{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-9730660","patent":{"patent_number":"US-9730660","title":"Converting low-dose to higher dose mammographic images through machine-learning processes","assignee":null,"inventors":[],"filing_date":"2015-01-14T00:00:00.000Z","publication_date":"2017-08-15T00:00:00.000Z","cpc_codes":["A61B","A61B","G06F","G06T","G06V","G16H","A61B","G06T","G06T","G06T"],"num_claims":37,"abstract":"A method and system for converting low-dose mammographic images with much noise into higher quality, less noise, higher-dose-like mammographic images, using of a trainable nonlinear regression (TNR) model with a patch-input-pixel-output scheme, which can be called a call pixel-based TNR (PTNR). An image patch is extracted from an input mammogram acquired at a reduced x-ray radiation dose (lower-dose), and pixel values in the patch are entered into the PTNR as input. The output of the PTNR is a single pixel that corresponds to a center pixel of the input image patch. The PTNR is trained with matched pairs of mammograms, inputting low-dose mammograms together with corresponding desired standard x-ray radiation dose mammograms (higher-dose), which are ideal images for the output images. Through the training, the PTNR learns to convert low-dose mammograms to high-dose-like mammograms. Once trained, the trained PTNR does not require the higher-dose mammograms anymore. When a new reduced x-ray radiation dose (low dose) mammogram is entered, the trained PTNR would output a pixel value similar to its desired pixel value, in other words, it would output high-dose-like mammograms or “virtual high-dose” mammograms where noise and artifacts due to low radiation dose are substantially reduced, i.e., a higher image quality. With the “virtual high-dose” mammograms, the detectability of lesions and clinically important findings such as masses and microcalcifications can be improved."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Converting low-dose to higher dose mammographic images through machine-learning processes","description":"A method and system for converting low-dose mammographic images with much noise into higher quality, less noise, higher-dose-like mammographic images, using of a trainable nonlinear regression (TNR) m","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-9730660","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-9730660","citation_suggestion":"Patentable. \"Converting low-dose to higher dose mammographic images through machine-learning processes\" (US-9730660). https://patentable.app/patents/US-9730660","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-9730660","json":"https://patentable.app/api/llm-context/US-9730660","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-06-06T03:57:08.633Z"}