Combining dual-tree complex wavelets and multiresolution in iterative CT reconstruction with application to metal artifact reduction.

Background: This paper investigates the benefits of data filtering via complex dual wavelet transform for metal artifact reduction (MAR). The advantage of using complex dual wavelet basis for MAR was studied on simulated dental computed tomography (CT) data for its efficiency in terms of noise suppression and removal of secondary artifacts. Dual-tree complex wavelet transform (DT-CWT) was selected due to its enhanced directional analysis of image details compared to the ordinary wavelet transform.

Adaptive multiresolution method for MAP reconstruction in electron tomography.

3D image reconstruction with electron tomography holds problems due to the severely limited range of projection angles and low signal to noise ratio of the acquired projection images. The maximum a posteriori (MAP) reconstruction methods have been successful in compensating for the missing information and suppressing noise with their intrinsic regularization techniques. There are two major problems in MAP reconstruction methods: (1) selection of the regularization parameter that controls the balance between the data fidelity and the prior information, and (2) long computation time.

Comparison of manual and automatic techniques for substriatal segmentation in 11C-raclopride high-resolution PET studies.

Background: The striatum is the primary target in regional C-raclopride-PET studies, and despite its small volume, it contains several functional and anatomical subregions. The outcome of the quantitative dopamine receptor study using C-raclopride-PET depends heavily on the quality of the region-of-interest (ROI) definition of these subregions. The aim of this study was to evaluate subregional analysis techniques because new approaches have emerged, but have not yet been compared directly.

A Bayesian approach for suppression of limited angular sampling artifacts in single particle 3D reconstruction.

In the single particle reconstruction, the initial 3D structure often suffers from the limited angular sampling artifact. Selecting 2D class averages of particle images generally improves the accuracy and efficiency of the reference-free 3D angle estimation, but causes an insufficient angular sampling to fill the information of the target object in the 3D frequency space. Similarly, the initial 3D structure by the random-conical tilt reconstruction has the well-known "missing cone" artifact.

Compensation of missing wedge effects with sequential statistical reconstruction in electron tomography.

Electron tomography (ET) of biological samples is used to study the organization and the structure of the whole cell and subcellular complexes in great detail. However, projections cannot be acquired over full tilt angle range with biological samples in electron microscopy. ET image reconstruction can be considered an ill-posed problem because of this missing information.

Evaluation of analytical reconstruction with a new gap-filling method in comparison to iterative reconstruction in [¹¹C]-raclopride PET studies.

Aim: The aim of the study was (1) to evaluate the reconstruction strategies with dynamic [¹¹C]-raclopride human positron emission tomography (PET) studies acquired from ECAT high-resolution research tomograph (HRRT) scanner and (2) to justify for the selected gap-filling method for analytical reconstruction with simulated phantom data.

Methods: A new transradial bicubic interpolation method has been implemented to enable faster analytical 3D-reprojection (3DRP) reconstructions for the ECAT HRRT PET scanner data. The transradial bicubic interpolation method was compared to the other gap-filling methods visually and quantitatively using the numerical Shepp-Logan phantom.

A Monte-Carlo based model of the AX-PET demonstrator and its experimental validation.

AX-PET is a novel PET detector based on axially oriented crystals and orthogonal wavelength shifter (WLS) strips, both individually read out by silicon photo-multipliers. Its design decouples sensitivity and spatial resolution, by reducing the parallax error due to the layered arrangement of the crystals. Additionally the granularity of AX-PET enhances the capability to track photons within the detector yielding a large fraction of inter-crystal scatter events.

Regional compensation for statistical maximum likelihood reconstruction error of PET image pixels.

In positron emission tomography (PET), there is an increasing interest in studying not only the regional mean tracer concentration, but its variation arising from local differences in physiology, the tissue heterogeneity. However, in reconstructed images this physiological variation is shadowed by a large reconstruction error, which is caused by noisy data and the inversion of tomographic problem. We present a new procedure which can quantify the error variation in regional reconstructed values for given PET measurement, and reveal the remaining tissue heterogeneity.

Automatic statistical shape analysis of cerebral asymmetry in 3D T1-weighted magnetic resonance images at vertex-level: application to neuroleptic-naïve schizophrenia.

The study of the structural asymmetries in the human brain can assist the early diagnosis and progression of various neuropsychiatric disorders, and give insights into the biological bases of several cognitive deficits. The high inter-subject variability in cortical morphology complicates the detection of abnormal asymmetries especially if only small samples are available. This work introduces a novel automatic method for the local (vertex-level) statistical shape analysis of gross cerebral hemispheric surface asymmetries which is robust to the individual cortical variations.

F-18 fluorodeoxyglucose uptake and water-perfusable tissue fraction in assessment of myocardial viability.

Objectives: (15)O-water-perfusable tissue fraction (PTF) has been shown to be a potential index for assessing myocardial viability in PET, an alternative to (18)F-fluorodeoxyglucose (FDG). This study aimed to directly compare these two independent methods in assessing myocardial viability in patients with abnormal wall motion.

Methods: PET study was performed on 16 patients with previous myocardial infarction, before coronary artery bypass graft operation (CABG).

Error-corrected estimation of regional kinetic parameter histograms directly from pet projections.

Positron emission tomography (PET) is a unique method to investigate physiology in the living body. Kinetic models with kinetic rate constants describe the dynamic radioactive tracer uptake in living tissue. If the variation of the kinetic parameter values within a specific tissue region could be determined accurately, it would give valuable quantitative information about the tissue heterogeneity.

Gap-filling methods for 3D PlanTIS data.

The range of positron emitters and their labeled compounds have led to high-resolution PET scanners becoming widely used, not only in clinical and pre-clinical studies but also in plant studies. A high-resolution PET scanner, plant tomographic imaging system (PlanTIS), was designed to study metabolic and physiological functions of plants noninvasively. The gantry of the PlanTIS scanner has detector-free regions.

Automatic FRAP analysis with inhomogeneous fluorescence distribution and movement compensation.

The analysis of fluorescence recovery after photobleaching (FRAP) data is complicated by the measurement noise, inhomogeneous fluorescence distribution, and image movement during experiment. Conventionally, these issues are tackled by data preprocessing and averaging, which causes loss of quantitative properties. In this study, we present a method which automatically estimates and compensates both the movement and inhomogeneous fluorescence distribution within the data analysis.

Hierarchical classification of dynamically varying radar pulse repetition interval modulation patterns.

The central purpose of passive signal intercept receivers is to perform automatic categorization of unknown radar signals. Currently, there is an urgent need to develop intelligent classification algorithms for these devices due to emerging complexity of radar waveforms. Especially multifunction radars (MFRs) capable of performing several simultaneous tasks by utilizing complex, dynamically varying scheduled waveforms are a major challenge for automatic pattern classification systems.

Automatic cerebral and cerebellar hemisphere segmentation in 3D MRI: adaptive disconnection algorithm.

This paper describes the automatic Adaptive Disconnection method to segment cerebral and cerebellar hemispheres of human brain in three-dimensional magnetic resonance imaging (MRI). Using the partial differential equations based shape bottlenecks algorithm cooperating with an information potential value clustering process, it detects and cuts, first, the compartmental connections between the cerebrum, the cerebellum and the brainstem in the white matter domain, and then, the interhemispheric connections of the extracted cerebrum and cerebellum volumes. As long as the subject orientation in the scanner is given, the variations in subject location and normal brain morphology in different images are accommodated automatically, thus no stereotaxic image registration is required.

Gap-filling for the high-resolution PET sinograms with a dedicated DCT-domain filter.

High-resolution positron emission tomography (PET) scanners have brought many improvements to the nuclear medicine imaging field. However, the mechanical limitations in the construction of the scanners introduced gaps between the detectors, and accordingly, to the acquired projection data. When the methods requiring full-sinogram dataset, e.

Segmentation of striatal brain structures from high resolution PET images.

We propose and evaluate an automatic segmentation method for extracting striatal brain structures (caudate, putamen, and ventral striatum) from parametric (11)C-raclopride positron emission tomography (PET) brain images. We focus on the images acquired using a novel brain dedicated high-resolution (HRRT) PET scanner. The segmentation method first extracts the striatum using a deformable surface model and then divides the striatum into its substructures based on a graph partitioning algorithm.

ICA based automatic segmentation of dynamic H(2)(15)O cardiac PET images.

In this study, we applied an iterative independent component analysis (ICA) method for the separation of cardiac tissue components (myocardium, right, and left ventricle) from dynamic positron emission tomography (PET) images. Previous phantom and animal studies have shown that ICA separation extracts the cardiac structures accurately. Our goal in this study was to investigate the methodology with human studies.

Joint penalized-likelihood reconstruction of time-activity curves and regions-of-interest from projection data in brain PET.

This paper presents a novel statistical approach for joint estimation of regions-of-interest (ROIs) and the corresponding time-activity curves (TACs) from dynamic positron emission tomography (PET) brain projection data. It is based on optimizing the joint objective function that consists of a data log-likelihood term and two penalty terms reflecting the available a priori information about the human brain anatomy. The developed local optimization strategy iteratively updates both the ROI and TAC parameters and is guaranteed to monotonically increase the objective function.

Cholesterol substitution increases the structural heterogeneity of caveolae.

Caveolin-1 binds cholesterol and caveola formation involves caveolin-1 oligomerization and cholesterol association. The role of cholesterol in caveolae has so far been addressed by methods that compromise membrane integrity and abolish caveolar invaginations. To study the importance of sterol specificity for the structure and function of caveolae, we replaced cholesterol in mammalian cells with its immediate precursor desmosterol by inhibiting 24-dehydrocholesterol reductase.

Evaluation of the automatic three-dimensional delineation of caudate and putamen for PET receptor occupancy studies.

Objective: PET receptor occupancy studies with a baseline study and an intervention study are increasingly used as an aid in dose-finding procedures for central nervous system drug development. The aim of this study was to evaluate, and confirm the feasibility of two automatic, paired, three-dimensional delineation methods of striatal structures (caudate and putamen) for the purposes of PET receptor occupancy studies.

Methods: The automatic extraction was done with the deformable surface models from PET binding potential images.

Genetic algorithms for finite mixture model based voxel classification in neuroimaging.

Finite mixture models (FMMs) are an indispensable tool for unsupervised classification in brain imaging. Fitting an FMM to the data leads to a complex optimization problem. This optimization problem is difficult to solve by standard local optimization methods, such as the expectation-maximization (EM) algorithm, if a principled initialization is not available.

Voxel-based NK1 receptor occupancy measurements with [(18)F]SPA-RQ and positron emission tomography: a procedure for assessing errors from image reconstruction and physiological modeling.

Purpose: Receptor occupancy studies with positron emission tomography (PET) are widely used as aids in the drug development process. This study introduces a general procedure for assessing errors that arise from the applied image processing methods in PET receptor occupancy studies using the neurokinin-1 (NK1) receptor occupancy study as an example.

Procedures: The bias and variance among eight combinations of image reconstruction and model calculation methods for estimating voxel-level receptor occupancy results were examined.

Alignment of 3-dimensional cardiac structures in O-15-labeled water PET emission images with mutual information.

Background: The aim of this study was to develop a method to correct the heart position between two oxygen 15-labeled water cardiac positron emission tomography (PET) image sets to be able to use the equivalent regions of interest for the quantification of the perfusion values in the same myocardial segments.

Methods And Results: Independent component analysis was applied to the dynamic image sets (simulated phantom and 6 rest-pharmacologic stress and 10 rest-rest image sets of healthy female volunteers) acquired at different time points to separate the cardiac structures (ventricles and myocardium). The separated component images from independent component analysis from the 2 studies of the same individual were aligned with a normalized mutual information-based registration method.