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Polarisation of light affords the means to perform robust orientational measurements of single molecules and sub-wavelength asymmetric scatterers. The precision with which such measurements can be made can be quantified using Fisher information and the Cramér-Rao lower bound. Specifically, a fundamental limit of 0.5/N radians (on average) is found where N is the number of detected photons. Measurement...
The main focus of this paper is to further improve the performance of the recently introduced higher degree total variation (HDTV) penalties, which are L1-Lp; p ≥ 1 norms of directional image derivatives. We generalize this class as the L1-Lp norms of image responses to rotated versions of an arbitrary derivative operator. We show that several penalties proposed by other researchers are special cases...
The differential phase contrast CT (DPC-CT) implemented with x-ray tube and grating is emerging as a new technology to improve the contrast sensitivity of the conventional CT. Via system modeling, analysis and computer simulation, we investigate the DPC-CT's characteristics of signal and noise and compare them with the conventional CT. The preliminary data show that the DPC-CT possesses a modulation...
This paper describes a method for medical images annotation based on the SURF descriptor and the SVM classifier. For the features extraction a Fast-Hessian detector was used. The feature matching was performed with a SVM with a quadratic kernel. The testing of the developed system was performed using a subset of the IRMA radiographic images. The results provided with the SURF descriptor are compared...
Computerized detection of vascular calcium depositions in mamagraphy is a new research topics, which is driven by the clinical hypothesis of the association with many related cardiovascular diseases. In several previous studies [7, 9], calcification cue plays a very important role in the computerized analysis. We observe that vascular calcium depositions can be identified with high confidence if they...
This paper presents an empirical Bayes (EB) estimator for detection of endocardial edges in 3D+T echocardiography recordings. A maximum likelihood (ML) edge detector, proposed in a previous study, combines the responses of multiple edge detectors to improve the detection accuracy. We aim to further extend this approach with the use of contextual priors, that gives the probabilistic distribution of...
In previous work we developed a support vector machine (SVM) approach for detection of microcalcifications (MCs) in mammogram images, which was demonstrated to outperform several existing methods for MC detection in the literature. In this work, we explore whether we can further improve the performance of the SVM detector by exploiting the fact that MCs are inherently invariant to their spatial orientation...
Diffuse optical imaging has been developed at University College London (UCL) as a new method of assessing cerebral function and pathology in the newborn infant brain. The technique exploits the relative transparency of biological tissue to near-infrared light (700–1000nm) and the wavelength dependent absorption characteristics of hemoglobin, which vary with oxygenation. Methods have been developed...
Coarctation of the aorta (CoA), is an obstruction of the aortic arch present in 5–8% of congenital heart diseases. For children older than a year, CoA is increasingly treated by aortic stenting instead of surgical repair. In pediatric cardiology, CMR is accepted as the standard non-invasive imaging modality to assess the aortic arch in it's entire spatial context [1]. Interpreting such 3D datasets...
Super-resolution localization microscopy methods such as PALM and STORM have been shown to provide imaging with resolutions up to a few tens of nanometers while using relatively simple setups. Biplane PALM has extended the PALM technique to three-dimensions, by simultaneously using two imaging planes, with different focal depths. A key aspect in achieving good axial localization results is the alignment...
In this paper, we consider the problem of the accuracy of estimating the location and other attributes of a moving single molecule whose trajectory is acquired in a sequence of time intervals by a pixelated detector. We present expressions of the Fisher information matrices from which the benchmark for the accuracy of the parameter estimates is obtained. In the absence of extraneous noise, it is shown...
In this paper, we propose a method to improve the automatic detection of the optic disc on fundus images. We have studied and implemented some of the optic disc detectors from concerning literature to organize them into an ensemble system. As a former work, we proposed an ensemble-based optic disc detection system, based on simple majority voting which already outperformed the individual detectors...
Automatic coronary extraction has great clinical importance in the effective handling and visualization of large amounts of 3D data. Despite tremendous previous research, coronary extraction remains difficult. Two such difficulties are extraction of both normal and abnormal vessels and reconstruction of exact tree structures based on anatomical knowledge. To solve the first difficulty, we propose...
Fourier transform infrared (FT-IR) spectroscopic imaging provides spatially resolved chemical information. Recent developments have shown that this chemical information can be used to determine tissue cell types. Our goal is then to use the spatial distribution of tissue cell types to perform accurate diagnosis of cancer. However, this step is limited by the spatial resolution provided by current...
We present a novel method for automated learning of features from unlabeled image patches for classification of tumor architecture. In contrast to previous manually-designed feature detectors (e.g., Gabor basis function), the proposed method utilizes inexpensive un-labeled data to construct features. The algorithm, also known as reconstruction independent subspace analysis, can be described as a two-layer...
View classification for cardiac MR images is a new topic in medical image analysis, and can support efficient content-based filtering, browsing, and retrieval. The major difficulty lies in large variability in image appearance caused by various acquisition protocols, heart phases and disease conditions. We propose a collaborative learning approach that exploits statistical dependencies at three levels:...
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