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dc.contributor.authorHillel, Philip G
dc.contributor.authorHastings, David L
dc.date.accessioned2010-05-24T16:16:28Z
dc.date.available2010-05-24T16:16:28Z
dc.date.issued1993-05
dc.identifier.citationA three-dimensional second-derivative surface-detection algorithm for volume determination on SPECT images. 1993, 38 (5):583-600 Phys Med Biolen
dc.identifier.issn0031-9155
dc.identifier.pmid8321888
dc.identifier.doi10.1088/0031-9155/38/5/002
dc.identifier.urihttp://hdl.handle.net/10541/99770
dc.description.abstractMost existing techniques for determining volumes on single-photon-emission computed tomography (SPECT) data employ thresholding, two-dimensional edge detection, or manual delineation of edges. These methods, however, are limited in both accuracy and applicability. In seeking to overcome these limitations, a truly three-dimensional (3D) second-derivative-based algorithm which can be implemented with relative ease has been developed. The method incorporates 3D matrix operators; these are convoluted with the SPECT count data in order to produce a 3D voxel map whose data elements correspond to the second derivative of counts in the image. This map is then searched, a suitable derivative-based edge-defining criterion being applied to each voxel position, in order to locate the derivative surface boundary which defines the volume. Validation is obtained using phantom data from 99Tcm-filled bottles of volumes 200, 580 and 2500 cm3 placed within a body-sized tank containing background activities set to give a range of contrasts between 1.00 and 0.75 (i.e. background 0% to 25%). The performance of the algorithm is encouraging: the volumes of the two larger bottles are determined to within a 3% accuracy without the need for any prior calibration, and the results obtained over all bottle sizes are found to be contrast independent to within approximately 4%.
dc.language.isoenen
dc.subject.meshAlgorithms
dc.subject.meshHumans
dc.subject.meshImage Processing, Computer-Assisted
dc.subject.meshModels, Structural
dc.subject.meshReproducibility of Results
dc.subject.meshSoftware
dc.subject.meshTomography, Emission-Computed, Single-Photon
dc.titleA three-dimensional second-derivative surface-detection algorithm for volume determination on SPECT images.en
dc.typeArticleen
dc.contributor.departmentNorth Western Medical Physics Department, Christie Hospital NHS Trust, Manchester, UK.en
dc.identifier.journalPhysics in Medicine and Biologyen
html.description.abstractMost existing techniques for determining volumes on single-photon-emission computed tomography (SPECT) data employ thresholding, two-dimensional edge detection, or manual delineation of edges. These methods, however, are limited in both accuracy and applicability. In seeking to overcome these limitations, a truly three-dimensional (3D) second-derivative-based algorithm which can be implemented with relative ease has been developed. The method incorporates 3D matrix operators; these are convoluted with the SPECT count data in order to produce a 3D voxel map whose data elements correspond to the second derivative of counts in the image. This map is then searched, a suitable derivative-based edge-defining criterion being applied to each voxel position, in order to locate the derivative surface boundary which defines the volume. Validation is obtained using phantom data from 99Tcm-filled bottles of volumes 200, 580 and 2500 cm3 placed within a body-sized tank containing background activities set to give a range of contrasts between 1.00 and 0.75 (i.e. background 0% to 25%). The performance of the algorithm is encouraging: the volumes of the two larger bottles are determined to within a 3% accuracy without the need for any prior calibration, and the results obtained over all bottle sizes are found to be contrast independent to within approximately 4%.


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