27 citations · 55 across the 4 of their papers we have counts for
4 papers
Robust automated radiation therapy treatment planning using scenario-specific dose prediction and robust dose mimicking
Oskar Eriksson, Tianfang Zhang
Purpose: We present a framework for robust automated treatment planning using machine learning, comprising scenario-specific dose prediction and robust dose mimicking. Methods: The…
Probabilistic Pareto plan generation for semiautomated multicriteria radiation therapy treatment planning
Tianfang Zhang, Rasmus Bokrantz, Jimmy Olsson
Objective: We propose a semiautomatic pipeline for radiation therapy treatment planning, combining ideas from machine learning-automated planning and multicriteria optimization (MC…
A similarity-based Bayesian mixture-of-experts model
Tianfang Zhang, Rasmus Bokrantz, Jimmy Olsson
We present a new nonparametric mixture-of-experts model for multivariate regression problems, inspired by the probabilistic k-nearest neighbors algorithm. Using a conditionally spe…
Probabilistic dose prediction using mixture density networks for automated radiation therapy treatment planning
Viktor Nilsson, Hanna Gruselius, Tianfang Zhang +2
We demonstrate the application of mixture density networks (MDNs) in the context of automated radiation therapy treatment planning. It is shown that an MDN can produce good predict…