Search Results for author:
Found 6 papers, 4 papers with code
Recalibration of Aleatoric and Epistemic Regression Uncertainty in Medical Imaging
We apply estimation of both aleatoric and epistemic uncertainty by variational Bayesian inference with Monte Carlo dropout to regression tasks and show that predictive uncertainty is systematically underestimated.
Well-Calibrated Regression Uncertainty in Medical Imaging with Deep Learning
The consideration of predictive uncertainty in medical imaging with deep learning is of utmost importance.
Retinal OCT disease classification with variational autoencoder regularization
A recent study established a diagnostic tool based on convolutional neural networks (CNN), which was trained on a large database of retinal OCT images.
Endoscopic vs. volumetric OCT imaging of mastoid bone structure for pose estimation in minimally invasive cochlear implant surgery
The resulting volumentric images provide additional information on the shape of caveties in the bone structure, which will be useful for image-to-patient registration and to estimate the drill trajectory.
Deep learning based 2.5D flow field estimation for maximum intensity projections of 4D optical coherence tomography
Subsequent to this, the projections are warped by predicted lateral flow and 1D depth flow is estimated.
A Dataset of Laryngeal Endoscopic Images with Comparative Study on Convolution Neural Network Based Semantic Segmentation
Methods Four machine learning based methods SegNet, UNet, ENet and ErfNet were trained with supervision on a novel 7-class dataset of the human larynx.
