An automatic classification technique for attenuation correction in positron emission tomography

Abstract

In this paper a clustering technique is proposed for attenuation correction (AC) in positron emission tomography (PET). The method is unsupervised and adaptive with respect to counting statistics in the transmission (TR) images. The technique allows the classification of pre- or post-injection TR images into main tissue components in terms of attenuation coefficients. The classified TR images are then forward projected to generate new TR sinograms to be used for AC in the reconstruction of the corresponding emission (EM) data. The technique has been tested on phantoms and clinical data of brain, heart and whole-body PET studies. The method allows: (a) reduction of noise propagation from TR into EM images, (b) reduction of TR scanning to a few minutes (3 min) with maintenance of the quantitative accuracy (within 6%) of longer acquisition scans (15-20 min), (c) reduction of the radiation dose to the patient, (d) performance of quantitative whole-body studies.

Ultra Low Dose CT Attenuation Correction Maps for Emission Computed Tomography

“…The region grower also has the ability to iterate around this critical point, and thus overcomes gross region underestimates caused by potentially large incremental step size. The resulting grown regions were stored as templates for the five different tissue types of interest, 3 I for Lung, 4 I for Bone, 5 I for soft tissue and 6 I for dense tissue. The purpose of the region grower is to provide a refinement on the tissue templates produced by globally thresholding the intensity values via the k-means algorithm.…”

Attenuation Correction Strategies in Emission Tomography

“…The majority of segmentation methods used for attenuation correction fall into one of the following two classes (see chapter 10): histogram-based thresholding techniques 72,73 and fuzzy-clustering based segmentation techniques. 74,75 Threshold approaches use the grey-level histogram counts to distinguish between regions. However, if the geometry of the attenuation map is based solely on the characteristics of the histogram, the technique is most likely to fail in regions where the total number of counts is small (e.g.…”

Evaluation of Transmission Methodology for the microPET Focus 220 Animal Scanner

“…The segmentation method introduced by Bettinardi et al [11] is an automated adaptive clustering method. The main properties of this technique are that there are no a priori assumptions made about the number of clusters and the centroid values.…”

“…To achieve low noise levels for short acquisition times of transmission data, methods of segmentation have been introduced (e.g. [9] - [11]) which result in an essentially noiseless image and potentially more accurate estimate of attenuation.…”

“…• To evaluate the potential role of segmentation of the attenuation images in reducing bias and noise propagation (based on the method developed by Bettinardi et al [11]). Ge a point source with activity ranging from 11.5-14 MBq was used.…”