Learning the ideal observer for joint detection and localization tasks by use of convolutional neural networks

Author:

Zhou Weimin,Anastasio Mark A.

Publisher

SPIE

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Ideal Observer Computation by Use of Markov-Chain Monte Carlo With Generative Adversarial Networks;IEEE Transactions on Medical Imaging;2023-12

2. A deep Q-learning method for optimizing visual search strategies in backgrounds of dynamic noise;Medical Imaging 2022: Image Perception, Observer Performance, and Technology Assessment;2022-04-04

3. Approximating the Ideal Observer for Joint Signal Detection and Localization Tasks by use of Supervised Learning Methods;IEEE Transactions on Medical Imaging;2020-12

4. Evaluation of convolutional neural networks for search in 1/f2.8 filtered noise and digital breast tomosynthesis phantoms;Medical Imaging 2020: Image Perception, Observer Performance, and Technology Assessment;2020-03-16

5. Progressively-Growing AmbientGANs for learning stochastic object models from imaging measurements;Medical Imaging 2020: Image Perception, Observer Performance, and Technology Assessment;2020-03-16

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