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Increasing the spatial resolution in diffusion-weighted imaging (DWI) is challenging with a single-shot EPI acquisition because of the decreased SNR and T2* relaxation. Recently, acquisition of orthogonal anisotropic acquisitions and super-resolution reconstruction (SRR) of the underlying high-resolution image has been proposed to achieve higher resolution. Promising results have been shown with simulations...
In this paper, a novel electric current flow (ECF) based model is proposed to perform feature based non-rigid brain image registration. The ECF features simultaneously capture both voxel intensity and inter-voxel distance information. In the proposed ECF framework, each voxel is regarded as exhibiting electric potential proportional to voxel intensity. Voxels are connected by conductive wires in a...
Recent advancement in live cell fluorescence microscopy has enabled image acquisition at single particle resolution, through which biologists can investigate the underlying mechanisms of cellular processes. In this paper, we present a method to automatically detect the features of sub-cellular particles in 2D fluorescence images, including x-y positions, fluorescence intensities, and relative sizes...
We consider the problem of localizing renal cancer cell nuclei in Tissue Micro Array (TMA) images. We address this problem in three steps. An initial image processing-based procedure finds potential candidate nuclei, while the subsequent phase employs a trained classifier to prune the candidate cell nuclei found in the first.
Quantification of distinct subcutaneous and visceral fat regions in the abdomen is essential in clinical studies of metabolic disorders and cardiovascular disease. Computed Tomography (CT) is a widely adopted imaging technology for abdominal fat quantification because the intensity range of fat in Hounsfield Units (HU) is distinct from other tissues in the pelvis and abdomen. Nevertheless, it has...
Image registration based on geodesic flows has gained much popularity in recent years. We describe a novel parametrization of the velocity field in a stationary flow equation. We show that the method offers both precision, flexibility, and simplicity of evaluation. With our representation, which is very similar to existing methods, we show that we can find an analytical solution. This solution converges...
Image segmentation and non-rigid registration are two widely investigated tasks in medical image analysis. Concurrent segmentation and registration methods have received considerable attention in recent years. While some models have been shown to give interesting results, most of them are either able to improve segmentation results alone or able to correct rigid rotation and translation only. In addition,...
Longitudinal analysis of anatomical changes is a vital component in many personalized-medicine applications for predicting disease onset, determining growth/atrophy patterns, evaluating disease progression, and monitoring recovery. Estimating anatomical changes in longitudinal studies, especially through magnetic resonance (MR) images, is challenging because of temporal variability in shape (e.g....
This paper describes a method for tracking a tumour using the planar projections of fiducial markers as surrogates. The projections can originate from various sources such as a beam-eye view X-ray, a portal imager or a fluoroscope. The two-dimensional position of the fiducial markers in the planar image in conjunction with a population-based statistical motion model is used to accurately predict and...
Quantitative analysis in medical imaging often relies on anatomical segmentation of MR or CT images. Several multi-atlas based segmentation propagation methods have recently been published due to the accurate structural segmentations produced by propagating and combining manual delineations from multiple templates in a database. We propose a new multi-label local ranking strategy for template selection...
The Free-Form Deformation (FFD) algorithm is a widely-used approach for non-rigid registration. Modifications have previously been proposed to ensure topology preservation and invertibility within this framework. However, in practice, none of these yield the inverse transformation itself, and one loses the parsimonious B-spline parameterisation.
We propose a multi-region approach to tractography that not only allows for competition between seed regions, but also allows for the incorporation of knowledge beyond a local scale. By formulating tractography as a graph-based random walk, we are able to obtain a closed-form solution for connection probabilities. Results on synthetic data and thirty images from the MIDAS database show that the introduction...
In order to detect small-scale deformations during disease propagation while allowing large-scale deformation needed for inter-subject registration, we wish to model deformation at multiple scales and represent the deformation at the relevant scales only. With the LDDMM registration framework, enforcing sparsity results in compact representations but with limited ability to represent deformation across...
This paper proposes a method to build a bone-cartilage atlas of the knee and to use it to automatically segment femoral and tibial cartilage from T1 weighted magnetic resonance (MR) images. Anisotropic spatial regularization is incorporated into a three-label segmentation framework to improve segmentation results for the thin cartilage layers. We jointly use the atlas information and the output of...
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