2020
DOI: 10.1002/mp.14127
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Creation of an anthropomorphic CT head phantom for verification of image segmentation

Abstract: Purpose: Many methods are available to segment structural magnetic resonance (MR) images of the brain into different tissue types. These have generally been developed for research purposes but there is some clinical use in the diagnosis of neurodegenerative diseases such as dementia. The potential exists for computed tomography (CT) segmentation to be used in place of MRI segmentation, but this will require a method to verify the accuracy of CT processing, particularly if algorithms developed for MR are used, … Show more

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Cited by 17 publications
(7 citation statements)
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“…Protected health information was removed from DICOM data sets, so corresponding approval from the local ethical committee was not required. The phantom was printed as a casting mold and filled with gypsum plaster and epoxy resin [34]. Since the DICOM format only represents a twodimensional image of the 3D layer of the body, a high-quality 3D model was created using the "3D Slicer" software.…”
Section: Fabrication Of the 3d Modelmentioning
confidence: 99%
“…Protected health information was removed from DICOM data sets, so corresponding approval from the local ethical committee was not required. The phantom was printed as a casting mold and filled with gypsum plaster and epoxy resin [34]. Since the DICOM format only represents a twodimensional image of the 3D layer of the body, a high-quality 3D model was created using the "3D Slicer" software.…”
Section: Fabrication Of the 3d Modelmentioning
confidence: 99%
“…hold. We have actualized the Dilation operations utilizing a fast-circular convolution method [14]. In the fastcircular convolution technique only defined, the kernel is padded up to the size of the output image for dilation.…”
Section: Region Growingmentioning
confidence: 99%
“…The algorithm was started with the segmentation of the stair objects in the image module. Image segmentation is a technique that divides the image into several regions based on the similarity of pixel values [17][18][19]. Since the stair object is an object with a pixel value of around +350 HU surrounded by water pixels of value around 0 HU [20], segmentation with athreshold value of 300 HU was sufficient to obtain good results (Fig.…”
Section: Automated Measurement Processmentioning
confidence: 99%