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Diabetic Retinopathy (DR) is a vascular disorder affecting the retina due to prolonged Diabetes. It can lead to sudden vision loss in advanced stages. Screening and routine monitoring is the most effective way of avoiding vision loss due to DR. Abramoff et al. developed and evaluated an automated DR screening system. One of the most important parts of this system, the information fusion module, combines...
In this paper we apply the random walk-based segmentation method to mesothelioma CT image datasets, aiming to establish an automatic segmentation routine that can provide volumetric assessments for monitoring progression of the disease and its treatments. We have validated the applicability of this method to our image data through a series of experimental trials, and demonstrated the superior performance...
We describe a novel method to segment the bladder wall in magnetic resonance imaging (MRI) to support the detection of disease, such as endometriosis, and for surgical planning. We segment the inner and outer wall boundary using T2- and T1-weighted MRI images, respectively. A new coupling technique for level sets is formulated and tested on 54 T2- and T1-weighted image pairs. A local phase based dimensionless...
Positron emission tomography (PET) is a molecular imaging technique which provides important functional information about the human body. However, thoracic PET images are often substantially degraded by respiratory motion, which adversely impacts on subsequent diagnosis. In this paper, a motion correction and attenuation correction method is proposed to correct for motion in respiratory gated PET...
The aim of this paper is to introduce effects well known to clinicians -but neglected to date- in the biomechanical modelling of breast malignant tumours. We develop a model of an isolated stellate breast tumour under mammographic compression forces. We study a range of reported mechanical properties, both linear elastic and hyperelastic. We also introduce different volumes of increased density/stiffness...
Our recent adaptation to PET of the method of Fitchard et al., for rigid body registration of CT sinograms enables motion between two temporal frames of PET data to be estimated and corrected prior to reconstruction. This avoids both the computation required by multiple reconstructions and the need to make choices regarding reconstruction methods that influence the images produced, and potentially...
We present a feature point detection algorithm which we use for non-rigid registration, illustrated for breast images (mammography, MRI). By associating the continuous intrinsic dimensionality of image structure with the output of a scale saliency algorithm, breast boundary points can be separated from internal feature points. Correspondences established for the breast boundary and internal feature...
Colorectal cancer is the third most common cancer diagnosed in men and women. Generally surgery is by total excision of the mesorectum (TME), though it often has a poor outcome due to affected lymph nodes close to the resection boundary. Advancements in diagnosis and treatment of colorectal cancer require integration of information from different sources such as pathology macroscopic and microscopic...
We develop a novel simultaneous reconstruction and registration algorithm for limited view transmission tomography. We derive a cost function using Bayesian probability theory, and propose a similarity metric based on the explicit modeling of the joint histogram as a sum of bivariate clusters. The resulting algorithm shows a robust mitigation of the data insufficiency problem in limited view tomography...
Monte Carlo-based PET simulators are powerful tools in the evaluation and validation of new PET algorithms. Accurate generation of projection data from spatiotemporal tracer distributions enable, for a given scanner specification and attenuating media distribution, quantitative analysis based on known ground truth. High activity-related phenomena, such as the contribution of randoms, as well as block...
We apply the joint entropy prior to limited view transmission tomography and demonstrate its sensitivity to local optima. We propose to increase robustness by modelling the joint histogram as the sum of a limited number of bivariate clusters. The method is illustrated for the case of Gaussian distributions. This approximation increases robustness by reducing the possible number of local optima in...
The aim of this work is to segment, and quantify, the vasculature of tumours, based on fluorescent microscope 3D images. Such images have poor contrast and the vascular features vary substantially within a 3D volume. In this paper, we introduce a method to estimate local phase in 3D images based on the monogenic signal theory, and illustrate its performance on our vasculature images.
The (semi-) automatic detection of significant (feature) points is a key task in in vivo assessment of cancer staging and progression. However, this is a challenging task due to the relatively poor signal-to-noise, limited resolution and variable intensity of medical images. We propose to use phase congruence (PC), the Morrone and Owens (1987) feature model, to extract local descriptors. We overcome...
Dynamic PET enables quantitative analysis of in-vivo metabolic activity. Commonly, each image in a temporal sequence is reconstructed independently using standard methods developed for static PET.We present reconstruction methods which use Empirical Mode Decomposition (EMD) based regularization. The methods extend conventional static OSEM reconstruction to ensure consistency between temporal frames...
There are various issues that limit the development and deployment of new software solutions in cancer image analysis research. In this paper we discuss some of these and propose a framework design based on cloud computing concepts, Microsoft technologies, existing middleware and imaging toolkits. Furthermore, we address some of these issues by introducing collaborative visual tools for visual input...
Tomographic reconstruction of fluorescence optical projection tomography (OPT) data is usually performed using the standard filtered back projection (FBP) algorithm. However, there are several physical aspects of fluorescence OPT that pose major challenges for the FBP algorithm. These include blurring, and the fact that for an isotropically emitting point source (or fluorophore), the power received...
We propose a nonrigid registration algorithm and apply it to align pre- and post-chemotherapy colorectal MRI images. The algorithm combines feature-based and intensity-based image registration methods. We use local phase, as computed by monogenic signal, as the feature descriptor, and as the similarity measure in the registration algorithm, phase mutual information, which is estimated using NP windows,...
Segmenting transparent phase objects, such as biological cells from brightfield microscope images, is a difficult problem due to the lack of observable intensity contrast and noise. Previous image analysis solutions have used excessive de- focusing or physical models to obtain the underlying phase properties. Here, an improved cell boundary detection algorithm is proposed to accurately segment multiple...
We present a new reconstruction algorithm for emission and transmission tomography. The algorithm performs maximum likelihood reconstruction and doubly stochastic segmentation simultaneously. The resulting reconstructions show promising edge-preservation as well as suppression of measurement noise.
The extraction of features for automated assessment for breast cancer detection and diagnosis requires identification of the breast tissue. The pectoral muscle in medio-lateral oblique (MLO) mammogram images is one of the few landmarks in the breast. Yet, it can bias and affect the results of any mammogram processing method. To avoid such effects it is often necessary to automatically identify and...
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