Data augmentation for medical imaging: A systematic literature review

This publication has 191 references indexed in Scilit:

• Improvement of fully automated airway segmentation on volumetric computed tomographic images using a 2.5 dimensional convolutional neural net
  Medical Image Analysis, 2019
• Osteoporosis detection in panoramic radiographs using a deep convolutional neural network-based computer-assisted diagnosis system: a preliminary study
  Dentomaxillofacial Radiology, 2019
• GAN-based synthetic medical image augmentation for increased CNN performance in liver lesion classification
  Neurocomputing, 2018
• Deep learning in medical imaging and radiation therapy
  Medical Physics, 2018
• 3-D Convolutional Neural Networks for Automatic Detection of Pulmonary Nodules in Chest CT
  IEEE Journal of Biomedical and Health Informatics, 2018
• Automatic Plaque Detection in IVOCT Pullbacks Using Convolutional Neural Networks
  IEEE Transactions on Medical Imaging, 2018
• Classification of Whole Mammogram and Tomosynthesis Images Using Deep Convolutional Neural Networks
  IEEE Transactions on Nanobioscience, 2018
• Prostate segmentation in MRI using a convolutional neural network architecture and training strategy based on statistical shape models
  International Journal of Computer Assisted Radiology and Surgery, 2018
• A survey on deep learning in medical image analysis
  Medical Image Analysis, 2017
• Medical Image Data and Datasets in the Era of Machine Learning—Whitepaper from the 2016 C-MIMI Meeting Dataset Session
  Journal of Digital Imaging, 2017