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In emission tomography (ET), fast developing Bayesian reconstruction methods can incorporate anatomical information derived from co-registered scanning modalities, such as magnetic resonance (MR) and computed tomography (CT). We propose a Bayesian image reconstruction method for single photon emission computed tomography (SPECT), using a joint entropy (JE) similarity measure to embed MR anatomical...
We have developed a visual-tracking-system (VTS) which uses stereo-imaging to track the motion of markers on patients during cardiac SPECT imaging with the goal of using the tracked motion to correct for patient motion. The aim of this study is to determine using MRI in volunteers if the rigid-body-motion (RBM) model can be used to predict the motion of the heart within the chest from the motion of...
Diagnostic magnetic resonance imaging (MRI) for prostate has achieved increasingly higher levels of accuracy. Because real‐time MR‐guided targeted biopsy is still a complicated and expensive procedure, there is considerable interest in a technique of MR/transrectal ultrasound (TRUS) hybridized image‐guided biopsy. However, because the 3‐D shapes of the prostate at the time of image‐acquisition at...
An accurate spatial relationship between 3D in-vivo carotid plaque and lumen imaging and histological cross sections is required to study the relationship between biomechanical parameters and atherosclerotic plaque components. We present and evaluate a fully three-dimensional approach for this registration problem, which accounts for deformations that occur during the processing of the specimens....
Registration algorithms can facilitate the automatic anatomical segmentation of pediatric brain MR data sets when segmentation priors (atlases) are in hand. Automatic segmentation can be achieved through label propagation and label fusion in target space. We investigated the performance of different age cohorts used as prior atlases for the segmentation of 13 MRIs of 1-year-olds. Thirty adults and...
MR images acquired from open magnetic resonance system have been applied to guide percutaneous puncture for ablation of liver tumors recently. However, the MR images do not always show the tumors clearly because of the lower magnetic field (0.5T) and various different surgical and pathological conditions. In our study, we use preoperative CT images to assist locate tumors by registration. In our method,...
This paper presents a glioma modelization method and a regression-like model to create a gradually glioma image (GlioIm). Multimodal signal, images of magnetic resonance imaging (MRI) and in vivo multivoxel MR spectroscopy (MRS) are combined by the regression-like model with spatial resolution registration. This modeling method consists of feature models of glioma such as the signal intensity of MR...
Intraoperative surface contour sensing can enable the registration of high-resolution three-dimensional preoperative images for precise guidance of surgical robots. This is particularly useful for guiding steerable needles in soft tissues. In this paper we combine a new minimally invasive surface scanning technique based on conoscopic holography with a steerable active cannula robot. We experimentally...
In this paper, we present a fast and accurate implementation of the diffusion-based non-rigid registration algorithm. Traditionally, finite differences are used to implement registration algorithms due to their ease of implementation. However, finite differences are sensitive to noise, and they have a narrow numerical stability range. Further, finite differences employ a uniform grid. This is often...
Intensity inhomogeneity is an important phenomenon affecting magnetic resonance imaging, which can greatly affect computational image analysis. Bias correction algorithms are commonly used, but are imperfect, leaving residual inhomogeneity that will usually differ in serial images of the same subject. This differential bias can have a detrimental effect on further processing, such as registration...
Magnetic resonance imaging of the brain at high fields (e.g. 3T) provides high resolution and high signal to noise ratio images suitable for a wide range of clinical applications. However, radiofrequency (or B1) inhomogeneity increases with the magnetic field and produces undesired intensity variations responsible for inaccuracies in quantitative analyses. A method to perform brain segmentation using...
A novel image registration method is presented for multi-modality, gated cardiac imaging. The motion of the myocardium is registered instead of attributes obtained from image intensities, which may be drastically different. Optical flow methods are used to estimate a set of 3D vector fields for both modalities. The 3D vector fields are assumed to be similar and are rigidly aligned by minimizing a...
We describe a probabilistic technique for separating two populations whereby analysis is performed on affine-invariant representations of each patient. The method begins by converting each voxel from a high-dimensional diffusion weighted signal to a low-dimensional diffusion tensor representation. Three orthogonal measures that capture different aspects of the local tissue are derived from the tensor...
This paper presents an automatic method for the segmentation of Optic Pathway Gliomas (OPGs) from multi-spectral MRI datasets. The method starts with the automatic localization of the OPG and its core with an anatomical tumor atlas followed by a binary voxel classification with a probabilistic tissue model whose parameters are estimated from MR images. The method effectively incorporates prior location,...
X-Ray Flouroscopy (XF) is one of the most commonly used imaging techniques in interventional radiology, with the main disadvantage of low soft tissue contrast. XFM tries to overcome this using information from MRI. In XFM, anatomical details gathered from a priori MRI is overlaid on top of live XF images during interventions. To achieve this, registration between MRI and XF spaces should be done,...
We present a novel methodological framework for leveraging multiple image sources, including different modalities, acquisition protocols or image features, in the registration of more than two images via information theoretic data fusion. The technique, referred to as multi-attribute combined mutual information (MACMI), adopts a multivariate application of mutual information (MI) to allow several...
In this paper we propose a variational approach for multimodal image registration based on the diffeomorphic demons algorithm. Diffeomorphic demons has proven to be a robust and efficient way for intensity-based image registration. However, the main drawback is that it cannot deal with multiple modalities. We propose to replace the standard demons similarity metric (image intensity differences) by...
We registered together 13 whole-body MR images of perfusion-fixed mice. Twelve organs in a single mouse were then manually segmented and the labels were propagated to the other mice. Registration performance was evaluated both visually and by averaging the volumes of the individual organs across the mice. We have found an excellent tool for rapidly phenotyping organs in whole body mouse images.
Vascular registration is a challenging problem with many potential applications. However, registering vessels accurately is difficult as they often occupy a small portion of the image and their relative motion/deformation is swamped by the displacements seen in large organs such as the heart and the liver. Our registration method uses a vessel detection algorithm to generate a vesselness image (probability...
This paper presents the first demonstration of real time 3D tracking of organ deformation based on one-sided, limited view needlescopic optical imaging and a single pre-operative MRI/CT scan. The reconstruction is based on the empirical observation that the spherical harmonic coefficients corresponding to distorted surfaces of any given organ lie in lower dimensional spaces that can be learned during...
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