Literature DB >> 32033551

Retrieving 3D medical data along fitted curved slices and their display.

Marco Paluszny1, Dany Ríos2.   

Abstract

BACKGROUND: Computeros tomography and magnetic resonance imaging are usually offered to the clinician in the form of sequences of axial, sagittal and coronal planar cuts. Frequently this does not allow for the full inspection of the morphology of the area of interest, because it is limited by the planarity. Efforts have been made to extract information along curved slices but their planar display is prone to metric deformation.
METHODS: We propose a new visualization alternative of 3D medical volumes using curved slices adapted to areas of interest. We use surfaces fitted to specific organs as visualization canvasses. We describe the differential geometry techniques used to build the surfaces that may be isometrically flattened. These are referred to as develpable surfaces.
RESULTS: We show concrete examples deemed useful for the development of clinical and educational tools. Our examples are centered in magnetic resonance data of the rotator cuff muscle complex and computed tomography data of maxillofacial and dental studies. We also look at the extraction and display of information from volumes of aortic aneurysms along transversal surfaces. DISCUSSION: We look at extensions of the technique and propose further possible clinical use of texturized surfaces in the context of volume navigation.
CONCLUSIONS: We presented a technique to extract information from computer tomography and magnetic resonance volumes, using two different texturization techniques. In the cases that the fitting surfaces are chosen to be developable, they may be flattened without distortion. We also discuss how tu use the technique in other visualization tasks such as volume navigation and detection of volumetric features.

Entities:  

Keywords:  Computed tomography; DICOM; Developable surface; Magnetic resonance

Mesh:

Year:  2020        PMID: 32033551      PMCID: PMC7007650          DOI: 10.1186/s12911-019-1018-2

Source DB:  PubMed          Journal:  BMC Med Inform Decis Mak        ISSN: 1472-6947            Impact factor:   2.796


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