{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-10493299","patent":{"patent_number":"US-10493299","title":"Determining parameters for a beam model of a radiation machine using deep convolutional neural networks","assignee":null,"inventors":[],"filing_date":"2017-12-08T00:00:00.000Z","publication_date":"2019-12-03T00:00:00.000Z","cpc_codes":["A61N","A61N","A61N","G06N","G06N","G16H","A61N","A61N","A61N","A61N","G06T","G06T","G06T"],"num_claims":20,"abstract":"Systems and methods can include training a deep convolutional neural network model to provide a beam model for a radiation machine, such as to deliver a radiation treatment dose to a subject. A method can include determining a range of parameter values for at least one parameter of a beam model corresponding to the radiation machine, generating a plurality of sets of beam model parameter values, wherein one or more individual sets of beam model parameter values can include a parameter value selected from the determined range of parameter values, providing a plurality of corresponding dose profiles respectively corresponding to respective individual sets beam model parameter values in the plurality of sets of beam model parameter values, and training the neural network model using the plurality of beam models and the corresponding dose profiles."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Determining parameters for a beam model of a radiation machine using deep convolutional neural networks","description":"Systems and methods can include training a deep convolutional neural network model to provide a beam model for a radiation machine, such as to deliver a radiation treatment dose to a subject. A method","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-10493299","license":"CC-BY-4.0-like","license_terms":"AI-generated analysis on this page (summary, layman_explanation, technical_analysis, business_analysis, faqs) may be reused with attribution and a visible link back to the canonical URL above. Patent abstracts, claims, and bibliographic data are USPTO public domain.","required_link":"https://patentable.app/patents/US-10493299","citation_suggestion":"Patentable. \"Determining parameters for a beam model of a radiation machine using deep convolutional neural networks\" (US-10493299). https://patentable.app/patents/US-10493299","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-10493299","json":"https://patentable.app/api/llm-context/US-10493299","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-30T18:49:57.401Z"}