{"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/nonnegative-gaussian-process-tomography-for","title":"Nonnegative Gaussian process tomography for generalized segmented planar detectors","arxiv_id":"1912.01058","date":"2019-12-02","proceeding":null,"authors":["D. Blyth","N. Mullins","E. Galyaev","J. Holmes"],"abstract":"The concept of Gaussian process tomography along with nonnegative constraints is applied in the context of high-resolution image reconstruction using segmented planar detectors with few readout channels.Expanding on the concept of 2-D projections onto strip-like readout segmentations, 3-D projections as well as more generalized detector segmentation and readout channel mappings are explored. A focus is placed on reconstructing dose distributions in proton therapy pencil beam scanning, and a fast, approximate approach to applying nonnegative constraints is developed and motivated for use in proton therapy beam imaging.","url_abs":"https://arxiv.org/abs/1912.01058v1","url_pdf":"https://arxiv.org/pdf/1912.01058v1.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":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"nonnegative-gaussian-process-tomography-for","repo_url":"https://github.com/decibelcooper/nngpt","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}