Detection of pneumonia in chest X‐ray images by using 2D discrete wavelet feature extraction with random forest
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[1] Banshidhar Majhi,et al. Mammogram classification using two dimensional discrete wavelet transform and gray-level co-occurrence matrix for detection of breast cancer , 2015, Neurocomputing.
[2] Michael H. Goldbaum,et al. Labeled Optical Coherence Tomography (OCT) and Chest X-Ray Images for Classification , 2018 .
[3] Thomas Brox,et al. U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.
[4] Victor Hugo C. de Albuquerque,et al. Lung nodule malignancy classification in chest computed tomography images using transfer learning and convolutional neural networks , 2018, Neural Computing and Applications.
[5] Marcin Wozniak,et al. Bio-inspired methods modeled for respiratory disease detection from medical images , 2018, Swarm Evol. Comput..
[6] Robertas Damasevicius,et al. A neuro-heuristic approach for recognition of lung diseases from X-ray images , 2019, Expert Syst. Appl..
[7] Li Yao,et al. Learning to diagnose from scratch by exploiting dependencies among labels , 2017, ArXiv.
[8] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[9] Mahesh Pal,et al. Random forest classifier for remote sensing classification , 2005 .
[10] Banshidhar Majhi,et al. Brain MR image classification using two-dimensional discrete wavelet transform and AdaBoost with random forests , 2016, Neurocomputing.
[11] Igor Rudan,et al. Epidemiology and etiology of childhood pneumonia. , 2008, Bulletin of the World Health Organization.
[12] Jinxing Li,et al. DualCheXNet: dual asymmetric feature learning for thoracic disease classification in chest X-rays , 2019, Biomed. Signal Process. Control..
[13] K. Yeom,et al. Radiomics in Brain Tumor: Image Assessment, Quantitative Feature Descriptors, and Machine-Learning Approaches , 2017, American Journal of Neuroradiology.
[14] Aditya Khamparia,et al. A Novel Transfer Learning Based Approach for Pneumonia Detection in Chest X-ray Images , 2020, Applied Sciences.
[15] Ronald M. Summers,et al. ChestX-ray: Hospital-Scale Chest X-ray Database and Benchmarks on Weakly Supervised Classification and Localization of Common Thorax Diseases , 2019, Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics.
[16] Loris Nanni,et al. Multilayer descriptors for medical image classification , 2016, Comput. Biol. Medicine.
[17] Miriam Seoane Santos,et al. Cross-Validation for Imbalanced Datasets: Avoiding Overoptimistic and Overfitting Approaches [Research Frontier] , 2018, IEEE Computational Intelligence Magazine.
[18] Daniel S. Kermany,et al. Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning , 2018, Cell.
[19] A. Mcluckie,et al. Respiratory Disease and its Management , 2009 .
[20] Hao Wu,et al. CXNet-m1: Anomaly Detection on Chest X-Rays With Image-Based Deep Learning , 2019, IEEE Access.
[21] B. Erickson,et al. Machine Learning for Medical Imaging. , 2017, Radiographics : a review publication of the Radiological Society of North America, Inc.
[22] Daisuke Komura,et al. Machine Learning Methods for Histopathological Image Analysis , 2017, Computational and structural biotechnology journal.
[23] Ruzena Bajcsy,et al. Fully Automated Echocardiogram Interpretation in Clinical Practice , 2018, Circulation.
[24] Mariana Belgiu,et al. Random forest in remote sensing: A review of applications and future directions , 2016 .
[25] J. Hanley,et al. The meaning and use of the area under a receiver operating characteristic (ROC) curve. , 1982, Radiology.
[26] H. Ünver,et al. Diagnosis of Pneumonia from Chest X-Ray Images Using Deep Learning , 2019, 2019 Scientific Meeting on Electrical-Electronics & Biomedical Engineering and Computer Science (EBBT).
[27] Lalit M. Patnaik,et al. Classification of magnetic resonance brain images using wavelets as input to support vector machine and neural network , 2006, Biomed. Signal Process. Control..
[28] Amit Kumar Jaiswal,et al. Identifying pneumonia in chest X-rays: A deep learning approach , 2019, Measurement.