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Phase retrieval from Fresnel diffraction patterns is a nonlinear ill-posed inverse problem of paramount importance in various areas of applied physics. Recently a new non-linear iterative algorithm based on a Landweber method with an analytic calculation of the Frechet derivative adjoint has been proposed. In this work, we refine this scheme by introducing Fienup projectors in the algorithm. The new...
Due to high scattering effects inside lumen, detection of luminal borders in intravascular ultrasound (IVUS) images becomes challenging when high frequency transducers are employed. In this paper, we further study previously developed three-dimensional (3D) multiscale overcomplete brushlet-driven harmonic analysis, motivated by what experts visually do, to trace the lumen borders by exploiting spatial...
We present an attempt at characterizing local patterns of cortical folding, an open problem in neuroscience. The technique is applied to an extremely variable sulcus: the left inferior frontal sulcus (LIFS). Our approach is based on the use of an average template as a reference to define features that characterize the position, presence, and orientation of elementary sulcal elements of the LIFS. Clustering...
Dynamic contrast enhanced magnetic resonance (DCE-MR) imaging is an exciting tool to study the pharmacokinetics of a suspected tumor tissue. Nonetheless, the inevitable partial volume effect in DCE-MR images may seriously hinder the quantitative analysis of the kinetic parameters. In this work, based on the conventional three-tissue compartment model, we propose an unsupervised nonnegative blind source...
In this work, we present an automatic branch and stenoses detection method that is capable of detecting all types of plaques in Computed Tomography Angiography (CTA) modality. Our method is based on the vessel extraction algorithm we proposed in [1], and detects branches and stenoses in a very fast way. We demonstrate the performance of our branch detection method on 3 complex tubular structured synthetic...
In a prior contribution, we described a semi-automated system that allowed a user to quantify the relative abundance of fluorescently labeled membrane proteins in confocal microscopy images. Here, we describe a step change in assay automation, enabled by explicitly casting the problem in terms of mathematical graphs. This permitted to include extensive and relevant image information in the tracing...
Tree-like vessel structures are an information-rich source for many image analysis tasks. Hence tracking algorithms extracting such structures have wide applicability. However, due to image artifacts and the minute nature of vessels, these algorithms face several challenges; two of the most common ones are 1) early termination, where tracking stops before the structure ends and 2) leaking, where tracking...
We propose a new feature that can be used to automatically detect cerebral aneurysms in angiographic images. It combines both low-level and high-level features to a feature indicating aneurysms. The feature is used in a system for aneurysm detection in two types of magnetic resonance angiography (MRA) images and computed tomography angiography (CTA) images. The method was tested on 66 angiographic...
We propose a novel affinity matrix for image segmentation in this paper. The affinity matrix is constructed by using the Gaussian weighted Chi-square distance with neighborhood information, in which the vital spatial structure of the image is considered. An adaptive local scaling parameter is used to refine the segmentation rather than selecting a single scaling parameter. We demonstrate that graph-based...
We introduce a novel boosting algorithm to boost — i.e. improve on — existing methods for deformable image registration. The proposed DIRBoost algorithm is inspired by the theory on hypothesis boosting, well-known in the field of machine learning. DIRBoost involves a classifier for landmark-based Registration Error Detection (RED). Based on these RED predictions a Voronoi tessellation is generated...
Positron emission tomography and computed tomography (PET-CT) is widely accepted as the best imaging in the management of cancer. To assess response to treatment, multiple scans of a patient are usually acquired and tumour changes are analysed at different stages during the treatment. However, it is difficult to assimilate these changes, especially where a patient has in excess of e.g. four temporal...
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