Machine learning-based mammary gland molybdenum target and MR image omics model establishment method

• Main Authors: JIANG XINHUA, LI LI, LI JIAO, XIE FEI, CUI CHUNYAN
• Format: Patent
• Language: Chinese; English
• Published: 02.10.2020
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; HANDLING RECORD CARRIERS; HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL; INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS; PHYSICS; PRESENTATION OF DATA; RECOGNITION OF DATA; RECORD CARRIERS

The invention provides a machine learning-based mammary gland molybdenum target and an MR image omics model establishment method. The method comprises the steps of (1) mammary gland molybdenum targetand MR image collection, (2) establishment of a machine learning-based mammary gland molybdenum target and an MR image segmentation algorithm, and (3) establishment of an omics analysis method and a risk prediction model of a mammary gland molybdenum target and MR image; (2) completion of manually sketching of focus areas and other interested areas of 1000 cases of mammary gland molybdenum targetsand MR images, and establishment of a training sample and a verification sample by utilizing the group of data; screening of characteristic parameters of a tumor region and a non-tumor region and screening of a tissue classification algorithm by using a machine learning algorithm; and establishment of a classifier prediction model through machine learning by using the screened characteristic parameters and a tissue classi