{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/efficient-and-accurate-inversion-of-multiple","title":"Efficient and accurate inversion of multiple scattering with deep learning","arxiv_id":"1803.06594","date":"2018-03-18","proceeding":null,"authors":["Yu Sun","Zhihao Xia","Ulugbek S. Kamilov"],"abstract":"Image reconstruction under multiple light scattering is crucial in a number\nof applications such as diffraction tomography. The reconstruction problem is\noften formulated as a nonconvex optimization, where a nonlinear measurement\nmodel is used to account for multiple scattering and regularization is used to\nenforce prior constraints on the object. In this paper, we propose a powerful\nalternative to this optimization-based view of image reconstruction by\ndesigning and training a deep convolutional neural network that can invert\nmultiple scattered measurements to produce a high-quality image of the\nrefractive index. Our results on both simulated and experimental datasets show\nthat the proposed approach is substantially faster and achieves higher imaging\nquality compared to the state-of-the-art methods based on optimization.","url_abs":"http://arxiv.org/abs/1803.06594v2","url_pdf":"http://arxiv.org/pdf/1803.06594v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"efficient-and-accurate-inversion-of-multiple","repo_url":"https://github.com/wustl-cig/ScatteringDecoder","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"efficient-and-accurate-inversion-of-multiple","repo_url":"https://github.com/sunyumark/ScaDec-deep-learning-diffractive-tomography","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"efficient-and-accurate-inversion-of-multiple","repo_url":"https://github.com/zouhanrui/2dunet","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"efficient-and-accurate-inversion-of-multiple","repo_url":"https://github.com/zouhanrui/mri","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}}],"tasks":[{"task_slug":"deep-learning","task_name":"Deep Learning"},{"task_slug":"image-reconstruction","task_name":"Image Reconstruction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1803.06594","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}