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M Landmann

Publications and source records attributed to M Landmann.

2 recordsLinked to original sources

Internal radionuclide therapy: software for treatment planning using tomographic data.

AIM: Accurate dosimetry must be performed for each patient before therapy with unsealed radionuclides. Recently, the software tool ULMDOS was developed to facilitate planar dosimetric calculations and to support traceability and documentation as a prerequisite for good clinical practice. Here, the extended version of ULMDOS for processing of tomographic data is presented. METHODS: ULMDOS is developed in IDL 6.1 (Interactive Data Language) under Windows XP/2000. Serial tomographic data can be loaded in an ECAT7 or DICOM format, and presented as maximum intensity projection. The definition of volumes of interest is supported by various tools (e.g., freehand, isocontour, polygon), region growing, and cluster analysis. Residence times are calculated from fits of the time activity data to exponential functions. RESULTS, DISCUSSION: Quantitative 3-dimensional data allow performing a more individualized dosimetry, as problems due to organ overlay, insufficient attenuation and scatter correction in the planar approach can be avoided. For traceability, documentation, retrospective examination and later processing all data can be saved in binary or ASCII format. Dosimetric calculations can be conducted within a single environment, thus it spares the time-consuming transfer of data between different software tools.

Humans↗

Simultaneous iterative reconstruction of emission and attenuation images in positron emission tomography from emission data only.

For quantitative image reconstruction in positron emission tomography attenuation correction is mandatory. In case that no data are available for the calculation of the attenuation correction factors one can try to determine them from the emission data alone. However, it is not clear if the information content is sufficient to yield an adequate attenuation correction together with a satisfactory activity distribution. Therefore, we determined the log likelihood distribution for a thorax phantom depending on the choice of attenuation and activity pixel values to measure the crosstalk between both. In addition an iterative image reconstruction (one-dimensional Newton-type algorithm with a maximum likelihood estimator), which simultaneously reconstructs the images of the activity distribution and the attenuation coefficients is used to demonstrate the problems and possibilities of such a reconstruction. As result we show that for a change of the log likelihood in the range of statistical noise, the associated change in the activity value of a structure is between 6% and 263%. In addition, we show that it is not possible to choose the best maximum on the basis of the log likelihood when a regularization is used, because the coupling between different structures mediated by the (smoothing) regularization prevents an adequate solution due to crosstalk. We conclude that taking into account the attenuation information in the emission data improves the performance of image reconstruction with respect to the bias of the activities, however, the reconstruction still is not quantitative.

Algorithms↗