{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-11501435","patent":{"patent_number":"US-11501435","title":"Unsupervised content-preserved domain adaptation method for multiple CT lung texture recognition","assignee":null,"inventors":[],"filing_date":"2020-12-04T00:00:00.000Z","publication_date":"2022-11-15T00:00:00.000Z","cpc_codes":["G06T","G06T","G06T","G06T","G06T","G06T","G06T"],"num_claims":2,"abstract":"The invention discloses an unsupervised content-preserved domain adaptation method for multiple CT lung texture recognition, which belongs to the field of image processing and computer vision. This method enables the deep network model of lung texture recognition trained in advance on one type of CT data (on the source domain), when applied to another CT image (on the target domain), under the premise of only obtaining target domain CT image and not requiring manually label the typical lung texture, the adversarial learning mechanism and the specially designed content consistency network module can be used to fine-tune the deep network model to maintain high performance in lung texture recognition on the target domain. This method not only saves development labor and time costs, but also is easy to implement and has high practicability."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Unsupervised content-preserved domain adaptation method for multiple CT lung texture recognition","description":"The invention discloses an unsupervised content-preserved domain adaptation method for multiple CT lung texture recognition, which belongs to the field of image processing and computer vision. This me","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-11501435","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-11501435","citation_suggestion":"Patentable. \"Unsupervised content-preserved domain adaptation method for multiple CT lung texture recognition\" (US-11501435). https://patentable.app/patents/US-11501435","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-11501435","json":"https://patentable.app/api/llm-context/US-11501435","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-30T17:06:21.643Z"}