Hybrid computer-aided classification system design using end-to-end Pre-trained CNN-based deep feature extraction and PCA-SVM classifier for chest radiographs

[1]  Zhao Wu,et al.  Feature selection method based on support vector machine and shape analysis for high-throughput medical data , 2017, Comput. Biol. Medicine.

[2]  Niall O' Mahony,et al.  Deep Learning vs. Traditional Computer Vision , 2019, CVC.

[3]  Jorge Cadima,et al.  Principal component analysis: a review and recent developments , 2016, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[4]  Shruti Jain,et al.  Research Journal of Pharmaceutical, Biological and Chemical Sciences Svm-based Characterization of Focal Kidney Lesions from B-mode Ultrasound Images , 2022 .

[5]  Hariharan Ravishankar,et al.  Understanding the Mechanisms of Deep Transfer Learning for Medical Images , 2016, LABELS/DLMIA@MICCAI.

[6]  Xiaolei Yang,et al.  Research on Feature Extraction of Tumor Image Based on Convolutional Neural Network , 2019, IEEE Access.

[7]  Mark A. Hall,et al.  Correlation-based Feature Selection for Discrete and Numeric Class Machine Learning , 1999, ICML.

[8]  Philomina Simon,et al.  Deep Learning based Feature Extraction for Texture Classification , 2020 .

[9]  Burhan Ergen,et al.  A Deep Feature Learning Model for Pneumonia Detection Applying a Combination of mRMR Feature Selection and Machine Learning Models , 2020, IRBM.

[10]  Suresh Dara,et al.  Feature Extraction By Using Deep Learning: A Survey , 2018, 2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA).

[11]  Ferat Sahin,et al.  A survey on feature selection methods , 2014, Comput. Electr. Eng..

[12]  Nikola Bogunovic,et al.  A review of feature selection methods with applications , 2015, 2015 38th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO).

[13]  Syed Muhammad Anwar,et al.  Medical Image Analysis using Convolutional Neural Networks: A Review , 2017, Journal of Medical Systems.

[14]  Mohan Allam,et al.  A Study on Optimization Techniques in Feature Selection for Medical Image Analysis , 2017 .

[15]  Oge Marques,et al.  Comparative Performance Analysis of Machine Learning Classifiers in Detection of Childhood Pneumonia Using Chest Radiographs , 2013, ICCS.

[16]  Peng Sun,et al.  An Improved SVM Classifier for Medical Image Classification , 2007, RSEISP.

[17]  Ming Cheng,et al.  Predict pneumonia with chest X-ray images based on convolutional deep neural learning networks , 2020, J. Intell. Fuzzy Syst..

[18]  Aboul Ella Hassanien,et al.  Breast cancer MRI diagnosis approach using support vector machine and pulse coupled neural networks , 2012, J. Appl. Log..

[19]  Antoine Geissbühler,et al.  Comparative Performance Analysis of State-of-the-Art Classification Algorithms Applied to Lung Tissue Categorization , 2010, Journal of Digital Imaging.

[20]  Oscar Camacho Nieto,et al.  A machine learning approach to medical image classification: Detecting age-related macular degeneration in fundus images , 2017, Comput. Electr. Eng..

[21]  Maarten De Vos,et al.  Smart diagnostic algorithms for automated detection of childhood pneumonia in resource-constrained settings , 2015, 2015 IEEE Global Humanitarian Technology Conference (GHTC).

[22]  Lejla Gurbeta,et al.  An Expert Diagnostic System to Automatically Identify Asthma and Chronic Obstructive Pulmonary Disease in Clinical Settings , 2018, Scientific Reports.

[23]  Vinod Kumar,et al.  Pca-SVm based caD System for Focal liver lesions using B-mode ultrasound Images , 2013 .

[24]  Hui-Huang Hsu,et al.  Feature Selection via Correlation Coefficient Clustering , 2010, J. Softw..

[25]  Petrus Mursanto,et al.  Segmentation-based Knowledge Extraction from Chest X-ray Images , 2019, 2019 4th Asia-Pacific Conference on Intelligent Robot Systems (ACIRS).

[26]  Lasse Laurson,et al.  Threshold-induced correlations in the Random Field Ising Model , 2018, Scientific Reports.

[27]  D. Mollura,et al.  Computer-aided diagnosis of pulmonary infections using texture analysis and support vector machine classification. , 2011, Academic radiology.

[28]  Vinod Kumar Jain,et al.  Correlation feature selection based improved-Binary Particle Swarm Optimization for gene selection and cancer classification , 2018, Appl. Soft Comput..

[29]  Ashis Pradhan,et al.  SUPPORT VECTOR MACHINE-A Survey , 2012 .

[30]  S.M. Krishnan,et al.  Extraction of Brain Tumor from MR Images Using One-Class Support Vector Machine , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[31]  Kurt Hornik,et al.  Support Vector Machines in R , 2006 .

[32]  Jitendra Virmani,et al.  SVM-based characterisation of liver cirrhosis by singular value decomposition of GLCM matrix , 2013, Int. J. Artif. Intell. Soft Comput..

[33]  Mohammad Farukh Hashmi,et al.  Efficient Pneumonia Detection in Chest Xray Images Using Deep Transfer Learning , 2020, Diagnostics.

[34]  William Stafford Noble,et al.  Support vector machine , 2013 .

[35]  Ankush Mittal,et al.  Pneumonia Detection Using CNN based Feature Extraction , 2019, 2019 IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT).

[36]  Clarimar José Coelho,et al.  Computer-aided diagnosis in chest radiography for detection of childhood pneumonia , 2008, Int. J. Medical Informatics.

[37]  André Carlos Ponce de Leon Ferreira de Carvalho,et al.  Combining meta-learning and search techniques to select parameters for support vector machines , 2012, Neurocomputing.

[38]  Jitendra Virmani,et al.  Classification of Breast Density Patterns Using PNN, NFC, and SVM Classifiers , 2018 .

[39]  Huan Liu,et al.  Feature Selection for Classification: A Review , 2014, Data Classification: Algorithms and Applications.

[40]  A. V.DavidSánchez,et al.  Advanced support vector machines and kernel methods , 2003, Neurocomputing.

[41]  Adam Czajka,et al.  Deep Learning-Based Feature Extraction in Iris Recognition: Use Existing Models, Fine-tune or Train From Scratch? , 2019, 2019 IEEE 10th International Conference on Biometrics Theory, Applications and Systems (BTAS).

[42]  Hung-Min Sun,et al.  Effective Pneumothorax Detection for Chest X-Ray Images Using Local Binary Pattern and Support Vector Machine , 2018, Journal of healthcare engineering.

[43]  F. Al-turjman,et al.  A machine learning-based framework for diagnosis of COVID-19 from chest X-ray images , 2021, Interdisciplinary Sciences: Computational Life Sciences.

[44]  C. Krishna Mohan,et al.  Discriminative feature extraction from X-ray images using deep convolutional neural networks , 2016, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[45]  Kadry Ali Ezzat,et al.  Automatic X-ray COVID-19 Lung Image Classification System based on Multi-Level Thresholding and Support Vector Machine , 2020, medRxiv.

[46]  Kenji Suzuki,et al.  Overview of deep learning in medical imaging , 2017, Radiological Physics and Technology.

[47]  Verónica Bolón-Canedo,et al.  A review of feature selection methods in medical applications , 2019, Comput. Biol. Medicine.

[48]  Jitendra Virmani,et al.  SVM-Based Characterization of Liver Ultrasound Images Using Wavelet Packet Texture Descriptors , 2013, Journal of Digital Imaging.

[49]  Krzysztof Michalak,et al.  CORRELATION-BASED FEATURE SELECTION STRATEGY IN CLASSIFICATION PROBLEMS , 2006 .

[50]  Nilanjan Dey,et al.  PCA-PNN and PCA-SVM Based CAD Systems for Breast Density Classification , 2016, Applications of Intelligent Optimization in Biology and Medicine.

[51]  Nilanjan Dey,et al.  Customized VGG19 Architecture for Pneumonia Detection in Chest X-Rays , 2021, Pattern Recognit. Lett..

[52]  Aditya Khamparia,et al.  A Novel Transfer Learning Based Approach for Pneumonia Detection in Chest X-ray Images , 2020, Applied Sciences.