# US 2023/0054619 A1 · Validation of ai-based result data > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2023/0054619 A1 - Document ID: US20230054619A1 - Status: Published application - Kind: A1 - Application number: 17/888,572 - Filed: 2022-08-16 - Published: 2023-02-23 - Earliest claimed: 2021-08-20 - Assignees: Siemens Healthcare GmbH - Applicants: Siemens Healthcare GmbH - Inventors: Andreas FIESELMANN; Christian HUEMMER; Ramyar BINIAZAN; Ludwig RITSCHL - Web page: https://patentgrep.com/patent/US20230054619A1 ## CPC - G06F 18/24317: {Piecewise classification, i.e. whereby each classification requires several discriminant rules} - G06V 10/776: Validation; Performance evaluation - G06F 18/24765: {Rule-based classification} - G06T 5/50: using two or more images, e.g. averaging or subtraction - G06T 5/70: Denoising; Smoothing - G06V 10/751: {Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching} - G06V 10/765: {using rules for classification or partitioning the feature space} - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL ## Abstract In a method, comparison features are extracted from labeled reference image data. Features are also extracted from the image data. A statistical comparison of the comparison features with the features then takes place. On the basis of the statistical comparison and a quality criterion, the quality of the AI-based result data is determined. A method for correcting result data is additionally described. Furthermore, a method for AI-based acquisition of result data on the basis of measured examination data is described. Also described is a validation entity. An entity for correcting result data is additionally described. Furthermore, an entity for acquiring result data is described. Also described is a medical imaging entity. ## Claims ### Claim 1 A method for validating result data acquired via artificial intelligence (AI), the method comprising: extracting comparison features from reference result data in a rule-based manner; extracting features from the result data; statistically comparing the comparison features with the features; and determining a quality of the result data based on the statistical comparison and a quality criterion. ### Claim 2 (depends on 1) The method as claimed in claim 1, further comprising: acquiring the result data based on image data. ### Claim 3 (depends on 1) The method as claimed in claim 1, wherein the result data comprises: image segmentation data; detected objects; classification data; or regression data. ### Claim 4 (depends on 1) The method as claimed in claim 1, wherein, in the event that the quality criterion is not satisfied, the method comprises: outputting information indicating that a reliability of the result data is not sufficient, or correcting the result data based on the comparison features and rules for the extracting of the comparison features. ### Claim 5 (depends on 1) The method as claimed in claim 1, wherein the comparison features include a reference image noise, and the method further includes comparing, as part of a procedure for reducing image noise of image data, the image noise of the image data with the reference image noise. ### Claim 6 (depends on 5) The method as claimed in claim 5, wherein the reference image noise is broken down into a number of frequency components, and the statistical comparison of the comparison features with the features includes comparing frequency components of the reference image noise with frequency components of the image noise of the image data. ### Claim 7 (depends on 1) A method for correcting result data, the method comprising: determining a validation result based on a method for validating result data as claimed in claim 1; and generating corrected result data in the event that the validation result is negative. ### Claim 8 (depends on 7) The method for correcting result data as claimed in claim 7, wherein the generating of the corrected result data comprises at least one of: capturing substitute result data and replacing the result data with the substitute result data, or correcting the result data directly based on the statistical comparison of the comparison features with the features, wherein the correcting includes correcting an extracted feature such that the extracted feature becomes valid in a statistical comparison with the comparison features, and generating corrected result data based on rules applied during the extracting of the comparison features. ### Claim 9 (depends on 1) A method for AI-based acquisition of result data based on measured examination data, the method comprising: capturing the measured examination data from an examination object; determining result data using AI based on the measured examination data; determining a validation result based on a method as claimed in claim 1; and determining the result data, which has been corrected based on the validation result. ### Claim 10 A validation entity comprising: an extraction unit for rule-based extraction of comparison features from labeled reference result data, and for extraction of features from result data; a comparison unit for statistical comparison of the comparison features with the features; and a validation unit to determine a quality of AI-based result data based on the statistical comparison and a quality criterion. ### Claim 11 (depends on 10) An entity for correcting result data, the entity comprising: a validation entity, as claimed in claim 10, to determine a validation result based on the AI-based result data and the labeled reference result data; and a correction unit to generate corrected result data in the event that the validation result is negative. ### Claim at position 12 ### Claim 12 (depends on 10) An entity for acquiring result data, the entity comprising: an input interface to capture measured examination data from an examination object; a determination unit for AI-based determination of the result data based on the measured examination data; a validation entity, as claimed in claim 10, to determine a validation result based on the result data; and a correction unit to generate corrected result data in the event that the validation result is negative. ### Claim at position 14 ### Claim 13 (depends on 10) A medical imaging entity, comprising: a recording unit to generate image data from an examination region; a determination unit for AI-based determination of result data based on the image data; and a validation entity, as claimed in claim 10, to validate the result data. ### Claim 14 (depends on 1) A non-transitory computer program product including a computer program having program sections that, when executed by at least one processor at a medical imaging entity, cause the medical imaging entity to perform the method of claim 1. ### Claim 15 (depends on 1) A non-transitory computer-readable medium storing program sections that, when executed by at least one processor of a computer unit, cause the computer unit to perform the method of claim 1. ### Claim 16 (depends on 9) The method of claim 9, wherein the measured examination data is medical image data. ### Claim 17 (depends on 7) A method for AI-based acquisition of result data based on measured examination data, the method comprising: capturing the measured examination data from an examination object; determining result data using AI based on the measured examination data; determining a validation result for the result data; and determining corrected result data based on the validation result, according to the method of claim 7. ### Claim 18 A medical imaging entity, comprising: a recording unit to generate image data from an examination region; a determination unit for AI-based determination of result data based on the image data; a validation entity to validate the result data; and an entity for correcting result data, as claimed in claim ### Claim 19 A medical imaging entity, comprising: a recording unit to generate image data from an examination region; a determination unit for AI-based determination of result data based on the image data; a validation entity to validate the result data; and an entity for acquiring result data, as claimed in claim ### Claim 20 (depends on 4) The method as claimed in claim 4, further comprising: using, as part of a procedure for reducing image noise of image data, a reference image noise as a comparison feature; and comparing the image noise of the image data with the reference image noise.