Hot spot detection, segmentation, and identification in PET images

Thomas Blaffert; Kirsten Meetz

doi:10.1117/12.651648

15 March 2006 Hot spot detection, segmentation, and identification in PET images

Thomas Blaffert, Kirsten Meetz

Proceedings Volume 6144, Medical Imaging 2006: Image Processing; 614457 (2006) https://doi.org/10.1117/12.651648
Event: Medical Imaging, 2006, San Diego, California, United States

Abstract

Positron Emission Tomography (PET) images provide functional or metabolic information from areas of high concentration of [18F]fluorodeoxyglucose (FDG) tracer, the "hot spots". These hot spots can be easily detected by the eye, but delineation and size determination required e.g. for diagnosis and staging of cancer is a tedious task that demands for automation. The approach for such an automated hot spot segmentation described in this paper comprises three steps: A region of interest detection by the watershed transform, a heart identification by an evaluation of scan lines, and the final segmentation of hot spot areas by a local threshold. The region of interest detection is the essential step, since it localizes the hot spot identification and the final segmentation. The heart identification is an example of how to differentiate between hot spots. Finally, we demonstrate the combination of PET and CT data. Our method is applicable to other techniques like SPECT.

Citation Download Citation

Thomas Blaffert and Kirsten Meetz "Hot spot detection, segmentation, and identification in PET images", Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 614457 (15 March 2006); https://doi.org/10.1117/12.651648

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