107 citations · 199 across the 20 of their papers we have counts for
Showing eess.SPShow all
3 papers · 1 filter
eess.SP2021
A Hybrid Approach for Approximating the Ideal Observer for Joint Signal Detection and Estimation Tasks by Use of Supervised Learning and Markov-Chain Monte Carlo Methods
Kaiyan Li, Weimin Zhou, Hua Li +1
The ideal observer (IO) sets an upper performance limit among all observers and has been advocated for assessing and optimizing imaging systems. For general joint detection and est…
eess.SP2020★ 15 cited
Approximating the Ideal Observer for joint signal detection and localization tasks by use of supervised learning methods
Weimin Zhou, Hua Li, Mark A. Anastasio
Medical imaging systems are commonly assessed and optimized by use of objective measures of image quality (IQ). The Ideal Observer (IO) performance has been advocated to provide a…
eess.SP2019★ 47 cited
Approximating the Ideal Observer and Hotelling Observer for binary signal detection tasks by use of supervised learning methods
Weimin Zhou, Hua Li, Mark A. Anastasio
It is widely accepted that optimization of medical imaging system performance should be guided by task-based measures of image quality (IQ). Task-based measures of IQ quantify the…