Method of automatically correcting mis-orientation of medical images

Abstract

This invention relates to a method and image processing apparatus for automatically correcting mis-orientation of medical images. One or more image processing software modules are used to extract (101) anatomical areas from the medical images. It is determined (103) whether the extracted anatomical areas correspond to reference anatomical areas, but the reference anatomical areas have associated thereto data indicating the orientation of the reference anatomical areas. If the extracted anatomical areas correspond with the reference anatomical areas, the true orientation of the extracted anatomical areas is determined (105) by realigning the medical image until the orientation of the extracted anatomical areas corresponds to the orientation of the reference anatomical areas.

Description

technical field [0001] The invention relates to a method and an image processing device for automatically correcting misorientations of medical images. Background technique [0002] Many vendors in the medical imaging industry have established communication standards to allow medical image data to be transmitted and processed by many different systems. A common standard is the Digital Imaging and Communications in Medicine (DICOM) protocol, which is a standard for the transfer of images and information, and the communication of electronic data, such as medical images and associated metadata, between medical diagnostic and / or imaging systems. transfer related. The DICOM protocol may be employed in communications between medical devices and image archives such as Picture Archiving and Communication Systems (PACS). [0003] The problem, however, is that images from a PACS eg in a hospital are sometimes misoriented, eg mirrored or turned upside down. Such misorientation may o...

AI Technical Summary

Problems solved by technology

This can cause the following problems: i) Any obvious misorientation (such as an image turned upside down) takes extra time for a human reader because the reader has to use the functionality of the visualization application to manually correct the orientation; In the case of a dataset, the reader also has to wait to correct the orientation of the image data; if the stored image data is not corrected for misorientation, the correction may have to be repeated each time the image data is retrieved for viewing, ii) it is not straightforward for the reader Subtle misorientations that are clearly obvious can lead to misdiagnosis and oversight errors, and iii) for automatic image processing algorithms such as computer-aided detection and diagnosis algorithms (CAD), misorientations can have serious consequences, because if the image is not correct orientation, many of these algorithms will fail

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