Dealing with Small Datasets for Deep Learning in Medical Imaging: An Evaluation of Self-Supervised Pre-Training on CT Scans Comparing Contrastive and Masked Autoencoder Methods for Convolutional Models.
Daniel WolfTristan PayerCatharina Silvia LissonChristoph Gerhard LissonMeinrad BeerTimo RopinskiMichael GötzPublished in: CoRR (2023)
Keyphrases
- deep learning
- restricted boltzmann machine
- medical imaging
- deep belief networks
- unsupervised feature learning
- deep architectures
- computed tomography
- ct images
- medical images
- ct scans
- computer aided diagnosis
- image analysis
- x ray
- image processing
- conditional random fields
- training set
- anatomical structures
- image segmentation
- medical image processing
- data mining
- machine learning
- computer vision
- imaging modalities
- remote sensing
- unsupervised learning
- image registration