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Copyright (c) 2024 Gilles Van De Vyver Based on work by Huawei Technologies Co., Ltd. Licensed under CC BY-NC-SA 4.0 (Attribution-NonCommercial-ShareAlike 4.0 International) (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode The code is released for academic research use only. For commercial use, please contact Huawei Technologies Co., Ltd. Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. Original project: guided-diffusion by Dhariwal and Nichol (OpenAI), available at https://github.com/openai/guided-diffusion, licensed under the MIT License. Modifications were made in the RePaint project by Lugmayr et al. (Huawei Technologies Co., Ltd.), available at https://github.com/andreas128/RePaint, licensed under CC BY-NC-SA 4.0. This project, EchoGAINS, by Van De Vyver et al. (Norwegian University of Science and Technology), is a modification of RePaint and is licensed under CC BY-NC-SA 4.0. If you use this work, please cite the original authors and the current authors. Dhariwal, Prafulla, and Alexander Nichol. "Diffusion models beat gans on image synthesis." Advances in neural information processing systems 34 (2021): 8780-8794. Lugmayr, Andreas, et al. "Repaint: Inpainting using denoising diffusion probabilistic models." Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. 2022. Van De Vyver, Gilles, et al. "Generative augmentations for improved cardiac ultrasound segmentation using diffusion models." arXiv preprint arXiv:2502.20100 (2025). |