Browse Proceedings

There is a great deal of interest in developing automated histological grading of tissue biopsies. Current approaches involve sophisticated algorithms for image segmentation, tissue architecture characterization, global texture feature extraction, and ...

Segmentation is one of the most critical problems in medical imaging. State-of-the art methods often are based on prior knowledge that can either encode geometry, appearance or both. Despite enormous work in the field, the mainstream is based on the ...

Cell-based fluorescence imaging assays have the potential to generate massive amount of data, which requires detailed quantitative analysis. Often, as a result of fixation, labeled nuclei overlap and create a clump of cells. However, it is important to ...

Iris recognition remains the most viable and reliable biometric method for security purposes. With the increasing demands in public safety and security, iris identification is becoming a requisite that seeks high accuracy with a fast and reliable ...

A novel method for the segmentation of brain structures combining registration-based and EM-based approaches is proposed. To address the issue of intensity variation within brain structures, we propose a method for creating spatial prior corresponding ...

Multi-atlas segmentation has been proved to perform well in segmenting sub-cortical structures from images. In this work, we study different components of multi-atlas segmentation and propose new techniques to improve the segmentation accuracy. We found ...

This paper presents a semi-automated segmentation method for short-axis cardiac CT and MR images. The main contributions of this work are: 1) using two different energy functionals for endocardium and epicardium segmentation to account for their ...

We present a new active contour-based, statistical method for simultaneous volumetric segmentation of multiple subcortical structures in the brain. Neighboring anatomical structures in the human brain exhibit co-dependencies which can aid in ...

Automatic extraction of aortic aneurysm thrombus is a nontrivial challenge for existing segmentation algorithms. Due to similar intensity, the boundary to surrounding tissue is characterized by a small gradient. On the other hand, the aneurysm contains ...

A new user interaction method called interactive polygons is presented in this paper. These interaction polygons are designed for use with the Active Volume Model segmentation method [1], which deforms with constraints from both Region Of Interest (ROI) ...

In this paper we present a new interactive method for tubular structure extraction. The main application and motivation for this work is vessel tracking in 3D medical images. The basic tools are minimal paths solved using the fast marching algorithm. ...

We have recently proposed a new level-set formulation, where the level-set is modelled as a continuous parametric function expressed in a B-spline basis. We propose in this paper to adapt this formalism to the class of narrow-band level-set methods, ...

In this paper, we propose a novel similarity-invariant approach to model-based segmentation of the left ventricle. The method assumes a control point representation of the model and an arbitrary interpolation strategy. First, we construct the prior ...

Segmentation is one of the basic problems in MRI analysis. We consider the problem of simultaneously segmenting multiple MR images, which, for example, could be a series of (2D/3D) images of the same tissue scanned over time, different slices of a ...

Investigating the effect of retinal oxygenation abnormalities in the development of common eye diseases requires accurate assessment of oxygen tension in retinal vasculatures. Estimation of oxygen tension in retinal capillaries using phosphorescence ...

Age related macular degeneration (AMD) is a condition of the retina that occurs with individuals over 50. AMD is characterized by the formation of drusen in the macula. This condition leads to a deterioration of foveal vision and eventually functional ...

This study was designed to characterize the spatio-temporal properties of intratumoral enhancement patterns by using voxel-wise temporal enhancement spectra and morphometry of their spatial distributions in dynamic contrast-enhanced (DCE) breast MRI. ...

Dynamic contrast-enhanced (DCE) MRI is a powerful tool for assessing tumour vasculature and for predicting patient response to therapy. DCE-MRI data can be quantified using pharmacokinetic models, allowing extraction of physiologically meaningful ...

Prostate cancer is one of the leading causes of cancer death for men. However, early detection before cancer spreads beyond the prostate can reduce the mortality. Therefore, invivo imaging techniques play an important role to localize the prostate ...

The demand for personalized health care requires a wide range of diagnostic tools for determining patient prognosis and theragnosis (response to treatment). These tools present us with data that is both multi-modal (imaging and non-imaging) and multi-...

We propose a spatial point process approach to improve the detection accuracy of clustered microcalcifications (MCs) in mammogram images. The conventional approach to MC detection has been to first detect the individual MCs in an image independently, ...

Assessing the precision in the estimation of lesion dimensions is a prerequisite for the determination of growth rates and response to therapy both in clinical practice and research. An initial study was designed and performed to evaluate three ...

Existing polyp detection methods rely heavily on curvature-based characteristics to differentiate between lesions. However, as curvature is a local feature and a second order differential quantity, noise caused by small bumpy structures and incoherent ...

The use of quantitative imaging for the characterization of hepatic tumors in MRI can improve the diagnosis and therefore the treatment. However, image parameters remain difficult to interpret because they result from a mixture of complex processes ...

This paper proposes a novel framework for tumor detection in Positron Emission Tomography (PET) images. A set of 8 second-order texture features obtained from the gray level co-occurrence matrix (GLCM) across 26 offsets, together with uptake value was ...

The widely adopted total variation (TV) filter is not optimal for MRI images with spatially varying noise levels, not to say those with also artifacts. To better preserve edges and fine structures while sufficiently removing noise and artifacts, we ...

Understanding the mechanisms of eye movement is difficult without a realistic biomechanical model. We present an efficient and robust computational framework for building subject-specific models of the orbit from magnetic resonance images (MRIs). We ...

Recent improvements of fetal MRI acquisitions now allow three-dimensional segmentation of fetal structures, to extract biometrical measures for pregnancy follow-up. Automation of the segmentation process remains a difficult challenge, given the ...

Various cortical measures such as cortical thickness are routinely computed along the vertices of cortical surface meshes. These metrics are used in surface-based morphometric studies. If one wishes to compare the surface-based morphometric studies to ...

We recently introduced a family of optimized interpolators to approximate the non-uniform Fourier transform of a finitely supported function. Theoretical comparisons indicated a significant improvement in performance over conventional approximations. In ...