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Many biomedical applications require detection of curvilinear networks in images, and would benefit from automatic or semiautomatic segmentation to allow high-throughput measurements. Here we discuss a contrast independent approach to identify curvilinear structures based on oriented phase congruency, the Phase Congruency Tensor. We show that the proposed approach is largely insensitive to intensity...
The human brain with all its faculties and intricacies has fascinated many generations of researchers [1] and will likely be the final frontier of science. Understanding the principles underlying the brain's higher-order cognitive functions is indeed a major challenge and will profoundly impact our views on what defines a human being. On a more down-to-earth level, knowledge of the structure, function,...
Better utilizing the vast amount of valuable information stored in the medical imaging databases is always an interesting research area, and one way is to retrieve similar images as a reference dataset to assist the diagnosis. Distance metric is a core component in image retrieval; and in this paper, we propose a new learning-based distance metric design, based on regression and classification techniques...
Imaging of the trabecular bone network has made significant advances in the last decade thanks to the outstanding development of 3D X-ray micro-CT. Compared to standard histomorphometry, this technique provides non-destructively 3D images of the trabecular bone permitting a so-called model-independent quantification of this network. Today, the assessment of the bone Lacuno-Canalicular Network (LCN)...
This study presents a shape and margin characterization method of breast mass lesions in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). The overlap between a mass lesion and its minimum volume enclosing ellipsoid (MVEE) is used to capture the overall shape of a lesion. Various statistical measurements on distance from the lesion surface to its MVEE surface are computed to characterize...
This work introduces a new generic framework to the analysis of ridges and its application to segmentation of planar structures in bioimaging. Based on a Gaussian model, local information associated to ridges is extracted, which actually characterise them. The theoretical basis of the framework is first presented for the one-dimensional case. Its extension to higher dimensions is then shown to be...
Morphology of bones, teeth, and some particular structures are widely used for categorizing species and studying their evolution. In this paper, we used groupwise registration to provide a representative image from the set of the image samples that represents its typical morphology. We also provided perturbation map which indicates the deviation of each point through the ensemble. These images support...
Image reconstruction from limited-angle data is an important issue in diffraction tomography. The limitation of angular coverage usually occurs due to the physical constraints in measurement systems. Insufficient information will deteriorate the quality of reconstructed images. In our experimental setup, the angular range of the data scanning is limited. Here, we applied the iterative algorithm of...
In this paper, we present a new fully automatic approach for noise parameter estimation in the context of fluorescence imaging systems. In particular, we address the problem of Poisson-Gaussian noise modeling in the nonstationary case. In microscopy practice, the nonstationarity is due to the photobleaching effect. The proposed method consists of an adequate moment based initialization followed by...
A population growth model that represents the growth trajectories of individual subjects is critical to study and understand neurodevelopment. This paper presents a framework for jointly estimating and modeling individual and population growth trajectories, and determining significant regional differences in growth pattern characteristics applied to longitudinal neuroimaging data. We use non-linear...
In this paper, we present a new metric combining regional measurements to improve image based population studies that use manifold learning techniques. These studies currently rely on a single score over the whole brain image domain. Thus, they require large amount of training data to uncover spatially complex variation in the whole brain impacted by diseases. We reduce the impact of this issue by...
Linear Minimum Mean Squared Error Estimation (LMMSE) is a simple, yet powerful denoising technique within MRI. It is based on the computation of the mean and variance of the data being filtered according to a noise model assumed, which is usually accomplished by calculating local moments over squared neighborhoods. When these neighborhoods are centered in pixels corresponding to image contours, the...
Pelvic fractures are a major cause of trauma patient mortality. Detection and management of pelvic injuries is challenging due to myriad injury patterns and associated complications such as hemorrhage and infection. In this paper, we propose an automated method of pelvic fracture detection from volumetric CT images. A coarse-to-fine strategy is adopted where a potential region containing the fracture...
Primary ciliary dyskinesia (PCD) implies cilia with dysmotility or total absence of motility, which may result in sinusitis, chronicbronchitis, bronchiectasis and male infertility. A large number of deficiencies detectable on the ultrastructural level give rise to PCD, but patients with normal cilia ultrastructure are common. An early diagnosis is very important since PCD can cause permanent lung...
A fully automated 3D Stitching tool designed for the very the large images produced by a special class of microscopes capable to acquire volumes of about 1 cm3 at micrometric resolution is presented. Exploiting some unique characteristics of the acquired images the tool makes it possible the accurate reconstruction of images of 1 TB or more in a reasonable time, even on workstations with limited resources...
Elevated intracranial pressure (ICP) is often associated with traumatic brain injury and can cause substantial complications. Elevated ICP also causes dilation of the optic nerve sheath, which can be observed and quantitated using intraocular ultrasound. We report on the use of 3-D ultrasound and automated processing algorithms to reduce operator variability in the assessment of sheath diameter. Using...
Mutual information (MI) has been widely used in image analysis tasks such as feature selection and image registration. In particular, it is the most widely used similarity measure for intensity based registration of multimodal images. However, a major drawback of MI is that it does not take the spatial neighbourhood into account. An effective way of incorporating spatial information could be of great...
In this paper, we present a fully automatic method to quantify Tree-in-Bud (TIB) patterns for respiratory tract infections. The proposed quantification method is based on our previous effort to detect and track TIB patterns with a computer assisted detection (CAD) system [9]. In addition to accurately identifying TIB on CT, quantifying TIB is important for measuring the volume of affected lung as...
We proposed a local scale-based Hessian analysis method for automated lymph node detection in contrast-enhanced abdominopelvic CT scans. First, spine and pelvic girdle were automatically segmented to locate the abdominopelvic region. Blood vessels were then segmented to narrow the search region to the perivascular space where lymph nodes are located. Lymph node candidates were generated by scale-based...
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