Search Results for author:
Found 5 papers, 1 papers with code
Respiratory motion forecasting with online learning of recurrent neural networks for safety enhancement in externally guided radiotherapy
We use UORO, SnAp-1, and DNI to forecast each marker's 3D position with horizons (the time interval in advance for which the prediction is made) h<=2. 1s and compare them with RTRL, least mean squares, and linear regression.
Unsupervised detection of small hyperreflective features in ultrahigh resolution optical coherence tomography
Recent advances in optical coherence tomography such as the development of high speed ultrahigh resolution scanners and corresponding signal processing techniques may reveal new potential biomarkers in retinal diseases.
Retinal blood flow speed quantification at the capillary level using temporal autocorrelation fitting OCTA
Optical coherence tomography angiography (OCTA) can visualize vasculature structures, but provides limited information about the blood flow speeds.
Prediction of the Position of External Markers Using a Recurrent Neural Network Trained With Unbiased Online Recurrent Optimization for Safe Lung Cancer Radiotherapy
Prediction with online learning of recurrent neural networks (RNN) allows for adaptation to non-stationary respiratory signals, but classical methods such as RTRL and truncated BPTT are respectively slow and biased.
Ranked #1 on
Multivariate Time Series Forecasting
on ExtMarker
Pathologist-Level Grading of Prostate Biopsies with Artificial Intelligence
We additionally evaluated grading performance on 87 biopsies individually graded by 23 experienced urological pathologists from the International Society of Urological Pathology.
