AI Article Synopsis

  • The study investigates four segmentation methods for accurately identifying regions of interest in SPET images.
  • The methods compared are fixed thresholding (FT), grey level histogram (GL), region growing (RG), and combined region growing and edge detection (RGE) using an elliptical phantom with varying volumes and activities of radionuclides.
  • FT and RG were found to offer effective volume measurements across different conditions, while GL showed less reliable results; however, all methods need optimization through phantom measurements before clinical application.

Article Abstract

Objective determination of regions of interest (ROIs) is a prerequisite for the accurate quantification of radionuclide volume distributions in single photon emission tomographic (SPET) images. In this study, we compared four segmentation methods: fixed thresholding (FT), grey level histogram (GL), region growing (RG) and combined region growing and edge detection (RGE). For this purpose, an elliptical phantom containing two cylinders with varying volumes (8-360 ml) and activities of 111In and 99Tcm (2.9-37 kBq ml-1) was employed. Using these methods, the following correlation was observed between true and measured phantom volumes: 111In, r = 0.95 (FT), 0.73 (GL), 0.93 (RG) and 0.92 (RGE); 99Tcm, r = 0.85 (FT), 0.72 (GL), 0.85 (RG) and 0.89 (RGE). Volume determination with FT and RG was not sensitive to the cut-off frequency used in image filtering. A significant correlation was observed between spleen volumes measured with the different segmentation methods, except GL, when applied to the SPET images of 25 patients administered 111In-labelled platelets. On the basis of these results, FT and RG are recommended for the clinical determination of ROIs, although they can be difficult to apply if the signal-to-noise ratio is very low or highly variable, when a combination of different imaging modalities may be the only accurate solution to the segmentation problem. The RGE method can also produce accurate results, but estimation of parameters is laborious with this method. Before being applied clinically, all segmentation methods tested in this study require phantom measurements for the determination of optimal parameters.

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http://dx.doi.org/10.1097/00006231-199505000-00009DOI Listing

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