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ORCIDDimitrios S. Gotsis
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2020 – today
- 2024
[i3]Rucha Deshpande, Varun A. Kelkar, Dimitrios S. Gotsis, Prabhat K. C., Rongping Zeng, Kyle J. Myers, Frank J. Brooks, Mark A. Anastasio:
Report on the AAPM Grand Challenge on deep generative modeling for learning medical image statistics. CoRR abs/2405.01822 (2024)- 2023
- [j1]Varun A. Kelkar, Dimitrios S. Gotsis, Frank J. Brooks, Prabhat K. C.
, Kyle J. Myers, Rongping Zeng, Mark A. Anastasio:
Assessing the Ability of Generative Adversarial Networks to Learn Canonical Medical Image Statistics. IEEE Trans. Medical Imaging 42(6): 1799-1808 (2023) - [c2]Varun A. Kelkar, Dimitrios S. Gotsis, Rucha Deshpande, Frank J. Brooks, Prabhat K. C., Kyle J. Myers, Rongping Zeng, Mark A. Anastasio:
Evaluating generative stochastic image models using task-based image quality measures. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2023 - 2022
- [c1]Varun A. Kelkar, Dimitrios S. Gotsis, Frank J. Brooks, Kyle J. Myers, Prabhat K. C., Rongping Zeng, Mark A. Anastasio:
Evaluating procedures for establishing generative adversarial network-based stochastic image models in medical imaging. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2022 - [i2]Varun A. Kelkar, Dimitrios S. Gotsis, Frank J. Brooks, Kyle J. Myers, Prabhat K. C., Rongping Zeng, Mark A. Anastasio:
Evaluating Procedures for Establishing Generative Adversarial Network-based Stochastic Image Models in Medical Imaging. CoRR abs/2204.03547 (2022) - [i1]Varun A. Kelkar, Dimitrios S. Gotsis, Frank J. Brooks, Prabhat K. C., Kyle J. Myers, Rongping Zeng, Mark A. Anastasio:
Assessing the ability of generative adversarial networks to learn canonical medical image statistics. CoRR abs/2204.12007 (2022)
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