# US 2019/0244353 A1 · Device and method for quality assessment of medical image datasets > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2019/0244353 A1 - Document ID: US20190244353A1 - Status: Published application - Kind: A1 - Application number: 16/339,053 - Filed: 2017-10-25 - Published: 2019-08-08 - Earliest claimed: 2016-10-25 - Assignees: Koninklijke Philips N.V. - Applicants: Koninklijke Philips N.V. - Inventors: Thomas BUELOW; Stewart YOUNG; Tanja NORDHOFF; Tim Philipp HARDER; Jan-Hendrik BUHK - Web page: https://patentgrep.com/patent/US20190244353A1 ## CPC - G06T 7/0014: {using an image reference approach} - A61B 6/032: {Transmission computed tomography [CT]} - A61B 6/501: {for diagnosis of the head, e.g. neuroimaging or craniography} - A61B 6/5258: {involving detection or reduction of artifacts or noise} - G16H 30/40: for processing medical images, e.g. editing - G16H 40/20: for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms - G16H 40/63: for local operation - G06T 2207/10081: Computed x-ray tomography [CT] - G06T 2207/30016: Brain - G06T 2207/30168: Image quality inspection - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) - G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA ## Abstract The present invention relates to a device and method for quality assessment of medical image datasets. To enable an automatic quality assessment of medical image datasets to identify potential errors or deviations that may be avoided in future imaging operations, the device comprises an image input (21) for obtaining medical image datasets together with respective acquisition information, each medical image dataset being acquired by scanning a field of view, FOV, of an examination object and the respective acquisition information representing information related to the acquisition of the respective medical image dataset; an image analysis unit (22) for comparing the FOV of an obtained medical image dataset with a reference FOV and for determining difference information indicating deviations of the FOV from the reference FOV; a correlation unit (23) for determining correlation information indicating correlations between the difference information determined for a plurality of obtained medical image datasets and the respective acquisition information; and an output unit (24) for issuing the determined correlation information. ## Claims ### Claim 1 A device for quality assessment of medical image datasets, said device comprising: an image input for obtaining medical image datasets together with respective acquisition information, each medical image dataset being acquired by scanning a field of view, FOV, of an examination object and the respective acquisition information representing information related to the acquisition of the respective medical image dataset; an image analysis unit for comparing the FOV of an obtained medical image dataset with a reference FOV and for determining difference information indicating deviations of the FOV from the reference FOV; a correlation unit for determining correlation information indicating correlations between the difference information determined for a plurality of obtained medical image datasets and the respective acquisition information; and an output unit for issuing the determined correlation information. ### Claim 2 (depends on 1) The device as claimed in claim 1, wherein said image analysis unit is configured to determine the reference FOV for comparison with the FOV of an obtained medical image dataset from said medical image dataset. ### Claim 3 (depends on 1) The device as claimed in claim 1, wherein said image analysis unit is configured to determine the reference FOV, one or more borders of the reference FOV, by use of anatomical landmarks within the obtained medical image dataset. ### Claim 4 (depends on 1) The device as claimed in claim 1, wherein said image analysis unit is configured to determine the reference FOV such that a predetermined anatomical region, predetermined one or more sensitive organs, are excluded from the reference FOV. ### Claim 5 (depends on 1) The device as claimed in claim 1, wherein said image analysis unit is configured to obtain the reference FOV for comparison with the FOV of an obtained medical image dataset from a database, an anatomical atlas, based on said medical image dataset. ### Claim 6 (depends on 1) The device as claimed in claim 1, wherein said image analysis unit is configured to determine difference information indicating deviations of the FOV from the reference FOV with respect to a predetermined condition, a predetermined anatomical region. ### Claim 7 (depends on 1) The device as claimed in claim 1, wherein said image analysis unit is configured to determine first if an obtained medical image dataset complies with a predetermined condition, if it contains a predetermined anatomical region, and to compare the FOV of an obtained medical image dataset with a reference FOV and to determine difference information for an obtained medical image dataset only if it has been determined that the obtained medical image dataset complies with a predetermined condition. ### Claim 8 (depends on 1) The device as claimed in claim 1, wherein said image analysis unit is configured to determine difference information comprising translational information indicating deviations in size and/or one or more borders of the FOV of an obtained medical image dataset with respect to a reference FOV. ### Claim 9 (depends on 1) The device as claimed in claim 1, wherein said image analysis unit is configured to determine difference information comprising rotational information indicating deviations of the FOV of an obtained medical image dataset with respect to a reference FOV in one or more rotational directions around one or more different rotational axes. ### Claim 10 (depends on 1) The device as claimed in claim 1, wherein said image analysis unit is configured to determine difference information comprising presence information indicating the extent of presence of a predetermined anatomical region, one or more sensitive organs, in the FOV of an obtained medical image dataset. ### Claim 11 (depends on 1) The device as claimed in claim 1, wherein said acquisition information comprises at least one of temporal information indicating the time, the day of the week and the time of day, of the acquisition of the respective medical image dataset, object information indicating the condition of the imaged examination object, position information indicating the position of the examination object with respect to an imaging device by which the respective medical image dataset has been acquired, and operator information about the operator indicating the operator who carried out the acquisition of respective medical image dataset. ### Claim 12 (depends on 4) The device as claimed in claim 4, wherein said medical image datasets are CT image datasets, of a human head, wherein said predetermined anatomical region are the eyes and said anatomical landmarks are the left and right supra orbital ridges and the opisthion of the occipital bone. ### Claim 13 (depends on 1) An imaging system comprising an image acquisition system for acquiring medical image datasets of examination objects, and a device as claimed in claim 1 for quality assessment of acquired medical image datasets. ### Claim 14 A method for quality assessment of medical image datasets, said method comprising: obtaining medical image datasets together with respective acquisition information, each medical image dataset being acquired by scanning a field of view, FOV, of an examination object and the respective acquisition information representing information related to the acquisition of the respective medical image dataset; comparing the FOV of an obtained medical image dataset with a reference FOV; determining difference information indicating deviations of the FOV from the reference FOV; determining correlation information indicating correlations between the difference information determined for a plurality of obtained medical image datasets and the respective acquisition information; and issuing the determined correlation information. ### Claim 15 (depends on 14) A computer program comprising program code means for causing a computer to carry out the steps of the method as claimed in claim 14 when said computer program is carried out on the computer.