A method and system for structured image analysis of pancreatic cystic lesions

By processing pancreatic cystic lesion data using interpolation and image correction, a classification model was constructed, which solved the problems of accuracy and consistency in the classification of pathological types of pancreatic cystic lesions, and achieved precise and efficient differentiation of pathological types.

CN122289256APending Publication Date: 2026-06-26TIANJIN TUMOR HOSPITAL
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
TIANJIN TUMOR HOSPITAL
Filing Date
2026-05-12
Publication Date
2026-06-26

AI Technical Summary

Technical Problem

The existing classification of pathological types of pancreatic cystic lesions suffers from problems such as insufficient data quality, low classification accuracy, and poor consistency. In particular, the lack of original clinical data, the deviation of imaging data, and the disorder of data types lead to inaccurate classification and poor consistency.

Method used

Missing original clinical data were processed by interpolation, and original imaging data were processed by image correction. A structured pathological type classification model of pancreatic cystic lesions was constructed, and the pathological types were distinguished by weighted summation.

Benefits of technology

This study improves the accuracy and consistency of the classification of pathological types of pancreatic cystic tumors, provides reliable clinical diagnostic and treatment support, and solves the problems of classification inaccuracy and consistency caused by missing data and bias.

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Abstract

This invention proposes a structured image analysis method and system for pancreatic cystic lesions, belonging to the field of image processing technology. It collects lesion data through an electronic medical record system, and obtains classification data, basic clinical data, and basic imaging data through interpolation and image correction methods. Based on these classification, clinical, and imaging data, a structured pathological type classification model for pancreatic cystic lesions is constructed to distinguish the pathological types of pancreatic cystic lesions. This invention solves the problems of inaccurate classification due to missing original clinical data, the impact of bias in original imaging data on classification accuracy, the disordered data types and lack of standardized processing, and the difficulty in distinguishing pathological types of pancreatic cystic lesions due to the lack of a systematic approach, achieving accurate and efficient classification of pancreatic cystic tumor pathological types.
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