Positron Emission Tomography (PET) systems using detectors with Depth of Interaction (DOI) capabilities could achieve higher spatial resolution and better image quality than those without DOI. Up till now, most DOI methods developed are not cost-efficient for a whole body PET system. In this paper, we present a DOI decoding method based on flood map for low-cost conventional block detector with four-PMT readout. Using this method, the DOI information can be directly ex- tracted from the DOI-related crystal spot deformation in the flood map. GATE simulations are then carried out to validate the method, confirming a DOI sorting accuracy of 85.27%. Therefore, we conclude that this method has the potential to be ap- plied in conventional detectors to achieve a reasonable DOI measurement without dramatically increasing their complexity and cost of an entire PET system.

/pdf/a-flood-map-based-doi-decoding-method-for-block-detector-a-4k7033z25y.pdf

A flood map based DOI decoding method for block detector: a GATE simulation study.

Structures were obtained from images with morphological characteristics to register with voxel-based method. We applied simple morphological operations to obtain human brain cortex and chose normalized mutual information as similarity measure for the geometric alignment of PET and MR images. Evaluation used nine patients, and the results showed that sub-voxel accuracy was achieved and the registration process was significantly more rapid. Thus this new automated multi-modality registration method is more robust and has high accuracy.

A novel magnetic resonance-positive emission image registration based on morphology.

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A novel magnetic resonance-positive emission image registration based on morphology.