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The recent introduction of high-resolution molecular imaging technology is considered by many experts as a major breakthrough that will potentially lead to a revolutionary paradigm shift in health care and revolutionize clinical practice. This paper intends to balance the capabilities of the two major molecular imaging modalities used in nuclear medicine,(More)
Reliable attenuation correction methods for quantitative emission CT (ECT) require accurate delineation of the body contour and often necessitate knowledge of internal anatomic structure. Two broad classes of methods have been used to calculate the attenuation map: transmission-less and transmission-based attenuation correction techniques. Whereas(More)
Historically, anatomical CT and MR images were used to delineate the gross tumour volumes (GTVs) for radiotherapy treatment planning. The capabilities offered by modern radiation therapy units and the widespread availability of combined PET/CT scanners stimulated the development of biological PET imaging-guided radiation therapy treatment planning with the(More)
Photon attenuation in tissues is the primary physical degrading factor limiting both visual qualitative interpretation and quantitative analysis capabilities of reconstructed Positron Emission Tomography (PET) images. This study investigates the implementation and applicability of transmission atlas-guided attenuation correction in cerebral 3D PET imaging,(More)
It has recently been shown that the attenuation map can be estimated from time-of-flight (TOF) PET emission data using joint maximum likelihood reconstruction of attenuation and activity (MLAA). In this work, we propose a novel MRI-guided MLAA algorithm for emission-based attenuation correction in whole-body PET/MR imaging. The algorithm imposes MR spatial(More)
– The maximum likelihood estimation of attenuation and activity (MLAA) has been proposed to jointly estimate activity and attenuation from emission data only. In this paper, we proposed an improved MLAA algorithm by imposing MR spatial and CT statistical constraints on the estimation of attenuation using a constrained Gaussian mixture model (GMM) and a(More)
— Medical volume segmentation is an essential stage in volume processing. This stage is important for tumour classification and quantification in medical volumes particularly in positron emission tomography (PET) imaging. Analysing PET volumes at early stage of illness is important for radiotherapy planning, tumour diagnosis, and fast recovery. There are(More)
In this article, the authors review novel techniques in the emerging field of spatiotemporal four-dimensional (4D) positron emission tomography (PET) image reconstruction. The conventional approach to dynamic PET imaging, involving independent reconstruction of individual PET frames, can suffer from limited temporal resolution, high noise (especially when(More)
PURPOSE Accurate and robust image segmentation was identified as one of the most challenging issues facing PET quantification in oncological imaging. This difficulty is compounded by the low spatial resolution and high noise characteristics of PET images. The fuzzy C-means (FCM) clustering algorithm was largely used in various medical image segmentation(More)
With the arrival of increasingly higher-resolution PET systems, small amounts of motion can cause significant blurring in the resulting images compared with the intrinsic resolution of the PET scanner. The authors review advanced correction methods for unwanted patient motion and for motion due to cardiac and respiratory cycles. A general theme in motion(More)