Evidence map›Paper›PMID 37255576›Full record

ArticleMethodsX2023

Optimization technique for increasing resolution in computed tomography imaging.

I V Grossu, O Savencu, M Verga, N Verga

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Article in MethodsX, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

I V GrossuColtea Clinical Hospital, I.C. Bratianu 1, Bucuresti 030171, Romania.
O Savencu"Carol Davila" University of Medicine and Pharmacy, Dionisie Lupu 37, Bucuresti 020021, Romania.
M VergaEmergency University Hospital, Splaiul Independentei, 169, Bucuresti 050098, Romania.
N Verga"Carol Davila" University of Medicine and Pharmacy, Dionisie Lupu 37, Bucuresti 020021, Romania.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Starting from the importance of conforming to biological reality in medicine, in this paper we propose an optimization technique for increasing resolution of computed tomography (CT) images acquired using various existing scanners. Considering a three-dimensional Hounsfield Units (HU) array, together with the corresponding spatial metadata of interest (pixel sizes and slice thickness), the procedure is based on halving each voxel along the directions of the device's Cartesian frame of reference and find those values which are both satisfying the X-Rays attenuation coefficient average requirement and minimizing the HU distance to classical interpolation points. The discussed method was tested by implementing a C# .Net 6, cross-platform library containing two algorithm flavors that could be independently applied: "Z" for doubling the number of slices, and "XY" for doubling the resolution of individual slices. This design allows also chaining (e.g. one could apply the "Z,XY,Z" sequence in order to reduce four times slice thickness). In the context of existing unavoidable limitations, the first results are suggesting the "CT compatible" interpolation technique could provide a reasonable approximation of reality. However, the main advantage comes from satisfying mass conservation, which is of high importance in medical diagnosis and treatment.•The Hounsfield Units scale is defined as a linear transformation of the X-Rays attenuation coefficients. Thus, splitting a computed tomography voxel into two congruent volumes must satisfy the HU average requirement (the initial value must equal the average of the two output HU values).•Existing interpolation methods (linear, spline, etc.) are not compatible with the computed tomography HU average requirement. This could also result in mass estimate anomalies with significant impact in medical diagnosis.•The proposed "CT compatible" interpolation method is based on finding those values which are both satisfying the X-Rays attenuation coefficient average requirement and minimizing the Hounsfield Units distance to classical interpolation points.

Indexed as

Computed tomographyComputed tomography compatible interpolationInterpolationMedical imagingSuper-resolutionX-Rays attenuation

Identifiers

PMID37255576
PMCPMC10225926

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.