etc. They proved correctness of proposed music recognition algorithm though experiments and analysis with various kind of musics.
Journal ArticleDOI
Detection of COVID-19 chest x-ray using support vector machine and convolutional neural network
Dian Candra Rini Novitasari,Rimuljo Hendradi,Rezzy Eko Caraka,Yuanita Rachmawati,Nurul Zainal Fanani,Anang Syarifudin,Toni Toharudin,Rung-Ching Chen +7 more
TL;DR: This study aims to detect whether patients examined are healthy, Coronavirus positive, or just have pneumonia based on chest X-ray data using Convolutional Neural Network method as feature extraction and Support Vector Machine as a classification method.
Journal ArticleDOI
Deep Metric Learning for Cervical Image Classification
Anabik Pal,Zhiyun Xue,Brian Befano,Ana Cecilia Rodriguez,L. Rodney Long,Mark Schiffman,Sameer Antani +6 more
TL;DR: In this paper, a deep learning-based algorithm for automatic visual evaluation (AVE) of aceto-whitened cervical images was shown to be effective in detecting confirmed precancer (i.e. direct precursor to invasive cervical cancer).
Journal ArticleDOI
Multi-state colposcopy image fusion for cervical precancerous lesion diagnosis using BF-CNN
TL;DR: In this paper, a bilinear fuse convolutional neural network (BF-CNN) was proposed to fuse two-state image features for automatic diagnosis of cervical precancerous lesions.
Proceedings ArticleDOI
A Comparative Analysis of Machine and Deep Learning Models for Cervical Cancer Classification
TL;DR: In this paper, the authors incorporate various deep learning and machine learning models for classification of normal and cancerous cervical cells as well as their types and a comparative analysis of performance measures such as accuracy, sensitivity, specificity and F1 score is made.
References
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TL;DR: A new technique for feature selection that uses information from a confusion matrix and evaluates one attribute at a time, creating subsets of attributes that are complementary that is, they misclassify different classes.