This is a repository that contains the papers about Ideal Observer in medical imaging.
- Medical Imaging 2018 [paper]
Learning the ideal observer for SKE detection tasks by use of convolutional neural networks (Cum Laude Poster Award)
- TMI 2019 [paper]
Approximating the Ideal Observer and Hotelling Observer for binary signal detection tasks by use of supervised learning methods
- Medical Imaging 2019 [paper]
Learning the Hotelling observer for SKE detection tasks by use of supervised learning methods
- Medical Imaging 2019 [paper]
Learning the ideal observer for joint detection and localization tasks by use of convolutional neural networks
- TMI 2020 [paper]
Approximating the Ideal Observer for Joint Signal Detection and Localization Tasks by use of Supervised Learning Methods
- Thesis 2020 [paper]
Deep Learning for Task-Based Image Quality Assessment in Medical Imaging
- Medical Imaging 2020 [paper]
Learning numerical observers using unsupervised domain adaptation
- Medical Imaging 2020 [paper]
Markov-Chain Monte Carlo approximation of the Ideal Observer using generative adversarial networks
- Medical Imaging 2021 [paper]
Supervised learning-based ideal observer approximation for joint detection and estimation tasks
- Medical Imaging 2021 [paper]
Task-based performance evaluation of deep neural network-based image denoising
- TMI 2021 [paper]
Assessing the Impact of Deep Neural Network-Based Image Denoising on Binary Signal Detection Tasks
- TMI 2021 [paper]
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
- Arxiv 2022 [paper]
On the impact of incorporating task-information in learning-based image denoising
- Medical Imaging 2022 [paper]
Investigation of adversarial robust training for establishing interpretable CNN-based numerical observers
- Medical Imaging 2022 [paper]
A deep Q-learning method for optimizing visual search strategies in backgrounds of dynamic noise
- Medical Imaging 2023 [paper]
Estimating task-based performance bounds for image reconstruction methods by use of learned-ideal observers
- Arxiv 2023 [paper]
Ideal Observer Computation by Use of Markov-Chain Monte Carlo with Generative Adversarial Networks