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Histogram Matched Chest X-Rays Based Tuberculosis Detection Using CNN

Computer Systems Science & Engineering 2023年第1期44卷 81-97页

作者： joe louis paul Ignatius Sasirekha Selvakumar kavin gabriel joe louis paul Aadhithya B.Kailash S.Keertivaas S.A.J.Akarvin Raja Prajan Department of Information Technology Sri Sivasubramaniya Nadar College of EngineeringRajiv Gandhi Salai(OMR)KalavakkamChennai603110Tamil NaduIndia Gullas College of Medicine-University of Visayas BaniladMandaue City6014CebuPhilippines

Tuberculosis(TB)is a severe infection that mostly affects the lungs and kills millions of people’s lives every *** can be diagnosed using chest X-rays(CXR)and data-driven deep learning(DL)*** of its better automated feature extraction capability,convolutional neural net-works(CNNs)trained on natural images are particularly effective in image cate-gorization.A combination of 3001 normal and 3001 TB CXR images was gathered for this study from different accessible public *** different deep CNNs(Resnet50,Resnet101,Resnet152,InceptionV3,VGG16,VGG19,DenseNet121,DenseNet169,DenseNet201,MobileNet)are trained and tested for identifying TB and normal *** study presents a deep CNN approach based on histogram matched CXR images that does not require object segmenta-tion of interest,and this coupled methodology of histogram matching with the CXRs improves the accuracy and detection performance of CNN models for TB ***,this research contains two separate experiments that used CXR images with and without histogram matching to classify TB and non-TB CXRs using deep *** was able to accurately detect TB from CXR images using pre-processing,data augmentation,and deep CNN *** histogram matching the best accuracy,sensitivity,specificity,precision and F1-score in the detection of TB using CXR images among ten models are 99.25%,99.48%,99.52%,99.48%and 99.22%*** histogram matching the best accuracy,sensitivity,specificity,precision and F1-score are 99.58%,99.82%,99.67%,99.65%and 99.56%*** proposed meth-odology,which has cutting-edge performance,will be useful in computer-assisted TB diagnosis and aids in minimizing irregularities in TB detection in developing countries.

关键词： Tuberculosis detection chest x-ray(CXR) convolutional neural networks(CNNs) transfer learning histogram matching

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