2,471 research outputs found
Intima-Media Thickness: Setting a Standard for a Completely Automated Method of Ultrasound Measurement
The intima – media thickness (IMT) of the common carotid artery is a widely used clinical marker of severe cardiovascular diseases. IMT is usually manually measured on longitudinal B-Mode ultrasound images. Many computer-based techniques for IMT measurement have been proposed to overcome the limits of manual segmentation. Most of these, however, require a certain degree of user interaction.
In this paper we describe a new completely automated layers extraction (CALEXia) technique for the segmentation and IMT measurement of carotid wall in ultrasound images. CALEXia is based on an integrated approach consisting of feature extraction, line fitting, and classification that enables the automated tracing of the carotid adventitial walls. IMT is then measured by relying on a fuzzy K-means classifier. We tested CALEXia on a database of 200 images. We compared CALEXia performances to those of a previously developed methodology that was based on signal analysis (CULEXsa). Three trained operators manually segmented the images and the average profiles were considered as the ground truth. The average error from CALEXia for lumen – intima (LI) and media – adventitia (MA) interface tracings were 1.46 ± 1.51 pixel (0.091 ± 0.093 mm) and 0.40 ± 0.87 pixel (0.025 ± 0.055 mm), respectively. The corresponding errors for CULEXsa were 0.55 ± 0.51 pixels (0.035 ± 0.032 mm) and 0.59 ± 0.46 pixels (0.037 ± 0.029 mm). The IMT measurement error was equal to 0.87 ± 0.56 pixel (0.054 ± 0.035 mm) for CALEXia and 0.12 ± 0.14 pixel (0.01 ± 0.01 mm) for CULEXsa. Thus, CALEXia showed limited performance in segmenting the LI interface, but outperformed CULEXsa in the MA interface and in the number of images correctly processed (10 for CALEXia and 16 for CULEXsa). Based on two complementary strategies, we anticipate fusing them for further IMT improvements
Documentation of the data analysis system for the gamma ray monitor aboard OSO-H
The programming system is presented which was developed to prepare the data from the gamma ray monitor on OSO-7 for scientific analysis. The detector, data, and objectives are described in detail. Programs presented include; FEEDER, PASS-1, CAL1, CAL2, PASS-3, Van Allen Belt Predict Program, Computation Center Plot Routine, and Response Function Programs
Designing Minimum Cost Nonblocking Communication Networks
This paper addresses the problem of topological design of ATM (and similar) communication networks. We formulate the problem from a worst-case point of view, seeking network desings that, subject to specified traffic constraints, are nonblocking for point-to-point and multicast virtual circuits. Within this model we give various conditions under which star networks are optimal or near-optimal. These conditions are approximately satisfied in many common situations making the results of practical significance. An important consequence of these results is that, where they apply, there is no added cost for nonblocking multicast communication, relative to networks that are nonblocking for point-to-point traffic only
Decoupling a Cooper-pair box to enhance the lifetime to 0.2 ms
We present a circuit QED experiment in which a separate transmission line is
used to address a quasi-lumped element superconducting microwave resonator
which is in turn coupled to an Al/AlO/Al Cooper-pair box (CPB) charge
qubit. In our measurements we find a strong correlation between the measured
lifetime of the CPB and the coupling between the qubit and the transmission
line. By monitoring perturbations of the resonator's 5.44 GHz resonant
frequency, we have measured the spectrum, lifetime (), Rabi, and Ramsey
oscillations of the CPB at the charge degeneracy point while the CPB was
detuned by up to 2.5 GHz . We find a maximum lifetime of the CPB was s for to 4.5 GHz. Our measured 's are consistent with
loss due to coupling to the transmission line, spurious microwave circuit
resonances, and a background decay rate on the order of
s of unknown origin, implying that the loss tangent in the AlO
junction barrier must be less than about at 4.5 GHz, about 4
orders of magnitude less than reported in larger area Al/AlO/Al tunnel
junctions
A Time-Space Tradeoff for Triangulations of Points in the Plane
In this paper, we consider time-space trade-offs for reporting a triangulation of points in the plane. The goal is to minimize the amount of working space while keeping the total running time small. We present the first multi-pass algorithm on the problem that returns the edges of a triangulation with their adjacency information. This even improves the previously best known random-access algorithm
CT attenuation analysis of carotid intraplaque hemorrhage
Background and Purpose: Intraplaque hemorrhage is considered a leading parameter of carotid plaque vulnerability. Our purpose was to assess the CT characteristics of intraplaque hemorrhage with histopathologic correlation to identify features that allow for confirming or ruling out the intraplaque hemorrhage. MATERIALS AND METHODS: This retrospective study included 91 patients (67 men; median age, 657 years; age range, 41-83 years) who underwent CT angiography and carotid endarterectomy from March 2010 to May 2013. Histopathologic analysis was performed for the tissue characterization and identification of intraplaque hemorrhage. Two observers assessed the plaque's attenuation values by using an ROI (≤1 and ≥2 mm2). Receiver operating characteristic curve, Mann-Whitney, and Wilcoxon analyses were performed. RESULTS: A total of 169 slices were assessed (59 intraplaque hemorrhage, 63 lipid-rich necrotic core, and 47 fibrous); the average values of the intraplaque hemorrhage, lipid-rich necrotic core, and fibrous tissue were 17.475 Hounsfield units (HU) and 18.407 HU, 39.476 HU and 48.048 HU, and 91.66 HU and 93.128 HU, respectively, before and after the administration of contrast medium. The Mann-Whitney test showed a statistically significant difference of HU values both in basal and after the administration of contrast material phase. Receiver operating characteristic analysis showed a statistical association between intraplaque hemorrhage and low HU values, and a threshold of 25 HU demonstrated the presence of intraplaque hemorrhage with a sensitivity and specificity of 93.22% and 92.73%, respectively. The Wilcoxon test showed that the attenuation of the plaque before and after administration of contrast material is different (intraplaque hemorrhage, lipid-rich necrotic core, and fibrous tissue had P values of .006, .0001, and .018, respectively). CONCLUSIONS: The results of this preliminary study suggest that CT can be used to identify the presence of intraplaque hemorrhage according to the attenuation. A threshold of 25 HU in the volume acquired after the administration of contrast medium is associated with an optimal sensitivity and specificity. Special care should be given to the correct identification of the ROI
Artificial Intelligence Applications in Cardiovascular Magnetic Resonance Imaging: Are We on the Path to Avoiding the Administration of Contrast Media?
In recent years, cardiovascular imaging examinations have experienced exponential growth due to technological innovation, and this trend is consistent with the most recent chest pain guidelines. Contrast media have a crucial role in cardiovascular magnetic resonance (CMR) imaging, allowing for more precise characterization of different cardiovascular diseases. However, contrast media have contraindications and side effects that limit their clinical application in determinant patients. The application of artificial intelligence (AI)-based techniques to CMR imaging has led to the development of non-contrast models. These AI models utilize non-contrast imaging data, either independently or in combination with clinical and demographic data, as input to generate diagnostic or prognostic algorithms. In this review, we provide an overview of the main concepts pertaining to AI, review the existing literature on non-contrast AI models in CMR, and finally, discuss the strengths and limitations of these AI models and their possible future development
Cost-Effective and Non-Invasive Automated Benign & Malignant Thyroid Lesion Classification in 3D Contrast-Enhanced Ultrasound Using Combination of Wavelets and Textures: A Class of ThyroScan™ Algorithms
Ultrasound has great potential to aid in the differential diagnosis of malignant and benign thyroid lesions, but interpretative pitfalls exist and the accuracy is still poor. To overcome these difficulties, we developed and analyzed a range of knowledge representation techniques, which are a class of ThyroScan™ algorithms from Global Biomedical Technologies Inc., California, USA, for automatic classification of benign and malignant thyroid lesions. The analysis is based on data obtained from twenty nodules (ten benign and ten malignant) taken from 3D contrast-enhanced ultrasound images. Fine needle aspiration biopsy and histology confirmed malignancy. Discrete Wavelet Transform (DWT) and texture algorithms are used to extract relevant features from the thyroid images. The resulting feature vectors are fed to three different classifiers: K-Nearest Neighbor (K-NN), Probabilistic Neural Network (PNN), and Decision Tree (DeTr). The performance of these classifiers is compared using Receiver Operating Characteristic (ROC) curves. Our results show that combination of DWT and texture features coupled with K-NN resulted in good performance measures with the area of under the ROC curve of 0.987, a classification accuracy of 98.9%, a sensitivity of 98%, and a specificity of 99.8%. Finally, we have proposed a novel integrated index called Thyroid Malignancy Index (TMI), which is made up of texture features, to diagnose benign or malignant nodules using just one index. We hope that this TMI will help clinicians in a more objective detection of benign and malignant thyroid lesions
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