Search results for "DETECT"
showing 10 items of 5902 documents
A high-resolution PET demonstrator using a silicon "magnifying glass".
2021
Abstract To assist ongoing investigations of the limits of the tradeoff between spatial resolution and noise in PET imaging, several PET instruments based on silicon-pad detectors have been developed. The latest is a segment of a dual-ring device to demonstrate that excellent reconstructed image resolution can be achieved with a scanner that uses highresolution detectors placed close to the object of interest or surrounding a small field-of-view in combination with detectors having modest resolution at larger radius. The outer ring of our demonstrator comprises conventional BGO block detectors scavenged from a clinical PET scanner and located at a 500 mm radius around a 50 mm diameter field…
Extraction of Airways from CT (EXACT'09)
2012
Contains fulltext : 107854.pdf (Publisher’s version ) (Open Access) This paper describes a framework for establishing a reference airway tree segmentation, which was used to quantitatively evaluate fifteen different airway tree extraction algorithms in a standardized manner. Because of the sheer difficulty involved in manually constructing a complete reference standard from scratch, we propose to construct the reference using results from all algorithms that are to be evaluated. We start by subdividing each segmented airway tree into its individual branch segments. Each branch segment is then visually scored by trained observers to determine whether or not it is a correctly segmented part o…
Studies on atomic layer deposition of IRMOF-8 thin films
2015
Deposition of IRMOF-8 thin films by atomic layer deposition was studied at 260–320 C. Zinc acetate and 2,6-naphthalenedicarboxylic acid were used as the precursors. The as-deposited amorphous films were crystallized in 70% relative humidity at room temperature resulting in an unknown phase with a large unit cell. An autoclave with dimethylformamide as the solvent was used to recrystallize the films into IRMOF-8 as confirmed by grazing incidence x-ray diffraction. The films were further characterized by high temperature x-ray diffraction (HTXRD), field emission scanning electron microscopy, Fourier transform infrared spectroscopy (FTIR), time-of-flight elastic recoil detection analysis (TOF-…
XENON100 dark matter results from a combination of 477 live days
2016
We report on WIMP search results of the XENON100 experiment, combining three runs summing up to 477 live days from January 2010 to January 2014. Data from the first two runs were already published. A blind analysis was applied to the last run recorded between April 2013 and January 2014 prior to combining the results. The ultra-low electromagnetic background of the experiment, ~$5 \times 10^{-3}$ events/(keV$_{\mathrm{ee}}\times$kg$\times$day) before electronic recoil rejection, together with the increased exposure of 48 kg $\times$ yr improves the sensitivity. A profile likelihood analysis using an energy range of (6.6 - 43.3) keV$_{\mathrm{nr}}$ sets a limit on the elastic, spin-independe…
Compressive imaging in scattering media.
2015
One challenge that has long held the attention of scientists is that of clearly seeing objects hidden by turbid media, as smoke, fog or biological tissue, which has major implications in fields such as remote sensing or early diagnosis of diseases. Here, we combine structured incoherent illumination and bucket detection for imaging an absorbing object completely embedded in a scattering medium. A sequence of low-intensity microstructured light patterns is launched onto the object, whose image is accurately reconstructed through the light fluctuations measured by a single-pixel detector. Our technique is noninvasive, does not require coherent sources, raster scanning nor time-gated detection…
A gray-level 2D feature detector using circular statistics
1997
Abstract This paper presents a new method for corner and circular feature detection in gray-level images. It is based on the application of standard statistical techniques to the distribution of gradient orientations in a circular neighborhood of the prospective feature point. An evaluation using standard procedures and a comparison with other approaches is presented. Results show the robustness of this method as compared to the other corner detectors analyzed. The main novelties are the possibility of detecting points that are centers of circular symmetries, and discriminating between junctions, which are classified into corners (two-edge junctions) and multiple edge junctions.
Application of Adaptive Hypergraph Model to Impulsive Noise Detection
2001
In this paper, using hypergraph theory, we introduce an image model called Adaptive Image Neighborhood Hypergraph (AINH). From this model we propose a combinatorial definition of noisy data. A detection procedure is used to classify the hyperedges either as noisy or clean data. Similar to other techniques, the proposed algorithm uses an estimation procedure to remove the effects of the noise. Extensive simulations show that the proposed scheme consistently works well in suppressing of impulsive noise.
A symbolic distributed event detection scheme for Wireless Sensor Networks
2016
Due to the possibility of extensive and pervasive deployment of many tiny sensor devices in the area of interest, Wireless Sensor Networks (WSNs) result particularly suitable to detect significant events and to react accordingly in industrial and home scenarios. In this context, fuzzy inference systems for event detection in WSNs have proved to be accurate enough in treating imprecise sensory readings to decrease the number of false alarms. Besides reacting to event occurrences, the whole network may infer more information to enrich the event semantics resulting from reasoning processes carried out on the individual nodes. Contextual knowledge, including spatial and temporal relationships, …
Toward Self-Supervised Feature Learning for Online Diagnosis of Multiple Faults in Electric Powertrains
2021
This article proposes a novel online fault diagnosis scheme for industrial powertrains without using historical faulty or labeled training data. The proposed method combines a one-class support vector machine (SVM) based anomaly detection and supervised convolutional neural network (CNN) algorithms to online detect multiple faults and fault severities under variable speeds and loads. The one-class SVM algorithm is to derive a score for defining faults or health classes in the first stage, and the resulting health classes are used as the training data for the CNN-based classifier in the second stage. Within this framework, the self-supervised learning of the proposed CNN algorithm allows the…
Gravitational-wave parameter inference using Deep Learning
2021
We explore machine learning methods to detect gravitational waves (GW) from binary black hole (BBH) mergers using deep learning (DL) algorithms. The DL networks are trained with gravitational waveforms obtained from BBH mergers with component masses randomly sampled in the range from 5 to 100 solar masses and luminosity distances from 100 Mpc to, at least, 2000 Mpc. The GW signal waveforms are injected in public data from the O2 run of the Advanced LIGO and Advanced Virgo detectors, in time windows that do not coincide with those of known detected signals, and the data from each detector in the Advanced LIGO and Advanced Virgo network is combined into a unique RGB image. We show that a clas…