Geometry planning and image registration in magnetic particle imaging using bimodal fiducial markers

International Nuclear Information System (INIS)

Werner, F.; Hofmann, M.; Them, K.; Knopp, T.; Jung, C.; Salamon, J.; Kaul, M. G.; Mummert, T.; Adam, G.; Ittrich, H.; Werner, R.; Säring, D.; Weber, O. M.

2016-01-01

Purpose: Magnetic particle imaging (MPI) is a quantitative imaging modality that allows the distribution of superparamagnetic nanoparticles to be visualized. Compared to other imaging techniques like x-ray radiography, computed tomography (CT), and magnetic resonance imaging (MRI), MPI only provides a signal from the administered tracer, but no additional morphological information, which complicates geometry planning and the interpretation of MP images. The purpose of the authors’ study was to develop bimodal fiducial markers that can be visualized by MPI and MRI in order to create MP–MR fusion images. Methods: A certain arrangement of three bimodal fiducial markers was developed and used in a combined MRI/MPI phantom and also during in vivo experiments in order to investigate its suitability for geometry planning and image fusion. An algorithm for automated marker extraction in both MR and MP images and rigid registration was established. Results: The developed bimodal fiducial markers can be visualized by MRI and MPI and allow for geometry planning as well as automated registration and fusion of MR–MP images. Conclusions: To date, exact positioning of the object to be imaged within the field of view (FOV) and the assignment of reconstructed MPI signals to corresponding morphological regions has been difficult. The developed bimodal fiducial markers and the automated image registration algorithm help to overcome these difficulties.

Geometry planning and image registration in magnetic particle imaging using bimodal fiducial markers

Energy Technology Data Exchange (ETDEWEB)

Werner, F., E-mail: f.werner@uke.de; Hofmann, M.; Them, K.; Knopp, T. [Section for Biomedical Imaging, University Medical Center Hamburg-Eppendorf, Hamburg 20246, Germany and Institute for Biomedical Imaging, Hamburg University of Technology, Hamburg 21073 (Germany); Jung, C.; Salamon, J.; Kaul, M. G.; Mummert, T.; Adam, G.; Ittrich, H. [Department of Diagnostic and Interventional Radiology, University Medical Center Hamburg-Eppendorf, Hamburg 20246 (Germany); Werner, R.; Säring, D. [Institute for Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg 20246 (Germany); Weber, O. M. [Philips Medical Systems DMC GmbH, Hamburg 22335 (Germany)

2016-06-15

Purpose: Magnetic particle imaging (MPI) is a quantitative imaging modality that allows the distribution of superparamagnetic nanoparticles to be visualized. Compared to other imaging techniques like x-ray radiography, computed tomography (CT), and magnetic resonance imaging (MRI), MPI only provides a signal from the administered tracer, but no additional morphological information, which complicates geometry planning and the interpretation of MP images. The purpose of the authors’ study was to develop bimodal fiducial markers that can be visualized by MPI and MRI in order to create MP–MR fusion images. Methods: A certain arrangement of three bimodal fiducial markers was developed and used in a combined MRI/MPI phantom and also during in vivo experiments in order to investigate its suitability for geometry planning and image fusion. An algorithm for automated marker extraction in both MR and MP images and rigid registration was established. Results: The developed bimodal fiducial markers can be visualized by MRI and MPI and allow for geometry planning as well as automated registration and fusion of MR–MP images. Conclusions: To date, exact positioning of the object to be imaged within the field of view (FOV) and the assignment of reconstructed MPI signals to corresponding morphological regions has been difficult. The developed bimodal fiducial markers and the automated image registration algorithm help to overcome these difficulties.

Fiducial inference - A Neyman-Pearson interpretation

NARCIS (Netherlands)

Salome, D; VonderLinden, W; Dose,; Fischer, R; Preuss, R

1999-01-01

Fisher's fiducial argument is a tool for deriving inferences in the form of a probability distribution on the parameter space, not based on Bayes's Theorem. Lindley established that in exceptional situations fiducial inferences coincide with posterior distributions; in the other situations fiducial

SU-F-P-30: Clinical Assessment of Auto Beam-Hold Triggered by Fiducial Localization During Prostate RapidArc Delivery

Energy Technology Data Exchange (ETDEWEB)

Atkinson, P; Chen, Q [Flower Hospital, Sylvania, OH (United States)

2016-06-15

Purpose: To assess the clinical efficacy of auto beam hold during prostate RapidArc delivery, triggered by fiducial localization on kV imaging with a Varian True Beam. Methods: Prostate patients with four gold fiducials were candidates in this study. Daily setup was accomplished by aligning to fiducials using orthogonal kV imaging. During RapidArc delivery, a kV image was automatically acquired with a momentary beam hold every 60 degrees of gantry rotation. The position of each fiducial was identified by a search algorithm and compared to a predetermined 1.4 cm diameter target area. Treatment continued if all the fiducials were within the target area. If any fiducial was outside the target area the beam hold was not released, and the operators determined if the patient needed re-alignment using the daily setup method. Results: Four patients were initially selected. For three patients, the auto beam hold performed seamlessly. In one instance, the system correctly identified misaligned fiducials, stopped treatment, and the patient was re-positioned. The fourth patient had a prosthetic hip which sometimes blocked the fiducials and caused the fiducial search algorithm to fail. The auto beam hold was disabled for this patient and the therapists manually monitored the fiducial positions during treatment. Average delivery time for a 2-arc fraction was increased by 59 seconds. Phantom studies indicated the dose discrepancy related to multiple beam holds is <0.1%. For a plan with 43 fractions, the additional imaging increased dose by an estimated 68 cGy. Conclusion: Automated intrafraction kV imaging can effectively perform auto beam holds due to patient movement, with the exception of prosthetic hip patients. The additional imaging dose and delivery time are clinically acceptable. It may be a cost-effective alternative to Calypso in RapidArc prostate patient delivery. Further study is warranted to explore its feasibility under various clinical conditions.

SU-F-P-30: Clinical Assessment of Auto Beam-Hold Triggered by Fiducial Localization During Prostate RapidArc Delivery

International Nuclear Information System (INIS)

Atkinson, P; Chen, Q

2016-01-01

Purpose: To assess the clinical efficacy of auto beam hold during prostate RapidArc delivery, triggered by fiducial localization on kV imaging with a Varian True Beam. Methods: Prostate patients with four gold fiducials were candidates in this study. Daily setup was accomplished by aligning to fiducials using orthogonal kV imaging. During RapidArc delivery, a kV image was automatically acquired with a momentary beam hold every 60 degrees of gantry rotation. The position of each fiducial was identified by a search algorithm and compared to a predetermined 1.4 cm diameter target area. Treatment continued if all the fiducials were within the target area. If any fiducial was outside the target area the beam hold was not released, and the operators determined if the patient needed re-alignment using the daily setup method. Results: Four patients were initially selected. For three patients, the auto beam hold performed seamlessly. In one instance, the system correctly identified misaligned fiducials, stopped treatment, and the patient was re-positioned. The fourth patient had a prosthetic hip which sometimes blocked the fiducials and caused the fiducial search algorithm to fail. The auto beam hold was disabled for this patient and the therapists manually monitored the fiducial positions during treatment. Average delivery time for a 2-arc fraction was increased by 59 seconds. Phantom studies indicated the dose discrepancy related to multiple beam holds is <0.1%. For a plan with 43 fractions, the additional imaging increased dose by an estimated 68 cGy. Conclusion: Automated intrafraction kV imaging can effectively perform auto beam holds due to patient movement, with the exception of prosthetic hip patients. The additional imaging dose and delivery time are clinically acceptable. It may be a cost-effective alternative to Calypso in RapidArc prostate patient delivery. Further study is warranted to explore its feasibility under various clinical conditions.

Magnet Fiducialization with Coordinate Measuring Machines

Energy Technology Data Exchange (ETDEWEB)

Friedsam, H.; Oren, W.; Pietryka, M.; /SLAC

2005-08-12

One of the fundamental alignment problems encountered when building a particle accelerator is the transfer of a component's magnetic centerline position to external fiducials. This operation, dubbed fiducialization, is critical because it can contribute significantly to the alignment error budget. The fiducialization process requires two measurements: (1) from magnetic centerline to mechanical centerline, and (2) from mechanical centerline to external fiducials. This paper will focus on methods for observing the second measurement. Two Stanford Linear Collider (SLC) examples are presented. The object of magnet fiducialization is to relate the magnet-defined beamline position to exterior reference surfaces. To be useful for later component alignment, this relationship must be established in a manner consistent with overall positioning tolerances. The error budget for the SLC's {+-} 100 {micro}m component to component alignment tolerance is as follows: magnetic centerline to mechanical centerline--{sigma} = {+-}30 {micro}m; mechanical centerline to fiducial marks--{sigma} = {+-}50 {micro}m; and fiducial marks to adjacent components--{sigma} = {+-}80 {micro}m; the TOTAL {sigma} = {+-}100 {micro}m. The offset between the mechanical and magnetic centerlines of well-known magnets is generally smaller than the {+-}30 {micro}m measurement tolerance. It is commonly assumed to be zero without measurement. When this tiny value must be measured, extreme care is necessary to avoid obscuring the offset with measurement tool registration errors. In contrast, the mechanical centerline to fiducial measurement must be performed on every magnet. The 50 {micro}m tolerance for this operation is only slightly larger and pushes conventional surveying technology to its limit.

Magnet Fiducialization with Coordinate Measuring Machines

International Nuclear Information System (INIS)

Friedsam, H.; Oren, W.; Pietryka, M.; SLAC

2005-01-01

One of the fundamental alignment problems encountered when building a particle accelerator is the transfer of a component's magnetic centerline position to external fiducials. This operation, dubbed fiducialization, is critical because it can contribute significantly to the alignment error budget. The fiducialization process requires two measurements: (1) from magnetic centerline to mechanical centerline, and (2) from mechanical centerline to external fiducials. This paper will focus on methods for observing the second measurement. Two Stanford Linear Collider (SLC) examples are presented. The object of magnet fiducialization is to relate the magnet-defined beamline position to exterior reference surfaces. To be useful for later component alignment, this relationship must be established in a manner consistent with overall positioning tolerances. The error budget for the SLC's ± 100 (micro)m component to component alignment tolerance is as follows: magnetic centerline to mechanical centerline--σ = ±30 (micro)m; mechanical centerline to fiducial marks--σ = ±50 (micro)m; and fiducial marks to adjacent components--σ = ±80 (micro)m; the TOTAL σ = ±100 (micro)m. The offset between the mechanical and magnetic centerlines of well-known magnets is generally smaller than the ±30 (micro)m measurement tolerance. It is commonly assumed to be zero without measurement. When this tiny value must be measured, extreme care is necessary to avoid obscuring the offset with measurement tool registration errors. In contrast, the mechanical centerline to fiducial measurement must be performed on every magnet. The 50 (micro)m tolerance for this operation is only slightly larger and pushes conventional surveying technology to its limit

Creating a distortion characterisation dataset for visual band cameras using fiducial markers

CSIR Research Space (South Africa)

Jermy, R

2015-11-01

Full Text Available . This will allow other researchers to perform the same steps and create better algorithms to accurately locate fiducial markers and calibrate cameras. A second dataset that can be used to assess the accuracy of the stereo vision of two calibrated cameras is also...

Implementation of Fiducial-Based Image Registration in the Cyberknife Robotic System

International Nuclear Information System (INIS)

Saw, Cheng B.; Chen Hungcheng; Wagner, Henry

2008-01-01

Fiducial-based image registration methodology as implemented in the Cyberknife system is explored. The Cyberknife is a radiosurgery system that uses image guidance technology and computer-controlled robotics to determine target positions and adjust beam directions accordingly during the dose delivery. The image guidance system consists of 2 x-ray sources mounted on the ceiling and a detection system mounted on both sides of the treatment couch. Two orthogonal live radiographs are taken prior to and during patient treatment. Fiducial markers are identified on these radiographs and compared to a library of digital reconstructed radiographs (DRRs) using the fiducial extraction software. The fiducial extraction software initially sets an intensity threshold on the live radiographs to generate white areas on black images referred to as 'blobs.' Different threshold values are being used and blobs at the same location are assumed to originate from the same object. The number of blobs is then reduced by examining each blob against a predefined set of properties such as shape and exposure levels. The remaining blobs are further reduced by examining the location of the blobs in the inferior-superior patient axis. Those blobs that have the corresponding positions are assumed to originate from the same object. The remaining blobs are used to create fiducial configurations and are compared to the reference configuration from the computed tomography (CT) image dataset for treatment planning. The best-fit configuration is considered to have the appropriate fiducial markers. The patient position is determined based on these fiducial markers. During the treatment, the radiation beam is turned off when the Cyberknife changes nodes. This allows a time window to acquire live radiographs for the determination of the patient target position and to update the robotic manipulator to change beam orientations accordingly

Multiple ECG Fiducial Points-Based Random Binary Sequence Generation for Securing Wireless Body Area Networks.

Science.gov (United States)

Zheng, Guanglou; Fang, Gengfa; Shankaran, Rajan; Orgun, Mehmet A; Zhou, Jie; Qiao, Li; Saleem, Kashif

2017-05-01

Generating random binary sequences (BSes) is a fundamental requirement in cryptography. A BS is a sequence of N bits, and each bit has a value of 0 or 1. For securing sensors within wireless body area networks (WBANs), electrocardiogram (ECG)-based BS generation methods have been widely investigated in which interpulse intervals (IPIs) from each heartbeat cycle are processed to produce BSes. Using these IPI-based methods to generate a 128-bit BS in real time normally takes around half a minute. In order to improve the time efficiency of such methods, this paper presents an ECG multiple fiducial-points based binary sequence generation (MFBSG) algorithm. The technique of discrete wavelet transforms is employed to detect arrival time of these fiducial points, such as P, Q, R, S, and T peaks. Time intervals between them, including RR, RQ, RS, RP, and RT intervals, are then calculated based on this arrival time, and are used as ECG features to generate random BSes with low latency. According to our analysis on real ECG data, these ECG feature values exhibit the property of randomness and, thus, can be utilized to generate random BSes. Compared with the schemes that solely rely on IPIs to generate BSes, this MFBSG algorithm uses five feature values from one heart beat cycle, and can be up to five times faster than the solely IPI-based methods. So, it achieves a design goal of low latency. According to our analysis, the complexity of the algorithm is comparable to that of fast Fourier transforms. These randomly generated ECG BSes can be used as security keys for encryption or authentication in a WBAN system.

Comparison between skin-mounted fiducials and bone-implanted fiducials for image-guided neurosurgery

Science.gov (United States)

Rost, Jennifer; Harris, Steven S.; Stefansic, James D.; Sillay, Karl; Galloway, Robert L., Jr.

2004-05-01

Point-based registration for image-guided neurosurgery has become the industry standard. While the use of intrinsic points is appealing because of its retrospective nature, affixing extrinsic objects to the head prior to scanning has been demonstrated to provide much more accurate registrations. Points of reference between image space and physical space are called fiducials. The extrinsic objects which generate those points are fiducial markers. The markers can be broken down into two classifications: skin-mounted and bone-implanted. Each has distinct advantages and disadvantages. Skin-mounted fiducials require simply sticking them on the patient in locations suggested by the manufacturer, however, they can move with tractions placed on the skin, fall off and perhaps the most dangerous problem, they can be replaced by the patient. Bone implanted markers being rigidly affixed to the skull do not present such problems. However, a minor surgical intervention (analogous to dental work) must be performed to implant the markers prior to surgery. Therefore marker type and use has become a decision point for image-guided surgery. We have performed a series of experiments in an attempt to better quantify aspects of the two types of markers so that better informed decisions can be made. We have created a phantom composed of a full-size plastic skull [Wards Scientific Supply] with a 500 ml bag of saline placed in the brain cavity. The skull was then sealed. A skin mimicking material, DragonSkinTM [SmoothOn Company] was painted onto the surface and allowed to dry. Skin mounted fiducials [Medtronic-SNT] and bone-implanted markers [Z-Kat]were placed on the phantom. In addition, three additional bone-implanted markers were placed (two on the base of the skull and one in the eye socket for use as targets). The markers were imaged in CT and 4 MRI sequences (T1-weighted, T2 weighted, SPGR, and a functional series.) The markers were also located in physical space using an Optotrak

Fiducial-based registration with a touchable region model.

Science.gov (United States)

Kim, Sungmin; Kazanzides, Peter

2017-02-01

Image-guided surgery requires registration between an image coordinate system and an intraoperative coordinate system that is typically referenced to a tracking device. In fiducial-based registration methods, this is achieved by localizing points (fiducials) in each coordinate system. Often, both localizations are performed manually, first by picking a fiducial point in the image and then by using a hand-held tracked pointer to physically touch the corresponding fiducial on the patient. These manual procedures introduce localization error that is user-dependent and can significantly decrease registration accuracy. Thus, there is a need for a registration method that is tolerant of imprecise fiducial localization in the preoperative and intraoperative phases. We propose the iterative closest touchable point (ICTP) registration framework, which uses model-based localization and a touchable region model. This method consists of three stages: (1) fiducial marker localization in image space, using a fiducial marker model, (2) initial registration with paired-point registration, and (3) fine registration based on the iterative closest point method. We perform phantom experiments with a fiducial marker design that is commonly used in neurosurgery. The results demonstrate that ICTP can provide accuracy improvements compared to the standard paired-point registration method that is widely used for surgical navigation and surgical robot systems, especially in cases where the surgeon introduces large localization errors. The results demonstrate that the proposed method can reduce the effect of the surgeon's localization performance on the accuracy of registration, thereby producing more consistent and less user-dependent registration outcomes.

WE-AB-303-05: Breathing Motion of Liver Segments From Fiducial Tracking During Robotic Radiosurgery and Comparison with 4D-CT-Derived Fiducial Motion

International Nuclear Information System (INIS)

Sutherland, J; Pantarotto, J; Nair, V; Cook, G; Plourde, M; Vandervoort, E

2015-01-01

Purpose: To quantify respiratory-induced motion of liver segments using the positions of implanted fiducials during robotic radiosurgery. This study also compared fiducial motion derived from four-dimensional computed tomography (4D-CT) maximum intensity projections (MIP) with motion derived from imaging during treatment. Methods: Forty-two consecutive liver patients treated with liver ablative radiotherapy were accrued to an ethics approved retrospective study. The liver segment in which each fiducial resided was identified. Fiducial positions throughout each treatment fraction were determined using orthogonal kilovoltage images. Any data due to patient repositioning or motion was removed. Mean fiducial positions were calculated. Fiducial positions beyond two standard deviations of the mean were discarded and remaining positions were fit to a line segment using least squares minimization (LSM). For eight patients, fiducial motion was derived from 4D-CT MIPs by calculating the CT number weighted mean position of the fiducial on each slice and fitting a line segment to these points using LSM. Treatment derived fiducial trajectories were corrected for patient rotation and compared to MIP derived trajectories. Results: The mean total magnitude of fiducial motion across all liver segments in left-right, anteroposterior, and superoinferior (SI) directions were 3.0 ± 0.2 mm, 9.3 ± 0.4 mm, and 20.5 ± 0.5 mm, respectively. Differences in per-segment mean fiducial motion were found with SI motion ranging from 12.6 ± 0.8 mm to 22.6 ± 0.9 mm for segments 3 and 8, respectively. Large, varied differences between treatment and MIP derived motion at simulation were found with the mean difference for SI motion being 2.6 mm (10.8 mm standard deviation). Conclusion: The magnitude of liver fiducial motion was found to differ by liver segment. MIP derived liver fiducial motion differed from motion observed during treatment, implying that 4D-CTs may not accurately capture the

WE-AB-303-05: Breathing Motion of Liver Segments From Fiducial Tracking During Robotic Radiosurgery and Comparison with 4D-CT-Derived Fiducial Motion

Energy Technology Data Exchange (ETDEWEB)

Sutherland, J; Pantarotto, J; Nair, V; Cook, G; Plourde, M; Vandervoort, E [The Ottawa Hospital Cancer Centre, Ottawa, Ontario (Canada)

2015-06-15

Purpose: To quantify respiratory-induced motion of liver segments using the positions of implanted fiducials during robotic radiosurgery. This study also compared fiducial motion derived from four-dimensional computed tomography (4D-CT) maximum intensity projections (MIP) with motion derived from imaging during treatment. Methods: Forty-two consecutive liver patients treated with liver ablative radiotherapy were accrued to an ethics approved retrospective study. The liver segment in which each fiducial resided was identified. Fiducial positions throughout each treatment fraction were determined using orthogonal kilovoltage images. Any data due to patient repositioning or motion was removed. Mean fiducial positions were calculated. Fiducial positions beyond two standard deviations of the mean were discarded and remaining positions were fit to a line segment using least squares minimization (LSM). For eight patients, fiducial motion was derived from 4D-CT MIPs by calculating the CT number weighted mean position of the fiducial on each slice and fitting a line segment to these points using LSM. Treatment derived fiducial trajectories were corrected for patient rotation and compared to MIP derived trajectories. Results: The mean total magnitude of fiducial motion across all liver segments in left-right, anteroposterior, and superoinferior (SI) directions were 3.0 ± 0.2 mm, 9.3 ± 0.4 mm, and 20.5 ± 0.5 mm, respectively. Differences in per-segment mean fiducial motion were found with SI motion ranging from 12.6 ± 0.8 mm to 22.6 ± 0.9 mm for segments 3 and 8, respectively. Large, varied differences between treatment and MIP derived motion at simulation were found with the mean difference for SI motion being 2.6 mm (10.8 mm standard deviation). Conclusion: The magnitude of liver fiducial motion was found to differ by liver segment. MIP derived liver fiducial motion differed from motion observed during treatment, implying that 4D-CTs may not accurately capture the

Limited Role for Biliary Stent as Surrogate Fiducial Marker in Pancreatic Cancer: Stent and Intratumoral Fiducials Compared

Energy Technology Data Exchange (ETDEWEB)

Horst, Astrid van der, E-mail: a.vanderhorst@amc.uva.nl [Department of Radiation Oncology, Academic Medical Center, University of Amsterdam, Amsterdam (Netherlands); Lens, Eelco; Wognum, Silvia; Jong, Rianne de [Department of Radiation Oncology, Academic Medical Center, University of Amsterdam, Amsterdam (Netherlands); Hooft, Jeanin E. van [Department of Gastroenterology and Hepatology, Academic Medical Center, University of Amsterdam, Amsterdam (Netherlands); Tienhoven, Geertjan van; Bel, Arjan [Department of Radiation Oncology, Academic Medical Center, University of Amsterdam, Amsterdam (Netherlands)

2014-07-01

Purpose: Because of low soft-tissue contrast of cone beam computed tomography (CBCT), fiducial markers are often used for radiation therapy patient setup verification. For pancreatic cancer patients, biliary stents have been suggested as surrogate fiducials. Using intratumoral fiducials as standard for tumor position, this study aims to quantify the suitability of biliary stents for measuring interfractional and respiratory-induced position variations of pancreatic tumors. Methods and Materials: Eleven pancreatic cancer patients with intratumoral fiducials and a biliary stent were included in this study. Daily CBCT scans (243 in total) were registered with a reference CT scan, based on bony anatomy, on fiducial markers, and on the biliary stent, respectively. We analyzed the differences in tumor position (ie, markers center-of-mass position) among these 3 registrations. In addition, we measured for 9 patients the magnitude of respiratory-induced motion (MM) of the markers and of the stent on 4-dimensional CT (4DCT) and determined the difference between these 2 magnitudes (ΔMM). Results: The stent indicated tumor position better than bony anatomy in 67% of fractions; the absolute difference between the markers and stent registration was >5 mm in 46% of fractions and >10 mm in 20% of fractions. Large PTV margins (superior-inferior direction, >19 mm) would be needed to account for this interfractional position variability. On 4DCT, we found in superior-inferior direction a mean ΔMM of 0.5 mm (range, –2.6 to 4.2 mm). Conclusions: For respiratory-induced motion, the mean ΔMM is small, but for individual patients the absolute difference can be >4 mm. For interfractional position variations, a stent is, on average, a better surrogate fiducial than bony anatomy, but large PTV margins would still be required. Therefore, intratumoral fiducials are recommended for online setup verification for all pancreatic patients scheduled for radiation therapy, including

A Modular Low-Complexity ECG Delineation Algorithm for Real-Time Embedded Systems.

Science.gov (United States)

Bote, Jose Manuel; Recas, Joaquin; Rincon, Francisco; Atienza, David; Hermida, Roman

2018-03-01

This work presents a new modular and low-complexity algorithm for the delineation of the different ECG waves (QRS, P and T peaks, onsets, and end). Involving a reduced number of operations per second and having a small memory footprint, this algorithm is intended to perform real-time delineation on resource-constrained embedded systems. The modular design allows the algorithm to automatically adjust the delineation quality in runtime to a wide range of modes and sampling rates, from a ultralow-power mode when no arrhythmia is detected, in which the ECG is sampled at low frequency, to a complete high-accuracy delineation mode, in which the ECG is sampled at high frequency and all the ECG fiducial points are detected, in the case of arrhythmia. The delineation algorithm has been adjusted using the QT database, providing very high sensitivity and positive predictivity, and validated with the MIT database. The errors in the delineation of all the fiducial points are below the tolerances given by the Common Standards for Electrocardiography Committee in the high-accuracy mode, except for the P wave onset, for which the algorithm is above the agreed tolerances by only a fraction of the sample duration. The computational load for the ultralow-power 8-MHz TI MSP430 series microcontroller ranges from 0.2% to 8.5% according to the mode used.

Line fiducial material and thickness considerations for ultrasound calibration

Science.gov (United States)

Ameri, Golafsoun; McLeod, A. J.; Baxter, John S. H.; Chen, Elvis C. S.; Peters, Terry M.

2015-03-01

Ultrasound calibration is a necessary procedure in many image-guided interventions, relating the position of tools and anatomical structures in the ultrasound image to a common coordinate system. This is a necessary component of augmented reality environments in image-guided interventions as it allows for a 3D visualization where other surgical tools outside the imaging plane can be found. Accuracy of ultrasound calibration fundamentally affects the total accuracy of this interventional guidance system. Many ultrasound calibration procedures have been proposed based on a variety of phantom materials and geometries. These differences lead to differences in representation of the phantom on the ultrasound image which subsequently affect the ability to accurately and automatically segment the phantom. For example, taut wires are commonly used as line fiducials in ultrasound calibration. However, at large depths or oblique angles, the fiducials appear blurred and smeared in ultrasound images making it hard to localize their cross-section with the ultrasound image plane. Intuitively, larger diameter phantoms with lower echogenicity are more accurately segmented in ultrasound images in comparison to highly reflective thin phantoms. In this work, an evaluation of a variety of calibration phantoms with different geometrical and material properties for the phantomless calibration procedure was performed. The phantoms used in this study include braided wire, plastic straws, and polyvinyl alcohol cryogel tubes with different diameters. Conventional B-mode and synthetic aperture images of the phantoms at different positions were obtained. The phantoms were automatically segmented from the ultrasound images using an ellipse fitting algorithm, the centroid of which is subsequently used as a fiducial for calibration. Calibration accuracy was evaluated for these procedures based on the leave-one-out target registration error. It was shown that larger diameter phantoms with lower

Alternative fiducial markers for Vero real-time tumor tracking radiotherapy: A phantom study

Science.gov (United States)

Park, Shin-Hyung; Kim, Jae-Chul; Kim, Sung Joon

2016-12-01

The objective of this study was to investigate the feasibility of potential fiducial markers consisting of various materials in a Vero real-time tumor-tracking (RTTT) system. In order to determine the applicability of fiducial markers for the Vero RTTT system, we tested various markers consisting of 8 kinds of material (titanium, stainless steel, high-carbon steel, pure steel, copper, silver, tantalum, and gold) with various diameters ranging from 0.3 mm to 1.6 mm and a length of 5 mm. Additionally, a commercial gold coil marker (Visicoil™, IBA dosimetry, Schwarzenbruck, Germany) of diameter 0.5 mm and length 1 cm was included for evaluation. The radiologic visibility on kV fluoroscopy/kV CT scan images of the fiducial markers was evaluated. The detectability on the RTTT system was tested using a two-dimensional moving phantom (Brainlab AG, Feldkirchen, Germany), producing sinusoidal motion. The target center's accuracy was evaluated by calculating the deviation of the position of a metal sphere from the center on the dose profile. Dose profiles were measured using Gafchromic EBT2 films (International Specialty Products, NJ, USA). All markers were visible on kV fluoroscopy/kV CT while markers with atomic number ≥ 25.7 were detectable on the Vero RTTT system. All the detected markers showed excellent geometric accuracy.

THE APPROACHING TRAIN DETECTION ALGORITHM

OpenAIRE

S. V. Bibikov

2015-01-01

The paper deals with detection algorithm for rail vibroacoustic waves caused by approaching train on the background of increased noise. The urgency of algorithm development for train detection in view of increased rail noise, when railway lines are close to roads or road intersections is justified. The algorithm is based on the method of weak signals detection in a noisy environment. The information statistics ultimate expression is adjusted. We present the results of algorithm research and t...

Linear feature detection algorithm for astronomical surveys - I. Algorithm description

Science.gov (United States)

Bektešević, Dino; Vinković, Dejan

2017-11-01

Computer vision algorithms are powerful tools in astronomical image analyses, especially when automation of object detection and extraction is required. Modern object detection algorithms in astronomy are oriented towards detection of stars and galaxies, ignoring completely the detection of existing linear features. With the emergence of wide-field sky surveys, linear features attract scientific interest as possible trails of fast flybys of near-Earth asteroids and meteors. In this work, we describe a new linear feature detection algorithm designed specifically for implementation in big data astronomy. The algorithm combines a series of algorithmic steps that first remove other objects (stars and galaxies) from the image and then enhance the line to enable more efficient line detection with the Hough algorithm. The rate of false positives is greatly reduced thanks to a step that replaces possible line segments with rectangles and then compares lines fitted to the rectangles with the lines obtained directly from the image. The speed of the algorithm and its applicability in astronomical surveys are also discussed.

A Fiducial Approach to Extremes and Multiple Comparisons

Science.gov (United States)

Wandler, Damian V.

2010-01-01

Generalized fiducial inference is a powerful tool for many difficult problems. Based on an extension of R. A. Fisher's work, we used generalized fiducial inference for two extreme value problems and a multiple comparison procedure. The first extreme value problem is dealing with the generalized Pareto distribution. The generalized Pareto…

On a laser beam fiducial line application for metrological purposes

International Nuclear Information System (INIS)

Batusov, V.; Budagov, J.; Lyablin, M.; Rusakovich, N.; Sisakyan, A.; Topilin, N.; Khubua, J.; Lasseur, C.

2008-01-01

The possibility of a collimated one-mode laser beam used as a fiducial line is considered. The technology of an 'extended' laser beam formation and application for a much extended fiducial line is proposed

Microscopic Gold Particle-Based Fiducial Markers for Proton Therapy of Prostate Cancer

International Nuclear Information System (INIS)

Lim, Young Kyung; Kwak, Jungwon; Kim, Dong Wook; Shin, Dongho; Yoon, Myonggeun; Park, Soah; Kim, Jin Sung; Ahn, Sung Hwan; Shin, Jungwook; Lee, Se Byeong; Park, Sung Yong; Pyo, Hong Ryeol; Kim, Dae Yong M.D.; Cho, Kwan Ho

2009-01-01

Purpose: We examined the feasibility of using fiducial markers composed of microscopic gold particles and human-compatible polymers as a means to overcome current problems with conventional macroscopic gold fiducial markers, such as dose reduction and artifact generation, in proton therapy for prostate cancer. Methods and Materials: We examined two types of gold particle fiducial marker interactions: that with diagnostic X-rays and with a therapeutic proton beam. That is, we qualitatively and quantitatively compared the radiographic visibility of conventional gold and gold particle fiducial markers and the CT artifacts and dose reduction associated with their use. Results: The gold particle fiducials could be easily distinguished from high-density structures, such as the pelvic bone, in diagnostic X-rays but were nearly transparent to a proton beam. The proton dose distribution was distorted <5% by the gold particle fiducials with a 4.9% normalized gold density; this was the case even in the worst configuration (i.e., parallel alignment with a single-direction proton beam). In addition, CT artifacts were dramatically reduced for the gold particle mixture. Conclusion: Mixtures of microscopic gold particles and human-compatible polymers have excellent potential as fiducial markers for proton therapy for prostate cancer. These include good radiographic visibility, low distortion of the depth-dose distribution, and few CT artifacts.

Improvement in Interobserver Accuracy in Delineation of the Lumpectomy Cavity Using Fiducial Markers

International Nuclear Information System (INIS)

Shaikh, Talha; Chen Ting; Khan, Atif; Yue, Ning J.; Kearney, Thomas; Cohler, Alan; Haffty, Bruce G.; Goyal, Sharad

2010-01-01

Purpose: To determine, whether the presence of gold fiducial markers would improve the inter- and intraphysician accuracy in the delineation of the surgical cavity compared with a matched group of patients who did not receive gold fiducial markers in the setting of accelerated partial-breast irradiation (APBI). Methods and Materials: Planning CT images of 22 lumpectomy cavities were reviewed in a cohort of 22 patients; 11 patients received four to six gold fiducial markers placed at the time of surgery. Three physicians categorized the seroma cavity according to cavity visualization score criteria and delineated each of the 22 seroma cavities and the clinical target volume. Distance between centers of mass, percentage overlap, and average surface distance for all patients were assessed. Results: The mean seroma volume was 36.9 cm 3 and 34.2 cm 3 for fiducial patients and non-fiducial patients, respectively (p = ns). Fiducial markers improved the mean cavity visualization score, to 3.6 ± 1.0 from 2.5 ± 1.3 (p < 0.05). The mean distance between centers of mass, average surface distance, and percentage overlap for the seroma and clinical target volume were significantly improved in the fiducial marker patients as compared with the non-fiducial marker patients (p < 0.001). Conclusions: The placement of gold fiducial markers placed at the time of lumpectomy improves interphysician identification and delineation of the seroma cavity and clinical target volume. This has implications in radiotherapy treatment planning for accelerated partial-breast irradiation and for boost after whole-breast irradiation.

Visibility of solid and liquid fiducial markers used for image-guided radiation therapy on optical coherence tomography: an esophageal phantom study (Conference Presentation)

Science.gov (United States)

Jelvehgaran, Pouya; Alderliesten, Tanja; Weda, Jelmer J. A.; de Bruin, Daniel M.; Faber, Dirk J.; Hulshof, Maarten C. C. M.; van Leeuwen, Ton G.; van Herk, Marcel B.; de Boer, Johannes F.

2017-03-01

Radiation therapy (RT) is used in operable and inoperable esophageal cancer patients. Endoscopic ultrasound-guided fiducial marker placement allows improved translation of the disease extent on endoscopy to computed tomography (CT) images used for RT planning and enables image-guided RT. However, microscopic tumor extent at the time of RT planning is unknown. Endoscopic optical coherence tomography (OCT) is a high-resolution (10-30µm) imaging modality with the potential for accurately determining the longitudinal disease extent. Visibility of fiducial markers on OCT is crucial for integrating OCT findings with the RT planning CT. We investigated the visibility on OCT (NinePoint Medical, Inc.) of 13 commercially available solid (Visicoil, Gold Anchor, Flexicoil, Polymark, and QLRAD) and liquid (BioXmark, Lipiodol, and Hydrogel) fiducial markers of different diameter. We designed and manufactured a set of dedicated Silicone-based esophageal phantoms to perform imaging in a controlled environment. The esophageal phantoms consist of several layers with different TiO2 concentrations to simulate the scattering properties of a typical healthy human esophagus. Markers were placed at various depths (0.5, 1.1, 2.0, and 3.0mm). OCT imaging allowed detection of all fiducial markers and phantom layers. The signal to background ratio was 6-fold higher for the solid fiducial markers than the liquid fiducial markers, yet OCT was capable of visualizing all 13 fiducial markers at all investigated depths. We conclude that RT fiducial markers can be visualized with OCT. This allows integration of OCT findings with CT for image-guided RT.

Novel Technique for Hepatic Fiducial Marker Placement for Stereotactic Body Radiation Therapy

International Nuclear Information System (INIS)

Jarraya, Hajer; Chalayer, Chloé; Tresch, Emmanuelle; Bonodeau, Francois; Lacornerie, Thomas; Mirabel, Xavier; Boulanger, Thomas; Taieb, Sophie; Kramar, Andrew; Lartigau, Eric; Ceugnart, Luc

2014-01-01

Purpose: To report experience with fiducial marker insertion and describe an advantageous, novel technique for fiducial placement in the liver for stereotactic body radiation therapy with respiratory tracking. Methods and Materials: We implanted 1444 fiducials (single: 834; linked: 610) in 328 patients with 424 hepatic lesions. Two methods of implantation were compared: the standard method (631 single fiducials) performed on 153 patients from May 2007 to May 2010, and the cube method (813 fiducials: 610 linked/203 single) applied to 175 patients from April 2010 to March 2013. The standard method involved implanting a single marker at a time. The novel technique entailed implanting 2 pairs of linked markers when possible in a way to occupy the perpendicular edges of a cube containing the tumor inside. Results: Mean duration of the cube method was shorter than the standard method (46 vs 61 minutes; P<.0001). Median numbers of skin and subcapsular entries were significantly smaller with the cube method (2 vs 4, P<.0001, and 2 vs 4, P<.0001, respectively). The rate of overall complications (total, major, and minor) was significantly lower in the cube method group compared with the standard method group (5.7% vs 13.7%; P=.013). Major complications occurred while using single markers only. The success rate was 98.9% for the cube method and 99.3% for the standard method. Conclusions: We propose a new technique of hepatic fiducial implantation that makes use of linked fiducials and involves fewer skin entries and shorter time of implantation. The technique is less complication-prone and is migration-resistant

Clinical Usefulness of Implanted Fiducial Markers for Hypofractionated Radiotherapy of Prostate Cancer

International Nuclear Information System (INIS)

Choi, Young Min; Ahn, Sung Hwan; Lee, Hyung Hwan; Lee, Hyung Sik; Hur, Woo Joo; Yoon, Jin Han; Kim, Tae Hyo; Kim, Soo Dong; Yun, Seong Guk

2011-01-01

To assess the usefulness of implanted fiducial markers in the setup of hypofractionated radiotherapy for prostate cancer patients by comparing a fiducial marker matched setup with a pelvic bone match. Four prostate cancer patients treated with definitive hypofractionated radiotherapy between September 2009 and August 2010 were enrolled in this study. Three gold fiducial markers were implanted into the prostate and through the rectum under ultrasound guidance around a week before radiotherapy. Glycerin enemas were given prior to each radiotherapy planning CT and every radiotherapy session. Hypofractionated radiotherapy was planned for a total dose of 59.5 Gy in daily 3.5 Gy with using the Novalis system. Orthogonal kV X-rays were taken before radiotherapy. Treatment positions were adjusted according to the results from the fusion of the fiducial markers on digitally reconstructed radiographs of a radiotherapy plan with those on orthogonal kV X-rays. When the difference in the coordinates from the fiducial marker fusion was less than 1 mm, the patient position was approved for radiotherapy. A virtual bone matching was carried out at the fiducial marker matched position, and then a setup difference between the fiducial marker matching and bone matching was evaluated. Three patients received a planned 17-fractionated radiotherapy and the rest underwent 16 fractionations. The setup error of the fiducial marker matching was 0.94±0.62 mm (range, 0.09 to 3.01 mm; median, 0.81 mm), and the means of the lateral, craniocaudal, and anteroposterior errors were 0.39±0.34 mm, 0.46±0.34 mm, and 0.57±0.59 mm, respectively. The setup error of the pelvic bony matching was 3.15±2.03 mm (range, 0.25 to 8.23 mm; median, 2.95 mm), and the error of craniocaudal direction (2.29±1.95 mm) was significantly larger than those of anteroposterior (1.73±1.31 mm) and lateral directions (0.45±0.37 mm), respectively (p< 0.05). Incidences of over 3 mm and 5 mm in setup difference among the

Detection of algorithmic trading

Science.gov (United States)

Bogoev, Dimitar; Karam, Arzé

2017-10-01

We develop a new approach to reflect the behavior of algorithmic traders. Specifically, we provide an analytical and tractable way to infer patterns of quote volatility and price momentum consistent with different types of strategies employed by algorithmic traders, and we propose two ratios to quantify these patterns. Quote volatility ratio is based on the rate of oscillation of the best ask and best bid quotes over an extremely short period of time; whereas price momentum ratio is based on identifying patterns of rapid upward or downward movement in prices. The two ratios are evaluated across several asset classes. We further run a two-stage Artificial Neural Network experiment on the quote volatility ratio; the first stage is used to detect the quote volatility patterns resulting from algorithmic activity, while the second is used to validate the quality of signal detection provided by our measure.

SU-F-J-137: Intrafractional Change of the Relationship Between Internal Fiducials and External Breathing Signal in Pancreatic Cancer Stereotactic Body Radiation Therapy

Energy Technology Data Exchange (ETDEWEB)

Pettersson, N; Murphy, J; Simpson, D; Cervino, L [University of California, San Diego, La Jolla, CA (United States)

2016-06-15

Purpose: The use of respiratory gating for management of breathing motion during stereotactic body radiation therapy (SBRT) relies on a consistent relationship between the breathing signal and the actual position of the internal target. This relationship was investigated in patients treated for pancreatic cancer. Methods: Four patients with pancreatic cancer undergoing SBRT that had implanted fiducials in the tumor were included in this study. Treatment plans were generated based on the exhale phases (30–70%) from the pre-treatment 4DCT. The margin between the internal target volume (ITV) and the planning target volume was three mm. After patient setup using cone-beam CT, simultaneous fluoroscopic imaging and breathing motion monitoring were used during at least three breathing cycles to verify the fiducial position and to optimize the gating window. After treatment, fluoroscopic images were acquired for verification purposes and exported for retrospective analyses. Fiducial positions were determined using a template-matching algorithm. For each dataset, we established a linear relationship between the fiducial position and the anterior-posterior (AP) breathing signal. The relationships before and after treatment were compared and the dose distribution impact evaluated. Results: Seven pre- and post-treatment fluoroscopic pairs were available for fiducial position analyses in the superior-inferior (SI) and left-right (LR) directions, and five in the AP direction. Time between image acquisitions was typically six to eight minutes. An average absolute change of 1.2±0.7 mm (range: 0.1–1.7) of the SI fiducial position relative to the external signal was found. Corresponding numbers for the LR and AP fiducial positions were 0.9±1.0 mm (range: 0.2–3.0) and 0.5±0.4 mm (range: 0.2–1.2), respectively. The dose distribution impact was small in both the ITV and organs-at-risk. Conclusion: The relationship change between fiducial position and external breathing

SU-F-J-137: Intrafractional Change of the Relationship Between Internal Fiducials and External Breathing Signal in Pancreatic Cancer Stereotactic Body Radiation Therapy

International Nuclear Information System (INIS)

Pettersson, N; Murphy, J; Simpson, D; Cervino, L

2016-01-01

Purpose: The use of respiratory gating for management of breathing motion during stereotactic body radiation therapy (SBRT) relies on a consistent relationship between the breathing signal and the actual position of the internal target. This relationship was investigated in patients treated for pancreatic cancer. Methods: Four patients with pancreatic cancer undergoing SBRT that had implanted fiducials in the tumor were included in this study. Treatment plans were generated based on the exhale phases (30–70%) from the pre-treatment 4DCT. The margin between the internal target volume (ITV) and the planning target volume was three mm. After patient setup using cone-beam CT, simultaneous fluoroscopic imaging and breathing motion monitoring were used during at least three breathing cycles to verify the fiducial position and to optimize the gating window. After treatment, fluoroscopic images were acquired for verification purposes and exported for retrospective analyses. Fiducial positions were determined using a template-matching algorithm. For each dataset, we established a linear relationship between the fiducial position and the anterior-posterior (AP) breathing signal. The relationships before and after treatment were compared and the dose distribution impact evaluated. Results: Seven pre- and post-treatment fluoroscopic pairs were available for fiducial position analyses in the superior-inferior (SI) and left-right (LR) directions, and five in the AP direction. Time between image acquisitions was typically six to eight minutes. An average absolute change of 1.2±0.7 mm (range: 0.1–1.7) of the SI fiducial position relative to the external signal was found. Corresponding numbers for the LR and AP fiducial positions were 0.9±1.0 mm (range: 0.2–3.0) and 0.5±0.4 mm (range: 0.2–1.2), respectively. The dose distribution impact was small in both the ITV and organs-at-risk. Conclusion: The relationship change between fiducial position and external breathing

Implementation of anomaly detection algorithms for detecting transmission control protocol synchronized flooding attacks

CSIR Research Space (South Africa)

Mkuzangwe, NNP

2015-08-01

Full Text Available This work implements two anomaly detection algorithms for detecting Transmission Control Protocol Synchronized (TCP SYN) flooding attack. The two algorithms are an adaptive threshold algorithm and a cumulative sum (CUSUM) based algorithm...

Fiducial-based fusion of 3D dental models with magnetic resonance imaging.

Science.gov (United States)

Abdi, Amir H; Hannam, Alan G; Fels, Sidney

2018-04-16

Magnetic resonance imaging (MRI) is widely used in study of maxillofacial structures. While MRI is the modality of choice for soft tissues, it fails to capture hard tissues such as bone and teeth. Virtual dental models, acquired by optical 3D scanners, are becoming more accessible for dental practice and are starting to replace the conventional dental impressions. The goal of this research is to fuse the high-resolution 3D dental models with MRI to enhance the value of imaging for applications where detailed analysis of maxillofacial structures are needed such as patient examination, surgical planning, and modeling. A subject-specific dental attachment was digitally designed and 3D printed based on the subject's face width and dental anatomy. The attachment contained 19 semi-ellipsoidal concavities in predetermined positions where oil-based ellipsoidal fiducial markers were later placed. The MRI was acquired while the subject bit on the dental attachment. The spatial position of the center of mass of each fiducial in the resultant MR Image was calculated by averaging its voxels' spatial coordinates. The rigid transformation to fuse dental models to MRI was calculated based on the least squares mapping of corresponding fiducials and solved via singular-value decomposition. The target registration error (TRE) of the proposed fusion process, calculated in a leave-one-fiducial-out fashion, was estimated at 0.49 mm. The results suggest that 6-9 fiducials suffice to achieve a TRE of equal to half the MRI voxel size. Ellipsoidal oil-based fiducials produce distinguishable intensities in MRI and can be used as registration fiducials. The achieved accuracy of the proposed approach is sufficient to leverage the merged 3D dental models with the MRI data for a finer analysis of the maxillofacial structures where complete geometry models are needed.

Transarterial Fiducial Marker Placement for Image-guided Proton Therapy for Malignant Liver Tumors

Energy Technology Data Exchange (ETDEWEB)

Ohta, Kengo, E-mail: yesterday.is.yesterday@gmail.com; Shimohira, Masashi, E-mail: mshimohira@gmail.com [Nagoya City University Graduate School of Medical Sciences, Department of Radiology (Japan); Sasaki, Shigeru, E-mail: ssasaki916@yahoo.co.jp; Iwata, Hiromitsu, E-mail: h-iwa-ncu@nifty.com; Nishikawa, Hiroko, E-mail: piroko1018@gmail.com; Ogino, Hiroyuki, E-mail: oginogio@gmail.com; Hara, Masaki, E-mail: mhara@med.nagoya-cu.ac.jp [Nagoya City West Medical Center, Department of Radiation Oncology, Nagoya Proton Therapy Center (Japan); Hashizume, Takuya, E-mail: tky300@gmail.com; Shibamoto, Yuta, E-mail: yshiba@med.nagoya-cu.ac.jp [Nagoya City University Graduate School of Medical Sciences, Department of Radiology (Japan)

2015-10-15

PurposeThe aim of this study is to analyze the technical and clinical success rates and safety of transarterial fiducial marker placement for image-guided proton therapy for malignant liver tumors.Methods and MaterialsFifty-five patients underwent this procedure as an interventional treatment. Five patients had 2 tumors, and 4 tumors required 2 markers each, so the total number of procedures was 64. The 60 tumors consisted of 46 hepatocellular carcinomas and 14 liver metastases. Five-mm-long straight microcoils of 0.018 inches in diameter were used as fiducial markers and placed in appropriate positions for each tumor. We assessed the technical and clinical success rates of transarterial fiducial marker placement, as well as the complications associated with it. Technical success was defined as the successful delivery and placement of the fiducial coil, and clinical success was defined as the completion of proton therapy.ResultsAll 64 fiducial coils were successfully installed, so the technical success rate was 100 % (64/64). Fifty-four patients underwent proton therapy without coil migration. In one patient, proton therapy was not performed because of obstructive jaundice due to bile duct invasion by hepatocellular carcinoma. Thus, the clinical success rate was 98 % (54/55). Slight bleeding was observed in one case, but it was stopped immediately and then observed. None of the patients developed hepatic infarctions due to fiducial marker migration.ConclusionTransarterial fiducial marker placement appears to be a useful and safe procedure for proton therapy for malignant liver tumors.

Transarterial Fiducial Marker Placement for Image-guided Proton Therapy for Malignant Liver Tumors

International Nuclear Information System (INIS)

Ohta, Kengo; Shimohira, Masashi; Sasaki, Shigeru; Iwata, Hiromitsu; Nishikawa, Hiroko; Ogino, Hiroyuki; Hara, Masaki; Hashizume, Takuya; Shibamoto, Yuta

2015-01-01

PurposeThe aim of this study is to analyze the technical and clinical success rates and safety of transarterial fiducial marker placement for image-guided proton therapy for malignant liver tumors.Methods and MaterialsFifty-five patients underwent this procedure as an interventional treatment. Five patients had 2 tumors, and 4 tumors required 2 markers each, so the total number of procedures was 64. The 60 tumors consisted of 46 hepatocellular carcinomas and 14 liver metastases. Five-mm-long straight microcoils of 0.018 inches in diameter were used as fiducial markers and placed in appropriate positions for each tumor. We assessed the technical and clinical success rates of transarterial fiducial marker placement, as well as the complications associated with it. Technical success was defined as the successful delivery and placement of the fiducial coil, and clinical success was defined as the completion of proton therapy.ResultsAll 64 fiducial coils were successfully installed, so the technical success rate was 100 % (64/64). Fifty-four patients underwent proton therapy without coil migration. In one patient, proton therapy was not performed because of obstructive jaundice due to bile duct invasion by hepatocellular carcinoma. Thus, the clinical success rate was 98 % (54/55). Slight bleeding was observed in one case, but it was stopped immediately and then observed. None of the patients developed hepatic infarctions due to fiducial marker migration.ConclusionTransarterial fiducial marker placement appears to be a useful and safe procedure for proton therapy for malignant liver tumors

A robust human face detection algorithm

Science.gov (United States)

Raviteja, Thaluru; Karanam, Srikrishna; Yeduguru, Dinesh Reddy V.

2012-01-01

Human face detection plays a vital role in many applications like video surveillance, managing a face image database, human computer interface among others. This paper proposes a robust algorithm for face detection in still color images that works well even in a crowded environment. The algorithm uses conjunction of skin color histogram, morphological processing and geometrical analysis for detecting human faces. To reinforce the accuracy of face detection, we further identify mouth and eye regions to establish the presence/absence of face in a particular region of interest.

Effects of line fiducial parameters and beamforming on ultrasound calibration

OpenAIRE

Ameri, Golafsoun; Baxter, John S. H.; McLeod, A. Jonathan; Peters, Terry M.; Chen, Elvis C. S.

2017-01-01

Ultrasound (US)-guided interventions are often enhanced via integration with an augmented reality environment, a necessary component of which is US calibration. Calibration requires the segmentation of fiducials, i.e., a phantom, in US images. Fiducial localization error (FLE) can decrease US calibration accuracy, which fundamentally affects the total accuracy of the interventional guidance system. Here, we investigate the effects of US image reconstruction techniques as well as phantom mater...

Fast algorithm for probabilistic bone edge detection (FAPBED)

Science.gov (United States)

Scepanovic, Danilo; Kirshtein, Joshua; Jain, Ameet K.; Taylor, Russell H.

2005-04-01

The registration of preoperative CT to intra-operative reality systems is a crucial step in Computer Assisted Orthopedic Surgery (CAOS). The intra-operative sensors include 3D digitizers, fiducials, X-rays and Ultrasound (US). FAPBED is designed to process CT volumes for registration to tracked US data. Tracked US is advantageous because it is real time, noninvasive, and non-ionizing, but it is also known to have inherent inaccuracies which create the need to develop a framework that is robust to various uncertainties, and can be useful in US-CT registration. Furthermore, conventional registration methods depend on accurate and absolute segmentation. Our proposed probabilistic framework addresses the segmentation-registration duality, wherein exact segmentation is not a prerequisite to achieve accurate registration. In this paper, we develop a method for fast and automatic probabilistic bone surface (edge) detection in CT images. Various features that influence the likelihood of the surface at each spatial coordinate are combined using a simple probabilistic framework, which strikes a fair balance between a high-level understanding of features in an image and the low-level number crunching of standard image processing techniques. The algorithm evaluates different features for detecting the probability of a bone surface at each voxel, and compounds the results of these methods to yield a final, low-noise, probability map of bone surfaces in the volume. Such a probability map can then be used in conjunction with a similar map from tracked intra-operative US to achieve accurate registration. Eight sample pelvic CT scans were used to extract feature parameters and validate the final probability maps. An un-optimized fully automatic Matlab code runs in five minutes per CT volume on average, and was validated by comparison against hand-segmented gold standards. The mean probability assigned to nonzero surface points was 0.8, while nonzero non-surface points had a mean

A fiducial skull marker for precise MRI-based stereotaxic surgery in large animal models.

Science.gov (United States)

Glud, Andreas Nørgaard; Bech, Johannes; Tvilling, Laura; Zaer, Hamed; Orlowski, Dariusz; Fitting, Lise Moberg; Ziedler, Dora; Geneser, Michael; Sangill, Ryan; Alstrup, Aage Kristian Olsen; Bjarkam, Carsten Reidies; Sørensen, Jens Christian Hedemann

2017-06-15

Stereotaxic neurosurgery in large animals is used widely in different sophisticated models, where precision is becoming more crucial as desired anatomical target regions are becoming smaller. Individually calculated coordinates are necessary in large animal models with cortical and subcortical anatomical differences. We present a convenient method to make an MRI-visible skull fiducial for 3D MRI-based stereotaxic procedures in larger experimental animals. Plastic screws were filled with either copper-sulfate solution or MRI-visible paste from a commercially available cranial head marker. The screw fiducials were inserted in the animal skulls and T1 weighted MRI was performed allowing identification of the inserted skull marker. Both types of fiducial markers were clearly visible on the MRÍs. This allows high precision in the stereotaxic space. The use of skull bone based fiducial markers gives high precision for both targeting and evaluation of stereotaxic systems. There are no metal artifacts and the fiducial is easily removed after surgery. The fiducial marker can be used as a very precise reference point, either for direct targeting or in evaluation of other stereotaxic systems. Copyright © 2017 Elsevier B.V. All rights reserved.

MUSIC algorithms for rebar detection

International Nuclear Information System (INIS)

Solimene, Raffaele; Leone, Giovanni; Dell’Aversano, Angela

2013-01-01

The MUSIC (MUltiple SIgnal Classification) algorithm is employed to detect and localize an unknown number of scattering objects which are small in size as compared to the wavelength. The ensemble of objects to be detected consists of both strong and weak scatterers. This represents a scattering environment challenging for detection purposes as strong scatterers tend to mask the weak ones. Consequently, the detection of more weakly scattering objects is not always guaranteed and can be completely impaired when the noise corrupting data is of a relatively high level. To overcome this drawback, here a new technique is proposed, starting from the idea of applying a two-stage MUSIC algorithm. In the first stage strong scatterers are detected. Then, information concerning their number and location is employed in the second stage focusing only on the weak scatterers. The role of an adequate scattering model is emphasized to improve drastically detection performance in realistic scenarios. (paper)

A hardware-algorithm co-design approach to optimize seizure detection algorithms for implantable applications.

Science.gov (United States)

Raghunathan, Shriram; Gupta, Sumeet K; Markandeya, Himanshu S; Roy, Kaushik; Irazoqui, Pedro P

2010-10-30

Implantable neural prostheses that deliver focal electrical stimulation upon demand are rapidly emerging as an alternate therapy for roughly a third of the epileptic patient population that is medically refractory. Seizure detection algorithms enable feedback mechanisms to provide focally and temporally specific intervention. Real-time feasibility and computational complexity often limit most reported detection algorithms to implementations using computers for bedside monitoring or external devices communicating with the implanted electrodes. A comparison of algorithms based on detection efficacy does not present a complete picture of the feasibility of the algorithm with limited computational power, as is the case with most battery-powered applications. We present a two-dimensional design optimization approach that takes into account both detection efficacy and hardware cost in evaluating algorithms for their feasibility in an implantable application. Detection features are first compared for their ability to detect electrographic seizures from micro-electrode data recorded from kainate-treated rats. Circuit models are then used to estimate the dynamic and leakage power consumption of the compared features. A score is assigned based on detection efficacy and the hardware cost for each of the features, then plotted on a two-dimensional design space. An optimal combination of compared features is used to construct an algorithm that provides maximal detection efficacy per unit hardware cost. The methods presented in this paper would facilitate the development of a common platform to benchmark seizure detection algorithms for comparison and feasibility analysis in the next generation of implantable neuroprosthetic devices to treat epilepsy. Copyright © 2010 Elsevier B.V. All rights reserved.

Local Community Detection Algorithm Based on Minimal Cluster

Directory of Open Access Journals (Sweden)

Yong Zhou

2016-01-01

Full Text Available In order to discover the structure of local community more effectively, this paper puts forward a new local community detection algorithm based on minimal cluster. Most of the local community detection algorithms begin from one node. The agglomeration ability of a single node must be less than multiple nodes, so the beginning of the community extension of the algorithm in this paper is no longer from the initial node only but from a node cluster containing this initial node and nodes in the cluster are relatively densely connected with each other. The algorithm mainly includes two phases. First it detects the minimal cluster and then finds the local community extended from the minimal cluster. Experimental results show that the quality of the local community detected by our algorithm is much better than other algorithms no matter in real networks or in simulated networks.

Dosimetric adaptive IMRT driven by fiducial points

International Nuclear Information System (INIS)

Crijns, Wouter; Van Herck, Hans; Defraene, Gilles; Van den Bergh, Laura; Haustermans, Karin; Slagmolen, Pieter; Maes, Frederik; Van den Heuvel, Frank

2014-01-01

Purpose: Intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy have become standard treatments but are more sensitive to anatomical variations than 3D conformal techniques. To correct for inter- and intrafraction anatomical variations, fast and easy to implement methods are needed. Here, the authors propose a full dosimetric IMRT correction that finds a compromise in-between basic repositioning (the current clinical practice) and full replanning. It simplifies replanning by avoiding a recontouring step and a full dose calculation. It surpasses repositioning by updating the preoptimized fluence and monitor units (MU) using a limited number of fiducial points and a pretreatment (CB)CT. To adapt the fluence the fiducial points were projected in the beam's eye view (BEV). To adapt the MUs, point dose calculation towards the same fiducial points were performed. The proposed method is intrinsically fast and robust, and simple to understand for operators, because of the use of only four fiducial points and the beam data based point dose calculations. Methods: To perform our dosimetric adaptation, two fluence corrections in the BEV are combined with two MU correction steps along the beam's path. (1) A transformation of the fluence map such that it is realigned with the current target geometry. (2) A correction for an unintended scaling of the penumbra margin when the treatment beams scale to the current target size. (3) A correction for the target depth relative to the body contour and (4) a correction for the target distance to the source. The impact of the correction strategy and its individual components was evaluated by simulations on a virtual prostate phantom. This heterogeneous reference phantom was systematically subjected to population based prostate transformations to simulate interfraction variations. Additionally, a patient example illustrated the clinical practice. The correction strategy was evaluated using both dosimetric

Dosimetric adaptive IMRT driven by fiducial points

Energy Technology Data Exchange (ETDEWEB)

Crijns, Wouter, E-mail: wouter.crijns@uzleuven.be [Department of Oncology, Laboratory of Experimental Radiotherapy, KU Leuven, Herestraat 49, 3000 Leuven, Belgium and Medical Imaging Research Center, KU Leuven, Herestraat 49, 3000 Leuven (Belgium); Van Herck, Hans [Medical Imaging Research Center, KU Leuven, Herestraat 49, 3000 Leuven, Belgium and Department of Electrical Engineering (ESAT) – PSI, Center for the Processing of Speech and Images, KU Leuven, 3000 Leuven (Belgium); Defraene, Gilles; Van den Bergh, Laura; Haustermans, Karin [Department of Oncology, Laboratory of Experimental Radiotherapy, KU Leuven, Herestraat 49, 3000 Leuven (Belgium); Slagmolen, Pieter [Medical Imaging Research Center, KU Leuven, Herestraat 49, 3000 Leuven (Belgium); Department of Electrical Engineering (ESAT) – PSI, Center for the Processing of Speech and Images, KU Leuven, 3000 Leuven (Belgium); iMinds-KU Leuven Medical IT Department, KU Leuven, 3000 Leuven (Belgium); Maes, Frederik [Medical Imaging Research Center, KU Leuven, Herestraat 49, 3000 Leuven (Belgium); Department of Electrical Engineering (ESAT) – PSI, Center for the Processing of Speech and Images, KU Leuven and iMinds, 3000 Leuven (Belgium); Van den Heuvel, Frank [Department of Oncology, Laboratory of Experimental Radiotherapy, KU Leuven, Herestraat 49, 3000 Leuven, Belgium and Department of Oncology, MRC-CR-UK Gray Institute of Radiation Oncology and Biology, University of Oxford, Oxford OX1 2JD (United Kingdom)

2014-06-15

Purpose: Intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy have become standard treatments but are more sensitive to anatomical variations than 3D conformal techniques. To correct for inter- and intrafraction anatomical variations, fast and easy to implement methods are needed. Here, the authors propose a full dosimetric IMRT correction that finds a compromise in-between basic repositioning (the current clinical practice) and full replanning. It simplifies replanning by avoiding a recontouring step and a full dose calculation. It surpasses repositioning by updating the preoptimized fluence and monitor units (MU) using a limited number of fiducial points and a pretreatment (CB)CT. To adapt the fluence the fiducial points were projected in the beam's eye view (BEV). To adapt the MUs, point dose calculation towards the same fiducial points were performed. The proposed method is intrinsically fast and robust, and simple to understand for operators, because of the use of only four fiducial points and the beam data based point dose calculations. Methods: To perform our dosimetric adaptation, two fluence corrections in the BEV are combined with two MU correction steps along the beam's path. (1) A transformation of the fluence map such that it is realigned with the current target geometry. (2) A correction for an unintended scaling of the penumbra margin when the treatment beams scale to the current target size. (3) A correction for the target depth relative to the body contour and (4) a correction for the target distance to the source. The impact of the correction strategy and its individual components was evaluated by simulations on a virtual prostate phantom. This heterogeneous reference phantom was systematically subjected to population based prostate transformations to simulate interfraction variations. Additionally, a patient example illustrated the clinical practice. The correction strategy was evaluated using both dosimetric

Effects of rotation and systematic occlusion on fiducial marker recognition

Directory of Open Access Journals (Sweden)

Sagitov Artur

2017-01-01

Full Text Available Fiducial marker systems consist of patterns that are placed in environment for miscellaneous applications and are further automatically detected with cameras. A variety of applications determines the criteria, which characterize qualitative properties of a marker and include such evaluation benchmarks as resilience to occlusion, distance to a marker, false positive and false negative rates, sensitivity to illumination, and others. The paper compares existing ARTag, AprilTag, and CALTag systems utilizing a high fidelity camera, which is a main vision sensor of a full-size Russian humanoid robot AR-601M. In experiments the comparison of the three marker systems reliability and detection rate in occlusions of various types and intensities was verified. Finally, a preferable for AR-601M robot visual applications marker system was selected.

Fiducialization of the small-aperture quadrupoles based on the vibrating wire method

Energy Technology Data Exchange (ETDEWEB)

Wang, Baichuan, E-mail: wangbaichuan@nint.ac.cn [State Key Laboratory of Intense Pulsed Radiation Simulation and Effect (Northwest Institute of Nuclear Technology), Xi' an 710024 (China); Tsinghua University, Beijing 100084 (China); Zheng, Shuxin, E-mail: zhengsx@tsinghua.edu.cn [Tsinghua University, Beijing 100084 (China); Wu, Lin; Du, Changtong; Xing, Qingzi [Tsinghua University, Beijing 100084 (China); Wang, Zhongming; Qiu, Mengtong [State Key Laboratory of Intense Pulsed Radiation Simulation and Effect (Northwest Institute of Nuclear Technology), Xi' an 710024 (China); Wang, Xuewu [Tsinghua University, Beijing 100084 (China)

2016-03-11

A fiducialization method based on vibrating wire is described dedicated to the problem of locating the magnetic center relative to external fiducials for the small-aperture quadrupoles. The advantage of this method is that the measurement of the wire position, which may be the main error source, is no longer needed. The position of the magnetic center can be directly obtained by measuring the position shift of the magnet fiducials. This method has been validated on small Permanent Magnet Quadrupoles (PMQs). Experiments have confirmed its feasibility of measuring PMQs with good repeatability of about 10 μm, and shown its high sensitivity as well as convenience.

The ν-cleus experiment: a gram-scale fiducial-volume cryogenic detector for the first detection of coherent neutrino-nucleus scattering

Energy Technology Data Exchange (ETDEWEB)

Strauss, R.; Rothe, J.; Angloher, G.; Hauff, D.; Mancuso, M.; Petricca, F.; Proebst, F.; Seidel, W.; Stodolsky, L. [Max-Planck-Institut fuer Physik, Muenchen (Germany); Bento, A. [Universidade de Coimbra, CIUC, Departamento de Fisica, Coimbra (Portugal); Guetlein, A.; Kluck, H.; Schieck, J. [Institut fuer Hochenergiephysik, Oesterreichische Akademie der Wissenschaften, Vienna (Austria); Vienna University of Technology, Atominstitut, Vienna (Austria); Oberauer, L.; Schoenert, S. [Technische Universitaet Muenchen, Physik-Department, Garching (Germany)

2017-08-15

We discuss a small-scale experiment, called ν-cleus, for the first detection of coherent neutrino-nucleus scattering by probing nuclear-recoil energies down to the 10 eV regime. The detector consists of low-threshold CaWO{sub 4} and Al{sub 2}O{sub 3} calorimeter arrays with a total mass of about 10 g and several cryogenic veto detectors operated at millikelvin temperatures. Realizing a fiducial volume and a multi-element target, the detector enables active discrimination of γ, neutron and surface backgrounds. A first prototype Al{sub 2}O{sub 3} device, operated above ground in a setup without shielding, has achieved an energy threshold of ∝20 eV and further improvements are in reach. A sensitivity study for the detection of coherent neutrino scattering at nuclear power plants shows a unique discovery potential (5 σ) within a measuring time of

Seizure detection algorithms based on EMG signals

DEFF Research Database (Denmark)

Conradsen, Isa

Background: the currently used non-invasive seizure detection methods are not reliable. Muscle fibers are directly connected to the nerves, whereby electric signals are generated during activity. Therefore, an alarm system on electromyography (EMG) signals is a theoretical possibility. Objective...... on the amplitude of the signal. The other algorithm was based on information of the signal in the frequency domain, and it focused on synchronisation of the electrical activity in a single muscle during the seizure. Results: The amplitude-based algorithm reliably detected seizures in 2 of the patients, while...... the frequency-based algorithm was efficient for detecting the seizures in the third patient. Conclusion: Our results suggest that EMG signals could be used to develop an automatic seizuredetection system. However, different patients might require different types of algorithms /approaches....

Fiducial registration error as a statistical process control metric in image-guided radiotherapy with prostatic markers

International Nuclear Information System (INIS)

Ung, M.N.; Wee, Leonard

2010-01-01

Full text: Portal imaging of implanted fiducial markers has been in use for image-guided radiotherapy (TORT) of prostate cancer, with ample attention to localization accuracy and organ motion. The geometric uncertainties in point-based rigid-body (PBRB) image registration during localization of prostate fiducial markers can be quantified in terms of a fiducial registration error (FRE). Statistical process control charts for individual patients can be designed to identify potentially significant deviation of FRE from expected behaviour. In this study, the aim was to retrospectively apply statistical process control methods to FREs in 34 individuals to identify parameters that may impact on the process stability in image-based localization. A robust procedure for estimating control parameters, control lim its and fixed tolerance levels from a small number of initial observations has been proposed and discussed. Four distinct types of qualitative control chart behavior have been observed. Probable clinical factors leading to IORT process instability are discussed in light of the control chart behaviour. Control charts have been shown to be a useful decision-making tool for detecting potentially out-of control processes on an individual basis. It can sensitively identify potential problems that warrant more detailed investigation in the 10RT of prostate cancer.

AdaBoost-based algorithm for network intrusion detection.

Science.gov (United States)

Hu, Weiming; Hu, Wei; Maybank, Steve

2008-04-01

Network intrusion detection aims at distinguishing the attacks on the Internet from normal use of the Internet. It is an indispensable part of the information security system. Due to the variety of network behaviors and the rapid development of attack fashions, it is necessary to develop fast machine-learning-based intrusion detection algorithms with high detection rates and low false-alarm rates. In this correspondence, we propose an intrusion detection algorithm based on the AdaBoost algorithm. In the algorithm, decision stumps are used as weak classifiers. The decision rules are provided for both categorical and continuous features. By combining the weak classifiers for continuous features and the weak classifiers for categorical features into a strong classifier, the relations between these two different types of features are handled naturally, without any forced conversions between continuous and categorical features. Adaptable initial weights and a simple strategy for avoiding overfitting are adopted to improve the performance of the algorithm. Experimental results show that our algorithm has low computational complexity and error rates, as compared with algorithms of higher computational complexity, as tested on the benchmark sample data.

Training nuclei detection algorithms with simple annotations

Directory of Open Access Journals (Sweden)

Henning Kost

2017-01-01

Full Text Available Background: Generating good training datasets is essential for machine learning-based nuclei detection methods. However, creating exhaustive nuclei contour annotations, to derive optimal training data from, is often infeasible. Methods: We compared different approaches for training nuclei detection methods solely based on nucleus center markers. Such markers contain less accurate information, especially with regard to nuclear boundaries, but can be produced much easier and in greater quantities. The approaches use different automated sample extraction methods to derive image positions and class labels from nucleus center markers. In addition, the approaches use different automated sample selection methods to improve the detection quality of the classification algorithm and reduce the run time of the training process. We evaluated the approaches based on a previously published generic nuclei detection algorithm and a set of Ki-67-stained breast cancer images. Results: A Voronoi tessellation-based sample extraction method produced the best performing training sets. However, subsampling of the extracted training samples was crucial. Even simple class balancing improved the detection quality considerably. The incorporation of active learning led to a further increase in detection quality. Conclusions: With appropriate sample extraction and selection methods, nuclei detection algorithms trained on the basis of simple center marker annotations can produce comparable quality to algorithms trained on conventionally created training sets.

A Plagiarism Detection Algorithm based on Extended Winnowing

Directory of Open Access Journals (Sweden)

Duan Xuliang

2017-01-01

Full Text Available Plagiarism is a common problem faced by academia and education. Mature commercial plagiarism detection system has the advantages of comprehensive and high accuracy, but the expensive detection costs make it unsuitable for real-time, lightweight application environment such as the student assignments plagiarism detection. This paper introduces the method of extending classic Winnowing plagiarism detection algorithm, expands the algorithm in functionality. The extended algorithm can retain the text location and length information in original document while extracting the fingerprints of a document, so that the locating and marking for plagiarism text fragment are much easier to achieve. The experimental results and several years of running practice show that the expansion of the algorithm has little effect on its performance, normal hardware configuration of PC will be able to meet small and medium-sized applications requirements. Based on the characteristics of lightweight, high efficiency, reliability and flexibility of Winnowing, the extended algorithm further enhances the adaptability and extends the application areas.

Quantification and comparison of visibility and image artifacts of a new liquid fiducial marker in a lung phantom for image-guided radiation therapy

Energy Technology Data Exchange (ETDEWEB)

Scherman Rydhög, Jonas, E-mail: per.jonas.scherman.rydhoeg@regionh.dk; Munck af Rosenschöld, Per [Department of Oncology, Section of Radiotherapy, 3994, Rigshospitalet, Blegdamsvej 9, Copenhagen 2100, Denmark and Niels Bohr Institute, University of Copenhagen, Blegdamsvej 17, Copenhagen 2100 (Denmark); Irming Jølck, Rasmus; Andresen, Thomas Lars [DTU Nanotech, Department of Micro- and Nanotechnology, Center for Nanomedicine and Theranostics, Technical University of Denmark, Building 423, Kongens Lyngby 2800 (Denmark)

2015-06-15

Purpose: A new biodegradable liquid fiducial marker was devised to allow for easy insertion in lung tumors using thin needles. The purpose of this study was to evaluate the visibility of the liquid fiducial markers for image-guided radiation therapy and compare to existing solid fiducial markers and to one existing liquid fiducial marker currently commercially available. Methods: Fiducial marker visibility was quantified in terms of contrast to noise ratio (CNR) on planar kilovoltage x-ray images in a thorax phantom for different concentrations of the radio-opaque component of the new liquid fiducial marker, four solid fiducial markers, and one existing liquid fiducial marker. Additionally, the image artifacts produced on computer tomography (CT) and cone-beam CT (CBCT) of all fiducial markers were quantified. Results: The authors found that the new liquid fiducial marker with the highest concentration of the radio-opaque component had a CNR > 2.05 for 62/63 exposures, which compared favorably to the existing solid fiducial markers and to the existing liquid fiducial marker evaluated. On CT and CBCT, the new liquid fiducial marker with the highest concentration produced lower streaking index artifact (30 and 14, respectively) than the solid gold markers (113 and 20, respectively) and the existing liquid fiducial marker (39 and 20, respectively). The size of the image artifact was larger for all of the liquid fiducial markers compared to the solid fiducial markers because of their larger physical size. Conclusions: The visibility and the image artifacts produced by the new liquid fiducial markers were comparable to existing solid fiducial markers and the existing liquid fiducial marker. The authors conclude that the new liquid fiducial marker represents an alternative to the fiducial markers tested.

Improvement and implementation for Canny edge detection algorithm

Science.gov (United States)

Yang, Tao; Qiu, Yue-hong

2015-07-01

Edge detection is necessary for image segmentation and pattern recognition. In this paper, an improved Canny edge detection approach is proposed due to the defect of traditional algorithm. A modified bilateral filter with a compensation function based on pixel intensity similarity judgment was used to smooth image instead of Gaussian filter, which could preserve edge feature and remove noise effectively. In order to solve the problems of sensitivity to the noise in gradient calculating, the algorithm used 4 directions gradient templates. Finally, Otsu algorithm adaptively obtain the dual-threshold. All of the algorithm simulated with OpenCV 2.4.0 library in the environments of vs2010, and through the experimental analysis, the improved algorithm has been proved to detect edge details more effectively and with more adaptability.

Nearest Neighbour Corner Points Matching Detection Algorithm

Directory of Open Access Journals (Sweden)

Zhang Changlong

2015-01-01

Full Text Available Accurate detection towards the corners plays an important part in camera calibration. To deal with the instability and inaccuracies of present corner detection algorithm, the nearest neighbour corners match-ing detection algorithms was brought forward. First, it dilates the binary image of the photographed pictures, searches and reserves quadrilateral outline of the image. Second, the blocks which accord with chess-board-corners are classified into a class. If too many blocks in class, it will be deleted; if not, it will be added, and then let the midpoint of the two vertex coordinates be the rough position of corner. At last, it precisely locates the position of the corners. The Experimental results have shown that the algorithm has obvious advantages on accuracy and validity in corner detection, and it can give security for camera calibration in traffic accident measurement.

Acoustic change detection algorithm using an FM radio

Science.gov (United States)

Goldman, Geoffrey H.; Wolfe, Owen

2012-06-01

The U.S. Army is interested in developing low-cost, low-power, non-line-of-sight sensors for monitoring human activity. One modality that is often overlooked is active acoustics using sources of opportunity such as speech or music. Active acoustics can be used to detect human activity by generating acoustic images of an area at different times, then testing for changes among the imagery. A change detection algorithm was developed to detect physical changes in a building, such as a door changing positions or a large box being moved using acoustics sources of opportunity. The algorithm is based on cross correlating the acoustic signal measured from two microphones. The performance of the algorithm was shown using data generated with a hand-held FM radio as a sound source and two microphones. The algorithm could detect a door being opened in a hallway.

A Formally Verified Conflict Detection Algorithm for Polynomial Trajectories

Science.gov (United States)

Narkawicz, Anthony; Munoz, Cesar

2015-01-01

In air traffic management, conflict detection algorithms are used to determine whether or not aircraft are predicted to lose horizontal and vertical separation minima within a time interval assuming a trajectory model. In the case of linear trajectories, conflict detection algorithms have been proposed that are both sound, i.e., they detect all conflicts, and complete, i.e., they do not present false alarms. In general, for arbitrary nonlinear trajectory models, it is possible to define detection algorithms that are either sound or complete, but not both. This paper considers the case of nonlinear aircraft trajectory models based on polynomial functions. In particular, it proposes a conflict detection algorithm that precisely determines whether, given a lookahead time, two aircraft flying polynomial trajectories are in conflict. That is, it has been formally verified that, assuming that the aircraft trajectories are modeled as polynomial functions, the proposed algorithm is both sound and complete.

Detection of Illegitimate Emails using Boosting Algorithm

DEFF Research Database (Denmark)

Nizamani, Sarwat; Memon, Nasrullah; Wiil, Uffe Kock

2011-01-01

and spam email detection. For our desired task, we have applied a boosting technique. With the use of boosting we can achieve high accuracy of traditional classification algorithms. When using boosting one has to choose a suitable weak learner as well as the number of boosting iterations. In this paper, we......In this paper, we report on experiments to detect illegitimate emails using boosting algorithm. We call an email illegitimate if it is not useful for the receiver or for the society. We have divided the problem into two major areas of illegitimate email detection: suspicious email detection...

SU-E-J-37: Feasibility of Utilizing Carbon Fiducials to Increase Localization Accuracy of Lumpectomy Cavity for Partial Breast Irradiation

International Nuclear Information System (INIS)

Zhang, Y; Hieken, T; Mutter, R; Park, S; Yan, E; Brinkmann, D; Pafundi, D

2015-01-01

Purpose To investigate the feasibility of utilizing carbon fiducials to increase localization accuracy of lumpectomy cavity for partial breast irradiation (PBI). Methods Carbon fiducials were placed intraoperatively in the lumpectomy cavity following resection of breast cancer in 11 patients. The patients were scheduled to receive whole breast irradiation (WBI) with a boost or 3D-conformal PBI. WBI patients were initially setup to skin tattoos using lasers, followed by orthogonal kV on-board-imaging (OBI) matching to bone per clinical practice. Cone beam CT (CBCT) was acquired weekly for offline review. For the boost component of WBI and PBI, patients were setup with lasers, followed by OBI matching to fiducials, with final alignment by CBCT matching to fiducials. Using carbon fiducials as a surrogate for the lumpectomy cavity and CBCT matching to fiducials as the gold standard, setup uncertainties to lasers, OBI bone, OBI fiducials, and CBCT breast were compared. Results Minimal imaging artifacts were introduced by fiducials on the planning CT and CBCT. The fiducials were sufficiently visible on OBI for online localization. The mean magnitude and standard deviation of setup errors were 8.4mm ± 5.3 mm (n=84), 7.3mm ± 3.7mm (n=87), 2.2mm ± 1.6mm (n=40) and 4.8mm ± 2.6mm (n=87), for lasers, OBI bone, OBI fiducials and CBCT breast tissue, respectively. Significant migration occurred in one of 39 implanted fiducials in a patient with a large postoperative seroma. Conclusion OBI carbon fiducial-based setup can improve localization accuracy with minimal imaging artifacts. With increased localization accuracy, setup uncertainties can be reduced from 8mm using OBI bone matching to 3mm using OBI fiducial matching for PBI treatment. This work demonstrates the feasibility of utilizing carbon fiducials to increase localization accuracy to the lumpectomy cavity for PBI. This may be particularly attractive for localization in the setting of proton therapy and other scenarios

SU-E-J-37: Feasibility of Utilizing Carbon Fiducials to Increase Localization Accuracy of Lumpectomy Cavity for Partial Breast Irradiation

Energy Technology Data Exchange (ETDEWEB)

Zhang, Y; Hieken, T; Mutter, R; Park, S; Yan, E; Brinkmann, D; Pafundi, D [Mayo Clinic, Rochester, MN (United States)

2015-06-15

Purpose To investigate the feasibility of utilizing carbon fiducials to increase localization accuracy of lumpectomy cavity for partial breast irradiation (PBI). Methods Carbon fiducials were placed intraoperatively in the lumpectomy cavity following resection of breast cancer in 11 patients. The patients were scheduled to receive whole breast irradiation (WBI) with a boost or 3D-conformal PBI. WBI patients were initially setup to skin tattoos using lasers, followed by orthogonal kV on-board-imaging (OBI) matching to bone per clinical practice. Cone beam CT (CBCT) was acquired weekly for offline review. For the boost component of WBI and PBI, patients were setup with lasers, followed by OBI matching to fiducials, with final alignment by CBCT matching to fiducials. Using carbon fiducials as a surrogate for the lumpectomy cavity and CBCT matching to fiducials as the gold standard, setup uncertainties to lasers, OBI bone, OBI fiducials, and CBCT breast were compared. Results Minimal imaging artifacts were introduced by fiducials on the planning CT and CBCT. The fiducials were sufficiently visible on OBI for online localization. The mean magnitude and standard deviation of setup errors were 8.4mm ± 5.3 mm (n=84), 7.3mm ± 3.7mm (n=87), 2.2mm ± 1.6mm (n=40) and 4.8mm ± 2.6mm (n=87), for lasers, OBI bone, OBI fiducials and CBCT breast tissue, respectively. Significant migration occurred in one of 39 implanted fiducials in a patient with a large postoperative seroma. Conclusion OBI carbon fiducial-based setup can improve localization accuracy with minimal imaging artifacts. With increased localization accuracy, setup uncertainties can be reduced from 8mm using OBI bone matching to 3mm using OBI fiducial matching for PBI treatment. This work demonstrates the feasibility of utilizing carbon fiducials to increase localization accuracy to the lumpectomy cavity for PBI. This may be particularly attractive for localization in the setting of proton therapy and other scenarios

Quantification and comparison of visibility and image artifacts of a new liquid fiducial marker in a lung phantom for image-guided radiation therapy

DEFF Research Database (Denmark)

Rydhög, Jonas Scherman; Jølck, Rasmus Irming; Andresen, Thomas Lars

2015-01-01

fiducial marker, four solid fiducial markers, and one existing liquid fiducial marker. Additionally, the image artifacts produced on computer tomography (CT) and cone-beam CT (CBCT) of all fiducial markers were quantified. Results : The authors found that the new liquid fiducial marker with the highest...... concentration of the radio-opaque component had a CNR > 2.05 for 62/63 exposures, which compared favorably to the existing solid fiducial markers and to the existing liquid fiducial marker evaluated. On CT and CBCT, the new liquid fiducial marker with the highest concentration produced lower streaking index...

Test of TEDA, Tsunami Early Detection Algorithm

Science.gov (United States)

Bressan, Lidia; Tinti, Stefano

2010-05-01

Tsunami detection in real-time, both offshore and at the coastline, plays a key role in Tsunami Warning Systems since it provides so far the only reliable and timely proof of tsunami generation, and is used to confirm or cancel tsunami warnings previously issued on the basis of seismic data alone. Moreover, in case of submarine or coastal landslide generated tsunamis, which are not announced by clear seismic signals and are typically local, real-time detection at the coastline might be the fastest way to release a warning, even if the useful time for emergency operations might be limited. TEDA is an algorithm for real-time detection of tsunami signal on sea-level records, developed by the Tsunami Research Team of the University of Bologna. The development and testing of the algorithm has been accomplished within the framework of the Italian national project DPC-INGV S3 and the European project TRANSFER. The algorithm is to be implemented at station level, and it is based therefore only on sea-level data of a single station, either a coastal tide-gauge or an offshore buoy. TEDA's principle is to discriminate the first tsunami wave from the previous background signal, which implies the assumption that the tsunami waves introduce a difference in the previous sea-level signal. Therefore, in TEDA the instantaneous (most recent) and the previous background sea-level elevation gradients are characterized and compared by proper functions (IS and BS) that are updated at every new data acquisition. Detection is triggered when the instantaneous signal function passes a set threshold and at the same time it is significantly bigger compared to the previous background signal. The functions IS and BS depend on temporal parameters that allow the algorithm to be adapted different situations: in general, coastal tide-gauges have a typical background spectrum depending on the location where the instrument is installed, due to local topography and bathymetry, while offshore buoys are

Adaptive sampling algorithm for detection of superpoints

Institute of Scientific and Technical Information of China (English)

CHENG Guang; GONG Jian; DING Wei; WU Hua; QIANG ShiQiang

2008-01-01

The superpoints are the sources (or the destinations) that connect with a great deal of destinations (or sources) during a measurement time interval, so detecting the superpoints in real time is very important to network security and management. Previous algorithms are not able to control the usage of the memory and to deliver the desired accuracy, so it is hard to detect the superpoints on a high speed link in real time. In this paper, we propose an adaptive sampling algorithm to detect the superpoints in real time, which uses a flow sample and hold module to reduce the detection of the non-superpoints and to improve the measurement accuracy of the superpoints. We also design a data stream structure to maintain the flow records, which compensates for the flow Hash collisions statistically. An adaptive process based on different sampling probabilities is used to maintain the recorded IP ad dresses in the limited memory. This algorithm is compared with the other algo rithms by analyzing the real network trace data. Experiment results and mathematic analysis show that this algorithm has the advantages of both the limited memory requirement and high measurement accuracy.

Algorithmic detectability threshold of the stochastic block model

Science.gov (United States)

Kawamoto, Tatsuro

2018-03-01

The assumption that the values of model parameters are known or correctly learned, i.e., the Nishimori condition, is one of the requirements for the detectability analysis of the stochastic block model in statistical inference. In practice, however, there is no example demonstrating that we can know the model parameters beforehand, and there is no guarantee that the model parameters can be learned accurately. In this study, we consider the expectation-maximization (EM) algorithm with belief propagation (BP) and derive its algorithmic detectability threshold. Our analysis is not restricted to the community structure but includes general modular structures. Because the algorithm cannot always learn the planted model parameters correctly, the algorithmic detectability threshold is qualitatively different from the one with the Nishimori condition.

STREAMFINDER I: A New Algorithm for detecting Stellar Streams

Science.gov (United States)

Malhan, Khyati; Ibata, Rodrigo A.

2018-04-01

We have designed a powerful new algorithm to detect stellar streams in an automated and systematic way. The algorithm, which we call the STREAMFINDER, is well suited for finding dynamically cold and thin stream structures that may lie along any simple or complex orbits in Galactic stellar surveys containing any combination of positional and kinematic information. In the present contribution we introduce the algorithm, lay out the ideas behind it, explain the methodology adopted to detect streams and detail its workings by running it on a suite of simulations of mock Galactic survey data of similar quality to that expected from the ESA/Gaia mission. We show that our algorithm is able to detect even ultra-faint stream features lying well below previous detection limits. Tests show that our algorithm will be able to detect distant halo stream structures >10° long containing as few as ˜15 members (ΣG ˜ 33.6 mag arcsec-2) in the Gaia dataset.

Sample positioning in neutron diffraction experiments using a multi-material fiducial marker

Energy Technology Data Exchange (ETDEWEB)

Marais, D., E-mail: Deon.Marais@necsa.co.za [Research and Development Division, South African Nuclear Energy Corporation (Necsa) SOC Limited, PO Box 582, Pretoria 0001 (South Africa); School of Mechanical and Nuclear Engineering, North-West University, Potchefstroom 2520 (South Africa); Venter, A.M., E-mail: Andrew.Venter@necsa.co.za [Research and Development Division, South African Nuclear Energy Corporation (Necsa) SOC Limited, PO Box 582, Pretoria 0001 (South Africa); Faculty of Agriculture Science and Technology, North-West University, Mahikeng 2790 (South Africa); Markgraaff, J., E-mail: Johan.Markgraaff@nwu.ac.za [School of Mechanical and Nuclear Engineering, North-West University, Potchefstroom 2520 (South Africa); James, J., E-mail: Jon.James@open.ac.uk [Faculty of Mathematics, Computing and Technology, The Open University, Milton Keynes, MK76AA England (United Kingdom)

2017-01-01

An alternative sample positioning method is reported for use in conjunction with sample positioning and experiment planning software systems deployed on some neutron diffraction strain scanners. In this approach, the spherical fiducial markers and location trackers used with optical metrology hardware are replaced with a specifically designed multi-material fiducial marker that requires one diffraction measurement. In a blind setting, the marker position can be determined within an accuracy of ±164 µm with respect to the instrument gauge volume. The scheme is based on a pre-determined relationship that links the diffracted peak intensity to the absolute positioning of the fiducial marker with respect to the instrument gauge volume. Two methods for establishing the linking relationship are presented, respectively based on fitting multi-dimensional quadratic functions and a cross-correlation artificial neural network.

Safety and Efficacy of Ultrasound-Guided Fiducial Marker Implantation for CyberKnife Radiation Therapy

Energy Technology Data Exchange (ETDEWEB)

Kim, Jae Hyun; Hong, Seong; Sook; Kim, Jung Hoon; Park, Hyun Jeong; Chang, Yun Woo; Chang, A Ram [Soonchunhyang University Seoul Hospital, Seoul (Korea, Republic of); Kwon, Seok Beom [Hallym University College of Medicine, Chuncheon (Korea, Republic of)

2012-06-15

To evaluate the safety and technical success rate of an ultrasound-guided fiducial marker implantation in preparation for CyberKnife radiation therapy. We retrospectively reviewed 270 percutaneous ultrasound-guided fiducial marker implantations in 77 patients, which were performed from June 2008 through March 2011. Of 270 implantations, 104 were implanted in metastatic lymph nodes, 96 were in the liver, 39 were in the pancreas, and 31 were in the prostate. During and after the implantation, major and minor procedure-related complications were documented. We defined technical success as the implantation enabling adequate treatment planning and CT simulation. The major and minor complication rates were 1% and 21%, respectively. One patient who had an implantation in the liver suffered severe abdominal pain, biloma, and pleural effusion, which were considered as major complication. Abdominal pain was the most common complication in 11 patients (14%). Among nine patients who had markers inserted in the prostate, one had transient hematuria for less than 24 hours, and the other experienced transient voiding difficulty. Of the 270 implantations, 261 were successful (97%). The reasons for unsuccessful implantations included migration of fiducial markers (five implantations, 2%) and failure to discriminate the fiducial markers (three implantations, 1%). Among the unsuccessful implantation cases, six patients required additional procedures (8%). The symptomatic complications following ultrasound-guided percutaneous implantation of fiducial markers are relatively low. However, careful consideration of the relatively higher rate of migration and discrimination failure is needed when performing ultrasound-guided percutaneous implantations of fiducial markers.

An Early Fire Detection Algorithm Using IP Cameras

Directory of Open Access Journals (Sweden)

Hector Perez-Meana

2012-05-01

Full Text Available The presence of smoke is the first symptom of fire; therefore to achieve early fire detection, accurate and quick estimation of the presence of smoke is very important. In this paper we propose an algorithm to detect the presence of smoke using video sequences captured by Internet Protocol (IP cameras, in which important features of smoke, such as color, motion and growth properties are employed. For an efficient smoke detection in the IP camera platform, a detection algorithm must operate directly in the Discrete Cosine Transform (DCT domain to reduce computational cost, avoiding a complete decoding process required for algorithms that operate in spatial domain. In the proposed algorithm the DCT Inter-transformation technique is used to increase the detection accuracy without inverse DCT operation. In the proposed scheme, firstly the candidate smoke regions are estimated using motion and color smoke properties; next using morphological operations the noise is reduced. Finally the growth properties of the candidate smoke regions are furthermore analyzed through time using the connected component labeling technique. Evaluation results show that a feasible smoke detection method with false negative and false positive error rates approximately equal to 4% and 2%, respectively, is obtained.

A new algorithmic approach for fingers detection and identification

Science.gov (United States)

Mubashar Khan, Arslan; Umar, Waqas; Choudhary, Taimoor; Hussain, Fawad; Haroon Yousaf, Muhammad

2013-03-01

Gesture recognition is concerned with the goal of interpreting human gestures through mathematical algorithms. Gestures can originate from any bodily motion or state but commonly originate from the face or hand. Hand gesture detection in a real time environment, where the time and memory are important issues, is a critical operation. Hand gesture recognition largely depends on the accurate detection of the fingers. This paper presents a new algorithmic approach to detect and identify fingers of human hand. The proposed algorithm does not depend upon the prior knowledge of the scene. It detects the active fingers and Metacarpophalangeal (MCP) of the inactive fingers from an already detected hand. Dynamic thresholding technique and connected component labeling scheme are employed for background elimination and hand detection respectively. Algorithm proposed a new approach for finger identification in real time environment keeping the memory and time constraint as low as possible.

Real time algorithms for sharp wave ripple detection.

Science.gov (United States)

Sethi, Ankit; Kemere, Caleb

2014-01-01

Neural activity during sharp wave ripples (SWR), short bursts of co-ordinated oscillatory activity in the CA1 region of the rodent hippocampus, is implicated in a variety of memory functions from consolidation to recall. Detection of these events in an algorithmic framework, has thus far relied on simple thresholding techniques with heuristically derived parameters. This study is an investigation into testing and improving the current methods for detection of SWR events in neural recordings. We propose and profile methods to reduce latency in ripple detection. Proposed algorithms are tested on simulated ripple data. The findings show that simple realtime algorithms can improve upon existing power thresholding methods and can detect ripple activity with latencies in the range of 10-20 ms.

Improving Polyp Detection Algorithms for CT Colonography: Pareto Front Approach.

Science.gov (United States)

Huang, Adam; Li, Jiang; Summers, Ronald M; Petrick, Nicholas; Hara, Amy K

2010-03-21

We investigated a Pareto front approach to improving polyp detection algorithms for CT colonography (CTC). A dataset of 56 CTC colon surfaces with 87 proven positive detections of 53 polyps sized 4 to 60 mm was used to evaluate the performance of a one-step and a two-step curvature-based region growing algorithm. The algorithmic performance was statistically evaluated and compared based on the Pareto optimal solutions from 20 experiments by evolutionary algorithms. The false positive rate was lower (pPareto optimization process can effectively help in fine-tuning and redesigning polyp detection algorithms.

Note: A simple image processing based fiducial auto-alignment method for sample registration.

Science.gov (United States)

Robertson, Wesley D; Porto, Lucas R; Ip, Candice J X; Nantel, Megan K T; Tellkamp, Friedjof; Lu, Yinfei; Miller, R J Dwayne

2015-08-01

A simple method for the location and auto-alignment of sample fiducials for sample registration using widely available MATLAB/LabVIEW software is demonstrated. The method is robust, easily implemented, and applicable to a wide variety of experiment types for improved reproducibility and increased setup speed. The software uses image processing to locate and measure the diameter and center point of circular fiducials for distance self-calibration and iterative alignment and can be used with most imaging systems. The method is demonstrated to be fast and reliable in locating and aligning sample fiducials, provided here by a nanofabricated array, with accuracy within the optical resolution of the imaging system. The software was further demonstrated to register, load, and sample the dynamically wetted array.

An Algorithm for Pedestrian Detection in Multispectral Image Sequences

Science.gov (United States)

Kniaz, V. V.; Fedorenko, V. V.

2017-05-01

The growing interest for self-driving cars provides a demand for scene understanding and obstacle detection algorithms. One of the most challenging problems in this field is the problem of pedestrian detection. Main difficulties arise from a diverse appearances of pedestrians. Poor visibility conditions such as fog and low light conditions also significantly decrease the quality of pedestrian detection. This paper presents a new optical flow based algorithm BipedDetet that provides robust pedestrian detection on a single-borad computer. The algorithm is based on the idea of simplified Kalman filtering suitable for realization on modern single-board computers. To detect a pedestrian a synthetic optical flow of the scene without pedestrians is generated using slanted-plane model. The estimate of a real optical flow is generated using a multispectral image sequence. The difference of the synthetic optical flow and the real optical flow provides the optical flow induced by pedestrians. The final detection of pedestrians is done by the segmentation of the difference of optical flows. To evaluate the BipedDetect algorithm a multispectral dataset was collected using a mobile robot.

Accuracy of heart rate variability estimation by photoplethysmography using an smartphone: Processing optimization and fiducial point selection.

Science.gov (United States)

Ferrer-Mileo, V; Guede-Fernandez, F; Fernandez-Chimeno, M; Ramos-Castro, J; Garcia-Gonzalez, M A

2015-08-01

This work compares several fiducial points to detect the arrival of a new pulse in a photoplethysmographic signal using the built-in camera of smartphones or a photoplethysmograph. Also, an optimization process for the signal preprocessing stage has been done. Finally we characterize the error produced when we use the best cutoff frequencies and fiducial point for smartphones and photopletysmograph and compare if the error of smartphones can be reasonably be explained by variations in pulse transit time. The results have revealed that the peak of the first derivative and the minimum of the second derivative of the pulse wave have the lowest error. Moreover, for these points, high pass filtering the signal between 0.1 to 0.8 Hz and low pass around 2.7 Hz or 3.5 Hz are the best cutoff frequencies. Finally, the error in smartphones is slightly higher than in a photoplethysmograph.

ANOMALY DETECTION IN NETWORKING USING HYBRID ARTIFICIAL IMMUNE ALGORITHM

Directory of Open Access Journals (Sweden)

D. Amutha Guka

2012-01-01

Full Text Available Especially in today’s network scenario, when computers are interconnected through internet, security of an information system is very important issue. Because no system can be absolutely secure, the timely and accurate detection of anomalies is necessary. The main aim of this research paper is to improve the anomaly detection by using Hybrid Artificial Immune Algorithm (HAIA which is based on Artificial Immune Systems (AIS and Genetic Algorithm (GA. In this research work, HAIA approach is used to develop Network Anomaly Detection System (NADS. The detector set is generated by using GA and the anomalies are identified using Negative Selection Algorithm (NSA which is based on AIS. The HAIA algorithm is tested with KDD Cup 99 benchmark dataset. The detection rate is used to measure the effectiveness of the NADS. The results and consistency of the HAIA are compared with earlier approaches and the results are presented. The proposed algorithm gives best results when compared to the earlier approaches.

Urethral catheterization facilitates preradiation fiducial marker placement in postprostatectomy patients.

Science.gov (United States)

Williams, Christopher; Costa, Joseph; Mandia, Stephen; Henderson, Randal; Marino, Robert; Mendenhall, Nancy

2012-05-01

Surgical absence of the prostate can make placement of fiducial markers difficult, because anatomic landmarks are distorted and there is a paucity of substantial tissue to hold fast the markers. We describe a method for improving the accuracy of fiducial marker placement for the purpose of salvage or adjuvant external beam radiation therapy for prostate cancer in patients who have undergone radical prostatectomy. To assist with identification of the urethrovesical junction and to facilitate placement of the markers, a Foley catheter was placed and the balloon was inflated. Gentle traction on the catheter seated the balloon at the bladder neck to echographically define the anatomy of the urethrovesical junction. Next, a rectal ultrasound probe was inserted into the rectum, allowing visualization of the region of the urethrovesical junction. Fiducial markers were then placed bilaterally in the detrusor muscle at the bladder neck or in the periurethral tissue using the applicator needle. The treating radiation oncologist verified that marker placement was suitable for assisting with radiation therapy in all cases. Preradiation pelvic imaging verified that markers were not in the bladder or urethral lumen, and there were no patient complaints of voiding out the markers with urination.

Objective assessment of the aesthetic outcomes of breast cancer treatment: toward automatic localization of fiducial points on digital photographs

Science.gov (United States)

Udpa, Nitin; Sampat, Mehul P.; Kim, Min Soon; Reece, Gregory P.; Markey, Mia K.

2007-03-01

The contemporary goals of breast cancer treatment are not limited to cure but include maximizing quality of life. All breast cancer treatment can adversely affect breast appearance. Developing objective, quantifiable methods to assess breast appearance is important to understand the impact of deformity on patient quality of life, guide selection of current treatments, and make rational treatment advances. A few measures of aesthetic properties such as symmetry have been developed. They are computed from the distances between manually identified fiducial points on digital photographs. However, this is time-consuming and subject to intra- and inter-observer variability. The purpose of this study is to investigate methods for automatic localization of fiducial points on anterior-posterior digital photographs taken to document the outcomes of breast reconstruction. Particular emphasis is placed on automatic localization of the nipple complex since the most widely used aesthetic measure, the Breast Retraction Assessment, quantifies the symmetry of nipple locations. The nipple complexes are automatically localized using normalized cross-correlation with a template bank of variants of Gaussian and Laplacian of Gaussian filters. A probability map of likely nipple locations determined from the image database is used to reduce the number of false positive detections from the matched filter operation. The accuracy of the nipple detection was evaluated relative to markings made by three human observers. The impact of using the fiducial point locations as identified by the automatic method, as opposed to the manual method, on the calculation of the Breast Retraction Assessment was also evaluated.

Texture orientation-based algorithm for detecting infrared maritime targets.

Science.gov (United States)

Wang, Bin; Dong, Lili; Zhao, Ming; Wu, Houde; Xu, Wenhai

2015-05-20

Infrared maritime target detection is a key technology for maritime target searching systems. However, in infrared maritime images (IMIs) taken under complicated sea conditions, background clutters, such as ocean waves, clouds or sea fog, usually have high intensity that can easily overwhelm the brightness of real targets, which is difficult for traditional target detection algorithms to deal with. To mitigate this problem, this paper proposes a novel target detection algorithm based on texture orientation. This algorithm first extracts suspected targets by analyzing the intersubband correlation between horizontal and vertical wavelet subbands of the original IMI on the first scale. Then the self-adaptive wavelet threshold denoising and local singularity analysis of the original IMI is combined to remove false alarms further. Experiments show that compared with traditional algorithms, this algorithm can suppress background clutter much better and realize better single-frame detection for infrared maritime targets. Besides, in order to guarantee accurate target extraction further, the pipeline-filtering algorithm is adopted to eliminate residual false alarms. The high practical value and applicability of this proposed strategy is backed strongly by experimental data acquired under different environmental conditions.

Three-phase Interstellar Medium in Galaxies Resolving Evolution with Star Formation and Supernova Feedback (TIGRESS): Algorithms, Fiducial Model, and Convergence

Science.gov (United States)

Kim, Chang-Goo; Ostriker, Eve C.

2017-09-01

We introduce TIGRESS, a novel framework for multi-physics numerical simulations of the star-forming interstellar medium (ISM) implemented in the Athena MHD code. The algorithms of TIGRESS are designed to spatially and temporally resolve key physical features, including: (1) the gravitational collapse and ongoing accretion of gas that leads to star formation in clusters; (2) the explosions of supernovae (SNe), both near their progenitor birth sites and from runaway OB stars, with time delays relative to star formation determined by population synthesis; (3) explicit evolution of SN remnants prior to the onset of cooling, which leads to the creation of the hot ISM; (4) photoelectric heating of the warm and cold phases of the ISM that tracks the time-dependent ambient FUV field from the young cluster population; (5) large-scale galactic differential rotation, which leads to epicyclic motion and shears out overdense structures, limiting large-scale gravitational collapse; (6) accurate evolution of magnetic fields, which can be important for vertical support of the ISM disk as well as angular momentum transport. We present tests of the newly implemented physics modules, and demonstrate application of TIGRESS in a fiducial model representing the solar neighborhood environment. We use a resolution study to demonstrate convergence and evaluate the minimum resolution {{Δ }}x required to correctly recover several ISM properties, including the star formation rate, wind mass-loss rate, disk scale height, turbulent and Alfvénic velocity dispersions, and volume fractions of warm and hot phases. For the solar neighborhood model, all these ISM properties are converged at {{Δ }}x≤slant 8 {pc}.

Development of radio frequency interference detection algorithms for passive microwave remote sensing

Science.gov (United States)

Misra, Sidharth

Radio Frequency Interference (RFI) signals are man-made sources that are increasingly plaguing passive microwave remote sensing measurements. RFI is of insidious nature, with some signals low power enough to go undetected but large enough to impact science measurements and their results. With the launch of the European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) satellite in November 2009 and the upcoming launches of the new NASA sea-surface salinity measuring Aquarius mission in June 2011 and soil-moisture measuring Soil Moisture Active Passive (SMAP) mission around 2015, active steps are being taken to detect and mitigate RFI at L-band. An RFI detection algorithm was designed for the Aquarius mission. The algorithm performance was analyzed using kurtosis based RFI ground-truth. The algorithm has been developed with several adjustable location dependant parameters to control the detection statistics (false-alarm rate and probability of detection). The kurtosis statistical detection algorithm has been compared with the Aquarius pulse detection method. The comparative study determines the feasibility of the kurtosis detector for the SMAP radiometer, as a primary RFI detection algorithm in terms of detectability and data bandwidth. The kurtosis algorithm has superior detection capabilities for low duty-cycle radar like pulses, which are more prevalent according to analysis of field campaign data. Most RFI algorithms developed have generally been optimized for performance with individual pulsed-sinusoidal RFI sources. A new RFI detection model is developed that takes into account multiple RFI sources within an antenna footprint. The performance of the kurtosis detection algorithm under such central-limit conditions is evaluated. The SMOS mission has a unique hardware system, and conventional RFI detection techniques cannot be applied. Instead, an RFI detection algorithm for SMOS is developed and applied in the angular domain. This algorithm compares

Algorithms for boundary detection in radiographic images

International Nuclear Information System (INIS)

Gonzaga, Adilson; Franca, Celso Aparecido de

1996-01-01

Edge detecting techniques applied to radiographic digital images are discussed. Some algorithms have been implemented and the results are displayed to enhance boundary or hide details. An algorithm applied in a pre processed image with contrast enhanced is proposed and the results are discussed

Detection algorithm of infrared small target based on improved SUSAN operator

Science.gov (United States)

Liu, Xingmiao; Wang, Shicheng; Zhao, Jing

2010-10-01

The methods of detecting small moving targets in infrared image sequences that contain moving nuisance objects and background noise is analyzed in this paper. A novel infrared small target detection algorithm based on improved SUSAN operator is put forward. The algorithm selects double templates for the infrared small target detection: one size is greater than the small target point size and another size is equal to the small target point size. First, the algorithm uses the big template to calculate the USAN of each pixel in the image and detect the small target, the edge of the image and isolated noise pixels; Then the algorithm uses the another template to calculate the USAN of pixels detected in the first step and improves the principles of SUSAN algorithm based on the characteristics of the small target so that the algorithm can only detect small targets and don't sensitive to the edge pixels of the image and isolated noise pixels. So the interference of the edge of the image and isolate noise points are removed and the candidate target points can be identified; At last, the target is detected by utilizing the continuity and consistency of target movement. The experimental results indicate that the improved SUSAN detection algorithm can quickly and effectively detect the infrared small targets.

Percutaneous fiducial marker placement prior to stereotactic body radiotherapy for malignant liver tumors: an initial experience

International Nuclear Information System (INIS)

Ohta, Kengo; Shimohira, Masashi; Murai, Taro; Nishimura, Junichi; Iwata, Hiromitsu; Ogino, Hiroyuki; Hashizume, Takuya; Shibamoto, Yuta

2016-01-01

The aim of this study was to describe our initial experience with a gold flexible linear fiducial marker and to evaluate the safety and technical and clinical efficacy of stereotactic body radiotherapy using this marker for malignant liver tumors. Between July 2012 and February 2015, 18 patients underwent percutaneous fiducial marker placement before stereotactic body radiotherapy for malignant liver tumors. We evaluated the technical and clinical success rates of the procedure and the associated complications. Technical success was defined as successful placement of the fiducial marker at the target site, and clinical success was defined as the completion of stereotactic body radiotherapy without the marker dropping out of position. All 18 fiducial markers were placed successfully, so the technical success rate was 100% (18/18). All 18 patients were able to undergo stereotactic body radiotherapy without marker migration. Thus, the clinical success rate was 100% (18/18). Slight pneumothorax occurred as a minor complication in one case. No major complications such as coil migration or bleeding were observed. The examined percutaneous fiducial marker was safely placed in the liver and appeared to be useful for stereotactic body radiotherapy for malignant liver tumors

A simulation study comparing aberration detection algorithms for syndromic surveillance

Directory of Open Access Journals (Sweden)

Painter Ian

2007-03-01

Full Text Available Abstract Background The usefulness of syndromic surveillance for early outbreak detection depends in part on effective statistical aberration detection. However, few published studies have compared different detection algorithms on identical data. In the largest simulation study conducted to date, we compared the performance of six aberration detection algorithms on simulated outbreaks superimposed on authentic syndromic surveillance data. Methods We compared three control-chart-based statistics, two exponential weighted moving averages, and a generalized linear model. We simulated 310 unique outbreak signals, and added these to actual daily counts of four syndromes monitored by Public Health – Seattle and King County's syndromic surveillance system. We compared the sensitivity of the six algorithms at detecting these simulated outbreaks at a fixed alert rate of 0.01. Results Stratified by baseline or by outbreak distribution, duration, or size, the generalized linear model was more sensitive than the other algorithms and detected 54% (95% CI = 52%–56% of the simulated epidemics when run at an alert rate of 0.01. However, all of the algorithms had poor sensitivity, particularly for outbreaks that did not begin with a surge of cases. Conclusion When tested on county-level data aggregated across age groups, these algorithms often did not perform well in detecting signals other than large, rapid increases in case counts relative to baseline levels.

Algorithm for detecting violations of traffic rules based on computer vision approaches

Directory of Open Access Journals (Sweden)

Ibadov Samir

2017-01-01

Full Text Available We propose a new algorithm for automatic detect violations of traffic rules for improving the people safety on the unregulated pedestrian crossing. The algorithm uses multi-step proceedings. They are zebra detection, cars detection, and pedestrian detection. For car detection, we use faster R-CNN deep learning tool. The algorithm shows promising results in the detection violations of traffic rules.

Community detection algorithm evaluation with ground-truth data

Science.gov (United States)

Jebabli, Malek; Cherifi, Hocine; Cherifi, Chantal; Hamouda, Atef

2018-02-01

Community structure is of paramount importance for the understanding of complex networks. Consequently, there is a tremendous effort in order to develop efficient community detection algorithms. Unfortunately, the issue of a fair assessment of these algorithms is a thriving open question. If the ground-truth community structure is available, various clustering-based metrics are used in order to compare it versus the one discovered by these algorithms. However, these metrics defined at the node level are fairly insensitive to the variation of the overall community structure. To overcome these limitations, we propose to exploit the topological features of the 'community graphs' (where the nodes are the communities and the links represent their interactions) in order to evaluate the algorithms. To illustrate our methodology, we conduct a comprehensive analysis of overlapping community detection algorithms using a set of real-world networks with known a priori community structure. Results provide a better perception of their relative performance as compared to classical metrics. Moreover, they show that more emphasis should be put on the topology of the community structure. We also investigate the relationship between the topological properties of the community structure and the alternative evaluation measures (quality metrics and clustering metrics). It appears clearly that they present different views of the community structure and that they must be combined in order to evaluate the effectiveness of community detection algorithms.

Visibility of fiducial markers used for image-guided radiation therapy on optical coherence tomography for registration with CT: An esophageal phantom study.

Science.gov (United States)

Jelvehgaran, Pouya; Alderliesten, Tanja; Weda, Jelmer J A; de Bruin, Martijn; Faber, Dirk J; Hulshof, Maarten C C M; van Leeuwen, Ton G; van Herk, Marcel; de Boer, Johannes F

2017-12-01

Optical coherence tomography (OCT) is of interest to visualize microscopic esophageal tumor extensions to improve tumor delineation for radiation therapy (RT) planning. Fiducial marker placement is a common method to ensure target localization during planning and treatment. Visualization of these fiducial markers on OCT permits integrating OCT and computed tomography (CT) images used for RT planning via image registration. We studied the visibility of 13 (eight types) commercially available solid and liquid fiducial markers in OCT images at different depths using dedicated esophageal phantoms and evaluated marker placement depth in clinical practice. We designed and fabricated dedicated esophageal phantoms, in which three layers mimic the anatomical wall structures of a healthy human esophagus. We successfully implanted 13 commercially available fiducial markers that varied in diameter and material property at depths between 0.5 and 3.0 mm. The resulting esophageal phantoms were imaged with OCT, and marker visibility was assessed qualitatively and quantitatively using the contrast-to-background-noise ratio (CNR). The CNR was defined as the difference between the mean intensity of the fiducial markers and the mean intensity of the background divided by the standard deviation of the background intensity. To determine whether, in current clinical practice, the implanted fiducial markers are within the OCT visualization range (up to 3.0 mm depth), we retrospectively measured the distance of 19 fiducial markers to the esophageal lumen on CT scans of 16 esophageal cancer patients. In the esophageal phantoms, all the included fiducial markers were visible on OCT at all investigated depths. Solid fiducial markers were better visible on OCT than liquid fiducial markers with a 1.74-fold higher CNR. Although fiducial marker identification per type and size was slightly easier for superficially implanted fiducial markers, we observed no difference in the ability of OCT to

A simple fall detection algorithm for Powered Two Wheelers

OpenAIRE

BOUBEZOUL, Abderrahmane; ESPIE, Stéphane; LARNAUDIE, Bruno; BOUAZIZ, Samir

2013-01-01

The aim of this study is to evaluate a low-complexity fall detection algorithm, that use both acceleration and angular velocity signals to trigger an alert-system or to inflate an airbag jacket. The proposed fall detection algorithm is a threshold-based algorithm, using data from 3-accelerometers and 3-gyroscopes sensors mounted on the motorcycle. During the first step, the commonly fall accident configurations were selected and analyzed in order to identify the main causation factors. On the...

Clinical results from first use of prostate stent as fiducial for radiotherapy of prostate cancer

Energy Technology Data Exchange (ETDEWEB)

Carl, Jesper; Nielsen, Jane (Dept. of Medical Physics, Dept. of Oncology, Aalborg Hospital, Aarhus Univ. Hospital, Aalborg (Denmark)), e-mail: jhc@rn.dk; Holmberg, Mats (Dept. of Oncology, Aalborg Hospital, Aarhus Univ. Hospital, Aalborg (Denmark)); Larsen, Erik Hoejkjaer; Fabrin, Knud (Dept. of Urology, Aalborg Hospital, Aarhus Univ. Hospital, Aalborg (Denmark)); Fisker, Rune V. (Dept. of Radiology, Aalborg Hospital, Aarhus Univ. Hospital, Aalborg (Denmark))

2011-05-15

Purpose. A clinical feasibility study using a removable prostate stent as fiducial for image-guided radiotherapy (IGRT) of localized prostate cancer (PC). Material and methods. The study included patients with local or locally advanced PC. The clinical target volume (CTV) was outlined on magnetic resonance (MR) images co-registered to planning computer tomography (CT) images. Daily online IGRT was delivered using the stent as fiducial. Risk of migration was estimated using multiple MR. Acute urinary toxicity was scored using the international prostate symptom score (IPSS). Late gastro-intestinal (GI) and genito-urinary (GU) toxicity was scored using the Radio Therapy Oncology Group (RTOG) score, biochemical failure (BF) was defined as an elevation of prostate specific antigen (PSA) above nadir plus 2 ng/ml after radiotherapy. Results. One hundred men were enrolled in the study. Ninety completed radiotherapy with the stent as fiducial. No migration of the stent was seen, but three cases of dislocation of the stent to the bladder were observed. Acute urinary toxicity based on IPSS was comparable to toxicity in patients who had gold markers (GM) as fiducials. Removal of the stent was associated with a high frequency of urinary retention. Late GI and GU toxicity and BF were comparable to those of other studies, but longer observation time is needed. Conclusions. This study reports the first clinical results of using a prostate stent as fiducial. No migration of the stent observed. Dislocation of the stent to the urinary bladder was observed in three cases, requiring removal of the stent and insertion of a new fiducial. Acute toxicity during radiotherapy evaluated from IPSS was comparable to toxicity in patients with GM. Removal of the stent was associated with a high frequency of post procedural urinary retention. Late toxicity and BF were comparable to those of other studies, though longer observation time is needed

Clinical results from first use of prostate stent as fiducial for radiotherapy of prostate cancer

International Nuclear Information System (INIS)

Carl, Jesper; Nielsen, Jane; Holmberg, Mats; Larsen, Erik Hoejkjaer; Fabrin, Knud; Fisker, Rune V.

2011-01-01

Purpose. A clinical feasibility study using a removable prostate stent as fiducial for image-guided radiotherapy (IGRT) of localized prostate cancer (PC). Material and methods. The study included patients with local or locally advanced PC. The clinical target volume (CTV) was outlined on magnetic resonance (MR) images co-registered to planning computer tomography (CT) images. Daily online IGRT was delivered using the stent as fiducial. Risk of migration was estimated using multiple MR. Acute urinary toxicity was scored using the international prostate symptom score (IPSS). Late gastro-intestinal (GI) and genito-urinary (GU) toxicity was scored using the Radio Therapy Oncology Group (RTOG) score, biochemical failure (BF) was defined as an elevation of prostate specific antigen (PSA) above nadir plus 2 ng/ml after radiotherapy. Results. One hundred men were enrolled in the study. Ninety completed radiotherapy with the stent as fiducial. No migration of the stent was seen, but three cases of dislocation of the stent to the bladder were observed. Acute urinary toxicity based on IPSS was comparable to toxicity in patients who had gold markers (GM) as fiducials. Removal of the stent was associated with a high frequency of urinary retention. Late GI and GU toxicity and BF were comparable to those of other studies, but longer observation time is needed. Conclusions. This study reports the first clinical results of using a prostate stent as fiducial. No migration of the stent observed. Dislocation of the stent to the urinary bladder was observed in three cases, requiring removal of the stent and insertion of a new fiducial. Acute toxicity during radiotherapy evaluated from IPSS was comparable to toxicity in patients with GM. Removal of the stent was associated with a high frequency of post procedural urinary retention. Late toxicity and BF were comparable to those of other studies, though longer observation time is needed

Clinical results from first use of prostate stent as fiducial for radiotherapy of prostate cancer.

Science.gov (United States)

Carl, Jesper; Nielsen, Jane; Holmberg, Mats; Larsen, Erik Hoejkjaer; Fabrin, Knud; Fisker, Rune V

2011-05-01

A clinical feasibility study using a removable prostate stent as fiducial for image-guided radiotherapy (IGRT) of localized prostate cancer (PC). The study included patients with local or locally advanced PC. The clinical target volume (CTV) was outlined on magnetic resonance (MR) images co-registered to planning computer tomography (CT) images. Daily online IGRT was delivered using the stent as fiducial. Risk of migration was estimated using multiple MR. Acute urinary toxicity was scored using the international prostate symptom score (IPSS). Late gastro-intestinal (GI) and genito-urinary (GU) toxicity was scored using the Radio Therapy Oncology Group (RTOG) score, biochemical failure (BF) was defined as an elevation of prostate specific antigen (PSA) above nadir plus 2 ng/ml after radiotherapy. One hundred men were enrolled in the study. Ninety completed radiotherapy with the stent as fiducial. No migration of the stent was seen, but three cases of dislocation of the stent to the bladder were observed. Acute urinary toxicity based on IPSS was comparable to toxicity in patients who had gold markers (GM) as fiducials. Removal of the stent was associated with a high frequency of urinary retention. Late GI and GU toxicity and BF were comparable to those of other studies, but longer observation time is needed. This study reports the first clinical results of using a prostate stent as fiducial. No migration of the stent observed. Dislocation of the stent to the urinary bladder was observed in three cases, requiring removal of the stent and insertion of a new fiducial. Acute toxicity during radiotherapy evaluated from IPSS was comparable to toxicity in patients with GM. Removal of the stent was associated with a high frequency of post procedural urinary retention. Late toxicity and BF were comparable to those of other studies, though longer observation time is needed.

Improved QRD-M Detection Algorithm for Generalized Spatial Modulation Scheme

Directory of Open Access Journals (Sweden)

Xiaorong Jing

2017-01-01

Full Text Available Generalized spatial modulation (GSM is a spectral and energy efficient multiple-input multiple-output (MIMO transmission scheme. It will lead to imperfect detection performance with relatively high computational complexity by directly applying the original QR-decomposition with M algorithm (QRD-M to the GSM scheme. In this paper an improved QRD-M algorithm is proposed for GSM signal detection, which achieves near-optimal performance but with relatively low complexity. Based on the QRD, the improved algorithm firstly transforms the maximum likelihood (ML detection of the GSM signals into searching an inverted tree structure. Then, in the searching process of the M branches, the branches corresponding to the illegitimate transmit antenna combinations (TACs and related to invalid number of active antennas are cut in order to improve the validity of the resultant branches at each level by taking advantage of characteristics of GSM signals. Simulation results show that the improved QRD-M detection algorithm provides similar performance to maximum likelihood (ML with the reduced computational complexity compared to the original QRD-M algorithm, and the optimal value of parameter M of the improved QRD-M algorithm for detection of the GSM scheme is equal to modulation order plus one.

An efficient community detection algorithm using greedy surprise maximization

International Nuclear Information System (INIS)

Jiang, Yawen; Jia, Caiyan; Yu, Jian

2014-01-01

Community detection is an important and crucial problem in complex network analysis. Although classical modularity function optimization approaches are widely used for identifying communities, the modularity function (Q) suffers from its resolution limit. Recently, the surprise function (S) was experimentally proved to be better than the Q function. However, up until now, there has been no algorithm available to perform searches to directly determine the maximal surprise values. In this paper, considering the superiority of the S function over the Q function, we propose an efficient community detection algorithm called AGSO (algorithm based on greedy surprise optimization) and its improved version FAGSO (fast-AGSO), which are based on greedy surprise optimization and do not suffer from the resolution limit. In addition, (F)AGSO does not need the number of communities K to be specified in advance. Tests on experimental networks show that (F)AGSO is able to detect optimal partitions in both simple and even more complex networks. Moreover, algorithms based on surprise maximization perform better than those algorithms based on modularity maximization, including Blondel–Guillaume–Lambiotte–Lefebvre (BGLL), Clauset–Newman–Moore (CNM) and the other state-of-the-art algorithms such as Infomap, order statistics local optimization method (OSLOM) and label propagation algorithm (LPA). (paper)

Comparison of public peak detection algorithms for MALDI mass spectrometry data analysis.

Science.gov (United States)

Yang, Chao; He, Zengyou; Yu, Weichuan

2009-01-06

In mass spectrometry (MS) based proteomic data analysis, peak detection is an essential step for subsequent analysis. Recently, there has been significant progress in the development of various peak detection algorithms. However, neither a comprehensive survey nor an experimental comparison of these algorithms is yet available. The main objective of this paper is to provide such a survey and to compare the performance of single spectrum based peak detection methods. In general, we can decompose a peak detection procedure into three consequent parts: smoothing, baseline correction and peak finding. We first categorize existing peak detection algorithms according to the techniques used in different phases. Such a categorization reveals the differences and similarities among existing peak detection algorithms. Then, we choose five typical peak detection algorithms to conduct a comprehensive experimental study using both simulation data and real MALDI MS data. The results of comparison show that the continuous wavelet-based algorithm provides the best average performance.

Multifeature Fusion Vehicle Detection Algorithm Based on Choquet Integral

Directory of Open Access Journals (Sweden)

Wenhui Li

2014-01-01

Full Text Available Vision-based multivehicle detection plays an important role in Forward Collision Warning Systems (FCWS and Blind Spot Detection Systems (BSDS. The performance of these systems depends on the real-time capability, accuracy, and robustness of vehicle detection methods. To improve the accuracy of vehicle detection algorithm, we propose a multifeature fusion vehicle detection algorithm based on Choquet integral. This algorithm divides the vehicle detection problem into two phases: feature similarity measure and multifeature fusion. In the feature similarity measure phase, we first propose a taillight-based vehicle detection method, and then vehicle taillight feature similarity measure is defined. Second, combining with the definition of Choquet integral, the vehicle symmetry similarity measure and the HOG + AdaBoost feature similarity measure are defined. Finally, these three features are fused together by Choquet integral. Being evaluated on public test collections and our own test images, the experimental results show that our method has achieved effective and robust multivehicle detection in complicated environments. Our method can not only improve the detection rate but also reduce the false alarm rate, which meets the engineering requirements of Advanced Driving Assistance Systems (ADAS.

A Modularity Degree Based Heuristic Community Detection Algorithm

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Dongming Chen

2014-01-01

Full Text Available A community in a complex network can be seen as a subgroup of nodes that are densely connected. Discovery of community structures is a basic problem of research and can be used in various areas, such as biology, computer science, and sociology. Existing community detection methods usually try to expand or collapse the nodes partitions in order to optimize a given quality function. These optimization function based methods share the same drawback of inefficiency. Here we propose a heuristic algorithm (MDBH algorithm based on network structure which employs modularity degree as a measure function. Experiments on both synthetic benchmarks and real-world networks show that our algorithm gives competitive accuracy with previous modularity optimization methods, even though it has less computational complexity. Furthermore, due to the use of modularity degree, our algorithm naturally improves the resolution limit in community detection.

A Space Object Detection Algorithm using Fourier Domain Likelihood Ratio Test

Science.gov (United States)

Becker, D.; Cain, S.

Space object detection is of great importance in the highly dependent yet competitive and congested space domain. Detection algorithms employed play a crucial role in fulfilling the detection component in the situational awareness mission to detect, track, characterize and catalog unknown space objects. Many current space detection algorithms use a matched filter or a spatial correlator to make a detection decision at a single pixel point of a spatial image based on the assumption that the data follows a Gaussian distribution. This paper explores the potential for detection performance advantages when operating in the Fourier domain of long exposure images of small and/or dim space objects from ground based telescopes. A binary hypothesis test is developed based on the joint probability distribution function of the image under the hypothesis that an object is present and under the hypothesis that the image only contains background noise. The detection algorithm tests each pixel point of the Fourier transformed images to make the determination if an object is present based on the criteria threshold found in the likelihood ratio test. Using simulated data, the performance of the Fourier domain detection algorithm is compared to the current algorithm used in space situational awareness applications to evaluate its value.

Assessment of fiducial markers to enable the co-registration of photographs and MRI data.

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Webb, Bridgette A; Petrovic, Andreas; Urschler, Martin; Scheurer, Eva

2015-03-01

To investigate the visualisation of novel external fiducial skin markers in photography and MRI. To co-register photographs and MR images, and additionally assess the spatial accuracy of these co-registrations with the view of future application in the investigation of forensically relevant soft tissue lesions. Strand-shaped fiducial markers were secured externally over hematomas on the thigh of 10 volunteers. The region of interest was photographed and examined using MRI at 3T in oblique and transversal orientations and the visibility of the markers assessed. Markers provided 'control points' in both sets of images, enabling the computation of an affine transform to register oblique MR images to photographs. The fiducial registration error was evaluated by calculating the root-mean-square error of nine corresponding evaluation points visible in both modalities. Fiducial markers were clearly visualised in both photography and MRI. The co-registration of photographs and oblique MR images was achieved for all participants. The overall root-mean-square error for registrations was 1.18mm (TIRM) and 1.46mm (TSE2D with SPAIR fat-suppression). The proposed approach led to the successful visualisation of non-invasive fiducial markers using photography and MRI (TIRM and TSE2D (SPAIR) sequences). This visualisation, combined with an affine transformation process provided a simple, cost-effective way to accurately co-register photographs and MR images of subcutaneous hematomas located on the thigh. Further investigation of the novel markers and the proposed co-visualisation approach holds potential to improve not only the forensic documentation of soft tissue lesions, but to also improve certain clinical applications, including the area of dermatology. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Research on data auto-analysis algorithms in the explosive detection system

International Nuclear Information System (INIS)

Wang Haidong; Li Yuanjing; Yang Yigang; Li Tiezhu; Chen Boxian; Cheng Jianping

2006-01-01

This paper mainly describe some auto-analysis algorithms in explosive detection system with TNA method. These include the auto-calibration algorithm when disturbed by other factors, MCA auto-calibration algorithm with calibrated spectrum, the auto-fitting and integral of hydrogen and nitrogen elements data. With these numerical algorithms, the authors can automatically and precisely analysis the gamma-spectra and ultimately achieve the explosive auto-detection. (authors)

A Region Tracking-Based Vehicle Detection Algorithm in Nighttime Traffic Scenes

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Jianqiang Wang

2013-12-01

Full Text Available The preceding vehicles detection technique in nighttime traffic scenes is an important part of the advanced driver assistance system (ADAS. This paper proposes a region tracking-based vehicle detection algorithm via the image processing technique. First, the brightness of the taillights during nighttime is used as the typical feature, and we use the existing global detection algorithm to detect and pair the taillights. When the vehicle is detected, a time series analysis model is introduced to predict vehicle positions and the possible region (PR of the vehicle in the next frame. Then, the vehicle is only detected in the PR. This could reduce the detection time and avoid the false pairing between the bright spots in the PR and the bright spots out of the PR. Additionally, we present a thresholds updating method to make the thresholds adaptive. Finally, experimental studies are provided to demonstrate the application and substantiate the superiority of the proposed algorithm. The results show that the proposed algorithm can simultaneously reduce both the false negative detection rate and the false positive detection rate.

An efficient and fast detection algorithm for multimode FBG sensing

DEFF Research Database (Denmark)

Ganziy, Denis; Jespersen, O.; Rose, B.

2015-01-01

We propose a novel dynamic gate algorithm (DGA) for fast and accurate peak detection. The algorithm uses threshold determined detection window and Center of gravity algorithm with bias compensation. We analyze the wavelength fit resolution of the DGA for different values of signal to noise ratio...... and different typical peak shapes. Our simulations and experiments demonstrate that the DGA method is fast and robust with higher stability and accuracy compared to conventional algorithms. This makes it very attractive for future implementation in sensing systems especially based on multimode fiber Bragg...

Real-time automatic fiducial marker tracking in low contrast cine-MV images

International Nuclear Information System (INIS)

Lin, Wei-Yang; Lin, Shu-Fang; Yang, Sheng-Chang; Liou, Shu-Cheng; Nath, Ravinder; Liu Wu

2013-01-01

Purpose: To develop a real-time automatic method for tracking implanted radiographic markers in low-contrast cine-MV patient images used in image-guided radiation therapy (IGRT). Methods: Intrafraction motion tracking using radiotherapy beam-line MV images have gained some attention recently in IGRT because no additional imaging dose is introduced. However, MV images have much lower contrast than kV images, therefore a robust and automatic algorithm for marker detection in MV images is a prerequisite. Previous marker detection methods are all based on template matching or its derivatives. Template matching needs to match object shape that changes significantly for different implantation and projection angle. While these methods require a large number of templates to cover various situations, they are often forced to use a smaller number of templates to reduce the computation load because their methods all require exhaustive search in the region of interest. The authors solve this problem by synergetic use of modern but well-tested computer vision and artificial intelligence techniques; specifically the authors detect implanted markers utilizing discriminant analysis for initialization and use mean-shift feature space analysis for sequential tracking. This novel approach avoids exhaustive search by exploiting the temporal correlation between consecutive frames and makes it possible to perform more sophisticated detection at the beginning to improve the accuracy, followed by ultrafast sequential tracking after the initialization. The method was evaluated and validated using 1149 cine-MV images from two prostate IGRT patients and compared with manual marker detection results from six researchers. The average of the manual detection results is considered as the ground truth for comparisons. Results: The average root-mean-square errors of our real-time automatic tracking method from the ground truth are 1.9 and 2.1 pixels for the two patients (0.26 mm/pixel). The

Real-time automatic fiducial marker tracking in low contrast cine-MV images

Energy Technology Data Exchange (ETDEWEB)

Lin, Wei-Yang; Lin, Shu-Fang; Yang, Sheng-Chang; Liou, Shu-Cheng; Nath, Ravinder; Liu Wu [Department of Computer Science and Information Engineering, National Chung Cheng University, Taiwan, 62102 (China); Department of Therapeutic Radiology, Yale University School of Medicine, New Haven, Connecticut 06510-3220 (United States)

2013-01-15

Purpose: To develop a real-time automatic method for tracking implanted radiographic markers in low-contrast cine-MV patient images used in image-guided radiation therapy (IGRT). Methods: Intrafraction motion tracking using radiotherapy beam-line MV images have gained some attention recently in IGRT because no additional imaging dose is introduced. However, MV images have much lower contrast than kV images, therefore a robust and automatic algorithm for marker detection in MV images is a prerequisite. Previous marker detection methods are all based on template matching or its derivatives. Template matching needs to match object shape that changes significantly for different implantation and projection angle. While these methods require a large number of templates to cover various situations, they are often forced to use a smaller number of templates to reduce the computation load because their methods all require exhaustive search in the region of interest. The authors solve this problem by synergetic use of modern but well-tested computer vision and artificial intelligence techniques; specifically the authors detect implanted markers utilizing discriminant analysis for initialization and use mean-shift feature space analysis for sequential tracking. This novel approach avoids exhaustive search by exploiting the temporal correlation between consecutive frames and makes it possible to perform more sophisticated detection at the beginning to improve the accuracy, followed by ultrafast sequential tracking after the initialization. The method was evaluated and validated using 1149 cine-MV images from two prostate IGRT patients and compared with manual marker detection results from six researchers. The average of the manual detection results is considered as the ground truth for comparisons. Results: The average root-mean-square errors of our real-time automatic tracking method from the ground truth are 1.9 and 2.1 pixels for the two patients (0.26 mm/pixel). The

Information dynamics algorithm for detecting communities in networks

Science.gov (United States)

Massaro, Emanuele; Bagnoli, Franco; Guazzini, Andrea; Lió, Pietro

2012-11-01

The problem of community detection is relevant in many scientific disciplines, from social science to statistical physics. Given the impact of community detection in many areas, such as psychology and social sciences, we have addressed the issue of modifying existing well performing algorithms by incorporating elements of the domain application fields, i.e. domain-inspired. We have focused on a psychology and social network-inspired approach which may be useful for further strengthening the link between social network studies and mathematics of community detection. Here we introduce a community-detection algorithm derived from the van Dongen's Markov Cluster algorithm (MCL) method [4] by considering networks' nodes as agents capable to take decisions. In this framework we have introduced a memory factor to mimic a typical human behavior such as the oblivion effect. The method is based on information diffusion and it includes a non-linear processing phase. We test our method on two classical community benchmark and on computer generated networks with known community structure. Our approach has three important features: the capacity of detecting overlapping communities, the capability of identifying communities from an individual point of view and the fine tuning the community detectability with respect to prior knowledge of the data. Finally we discuss how to use a Shannon entropy measure for parameter estimation in complex networks.

SU-F-J-43: Positional Variation of Implanted Fiducial Markers Over the Course of Image Guided Radiotherapy for Pancreatic Cancer

Energy Technology Data Exchange (ETDEWEB)

Shen, S; Jacob, R; Popple, R; Wu, X; Cardan, R; Brezovich, I [University Alabama Birmingham, Birmingham, AL (United States)

2016-06-15

Purpose: Pancreas is a soft-tissue organ, implanted fiducials can change positions due to migration or tissue deformation. This study quantified positional variation of fiducials in IGRT for pancreatic cancer. Methods: 20 patients had at least 3 gold fiducials implanted in pancreas under EUS guidance. Patients had 4D-CT simulation for gated treatment. Daily gated OBI kV images (Turebeam) were used for positional alignment with fiducials for total of 25 or 28 fractions. Relative distances among 3 fiducials (d{sub 1–} {sub 2}, d{sub 1–3}, d{sub 2–3}) were measured from 4D-CT end-of-expiration phase bin; and from gated kV images in first, mid, and last fraction (n=180). Results: The median duration between implant and simulation was 11 (range 0–41) days. The median duration between simulation and first fraction was 17 (range 8–24) days. The median relative distance was 12 (range 4–78) mm for d{sub 1–2}, 24 (range 6–80) mm for d{sub 1–3}, and 19 (range 5–63) mm for d{sub 2–3}. The median deviation was 1 mm for d{sub 1–2}, d{sub 1–3}, d{sub 2–3} between simulation and first fraction, first and mid fraction, mid and last fraction (n=180). Two patients (10%) had deviation >= 5 mm (5, 11 mm) between simulation and first fraction. One patient (5%) had deviation >= 5 mm (11 mm) between first and mid fraction. No patient (0%) had deviation >= 5 mm between mid and last fraction. In all 3 cases with deviation >=5 mm, only one fiducial was significantly deviated. No clear evidence that deviation size was associated with time interval between implant and first fraction. Conclusion: Implanted gold fiducials were quite stable over time in their relative positions in pancreas. Our data suggested at least 3 fiducials are needed. In cases that one fiducial was significantly deviated in daily kV images, this fiducial should be excluded in image guidance.

Cardiac embolization of an implanted fiducial marker for hepatic stereotactic body radiotherapy: a case report

Directory of Open Access Journals (Sweden)

Hennessey Hooman

2009-11-01

Full Text Available Abstract Introduction In liver stereotactic body radiotherapy, reduction of normal tissue irradiation requires daily image guidance. This is typically accomplished by imaging a surrogate to the tumor. The surrogate is often an implanted metal fiducial marker. There are few reports addressing the specific risks of hepatic fiducial marker implantation. These risks are assumed to be similar to percutaneous liver biopsies which are associated with a 1-4% complication rate - almost always pain or bleeding. To the best of our knowledge, we present the first case of such a fiducial marker migrating to the heart. Case presentation An 81-year-old Caucasian man (5 years post-gastrectomy for a gastric adenocarcinoma was referred post-second line palliative chemotherapy for radiotherapy of an isolated liver metastasis. It was decided to proceed with treatment and platinum fiducials were chosen for radiation targeting. Under local anesthesia, three Nester embolization coils (Cook Medical Inc., Bloomington, IN, USA were implanted under computed tomography guidance. Before the placement of each coil, the location of the tip of the delivery needle was confirmed by computed tomography imaging. During the procedure, the third coil unexpectedly migrated through the hepatic vein to the inferior vena cava and lodged at the junction of the vena cava and the right atrium. The patient remained asymptomatic. He was immediately referred to angiography for extraction of the coil. Using fluoroscopic guidance, an EN Snare Retrieval System (Hatch Medical L.L.C., Snellville, GA, USA was introduced through a jugular catheter; it successfully grasped the coil and the coil was removed. The patient was kept overnight for observation and no immediate or delayed complications were encountered due to the migration or retrieval of the coil. He subsequently went on to be treated using the remaining fiducials. Conclusion Implanted fiducial markers are increasingly used for stereotactic

Lining seam elimination algorithm and surface crack detection in concrete tunnel lining

Science.gov (United States)

Qu, Zhong; Bai, Ling; An, Shi-Quan; Ju, Fang-Rong; Liu, Ling

2016-11-01

Due to the particularity of the surface of concrete tunnel lining and the diversity of detection environments such as uneven illumination, smudges, localized rock falls, water leakage, and the inherent seams of the lining structure, existing crack detection algorithms cannot detect real cracks accurately. This paper proposed an algorithm that combines lining seam elimination with the improved percolation detection algorithm based on grid cell analysis for surface crack detection in concrete tunnel lining. First, check the characteristics of pixels within the overlapping grid to remove the background noise and generate the percolation seed map (PSM). Second, cracks are detected based on the PSM by the accelerated percolation algorithm so that the fracture unit areas can be scanned and connected. Finally, the real surface cracks in concrete tunnel lining can be obtained by removing the lining seam and performing percolation denoising. Experimental results show that the proposed algorithm can accurately, quickly, and effectively detect the real surface cracks. Furthermore, it can fill the gap in the existing concrete tunnel lining surface crack detection by removing the lining seam.

A New Lightweight Watchdog-Based Algorithm for Detecting Sybil Nodes in Mobile WSNs

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Rezvan Almas Shehni

2017-12-01

Full Text Available Wide-spread deployment of Wireless Sensor Networks (WSN necessitates special attention to security issues, amongst which Sybil attacks are the most important ones. As a core to Sybil attacks, malicious nodes try to disrupt network operations by creating several fabricated IDs. Due to energy consumption concerns in WSNs, devising detection algorithms which release the sensor nodes from high computational and communicational loads are of great importance. In this paper, a new computationally lightweight watchdog-based algorithm is proposed for detecting Sybil IDs in mobile WSNs. The proposed algorithm employs watchdog nodes for collecting detection information and a designated watchdog node for detection information processing and the final Sybil list generation. Benefiting from a newly devised co-presence state diagram and adequate detection rules, the new algorithm features low extra communication overhead, as well as a satisfactory compromise between two otherwise contradictory detection measures of performance, True Detection Rate (TDR and False Detection Rate (FDR. Extensive simulation results illustrate the merits of the new algorithm compared to a couple of recent watchdog-based Sybil detection algorithms.

SU-F-P-40: Analysis of Pelvic Lymph Node Margin Using Prostate Fiducial Markers, for SBRT Treatments

Energy Technology Data Exchange (ETDEWEB)

Torres, J; Castro Pena, P; Garrigo, E; Zunino, S; Venencia, C [Instituto de Radioterapia - Fundacion Marie Curie, Cordoba (Argentina)

2016-06-15

Purpose: The use of fiducials markers in prostate treatment allows a precise localization of this volume. Typical prostate SBRT margins with fiducials markers are 5mm in all directions, except toward the rectum, where 3mm is used. For some patients nearby pelvic lymph nodes with 5mm margin need to be irradiate assuming that its localization is linked to the prostate fiducial markers instead of bony anatomy. The purpose of this work was to analyze the geometric impact of locate the lymph node regions through the patient positioning by prostate fiducial markers. Methods: 10 patients with prostate SBRT with lymph nodes irradiation were selected. Each patient had 5 implanted titanium fiducial markers. A Novalis TX (BrainLAB-Varian) with ExacTrac and aSi1000 portal image was used. Treatment plan uses 11 beams with a dose prescription (D95%) of 40Gy to the prostate and 25Gy to the lymph node in 5 fractions. Daily positioning was carried out by ExacTrac system based on the implanted fiducials as the reference treatment position; further position verification was performed using the ExacTrac and two portal images (gantry angle 0 and 90) based on bony structures. Comparison between reference position with bony based ExacTrac and portal image localization, was done for each treatment fraction Results: A total of 50 positioning analysis were done. The average discrepancy between reference treatment position and ExacTrac based on bony anatomy (pubic area) was 4.2mm [0.3; 11.2]. The discrepancy was <5mm in 61% of the cases and <9mm in 92%. Using portal images the average discrepancy was 3.7mm [0.0; 11.1]. The discrepancy was <5mm in 69% of the cases and <9mm in 96%. Conclusion: Localizing lymph node by prostate fiducial markers may produce large discrepancy as large as 11mm compared to bony based localization. Dosimetric impact of this discrepancy should be studied.

A Supervised Classification Algorithm for Note Onset Detection

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Douglas Eck

2007-01-01

Full Text Available This paper presents a novel approach to detecting onsets in music audio files. We use a supervised learning algorithm to classify spectrogram frames extracted from digital audio as being onsets or nononsets. Frames classified as onsets are then treated with a simple peak-picking algorithm based on a moving average. We present two versions of this approach. The first version uses a single neural network classifier. The second version combines the predictions of several networks trained using different hyperparameters. We describe the details of the algorithm and summarize the performance of both variants on several datasets. We also examine our choice of hyperparameters by describing results of cross-validation experiments done on a custom dataset. We conclude that a supervised learning approach to note onset detection performs well and warrants further investigation.

A new edge detection algorithm based on Canny idea

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Feng, Yingke; Zhang, Jinmin; Wang, Siming

2017-10-01

The traditional Canny algorithm has poor self-adaptability threshold, and it is more sensitive to noise. In order to overcome these drawbacks, this paper proposed a new edge detection method based on Canny algorithm. Firstly, the media filtering and filtering based on the method of Euclidean distance are adopted to process it; secondly using the Frei-chen algorithm to calculate gradient amplitude; finally, using the Otsu algorithm to calculate partial gradient amplitude operation to get images of thresholds value, then find the average of all thresholds that had been calculated, half of the average is high threshold value, and the half of the high threshold value is low threshold value. Experiment results show that this new method can effectively suppress noise disturbance, keep the edge information, and also improve the edge detection accuracy.

Global Geodesy Using GPS Without Fiducial Sites

Science.gov (United States)

Heflin, Michael B.; Blewitt, Geoffrey

1994-01-01

Global Positioning System, GPS, used to make global geodetic measurements without use of fiducial site coordinates. Baseline lengths and geocentric radii for each site determined without having to fix any site coordinates. Given n globally distributed sites, n baseline lengths and n geocentric radii form polyhedron with each site at vertex and with geocenter at intersection of all radii. Geodetic information derived from structure of polyhedron and its change with time. Approach applied to any global geodetic technique.

A Fast Detection Algorithm for the X-Ray Pulsar Signal

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Hao Liang

2017-01-01

Full Text Available The detection of the X-ray pulsar signal is important for the autonomous navigation system using X-ray pulsars. In the condition of short observation time and limited number of photons for detection, the noise does not obey the Gaussian distribution. This fact has been little considered extant. In this paper, the model of the X-ray pulsar signal is rebuilt as the nonhomogeneous Poisson distribution and, in the condition of a fixed false alarm rate, a fast detection algorithm based on maximizing the detection probability is proposed. Simulation results show the effectiveness of the proposed detection algorithm.

Comparative study of adaptive-noise-cancellation algorithms for intrusion detection systems

International Nuclear Information System (INIS)

Claassen, J.P.; Patterson, M.M.

1981-01-01

Some intrusion detection systems are susceptible to nonstationary noise resulting in frequent nuisance alarms and poor detection when the noise is present. Adaptive inverse filtering for single channel systems and adaptive noise cancellation for two channel systems have both demonstrated good potential in removing correlated noise components prior detection. For such noise susceptible systems the suitability of a noise reduction algorithm must be established in a trade-off study weighing algorithm complexity against performance. The performance characteristics of several distinct classes of algorithms are established through comparative computer studies using real signals. The relative merits of the different algorithms are discussed in the light of the nature of intruder and noise signals

A novel line segment detection algorithm based on graph search

Science.gov (United States)

Zhao, Hong-dan; Liu, Guo-ying; Song, Xu

2018-02-01

To overcome the problem of extracting line segment from an image, a method of line segment detection was proposed based on the graph search algorithm. After obtaining the edge detection result of the image, the candidate straight line segments are obtained in four directions. For the candidate straight line segments, their adjacency relationships are depicted by a graph model, based on which the depth-first search algorithm is employed to determine how many adjacent line segments need to be merged. Finally we use the least squares method to fit the detected straight lines. The comparative experimental results verify that the proposed algorithm has achieved better results than the line segment detector (LSD).

Adaptive algorithm of magnetic heading detection

Science.gov (United States)

Liu, Gong-Xu; Shi, Ling-Feng

2017-11-01

Magnetic data obtained from a magnetic sensor usually fluctuate in a certain range, which makes it difficult to estimate the magnetic heading accurately. In fact, magnetic heading information is usually submerged in noise because of all kinds of electromagnetic interference and the diversity of the pedestrian’s motion states. In order to solve this problem, a new adaptive algorithm based on the (typically) right-angled corridors of a building or residential buildings is put forward to process heading information. First, a 3D indoor localization platform is set up based on MPU9250. Then, several groups of data are measured by changing the experimental environment and pedestrian’s motion pace. The raw data from the attached inertial measurement unit are calibrated and arranged into a time-stamped array and written to a data file. Later, the data file is imported into MATLAB for processing and analysis using the proposed adaptive algorithm. Finally, the algorithm is verified by comparison with the existing algorithm. The experimental results show that the algorithm has strong robustness and good fault tolerance, which can detect the heading information accurately and in real-time.

A Moving Object Detection Algorithm Based on Color Information

International Nuclear Information System (INIS)

Fang, X H; Xiong, W; Hu, B J; Wang, L T

2006-01-01

This paper designed a new algorithm of moving object detection for the aim of quick moving object detection and orientation, which used a pixel and its neighbors as an image vector to represent that pixel and modeled different chrominance component pixel as a mixture of Gaussians, and set up different mixture model of Gauss for different YUV chrominance components. In order to make full use of the spatial information, color segmentation and background model were combined. Simulation results show that the algorithm can detect intact moving objects even when the foreground has low contrast with background

The derivation of distributed termination detection algorithms from garbage collection schemes

NARCIS (Netherlands)

Tel, G.; Mattern, F.

1990-01-01

It is shown that the termination detection problem for distributed computations can be modelled as an instance of the garbage collection problem. Consequently, algorithms for the termination detection problem are obtained by applying transformations to garbage collection algorithms. The

Robust and accurate detection algorithm for multimode polymer optical FBG sensor system

DEFF Research Database (Denmark)

Ganziy, Denis; Jespersen, O.; Rose, B.

2015-01-01

We propose a novel dynamic gate algorithm (DGA) for robust and fast peak detection. The algorithm uses a threshold determined detection window and center of gravity algorithm with bias compensation. Our experiment demonstrates that the DGA method is fast and robust with better stability and accur...

Performances of the New Real Time Tsunami Detection Algorithm applied to tide gauges data

Science.gov (United States)

Chierici, F.; Embriaco, D.; Morucci, S.

2017-12-01

Real-time tsunami detection algorithms play a key role in any Tsunami Early Warning System. We have developed a new algorithm for tsunami detection (TDA) based on the real-time tide removal and real-time band-pass filtering of seabed pressure time series acquired by Bottom Pressure Recorders. The TDA algorithm greatly increases the tsunami detection probability, shortens the detection delay and enhances detection reliability with respect to the most widely used tsunami detection algorithm, while containing the computational cost. The algorithm is designed to be used also in autonomous early warning systems with a set of input parameters and procedures which can be reconfigured in real time. We have also developed a methodology based on Monte Carlo simulations to test the tsunami detection algorithms. The algorithm performance is estimated by defining and evaluating statistical parameters, namely the detection probability, the detection delay, which are functions of the tsunami amplitude and wavelength, and the occurring rate of false alarms. In this work we present the performance of the TDA algorithm applied to tide gauge data. We have adapted the new tsunami detection algorithm and the Monte Carlo test methodology to tide gauges. Sea level data acquired by coastal tide gauges in different locations and environmental conditions have been used in order to consider real working scenarios in the test. We also present an application of the algorithm to the tsunami event generated by Tohoku earthquake on March 11th 2011, using data recorded by several tide gauges scattered all over the Pacific area.

SU-E-T-507: Interfractional Variation of Fiducial Marker Position During HDR Brachytherapy with Cervical Interstitial Needle Template

Energy Technology Data Exchange (ETDEWEB)

Shen, S; Kim, R; Benhabib, S; Araujo, J; Burnett, L; Duan, J; Popple, R; Wu, X; Cardan, R; Brezovich, I [UniversityAlabama Birmingham, Birmingham, AL (United Kingdom)

2014-06-01

Purpose: HDR brachytherapy using interstitial needle template for cervical cancer is commonly delivered in 4-5 fractions. Routine verification of needle positions before each fraction is often based on radiographic imaging of implanted fiducial markers. The current study evaluated interfractional displacement of implanted fiducial markers using CT images. Methods: 9 sequential patients with cervical interstitial needle implants were evaluated. The superior and inferior borders of the target volumes were defined by fiducial markers in planning CT. The implant position was verified with kV orthogonal images before each fraction. A second CT was acquired prior 3rd fraction (one or 2 days post planning CT). Distances from inferior and superior fiducial markers to pubic symphysis plane (perpendicular to vaginal obtulator)were measured. Distance from needle tip of a reference needle (next to the inferior marker) to the pubic symphysis plane was also determined. The difference in fiducial marker distance or needle tip distance between planning CT and CT prior 3rd fraction were measured to assess markers migration and needle displacement. Results: The mean inferior marker displacement was 4.5 mm and ranged 0.9 to 11.3 mm. The mean superior marker displacement was 2.7 mm and ranged 0 to 10.4 mm. There was a good association between inferior and superior marker displacement (r=0.95). Mean averaged inferior and superior marker displacement was 3.3 mm and ranged from 0.1 to 10.9 mm, with a standard deviation of 3.2 mm. The mean needle displacement was 5.6 mm and ranged 0.2 to 15.6 mm. Needle displacements were reduced (p<0.05) after adjusting according to needle-to-fiducials distance. Conclusion: There were small fiducial marker displacements between HDR fractions. Our study suggests a target margin of 9.7 mm to cover interfractional marker displacements (in 95% cases) for pretreatment verification based on radiographic imaging.

A low complexity VBLAST OFDM detection algorithm for wireless LAN systems

NARCIS (Netherlands)

Wu, Y.; Lei, Zhongding; Sun, Sumei

2004-01-01

A low complexity detection algorithm for VBLAST OFDM system is presented. Using the fact that the correlation among neighboring subcarriers is high for wireless LAN channels, this algorithm significantly reduces the complexity of VBLAST OFDM detection. The performance degradation of the proposed

Improved target detection algorithm using Fukunaga-Koontz transform and distance classifier correlation filter

Science.gov (United States)

Bal, A.; Alam, M. S.; Aslan, M. S.

2006-05-01

Often sensor ego-motion or fast target movement causes the target to temporarily go out of the field-of-view leading to reappearing target detection problem in target tracking applications. Since the target goes out of the current frame and reenters at a later frame, the reentering location and variations in rotation, scale, and other 3D orientations of the target are not known thus complicating the detection algorithm has been developed using Fukunaga-Koontz Transform (FKT) and distance classifier correlation filter (DCCF). The detection algorithm uses target and background information, extracted from training samples, to detect possible candidate target images. The detected candidate target images are then introduced into the second algorithm, DCCF, called clutter rejection module, to determine the target coordinates are detected and tracking algorithm is initiated. The performance of the proposed FKT-DCCF based target detection algorithm has been tested using real-world forward looking infrared (FLIR) video sequences.

Assessment of prostate motion during radiotherapy using fiducial markers and CT reconstruction

International Nuclear Information System (INIS)

Crook, J.; Salhani, D.; Yang, H.; Deshaies, Y.; Raymond, Y.; Malone, S.; Esche, B.

1996-01-01

Purpose: To assess changes in prostate position during a course of pelvic radiotherapy for prostate cancer using fiducial markers and sequential planning CT scans. Methods and Materials: Three gold seeds are implanted in the apex, base and posterior aspect of the prostate under trans-rectal ultrasound guidance prior to initial simulation. In addition, treatment planning CT scans with 5 mm slices through the prostate are obtained at 0 and 40 Gy. Patients are scanned, simulated and treated with full bladder and are positioned using a standard foam leg support from the knees to the ankles. Prostate movement is assessed by two independent methods: [1] Localization of the fiducial markers using orthogonal simulator films taken just prior to the initial and boost stages of treatment and [2] a three-dimensional reconstruction methodology using CT datasets again obtained prior to the initial and boost stages. In both cases, rigid-body transformations of selected bony landmarks were used to eliminate patient movement between simulations and CT scans. For CT reconstruction, high order polynomial extrapolation and Chebychev multi-domain interpolation methods are employed to determine the coordinates of the fiducial markers. Prostatic movement, between initial and boost imaging, is estimated from the variance of the position of the corresponding seeds. Results: At present, seed data is available for sixty (60) patients. An additional nineteen (19) patients were excluded because of suspected seed migration > 3.0 mm or a localization uncertainty > 1.5 mm. The range of movement seen in the lateral direction is -0.25 to 0.48 cm (mean: 0.11, SD: 0.15), in the cranio-caudal direction -1.57 to 0.64 cm (mean: 0.59 SD: 0.48), and in the antero-posterior direction -1.91 to .47 cm (mean: 0.53, SD: 0.39). Results disclosed 53% of the patients with a caudal shift of the prostate > 0.5 cm and 10% > 1.0 cm. Further, 60% of the patients showed a posterior shift > 0.5 cm and 27% > 1.0 cm. CT

Statistical Algorithm for the Adaptation of Detection Thresholds

DEFF Research Database (Denmark)

Stotsky, Alexander A.

2008-01-01

Many event detection mechanisms in spark ignition automotive engines are based on the comparison of the engine signals to the detection threshold values. Different signal qualities for new and aged engines necessitate the development of an adaptation algorithm for the detection thresholds...... remains constant regardless of engine age and changing detection threshold values. This, in turn, guarantees the same event detection performance for new and aged engines/sensors. Adaptation of the engine knock detection threshold is given as an example. Udgivelsesdato: 2008...

Photon Counting Using Edge-Detection Algorithm

Science.gov (United States)

Gin, Jonathan W.; Nguyen, Danh H.; Farr, William H.

2010-01-01

New applications such as high-datarate, photon-starved, free-space optical communications require photon counting at flux rates into gigaphoton-per-second regimes coupled with subnanosecond timing accuracy. Current single-photon detectors that are capable of handling such operating conditions are designed in an array format and produce output pulses that span multiple sample times. In order to discern one pulse from another and not to overcount the number of incoming photons, a detection algorithm must be applied to the sampled detector output pulses. As flux rates increase, the ability to implement such a detection algorithm becomes difficult within a digital processor that may reside within a field-programmable gate array (FPGA). Systems have been developed and implemented to both characterize gigahertz bandwidth single-photon detectors, as well as process photon count signals at rates into gigaphotons per second in order to implement communications links at SCPPM (serial concatenated pulse position modulation) encoded data rates exceeding 100 megabits per second with efficiencies greater than two bits per detected photon. A hardware edge-detection algorithm and corresponding signal combining and deserialization hardware were developed to meet these requirements at sample rates up to 10 GHz. The photon discriminator deserializer hardware board accepts four inputs, which allows for the ability to take inputs from a quadphoton counting detector, to support requirements for optical tracking with a reduced number of hardware components. The four inputs are hardware leading-edge detected independently. After leading-edge detection, the resultant samples are ORed together prior to deserialization. The deserialization is performed to reduce the rate at which data is passed to a digital signal processor, perhaps residing within an FPGA. The hardware implements four separate analog inputs that are connected through RF connectors. Each analog input is fed to a high-speed 1

Hardware Implementation of a Modified Delay-Coordinate Mapping-Based QRS Complex Detection Algorithm

Directory of Open Access Journals (Sweden)

Andrej Zemva

2007-01-01

Full Text Available We present a modified delay-coordinate mapping-based QRS complex detection algorithm, suitable for hardware implementation. In the original algorithm, the phase-space portrait of an electrocardiogram signal is reconstructed in a two-dimensional plane using the method of delays. Geometrical properties of the obtained phase-space portrait are exploited for QRS complex detection. In our solution, a bandpass filter is used for ECG signal prefiltering and an improved method for detection threshold-level calculation is utilized. We developed the algorithm on the MIT-BIH Arrhythmia Database (sensitivity of 99.82% and positive predictivity of 99.82% and tested it on the long-term ST database (sensitivity of 99.72% and positive predictivity of 99.37%. Our algorithm outperforms several well-known QRS complex detection algorithms, including the original algorithm.

Quantification of MRI visibility and artifacts at 3T of liquid fiducial marker in a pancreas tissue-mimicking phantom

DEFF Research Database (Denmark)

Schneider, Sergej; Jølck, Rasmus Irming; Troost, Esther Gera Cornelia

2018-01-01

Purpose: X-ray-based position verification of the target volume in image-guided radiation therapy (IGRT) of patients with pancreatic ductal adenocarcinoma (PDAC) is currently performed on solid fiducial markers that are implanted under endoscopic ultrasonography. A new biodegradable liquid fiduci...

An OMIC biomarker detection algorithm TriVote and its application in methylomic biomarker detection.

Science.gov (United States)

Xu, Cheng; Liu, Jiamei; Yang, Weifeng; Shu, Yayun; Wei, Zhipeng; Zheng, Weiwei; Feng, Xin; Zhou, Fengfeng

2018-04-01

Transcriptomic and methylomic patterns represent two major OMIC data sources impacted by both inheritable genetic information and environmental factors, and have been widely used as disease diagnosis and prognosis biomarkers. Modern transcriptomic and methylomic profiling technologies detect the status of tens of thousands or even millions of probing residues in the human genome, and introduce a major computational challenge for the existing feature selection algorithms. This study proposes a three-step feature selection algorithm, TriVote, to detect a subset of transcriptomic or methylomic residues with highly accurate binary classification performance. TriVote outperforms both filter and wrapper feature selection algorithms with both higher classification accuracy and smaller feature number on 17 transcriptomes and two methylomes. Biological functions of the methylome biomarkers detected by TriVote were discussed for their disease associations. An easy-to-use Python package is also released to facilitate the further applications.

Research of time fiducial and imaging VISAR laser for Shenguang-III laser facility

Science.gov (United States)

Zhang, Rui; Wang, Zhenguo; Tian, Xiaocheng; Zhou, Dandan; Zhu, Na; Wang, Jianjun; Li, Mingzhong; Xu, Dangpeng; Dang, Zhao; Hu, Dongxia; Zhu, Qihua; Zheng, Wanguo; Wang, Feng

2015-10-01

Time fiducial laser is an important tool for the precise measurement in high energy density physics experiments. The VISAR probe laser is also vital for shock wave diagnostics in ICF experiments. Here, time fiducial laser and VISAR light were generated from one source on SG-III laser facility. After generated from a 1064-nm DFB laser, the laser is modulated by an amplitude modulator driven by 10 GS/s arbitrary waveform generator. Using time division multiplexing technology, the ten-pulse time fiducial laser and the 20-ns VISAR pulse were split by a 1×2 multiplexer and then chosen by two acoustic optic modulators. Using the technique, cost of the system was reduced. The technologies adopted in the system also include pulse polarization stabilization, high precision fiber coupling and energy transmission. The time fiducial laser generated synchronized 12-beam 2ω and 4-beam 3ω laser, providing important reference marks for different detectors and making it convenient for the analysis of diagnostic data. After being amplified by fiber amplifiers and Nd:YAG rod amplifiers, the VISAR laser pulse was frequency-converted to 532-nm pulse by a thermally controlled LBO crystal with final output energy larger than 20 mJ. Finally, the green light was coupled into a 1-mm core diameter, multimode fused silica optical fiber and propagated to the imaging VISAR. The VISAR laser has been used in the VISAR diagnostic physics experiments. Shock wave loading and slowdown processes were measured. Function to measure velocity history of shock wave front movement in different kinds of materials was added to the SG-III laser facility.

A Fiducial Reference Stie for Satellite Altimetry in Crete, Greece

Science.gov (United States)

Mertikas, Stelios; Donlon, Craig; Mavrocordatos, Constantin; Bojkov, Bojan; Femenias, Pierre; Parrinello, Tommaso; Picot, Nicolas; Desjonqueres, Jean-Damien; Andersen, Ole Baltazar

2016-08-01

With the advent of diverse satellite altimeters and variant measuring techniques, it has become mature in the scientific community, that an absolute reference Cal/Val site is regularly maintained to define, monitor, control the responses of any altimetric system.This work sets the ground for the establishment of a Fiducial Reference Site for ESA satellite altimetry in Gavdos and West Crete, Greece. It will consistently and reliably determine (a) absolute altimeter biases and their drifts; (b) relative bias among diverse missions; but also (c) continuously and independently connect different missions, on a common and reliable reference and also to SI-traceable measurements. Results from this fiducial reference site will be based on historic Cal/Val site measurement records, and will be the yardstick for building up capacity for monitoring climate change. This will be achieved by defining and assessing any satellite altimeter measurements to known, controlled and absolute reference signals with different techniques, processes and instrumentation.

Artifact removal algorithms for stroke detection using a multistatic MIST beamforming algorithm.

Science.gov (United States)

Ricci, E; Di Domenico, S; Cianca, E; Rossi, T

2015-01-01

Microwave imaging (MWI) has been recently proved as a promising imaging modality for low-complexity, low-cost and fast brain imaging tools, which could play a fundamental role to efficiently manage emergencies related to stroke and hemorrhages. This paper focuses on the UWB radar imaging approach and in particular on the processing algorithms of the backscattered signals. Assuming the use of the multistatic version of the MIST (Microwave Imaging Space-Time) beamforming algorithm, developed by Hagness et al. for the early detection of breast cancer, the paper proposes and compares two artifact removal algorithms. Artifacts removal is an essential step of any UWB radar imaging system and currently considered artifact removal algorithms have been shown not to be effective in the specific scenario of brain imaging. First of all, the paper proposes modifications of a known artifact removal algorithm. These modifications are shown to be effective to achieve good localization accuracy and lower false positives. However, the main contribution is the proposal of an artifact removal algorithm based on statistical methods, which allows to achieve even better performance but with much lower computational complexity.

Prefiltering Model for Homology Detection Algorithms on GPU.

Science.gov (United States)

Retamosa, Germán; de Pedro, Luis; González, Ivan; Tamames, Javier

2016-01-01

Homology detection has evolved over the time from heavy algorithms based on dynamic programming approaches to lightweight alternatives based on different heuristic models. However, the main problem with these algorithms is that they use complex statistical models, which makes it difficult to achieve a relevant speedup and find exact matches with the original results. Thus, their acceleration is essential. The aim of this article was to prefilter a sequence database. To make this work, we have implemented a groundbreaking heuristic model based on NVIDIA's graphics processing units (GPUs) and multicore processors. Depending on the sensitivity settings, this makes it possible to quickly reduce the sequence database by factors between 50% and 95%, while rejecting no significant sequences. Furthermore, this prefiltering application can be used together with multiple homology detection algorithms as a part of a next-generation sequencing system. Extensive performance and accuracy tests have been carried out in the Spanish National Centre for Biotechnology (NCB). The results show that GPU hardware can accelerate the execution times of former homology detection applications, such as National Centre for Biotechnology Information (NCBI), Basic Local Alignment Search Tool for Proteins (BLASTP), up to a factor of 4.

Regression algorithm for emotion detection

OpenAIRE

Berthelon , Franck; Sander , Peter

2013-01-01

International audience; We present here two components of a computational system for emotion detection. PEMs (Personalized Emotion Maps) store links between bodily expressions and emotion values, and are individually calibrated to capture each person's emotion profile. They are an implementation based on aspects of Scherer's theoretical complex system model of emotion~\\cite{scherer00, scherer09}. We also present a regression algorithm that determines a person's emotional feeling from sensor m...

Detecting an atomic clock frequency anomaly using an adaptive Kalman filter algorithm

Science.gov (United States)

Song, Huijie; Dong, Shaowu; Wu, Wenjun; Jiang, Meng; Wang, Weixiong

2018-06-01

The abnormal frequencies of an atomic clock mainly include frequency jump and frequency drift jump. Atomic clock frequency anomaly detection is a key technique in time-keeping. The Kalman filter algorithm, as a linear optimal algorithm, has been widely used in real-time detection for abnormal frequency. In order to obtain an optimal state estimation, the observation model and dynamic model of the Kalman filter algorithm should satisfy Gaussian white noise conditions. The detection performance is degraded if anomalies affect the observation model or dynamic model. The idea of the adaptive Kalman filter algorithm, applied to clock frequency anomaly detection, uses the residuals given by the prediction for building ‘an adaptive factor’ the prediction state covariance matrix is real-time corrected by the adaptive factor. The results show that the model error is reduced and the detection performance is improved. The effectiveness of the algorithm is verified by the frequency jump simulation, the frequency drift jump simulation and the measured data of the atomic clock by using the chi-square test.

W+W- production at the LHC. Fiducial cross sections and distributions in NNLO QCD

International Nuclear Information System (INIS)

Grazzini, Massimiliano; Wiesemann, Marius; Kallweit, Stefan; California Univ., Santa Barbara, CA; Pozzorini, Stefano; California Univ., Santa Barbara, CA; Rathlev, Dirk

2016-05-01

We consider QCD radiative corrections to W + W - production at the LHC and present the first fully differential predictions for this process at next-to-next-to-leading order (NNLO) in perturbation theory. Our computation consistently includes the leptonic decays of the W bosons, taking into account spin correlations, off-shell effects and non-resonant contributions. Detailed predictions are presented for the different-flavour channel pp→μ + e - ν μ anti ν e +X at √(s)=8 and 13 TeV. In particular, we discuss fiducial cross sections and distributions in the presence of standard selection cuts used in experimental W + W - and H→W + W - analyses at the LHC. The inclusive W + W - cross section receives large NNLO corrections, and, due to the presence of a jet veto, typical fiducial cuts have a sizeable influence on the behaviour of the perturbative expansion. The availability of differential NNLO predictions, both for inclusive and fiducial observables, will play an important role in the rich physics programme that is based on precision studies of W + W - signatures at the LHC.

A street rubbish detection algorithm based on Sift and RCNN

Science.gov (United States)

Yu, XiPeng; Chen, Zhong; Zhang, Shuo; Zhang, Ting

2018-02-01

This paper presents a street rubbish detection algorithm based on image registration with Sift feature and RCNN. Firstly, obtain the rubbish region proposal on the real-time street image and set up the CNN convolution neural network trained by the rubbish samples set consists of rubbish and non-rubbish images; Secondly, for every clean street image, obtain the Sift feature and do image registration with the real-time street image to obtain the differential image, the differential image filters a lot of background information, obtain the rubbish region proposal rect where the rubbish may appear on the differential image by the selective search algorithm. Then, the CNN model is used to detect the image pixel data in each of the region proposal on the real-time street image. According to the output vector of the CNN, it is judged whether the rubbish is in the region proposal or not. If it is rubbish, the region proposal on the real-time street image is marked. This algorithm avoids the large number of false detection caused by the detection on the whole image because the CNN is used to identify the image only in the region proposal on the real-time street image that may appear rubbish. Different from the traditional object detection algorithm based on the region proposal, the region proposal is obtained on the differential image not whole real-time street image, and the number of the invalid region proposal is greatly reduced. The algorithm has the high mean average precision (mAP).

Decision algorithms in fire detection systems

Directory of Open Access Journals (Sweden)

Ristić Jovan D.

2011-01-01

Full Text Available Analogue (and addressable fire detection systems enables a new quality in improving sensitivity to real fires and reducing susceptibility to nuisance alarm sources. Different decision algorithms types were developed with intention to improve sensitivity and reduce false alarm occurrence. At the beginning, it was free alarm level adjustment based on preset level. Majority of multi-criteria decision work was based on multi-sensor (multi-signature decision algorithms - using different type of sensors on the same location or, rather, using different aspects (level and rise of one sensor measured value. Our idea is to improve sensitivity and reduce false alarm occurrence by forming groups of sensors that work in similar conditions (same world side in the building, same or similar technology or working time. Original multi-criteria decision algorithms based on level, rise and difference of level and rise from group average are discussed in this paper.

A hybrid neural network – world cup optimization algorithm for melanoma detection

Directory of Open Access Journals (Sweden)

Razmjooy Navid

2018-03-01

Full Text Available One of the most dangerous cancers in humans is Melanoma. However, early detection of melanoma can help us to cure it completely. This paper presents a new efficient method to detect malignancy in melanoma via images. At first, the extra scales are eliminated by using edge detection and smoothing. Afterwards, the proposed method can be utilized to segment the cancer images. Finally, the extra information is eliminated by morphological operations and used to focus on the area which melanoma boundary potentially exists. To do this, World Cup Optimization algorithm is utilized to optimize an MLP neural Networks (ANN. World Cup Optimization algorithm is a new meta-heuristic algorithm which is recently presented and has a good performance in some optimization problems. WCO is a derivative-free, Meta-Heuristic algorithm, mimicking the world’s FIFA competitions. World cup Optimization algorithm is a global search algorithm while gradient-based back propagation method is local search. In this proposed algorithm, multi-layer perceptron network (MLP employs the problem’s constraints and WCO algorithm attempts to minimize the root mean square error. Experimental results show that the proposed method can develop the performance of the standard MLP algorithm significantly.

On the performance of pre-microRNA detection algorithms

DEFF Research Database (Denmark)

Saçar Demirci, Müşerref Duygu; Baumbach, Jan; Allmer, Jens

2017-01-01

assess 13 ab initio pre-miRNA detection approaches using all relevant, published, and novel data sets while judging algorithm performance based on ten intrinsic performance measures. We present an extensible framework, izMiR, which allows for the unbiased comparison of existing algorithms, adding new...

R Peak Detection Method Using Wavelet Transform and Modified Shannon Energy Envelope.

Science.gov (United States)

Park, Jeong-Seon; Lee, Sang-Woong; Park, Unsang

2017-01-01

Rapid automatic detection of the fiducial points-namely, the P wave, QRS complex, and T wave-is necessary for early detection of cardiovascular diseases (CVDs). In this paper, we present an R peak detection method using the wavelet transform (WT) and a modified Shannon energy envelope (SEE) for rapid ECG analysis. The proposed WTSEE algorithm performs a wavelet transform to reduce the size and noise of ECG signals and creates SEE after first-order differentiation and amplitude normalization. Subsequently, the peak energy envelope (PEE) is extracted from the SEE. Then, R peaks are estimated from the PEE, and the estimated peaks are adjusted from the input ECG. Finally, the algorithm generates the final R features by validating R-R intervals and updating the extracted R peaks. The proposed R peak detection method was validated using 48 first-channel ECG records of the MIT-BIH arrhythmia database with a sensitivity of 99.93%, positive predictability of 99.91%, detection error rate of 0.16%, and accuracy of 99.84%. Considering the high detection accuracy and fast processing speed due to the wavelet transform applied before calculating SEE, the proposed method is highly effective for real-time applications in early detection of CVDs.

Improved algorithm for quantum separability and entanglement detection

International Nuclear Information System (INIS)

Ioannou, L.M.; Ekert, A.K.; Travaglione, B.C.; Cheung, D.

2004-01-01

Determining whether a quantum state is separable or entangled is a problem of fundamental importance in quantum information science. It has recently been shown that this problem is NP-hard, suggesting that an efficient, general solution does not exist. There is a highly inefficient 'basic algorithm' for solving the quantum separability problem which follows from the definition of a separable state. By exploiting specific properties of the set of separable states, we introduce a classical algorithm that solves the problem significantly faster than the 'basic algorithm', allowing a feasible separability test where none previously existed, e.g., in 3x3-dimensional systems. Our algorithm also provides a unique tool in the experimental detection of entanglement

Detecting microsatellites within genomes: significant variation among algorithms

Directory of Open Access Journals (Sweden)

Rivals Eric

2007-04-01

Full Text Available Abstract Background Microsatellites are short, tandemly-repeated DNA sequences which are widely distributed among genomes. Their structure, role and evolution can be analyzed based on exhaustive extraction from sequenced genomes. Several dedicated algorithms have been developed for this purpose. Here, we compared the detection efficiency of five of them (TRF, Mreps, Sputnik, STAR, and RepeatMasker. Results Our analysis was first conducted on the human X chromosome, and microsatellite distributions were characterized by microsatellite number, length, and divergence from a pure motif. The algorithms work with user-defined parameters, and we demonstrate that the parameter values chosen can strongly influence microsatellite distributions. The five algorithms were then compared by fixing parameters settings, and the analysis was extended to three other genomes (Saccharomyces cerevisiae, Neurospora crassa and Drosophila melanogaster spanning a wide range of size and structure. Significant differences for all characteristics of microsatellites were observed among algorithms, but not among genomes, for both perfect and imperfect microsatellites. Striking differences were detected for short microsatellites (below 20 bp, regardless of motif. Conclusion Since the algorithm used strongly influences empirical distributions, studies analyzing microsatellite evolution based on a comparison between empirical and theoretical size distributions should therefore be considered with caution. We also discuss why a typological definition of microsatellites limits our capacity to capture their genomic distributions.

Crowdsourcing seizure detection: algorithm development and validation on human implanted device recordings.

Science.gov (United States)

Baldassano, Steven N; Brinkmann, Benjamin H; Ung, Hoameng; Blevins, Tyler; Conrad, Erin C; Leyde, Kent; Cook, Mark J; Khambhati, Ankit N; Wagenaar, Joost B; Worrell, Gregory A; Litt, Brian

2017-06-01

There exist significant clinical and basic research needs for accurate, automated seizure detection algorithms. These algorithms have translational potential in responsive neurostimulation devices and in automatic parsing of continuous intracranial electroencephalography data. An important barrier to developing accurate, validated algorithms for seizure detection is limited access to high-quality, expertly annotated seizure data from prolonged recordings. To overcome this, we hosted a kaggle.com competition to crowdsource the development of seizure detection algorithms using intracranial electroencephalography from canines and humans with epilepsy. The top three performing algorithms from the contest were then validated on out-of-sample patient data including standard clinical data and continuous ambulatory human data obtained over several years using the implantable NeuroVista seizure advisory system. Two hundred teams of data scientists from all over the world participated in the kaggle.com competition. The top performing teams submitted highly accurate algorithms with consistent performance in the out-of-sample validation study. The performance of these seizure detection algorithms, achieved using freely available code and data, sets a new reproducible benchmark for personalized seizure detection. We have also shared a 'plug and play' pipeline to allow other researchers to easily use these algorithms on their own datasets. The success of this competition demonstrates how sharing code and high quality data results in the creation of powerful translational tools with significant potential to impact patient care. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

SU-F-T-660: Evaluating the Benefit of Using Dual-Function Fiducial Markers for In-Situ Delivery of Radiosenistizing Gold Nanoparticles During Image-Guided Radiotherapy

Energy Technology Data Exchange (ETDEWEB)

AlMansour, S; Chin, J; Sajo, E; Ngwa, W [University Massachusetts Lowell, Lowell, MA (United States)

2016-06-15

Purpose: Dual-function fiducials loaded with radiosensitizers, like gold nanoparticles (GNP), offer an innovative approach for ensuring geometric accuracy during image-guided radiotherapy (IGRT) and significantly increasing therapeutic efficacy due to controlled in-situ release of the radiosensitizers. This study retrospectively investigates the dosimetric benefit of using up to two such dual-function fiducial markers instead of traditional single function fiducials during IGRT. Methods: A computational code was developed to investigate the dosimetric benefit for 10 real patient tumor volumes of up to 6.5 cm diameter. The intra-tumoral space-time biodistribution of the GNP was modeled as in previous studies based on Fick’s second law. The corresponding dose-enhancement for each tumor voxel due to the GNP was also calculated for clinical 6MV beam configurations. Various loading concentrations (25–50 mg/g) were studied, as a function of GNP size, to determine potential for clinically significant dose enhancement. The time between initial implantation of dual-function fiducials to the beginning of radiotherapy was assumed to be 14 days as typical for many clinics. Results: A single dual-function fiducial could achieve at least a DEF of 1.2 for patients with tumors less than 1.4 cm diameter after 14 days. Replacing two single function fiducials with dual-function ones at the same locations achieved at least the required minimal DEF for tumors that are 2 cm diameter in 3 patients. The results also revealed dosimetrically better fiducial locations which could enable significant DEF when using one or two dual function fiducials. 2 nm sizes showed the most feasibility. Conclusion: The results highlight the potential of tumor sub-volume radiation boosting using GNP released from fiducials, and the ability to customize the DEF throughout the tumor by using two dual-function fiducials, varying the initial concentration and nanoparticle size. The results demonstrate

SU-F-T-660: Evaluating the Benefit of Using Dual-Function Fiducial Markers for In-Situ Delivery of Radiosenistizing Gold Nanoparticles During Image-Guided Radiotherapy

International Nuclear Information System (INIS)

AlMansour, S; Chin, J; Sajo, E; Ngwa, W

2016-01-01

Purpose: Dual-function fiducials loaded with radiosensitizers, like gold nanoparticles (GNP), offer an innovative approach for ensuring geometric accuracy during image-guided radiotherapy (IGRT) and significantly increasing therapeutic efficacy due to controlled in-situ release of the radiosensitizers. This study retrospectively investigates the dosimetric benefit of using up to two such dual-function fiducial markers instead of traditional single function fiducials during IGRT. Methods: A computational code was developed to investigate the dosimetric benefit for 10 real patient tumor volumes of up to 6.5 cm diameter. The intra-tumoral space-time biodistribution of the GNP was modeled as in previous studies based on Fick’s second law. The corresponding dose-enhancement for each tumor voxel due to the GNP was also calculated for clinical 6MV beam configurations. Various loading concentrations (25–50 mg/g) were studied, as a function of GNP size, to determine potential for clinically significant dose enhancement. The time between initial implantation of dual-function fiducials to the beginning of radiotherapy was assumed to be 14 days as typical for many clinics. Results: A single dual-function fiducial could achieve at least a DEF of 1.2 for patients with tumors less than 1.4 cm diameter after 14 days. Replacing two single function fiducials with dual-function ones at the same locations achieved at least the required minimal DEF for tumors that are 2 cm diameter in 3 patients. The results also revealed dosimetrically better fiducial locations which could enable significant DEF when using one or two dual function fiducials. 2 nm sizes showed the most feasibility. Conclusion: The results highlight the potential of tumor sub-volume radiation boosting using GNP released from fiducials, and the ability to customize the DEF throughout the tumor by using two dual-function fiducials, varying the initial concentration and nanoparticle size. The results demonstrate

Detecting structural breaks in time series via genetic algorithms

DEFF Research Database (Denmark)

Doerr, Benjamin; Fischer, Paul; Hilbert, Astrid

2016-01-01

of the time series under consideration is available. Therefore, a black-box optimization approach is our method of choice for detecting structural breaks. We describe a genetic algorithm framework which easily adapts to a large number of statistical settings. To evaluate the usefulness of different crossover...... and mutation operations for this problem, we conduct extensive experiments to determine good choices for the parameters and operators of the genetic algorithm. One surprising observation is that use of uniform and one-point crossover together gave significantly better results than using either crossover...... operator alone. Moreover, we present a specific fitness function which exploits the sparse structure of the break points and which can be evaluated particularly efficiently. The experiments on artificial and real-world time series show that the resulting algorithm detects break points with high precision...

Swarm, genetic and evolutionary programming algorithms applied to multiuser detection

Directory of Open Access Journals (Sweden)

Paul Jean Etienne Jeszensky

2005-02-01

Full Text Available In this paper, the particles swarm optimization technique, recently published in the literature, and applied to Direct Sequence/Code Division Multiple Access systems (DS/CDMA with multiuser detection (MuD is analyzed, evaluated and compared. The Swarm algorithm efficiency when applied to the DS-CDMA multiuser detection (Swarm-MuD is compared through the tradeoff performance versus computational complexity, being the complexity expressed in terms of the number of necessary operations in order to reach the performance obtained through the optimum detector or the Maximum Likelihood detector (ML. The comparison is accomplished among the genetic algorithm, evolutionary programming with cloning and Swarm algorithm under the same simulation basis. Additionally, it is proposed an heuristics-MuD complexity analysis through the number of computational operations. Finally, an analysis is carried out for the input parameters of the Swarm algorithm in the attempt to find the optimum parameters (or almost-optimum for the algorithm applied to the MuD problem.

Detection of Cheating by Decimation Algorithm

Science.gov (United States)

Yamanaka, Shogo; Ohzeki, Masayuki; Decelle, Aurélien

2015-02-01

We expand the item response theory to study the case of "cheating students" for a set of exams, trying to detect them by applying a greedy algorithm of inference. This extended model is closely related to the Boltzmann machine learning. In this paper we aim to infer the correct biases and interactions of our model by considering a relatively small number of sets of training data. Nevertheless, the greedy algorithm that we employed in the present study exhibits good performance with a few number of training data. The key point is the sparseness of the interactions in our problem in the context of the Boltzmann machine learning: the existence of cheating students is expected to be very rare (possibly even in real world). We compare a standard approach to infer the sparse interactions in the Boltzmann machine learning to our greedy algorithm and we find the latter to be superior in several aspects.

Gear Tooth Wear Detection Algorithm

Science.gov (United States)

Delgado, Irebert R.

2015-01-01

Vibration-based condition indicators continue to be developed for Health Usage Monitoring of rotorcraft gearboxes. Testing performed at NASA Glenn Research Center have shown correlations between specific condition indicators and specific types of gear wear. To speed up the detection and analysis of gear teeth, an image detection program based on the Viola-Jones algorithm was trained to automatically detect spiral bevel gear wear pitting. The detector was tested using a training set of gear wear pictures and a blind set of gear wear pictures. The detector accuracy for the training set was 75 percent while the accuracy for the blind set was 15 percent. Further improvements on the accuracy of the detector are required but preliminary results have shown its ability to automatically detect gear tooth wear. The trained detector would be used to quickly evaluate a set of gear or pinion pictures for pits, spalls, or abrasive wear. The results could then be used to correlate with vibration or oil debris data. In general, the program could be retrained to detect features of interest from pictures of a component taken over a period of time.

A Contextual Fire Detection Algorithm for Simulated HJ-1B Imagery

Directory of Open Access Journals (Sweden)

Xiangsheng Kong

2009-02-01

Full Text Available The HJ-1B satellite, which was launched on September 6, 2008, is one of the small ones placed in the constellation for disaster prediction and monitoring. HJ-1B imagery was simulated in this paper, which contains fires of various sizes and temperatures in a wide range of terrestrial biomes and climates, including RED, NIR, MIR and TIR channels. Based on the MODIS version 4 contextual algorithm and the characteristics of HJ-1B sensor, a contextual fire detection algorithm was proposed and tested using simulated HJ-1B data. It was evaluated by the probability of fire detection and false alarm as functions of fire temperature and fire area. Results indicate that when the simulated fire area is larger than 45 m2 and the simulated fire temperature is larger than 800 K, the algorithm has a higher probability of detection. But if the simulated fire area is smaller than 10 m2, only when the simulated fire temperature is larger than 900 K, may the fire be detected. For fire areas about 100 m2, the proposed algorithm has a higher detection probability than that of the MODIS product. Finally, the omission and commission error were evaluated which are important factors to affect the performance of this algorithm. It has been demonstrated that HJ-1B satellite data are much sensitive to smaller and cooler fires than MODIS or AVHRR data and the improved capabilities of HJ-1B data will offer a fine opportunity for the fire detection.

AN ALGORITHM TO DETECT THE RETINAL REGION OF INTEREST

Directory of Open Access Journals (Sweden)

E. Şehirli

2017-11-01

Full Text Available Retina is one of the important layers of the eyes, which includes sensitive cells to colour and light and nerve fibers. Retina can be displayed by using some medical devices such as fundus camera, ophthalmoscope. Hence, some lesions like microaneurysm, haemorrhage, exudate with many diseases of the eye can be detected by looking at the images taken by devices. In computer vision and biomedical areas, studies to detect lesions of the eyes automatically have been done for a long time. In order to make automated detections, the concept of ROI may be utilized. ROI which stands for region of interest generally serves the purpose of focusing on particular targets. The main concentration of this paper is the algorithm to automatically detect retinal region of interest belonging to different retinal images on a software application. The algorithm consists of three stages such as pre-processing stage, detecting ROI on processed images and overlapping between input image and obtained ROI of the image.

An Algorithm to Detect the Retinal Region of Interest

Science.gov (United States)

Şehirli, E.; Turan, M. K.; Demiral, E.

2017-11-01

Retina is one of the important layers of the eyes, which includes sensitive cells to colour and light and nerve fibers. Retina can be displayed by using some medical devices such as fundus camera, ophthalmoscope. Hence, some lesions like microaneurysm, haemorrhage, exudate with many diseases of the eye can be detected by looking at the images taken by devices. In computer vision and biomedical areas, studies to detect lesions of the eyes automatically have been done for a long time. In order to make automated detections, the concept of ROI may be utilized. ROI which stands for region of interest generally serves the purpose of focusing on particular targets. The main concentration of this paper is the algorithm to automatically detect retinal region of interest belonging to different retinal images on a software application. The algorithm consists of three stages such as pre-processing stage, detecting ROI on processed images and overlapping between input image and obtained ROI of the image.

NASA airborne radar wind shear detection algorithm and the detection of wet microbursts in the vicinity of Orlando, Florida

Science.gov (United States)

Britt, Charles L.; Bracalente, Emedio M.

1992-01-01

The algorithms used in the NASA experimental wind shear radar system for detection, characterization, and determination of windshear hazard are discussed. The performance of the algorithms in the detection of wet microbursts near Orlando is presented. Various suggested algorithms that are currently being evaluated using the flight test results from Denver and Orlando are reviewed.

Advanced defect detection algorithm using clustering in ultrasonic NDE

Science.gov (United States)

Gongzhang, Rui; Gachagan, Anthony

2016-02-01

A range of materials used in industry exhibit scattering properties which limits ultrasonic NDE. Many algorithms have been proposed to enhance defect detection ability, such as the well-known Split Spectrum Processing (SSP) technique. Scattering noise usually cannot be fully removed and the remaining noise can be easily confused with real feature signals, hence becoming artefacts during the image interpretation stage. This paper presents an advanced algorithm to further reduce the influence of artefacts remaining in A-scan data after processing using a conventional defect detection algorithm. The raw A-scan data can be acquired from either traditional single transducer or phased array configurations. The proposed algorithm uses the concept of unsupervised machine learning to cluster segmental defect signals from pre-processed A-scans into different classes. The distinction and similarity between each class and the ensemble of randomly selected noise segments can be observed by applying a classification algorithm. Each class will then be labelled as `legitimate reflector' or `artefacts' based on this observation and the expected probability of defection (PoD) and probability of false alarm (PFA) determined. To facilitate data collection and validate the proposed algorithm, a 5MHz linear array transducer is used to collect A-scans from both austenitic steel and Inconel samples. Each pulse-echo A-scan is pre-processed using SSP and the subsequent application of the proposed clustering algorithm has provided an additional reduction to PFA while maintaining PoD for both samples compared with SSP results alone.

Combined Dust Detection Algorithm by Using MODIS Infrared Channels over East Asia

Science.gov (United States)

Park, Sang Seo; Kim, Jhoon; Lee, Jaehwa; Lee, Sukjo; Kim, Jeong Soo; Chang, Lim Seok; Ou, Steve

2014-01-01

A new dust detection algorithm is developed by combining the results of multiple dust detectionmethods using IR channels onboard the MODerate resolution Imaging Spectroradiometer (MODIS). Brightness Temperature Difference (BTD) between two wavelength channels has been used widely in previous dust detection methods. However, BTDmethods have limitations in identifying the offset values of the BTDto discriminate clear-sky areas. The current algorithm overcomes the disadvantages of previous dust detection methods by considering the Brightness Temperature Ratio (BTR) values of the dual wavelength channels with 30-day composite, the optical properties of the dust particles, the variability of surface properties, and the cloud contamination. Therefore, the current algorithm shows improvements in detecting the dust loaded region over land during daytime. Finally, the confidence index of the current dust algorithm is shown in 10 × 10 pixels of the MODIS observations. From January to June, 2006, the results of the current algorithm are within 64 to 81% of those found using the fine mode fraction (FMF) and aerosol index (AI) from the MODIS and Ozone Monitoring Instrument (OMI). The agreement between the results of the current algorithm and the OMI AI over the non-polluted land also ranges from 60 to 67% to avoid errors due to the anthropogenic aerosol. In addition, the developed algorithm shows statistically significant results at four AErosol RObotic NETwork (AERONET) sites in East Asia.

Effects of line fiducial parameters and beamforming on ultrasound calibration.

Science.gov (United States)

Ameri, Golafsoun; Baxter, John S H; McLeod, A Jonathan; Peters, Terry M; Chen, Elvis C S

2017-01-01

Ultrasound (US)-guided interventions are often enhanced via integration with an augmented reality environment, a necessary component of which is US calibration. Calibration requires the segmentation of fiducials, i.e., a phantom, in US images. Fiducial localization error (FLE) can decrease US calibration accuracy, which fundamentally affects the total accuracy of the interventional guidance system. Here, we investigate the effects of US image reconstruction techniques as well as phantom material and geometry on US calibration. It was shown that the FLE was reduced by 29% with synthetic transmit aperture imaging compared with conventional B-mode imaging in a Z-bar calibration, resulting in a 10% reduction of calibration error. In addition, an evaluation of a variety of calibration phantoms with different geometrical and material properties was performed. The phantoms included braided wire, plastic straws, and polyvinyl alcohol cryogel tubes with different diameters. It was shown that these properties have a significant effect on calibration error, which is a variable based on US beamforming techniques. These results would have important implications for calibration procedures and their feasibility in the context of image-guided procedures.

Night-Time Vehicle Detection Algorithm Based on Visual Saliency and Deep Learning

Directory of Open Access Journals (Sweden)

Yingfeng Cai

2016-01-01

Full Text Available Night vision systems get more and more attention in the field of automotive active safety field. In this area, a number of researchers have proposed far-infrared sensor based night-time vehicle detection algorithm. However, existing algorithms have low performance in some indicators such as the detection rate and processing time. To solve this problem, we propose a far-infrared image vehicle detection algorithm based on visual saliency and deep learning. Firstly, most of the nonvehicle pixels will be removed with visual saliency computation. Then, vehicle candidate will be generated by using prior information such as camera parameters and vehicle size. Finally, classifier trained with deep belief networks will be applied to verify the candidates generated in last step. The proposed algorithm is tested in around 6000 images and achieves detection rate of 92.3% and processing time of 25 Hz which is better than existing methods.

A CDMA multiuser detection algorithm on the basis of belief propagation

International Nuclear Information System (INIS)

Kabashima, Yoshiyuki

2003-01-01

An iterative algorithm for the multiuser detection problem that arises in code division multiple access (CDMA) systems is developed on the basis of Pearl's belief propagation (BP). We show that the BP-based algorithm exhibits nearly optimal performance in a practical time scale by utilizing the central limit theorem and self-averaging property appropriately, whereas direct application of BP to the detection problem is computationally difficult and far from practical. We further present close relationships of the proposed algorithm to the Thouless-Anderson-Palmer approach and replica analysis known in spin-glass research

Detection of honeycomb cell walls from measurement data based on Harris corner detection algorithm

Science.gov (United States)

Qin, Yan; Dong, Zhigang; Kang, Renke; Yang, Jie; Ayinde, Babajide O.

2018-06-01

A honeycomb core is a discontinuous material with a thin-wall structure—a characteristic that makes accurate surface measurement difficult. This paper presents a cell wall detection method based on the Harris corner detection algorithm using laser measurement data. The vertexes of honeycomb cores are recognized with two different methods: one method is the reduction of data density, and the other is the optimization of the threshold of the Harris corner detection algorithm. Each cell wall is then identified in accordance with the neighboring relationships of its vertexes. Experiments were carried out for different types and surface shapes of honeycomb cores, where the proposed method was proved effective in dealing with noise due to burrs and/or deformation of cell walls.

From Pixels to Region: A Salient Region Detection Algorithm for Location-Quantification Image

Directory of Open Access Journals (Sweden)

Mengmeng Zhang

2014-01-01

Full Text Available Image saliency detection has become increasingly important with the development of intelligent identification and machine vision technology. This process is essential for many image processing algorithms such as image retrieval, image segmentation, image recognition, and adaptive image compression. We propose a salient region detection algorithm for full-resolution images. This algorithm analyzes the randomness and correlation of image pixels and pixel-to-region saliency computation mechanism. The algorithm first obtains points with more saliency probability by using the improved smallest univalue segment assimilating nucleus operator. It then reconstructs the entire saliency region detection by taking these points as reference and combining them with image spatial color distribution, as well as regional and global contrasts. The results for subjective and objective image saliency detection show that the proposed algorithm exhibits outstanding performance in terms of technology indices such as precision and recall rates.

A Comparative Evaluation of Unsupervised Anomaly Detection Algorithms for Multivariate Data

Science.gov (United States)

Goldstein, Markus; Uchida, Seiichi

2016-01-01

Anomaly detection is the process of identifying unexpected items or events in datasets, which differ from the norm. In contrast to standard classification tasks, anomaly detection is often applied on unlabeled data, taking only the internal structure of the dataset into account. This challenge is known as unsupervised anomaly detection and is addressed in many practical applications, for example in network intrusion detection, fraud detection as well as in the life science and medical domain. Dozens of algorithms have been proposed in this area, but unfortunately the research community still lacks a comparative universal evaluation as well as common publicly available datasets. These shortcomings are addressed in this study, where 19 different unsupervised anomaly detection algorithms are evaluated on 10 different datasets from multiple application domains. By publishing the source code and the datasets, this paper aims to be a new well-funded basis for unsupervised anomaly detection research. Additionally, this evaluation reveals the strengths and weaknesses of the different approaches for the first time. Besides the anomaly detection performance, computational effort, the impact of parameter settings as well as the global/local anomaly detection behavior is outlined. As a conclusion, we give an advise on algorithm selection for typical real-world tasks. PMID:27093601

Automatic Detection and Quantification of WBCs and RBCs Using Iterative Structured Circle Detection Algorithm

Directory of Open Access Journals (Sweden)

Yazan M. Alomari

2014-01-01

Full Text Available Segmentation and counting of blood cells are considered as an important step that helps to extract features to diagnose some specific diseases like malaria or leukemia. The manual counting of white blood cells (WBCs and red blood cells (RBCs in microscopic images is an extremely tedious, time consuming, and inaccurate process. Automatic analysis will allow hematologist experts to perform faster and more accurately. The proposed method uses an iterative structured circle detection algorithm for the segmentation and counting of WBCs and RBCs. The separation of WBCs from RBCs was achieved by thresholding, and specific preprocessing steps were developed for each cell type. Counting was performed for each image using the proposed method based on modified circle detection, which automatically counted the cells. Several modifications were made to the basic (RCD algorithm to solve the initialization problem, detecting irregular circles (cells, selecting the optimal circle from the candidate circles, determining the number of iterations in a fully dynamic way to enhance algorithm detection, and running time. The validation method used to determine segmentation accuracy was a quantitative analysis that included Precision, Recall, and F-measurement tests. The average accuracy of the proposed method was 95.3% for RBCs and 98.4% for WBCs.

Fast intersection detection algorithm for PC-based robot off-line programming

Science.gov (United States)

Fedrowitz, Christian H.

1994-11-01

This paper presents a method for fast and reliable collision detection in complex production cells. The algorithm is part of the PC-based robot off-line programming system of the University of Siegen (Ropsus). The method is based on a solid model which is managed by a simplified constructive solid geometry model (CSG-model). The collision detection problem is divided in two steps. In the first step the complexity of the problem is reduced in linear time. In the second step the remaining solids are tested for intersection. For this the Simplex algorithm, which is known from linear optimization, is used. It computes a point which is common to two convex polyhedra. The polyhedra intersect, if such a point exists. Regarding the simplified geometrical model of Ropsus the algorithm runs also in linear time. In conjunction with the first step a resultant collision detection algorithm is found which requires linear time in all. Moreover it computes the resultant intersection polyhedron using the dual transformation.

Robust augmented reality registration method for localization of solid organs' tumors using CT-derived virtual biomechanical model and fluorescent fiducials.

Science.gov (United States)

Kong, Seong-Ho; Haouchine, Nazim; Soares, Renato; Klymchenko, Andrey; Andreiuk, Bohdan; Marques, Bruno; Shabat, Galyna; Piechaud, Thierry; Diana, Michele; Cotin, Stéphane; Marescaux, Jacques

2017-07-01

Augmented reality (AR) is the fusion of computer-generated and real-time images. AR can be used in surgery as a navigation tool, by creating a patient-specific virtual model through 3D software manipulation of DICOM imaging (e.g., CT scan). The virtual model can be superimposed to real-time images enabling transparency visualization of internal anatomy and accurate localization of tumors. However, the 3D model is rigid and does not take into account inner structures' deformations. We present a concept of automated AR registration, while the organs undergo deformation during surgical manipulation, based on finite element modeling (FEM) coupled with optical imaging of fluorescent surface fiducials. Two 10 × 1 mm wires (pseudo-tumors) and six 10 × 0.9 mm fluorescent fiducials were placed in ex vivo porcine kidneys (n = 10). Biomechanical FEM-based models were generated from CT scan. Kidneys were deformed and the shape changes were identified by tracking the fiducials, using a near-infrared optical system. The changes were registered automatically with the virtual model, which was deformed accordingly. Accuracy of prediction of pseudo-tumors' location was evaluated with a CT scan in the deformed status (ground truth). In vivo: fluorescent fiducials were inserted under ultrasound guidance in the kidney of one pig, followed by a CT scan. The FEM-based virtual model was superimposed on laparoscopic images by automatic registration of the fiducials. Biomechanical models were successfully generated and accurately superimposed on optical images. The mean measured distance between the estimated tumor by biomechanical propagation and the scanned tumor (ground truth) was 0.84 ± 0.42 mm. All fiducials were successfully placed in in vivo kidney and well visualized in near-infrared mode enabling accurate automatic registration of the virtual model on the laparoscopic images. Our preliminary experiments showed the potential of a biomechanical model with fluorescent

A New Multiobjective Evolutionary Algorithm for Community Detection in Dynamic Complex Networks

Directory of Open Access Journals (Sweden)

Guoqiang Chen

2013-01-01

Full Text Available Community detection in dynamic networks is an important research topic and has received an enormous amount of attention in recent years. Modularity is selected as a measure to quantify the quality of the community partition in previous detection methods. But, the modularity has been exposed to resolution limits. In this paper, we propose a novel multiobjective evolutionary algorithm for dynamic networks community detection based on the framework of nondominated sorting genetic algorithm. Modularity density which can address the limitations of modularity function is adopted to measure the snapshot cost, and normalized mutual information is selected to measure temporal cost, respectively. The characteristics knowledge of the problem is used in designing the genetic operators. Furthermore, a local search operator was designed, which can improve the effectiveness and efficiency of community detection. Experimental studies based on synthetic datasets show that the proposed algorithm can obtain better performance than the compared algorithms.

Change detection using landsat time series: A review of frequencies, preprocessing, algorithms, and applications

Science.gov (United States)

Zhu, Zhe

2017-08-01

The free and open access to all archived Landsat images in 2008 has completely changed the way of using Landsat data. Many novel change detection algorithms based on Landsat time series have been developed We present a comprehensive review of four important aspects of change detection studies based on Landsat time series, including frequencies, preprocessing, algorithms, and applications. We observed the trend that the more recent the study, the higher the frequency of Landsat time series used. We reviewed a series of image preprocessing steps, including atmospheric correction, cloud and cloud shadow detection, and composite/fusion/metrics techniques. We divided all change detection algorithms into six categories, including thresholding, differencing, segmentation, trajectory classification, statistical boundary, and regression. Within each category, six major characteristics of different algorithms, such as frequency, change index, univariate/multivariate, online/offline, abrupt/gradual change, and sub-pixel/pixel/spatial were analyzed. Moreover, some of the widely-used change detection algorithms were also discussed. Finally, we reviewed different change detection applications by dividing these applications into two categories, change target and change agent detection.

Fiducial-based monocular 3D displacement measurement of breakwater armour unit models.

CSIR Research Space (South Africa)

Vieira, R

2008-11-01

Full Text Available This paper presents a fiducial-based approach to monitoring the movement of breakwater armour units in a model hall environment. Target symbols with known dimensions are attached to the physical models, allowing the recovery of three...

Modified automatic R-peak detection algorithm for patients with epilepsy using a portable electrocardiogram recorder.

Science.gov (United States)

Jeppesen, J; Beniczky, S; Fuglsang Frederiksen, A; Sidenius, P; Johansen, P

2017-07-01

Earlier studies have shown that short term heart rate variability (HRV) analysis of ECG seems promising for detection of epileptic seizures. A precise and accurate automatic R-peak detection algorithm is a necessity in a real-time, continuous measurement of HRV, in a portable ECG device. We used the portable CE marked ePatch® heart monitor to record the ECG of 14 patients, who were enrolled in the videoEEG long term monitoring unit for clinical workup of epilepsy. Recordings of the first 7 patients were used as training set of data for the R-peak detection algorithm and the recordings of the last 7 patients (467.6 recording hours) were used to test the performance of the algorithm. We aimed to modify an existing QRS-detection algorithm to a more precise R-peak detection algorithm to avoid the possible jitter Qand S-peaks can create in the tachogram, which causes error in short-term HRVanalysis. The proposed R-peak detection algorithm showed a high sensitivity (Se = 99.979%) and positive predictive value (P+ = 99.976%), which was comparable with a previously published QRS-detection algorithm for the ePatch® ECG device, when testing the same dataset. The novel R-peak detection algorithm designed to avoid jitter has very high sensitivity and specificity and thus is a suitable tool for a robust, fast, real-time HRV-analysis in patients with epilepsy, creating the possibility for real-time seizure detection for these patients.

New algorithm to detect modules in a fault tree for a PSA

International Nuclear Information System (INIS)

Jung, Woo Sik

2015-01-01

A module or independent subtree is a part of a fault tree whose child gates or basic events are not repeated in the remaining part of the fault tree. Modules are necessarily employed in order to reduce the computational costs of fault tree quantification. This paper presents a new linear time algorithm to detect modules of large fault trees. The size of cut sets can be substantially reduced by replacing independent subtrees in a fault tree with super-components. Chatterjee and Birnbaum developed properties of modules, and demonstrated their use in the fault tree analysis. Locks expanded the concept of modules to non-coherent fault trees. Independent subtrees were manually identified while coding a fault tree for computer analysis. However, nowadays, the independent subtrees are automatically identified by the fault tree solver. A Dutuit and Rauzy (DR) algorithm to detect modules of a fault tree for coherent or non-coherent fault tree was proposed in 1996. It has been well known that this algorithm quickly detects modules since it is a linear time algorithm. The new algorithm minimizes computational memory and quickly detects modules. Furthermore, it can be easily implemented into industry fault tree solvers that are based on traditional Boolean algebra, binary decision diagrams (BDDs), or Zero-suppressed BDDs. The new algorithm employs only two scalar variables in Eqs. to that are volatile information. After finishing the traversal and module detection of each node, the volatile information is destroyed. Thus, the new algorithm does not employ any other additional computational memory and operations. It is recommended that this method be implemented into fault tree solvers for efficient probabilistic safety assessment (PSA) of nuclear power plants

New algorithm to detect modules in a fault tree for a PSA

Energy Technology Data Exchange (ETDEWEB)

Jung, Woo Sik [Sejong University, Seoul (Korea, Republic of)

2015-05-15

A module or independent subtree is a part of a fault tree whose child gates or basic events are not repeated in the remaining part of the fault tree. Modules are necessarily employed in order to reduce the computational costs of fault tree quantification. This paper presents a new linear time algorithm to detect modules of large fault trees. The size of cut sets can be substantially reduced by replacing independent subtrees in a fault tree with super-components. Chatterjee and Birnbaum developed properties of modules, and demonstrated their use in the fault tree analysis. Locks expanded the concept of modules to non-coherent fault trees. Independent subtrees were manually identified while coding a fault tree for computer analysis. However, nowadays, the independent subtrees are automatically identified by the fault tree solver. A Dutuit and Rauzy (DR) algorithm to detect modules of a fault tree for coherent or non-coherent fault tree was proposed in 1996. It has been well known that this algorithm quickly detects modules since it is a linear time algorithm. The new algorithm minimizes computational memory and quickly detects modules. Furthermore, it can be easily implemented into industry fault tree solvers that are based on traditional Boolean algebra, binary decision diagrams (BDDs), or Zero-suppressed BDDs. The new algorithm employs only two scalar variables in Eqs. to that are volatile information. After finishing the traversal and module detection of each node, the volatile information is destroyed. Thus, the new algorithm does not employ any other additional computational memory and operations. It is recommended that this method be implemented into fault tree solvers for efficient probabilistic safety assessment (PSA) of nuclear power plants.

Radiation anomaly detection algorithms for field-acquired gamma energy spectra

Science.gov (United States)

Mukhopadhyay, Sanjoy; Maurer, Richard; Wolff, Ron; Guss, Paul; Mitchell, Stephen

2015-08-01

The Remote Sensing Laboratory (RSL) is developing a tactical, networked radiation detection system that will be agile, reconfigurable, and capable of rapid threat assessment with high degree of fidelity and certainty. Our design is driven by the needs of users such as law enforcement personnel who must make decisions by evaluating threat signatures in urban settings. The most efficient tool available to identify the nature of the threat object is real-time gamma spectroscopic analysis, as it is fast and has a very low probability of producing false positive alarm conditions. Urban radiological searches are inherently challenged by the rapid and large spatial variation of background gamma radiation, the presence of benign radioactive materials in terms of the normally occurring radioactive materials (NORM), and shielded and/or masked threat sources. Multiple spectral anomaly detection algorithms have been developed by national laboratories and commercial vendors. For example, the Gamma Detector Response and Analysis Software (GADRAS) a one-dimensional deterministic radiation transport software capable of calculating gamma ray spectra using physics-based detector response functions was developed at Sandia National Laboratories. The nuisance-rejection spectral comparison ratio anomaly detection algorithm (or NSCRAD), developed at Pacific Northwest National Laboratory, uses spectral comparison ratios to detect deviation from benign medical and NORM radiation source and can work in spite of strong presence of NORM and or medical sources. RSL has developed its own wavelet-based gamma energy spectral anomaly detection algorithm called WAVRAD. Test results and relative merits of these different algorithms will be discussed and demonstrated.

Anomaly Detection and Diagnosis Algorithms for Discrete Symbols

Data.gov (United States)

National Aeronautics and Space Administration — We present a set of novel algorithms which we call sequenceMiner that detect and characterize anomalies in large sets of high-dimensional symbol sequences that arise...

Linear segmentation algorithm for detecting layer boundary with lidar.

Science.gov (United States)

Mao, Feiyue; Gong, Wei; Logan, Timothy

2013-11-04

The automatic detection of aerosol- and cloud-layer boundary (base and top) is important in atmospheric lidar data processing, because the boundary information is not only useful for environment and climate studies, but can also be used as input for further data processing. Previous methods have demonstrated limitations in defining the base and top, window-size setting, and have neglected the in-layer attenuation. To overcome these limitations, we present a new layer detection scheme for up-looking lidars based on linear segmentation with a reasonable threshold setting, boundary selecting, and false positive removing strategies. Preliminary results from both real and simulated data show that this algorithm cannot only detect the layer-base as accurate as the simple multi-scale method, but can also detect the layer-top more accurately than that of the simple multi-scale method. Our algorithm can be directly applied to uncalibrated data without requiring any additional measurements or window size selections.

MR-guided stereotactic neurosurgery-comparison of fiducial-based and anatomical landmark transformation approaches

International Nuclear Information System (INIS)

Hunsche, S; Sauner, D; Maarouf, M; Hoevels, M; Luyken, K; Schulte, O; Lackner, K; Sturm, V; Treuer, H

2004-01-01

For application in magnetic resonance (MR) guided stereotactic neurosurgery, two methods for transformation of MR-image coordinates in stereotactic, frame-based coordinates exist: the direct stereotactic fiducial-based transformation method and the indirect anatomical landmark method. In contrast to direct stereotactic MR transformation, indirect transformation is based on anatomical landmark coregistration of stereotactic computerized tomography and non-stereotactic MR images. In a patient study, both transformation methods have been investigated with visual inspection and mutual information analysis. Comparison was done for our standard imaging protocol, including t2-weighted spin-echo as well as contrast enhanced t1-weighted gradient-echo imaging. For t2-weighted spin-echo imaging, both methods showed almost similar and satisfying performance with a small, but significant advantage for fiducial-based transformation. In contrast, for t1-weighted gradient-echo imaging with more geometric distortions due to field inhomogenities and gradient nonlinearity than t2-weighted spin-echo imaging, mainly caused by a reduced bandwidth per pixel, anatomical landmark transformation delivered markedly better results. Here, fiducial-based transformation yielded results which are intolerable for stereotactic neurosurgery. Mean Euclidian distances between both transformation methods were 0.96 mm for t2-weighted spin-echo and 1.67 mm for t1-weighted gradient-echo imaging. Maximum deviations were 1.72 mm and 3.06 mm, respectively

MR-guided stereotactic neurosurgery-comparison of fiducial-based and anatomical landmark transformation approaches

Energy Technology Data Exchange (ETDEWEB)

Hunsche, S [Department of Stereotaxy and Functional Neurosurgery, University of Cologne, Cologne (Germany); Sauner, D [Institute for Diagnostic and Interventional Radiology, Friedrich-Schiller-University of Jena, Jena (Germany); Maarouf, M [Department of Stereotaxy and Functional Neurosurgery, University of Cologne, Cologne (Germany); Hoevels, M [Department of Stereotaxy and Functional Neurosurgery, University of Cologne, Cologne (Germany); Luyken, K [Department of Stereotaxy and Functional Neurosurgery, University of Cologne, Cologne (Germany); Schulte, O [Department of Radiology, University of Cologne, Cologne (Germany); Lackner, K [Department of Radiology, University of Cologne, Cologne (Germany); Sturm, V [Department of Stereotaxy and Functional Neurosurgery, University of Cologne, Cologne (Germany); Treuer, H [Department of Stereotaxy and Functional Neurosurgery, University of Cologne, Cologne (Germany)

2004-06-21

For application in magnetic resonance (MR) guided stereotactic neurosurgery, two methods for transformation of MR-image coordinates in stereotactic, frame-based coordinates exist: the direct stereotactic fiducial-based transformation method and the indirect anatomical landmark method. In contrast to direct stereotactic MR transformation, indirect transformation is based on anatomical landmark coregistration of stereotactic computerized tomography and non-stereotactic MR images. In a patient study, both transformation methods have been investigated with visual inspection and mutual information analysis. Comparison was done for our standard imaging protocol, including t2-weighted spin-echo as well as contrast enhanced t1-weighted gradient-echo imaging. For t2-weighted spin-echo imaging, both methods showed almost similar and satisfying performance with a small, but significant advantage for fiducial-based transformation. In contrast, for t1-weighted gradient-echo imaging with more geometric distortions due to field inhomogenities and gradient nonlinearity than t2-weighted spin-echo imaging, mainly caused by a reduced bandwidth per pixel, anatomical landmark transformation delivered markedly better results. Here, fiducial-based transformation yielded results which are intolerable for stereotactic neurosurgery. Mean Euclidian distances between both transformation methods were 0.96 mm for t2-weighted spin-echo and 1.67 mm for t1-weighted gradient-echo imaging. Maximum deviations were 1.72 mm and 3.06 mm, respectively.

Daily online localization using implanted fiducial markers and its impact on planning target volume for carcinoma prostate.

Science.gov (United States)

Khosa, Robin; Nangia, Sapna; Chufal, Kundan S; Ghosh, D; Kaul, Rakesh; Sharma, Lalit

2010-01-01

Aim of the study was to assess prostate motion on daily basis with respect to setup and to compare the shifts based on bony anatomy and gold fiducial markers. Gold fiducial markers were inserted in prostate under U/S guidance and daily portal images were taken and compared with digitally reconstructed images, both using bony landmarks and fiducial markers as reference. A dose of 2 MU was given for two orthogonal images daily. The mean and standard deviation of displacement using gold seeds and bone were calculated. Systematic and random errors were generated. The planning target volume (PTV) was calculated using the Van Herk formula. A total of 180 portal images from 10 patients were studied. The mean displacement along x, y and z axes was 1.67 mm, 3.58 mm, and 1.76 mm using fiducial markers and 2.12 mm, 3.47 mm, and 2.09 mm using bony landmarks, respectively. The mean internal organ motion was 1.23 mm (+1.45), 3.11 mm (+2.69 mm); and 1.87 mm (+1.67 mm) along x, y and z axes, respectively. The PTV to account for prostate motion if daily matching was not done was 4.64 mm, 10.41 mm and 4.40 mm along lateral, superoinferior, and anteroposterior directions, respectively. If bony landmarks were used for daily matching, margins of 3.61 mm, 7.31 mm, and 4.72 mm in lateral, superoinferior, and anteroposterior directions should be added to the clinical target volume. Daily alignment using gold fiducial markers is an effective method of localizing prostate displacement. It provides the option of reducing margins, thus limiting normal tissue toxicity and allowing the possibility of dose escalation for better long-term control.

Automatic tracking of implanted fiducial markers in cone beam CT projection images

International Nuclear Information System (INIS)

Marchant, T. E.; Skalski, A.; Matuszewski, B. J.

2012-01-01

Purpose: This paper describes a novel method for simultaneous intrafraction tracking of multiple fiducial markers. Although the proposed method is generic and can be adopted for a number of applications including fluoroscopy based patient position monitoring and gated radiotherapy, the tracking results presented in this paper are specific to tracking fiducial markers in a sequence of cone beam CT projection images. Methods: The proposed method is accurate and robust thanks to utilizing the mean shift and random sampling principles, respectively. The performance of the proposed method was evaluated with qualitative and quantitative methods, using data from two pancreatic and one prostate cancer patients and a moving phantom. The ground truth, for quantitative evaluation, was calculated based on manual tracking preformed by three observers. Results: The average dispersion of marker position error calculated from the tracking results for pancreas data (six markers tracked over 640 frames, 3840 marker identifications) was 0.25 mm (at iscoenter), compared with an average dispersion for the manual ground truth estimated at 0.22 mm. For prostate data (three markers tracked over 366 frames, 1098 marker identifications), the average error was 0.34 mm. The estimated tracking error in the pancreas data was < 1 mm (2 pixels) in 97.6% of cases where nearby image clutter was detected and in 100.0% of cases with no nearby image clutter. Conclusions: The proposed method has accuracy comparable to that of manual tracking and, in combination with the proposed batch postprocessing, superior robustness. Marker tracking in cone beam CT (CBCT) projections is useful for a variety of purposes, such as providing data for assessment of intrafraction motion, target tracking during rotational treatment delivery, motion correction of CBCT, and phase sorting for 4D CBCT.

An Overlapping Communities Detection Algorithm via Maxing Modularity in Opportunistic Networks

Directory of Open Access Journals (Sweden)

Gao Zhi-Peng

2016-01-01

Full Text Available Community detection in opportunistic networks has been a significant and hot issue, which is used to understand characteristics of networks through analyzing structure of it. Community is used to represent a group of nodes in a network where nodes inside the community have more internal connections than external connections. However, most of the existing community detection algorithms focus on binary networks or disjoint community detection. In this paper, we propose a novel algorithm via maxing modularity of communities (MMCto find overlapping community structure in opportunistic networks. It utilizes contact history of nodes to calculate the relation intensity between nodes. It finds nodes with high relation intensity as the initial community and extend the community with nodes of higher belong degree. The algorithm achieves a rapid and efficient overlapping community detection method by maxing the modularity of community continuously. The experiments prove that MMC is effective for uncovering overlapping communities and it achieves better performance than COPRA and Conductance.

Penalty dynamic programming algorithm for dim targets detection in sensor systems.

Science.gov (United States)

Huang, Dayu; Xue, Anke; Guo, Yunfei

2012-01-01

In order to detect and track multiple maneuvering dim targets in sensor systems, an improved dynamic programming track-before-detect algorithm (DP-TBD) called penalty DP-TBD (PDP-TBD) is proposed. The performances of tracking techniques are used as a feedback to the detection part. The feedback is constructed by a penalty term in the merit function, and the penalty term is a function of the possible target state estimation, which can be obtained by the tracking methods. With this feedback, the algorithm combines traditional tracking techniques with DP-TBD and it can be applied to simultaneously detect and track maneuvering dim targets. Meanwhile, a reasonable constraint that a sensor measurement can originate from one target or clutter is proposed to minimize track separation. Thus, the algorithm can be used in the multi-target situation with unknown target numbers. The efficiency and advantages of PDP-TBD compared with two existing methods are demonstrated by several simulations.

Penalty Dynamic Programming Algorithm for Dim Targets Detection in Sensor Systems

Directory of Open Access Journals (Sweden)

Yunfei Guo

2012-04-01

Full Text Available In order to detect and track multiple maneuvering dim targets in sensor systems, an improved dynamic programming track-before-detect algorithm (DP-TBD called penalty DP-TBD (PDP-TBD is proposed. The performances of tracking techniques are used as a feedback to the detection part. The feedback is constructed by a penalty term in the merit function, and the penalty term is a function of the possible target state estimation, which can be obtained by the tracking methods. With this feedback, the algorithm combines traditional tracking techniques with DP-TBD and it can be applied to simultaneously detect and track maneuvering dim targets. Meanwhile, a reasonable constraint that a sensor measurement can originate from one target or clutter is proposed to minimize track separation. Thus, the algorithm can be used in the multi-target situation with unknown target numbers. The efficiency and advantages of PDP-TBD compared with two existing methods are demonstrated by several simulations.

Characterization of Target Volume Changes During Breast Radiotherapy Using Implanted Fiducial Markers and Portal Imaging

International Nuclear Information System (INIS)

Harris, Emma J.; Donovan, Ellen M.; Yarnold, John R.; Coles, Charlotte E.; Evans, Philip M.

2009-01-01

Purpose: To determine target volume changes by using volume and shape analysis for patients receiving radiotherapy after breast conservation surgery and to compare different methods of automatically identifying changes in target volume, position, size, and shape during radiotherapy for use in adaptive radiotherapy. Methods and Materials: Eleven patients undergoing whole breast radiotherapy had fiducial markers sutured into the excision cavity at the time of surgery. Patients underwent imaging using computed tomography (for planning and at the end of treatment) and during treatment by using portal imaging. A marker volume (MV) was defined by using the measured marker positions. Changes in both individual marker positions and MVs were identified manually and using six automated similarity indices. Comparison of the two types of analysis (manual and automated) was undertaken to establish whether similarity indices can be used to automatically detect changes in target volumes. Results: Manual analysis showed that 3 patients had significant MV reduction. This analysis also showed significant changes between planning computed tomography and the start of treatment for 9 patients, including single and multiple marker movement, deformation (shape change), and rotation. Four of the six similarity indices were shown to be sensitive to the observed changes. Conclusions: Significant changes in size, shape, and position occur to the fiducial marker-defined volume. Four similarity indices can be used to identify these changes, and a protocol for their use in adaptive radiotherapy is suggested

Low power multi-camera system and algorithms for automated threat detection

Science.gov (United States)

Huber, David J.; Khosla, Deepak; Chen, Yang; Van Buer, Darrel J.; Martin, Kevin

2013-05-01

A key to any robust automated surveillance system is continuous, wide field-of-view sensor coverage and high accuracy target detection algorithms. Newer systems typically employ an array of multiple fixed cameras that provide individual data streams, each of which is managed by its own processor. This array can continuously capture the entire field of view, but collecting all the data and back-end detection algorithm consumes additional power and increases the size, weight, and power (SWaP) of the package. This is often unacceptable, as many potential surveillance applications have strict system SWaP requirements. This paper describes a wide field-of-view video system that employs multiple fixed cameras and exhibits low SWaP without compromising the target detection rate. We cycle through the sensors, fetch a fixed number of frames, and process them through a modified target detection algorithm. During this time, the other sensors remain powered-down, which reduces the required hardware and power consumption of the system. We show that the resulting gaps in coverage and irregular frame rate do not affect the detection accuracy of the underlying algorithms. This reduces the power of an N-camera system by up to approximately N-fold compared to the baseline normal operation. This work was applied to Phase 2 of DARPA Cognitive Technology Threat Warning System (CT2WS) program and used during field testing.

Algorithms for the detection of chewing behavior in dietary monitoring applications

Science.gov (United States)

Schmalz, Mark S.; Helal, Abdelsalam; Mendez-Vasquez, Andres

2009-08-01

The detection of food consumption is key to the implementation of successful behavior modification in support of dietary monitoring and therapy, for example, during the course of controlling obesity, diabetes, or cardiovascular disease. Since the vast majority of humans consume food via mastication (chewing), we have designed an algorithm that automatically detects chewing behaviors in surveillance video of a person eating. Our algorithm first detects the mouth region, then computes the spatiotemporal frequency spectrum of a small perioral region (including the mouth). Spectral data are analyzed to determine the presence of periodic motion that characterizes chewing. A classifier is then applied to discriminate different types of chewing behaviors. Our algorithm was tested on seven volunteers, whose behaviors included chewing with mouth open, chewing with mouth closed, talking, static face presentation (control case), and moving face presentation. Early test results show that the chewing behaviors induce a temporal frequency peak at 0.5Hz to 2.5Hz, which is readily detected using a distance-based classifier. Computational cost is analyzed for implementation on embedded processing nodes, for example, in a healthcare sensor network. Complexity analysis emphasizes the relationship between the work and space estimates of the algorithm, and its estimated error. It is shown that chewing detection is possible within a computationally efficient, accurate, and subject-independent framework.

Intraprostatic fiducials for image guidance: Workflow implications in a single linac department

International Nuclear Information System (INIS)

Middleton, Mark; See, Andrew; Rolfo, Aldo; Medwell, Steve; Joon, Michael Lim; Joon, Daryl Lim; Martin, Jarad; Khoo, Vincent

2008-01-01

Purpose: To assess the accuracy and implications on workflow of an online correction electronic portal imaging (EPI) protocol utilising bony anatomy in the online environment and an assessment of three implanted gold seed fiducial markers in the offline environment. This paper summarises an initial trial to establish the range of systematic and random errors present in patient set-up for both bony anatomy and fiducial markers, and to calculate optimal clinical target volume (CTV) to planning target volume (PTV) margins. The impact of the introduction of such a technique was also assessed in terms of impact on workflow and resource management in a single machine unit (SMU). Methods and materials: Pre treatment electronic portal images (EPIs) were acquired and bony anatomy was matched with CT derived digitally reconstructed radiographs (DRRs). Intervention in field placement was made if field placement fell outside the range of 4 mm on any of the orthogonal axes. In the offline environment the position of the implanted gold seed fiducials was aligned with that of the DRRs. An analysis of set-up error, total error and internal organ motion was then undertaken, with full statistical analysis of systematic and random errors. Results: Eleven patients completed treatment as specified, with 1006 EPIs available for analysis. Treatment times were in the order of 10.4 min. Set-up errors were in the order of 2.7 mm right-left, 2.4 mm sup-inf and 1.6 mm ant-pst. These were reduced to 1.2 mm, 0.7 mm and 0.9 mm respectively utilising an online correction protocol. However there was minimal impact on total error and internal organ motion. Using the data obtained in both the online and offline environments optimal CTV-PTV margins were calculated for correcting to bone, correcting to gold seed fiducials and also the possibility of EPI malfunction. Conclusions: Daily targeting of the prostate is both technically feasible and can be carried out in an efficient and accurate manner. An

A Greedy Algorithm for Neighborhood Overlap-Based Community Detection

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Natarajan Meghanathan

2016-01-01

Full Text Available The neighborhood overlap (NOVER of an edge u-v is defined as the ratio of the number of nodes who are neighbors for both u and v to that of the number of nodes who are neighbors of at least u or v. In this paper, we hypothesize that an edge u-v with a lower NOVER score bridges two or more sets of vertices, with very few edges (other than u-v connecting vertices from one set to another set. Accordingly, we propose a greedy algorithm of iteratively removing the edges of a network in the increasing order of their neighborhood overlap and calculating the modularity score of the resulting network component(s after the removal of each edge. The network component(s that have the largest cumulative modularity score are identified as the different communities of the network. We evaluate the performance of the proposed NOVER-based community detection algorithm on nine real-world network graphs and compare the performance against the multi-level aggregation-based Louvain algorithm, as well as the original and time-efficient versions of the edge betweenness-based Girvan-Newman (GN community detection algorithm.

Computerized detection of masses on mammograms: A comparative study of two algorithms

International Nuclear Information System (INIS)

Tiedeu, A.; Kom, G.; Kom, M.

2007-02-01

In this paper, we implement and carry out the comparison of two methods of computer-aided-detection of masses on mammograms. The two algorithms basically consist of 3 steps each: segmentation, binarization and noise suppression but using different techniques for each step. A database of 60 images was used to compare the performance of the two algorithms in terms of general detection efficiency, conservation of size and shape of detected masses. (author)

Optimization of an Accelerometer and Gyroscope-Based Fall Detection Algorithm

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Quoc T. Huynh

2015-01-01

Full Text Available Falling is a common and significant cause of injury in elderly adults (>65 yrs old, often leading to disability and death. In the USA, one in three of the elderly suffers from fall injuries annually. This study’s purpose is to develop, optimize, and assess the efficacy of a falls detection algorithm based upon a wireless, wearable sensor system (WSS comprised of a 3-axis accelerometer and gyroscope. For this study, the WSS is placed at the chest center to collect real-time motion data of various simulated daily activities (i.e., walking, running, stepping, and falling. Tests were conducted on 36 human subjects with a total of 702 different movements collected in a laboratory setting. Half of the dataset was used for development of the fall detection algorithm including investigations of critical sensor thresholds and the remaining dataset was used for assessment of algorithm sensitivity and specificity. Experimental results show that the algorithm detects falls compared to other daily movements with a sensitivity and specificity of 96.3% and 96.2%, respectively. The addition of gyroscope information enhances sensitivity dramatically from results in the literature as angular velocity changes provide further delineation of a fall event from other activities that may also experience high acceleration peaks.

A Hybrid Swarm Intelligence Algorithm for Intrusion Detection Using Significant Features

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P. Amudha

2015-01-01

Full Text Available Intrusion detection has become a main part of network security due to the huge number of attacks which affects the computers. This is due to the extensive growth of internet connectivity and accessibility to information systems worldwide. To deal with this problem, in this paper a hybrid algorithm is proposed to integrate Modified Artificial Bee Colony (MABC with Enhanced Particle Swarm Optimization (EPSO to predict the intrusion detection problem. The algorithms are combined together to find out better optimization results and the classification accuracies are obtained by 10-fold cross-validation method. The purpose of this paper is to select the most relevant features that can represent the pattern of the network traffic and test its effect on the success of the proposed hybrid classification algorithm. To investigate the performance of the proposed method, intrusion detection KDDCup’99 benchmark dataset from the UCI Machine Learning repository is used. The performance of the proposed method is compared with the other machine learning algorithms and found to be significantly different.

Assessment of a novel mass detection algorithm in mammograms

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Ehsan Kozegar

2013-01-01

Settings and Design: The proposed mass detector consists of two major steps. In the first step, several suspicious regions are extracted from the mammograms using an adaptive thresholding technique. In the second step, false positives originating by the previous stage are reduced by a machine learning approach. Materials and Methods: All modules of the mass detector were assessed on mini-MIAS database. In addition, the algorithm was tested on INBreast database for more validation. Results: According to FROC analysis, our mass detection algorithm outperforms other competing methods. Conclusions: We should not just insist on sensitivity in the segmentation phase because if we forgot FP rate, and our goal was just higher sensitivity, then the learning algorithm would be biased more toward false positives and the sensitivity would decrease dramatically in the false positive reduction phase. Therefore, we should consider the mass detection problem as a cost sensitive problem because misclassification costs are not the same in this type of problems.

Advanced Oil Spill Detection Algorithms For Satellite Based Maritime Environment Monitoring

Science.gov (United States)

Radius, Andrea; Azevedo, Rui; Sapage, Tania; Carmo, Paulo

2013-12-01

During the last years, the increasing pollution occurrence and the alarming deterioration of the environmental health conditions of the sea, lead to the need of global monitoring capabilities, namely for marine environment management in terms of oil spill detection and indication of the suspected polluter. The sensitivity of Synthetic Aperture Radar (SAR) to the different phenomena on the sea, especially for oil spill and vessel detection, makes it a key instrument for global pollution monitoring. The SAR performances in maritime pollution monitoring are being operationally explored by a set of service providers on behalf of the European Maritime Safety Agency (EMSA), which has launched in 2007 the CleanSeaNet (CSN) project - a pan-European satellite based oil monitoring service. EDISOFT, which is from the beginning a service provider for CSN, is continuously investing in R&D activities that will ultimately lead to better algorithms and better performance on oil spill detection from SAR imagery. This strategy is being pursued through EDISOFT participation in the FP7 EC Sea-U project and in the Automatic Oil Spill Detection (AOSD) ESA project. The Sea-U project has the aim to improve the current state of oil spill detection algorithms, through the informative content maximization obtained with data fusion, the exploitation of different type of data/ sensors and the development of advanced image processing, segmentation and classification techniques. The AOSD project is closely related to the operational segment, because it is focused on the automation of the oil spill detection processing chain, integrating auxiliary data, like wind information, together with image and geometry analysis techniques. The synergy between these different objectives (R&D versus operational) allowed EDISOFT to develop oil spill detection software, that combines the operational automatic aspect, obtained through dedicated integration of the processing chain in the existing open source NEST

Comparison of prostate set-up accuracy and margins with off-line bony anatomy corrections and online implanted fiducial-based corrections.

Science.gov (United States)

Greer, P B; Dahl, K; Ebert, M A; Wratten, C; White, M; Denham, J W

2008-10-01

The aim of the study was to determine prostate set-up accuracy and set-up margins with off-line bony anatomy-based imaging protocols, compared with online implanted fiducial marker-based imaging with daily corrections. Eleven patients were treated with implanted prostate fiducial markers and online set-up corrections. Pretreatment orthogonal electronic portal images were acquired to determine couch shifts and verification images were acquired during treatment to measure residual set-up error. The prostate set-up errors that would result from skin marker set-up, off-line bony anatomy-based protocols and online fiducial marker-based corrections were determined. Set-up margins were calculated for each set-up technique using the percentage of encompassed isocentres and a margin recipe. The prostate systematic set-up errors in the medial-lateral, superior-inferior and anterior-posterior directions for skin marker set-up were 2.2, 3.6 and 4.5 mm (1 standard deviation). For our bony anatomy-based off-line protocol the prostate systematic set-up errors were 1.6, 2.5 and 4.4 mm. For the online fiducial based set-up the results were 0.5, 1.4 and 1.4 mm. A prostate systematic error of 10.2 mm was uncorrected by the off-line bone protocol in one patient. Set-up margins calculated to encompass 98% of prostate set-up shifts were 11-14 mm with bone off-line set-up and 4-7 mm with online fiducial markers. Margins from the van Herk margin recipe were generally 1-2 mm smaller. Bony anatomy-based set-up protocols improve the group prostate set-up error compared with skin marks; however, large prostate systematic errors can remain undetected or systematic errors increased for individual patients. The margin required for set-up errors was found to be 10-15 mm unless implanted fiducial markers are available for treatment guidance.

Aircraft target detection algorithm based on high resolution spaceborne SAR imagery

Science.gov (United States)

Zhang, Hui; Hao, Mengxi; Zhang, Cong; Su, Xiaojing

2018-03-01

In this paper, an image classification algorithm for airport area is proposed, which based on the statistical features of synthetic aperture radar (SAR) images and the spatial information of pixels. The algorithm combines Gamma mixture model and MRF. The algorithm using Gamma mixture model to obtain the initial classification result. Pixel space correlation based on the classification results are optimized by the MRF technique. Additionally, morphology methods are employed to extract airport (ROI) region where the suspected aircraft target samples are clarified to reduce the false alarm and increase the detection performance. Finally, this paper presents the plane target detection, which have been verified by simulation test.

Anomaly detection in wide area network mesh using two machine learning anomaly detection algorithms

OpenAIRE

Zhang, James; Vukotic, Ilija; Gardner, Robert

2018-01-01

Anomaly detection is the practice of identifying items or events that do not conform to an expected behavior or do not correlate with other items in a dataset. It has previously been applied to areas such as intrusion detection, system health monitoring, and fraud detection in credit card transactions. In this paper, we describe a new method for detecting anomalous behavior over network performance data, gathered by perfSONAR, using two machine learning algorithms: Boosted Decision Trees (BDT...

Algorithm for detection of the broken phase conductor in the radial networks

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Ostojić Mladen M.

2016-01-01

Full Text Available The paper presents an algorithm for a directional relay to be used for a detection of the broken phase conductor in the radial networks. The algorithm would use synchronized voltages, measured at the beginning and at the end of the line, as input signals. During the process, the measured voltages would be phase-compared. On the basis of the normalized energy, the direction of the phase conductor, with a broken point, would be detected. Software tool Matlab/Simulink package has developed a radial network model which simulates the broken phase conductor. The simulations generated required input signals by which the algorithm was tested. Development of the algorithm along with the formation of the simulation model and the test results of the proposed algorithm are presented in this paper.

An improved algorithm of laser spot center detection in strong noise background

Science.gov (United States)

Zhang, Le; Wang, Qianqian; Cui, Xutai; Zhao, Yu; Peng, Zhong

2018-01-01

Laser spot center detection is demanded in many applications. The common algorithms for laser spot center detection such as centroid and Hough transform method have poor anti-interference ability and low detection accuracy in the condition of strong background noise. In this paper, firstly, the median filtering was used to remove the noise while preserving the edge details of the image. Secondly, the binarization of the laser facula image was carried out to extract target image from background. Then the morphological filtering was performed to eliminate the noise points inside and outside the spot. At last, the edge of pretreated facula image was extracted and the laser spot center was obtained by using the circle fitting method. In the foundation of the circle fitting algorithm, the improved algorithm added median filtering, morphological filtering and other processing methods. This method could effectively filter background noise through theoretical analysis and experimental verification, which enhanced the anti-interference ability of laser spot center detection and also improved the detection accuracy.

Evaluation of Face Detection Algorithms for the Bank Client Identity Verification

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Szczodrak Maciej

2017-06-01

Full Text Available Results of investigation of face detection algorithms efficiency in the banking client visual verification system are presented. The video recordings were made in real conditions met in three bank operating outlets employing a miniature industrial USB camera. The aim of the experiments was to check the practical usability of the face detection method in the biometric bank client verification system. The main assumption was to provide a simplified as much as possible user interaction with the application. Applied algorithms for face detection are described and achieved results of face detection in the real bank environment conditions are presented. Practical limitations of the application based on encountered problems are discussed.

BioXmark for high-precision radiotherapy in an orthotopic pancreatic tumor mouse model. Experiences with a liquid fiducial marker

International Nuclear Information System (INIS)

Dobiasch, S.; Kampfer, S.; Burkhardt, R.; Wilkens, J.J.; Schilling, D.; Schmid, T.E.; Combs, S.E.

2017-01-01

High-precision radiotherapy (RT) requires precise positioning, particularly with high single doses. Fiducial markers in combination with onboard imaging are excellent tools to support this. The purpose of this study is to establish a pancreatic cancer mouse model for high-precision image-guided RT (IGRT) using the liquid fiducial marker BioXmark (Nanovi, Kongens Lyngby, Denmark). In an animal-based cancer model, different volumes of BioXmark (10-50 μl), application forms, and imaging modalities - cone-beam computer tomography (CBCT) incorporated in either the Small Animal Radiation Research Platform (SARRP) or the small-animal micro-CT Scanner (SkyScan; Bruker, Brussels, Belgium) - as well as subsequent RT with the SARRP system were analyzed to derive recommendations for BioXmark. Even small volumes (10 μl) of BioXmark could be detected by CBCT (SARRP and Skyscan). Larger volumes (50 μl) led to hardening artefacts. The position of BioXmark was monitored at least weekly by CBCT and was stable over 4 months. BioXmark was shown to be well tolerated; no changes in physical condition or toxic side effects were observed in comparison to control mice. BioXmark enabled an exact fusion with the original treatment plan with less hardening artefacts, and minimized the application of contrast agent for fractionated RT. An orthotopic pancreatic tumor mouse model was established for high-precision IGRT using a fiducial marker. BioXmark was successfully tested and provides the perfect basis for improved imaging in high-precision RT. BioXmark enables a unique application method and optimal targeted precision in fractionated RT. Therefore, preclinical trials evaluating novel fractionation regimens and/or combination treatment with high-end RT can be performed. (orig.) [de

ASPeak: an abundance sensitive peak detection algorithm for RIP-Seq.

Science.gov (United States)

Kucukural, Alper; Özadam, Hakan; Singh, Guramrit; Moore, Melissa J; Cenik, Can

2013-10-01

Unlike DNA, RNA abundances can vary over several orders of magnitude. Thus, identification of RNA-protein binding sites from high-throughput sequencing data presents unique challenges. Although peak identification in ChIP-Seq data has been extensively explored, there are few bioinformatics tools tailored for peak calling on analogous datasets for RNA-binding proteins. Here we describe ASPeak (abundance sensitive peak detection algorithm), an implementation of an algorithm that we previously applied to detect peaks in exon junction complex RNA immunoprecipitation in tandem experiments. Our peak detection algorithm yields stringent and robust target sets enabling sensitive motif finding and downstream functional analyses. ASPeak is implemented in Perl as a complete pipeline that takes bedGraph files as input. ASPeak implementation is freely available at https://sourceforge.net/projects/as-peak under the GNU General Public License. ASPeak can be run on a personal computer, yet is designed to be easily parallelizable. ASPeak can also run on high performance computing clusters providing efficient speedup. The documentation and user manual can be obtained from http://master.dl.sourceforge.net/project/as-peak/manual.pdf.

Species-specific audio detection: a comparison of three template-based detection algorithms using random forests

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Carlos J. Corrada Bravo

2017-04-01

Full Text Available We developed a web-based cloud-hosted system that allow users to archive, listen, visualize, and annotate recordings. The system also provides tools to convert these annotations into datasets that can be used to train a computer to detect the presence or absence of a species. The algorithm used by the system was selected after comparing the accuracy and efficiency of three variants of a template-based detection. The algorithm computes a similarity vector by comparing a template of a species call with time increments across the spectrogram. Statistical features are extracted from this vector and used as input for a Random Forest classifier that predicts presence or absence of the species in the recording. The fastest algorithm variant had the highest average accuracy and specificity; therefore, it was implemented in the ARBIMON web-based system.

Algorithms and data structures for automated change detection and classification of sidescan sonar imagery

Science.gov (United States)

Gendron, Marlin Lee

During Mine Warfare (MIW) operations, MIW analysts perform change detection by visually comparing historical sidescan sonar imagery (SSI) collected by a sidescan sonar with recently collected SSI in an attempt to identify objects (which might be explosive mines) placed at sea since the last time the area was surveyed. This dissertation presents a data structure and three algorithms, developed by the author, that are part of an automated change detection and classification (ACDC) system. MIW analysts at the Naval Oceanographic Office, to reduce the amount of time to perform change detection, are currently using ACDC. The dissertation introductory chapter gives background information on change detection, ACDC, and describes how SSI is produced from raw sonar data. Chapter 2 presents the author's Geospatial Bitmap (GB) data structure, which is capable of storing information geographically and is utilized by the three algorithms. This chapter shows that a GB data structure used in a polygon-smoothing algorithm ran between 1.3--48.4x faster than a sparse matrix data structure. Chapter 3 describes the GB clustering algorithm, which is the author's repeatable, order-independent method for clustering. Results from tests performed in this chapter show that the time to cluster a set of points is not affected by the distribution or the order of the points. In Chapter 4, the author presents his real-time computer-aided detection (CAD) algorithm that automatically detects mine-like objects on the seafloor in SSI. The author ran his GB-based CAD algorithm on real SSI data, and results of these tests indicate that his real-time CAD algorithm performs comparably to or better than other non-real-time CAD algorithms. The author presents his computer-aided search (CAS) algorithm in Chapter 5. CAS helps MIW analysts locate mine-like features that are geospatially close to previously detected features. A comparison between the CAS and a great circle distance algorithm shows that the

A Novel Algorithm for Intrusion Detection Based on RASL Model Checking

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Weijun Zhu

2013-01-01

Full Text Available The interval temporal logic (ITL model checking (MC technique enhances the power of intrusion detection systems (IDSs to detect concurrent attacks due to the strong expressive power of ITL. However, an ITL formula suffers from difficulty in the description of the time constraints between different actions in the same attack. To address this problem, we formalize a novel real-time interval temporal logic—real-time attack signature logic (RASL. Based on such a new logic, we put forward a RASL model checking algorithm. Furthermore, we use RASL formulas to describe attack signatures and employ discrete timed automata to create an audit log. As a result, RASL model checking algorithm can be used to automatically verify whether the automata satisfy the formulas, that is, whether the audit log coincides with the attack signatures. The simulation experiments show that the new approach effectively enhances the detection power of the MC-based intrusion detection methods for a number of telnet attacks, p-trace attacks, and the other sixteen types of attacks. And these experiments indicate that the new algorithm can find several types of real-time attacks, whereas the existing MC-based intrusion detection approaches cannot do that.

A Novel Online Data-Driven Algorithm for Detecting UAV Navigation Sensor Faults.

Science.gov (United States)

Sun, Rui; Cheng, Qi; Wang, Guanyu; Ochieng, Washington Yotto

2017-09-29

The use of Unmanned Aerial Vehicles (UAVs) has increased significantly in recent years. On-board integrated navigation sensors are a key component of UAVs' flight control systems and are essential for flight safety. In order to ensure flight safety, timely and effective navigation sensor fault detection capability is required. In this paper, a novel data-driven Adaptive Neuron Fuzzy Inference System (ANFIS)-based approach is presented for the detection of on-board navigation sensor faults in UAVs. Contrary to the classic UAV sensor fault detection algorithms, based on predefined or modelled faults, the proposed algorithm combines an online data training mechanism with the ANFIS-based decision system. The main advantages of this algorithm are that it allows real-time model-free residual analysis from Kalman Filter (KF) estimates and the ANFIS to build a reliable fault detection system. In addition, it allows fast and accurate detection of faults, which makes it suitable for real-time applications. Experimental results have demonstrated the effectiveness of the proposed fault detection method in terms of accuracy and misdetection rate.

A Novel Online Data-Driven Algorithm for Detecting UAV Navigation Sensor Faults

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Rui Sun

2017-09-01

Full Text Available The use of Unmanned Aerial Vehicles (UAVs has increased significantly in recent years. On-board integrated navigation sensors are a key component of UAVs’ flight control systems and are essential for flight safety. In order to ensure flight safety, timely and effective navigation sensor fault detection capability is required. In this paper, a novel data-driven Adaptive Neuron Fuzzy Inference System (ANFIS-based approach is presented for the detection of on-board navigation sensor faults in UAVs. Contrary to the classic UAV sensor fault detection algorithms, based on predefined or modelled faults, the proposed algorithm combines an online data training mechanism with the ANFIS-based decision system. The main advantages of this algorithm are that it allows real-time model-free residual analysis from Kalman Filter (KF estimates and the ANFIS to build a reliable fault detection system. In addition, it allows fast and accurate detection of faults, which makes it suitable for real-time applications. Experimental results have demonstrated the effectiveness of the proposed fault detection method in terms of accuracy and misdetection rate.

Detection of Human Impacts by an Adaptive Energy-Based Anisotropic Algorithm

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Manuel Prado-Velasco

2013-10-01

Full Text Available Boosted by health consequences and the cost of falls in the elderly, this work develops and tests a novel algorithm and methodology to detect human impacts that will act as triggers of a two-layer fall monitor. The two main requirements demanded by socio-healthcare providers—unobtrusiveness and reliability—defined the objectives of the research. We have demonstrated that a very agile, adaptive, and energy-based anisotropic algorithm can provide 100% sensitivity and 78% specificity, in the task of detecting impacts under demanding laboratory conditions. The algorithm works together with an unsupervised real-time learning technique that addresses the adaptive capability, and this is also presented. The work demonstrates the robustness and reliability of our new algorithm, which will be the basis of a smart falling monitor. This is shown in this work to underline the relevance of the results.

A matched-filter algorithm to detect amperometric spikes resulting from quantal secretion.

Science.gov (United States)

Balaji Ramachandran, Supriya; Gillis, Kevin D

2018-01-01

Electrochemical microelectrodes located immediately adjacent to the cell surface can detect spikes of amperometric current during exocytosis as the transmitter released from a single vesicle is oxidized on the electrode surface. Automated techniques to detect spikes are needed in order to quantify the spike rate as a measure of the rate of exocytosis. We have developed a Matched Filter (MF) detection algorithm that scans the data set with a library of prototype spike templates while performing a least-squares fit to determine the amplitude and standard error. The ratio of the fit amplitude to the standard error constitutes a criterion score that is assigned for each time point and for each template. A spike is detected when the criterion score exceeds a threshold and the highest-scoring template and the time of peak score is identified. The search for the next spike commences only after the score falls below a second, lower threshold to reduce false positives. The approach was extended to detect spikes with double-exponential decays with the sum of two templates. Receiver Operating Characteristic plots (ROCs) demonstrate that the algorithm detects >95% of manually identified spikes with a false-positive rate of ∼2%. ROCs demonstrate that the MF algorithm performs better than algorithms that detect spikes based on a derivative-threshold approach. The MF approach performs well and leads into approaches to identify spike parameters. Copyright © 2017 Elsevier B.V. All rights reserved.

An Automated Energy Detection Algorithm Based on Morphological Filter Processing with a Modified Watershed Transform

Science.gov (United States)

2018-01-01

ARL-TR-8270 ● JAN 2018 US Army Research Laboratory An Automated Energy Detection Algorithm Based on Morphological Filter...Automated Energy Detection Algorithm Based on Morphological Filter Processing with a Modified Watershed Transform by Kwok F Tom Sensors and Electron...1 October 2016–30 September 2017 4. TITLE AND SUBTITLE An Automated Energy Detection Algorithm Based on Morphological Filter Processing with a

Practical Algorithms for Subgroup Detection in Covert Networks

DEFF Research Database (Denmark)

Memon, Nasrullah; Wiil, Uffe Kock; Qureshi, Pir Abdul Rasool

2010-01-01

In this paper, we present algorithms for subgroup detection and demonstrated them with a real-time case study of USS Cole bombing terrorist network. The algorithms are demonstrated in an application by a prototype system. The system finds associations between terrorist and terrorist organisations...... and is capable of determining links between terrorism plots occurred in the past, their affiliation with terrorist camps, travel record, funds transfer, etc. The findings are represented by a network in the form of an Attributed Relational Graph (ARG). Paths from a node to any other node in the network indicate...

Evaluation of hybrids algorithms for mass detection in digitalized mammograms

International Nuclear Information System (INIS)

Cordero, Jose; Garzon Reyes, Johnson

2011-01-01

The breast cancer remains being a significant public health problem, the early detection of the lesions can increase the success possibilities of the medical treatments. The mammography is an image modality effective to early diagnosis of abnormalities, where the medical image is obtained of the mammary gland with X-rays of low radiation, this allows detect a tumor or circumscribed mass between two to three years before that it was clinically palpable, and is the only method that until now achieved reducing the mortality by breast cancer. In this paper three hybrids algorithms for circumscribed mass detection on digitalized mammograms are evaluated. In the first stage correspond to a review of the enhancement and segmentation techniques used in the processing of the mammographic images. After a shape filtering was applied to the resulting regions. By mean of a Bayesian filter the survivors regions were processed, where the characteristics vector for the classifier was constructed with few measurements. Later, the implemented algorithms were evaluated by ROC curves, where 40 images were taken for the test, 20 normal images and 20 images with circumscribed lesions. Finally, the advantages and disadvantages in the correct detection of a lesion of every algorithm are discussed.

Vision-based vehicle detection and tracking algorithm design

Science.gov (United States)

Hwang, Junyeon; Huh, Kunsoo; Lee, Donghwi

2009-12-01

The vision-based vehicle detection in front of an ego-vehicle is regarded as promising for driver assistance as well as for autonomous vehicle guidance. The feasibility of vehicle detection in a passenger car requires accurate and robust sensing performance. A multivehicle detection system based on stereo vision has been developed for better accuracy and robustness. This system utilizes morphological filter, feature detector, template matching, and epipolar constraint techniques in order to detect the corresponding pairs of vehicles. After the initial detection, the system executes the tracking algorithm for the vehicles. The proposed system can detect front vehicles such as the leading vehicle and side-lane vehicles. The position parameters of the vehicles located in front are obtained based on the detection information. The proposed vehicle detection system is implemented on a passenger car, and its performance is verified experimentally.

Conformal radiotherapy for prostate cancer: contribution of pelvic immobilization and new fiducial markers

International Nuclear Information System (INIS)

Garcia, R.; Oozeer, R.; Le Thanh, H.; Chauvet, B.; Toy, B.J.; Reboul, F.

1997-01-01

To reduce errors in the positioning of patients treated with external conformal radiotherapy for prostate cancer, we evaluated both the use of an immobilization device and new fiducial markers. The immobilization device consisted of an individual mold made of polyurethane foam. Two sets of skin markers located on the anterior tibial surfaces were used to identify the pelvic isocenter. The patient's position was evaluated by orthogonal port film which were then compared with the original simulation film. Results are presented with respect to orthogonal axes. Comparison with classic procedures without immobilization showed that use of the mold and new fiducial markers led to a decrease in set-up errors which were less than 5 mm. With the use of an immobilization device and optimized techniques for patients' positioning, conformal radiotherapy of prostate cancer is more accurate. (authors)

Road detection in SAR images using a tensor voting algorithm

Science.gov (United States)

Shen, Dajiang; Hu, Chun; Yang, Bing; Tian, Jinwen; Liu, Jian

2007-11-01

In this paper, the problem of the detection of road networks in Synthetic Aperture Radar (SAR) images is addressed. Most of the previous methods extract the road by detecting lines and network reconstruction. Traditional algorithms such as MRFs, GA, Level Set, used in the progress of reconstruction are iterative. The tensor voting methodology we proposed is non-iterative, and non-sensitive to initialization. Furthermore, the only free parameter is the size of the neighborhood, related to the scale. The algorithm we present is verified to be effective when it's applied to the road extraction using the real Radarsat Image.

Object Detection and Tracking using Modified Diamond Search Block Matching Motion Estimation Algorithm

Directory of Open Access Journals (Sweden)

Apurva Samdurkar

2018-06-01

Full Text Available Object tracking is one of the main fields within computer vision. Amongst various methods/ approaches for object detection and tracking, the background subtraction approach makes the detection of object easier. To the detected object, apply the proposed block matching algorithm for generating the motion vectors. The existing diamond search (DS and cross diamond search algorithms (CDS are studied and experiments are carried out on various standard video data sets and user defined data sets. Based on the study and analysis of these two existing algorithms a modified diamond search pattern (MDS algorithm is proposed using small diamond shape search pattern in initial step and large diamond shape (LDS in further steps for motion estimation. The initial search pattern consists of five points in small diamond shape pattern and gradually grows into a large diamond shape pattern, based on the point with minimum cost function. The algorithm ends with the small shape pattern at last. The proposed MDS algorithm finds the smaller motion vectors and fewer searching points than the existing DS and CDS algorithms. Further, object detection is carried out by using background subtraction approach and finally, MDS motion estimation algorithm is used for tracking the object in color video sequences. The experiments are carried out by using different video data sets containing a single object. The results are evaluated and compared by using the evaluation parameters like average searching points per frame and average computational time per frame. The experimental results show that the MDS performs better than DS and CDS on average search point and average computation time.

An evaluation of classification algorithms for intrusion detection ...

African Journals Online (AJOL)

An evaluation of classification algorithms for intrusion detection. ... Log in or Register to get access to full text downloads. ... Most of the available IDSs use all the 41 features in the network to evaluate and search for intrusive pattern in which ...

Assessment of prostatic fiducial marker introduction: patient morbidity, staff satisfaction and improved treatment field placement

International Nuclear Information System (INIS)

Brown, Simon; Lehman, Margot; Ferrari-Anderson, Janet; Glyde, Alan; Burmeister, Elizabeth; Nicol, David

2011-01-01

Increased accuracy when using fiducial markers for prostate localisation is well documented. This project aimed to establish the improvement in accuracy when using gold markers for daily prostate localisation, to assess patient satisfaction and morbidity from the transrectal implantation of gold seed markers and establish staff attitudes towards the newly introduced processes. Twenty patients with prostate cancer had three gold seeds implanted into the base, apex and central zone of the prostate transrectally using ultrasound guidance. Surveys were conducted to assess staff and patient satisfaction with the process of gold seed localisation. The gold markers were used to localise the prostate on a daily basis using megavoltage electronic portal imaging. Measurements were taken to establish the increase in accuracy when using gold fiducial markers compared with using the surrounding bony anatomy. Inter-fraction motion (1 standard deviation (SD)) of the fiducial markers was 2.20, 4.28 and 4.27 mm in the LR, SI and AP directions, respectively. Intra-fraction prostate motion (1 SD) was measured as 0.8 mm LR, 1.1 mm SI and 2.0 mm AP. The patient survey showed that the insertion and associated side effects were acceptable, with 5% of patients stating that the seed insertion was worse than the prostate biopsy, and 23.1% of patients experienced short duration (1–2 days) haematuria. The staff survey showed that daily online image guidance was achievable without affecting patient throughput. Thirty percent of treatment staff believed that performing online daily localisation did not add any extra time to a standard treatment, and the remaining 70% thought that the added time was minimal (2–4 min). Gold fiducial markers are an accurate, reliable and tolerable method of daily prostate localisation.

Leakage Detection and Estimation Algorithm for Loss Reduction in Water Piping Networks

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Kazeem B. Adedeji

2017-10-01

Full Text Available Water loss through leaking pipes constitutes a major challenge to the operational service of water utilities. In recent years, increasing concern about the financial loss and environmental pollution caused by leaking pipes has been driving the development of efficient algorithms for detecting leakage in water piping networks. Water distribution networks (WDNs are disperse in nature with numerous number of nodes and branches. Consequently, identifying the segment(s of the network and the exact leaking pipelines connected to this segment(s where higher background leakage outflow occurs is a challenging task. Background leakage concerns the outflow from small cracks or deteriorated joints. In addition, because they are diffuse flow, they are not characterised by quick pressure drop and are not detectable by measuring instruments. Consequently, they go unreported for a long period of time posing a threat to water loss volume. Most of the existing research focuses on the detection and localisation of burst type leakages which are characterised by a sudden pressure drop. In this work, an algorithm for detecting and estimating background leakage in water distribution networks is presented. The algorithm integrates a leakage model into a classical WDN hydraulic model for solving the network leakage flows. The applicability of the developed algorithm is demonstrated on two different water networks. The results of the tested networks are discussed and the solutions obtained show the benefits of the proposed algorithm. A noteworthy evidence is that the algorithm permits the detection of critical segments or pipes of the network experiencing higher leakage outflow and indicates the probable pipes of the network where pressure control can be performed. However, the possible position of pressure control elements along such critical pipes will be addressed in future work.

A review of feature detection and match algorithms for localization and mapping

Science.gov (United States)

Li, Shimiao

2017-09-01

Localization and mapping is an essential ability of a robot to keep track of its own location in an unknown environment. Among existing methods for this purpose, vision-based methods are more effective solutions for being accurate, inexpensive and versatile. Vision-based methods can generally be categorized as feature-based approaches and appearance-based approaches. The feature-based approaches prove higher performance in textured scenarios. However, their performance depend highly on the applied feature-detection algorithms. In this paper, we surveyed algorithms for feature detection, which is an essential step in achieving vision-based localization and mapping. In this pater, we present mathematical models of the algorithms one after another. To compare the performances of the algorithms, we conducted a series of experiments on their accuracy, speed, scale invariance and rotation invariance. The results of the experiments showed that ORB is the fastest algorithm in detecting and matching features, the speed of which is more than 10 times that of SURF and approximately 40 times that of SIFT. And SIFT, although with no advantage in terms of speed, shows the most correct matching pairs and proves its accuracy.

Breadth-First Search-Based Single-Phase Algorithms for Bridge Detection in Wireless Sensor Networks

Science.gov (United States)

Akram, Vahid Khalilpour; Dagdeviren, Orhan

2013-01-01

Wireless sensor networks (WSNs) are promising technologies for exploring harsh environments, such as oceans, wild forests, volcanic regions and outer space. Since sensor nodes may have limited transmission range, application packets may be transmitted by multi-hop communication. Thus, connectivity is a very important issue. A bridge is a critical edge whose removal breaks the connectivity of the network. Hence, it is crucial to detect bridges and take preventions. Since sensor nodes are battery-powered, services running on nodes should consume low energy. In this paper, we propose energy-efficient and distributed bridge detection algorithms for WSNs. Our algorithms run single phase and they are integrated with the Breadth-First Search (BFS) algorithm, which is a popular routing algorithm. Our first algorithm is an extended version of Milic's algorithm, which is designed to reduce the message length. Our second algorithm is novel and uses ancestral knowledge to detect bridges. We explain the operation of the algorithms, analyze their proof of correctness, message, time, space and computational complexities. To evaluate practical importance, we provide testbed experiments and extensive simulations. We show that our proposed algorithms provide less resource consumption, and the energy savings of our algorithms are up by 5.5-times. PMID:23845930

High Precision Edge Detection Algorithm for Mechanical Parts

Science.gov (United States)

Duan, Zhenyun; Wang, Ning; Fu, Jingshun; Zhao, Wenhui; Duan, Boqiang; Zhao, Jungui

2018-04-01

High precision and high efficiency measurement is becoming an imperative requirement for a lot of mechanical parts. So in this study, a subpixel-level edge detection algorithm based on the Gaussian integral model is proposed. For this purpose, the step edge normal section line Gaussian integral model of the backlight image is constructed, combined with the point spread function and the single step model. Then gray value of discrete points on the normal section line of pixel edge is calculated by surface interpolation, and the coordinate as well as gray information affected by noise is fitted in accordance with the Gaussian integral model. Therefore, a precise location of a subpixel edge was determined by searching the mean point. Finally, a gear tooth was measured by M&M3525 gear measurement center to verify the proposed algorithm. The theoretical analysis and experimental results show that the local edge fluctuation is reduced effectively by the proposed method in comparison with the existing subpixel edge detection algorithms. The subpixel edge location accuracy and computation speed are improved. And the maximum error of gear tooth profile total deviation is 1.9 μm compared with measurement result with gear measurement center. It indicates that the method has high reliability to meet the requirement of high precision measurement.

A Self-embedding Robust Digital Watermarking Algorithm with Blind Detection

Directory of Open Access Journals (Sweden)

Gong Yunfeng

2014-08-01

Full Text Available In order to achieve the perfectly blind detection of robustness watermarking algorithm, a novel self-embedding robust digital watermarking algorithm with blind detection is proposed in this paper. Firstly the original image is divided to not overlap image blocks and then decomposable coefficients are obtained by lifting-based wavelet transform in every image blocks. Secondly the low-frequency coefficients of block images are selected and then approximately represented as a product of a base matrix and a coefficient matrix using NMF. Then the feature vector represent original image is obtained by quantizing coefficient matrix, and finally the adaptive quantization of the robustness watermark is embedded in the low-frequency coefficients of LWT. Experimental results show that the scheme is robust against common signal processing attacks, meanwhile perfect blind detection is achieve.

Multispectral fluorescence image algorithms for detection of frass on mature tomatoes

Science.gov (United States)

A multispectral algorithm derived from hyperspectral line-scan fluorescence imaging under violet LED excitation was developed for the detection of frass contamination on mature tomatoes. The algorithm utilized the fluorescence intensities at five wavebands, 515 nm, 640 nm, 664 nm, 690 nm, and 724 nm...

Clinical outcome of fiducial-less CyberKnife radiosurgery for stage I non-small cell lung cancer

International Nuclear Information System (INIS)

Jung, In Hye; Song, Si Yeol; Cho, Byung Chul; Kwak, Jung Won; Jung, Nuri Hyun; Kim, Su Ssan; Choi, Eun Kyung; Jung, Jin Hong; Je, Hyoung Uk; Choi, Won Sik

2015-01-01

To evaluate the treatment results in early stage non-small cell lung cancer patients who have undergone fiducial-less CyberKnife radiosurgery (CKRS). From June 2011 to November 2013, 58 patients underwent CKRS at Asan Medical Center for stage I lung cancer. After excluding 14 patients, we retrospectively reviewed the records of the remaining 44 patients. All analyses were performed using SPSS ver. 21. The median age at diagnosis was 75 years. Most patients had inoperable primary lung cancer with a poor pulmonary function test with comorbidity or old age. The clinical stage was IA in 30 patients (68.2%), IB in 14 (31.8%). The mean tumor size was 2.6 cm (range, 1.2 to 4.8 cm), and the tumor was smaller than 2 cm in 12 patients (27.3%). The radiation dose given was 48-60 Gy in 3-4 fractions. In a median follow-up of 23.1 months, local recurrence occurred in three patients (2-year local recurrence-free survival rate, 90.4%) and distant metastasis occurred in 13 patients. All patients tolerated the radiosurgery well, only two patients developing grade 3 dyspnea. The most common complications were radiation-induced fibrosis and pneumonitis. Eight patients died due to cancer progression. The results showed that fiducial-less CKRS shows comparable local tumor control and survival rates to those of LINAC-based SABR or CKRS with a fiducial marker. Thus, fiducial-less CKRS using Xsight lung tracking system can be effectively and safely performed for patients with medically inoperable stage I non-small cell lung cancer without any risk of procedure-related complication

Clinical outcome of fiducial-less CyberKnife radiosurgery for stage I non-small cell lung cancer

Energy Technology Data Exchange (ETDEWEB)

Jung, In Hye; Song, Si Yeol; Cho, Byung Chul; Kwak, Jung Won; Jung, Nuri Hyun; Kim, Su Ssan; Choi, Eun Kyung [Dept. of Radiation Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul (Korea, Republic of); Jung, Jin Hong [Dept. of Radiation Oncology, Kyung Hee University Medical Center, Kyung Hee University School of Medicine, Seoul (Korea, Republic of); Je, Hyoung Uk [Dept. of Radiation Oncology, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan (Korea, Republic of); Choi, Won Sik [Dept. of Radiation Oncology, Gangneung Asan Hospital, Uiversity of Ulsan College of Medicine, Gangneung (Korea, Republic of)

2015-06-15

To evaluate the treatment results in early stage non-small cell lung cancer patients who have undergone fiducial-less CyberKnife radiosurgery (CKRS). From June 2011 to November 2013, 58 patients underwent CKRS at Asan Medical Center for stage I lung cancer. After excluding 14 patients, we retrospectively reviewed the records of the remaining 44 patients. All analyses were performed using SPSS ver. 21. The median age at diagnosis was 75 years. Most patients had inoperable primary lung cancer with a poor pulmonary function test with comorbidity or old age. The clinical stage was IA in 30 patients (68.2%), IB in 14 (31.8%). The mean tumor size was 2.6 cm (range, 1.2 to 4.8 cm), and the tumor was smaller than 2 cm in 12 patients (27.3%). The radiation dose given was 48-60 Gy in 3-4 fractions. In a median follow-up of 23.1 months, local recurrence occurred in three patients (2-year local recurrence-free survival rate, 90.4%) and distant metastasis occurred in 13 patients. All patients tolerated the radiosurgery well, only two patients developing grade 3 dyspnea. The most common complications were radiation-induced fibrosis and pneumonitis. Eight patients died due to cancer progression. The results showed that fiducial-less CKRS shows comparable local tumor control and survival rates to those of LINAC-based SABR or CKRS with a fiducial marker. Thus, fiducial-less CKRS using Xsight lung tracking system can be effectively and safely performed for patients with medically inoperable stage I non-small cell lung cancer without any risk of procedure-related complication.

Zero-crossing detection algorithm for arrays of optical spatial filtering velocimetry sensors

DEFF Research Database (Denmark)

Jakobsen, Michael Linde; Pedersen, Finn; Hanson, Steen Grüner

2008-01-01

This paper presents a zero-crossing detection algorithm for arrays of compact low-cost optical sensors based on spatial filtering for measuring fluctuations in angular velocity of rotating solid structures. The algorithm is applicable for signals with moderate signal-to-noise ratios, and delivers...... repeating the same measurement error for each revolution of the target, and to gain high performance measurement of angular velocity. The traditional zero-crossing detection is extended by 1) inserting an appropriate band-pass filter before the zero-crossing detection, 2) measuring time periods between zero...

Hawking, fiducial, and free-fall temperature of black hole on gravity's rainbow

Energy Technology Data Exchange (ETDEWEB)

Gim, Yongwan; Kim, Wontae [Sogang University, Department of Physics, Seoul (Korea, Republic of)

2016-03-15

On gravity's rainbow, the energy of test particles deforms the geometry of a black hole in such a way that the corresponding Hawking temperature is expected to be modified. It means that the fiducial and free-fall temperatures on the black hole background should also be modified according to deformation of the geometry. In this work, the probing energy of test particles is assumed as the average energy of the Hawking particle in order to study the particle back reaction of the geometry by using the advantage of gravity's rainbow. We shall obtain the modified fiducial and free-fall temperatures, respectively. The behaviors of these two temperatures on the horizon tell us that black hole complementarity is still well defined on gravity's rainbow. (orig.)

Generalized Confidence Intervals and Fiducial Intervals for Some Epidemiological Measures

Directory of Open Access Journals (Sweden)

Ionut Bebu

2016-06-01

Full Text Available For binary outcome data from epidemiological studies, this article investigates the interval estimation of several measures of interest in the absence or presence of categorical covariates. When covariates are present, the logistic regression model as well as the log-binomial model are investigated. The measures considered include the common odds ratio (OR from several studies, the number needed to treat (NNT, and the prevalence ratio. For each parameter, confidence intervals are constructed using the concepts of generalized pivotal quantities and fiducial quantities. Numerical results show that the confidence intervals so obtained exhibit satisfactory performance in terms of maintaining the coverage probabilities even when the sample sizes are not large. An appealing feature of the proposed solutions is that they are not based on maximization of the likelihood, and hence are free from convergence issues associated with the numerical calculation of the maximum likelihood estimators, especially in the context of the log-binomial model. The results are illustrated with a number of examples. The overall conclusion is that the proposed methodologies based on generalized pivotal quantities and fiducial quantities provide an accurate and unified approach for the interval estimation of the various epidemiological measures in the context of binary outcome data with or without covariates.

An Adaptive and Time-Efficient ECG R-Peak Detection Algorithm.

Science.gov (United States)

Qin, Qin; Li, Jianqing; Yue, Yinggao; Liu, Chengyu

2017-01-01

R-peak detection is crucial in electrocardiogram (ECG) signal analysis. This study proposed an adaptive and time-efficient R-peak detection algorithm for ECG processing. First, wavelet multiresolution analysis was applied to enhance the ECG signal representation. Then, ECG was mirrored to convert large negative R-peaks to positive ones. After that, local maximums were calculated by the first-order forward differential approach and were truncated by the amplitude and time interval thresholds to locate the R-peaks. The algorithm performances, including detection accuracy and time consumption, were tested on the MIT-BIH arrhythmia database and the QT database. Experimental results showed that the proposed algorithm achieved mean sensitivity of 99.39%, positive predictivity of 99.49%, and accuracy of 98.89% on the MIT-BIH arrhythmia database and 99.83%, 99.90%, and 99.73%, respectively, on the QT database. By processing one ECG record, the mean time consumptions were 0.872 s and 0.763 s for the MIT-BIH arrhythmia database and QT database, respectively, yielding 30.6% and 32.9% of time reduction compared to the traditional Pan-Tompkins method.

ICPD-a new peak detection algorithm for LC/MS.

Science.gov (United States)

Zhang, Jianqiu; Haskins, William

2010-12-01

The identification and quantification of proteins using label-free Liquid Chromatography/Mass Spectrometry (LC/MS) play crucial roles in biological and biomedical research. Increasing evidence has shown that biomarkers are often low abundance proteins. However, LC/MS systems are subject to considerable noise and sample variability, whose statistical characteristics are still elusive, making computational identification of low abundance proteins extremely challenging. As a result, the inability of identifying low abundance proteins in a proteomic study is the main bottleneck in protein biomarker discovery. In this paper, we propose a new peak detection method called Information Combining Peak Detection (ICPD ) for high resolution LC/MS. In LC/MS, peptides elute during a certain time period and as a result, peptide isotope patterns are registered in multiple MS scans. The key feature of the new algorithm is that the observed isotope patterns registered in multiple scans are combined together for estimating the likelihood of the peptide existence. An isotope pattern matching score based on the likelihood probability is provided and utilized for peak detection. The performance of the new algorithm is evaluated based on protein standards with 48 known proteins. The evaluation shows better peak detection accuracy for low abundance proteins than other LC/MS peak detection methods.

Daily online bony correction is required for prostate patients without fiducial markers or soft-tissue imaging.

Science.gov (United States)

Johnston, M L; Vial, P; Wiltshire, K L; Bell, L J; Blome, S; Kerestes, Z; Morgan, G W; O'Driscoll, D; Shakespeare, T P; Eade, T N

2011-09-01

To compare online position verification strategies with offline correction protocols for patients undergoing definitive prostate radiotherapy. We analysed 50 patients with implanted fiducial markers undergoing curative prostate radiation treatment, all of whom underwent daily kilovoltage imaging using an on-board imager. For each treatment, patients were set-up initially with skin tattoos and in-room lasers. Orthogonal on-board imager images were acquired and the couch shift to match both bony anatomy and the fiducial markers recorded. The set-up error using skin tattoos and offline bone correction was compared with online bone correction. The fiducial markers were used as the reference. Data from 1923 fractions were analysed. The systematic error was ≤1 mm for all protocols. The average random error was 2-3mm for online bony correction and 3-5mm for skin tattoos or offline-bone. Online-bone showed a significant improvement compared with offline-bone in the number of patients with >5mm set-up errors for >10% (P20% (Pmarkers or daily soft-tissue imaging. Copyright © 2011 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Algorithms for Anomaly Detection - Lecture 1

CERN Multimedia

CERN. Geneva

2017-01-01

The concept of statistical anomalies, or outliers, has fascinated experimentalists since the earliest attempts to interpret data. We want to know why some data points don’t seem to belong with the others: perhaps we want to eliminate spurious or unrepresentative data from our model. Or, the anomalies themselves may be what we are interested in: an outlier could represent the symptom of a disease, an attack on a computer network, a scientific discovery, or even an unfaithful partner. We start with some general considerations, such as the relationship between clustering and anomaly detection, the choice between supervised and unsupervised methods, and the difference between global and local anomalies. Then we will survey the most representative anomaly detection algorithms, highlighting what kind of data each approach is best suited to, and discussing their limitations. We will finish with a discussion of the difficulties of anomaly detection in high-dimensional data and some new directions for anomaly detec...

Algorithms for Anomaly Detection - Lecture 2

CERN Multimedia

CERN. Geneva

2017-01-01

The concept of statistical anomalies, or outliers, has fascinated experimentalists since the earliest attempts to interpret data. We want to know why some data points don’t seem to belong with the others: perhaps we want to eliminate spurious or unrepresentative data from our model. Or, the anomalies themselves may be what we are interested in: an outlier could represent the symptom of a disease, an attack on a computer network, a scientific discovery, or even an unfaithful partner. We start with some general considerations, such as the relationship between clustering and anomaly detection, the choice between supervised and unsupervised methods, and the difference between global and local anomalies. Then we will survey the most representative anomaly detection algorithms, highlighting what kind of data each approach is best suited to, and discussing their limitations. We will finish with a discussion of the difficulties of anomaly detection in high-dimensional data and some new directions for anomaly detec...

Comparison of prostate set-up accuracy and margins with off-line bony anatomy corrections and online implanted fiducial-based corrections

International Nuclear Information System (INIS)

Greer, P. B.; Dahl, K.; Ebert, M. A.; Wratten, C.; White, M.; Denham, K. W.

2008-01-01

Full text: The aim of the study was to determine prostate set-up accuracy and set-up margins with off-line bony anatomy-based imaging protocols, compared with online implanted fiducial marker-based imaging with daily corrections. Eleven patients were treated with implanted prostate fiducial markers and online set-up corrections. Pretreatment orthogonal electronic portal images were acquired to determine couch shifts and verification images were acquired during treatment to measure residual set-up error. The prostate set-up errors that would result from skin marker set-up, off-line bony anatomy-based protocols and online fiducial marker-based corrections were determined. Set-up margins were calculated for each set-up technique using the percentage of encompassed isocentres land a margin recipe. The prostate systematic set-up errors in the medial-lateral, superior-inferior and anterior-I posterior directions for skin marker set-up were 2.2, 3.6 and 4.5 mm (1 standard deviation). For our bony anatomy-I based off-line protocol the prostate systematic set-up errors were 1.6, 2.5 and 4.4 mm. For the online fiducial based set-up the results were 0.5, 1.4 and 1.4 mm. A prostate systematic error of 10.2 mm was uncorrected by the off-line bone protocol in one patient. Set-up margins calculated to encompass 98% of prostate set-up shifts were 111-14 mm with bone off-line set-up and 4-7 mm with online fiducial markers. Margins from the van Herk margin I recipe were generally 1-2 mm smaller. Bony anatomy-based set-up protocols improve the group prostate set-up error compared with skin marks; however, large prostate systematic errors can remain undetected or systematic (errors increased for individual patients. The margin required for set-up errors was found to be 10-15 mm unless I implanted fiducial markers are available for treatment guidance.

Extended seizure detection algorithm for intracranial EEG recordings

DEFF Research Database (Denmark)

Kjaer, T. W.; Remvig, L. S.; Henriksen, J.

2010-01-01

Objective: We implemented and tested an existing seizure detection algorithm for scalp EEG (sEEG) with the purpose of improving it to intracranial EEG (iEEG) recordings. Method: iEEG was obtained from 16 patients with focal epilepsy undergoing work up for resective epilepsy surgery. Each patient...... had 4 or 5 recorded seizures and 24 hours of non-ictal data were used for evaluation. Data from three electrodes placed at the ictal focus were used for the analysis. A wavelet based feature extraction algorithm delivered input to a support vector machine (SVM) classifier for distinction between ictal...... and non-ictal iEEG. We compare our results to a method published by Shoeb in 2004. While the original method on sEEG was optimal with the use of only four subbands in the wavelet analysis, we found that better seizure detection could be made if all subbands were used for iEEG. Results: When using...

A Gaussian Process Based Online Change Detection Algorithm for Monitoring Periodic Time Series

Energy Technology Data Exchange (ETDEWEB)

Chandola, Varun [ORNL; Vatsavai, Raju [ORNL

2011-01-01

Online time series change detection is a critical component of many monitoring systems, such as space and air-borne remote sensing instruments, cardiac monitors, and network traffic profilers, which continuously analyze observations recorded by sensors. Data collected by such sensors typically has a periodic (seasonal) component. Most existing time series change detection methods are not directly applicable to handle such data, either because they are not designed to handle periodic time series or because they cannot operate in an online mode. We propose an online change detection algorithm which can handle periodic time series. The algorithm uses a Gaussian process based non-parametric time series prediction model and monitors the difference between the predictions and actual observations within a statistically principled control chart framework to identify changes. A key challenge in using Gaussian process in an online mode is the need to solve a large system of equations involving the associated covariance matrix which grows with every time step. The proposed algorithm exploits the special structure of the covariance matrix and can analyze a time series of length T in O(T^2) time while maintaining a O(T) memory footprint, compared to O(T^4) time and O(T^2) memory requirement of standard matrix manipulation methods. We experimentally demonstrate the superiority of the proposed algorithm over several existing time series change detection algorithms on a set of synthetic and real time series. Finally, we illustrate the effectiveness of the proposed algorithm for identifying land use land cover changes using Normalized Difference Vegetation Index (NDVI) data collected for an agricultural region in Iowa state, USA. Our algorithm is able to detect different types of changes in a NDVI validation data set (with ~80% accuracy) which occur due to crop type changes as well as disruptive changes (e.g., natural disasters).

A Novel Immune-Inspired Shellcode Detection Algorithm Based on Hyperellipsoid Detectors

Directory of Open Access Journals (Sweden)

Tianliang Lu

2018-01-01

Full Text Available Shellcodes are machine language codes injected into target programs in the form of network packets or malformed files. Shellcodes can trigger buffer overflow vulnerability and execute malicious instructions. Signature matching technology used by antivirus software or intrusion detection system has low detection rate for unknown or polymorphic shellcodes; to solve such problem, an immune-inspired shellcode detection algorithm was proposed, named ISDA. Static analysis and dynamic analysis were both applied. The shellcodes were disassembled to assembly instructions during static analysis and, for dynamic analysis, the API function sequences of shellcodes were obtained by simulation execution to get the behavioral features of polymorphic shellcodes. The extracted features of shellcodes were encoded to antigens based on n-gram model. Immature detectors become mature after immune tolerance based on negative selection algorithm. To improve nonself space coverage rate, the immune detectors were encoded to hyperellipsoids. To generate better antibody offspring, the detectors were optimized through clonal selection algorithm with genetic mutation. Finally, shellcode samples were collected and tested, and result shows that the proposed method has higher detection accuracy for both nonencoded and polymorphic shellcodes.

Improved Genetic Algorithm Optimization for Forward Vehicle Detection Problems

Directory of Open Access Journals (Sweden)

Longhui Gang

2015-07-01

Full Text Available Automated forward vehicle detection is an integral component of many advanced driver-assistance systems. The method based on multi-visual information fusion, with its exclusive advantages, has become one of the important topics in this research field. During the whole detection process, there are two key points that should to be resolved. One is to find the robust features for identification and the other is to apply an efficient algorithm for training the model designed with multi-information. This paper presents an adaptive SVM (Support Vector Machine model to detect vehicle with range estimation using an on-board camera. Due to the extrinsic factors such as shadows and illumination, we pay more attention to enhancing the system with several robust features extracted from a real driving environment. Then, with the introduction of an improved genetic algorithm, the features are fused efficiently by the proposed SVM model. In order to apply the model in the forward collision warning system, longitudinal distance information is provided simultaneously. The proposed method is successfully implemented on a test car and evaluation experimental results show reliability in terms of both the detection rate and potential effectiveness in a real-driving environment.

A false-alarm aware methodology to develop robust and efficient multi-scale infrared small target detection algorithm

Science.gov (United States)

Moradi, Saed; Moallem, Payman; Sabahi, Mohamad Farzan

2018-03-01

False alarm rate and detection rate are still two contradictory metrics for infrared small target detection in an infrared search and track system (IRST), despite the development of new detection algorithms. In certain circumstances, not detecting true targets is more tolerable than detecting false items as true targets. Hence, considering background clutter and detector noise as the sources of the false alarm in an IRST system, in this paper, a false alarm aware methodology is presented to reduce false alarm rate while the detection rate remains undegraded. To this end, advantages and disadvantages of each detection algorithm are investigated and the sources of the false alarms are determined. Two target detection algorithms having independent false alarm sources are chosen in a way that the disadvantages of the one algorithm can be compensated by the advantages of the other one. In this work, multi-scale average absolute gray difference (AAGD) and Laplacian of point spread function (LoPSF) are utilized as the cornerstones of the desired algorithm of the proposed methodology. After presenting a conceptual model for the desired algorithm, it is implemented through the most straightforward mechanism. The desired algorithm effectively suppresses background clutter and eliminates detector noise. Also, since the input images are processed through just four different scales, the desired algorithm has good capability for real-time implementation. Simulation results in term of signal to clutter ratio and background suppression factor on real and simulated images prove the effectiveness and the performance of the proposed methodology. Since the desired algorithm was developed based on independent false alarm sources, our proposed methodology is expandable to any pair of detection algorithms which have different false alarm sources.

An Anomaly Detection Algorithm of Cloud Platform Based on Self-Organizing Maps

Directory of Open Access Journals (Sweden)

Jun Liu

2016-01-01

Full Text Available Virtual machines (VM on a Cloud platform can be influenced by a variety of factors which can lead to decreased performance and downtime, affecting the reliability of the Cloud platform. Traditional anomaly detection algorithms and strategies for Cloud platforms have some flaws in their accuracy of detection, detection speed, and adaptability. In this paper, a dynamic and adaptive anomaly detection algorithm based on Self-Organizing Maps (SOM for virtual machines is proposed. A unified modeling method based on SOM to detect the machine performance within the detection region is presented, which avoids the cost of modeling a single virtual machine and enhances the detection speed and reliability of large-scale virtual machines in Cloud platform. The important parameters that affect the modeling speed are optimized in the SOM process to significantly improve the accuracy of the SOM modeling and therefore the anomaly detection accuracy of the virtual machine.

Histopathologic Consideration of Fiducial Gold Markers Inserted for Real-Time Tumor-Tracking Radiotherapy Against Lung Cancer

International Nuclear Information System (INIS)

Imura, Mikado; Yamazaki, Koichi; Kubota, Kanako C.; Itoh, Tomoo; Onimaru, Rikiya; Cho, Yasushi; Hida, Yasuhiro; Kaga, Kichizo; Onodera, Yuya; Ogura, Shigeaki; Dosaka-Akita, Hirotoshi; Shirato, Hiroki; Nishimura, Masaharu

2008-01-01

Purpose: Internal fiducial gold markers, safely inserted with bronchoscopy, have been used in real-time tumor-tracking radiotherapy for lung cancer. We investigated the histopathologic findings at several points after the insertion of the gold markers. Methods and Materials: Sixteen gold markers were inserted for preoperative marking in 7 patients who subsequently underwent partial resection of tumors by video-assisted thoracoscopic surgery within 7 days. Results: Fibrotic changes and hyperplasia of type 2 pneumocytes around the markers were seen 5 or 7 days after insertion, and fibrin exudation without fibrosis was detected 1 or 2 days after insertion. Conclusions: Because fibroblastic changes start approximately 5 days after gold marker insertion, real-time tumor-tracking radiotherapy should be started >5 days after gold marker insertion

Fiducial marker guided stereotactic liver radiotherapy: Is a time delay between marker implantation and planning CT needed?

DEFF Research Database (Denmark)

Worm, Esben S; Bertholet, Jenny; Høyer, Morten

2016-01-01

To minimize the risk of marker migration in fiducial marker guided liver SBRT it is common to add a delay of a week between marker implantation and planning CT. This study found that such a delay is unnecessary and could be avoided to minimize the treatment preparation time.......To minimize the risk of marker migration in fiducial marker guided liver SBRT it is common to add a delay of a week between marker implantation and planning CT. This study found that such a delay is unnecessary and could be avoided to minimize the treatment preparation time....

Multivariate algorithms for initiating event detection and identification in nuclear power plants

International Nuclear Information System (INIS)

Wu, Shun-Chi; Chen, Kuang-You; Lin, Ting-Han; Chou, Hwai-Pwu

2018-01-01

Highlights: •Multivariate algorithms for NPP initiating event detection and identification. •Recordings from multiple sensors are simultaneously considered for detection. •Both spatial and temporal information is used for event identification. •Untrained event isolation avoids falsely relating an untrained event. •Efficacy of the algorithms is verified with data from the Maanshan NPP simulator. -- Abstract: To prevent escalation of an initiating event into a severe accident, promptly detecting its occurrence and precisely identifying its type are essential. In this study, several multivariate algorithms for initiating event detection and identification are proposed to help maintain safe operations of nuclear power plants (NPPs). By monitoring changes in the NPP sensing variables, an event is detected when the preset thresholds are exceeded. Unlike existing approaches, recordings from sensors of the same type are simultaneously considered for detection, and no subjective reasoning is involved in setting these thresholds. To facilitate efficient event identification, a spatiotemporal feature extractor is proposed. The extracted features consist of the temporal traits used by existing techniques and the spatial signature of an event. Through an F-score-based feature ranking, only those that are most discriminant in classifying the events under consideration will be retained for identification. Moreover, an untrained event isolation scheme is introduced to avoid relating an untrained event to those in the event dataset so that improper recovery actions can be prevented. Results from experiments containing data of 12 event classes and a total of 125 events generated using a Taiwan’s Maanshan NPP simulator are provided to illustrate the efficacy of the proposed algorithms.

An epileptic seizures detection algorithm based on the empirical mode decomposition of EEG.

Science.gov (United States)

Orosco, Lorena; Laciar, Eric; Correa, Agustina Garces; Torres, Abel; Graffigna, Juan P

2009-01-01

Epilepsy is a neurological disorder that affects around 50 million people worldwide. The seizure detection is an important component in the diagnosis of epilepsy. In this study, the Empirical Mode Decomposition (EMD) method was proposed on the development of an automatic epileptic seizure detection algorithm. The algorithm first computes the Intrinsic Mode Functions (IMFs) of EEG records, then calculates the energy of each IMF and performs the detection based on an energy threshold and a minimum duration decision. The algorithm was tested in 9 invasive EEG records provided and validated by the Epilepsy Center of the University Hospital of Freiburg. In 90 segments analyzed (39 with epileptic seizures) the sensitivity and specificity obtained with the method were of 56.41% and 75.86% respectively. It could be concluded that EMD is a promissory method for epileptic seizure detection in EEG records.

High Precision Edge Detection Algorithm for Mechanical Parts

Directory of Open Access Journals (Sweden)

Duan Zhenyun

2018-04-01

Full Text Available High precision and high efficiency measurement is becoming an imperative requirement for a lot of mechanical parts. So in this study, a subpixel-level edge detection algorithm based on the Gaussian integral model is proposed. For this purpose, the step edge normal section line Gaussian integral model of the backlight image is constructed, combined with the point spread function and the single step model. Then gray value of discrete points on the normal section line of pixel edge is calculated by surface interpolation, and the coordinate as well as gray information affected by noise is fitted in accordance with the Gaussian integral model. Therefore, a precise location of a subpixel edge was determined by searching the mean point. Finally, a gear tooth was measured by M&M3525 gear measurement center to verify the proposed algorithm. The theoretical analysis and experimental results show that the local edge fluctuation is reduced effectively by the proposed method in comparison with the existing subpixel edge detection algorithms. The subpixel edge location accuracy and computation speed are improved. And the maximum error of gear tooth profile total deviation is 1.9 μm compared with measurement result with gear measurement center. It indicates that the method has high reliability to meet the requirement of high precision measurement.

A Detection Algorithm for the BOC Signal Based on Quadrature Channel Correlation

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Bo Qian

2018-01-01

Full Text Available In order to solve the problem of detecting a BOC signal, which uses a long-period pseudo random sequence, an algorithm is presented based on quadrature channel correlation. The quadrature channel correlation method eliminates the autocorrelation component of the carrier wave, allowing for the extraction of the absolute autocorrelation peaks of the BOC sequence. If the same lag difference and height difference exist for the adjacent peaks, the BOC signal can be detected effectively using a statistical analysis of the multiple autocorrelation peaks. The simulation results show that the interference of the carrier wave component is eliminated and the autocorrelation peaks of the BOC sequence are obtained effectively without demodulation. The BOC signal can be detected effectively when the SNR is greater than −12 dB. The detection ability can be improved further by increasing the number of sampling points. The higher the ratio of the square wave subcarrier speed to the pseudo random sequence speed is, the greater the detection ability is with a lower SNR. The algorithm presented in this paper is superior to the algorithm based on the spectral correlation.

GA-DoSLD: Genetic Algorithm Based Denial-of-Sleep Attack Detection in WSN

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Mahalakshmi Gunasekaran

2017-01-01

Full Text Available Denial-of-sleep (DoSL attack is a special category of denial-of-service attack that prevents the battery powered sensor nodes from going into the sleep mode, thus affecting the network performance. The existing schemes used for the DoSL attack detection do not provide an optimal energy conservation and key pairing operation. Hence, in this paper, an efficient Genetic Algorithm (GA based denial-of-sleep attack detection (GA-DoSLD algorithm is suggested for analyzing the misbehaviors of the nodes. The suggested algorithm implements a Modified-RSA (MRSA algorithm in the base station (BS for generating and distributing the key pair among the sensor nodes. Before sending/receiving the packets, the sensor nodes determine the optimal route using Ad Hoc On-Demand Distance Vector Routing (AODV protocol and then ensure the trustworthiness of the relay node using the fitness calculation. The crossover and mutation operations detect and analyze the methods that the attackers use for implementing the attack. On determining an attacker node, the BS broadcasts the blocked information to all the other sensor nodes in the network. Simulation results prove that the suggested algorithm is optimal compared to the existing algorithms such as X-MAC, ZKP, and TE2P schemes.

Automatic metal parts inspection: Use of thermographic images and anomaly detection algorithms

Science.gov (United States)

Benmoussat, M. S.; Guillaume, M.; Caulier, Y.; Spinnler, K.

2013-11-01

A fully-automatic approach based on the use of induction thermography and detection algorithms is proposed to inspect industrial metallic parts containing different surface and sub-surface anomalies such as open cracks, open and closed notches with different sizes and depths. A practical experimental setup is developed, where lock-in and pulsed thermography (LT and PT, respectively) techniques are used to establish a dataset of thermal images for three different mockups. Data cubes are constructed by stacking up the temporal sequence of thermogram images. After the reduction of the data space dimension by means of denoising and dimensionality reduction methods; anomaly detection algorithms are applied on the reduced data cubes. The dimensions of the reduced data spaces are automatically calculated with arbitrary criterion. The results show that, when reduced data cubes are used, the anomaly detection algorithms originally developed for hyperspectral data, the well-known Reed and Xiaoli Yu detector (RX) and the regularized adaptive RX (RARX), give good detection performances for both surface and sub-surface defects in a non-supervised way.

Geostationary Sensor Based Forest Fire Detection and Monitoring: An Improved Version of the SFIDE Algorithm

Directory of Open Access Journals (Sweden)

Valeria Di Biase

2018-05-01

Full Text Available The paper aims to present the results obtained in the development of a system allowing for the detection and monitoring of forest fires and the continuous comparison of their intensity when several events occur simultaneously—a common occurrence in European Mediterranean countries during the summer season. The system, called SFIDE (Satellite FIre DEtection, exploits a geostationary satellite sensor (SEVIRI, Spinning Enhanced Visible and InfraRed Imager, on board of MSG, Meteosat Second Generation, satellite series. The algorithm was developed several years ago in the framework of a project (SIGRI funded by the Italian Space Agency (ASI. This algorithm has been completely reviewed in order to enhance its efficiency by reducing false alarms rate preserving a high sensitivity. Due to the very low spatial resolution of SEVIRI images (4 × 4 km2 at Mediterranean latitude the sensitivity of the algorithm should be very high to detect even small fires. The improvement of the algorithm has been obtained by: introducing the sun elevation angle in the computation of the preliminary thresholds to identify potential thermal anomalies (hot spots, introducing a contextual analysis in the detection of clouds and in the detection of night-time fires. The results of the algorithm have been validated in the Sardinia region by using ground true data provided by the regional Corpo Forestale e di Vigilanza Ambientale (CFVA. A significant reduction of the commission error (less than 10% has been obtained with respect to the previous version of the algorithm and also with respect to fire-detection algorithms based on low earth orbit satellites.

Performance improvement of multi-class detection using greedy algorithm for Viola-Jones cascade selection

Science.gov (United States)

Tereshin, Alexander A.; Usilin, Sergey A.; Arlazarov, Vladimir V.

2018-04-01

This paper aims to study the problem of multi-class object detection in video stream with Viola-Jones cascades. An adaptive algorithm for selecting Viola-Jones cascade based on greedy choice strategy in solution of the N-armed bandit problem is proposed. The efficiency of the algorithm on the problem of detection and recognition of the bank card logos in the video stream is shown. The proposed algorithm can be effectively used in documents localization and identification, recognition of road scene elements, localization and tracking of the lengthy objects , and for solving other problems of rigid object detection in a heterogeneous data flows. The computational efficiency of the algorithm makes it possible to use it both on personal computers and on mobile devices based on processors with low power consumption.

A Forest Early Fire Detection Algorithm Based on Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

CHENG Qiang

2014-03-01

Full Text Available Wireless Sensor Networks (WSN adopt GHz as their communication carrier, and it has been found that GHz carrier attenuation model in transmission path is associated with vegetation water content. In this paper, based on RSSI mechanism of WSN nodes we formed vegetation dehydration sensors. Through relationships between vegetation water content and carrier attenuation, we perceived forest vegetation water content variations and early fire gestation process, and established algorithms of early forest fires detection. Experiments confirm that wireless sensor networks can accurately perceive vegetation dehydration events and forest fire events. Simulation results show that, WSN dehydration perception channel (P2P representing 75 % amounts of carrier channel or more, it can meet the detection requirements, which presented a new algorithm of early forest fire detection.

Algorithms for detecting and analysing autocatalytic sets.

Science.gov (United States)

Hordijk, Wim; Smith, Joshua I; Steel, Mike

2015-01-01

Autocatalytic sets are considered to be fundamental to the origin of life. Prior theoretical and computational work on the existence and properties of these sets has relied on a fast algorithm for detectingself-sustaining autocatalytic sets in chemical reaction systems. Here, we introduce and apply a modified version and several extensions of the basic algorithm: (i) a modification aimed at reducing the number of calls to the computationally most expensive part of the algorithm, (ii) the application of a previously introduced extension of the basic algorithm to sample the smallest possible autocatalytic sets within a reaction network, and the application of a statistical test which provides a probable lower bound on the number of such smallest sets, (iii) the introduction and application of another extension of the basic algorithm to detect autocatalytic sets in a reaction system where molecules can also inhibit (as well as catalyse) reactions, (iv) a further, more abstract, extension of the theory behind searching for autocatalytic sets. (i) The modified algorithm outperforms the original one in the number of calls to the computationally most expensive procedure, which, in some cases also leads to a significant improvement in overall running time, (ii) our statistical test provides strong support for the existence of very large numbers (even millions) of minimal autocatalytic sets in a well-studied polymer model, where these minimal sets share about half of their reactions on average, (iii) "uninhibited" autocatalytic sets can be found in reaction systems that allow inhibition, but their number and sizes depend on the level of inhibition relative to the level of catalysis. (i) Improvements in the overall running time when searching for autocatalytic sets can potentially be obtained by using a modified version of the algorithm, (ii) the existence of large numbers of minimal autocatalytic sets can have important consequences for the possible evolvability of

A novel fast phase correlation algorithm for peak wavelength detection of Fiber Bragg Grating sensors.

Science.gov (United States)

Lamberti, A; Vanlanduit, S; De Pauw, B; Berghmans, F

2014-03-24

Fiber Bragg Gratings (FBGs) can be used as sensors for strain, temperature and pressure measurements. For this purpose, the ability to determine the Bragg peak wavelength with adequate wavelength resolution and accuracy is essential. However, conventional peak detection techniques, such as the maximum detection algorithm, can yield inaccurate and imprecise results, especially when the Signal to Noise Ratio (SNR) and the wavelength resolution are poor. Other techniques, such as the cross-correlation demodulation algorithm are more precise and accurate but require a considerable higher computational effort. To overcome these problems, we developed a novel fast phase correlation (FPC) peak detection algorithm, which computes the wavelength shift in the reflected spectrum of a FBG sensor. This paper analyzes the performance of the FPC algorithm for different values of the SNR and wavelength resolution. Using simulations and experiments, we compared the FPC with the maximum detection and cross-correlation algorithms. The FPC method demonstrated a detection precision and accuracy comparable with those of cross-correlation demodulation and considerably higher than those obtained with the maximum detection technique. Additionally, FPC showed to be about 50 times faster than the cross-correlation. It is therefore a promising tool for future implementation in real-time systems or in embedded hardware intended for FBG sensor interrogation.

Analysis of the Chirplet Transform-Based Algorithm for Radar Detection of Accelerated Targets

Science.gov (United States)

Galushko, V. G.; Vavriv, D. M.

2017-06-01

Purpose: Efficiency analysis of an optimal algorithm of chirp signal processing based on the chirplet transform as applied to detection of radar targets in uniformly accelerated motion. Design/methodology/approach: Standard methods of the optimal filtration theory are used to investigate the ambiguity function of chirp signals. Findings: An analytical expression has been derived for the ambiguity function of chirp signals that is analyzed with respect to detection of radar targets moving at a constant acceleration. Sidelobe level and characteristic width of the ambiguity function with respect to the coordinates frequency and rate of its change have been estimated. The gain in the signal-to-noise ratio has been assessed that is provided by the algorithm under consideration as compared with application of the standard Fourier transform to detection of chirp signals against a “white” noise background. It is shown that already with a comparatively small (processing channels (elementary filters with respect to the frequency change rate) the gain in the signal-tonoise ratio exceeds 10 dB. A block diagram of implementation of the algorithm under consideration is suggested on the basis of a multichannel weighted Fourier transform. Recommendations as for selection of the detection algorithm parameters have been developed. Conclusions: The obtained results testify to efficiency of application of the algorithm under consideration to detection of radar targets moving at a constant acceleration. Nevertheless, it seems expedient to perform computer simulations of its operability with account for the noise impact along with trial measurements in real conditions.

Wavelet based edge detection algorithm for web surface inspection of coated board web

Energy Technology Data Exchange (ETDEWEB)

Barjaktarovic, M; Petricevic, S, E-mail: slobodan@etf.bg.ac.r [School of Electrical Engineering, Bulevar Kralja Aleksandra 73, 11000 Belgrade (Serbia)

2010-07-15

This paper presents significant improvement of the already installed vision system. System was designed for real time coated board inspection. The improvement is achieved with development of a new algorithm for edge detection. The algorithm is based on the redundant (undecimated) wavelet transform. Compared to the existing algorithm better delineation of edges is achieved. This yields to better defect detection probability and more accurate geometrical classification, which will provide additional reduction of waste. Also, algorithm will provide detailed classification and more reliably tracking of defects. This improvement requires minimal changes in processing hardware, only a replacement of the graphic card would be needed, adding only negligibly to the system cost. Other changes are accomplished entirely in the image processing software.

A wavelet transform algorithm for peak detection and application to powder x-ray diffraction data.

Science.gov (United States)

Gregoire, John M; Dale, Darren; van Dover, R Bruce

2011-01-01

Peak detection is ubiquitous in the analysis of spectral data. While many noise-filtering algorithms and peak identification algorithms have been developed, recent work [P. Du, W. Kibbe, and S. Lin, Bioinformatics 22, 2059 (2006); A. Wee, D. Grayden, Y. Zhu, K. Petkovic-Duran, and D. Smith, Electrophoresis 29, 4215 (2008)] has demonstrated that both of these tasks are efficiently performed through analysis of the wavelet transform of the data. In this paper, we present a wavelet-based peak detection algorithm with user-defined parameters that can be readily applied to the application of any spectral data. Particular attention is given to the algorithm's resolution of overlapping peaks. The algorithm is implemented for the analysis of powder diffraction data, and successful detection of Bragg peaks is demonstrated for both low signal-to-noise data from theta-theta diffraction of nanoparticles and combinatorial x-ray diffraction data from a composition spread thin film. These datasets have different types of background signals which are effectively removed in the wavelet-based method, and the results demonstrate that the algorithm provides a robust method for automated peak detection.

A Linked List-Based Algorithm for Blob Detection on Embedded Vision-Based Sensors

Directory of Open Access Journals (Sweden)

Ricardo Acevedo-Avila

2016-05-01

Full Text Available Blob detection is a common task in vision-based applications. Most existing algorithms are aimed at execution on general purpose computers; while very few can be adapted to the computing restrictions present in embedded platforms. This paper focuses on the design of an algorithm capable of real-time blob detection that minimizes system memory consumption. The proposed algorithm detects objects in one image scan; it is based on a linked-list data structure tree used to label blobs depending on their shape and node information. An example application showing the results of a blob detection co-processor has been built on a low-powered field programmable gate array hardware as a step towards developing a smart video surveillance system. The detection method is intended for general purpose application. As such, several test cases focused on character recognition are also examined. The results obtained present a fair trade-off between accuracy and memory requirements; and prove the validity of the proposed approach for real-time implementation on resource-constrained computing platforms.

A Linked List-Based Algorithm for Blob Detection on Embedded Vision-Based Sensors.

Science.gov (United States)

Acevedo-Avila, Ricardo; Gonzalez-Mendoza, Miguel; Garcia-Garcia, Andres

2016-05-28

Blob detection is a common task in vision-based applications. Most existing algorithms are aimed at execution on general purpose computers; while very few can be adapted to the computing restrictions present in embedded platforms. This paper focuses on the design of an algorithm capable of real-time blob detection that minimizes system memory consumption. The proposed algorithm detects objects in one image scan; it is based on a linked-list data structure tree used to label blobs depending on their shape and node information. An example application showing the results of a blob detection co-processor has been built on a low-powered field programmable gate array hardware as a step towards developing a smart video surveillance system. The detection method is intended for general purpose application. As such, several test cases focused on character recognition are also examined. The results obtained present a fair trade-off between accuracy and memory requirements; and prove the validity of the proposed approach for real-time implementation on resource-constrained computing platforms.

Liquid fiducial marker performance during radiotherapy of locally advanced non small cell lung cancer

DEFF Research Database (Denmark)

Rydhög, Jonas Scherman; Mortensen, Steen Riisgaard; Larsen, Klaus Richter

2016-01-01

We analysed the positional and structural stability of a long-term biodegradable liquid fiducial marker (BioXmark) for radiotherapy in patients with locally advanced lung cancer. Markers were injected via endoscopic- or endobronchial ultrasound in lymph nodes and reachable primary tumours. Marker...

Detecting lung cancer symptoms with analogic CNN algorithms based on a constrained diffusion template

International Nuclear Information System (INIS)

Hirakawa, Satoshi; Nishio, Yoshifumi; Ushida, Akio; Ueno, Junji; Kasem, I.; Nishitani, Hiromu; Rekeczky, C.; Roska, T.

1997-01-01

In this article, a new type of diffusion template and an analogic CNN algorithm using this diffusion template for detecting some lung cancer symptoms in X-ray films are proposed. The performance of the diffusion template is investigated and our CNN algorithm is verified to detect some key lung cancer symptoms, successfully. (author)

An efficient algorithm for the detection of exposed and hidden wormhole attack

International Nuclear Information System (INIS)

Khan, Z.A.; Rehman, S.U.; Islam, M.H.

2016-01-01

MANETs (Mobile Ad Hoc Networks) are slowly integrating into our everyday lives, their most prominent uses are visible in the disaster and war struck areas where physical infrastructure is almost impossible or very hard to build. MANETs like other networks are facing the threat of malicious users and their activities. A number of attacks have been identified but the most severe of them is the wormhole attack which has the ability to succeed even in case of encrypted traffic and secure networks. Once wormhole is launched successfully, the severity increases by the fact that attackers can launch other attacks too. This paper presents a comprehensive algorithm for the detection of exposed as well as hidden wormhole attack while keeping the detection rate to maximum and at the same reducing false alarms. The algorithm does not require any extra hardware, time synchronization or any special type of nodes. The architecture consists of the combination of Routing Table, RTT (Round Trip Time) and RSSI (Received Signal Strength Indicator) for comprehensive detection of wormhole attack. The proposed technique is robust, light weight, has low resource requirements and provides real-time detection against the wormhole attack. Simulation results show that the algorithm is able to provide a higher detection rate, packet delivery ratio, negligible false alarms and is also better in terms of Ease of Implementation, Detection Accuracy/ Speed and processing overhead. (author)

Fall detection using supervised machine learning algorithms: A comparative study

KAUST Repository

Zerrouki, Nabil; Harrou, Fouzi; Houacine, Amrane; Sun, Ying

2017-01-01

Fall incidents are considered as the leading cause of disability and even mortality among older adults. To address this problem, fall detection and prevention fields receive a lot of intention over the past years and attracted many researcher efforts. We present in the current study an overall performance comparison between fall detection systems using the most popular machine learning approaches which are: Naïve Bayes, K nearest neighbor, neural network, and support vector machine. The analysis of the classification power associated to these most widely utilized algorithms is conducted on two fall detection databases namely FDD and URFD. Since the performance of the classification algorithm is inherently dependent on the features, we extracted and used the same features for all classifiers. The classification evaluation is conducted using different state of the art statistical measures such as the overall accuracy, the F-measure coefficient, and the area under ROC curve (AUC) value.

A novel through-wall respiration detection algorithm using UWB radar.

Science.gov (United States)

Li, Xin; Qiao, Dengyu; Li, Ye; Dai, Huhe

2013-01-01

Through-wall respiration detection using Ultra-wideband (UWB) impulse radar can be applied to the post-disaster rescue, e.g., searching living persons trapped in ruined buildings after an earthquake. Since strong interference signals always exist in the real-life scenarios, such as static clutter, noise, etc., while the respiratory signal is very weak, the signal to noise and clutter ratio (SNCR) is quite low. Therefore, through-wall respiration detection using UWB impulse radar under low SNCR is a challenging work in the research field of searching survivors after disaster. In this paper, an improved UWB respiratory signal model is built up based on an even power of cosine function for the first time. This model is used to reveal the harmonic structure of respiratory signal, based on which a novel high-performance respiration detection algorithm is proposed. This novel algorithm is assessed by experimental verification and simulation and shows about a 1.5dB improvement of SNR and SNCR.

Fall detection using supervised machine learning algorithms: A comparative study

KAUST Repository

Zerrouki, Nabil

2017-01-05

Fall incidents are considered as the leading cause of disability and even mortality among older adults. To address this problem, fall detection and prevention fields receive a lot of intention over the past years and attracted many researcher efforts. We present in the current study an overall performance comparison between fall detection systems using the most popular machine learning approaches which are: Naïve Bayes, K nearest neighbor, neural network, and support vector machine. The analysis of the classification power associated to these most widely utilized algorithms is conducted on two fall detection databases namely FDD and URFD. Since the performance of the classification algorithm is inherently dependent on the features, we extracted and used the same features for all classifiers. The classification evaluation is conducted using different state of the art statistical measures such as the overall accuracy, the F-measure coefficient, and the area under ROC curve (AUC) value.

Detection of cracks in shafts with the Approximated Entropy algorithm

Science.gov (United States)

Sampaio, Diego Luchesi; Nicoletti, Rodrigo

2016-05-01

The Approximate Entropy is a statistical calculus used primarily in the fields of Medicine, Biology, and Telecommunication for classifying and identifying complex signal data. In this work, an Approximate Entropy algorithm is used to detect cracks in a rotating shaft. The signals of the cracked shaft are obtained from numerical simulations of a de Laval rotor with breathing cracks modelled by the Fracture Mechanics. In this case, one analysed the vertical displacements of the rotor during run-up transients. The results show the feasibility of detecting cracks from 5% depth, irrespective of the unbalance of the rotating system and crack orientation in the shaft. The results also show that the algorithm can differentiate the occurrence of crack only, misalignment only, and crack + misalignment in the system. However, the algorithm is sensitive to intrinsic parameters p (number of data points in a sample vector) and f (fraction of the standard deviation that defines the minimum distance between two sample vectors), and good results are only obtained by appropriately choosing their values according to the sampling rate of the signal.

Combined kV and MV imaging for real-time tracking of implanted fiducial markers

International Nuclear Information System (INIS)

Wiersma, R. D.; Mao Weihua; Xing, L.

2008-01-01

In the presence of intrafraction organ motion, target localization uncertainty can greatly hamper the advantage of highly conformal dose techniques such as intensity modulated radiation therapy (IMRT). To minimize the adverse dosimetric effect caused by tumor motion, a real-time knowledge of the tumor position is required throughout the beam delivery process. The recent integration of onboard kV diagnostic imaging together with MV electronic portal imaging devices on linear accelerators can allow for real-time three-dimensional (3D) tumor position monitoring during a treatment delivery. The aim of this study is to demonstrate a near real-time 3D internal fiducial tracking system based on the combined use of kV and MV imaging. A commercially available radiotherapy system equipped with both kV and MV imaging systems was used in this work. A hardware video frame grabber was used to capture both kV and MV video streams simultaneously through independent video channels at 30 frames per second. The fiducial locations were extracted from the kV and MV images using a software tool. The geometric tracking capabilities of the system were evaluated using a pelvic phantom with embedded fiducials placed on a moveable stage. The maximum tracking speed of the kV/MV system is approximately 9 Hz, which is primarily limited by the frame rate of the MV imager. The geometric accuracy of the system is found to be on the order of less than 1 mm in all three spatial dimensions. The technique requires minimal hardware modification and is potentially useful for image-guided radiation therapy systems

Comparison of respiratory surrogates for gated lung radiotherapy without internal fiducials

International Nuclear Information System (INIS)

Korreman, S.; Mostafavi, H.; Le, Q.T.; Boyer, A.

2006-01-01

An investigation was carried out to compare the ability of two respiratory surrogates to mimic actual lung tumor motion during audio coaching. The investigation employed video clips acquired after patients had had fiducial markers implanted in lung tumors to be used for image-guided stereoscopic radiotherapy. The positions of the markers in the clips were measured within the video frames and used as the standard for tumor volume motion. An external marker was tracked optically during the fluoroscopic acquisitions. An image correlation technique was developed to compute a gating signal from the fluoroscopic images. The correlation gating trace was similar to the optical gating trace in the phase regions of the respiratory cycle used for gating. A cross correlation analysis and comparison of the external optical marker gating with internal fluoroscopic gating was performed. The fluoroscopic image correlation surrogate was found to be superior to the external optical surrogate in the AP-views in four out of six cases. In one of the remaining two cases, the two surrogates performed comparably, while in the last case, the external fiducial trace performed best. It was concluded that fluoroscopic gating based on correlation of native image features in the fluoroscopic images will be adequate for respiratory gating

Comparison of respiratory surrogates for gated lung radiotherapy without internal fiducials

Energy Technology Data Exchange (ETDEWEB)

Korreman, S. [Rigshospitalet, Copenhagen (Denmark). Dept. of Radiation Oncology; Mostafavi, H. [Varian Medical Systems, Mountain View, CA (United States). Gintzon Technology Center; Le, Q.T.; Boyer, A. [Stanford Univ. School of Medicine, CA (United States). Dept. of Radiation Oncology

2006-09-15

An investigation was carried out to compare the ability of two respiratory surrogates to mimic actual lung tumor motion during audio coaching. The investigation employed video clips acquired after patients had had fiducial markers implanted in lung tumors to be used for image-guided stereoscopic radiotherapy. The positions of the markers in the clips were measured within the video frames and used as the standard for tumor volume motion. An external marker was tracked optically during the fluoroscopic acquisitions. An image correlation technique was developed to compute a gating signal from the fluoroscopic images. The correlation gating trace was similar to the optical gating trace in the phase regions of the respiratory cycle used for gating. A cross correlation analysis and comparison of the external optical marker gating with internal fluoroscopic gating was performed. The fluoroscopic image correlation surrogate was found to be superior to the external optical surrogate in the AP-views in four out of six cases. In one of the remaining two cases, the two surrogates performed comparably, while in the last case, the external fiducial trace performed best. It was concluded that fluoroscopic gating based on correlation of native image features in the fluoroscopic images will be adequate for respiratory gating.

A stationary wavelet transform and a time-frequency based spike detection algorithm for extracellular recorded data.

Science.gov (United States)

Lieb, Florian; Stark, Hans-Georg; Thielemann, Christiane

2017-06-01

Spike detection from extracellular recordings is a crucial preprocessing step when analyzing neuronal activity. The decision whether a specific part of the signal is a spike or not is important for any kind of other subsequent preprocessing steps, like spike sorting or burst detection in order to reduce the classification of erroneously identified spikes. Many spike detection algorithms have already been suggested, all working reasonably well whenever the signal-to-noise ratio is large enough. When the noise level is high, however, these algorithms have a poor performance. In this paper we present two new spike detection algorithms. The first is based on a stationary wavelet energy operator and the second is based on the time-frequency representation of spikes. Both algorithms are more reliable than all of the most commonly used methods. The performance of the algorithms is confirmed by using simulated data, resembling original data recorded from cortical neurons with multielectrode arrays. In order to demonstrate that the performance of the algorithms is not restricted to only one specific set of data, we also verify the performance using a simulated publicly available data set. We show that both proposed algorithms have the best performance under all tested methods, regardless of the signal-to-noise ratio in both data sets. This contribution will redound to the benefit of electrophysiological investigations of human cells. Especially the spatial and temporal analysis of neural network communications is improved by using the proposed spike detection algorithms.

Comparison of machine learning algorithms for detecting coral reef

Directory of Open Access Journals (Sweden)

Eduardo Tusa

2014-09-01

Full Text Available (Received: 2014/07/31 - Accepted: 2014/09/23This work focuses on developing a fast coral reef detector, which is used for an autonomous underwater vehicle, AUV. A fast detection secures the AUV stabilization respect to an area of reef as fast as possible, and prevents devastating collisions. We use the algorithm of Purser et al. (2009 because of its precision. This detector has two parts: feature extraction that uses Gabor Wavelet filters, and feature classification that uses machine learning based on Neural Networks. Due to the extensive time of the Neural Networks, we exchange for a classification algorithm based on Decision Trees. We use a database of 621 images of coral reef in Belize (110 images for training and 511 images for testing. We implement the bank of Gabor Wavelets filters using C++ and the OpenCV library. We compare the accuracy and running time of 9 machine learning algorithms, whose result was the selection of the Decision Trees algorithm. Our coral detector performs 70ms of running time in comparison to 22s executed by the algorithm of Purser et al. (2009.

ALGORITHMS FOR OPTIMIZATION OF SYSYTEM PERFORMANCE IN LAYERED DETECTION SYSTEMS UNDER DETECTOR COORELATION

International Nuclear Information System (INIS)

Wood, Thomas W.; Heasler, Patrick G.; Daly, Don S.

2010-01-01

Almost all of the 'architectures' for radiation detection systems in Department of Energy (DOE) and other USG programs rely on some version of layered detector deployment. Efficacy analyses of layered (or more generally extended) detection systems in many contexts often assume statistical independence among detection events and thus predict monotonically increasing system performance with the addition of detection layers. We show this to be a false conclusion for the ROC curves typical of most current technology gamma detectors, and more generally show that statistical independence is often an unwarranted assumption for systems in which there is ambiguity about the objects to be detected. In such systems, a model of correlation among detection events allows optimization of system algorithms for interpretation of detector signals. These algorithms are framed as optimal discriminant functions in joint signal space, and may be applied to gross counting or spectroscopic detector systems. We have shown how system algorithms derived from this model dramatically improve detection probabilities compared to the standard serial detection operating paradigm for these systems. These results would not surprise anyone who has confronted the problem of correlated errors (or failure rates) in the analogous contexts, but is seems to be largely underappreciated among those analyzing the radiation detection problem - independence is widely assumed and experimental studies typical fail to measure correlation. This situation, if not rectified, will lead to several unfortunate results. Including overconfidence in system efficacy, overinvestment in layers of similar technology, and underinvestment in diversity among detection assets.

A Robust Motion Artifact Detection Algorithm for Accurate Detection of Heart Rates From Photoplethysmographic Signals Using Time-Frequency Spectral Features.

Science.gov (United States)

Dao, Duy; Salehizadeh, S M A; Noh, Yeonsik; Chong, Jo Woon; Cho, Chae Ho; McManus, Dave; Darling, Chad E; Mendelson, Yitzhak; Chon, Ki H

2017-09-01

Motion and noise artifacts (MNAs) impose limits on the usability of the photoplethysmogram (PPG), particularly in the context of ambulatory monitoring. MNAs can distort PPG, causing erroneous estimation of physiological parameters such as heart rate (HR) and arterial oxygen saturation (SpO2). In this study, we present a novel approach, "TifMA," based on using the time-frequency spectrum of PPG to first detect the MNA-corrupted data and next discard the nonusable part of the corrupted data. The term "nonusable" refers to segments of PPG data from which the HR signal cannot be recovered accurately. Two sequential classification procedures were included in the TifMA algorithm. The first classifier distinguishes between MNA-corrupted and MNA-free PPG data. Once a segment of data is deemed MNA-corrupted, the next classifier determines whether the HR can be recovered from the corrupted segment or not. A support vector machine (SVM) classifier was used to build a decision boundary for the first classification task using data segments from a training dataset. Features from time-frequency spectra of PPG were extracted to build the detection model. Five datasets were considered for evaluating TifMA performance: (1) and (2) were laboratory-controlled PPG recordings from forehead and finger pulse oximeter sensors with subjects making random movements, (3) and (4) were actual patient PPG recordings from UMass Memorial Medical Center with random free movements and (5) was a laboratory-controlled PPG recording dataset measured at the forehead while the subjects ran on a treadmill. The first dataset was used to analyze the noise sensitivity of the algorithm. Datasets 2-4 were used to evaluate the MNA detection phase of the algorithm. The results from the first phase of the algorithm (MNA detection) were compared to results from three existing MNA detection algorithms: the Hjorth, kurtosis-Shannon entropy, and time-domain variability-SVM approaches. This last is an approach

Bladed wheels damage detection through Non-Harmonic Fourier Analysis improved algorithm

Science.gov (United States)

Neri, P.

2017-05-01

Recent papers introduced the Non-Harmonic Fourier Analysis for bladed wheels damage detection. This technique showed its potential in estimating the frequency of sinusoidal signals even when the acquisition time is short with respect to the vibration period, provided that some hypothesis are fulfilled. Anyway, previously proposed algorithms showed severe limitations in cracks detection at their early stage. The present paper proposes an improved algorithm which allows to detect a blade vibration frequency shift due to a crack whose size is really small compared to the blade width. Such a technique could be implemented for condition-based maintenance, allowing to use non-contact methods for vibration measurements. A stator-fixed laser sensor could monitor all the blades as they pass in front of the spot, giving precious information about the wheel health. This configuration determines an acquisition time for each blade which become shorter as the machine rotational speed increases. In this situation, traditional Discrete Fourier Transform analysis results in poor frequency resolution, being not suitable for small frequency shift detection. Non-Harmonic Fourier Analysis instead showed high reliability in vibration frequency estimation even with data samples collected in a short time range. A description of the improved algorithm is provided in the paper, along with a comparison with the previous one. Finally, a validation of the method is presented, based on finite element simulations results.

Validation of an automated seizure detection algorithm for term neonates

Science.gov (United States)

Mathieson, Sean R.; Stevenson, Nathan J.; Low, Evonne; Marnane, William P.; Rennie, Janet M.; Temko, Andrey; Lightbody, Gordon; Boylan, Geraldine B.

2016-01-01

Objective The objective of this study was to validate the performance of a seizure detection algorithm (SDA) developed by our group, on previously unseen, prolonged, unedited EEG recordings from 70 babies from 2 centres. Methods EEGs of 70 babies (35 seizure, 35 non-seizure) were annotated for seizures by experts as the gold standard. The SDA was tested on the EEGs at a range of sensitivity settings. Annotations from the expert and SDA were compared using event and epoch based metrics. The effect of seizure duration on SDA performance was also analysed. Results Between sensitivity settings of 0.5 and 0.3, the algorithm achieved seizure detection rates of 52.6–75.0%, with false detection (FD) rates of 0.04–0.36 FD/h for event based analysis, which was deemed to be acceptable in a clinical environment. Time based comparison of expert and SDA annotations using Cohen’s Kappa Index revealed a best performing SDA threshold of 0.4 (Kappa 0.630). The SDA showed improved detection performance with longer seizures. Conclusion The SDA achieved promising performance and warrants further testing in a live clinical evaluation. Significance The SDA has the potential to improve seizure detection and provide a robust tool for comparing treatment regimens. PMID:26055336

Lack of Correlation Between External Fiducial Positions and Internal Tumor Positions During Breath-Hold CT

International Nuclear Information System (INIS)

Hunjan, Sandeep; Starkschall, George; Prado, Karl; Dong Lei; Balter, Peter

2010-01-01

Purpose: For thoracic tumors, if four-dimensional computed tomography (4DCT) is unavailable, the internal margin can be estimated by use of breath-hold (BH) CT scans acquired at end inspiration (EI) and end expiration (EE). By use of external surrogates for tumor position, BH accuracy is estimated by minimizing the difference between respiratory extrema BH and mean equivalent-phase free breathing (FB) positions. We tested the assumption that an external surrogate for BH accuracy correlates with internal tumor positional accuracy during BH CT. Methods and Materials: In 16 lung cancer patients, 4DCT images, as well as BH CT images at EI and EE, were acquired. Absolute differences between BH and mean equivalent-phase (FB) positions were calculated for both external fiducials and gross tumor volume (GTV) centroids as metrics of external and internal BH accuracy, respectively, and the results were correlated. Results: At EI, the absolute difference between mean FB and BH fiducial displacement correlated poorly with the absolute difference between FB and BH GTV centroid positions on CT images (R 2 = 0.11). Similarly, at EE, the absolute difference between mean FB and BH fiducial displacements correlated poorly with the absolute difference between FB and BH GTV centroid positions on CT images (R 2 = 0.18). Conclusions: External surrogates for tumor position are not an accurate metric of BH accuracy for lung cancer patients. This implies that care should be taken when using such an approach because an incorrect internal margin could be generated.

Cloud detection algorithm comparison and validation for operational Landsat data products

Science.gov (United States)

Foga, Steven Curtis; Scaramuzza, Pat; Guo, Song; Zhu, Zhe; Dilley, Ronald; Beckmann, Tim; Schmidt, Gail L.; Dwyer, John L.; Hughes, MJ; Laue, Brady

2017-01-01

Clouds are a pervasive and unavoidable issue in satellite-borne optical imagery. Accurate, well-documented, and automated cloud detection algorithms are necessary to effectively leverage large collections of remotely sensed data. The Landsat project is uniquely suited for comparative validation of cloud assessment algorithms because the modular architecture of the Landsat ground system allows for quick evaluation of new code, and because Landsat has the most comprehensive manual truth masks of any current satellite data archive. Currently, the Landsat Level-1 Product Generation System (LPGS) uses separate algorithms for determining clouds, cirrus clouds, and snow and/or ice probability on a per-pixel basis. With more bands onboard the Landsat 8 Operational Land Imager (OLI)/Thermal Infrared Sensor (TIRS) satellite, and a greater number of cloud masking algorithms, the U.S. Geological Survey (USGS) is replacing the current cloud masking workflow with a more robust algorithm that is capable of working across multiple Landsat sensors with minimal modification. Because of the inherent error from stray light and intermittent data availability of TIRS, these algorithms need to operate both with and without thermal data. In this study, we created a workflow to evaluate cloud and cloud shadow masking algorithms using cloud validation masks manually derived from both Landsat 7 Enhanced Thematic Mapper Plus (ETM +) and Landsat 8 OLI/TIRS data. We created a new validation dataset consisting of 96 Landsat 8 scenes, representing different biomes and proportions of cloud cover. We evaluated algorithm performance by overall accuracy, omission error, and commission error for both cloud and cloud shadow. We found that CFMask, C code based on the Function of Mask (Fmask) algorithm, and its confidence bands have the best overall accuracy among the many algorithms tested using our validation data. The Artificial Thermal-Automated Cloud Cover Algorithm (AT-ACCA) is the most accurate

Planning and implementing an implanted fiducial programme for prostate cancer radiation therapy

International Nuclear Information System (INIS)

Thompson, A.; Owen, R.; Laferlita, M.; Fox, C.; Foroudi, F.; Tai, K. H.; Styles, C.

2008-01-01

Full text: Using implanted gold seeds as fiducial markers to verify the position of the prostate in radiation therapy is well accepted and is becoming the standard of practice and requirement for international multicentre trials. In 2006 the decision was made at the Peter MacCallum Caner Centre (Peter Mac) to plan for and implement this process as standard clinical practice for radical dose prostate treatments (74-78 Gy). Before this, programme verification of field placement for prostate cancer radiation treatment was routinely carried out using regular off-line electronic portal imaging with matching of bony anatomy. A small multidisciplinary team investigated and assisted in the implementation of this new practice across the Peter Mac sites at East Melbourne and our three satellite centres. Issues considered included seed size, number and position in the prostate, implant equipment, imaging equipment and procedure and consent and information forms. The use of a custom made fiducial pack, comprehensive patient information and a daily on-line imaging process was implemented. The experience of the first 28 patients at Peter Mac from January 2007 to May 2007 inclusive is reported on.

Automatic detection of ECG electrode misplacement: a tale of two algorithms

International Nuclear Information System (INIS)

Xia, Henian; Garcia, Gabriel A; Zhao, Xiaopeng

2012-01-01

Artifacts in an electrocardiogram (ECG) due to electrode misplacement can lead to wrong diagnoses. Various computer methods have been developed for automatic detection of electrode misplacement. Here we reviewed and compared the performance of two algorithms with the highest accuracies on several databases from PhysioNet. These algorithms were implemented into four models. For clean ECG records with clearly distinguishable waves, the best model produced excellent accuracies (> = 98.4%) for all misplacements except the LA/LL interchange (87.4%). However, the accuracies were significantly lower for records with noise and arrhythmias. Moreover, when the algorithms were tested on a database that was independent from the training database, the accuracies may be poor. For the worst scenario, the best accuracies for different types of misplacements ranged from 36.1% to 78.4%. A large number of ECGs of various qualities and pathological conditions are collected every day. To improve the quality of health care, the results of this paper call for more robust and accurate algorithms for automatic detection of electrode misplacement, which should be developed and tested using a database of extensive ECG records. (paper)

An Algorithm for Detection of DVB-T Signals Based on Their Second-Order Statistics

Directory of Open Access Journals (Sweden)

Jallon Pierre

2008-01-01

Full Text Available Abstract We propose in this paper a detection algorithm based on a cost function that jointly tests the correlation induced by the cyclic prefix and the fact that this correlation is time-periodic. In the first part of the paper, the cost function is introduced and some analytical results are given. In particular, the noise and multipath channel impacts on its values are theoretically analysed. In a second part of the paper, some asymptotic results are derived. A first exploitation of these results is used to build a detection test based on the false alarm probability. These results are also used to evaluate the impact of the number of cycle frequencies taken into account in the cost function on the detection performances. Thanks to numerical estimations, we have been able to estimate that the proposed algorithm detects DVB-T signals with an SNR of  dB. As a comparison, and in the same context, the detection algorithm proposed by the 802.22 WG in 2006 is able to detect these signals with an SNR of  dB.

A computerized algorithm for arousal detection in healthy adults and patients with Parkinson disease

DEFF Research Database (Denmark)

Sørensen, Gertrud Laura; Jennum, Poul; Kempfner, Jacob

2012-01-01

arousals from non-rapid eye movement (REM) and REM sleep, independent of the subject's age and disease. The proposed algorithm uses features from EEG, EMG, and the manual sleep stage scoring as input to a feed-forward artificial neural network (ANN). The performance of the algorithm has been assessed using......Arousals occur from all sleep stages and can be identified as abrupt electroencephalogram (EEG) and electromyogram (EMG) changes. Manual scoring of arousals is time consuming with low interscore agreement. The aim of this study was to design an arousal detection algorithm capable of detecting...

Stochastic Resonance algorithms to enhance damage detection in bearing faults

Directory of Open Access Journals (Sweden)

Castiglione Roberto

2015-01-01

Full Text Available Stochastic Resonance is a phenomenon, studied and mainly exploited in telecommunication, which permits the amplification and detection of weak signals by the assistance of noise. The first papers on this technique are dated early 80 s and were developed to explain the periodically recurrent ice ages. Other applications mainly concern neuroscience, biology, medicine and obviously signal analysis and processing. Recently, some researchers have applied the technique for detecting faults in mechanical systems and bearings. In this paper, we try to better understand the conditions of applicability and which is the best algorithm to be adopted for these purposes. In fact, to get the methodology profitable and efficient to enhance the signal spikes due to fault in rings and balls/rollers of bearings, some parameters have to be properly selected. This is a problem since in system identification this procedure should be as blind as possible. Two algorithms are analysed: the first exploits classical SR with three parameters mutually dependent, while the other uses Woods-Saxon potential, with three parameters yet but holding a different meaning. The comparison of the performances of the two algorithms and the optimal choice of their parameters are the scopes of this paper. Algorithms are tested on simulated and experimental data showing an evident capacity of increasing the signal to noise ratio.

Measurement of Neutrino Oscillation Parameters Using Anti-fiducial Charged Current Events in MINOS

Energy Technology Data Exchange (ETDEWEB)

Strait, Matthew Levy [Univ. of Minnesota, Minneapolis, MN (United States)

2010-09-01

Abstract The Main Injector Neutrino Oscillation Search (MINOS) obse rves the disappearance of muon neutrinos as they propagate in the long baseline Neutri nos at the Main Injector (NuMI) beam. MINOS consists of two detectors. The near detector sam ples the initial composition of the beam. The far detector, 735 km away, looks for an energy-d ependent deficit in the neutrino spectrum. This energy-dependent deficit is interpreted as q uantum mechanical oscillations be- tween neutrino flavors. A measurement is made of the effective two-neutrino mixing parameters Δ m 2 ≈ Δ m ² 23 and sin ² 2 θ ≈ sin ² 2 θ ₂₃ . The primary MINOS analysis uses charged current events in the fiducial volume of the far detector. This analysis uses the roughly equal-sized sample of events that fails the fiducial cut, consisting of interact ions outside the fiducial region of the detector and in the surrounding rock. These events provide a n independent and complementary measurement, albeit weaker due to incomplete reconstructi on of the events. This analysis reports on an exposure of 7 . 25 × 10 ²⁰ protons-on-target. Due to poor energy resolution, the meas urement of sin ² 2 θ is much weaker than established results, but the measuremen t of sin ² 2 θ > 0 . 56 at 90% confidence is consistent with the accepted value. The measur ement of Δ m 2 is much stronger. Assuming sin 2 ² θ = 1 , Δ m ² = (2 . 20 ± 0 . 18[stat] ± 0 . 14[syst]) × 10 - ^-3 eV ² .

Respiratory-Gated Proton Beam Therapy for Hepatocellular Carcinoma Adjacent to the Gastrointestinal Tract without Fiducial Markers

Directory of Open Access Journals (Sweden)

Miu Mizuhata

2018-02-01

Full Text Available The efficacy of proton beam therapy (PBT for hepatocellular carcinoma (HCC has been reported, but insertion of fiducial markers in the liver is usually required. We evaluated the efficacy and toxicity of respiratory-gated PBT without fiducial markers for HCC located within 2 cm of the gastrointestinal tract. From March 2011 to December 2015 at our institution, 40 patients were evaluated (median age, 72 years; range, 38–87 years. All patients underwent PBT at a dose of 60 to 80 cobalt gray equivalents (CGE in 20 to 38 fractions. The median follow-up period was 19.9 months (range, 1.2–72.3 months. The median tumor size was 36.5 mm (range, 11–124 mm. Kaplan–Meier estimates of the 2-year overall survival, progression-free survival, and local tumor control rates were 76%, 60%, and 94%, respectively. One patient (2.5% developed a grade 3 gastric ulcer and one (2.5% developed grade 3 ascites retention; none of the remaining patients developed grade >3 toxicities (National Cancer Institute Common Terminology Criteria for Adverse Events ver. 4.0.. This study indicates that PBT without fiducial markers achieves good local control without severe treatment-related toxicity of the gastrointestinal tract for HCC located within 2 cm of the gastrointestinal tract.

Automated computer analysis of plasma-streak traces from SCYLLAC

International Nuclear Information System (INIS)

Whitman, R.L.; Jahoda, F.C.; Kruger, R.P.

1977-01-01

An automated computer analysis technique that locates and references the approximate centroid of single- or dual-streak traces from the Los Alamos Scientific Laboratory SCYLLAC facility is described. The technique also determines the plasma-trace width over a limited self-adjusting region. The plasma traces are recorded with streak cameras on Polaroid film, then scanned and digitized for processing. The analysis technique uses scene segmentation to separate the plasma trace from a reference fiducial trace. The technique employs two methods of peak detection; one for the plasma trace and one for the fiducial trace. The width is obtained using an edge-detection, or slope, method. Timing data are derived from the intensity modulation of the fiducial trace. To smooth (despike) the output graphs showing the plasma-trace centroid and width, a technique of ''twicing'' developed by Tukey was employed. In addition, an interactive sorting algorithm allows retrieval of the centroid, width, and fiducial data from any test shot plasma for post analysis. As yet, only a limited set of sixteen plasma traces has been processed using this technique

Automated computer analysis of plasma-streak traces from SCYLLAC

International Nuclear Information System (INIS)

Whiteman, R.L.; Jahoda, F.C.; Kruger, R.P.

1977-11-01

An automated computer analysis technique that locates and references the approximate centroid of single- or dual-streak traces from the Los Alamos Scientific Laboratory SCYLLAC facility is described. The technique also determines the plasma-trace width over a limited self-adjusting region. The plasma traces are recorded with streak cameras on Polaroid film, then scanned and digitized for processing. The analysis technique uses scene segmentation to separate the plasma trace from a reference fiducial trace. The technique employs two methods of peak detection; one for the plasma trace and one for the fiducial trace. The width is obtained using an edge-detection, or slope, method. Timing data are derived from the intensity modulation of the fiducial trace. To smooth (despike) the output graphs showing the plasma-trace centroid and width, a technique of ''twicing'' developed by Tukey was employed. In addition, an interactive sorting algorithm allows retrieval of the centroid, width, and fiducial data from any test shot plasma for post analysis. As yet, only a limited set of the plasma traces has been processed with this technique

A stationary wavelet transform and a time-frequency based spike detection algorithm for extracellular recorded data

Science.gov (United States)

Lieb, Florian; Stark, Hans-Georg; Thielemann, Christiane

2017-06-01

Objective. Spike detection from extracellular recordings is a crucial preprocessing step when analyzing neuronal activity. The decision whether a specific part of the signal is a spike or not is important for any kind of other subsequent preprocessing steps, like spike sorting or burst detection in order to reduce the classification of erroneously identified spikes. Many spike detection algorithms have already been suggested, all working reasonably well whenever the signal-to-noise ratio is large enough. When the noise level is high, however, these algorithms have a poor performance. Approach. In this paper we present two new spike detection algorithms. The first is based on a stationary wavelet energy operator and the second is based on the time-frequency representation of spikes. Both algorithms are more reliable than all of the most commonly used methods. Main results. The performance of the algorithms is confirmed by using simulated data, resembling original data recorded from cortical neurons with multielectrode arrays. In order to demonstrate that the performance of the algorithms is not restricted to only one specific set of data, we also verify the performance using a simulated publicly available data set. We show that both proposed algorithms have the best performance under all tested methods, regardless of the signal-to-noise ratio in both data sets. Significance. This contribution will redound to the benefit of electrophysiological investigations of human cells. Especially the spatial and temporal analysis of neural network communications is improved by using the proposed spike detection algorithms.

Automated seismic detection of landslides at regional scales: a Random Forest based detection algorithm

Science.gov (United States)

Hibert, C.; Michéa, D.; Provost, F.; Malet, J. P.; Geertsema, M.

2017-12-01

Detection of landslide occurrences and measurement of their dynamics properties during run-out is a high research priority but a logistical and technical challenge. Seismology has started to help in several important ways. Taking advantage of the densification of global, regional and local networks of broadband seismic stations, recent advances now permit the seismic detection and location of landslides in near-real-time. This seismic detection could potentially greatly increase the spatio-temporal resolution at which we study landslides triggering, which is critical to better understand the influence of external forcings such as rainfalls and earthquakes. However, detecting automatically seismic signals generated by landslides still represents a challenge, especially for events with small mass. The low signal-to-noise ratio classically observed for landslide-generated seismic signals and the difficulty to discriminate these signals from those generated by regional earthquakes or anthropogenic and natural noises are some of the obstacles that have to be circumvented. We present a new method for automatically constructing instrumental landslide catalogues from continuous seismic data. We developed a robust and versatile solution, which can be implemented in any context where a seismic detection of landslides or other mass movements is relevant. The method is based on a spectral detection of the seismic signals and the identification of the sources with a Random Forest machine learning algorithm. The spectral detection allows detecting signals with low signal-to-noise ratio, while the Random Forest algorithm achieve a high rate of positive identification of the seismic signals generated by landslides and other seismic sources. The processing chain is implemented to work in a High Performance Computers centre which permits to explore years of continuous seismic data rapidly. We present here the preliminary results of the application of this processing chain for years

Arctic lead detection using a waveform mixture algorithm from CryoSat-2 data

Science.gov (United States)

Lee, Sanggyun; Kim, Hyun-cheol; Im, Jungho

2018-05-01

We propose a waveform mixture algorithm to detect leads from CryoSat-2 data, which is novel and different from the existing threshold-based lead detection methods. The waveform mixture algorithm adopts the concept of spectral mixture analysis, which is widely used in the field of hyperspectral image analysis. This lead detection method was evaluated with high-resolution (250 m) MODIS images and showed comparable and promising performance in detecting leads when compared to the previous methods. The robustness of the proposed approach also lies in the fact that it does not require the rescaling of parameters (i.e., stack standard deviation, stack skewness, stack kurtosis, pulse peakiness, and backscatter σ0), as it directly uses L1B waveform data, unlike the existing threshold-based methods. Monthly lead fraction maps were produced by the waveform mixture algorithm, which shows interannual variability of recent sea ice cover during 2011-2016, excluding the summer season (i.e., June to September). We also compared the lead fraction maps to other lead fraction maps generated from previously published data sets, resulting in similar spatiotemporal patterns.

Measurement of the Higgs boson fiducial and differential cross sections in the 4\\ell decay channel at 13 TeV with the ATLAS detector

CERN Document Server

Salvucci, Antonio; The ATLAS collaboration

2017-01-01

This poster presents a measurement of the inclusive and differential fiducial cross sections of Higgs-boson production in the four leptons (electrons or muons) final state. The data sample, collected by the ATLAS experiment in 2015 and 2016, corresponds to an integrated luminosity of \\SI{36.1}{\\per\\femto\\barn} of proton-proton collisions produced at the Large Hadron Collider at a centre-of-mass energy of \\SI{13}{\\TeV}. The inclusive fiducial cross section has been measured to be in agreement with the Standard Model (SM) prediction. Moreover, several differential fiducial cross sections have been measured for observables sensitive to the Higgs-boson production and decay. Good agreement has been found between data and SM predictions.

Statistical Assessment of Gene Fusion Detection Algorithms using RNASequencing Data

NARCIS (Netherlands)

Varadan, V.; Janevski, A.; Kamalakaran, S.; Banerjee, N.; Harris, L.; Dimitrova, D.

2012-01-01

The detection and quantification of fusion transcripts has both biological and clinical implications. RNA sequencing technology provides a means for unbiased and high resolution characterization of fusion transcript information in tissue samples. We evaluated two fusiondetection algorithms,

ROAD DETECTION BY NEURAL AND GENETIC ALGORITHM IN URBAN ENVIRONMENT

Directory of Open Access Journals (Sweden)

A. Barsi

2012-07-01

Full Text Available In the urban object detection challenge organized by the ISPRS WG III/4 high geometric and radiometric resolution aerial images about Vaihingen/Stuttgart, Germany are distributed. The acquired data set contains optical false color, near infrared images and airborne laserscanning data. The presented research focused exclusively on the optical image, so the elevation information was ignored. The road detection procedure has been built up of two main phases: a segmentation done by neural networks and a compilation made by genetic algorithms. The applied neural networks were support vector machines with radial basis kernel function and self-organizing maps with hexagonal network topology and Euclidean distance function for neighborhood management. The neural techniques have been compared by hyperbox classifier, known from the statistical image classification practice. The compilation of the segmentation is realized by a novel application of the common genetic algorithm and by differential evolution technique. The genes were implemented to detect the road elements by evaluating a special binary fitness function. The results have proven that the evolutional technique can automatically find major road segments.

Software Piracy Detection Model Using Ant Colony Optimization Algorithm

Science.gov (United States)

Astiqah Omar, Nor; Zakuan, Zeti Zuryani Mohd; Saian, Rizauddin

2017-06-01

Internet enables information to be accessible anytime and anywhere. This scenario creates an environment whereby information can be easily copied. Easy access to the internet is one of the factors which contribute towards piracy in Malaysia as well as the rest of the world. According to a survey conducted by Compliance Gap BSA Global Software Survey in 2013 on software piracy, found out that 43 percent of the software installed on PCs around the world was not properly licensed, the commercial value of the unlicensed installations worldwide was reported to be 62.7 billion. Piracy can happen anywhere including universities. Malaysia as well as other countries in the world is faced with issues of piracy committed by the students in universities. Piracy in universities concern about acts of stealing intellectual property. It can be in the form of software piracy, music piracy, movies piracy and piracy of intellectual materials such as books, articles and journals. This scenario affected the owner of intellectual property as their property is in jeopardy. This study has developed a classification model for detecting software piracy. The model was developed using a swarm intelligence algorithm called the Ant Colony Optimization algorithm. The data for training was collected by a study conducted in Universiti Teknologi MARA (Perlis). Experimental results show that the model detection accuracy rate is better as compared to J48 algorithm.

Dynamic multiple thresholding breast boundary detection algorithm for mammograms

International Nuclear Information System (INIS)

Wu, Yi-Ta; Zhou Chuan; Chan, Heang-Ping; Paramagul, Chintana; Hadjiiski, Lubomir M.; Daly, Caroline Plowden; Douglas, Julie A.; Zhang Yiheng; Sahiner, Berkman; Shi Jiazheng; Wei Jun

2010-01-01

Purpose: Automated detection of breast boundary is one of the fundamental steps for computer-aided analysis of mammograms. In this study, the authors developed a new dynamic multiple thresholding based breast boundary (MTBB) detection method for digitized mammograms. Methods: A large data set of 716 screen-film mammograms (442 CC view and 274 MLO view) obtained from consecutive cases of an Institutional Review Board approved project were used. An experienced breast radiologist manually traced the breast boundary on each digitized image using a graphical interface to provide a reference standard. The initial breast boundary (MTBB-Initial) was obtained by dynamically adapting the threshold to the gray level range in local regions of the breast periphery. The initial breast boundary was then refined by using gradient information from horizontal and vertical Sobel filtering to obtain the final breast boundary (MTBB-Final). The accuracy of the breast boundary detection algorithm was evaluated by comparison with the reference standard using three performance metrics: The Hausdorff distance (HDist), the average minimum Euclidean distance (AMinDist), and the area overlap measure (AOM). Results: In comparison with the authors' previously developed gradient-based breast boundary (GBB) algorithm, it was found that 68%, 85%, and 94% of images had HDist errors less than 6 pixels (4.8 mm) for GBB, MTBB-Initial, and MTBB-Final, respectively. 89%, 90%, and 96% of images had AMinDist errors less than 1.5 pixels (1.2 mm) for GBB, MTBB-Initial, and MTBB-Final, respectively. 96%, 98%, and 99% of images had AOM values larger than 0.9 for GBB, MTBB-Initial, and MTBB-Final, respectively. The improvement by the MTBB-Final method was statistically significant for all the evaluation measures by the Wilcoxon signed rank test (p<0.0001). Conclusions: The MTBB approach that combined dynamic multiple thresholding and gradient information provided better performance than the breast boundary

Detection of Carious Lesions and Restorations Using Particle Swarm Optimization Algorithm

Directory of Open Access Journals (Sweden)

Mohammad Naebi

2016-01-01

Full Text Available Background/Purpose. In terms of the detection of tooth diagnosis, no intelligent detection has been done up till now. Dentists just look at images and then they can detect the diagnosis position in tooth based on their experiences. Using new technologies, scientists will implement detection and repair of tooth diagnosis intelligently. In this paper, we have introduced one intelligent method for detection using particle swarm optimization (PSO and our mathematical formulation. This method was applied to 2D special images. Using developing of our method, we can detect tooth diagnosis for all of 2D and 3D images. Materials and Methods. In recent years, it is possible to implement intelligent processing of images by high efficiency optimization algorithms in many applications especially for detection of dental caries and restoration without human intervention. In the present work, we explain PSO algorithm with our detection formula for detection of dental caries and restoration. Also image processing helped us to implement our method. And to do so, pictures taken by digital radiography systems of tooth are used. Results and Conclusion. We implement some mathematics formula for fitness of PSO. Our results show that this method can detect dental caries and restoration in digital radiography pictures with the good convergence. In fact, the error rate of this method was 8%, so that it can be implemented for detection of dental caries and restoration. Using some parameters, it is possible that the error rate can be even reduced below 0.5%.

SU-G-BRA-05: Application of a Feature-Based Tracking Algorithm to KV X-Ray Fluoroscopic Images Toward Marker-Less Real-Time Tumor Tracking

Energy Technology Data Exchange (ETDEWEB)

Nakamura, M; Matsuo, Y; Mukumoto, N; Iizuka, Y; Yokota, K; Mizowaki, T; Hiraoka, M [Kyoto University, Graduate School of Medicine, Kyoto (Japan); Nakao, M [Kyoto University, Graduate School of Informatics, Kyoto (Japan)

2016-06-15

Purpose: To detect target position on kV X-ray fluoroscopic images using a feature-based tracking algorithm, Accelerated-KAZE (AKAZE), for markerless real-time tumor tracking (RTTT). Methods: Twelve lung cancer patients treated with RTTT on the Vero4DRT (Mitsubishi Heavy Industries, Japan, and Brainlab AG, Feldkirchen, Germany) were enrolled in this study. Respiratory tumor movement was greater than 10 mm. Three to five fiducial markers were implanted around the lung tumor transbronchially for each patient. Before beam delivery, external infrared (IR) markers and the fiducial markers were monitored for 20 to 40 s with the IR camera every 16.7 ms and with an orthogonal kV x-ray imaging subsystem every 80 or 160 ms, respectively. Target positions derived from the fiducial markers were determined on the orthogonal kV x-ray images, which were used as the ground truth in this study. Meanwhile, tracking positions were identified by AKAZE. Among a lot of feature points, AKAZE found high-quality feature points through sequential cross-check and distance-check between two consecutive images. Then, these 2D positional data were converted to the 3D positional data by a transformation matrix with a predefined calibration parameter. Root mean square error (RMSE) was calculated to evaluate the difference between 3D tracking and target positions. A total of 393 frames was analyzed. The experiment was conducted on a personal computer with 16 GB RAM, Intel Core i7-2600, 3.4 GHz processor. Results: Reproducibility of the target position during the same respiratory phase was 0.6 +/− 0.6 mm (range, 0.1–3.3 mm). Mean +/− SD of the RMSEs was 0.3 +/− 0.2 mm (range, 0.0–1.0 mm). Median computation time per frame was 179 msec (range, 154–247 msec). Conclusion: AKAZE successfully and quickly detected the target position on kV X-ray fluoroscopic images. Initial results indicate that the differences between 3D tracking and target position would be clinically acceptable.

SU-G-BRA-05: Application of a Feature-Based Tracking Algorithm to KV X-Ray Fluoroscopic Images Toward Marker-Less Real-Time Tumor Tracking

International Nuclear Information System (INIS)

Nakamura, M; Matsuo, Y; Mukumoto, N; Iizuka, Y; Yokota, K; Mizowaki, T; Hiraoka, M; Nakao, M

2016-01-01

Purpose: To detect target position on kV X-ray fluoroscopic images using a feature-based tracking algorithm, Accelerated-KAZE (AKAZE), for markerless real-time tumor tracking (RTTT). Methods: Twelve lung cancer patients treated with RTTT on the Vero4DRT (Mitsubishi Heavy Industries, Japan, and Brainlab AG, Feldkirchen, Germany) were enrolled in this study. Respiratory tumor movement was greater than 10 mm. Three to five fiducial markers were implanted around the lung tumor transbronchially for each patient. Before beam delivery, external infrared (IR) markers and the fiducial markers were monitored for 20 to 40 s with the IR camera every 16.7 ms and with an orthogonal kV x-ray imaging subsystem every 80 or 160 ms, respectively. Target positions derived from the fiducial markers were determined on the orthogonal kV x-ray images, which were used as the ground truth in this study. Meanwhile, tracking positions were identified by AKAZE. Among a lot of feature points, AKAZE found high-quality feature points through sequential cross-check and distance-check between two consecutive images. Then, these 2D positional data were converted to the 3D positional data by a transformation matrix with a predefined calibration parameter. Root mean square error (RMSE) was calculated to evaluate the difference between 3D tracking and target positions. A total of 393 frames was analyzed. The experiment was conducted on a personal computer with 16 GB RAM, Intel Core i7-2600, 3.4 GHz processor. Results: Reproducibility of the target position during the same respiratory phase was 0.6 +/− 0.6 mm (range, 0.1–3.3 mm). Mean +/− SD of the RMSEs was 0.3 +/− 0.2 mm (range, 0.0–1.0 mm). Median computation time per frame was 179 msec (range, 154–247 msec). Conclusion: AKAZE successfully and quickly detected the target position on kV X-ray fluoroscopic images. Initial results indicate that the differences between 3D tracking and target position would be clinically acceptable.

On a Hopping-Points SVD and Hough Transform-Based Line Detection Algorithm for Robot Localization and Mapping

Directory of Open Access Journals (Sweden)

Abhijeet Ravankar

2016-05-01

Full Text Available Line detection is an important problem in computer vision, graphics and autonomous robot navigation. Lines detected using a laser range sensor (LRS mounted on a robot can be used as features to build a map of the environment, and later to localize the robot in the map, in a process known as Simultaneous Localization and Mapping (SLAM. We propose an efficient algorithm for line detection from LRS data using a novel hopping-points Singular Value Decomposition (SVD and Hough transform-based algorithm, in which SVD is applied to intermittent LRS points to accelerate the algorithm. A reverse-hop mechanism ensures that the end points of the line segments are accurately extracted. Line segments extracted from the proposed algorithm are used to form a map and, subsequently, LRS data points are matched with the line segments to localize the robot. The proposed algorithm eliminates the drawbacks of point-based matching algorithms like the Iterative Closest Points (ICP algorithm, the performance of which degrades with an increasing number of points. We tested the proposed algorithm for mapping and localization in both simulated and real environments, and found it to detect lines accurately and build maps with good self-localization.

Costs and consequences of automated algorithms versus manual grading for the detection of referable diabetic retinopathy.

Science.gov (United States)

Scotland, G S; McNamee, P; Fleming, A D; Goatman, K A; Philip, S; Prescott, G J; Sharp, P F; Williams, G J; Wykes, W; Leese, G P; Olson, J A

2010-06-01

To assess the cost-effectiveness of an improved automated grading algorithm for diabetic retinopathy against a previously described algorithm, and in comparison with manual grading. Efficacy of the alternative algorithms was assessed using a reference graded set of images from three screening centres in Scotland (1253 cases with observable/referable retinopathy and 6333 individuals with mild or no retinopathy). Screening outcomes and grading and diagnosis costs were modelled for a cohort of 180 000 people, with prevalence of referable retinopathy at 4%. Algorithm (b), which combines image quality assessment with detection algorithms for microaneurysms (MA), blot haemorrhages and exudates, was compared with a simpler algorithm (a) (using image quality assessment and MA/dot haemorrhage (DH) detection), and the current practice of manual grading. Compared with algorithm (a), algorithm (b) would identify an additional 113 cases of referable retinopathy for an incremental cost of pound 68 per additional case. Compared with manual grading, automated grading would be expected to identify between 54 and 123 fewer referable cases, for a grading cost saving between pound 3834 and pound 1727 per case missed. Extrapolation modelling over a 20-year time horizon suggests manual grading would cost between pound 25,676 and pound 267,115 per additional quality adjusted life year gained. Algorithm (b) is more cost-effective than the algorithm based on quality assessment and MA/DH detection. With respect to the value of introducing automated detection systems into screening programmes, automated grading operates within the recommended national standards in Scotland and is likely to be considered a cost-effective alternative to manual disease/no disease grading.

Multivariate anomaly detection for Earth observations: a comparison of algorithms and feature extraction techniques

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M. Flach

2017-08-01

Full Text Available Today, many processes at the Earth's surface are constantly monitored by multiple data streams. These observations have become central to advancing our understanding of vegetation dynamics in response to climate or land use change. Another set of important applications is monitoring effects of extreme climatic events, other disturbances such as fires, or abrupt land transitions. One important methodological question is how to reliably detect anomalies in an automated and generic way within multivariate data streams, which typically vary seasonally and are interconnected across variables. Although many algorithms have been proposed for detecting anomalies in multivariate data, only a few have been investigated in the context of Earth system science applications. In this study, we systematically combine and compare feature extraction and anomaly detection algorithms for detecting anomalous events. Our aim is to identify suitable workflows for automatically detecting anomalous patterns in multivariate Earth system data streams. We rely on artificial data that mimic typical properties and anomalies in multivariate spatiotemporal Earth observations like sudden changes in basic characteristics of time series such as the sample mean, the variance, changes in the cycle amplitude, and trends. This artificial experiment is needed as there is no gold standard for the identification of anomalies in real Earth observations. Our results show that a well-chosen feature extraction step (e.g., subtracting seasonal cycles, or dimensionality reduction is more important than the choice of a particular anomaly detection algorithm. Nevertheless, we identify three detection algorithms (k-nearest neighbors mean distance, kernel density estimation, a recurrence approach and their combinations (ensembles that outperform other multivariate approaches as well as univariate extreme-event detection methods. Our results therefore provide an effective workflow to

Influenza detection and prediction algorithms: comparative accuracy trial in Östergötland county, Sweden, 2008-2012.

Science.gov (United States)

Spreco, A; Eriksson, O; Dahlström, Ö; Timpka, T

2017-07-01

Methods for the detection of influenza epidemics and prediction of their progress have seldom been comparatively evaluated using prospective designs. This study aimed to perform a prospective comparative trial of algorithms for the detection and prediction of increased local influenza activity. Data on clinical influenza diagnoses recorded by physicians and syndromic data from a telenursing service were used. Five detection and three prediction algorithms previously evaluated in public health settings were calibrated and then evaluated over 3 years. When applied on diagnostic data, only detection using the Serfling regression method and prediction using the non-adaptive log-linear regression method showed acceptable performances during winter influenza seasons. For the syndromic data, none of the detection algorithms displayed a satisfactory performance, while non-adaptive log-linear regression was the best performing prediction method. We conclude that evidence was found for that available algorithms for influenza detection and prediction display satisfactory performance when applied on local diagnostic data during winter influenza seasons. When applied on local syndromic data, the evaluated algorithms did not display consistent performance. Further evaluations and research on combination of methods of these types in public health information infrastructures for 'nowcasting' (integrated detection and prediction) of influenza activity are warranted.

A novel time-domain signal processing algorithm for real time ventricular fibrillation detection

International Nuclear Information System (INIS)

Monte, G E; Scarone, N C; Liscovsky, P O; Rotter, P

2011-01-01

This paper presents an application of a novel algorithm for real time detection of ECG pathologies, especially ventricular fibrillation. It is based on segmentation and labeling process of an oversampled signal. After this treatment, analyzing sequence of segments, global signal behaviours are obtained in the same way like a human being does. The entire process can be seen as a morphological filtering after a smart data sampling. The algorithm does not require any ECG digital signal pre-processing, and the computational cost is low, so it can be embedded into the sensors for wearable and permanent applications. The proposed algorithms could be the input signal description to expert systems or to artificial intelligence software in order to detect other pathologies.

A novel time-domain signal processing algorithm for real time ventricular fibrillation detection

Science.gov (United States)

Monte, G. E.; Scarone, N. C.; Liscovsky, P. O.; Rotter S/N, P.

2011-12-01

This paper presents an application of a novel algorithm for real time detection of ECG pathologies, especially ventricular fibrillation. It is based on segmentation and labeling process of an oversampled signal. After this treatment, analyzing sequence of segments, global signal behaviours are obtained in the same way like a human being does. The entire process can be seen as a morphological filtering after a smart data sampling. The algorithm does not require any ECG digital signal pre-processing, and the computational cost is low, so it can be embedded into the sensors for wearable and permanent applications. The proposed algorithms could be the input signal description to expert systems or to artificial intelligence software in order to detect other pathologies.

IMPLEMENTATION OF INCIDENT DETECTION ALGORITHM BASED ON FUZZY LOGIC IN PTV VISSIM

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Andrey Borisovich Nikolaev

2017-05-01

Full Text Available Traffic incident management is a major challenge in the management of movement, requiring constant attention and significant investment, as well as fast and accurate solutions in order to re-establish normal traffic conditions. Automatic control methods are becoming an important factor for the reduction of traffic congestion caused by an arising incident. In this paper, the algorithm of automatic detection incident based on fuzzy logic is implemented in the software PTV VISSIM. 9 different types of tests were conducted on the two lane road section segment with changing traffic conditions: the location of the road accident, loading of traffic. The main conclusion of the research is that the proposed algorithm for the incidents detection demonstrates good performance in the time of detection and false alarms

Optimized Swinging Door Algorithm for Wind Power Ramp Event Detection: Preprint

Energy Technology Data Exchange (ETDEWEB)

Cui, Mingjian; Zhang, Jie; Florita, Anthony R.; Hodge, Bri-Mathias; Ke, Deping; Sun, Yuanzhang

2015-08-06

Significant wind power ramp events (WPREs) are those that influence the integration of wind power, and they are a concern to the continued reliable operation of the power grid. As wind power penetration has increased in recent years, so has the importance of wind power ramps. In this paper, an optimized swinging door algorithm (SDA) is developed to improve ramp detection performance. Wind power time series data are segmented by the original SDA, and then all significant ramps are detected and merged through a dynamic programming algorithm. An application of the optimized SDA is provided to ascertain the optimal parameter of the original SDA. Measured wind power data from the Electric Reliability Council of Texas (ERCOT) are used to evaluate the proposed optimized SDA.

Implementing a Parallel Image Edge Detection Algorithm Based on the Otsu-Canny Operator on the Hadoop Platform.

Science.gov (United States)

Cao, Jianfang; Chen, Lichao; Wang, Min; Tian, Yun

2018-01-01

The Canny operator is widely used to detect edges in images. However, as the size of the image dataset increases, the edge detection performance of the Canny operator decreases and its runtime becomes excessive. To improve the runtime and edge detection performance of the Canny operator, in this paper, we propose a parallel design and implementation for an Otsu-optimized Canny operator using a MapReduce parallel programming model that runs on the Hadoop platform. The Otsu algorithm is used to optimize the Canny operator's dual threshold and improve the edge detection performance, while the MapReduce parallel programming model facilitates parallel processing for the Canny operator to solve the processing speed and communication cost problems that occur when the Canny edge detection algorithm is applied to big data. For the experiments, we constructed datasets of different scales from the Pascal VOC2012 image database. The proposed parallel Otsu-Canny edge detection algorithm performs better than other traditional edge detection algorithms. The parallel approach reduced the running time by approximately 67.2% on a Hadoop cluster architecture consisting of 5 nodes with a dataset of 60,000 images. Overall, our approach system speeds up the system by approximately 3.4 times when processing large-scale datasets, which demonstrates the obvious superiority of our method. The proposed algorithm in this study demonstrates both better edge detection performance and improved time performance.

Model-based fault detection algorithm for photovoltaic system monitoring

KAUST Repository

Harrou, Fouzi

2018-02-12

Reliable detection of faults in PV systems plays an important role in improving their reliability, productivity, and safety. This paper addresses the detection of faults in the direct current (DC) side of photovoltaic (PV) systems using a statistical approach. Specifically, a simulation model that mimics the theoretical performances of the inspected PV system is designed. Residuals, which are the difference between the measured and estimated output data, are used as a fault indicator. Indeed, residuals are used as the input for the Multivariate CUmulative SUM (MCUSUM) algorithm to detect potential faults. We evaluated the proposed method by using data from an actual 20 MWp grid-connected PV system located in the province of Adrar, Algeria.

Robust frameless stereotactic localization in extra-cranial radiotherapy

International Nuclear Information System (INIS)

Riboldi, Marco; Baroni, Guido; Spadea, Maria Francesca; Bassanini, Fabio; Tagaste, Barbara; Garibaldi, Cristina; Orecchia, Roberto; Pedotti, Antonio

2006-01-01

In the field of extra-cranial radiotherapy, several inaccuracies can make the application of frameless stereotactic localization techniques error-prone. When optical tracking systems based on surface fiducials are used, inter- and intra-fractional uncertainties in marker three-dimensional (3D) detection may lead to inexact tumor position estimation, resulting in erroneous patient setup. This is due to the fact that external fiducials misdetection results in deformation effects that are poorly handled in a rigid-body approach. In this work, the performance of two frameless stereotactic localization algorithms for 3D tumor position reconstruction in extra-cranial radiotherapy has been specifically tested. Two strategies, unweighted versus weighted, for stereotactic tumor localization were examined by exploiting data coming from 46 patients treated for extra-cranial lesions. Measured isocenter displacements and rotations were combined to define isocentric procedures, featuring 6 degrees of freedom, for correcting patient alignment (isocentric positioning correction). The sensitivity of the algorithms to uncertainties in the 3D localization of fiducials was investigated by means of 184 numerical simulations. The performance of the implemented isocentric positioning correction was compared to conventional point-based registration. The isocentric positioning correction algorithm was tested on a clinical dataset of inter-fractional and intra-fractional setup errors, which was collected by means of an optical tracker on the same group of patients. The weighted strategy exhibited a lower sensitivity to fiducial localization errors in simulated misalignments than those of the unweighted strategy. Isocenter 3D displacements provided by the weighted strategy were consistently smaller than those featured by the unweighted strategy. The peak decrease in median and quartile values of isocenter 3D displacements were 1.4 and 2.7 mm, respectively. Concerning clinical data, the

A non-linear algorithm for current signal filtering and peak detection in SiPM

International Nuclear Information System (INIS)

Putignano, M; Intermite, A; Welsch, C P

2012-01-01

Read-out of Silicon Photomultipliers is commonly achieved by means of charge integration, a method particularly susceptible to after-pulsing noise and not efficient for low level light signals. Current signal monitoring, characterized by easier electronic implementation and intrinsically faster than charge integration, is also more suitable for low level light signals and can potentially result in much decreased after-pulsing noise effects. However, its use is to date limited by the need of developing a suitable read-out algorithm for signal analysis and filtering able to achieve current peak detection and measurement with the needed precision and accuracy. In this paper we present an original algorithm, based on a piecewise linear-fitting approach, to filter the noise of the current signal and hence efficiently identifying and measuring current peaks. The proposed algorithm is then compared with the optimal linear filtering algorithm for time-encoded peak detection, based on a moving average routine, and assessed in terms of accuracy, precision, and peak detection efficiency, demonstrating improvements of 1÷2 orders of magnitude in all these quality factors.

A game theoretic algorithm to detect overlapping community structure in networks

Science.gov (United States)

Zhou, Xu; Zhao, Xiaohui; Liu, Yanheng; Sun, Geng

2018-04-01

Community detection can be used as an important technique for product and personalized service recommendation. A game theory based approach to detect overlapping community structure is introduced in this paper. The process of the community formation is converted into a game, when all agents (nodes) cannot improve their own utility, the game process will be terminated. The utility function is composed of a gain and a loss function and we present a new gain function in this paper. In addition, different from choosing action randomly among join, quit and switch for each agent to get new label, two new strategies for each agent to update its label are designed during the game, and the strategies are also evaluated and compared for each agent in order to find its best result. The overlapping community structure is naturally presented when the stop criterion is satisfied. The experimental results demonstrate that the proposed algorithm outperforms other similar algorithms for detecting overlapping communities in networks.

Semi-supervised spectral algorithms for community detection in complex networks based on equivalence of clustering methods

Science.gov (United States)

Ma, Xiaoke; Wang, Bingbo; Yu, Liang

2018-01-01

Community detection is fundamental for revealing the structure-functionality relationship in complex networks, which involves two issues-the quantitative function for community as well as algorithms to discover communities. Despite significant research on either of them, few attempt has been made to establish the connection between the two issues. To attack this problem, a generalized quantification function is proposed for community in weighted networks, which provides a framework that unifies several well-known measures. Then, we prove that the trace optimization of the proposed measure is equivalent with the objective functions of algorithms such as nonnegative matrix factorization, kernel K-means as well as spectral clustering. It serves as the theoretical foundation for designing algorithms for community detection. On the second issue, a semi-supervised spectral clustering algorithm is developed by exploring the equivalence relation via combining the nonnegative matrix factorization and spectral clustering. Different from the traditional semi-supervised algorithms, the partial supervision is integrated into the objective of the spectral algorithm. Finally, through extensive experiments on both artificial and real world networks, we demonstrate that the proposed method improves the accuracy of the traditional spectral algorithms in community detection.

Arctic lead detection using a waveform mixture algorithm from CryoSat-2 data

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S. Lee

2018-05-01

Full Text Available We propose a waveform mixture algorithm to detect leads from CryoSat-2 data, which is novel and different from the existing threshold-based lead detection methods. The waveform mixture algorithm adopts the concept of spectral mixture analysis, which is widely used in the field of hyperspectral image analysis. This lead detection method was evaluated with high-resolution (250 m MODIS images and showed comparable and promising performance in detecting leads when compared to the previous methods. The robustness of the proposed approach also lies in the fact that it does not require the rescaling of parameters (i.e., stack standard deviation, stack skewness, stack kurtosis, pulse peakiness, and backscatter σ0, as it directly uses L1B waveform data, unlike the existing threshold-based methods. Monthly lead fraction maps were produced by the waveform mixture algorithm, which shows interannual variability of recent sea ice cover during 2011–2016, excluding the summer season (i.e., June to September. We also compared the lead fraction maps to other lead fraction maps generated from previously published data sets, resulting in similar spatiotemporal patterns.

Intrusion-Aware Alert Validation Algorithm for Cooperative Distributed Intrusion Detection Schemes of Wireless Sensor Networks

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Young-Jae Song

2009-07-01

Full Text Available Existing anomaly and intrusion detection schemes of wireless sensor networks have mainly focused on the detection of intrusions. Once the intrusion is detected, an alerts or claims will be generated. However, any unidentified malicious nodes in the network could send faulty anomaly and intrusion claims about the legitimate nodes to the other nodes. Verifying the validity of such claims is a critical and challenging issue that is not considered in the existing cooperative-based distributed anomaly and intrusion detection schemes of wireless sensor networks. In this paper, we propose a validation algorithm that addresses this problem. This algorithm utilizes the concept of intrusion-aware reliability that helps to provide adequate reliability at a modest communication cost. In this paper, we also provide a security resiliency analysis of the proposed intrusion-aware alert validation algorithm.

A new approach to optic disc detection in human retinal images using the firefly algorithm.

Science.gov (United States)

Rahebi, Javad; Hardalaç, Fırat

2016-03-01

There are various methods and algorithms to detect the optic discs in retinal images. In recent years, much attention has been given to the utilization of the intelligent algorithms. In this paper, we present a new automated method of optic disc detection in human retinal images using the firefly algorithm. The firefly intelligent algorithm is an emerging intelligent algorithm that was inspired by the social behavior of fireflies. The population in this algorithm includes the fireflies, each of which has a specific rate of lighting or fitness. In this method, the insects are compared two by two, and the less attractive insects can be observed to move toward the more attractive insects. Finally, one of the insects is selected as the most attractive, and this insect presents the optimum response to the problem in question. Here, we used the light intensity of the pixels of the retinal image pixels instead of firefly lightings. The movement of these insects due to local fluctuations produces different light intensity values in the images. Because the optic disc is the brightest area in the retinal images, all of the insects move toward brightest area and thus specify the location of the optic disc in the image. The results of implementation show that proposed algorithm could acquire an accuracy rate of 100 % in DRIVE dataset, 95 % in STARE dataset, and 94.38 % in DiaRetDB1 dataset. The results of implementation reveal high capability and accuracy of proposed algorithm in the detection of the optic disc from retinal images. Also, recorded required time for the detection of the optic disc in these images is 2.13 s for DRIVE dataset, 2.81 s for STARE dataset, and 3.52 s for DiaRetDB1 dataset accordingly. These time values are average value.

Botnet Propagation Via Public Websited Detection Algorithm

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Jonas Juknius

2011-08-01

Full Text Available The networks of compromised and remotely controlled computers (bots are widely used in many Internet fraudulent activities, especially in the distributed denial of service attacks. Brute force gives enormous power to bot masters and makes botnet traffic visible; therefore, some countermeasures might be applied at early stages. Our study focuses on detecting botnet propagation via public websites. The provided algorithm might help with preventing from massive infections when popular web sites are compromised without spreading visual changes used for malware in botnets.Article in English

Detection of the arcuate fasciculus in congenital amusia depends on the tractography algorithm

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Joyce L Chen

2015-01-01

Full Text Available The advent of diffusion magnetic resonance imaging allows researchers to virtually dissect white matter fibre pathways in the brain in vivo. This, for example, allows us to characterize and quantify how fibre tracts differ across populations in health and disease, and change as a function of training. Based on diffusion MRI, prior literature reports the absence of the arcuate fasciculus (AF in some control individuals and as well in those with congenital amusia. The complete absence of such a major anatomical tract is surprising given the subtle impairments that characterize amusia. Thus, we hypothesize that failure to detect the AF in this population may relate to the tracking algorithm used, and is not necessarily reflective of their phenotype. Diffusion data in control and amusic individuals were analyzed using three different tracking algorithms: deterministic and probabilistic, the latter either modeling two or one fibre populations. Across the three algorithms, we replicate prior findings of a left greater than right AF volume, but do not find group differences or an interaction. We detect the AF in all individuals using the probabilistic 2-fibre model, however, tracking failed in some control and amusic individuals when deterministic tractography was applied. These findings show that the ability to detect the AF in our sample is dependent on the type of tractography algorithm. This raises the question of whether failure to detect the AF in prior studies may be unrelated to the underlying anatomy or phenotype.

Detection of the arcuate fasciculus in congenital amusia depends on the tractography algorithm.

Science.gov (United States)

Chen, Joyce L; Kumar, Sukhbinder; Williamson, Victoria J; Scholz, Jan; Griffiths, Timothy D; Stewart, Lauren

2015-01-01

The advent of diffusion magnetic resonance imaging (MRI) allows researchers to virtually dissect white matter fiber pathways in the brain in vivo. This, for example, allows us to characterize and quantify how fiber tracts differ across populations in health and disease, and change as a function of training. Based on diffusion MRI, prior literature reports the absence of the arcuate fasciculus (AF) in some control individuals and as well in those with congenital amusia. The complete absence of such a major anatomical tract is surprising given the subtle impairments that characterize amusia. Thus, we hypothesize that failure to detect the AF in this population may relate to the tracking algorithm used, and is not necessarily reflective of their phenotype. Diffusion data in control and amusic individuals were analyzed using three different tracking algorithms: deterministic and probabilistic, the latter either modeling two or one fiber populations. Across the three algorithms, we replicate prior findings of a left greater than right AF volume, but do not find group differences or an interaction. We detect the AF in all individuals using the probabilistic 2-fiber model, however, tracking failed in some control and amusic individuals when deterministic tractography was applied. These findings show that the ability to detect the AF in our sample is dependent on the type of tractography algorithm. This raises the question of whether failure to detect the AF in prior studies may be unrelated to the underlying anatomy or phenotype.

Development and testing of incident detection algorithms. Vol. 2, research methodology and detailed results.

Science.gov (United States)

1976-04-01

The development and testing of incident detection algorithms was based on Los Angeles and Minneapolis freeway surveillance data. Algorithms considered were based on times series and pattern recognition techniques. Attention was given to the effects o...

Optimal Seamline Detection for Orthoimage Mosaicking Based on DSM and Improved JPS Algorithm

Directory of Open Access Journals (Sweden)

Gang Chen

2018-05-01

Full Text Available Based on the digital surface model (DSM and jump point search (JPS algorithm, this study proposed a novel approach to detect the optimal seamline for orthoimage mosaicking. By threshold segmentation, DSM was first identified as ground regions and obstacle regions (e.g., buildings, trees, and cars. Then, the mathematical morphology method was used to make the edge of obstacles more prominent. Subsequently, the processed DSM was considered as a uniform-cost grid map, and the JPS algorithm was improved and employed to search for key jump points in the map. Meanwhile, the jump points would be evaluated according to an optimized function, finally generating a minimum cost path as the optimal seamline. Furthermore, the search strategy was modified to avoid search failure when the search map was completely blocked by obstacles in the search direction. Comparison of the proposed method and the Dijkstra’s algorithm was carried out based on two groups of image data with different characteristics. Results showed the following: (1 the proposed method could detect better seamlines near the centerlines of the overlap regions, crossing far fewer ground objects; (2 the efficiency and resource consumption were greatly improved since the improved JPS algorithm skips many image pixels without them being explicitly evaluated. In general, based on DSM, the proposed method combining threshold segmentation, mathematical morphology, and improved JPS algorithms was helpful for detecting the optimal seamline for orthoimage mosaicking.

Probability of failure of the watershed algorithm for peak detection in comprehensive two-dimensional chromatography

NARCIS (Netherlands)

Vivó-Truyols, G.; Janssen, H.-G.

2010-01-01

The watershed algorithm is the most common method used for peak detection and integration In two-dimensional chromatography However, the retention time variability in the second dimension may render the algorithm to fail A study calculating the probabilities of failure of the watershed algorithm was

Improving staff response to seizures on the epilepsy monitoring unit with online EEG seizure detection algorithms.

Science.gov (United States)

Rommens, Nicole; Geertsema, Evelien; Jansen Holleboom, Lisanne; Cox, Fieke; Visser, Gerhard

2018-05-11

User safety and the quality of diagnostics on the epilepsy monitoring unit (EMU) depend on reaction to seizures. Online seizure detection might improve this. While good sensitivity and specificity is reported, the added value above staff response is unclear. We ascertained the added value of two electroencephalograph (EEG) seizure detection algorithms in terms of additional detected seizures or faster detection time. EEG-video seizure recordings of people admitted to an EMU over one year were included, with a maximum of two seizures per subject. All recordings were retrospectively analyzed using Encevis EpiScan and BESA Epilepsy. Detection sensitivity and latency of the algorithms were compared to staff responses. False positive rates were estimated on 30 uninterrupted recordings (roughly 24 h per subject) of consecutive subjects admitted to the EMU. EEG-video recordings used included 188 seizures. The response rate of staff was 67%, of Encevis 67%, and of BESA Epilepsy 65%. Of the 62 seizures missed by staff, 66% were recognized by Encevis and 39% by BESA Epilepsy. The median latency was 31 s (staff), 10 s (Encevis), and 14 s (BESA Epilepsy). After correcting for walking time from the observation room to the subject, both algorithms detected faster than staff in 65% of detected seizures. The full recordings included 617 h of EEG. Encevis had a median false positive rate of 4.9 per 24 h and BESA Epilepsy of 2.1 per 24 h. EEG-video seizure detection algorithms may improve reaction to seizures by improving the total number of seizures detected and the speed of detection. The false positive rate is feasible for use in a clinical situation. Implementation of these algorithms might result in faster diagnostic testing and better observation during seizures. Copyright © 2018. Published by Elsevier Inc.

A Low-Complexity Joint Detection-Decoding Algorithm for Nonbinary LDPC-Coded Modulation Systems

OpenAIRE

Wang, Xuepeng; Bai, Baoming; Ma, Xiao

2010-01-01

In this paper, we present a low-complexity joint detection-decoding algorithm for nonbinary LDPC codedmodulation systems. The algorithm combines hard-decision decoding using the message-passing strategy with the signal detector in an iterative manner. It requires low computational complexity, offers good system performance and has a fast rate of decoding convergence. Compared to the q-ary sum-product algorithm (QSPA), it provides an attractive candidate for practical applications of q-ary LDP...

Shot Boundary Detection in Soccer Video using Twin-comparison Algorithm and Dominant Color Region

Directory of Open Access Journals (Sweden)

Matko Šarić

2008-06-01

Full Text Available The first step in generic video processing is temporal segmentation, i.e. shot boundary detection. Camera shot transitions can be either abrupt (e.g. cuts or gradual (e.g. fades, dissolves, wipes. Sports video is one of the most challenging domains for robust shot boundary detection. We proposed a shot boundary detection algorithm for soccer video based on the twin-comparison method and the absolute difference between frames in their ratios of dominant colored pixels to total number of pixels. With this approach the detection of gradual transitions is improved by decreasing the number of false positives caused by some camera operations. We also compared performances of our algorithm and the standard twin-comparison method.

Vibration-Based Damage Detection in Beams by Cooperative Coevolutionary Genetic Algorithm

Directory of Open Access Journals (Sweden)

Kittipong Boonlong

2014-03-01

Full Text Available Vibration-based damage detection, a nondestructive method, is based on the fact that vibration characteristics such as natural frequencies and mode shapes of structures are changed when the damage happens. This paper presents cooperative coevolutionary genetic algorithm (CCGA, which is capable for an optimization problem with a large number of decision variables, as the optimizer for the vibration-based damage detection in beams. In the CCGA, a minimized objective function is a numerical indicator of differences between vibration characteristics of the actual damage and those of the anticipated damage. The damage detection in a uniform cross-section cantilever beam, a uniform strength cantilever beam, and a uniform cross-section simply supported beam is used as the test problems. Random noise in the vibration characteristics is also considered in the damage detection. In the simulation analysis, the CCGA provides the superior solutions to those that use standard genetic algorithms presented in previous works, although it uses less numbers of the generated solutions in solution search. The simulation results reveal that the CCGA can efficiently identify the occurred damage in beams for all test problems including the damage detection in a beam with a large number of divided elements such as 300 elements.

A new comparison of hyperspectral anomaly detection algorithms for real-time applications

Science.gov (United States)

Díaz, María.; López, Sebastián.; Sarmiento, Roberto

2016-10-01

Due to the high spectral resolution that remotely sensed hyperspectral images provide, there has been an increasing interest in anomaly detection. The aim of anomaly detection is to stand over pixels whose spectral signature differs significantly from the background spectra. Basically, anomaly detectors mark pixels with a certain score, considering as anomalies those whose scores are higher than a threshold. Receiver Operating Characteristic (ROC) curves have been widely used as an assessment measure in order to compare the performance of different algorithms. ROC curves are graphical plots which illustrate the trade- off between false positive and true positive rates. However, they are limited in order to make deep comparisons due to the fact that they discard relevant factors required in real-time applications such as run times, costs of misclassification and the competence to mark anomalies with high scores. This last fact is fundamental in anomaly detection in order to distinguish them easily from the background without any posterior processing. An extensive set of simulations have been made using different anomaly detection algorithms, comparing their performances and efficiencies using several extra metrics in order to complement ROC curves analysis. Results support our proposal and demonstrate that ROC curves do not provide a good visualization of detection performances for themselves. Moreover, a figure of merit has been proposed in this paper which encompasses in a single global metric all the measures yielded for the proposed additional metrics. Therefore, this figure, named Detection Efficiency (DE), takes into account several crucial types of performance assessment that ROC curves do not consider. Results demonstrate that algorithms with the best detection performances according to ROC curves do not have the highest DE values. Consequently, the recommendation of using extra measures to properly evaluate performances have been supported and justified by

An Algorithm for Detection of DVB-T Signals Based on Their Second-Order Statistics

Directory of Open Access Journals (Sweden)

Pierre Jallon

2008-03-01

Full Text Available We propose in this paper a detection algorithm based on a cost function that jointly tests the correlation induced by the cyclic prefix and the fact that this correlation is time-periodic. In the first part of the paper, the cost function is introduced and some analytical results are given. In particular, the noise and multipath channel impacts on its values are theoretically analysed. In a second part of the paper, some asymptotic results are derived. A first exploitation of these results is used to build a detection test based on the false alarm probability. These results are also used to evaluate the impact of the number of cycle frequencies taken into account in the cost function on the detection performances. Thanks to numerical estimations, we have been able to estimate that the proposed algorithm detects DVB-T signals with an SNR of −12 dB. As a comparison, and in the same context, the detection algorithm proposed by the 802.22 WG in 2006 is able to detect these signals with an SNR of −8 dB.

An effective detection algorithm for region duplication forgery in digital images

Science.gov (United States)

Yavuz, Fatih; Bal, Abdullah; Cukur, Huseyin

2016-04-01

Powerful image editing tools are very common and easy to use these days. This situation may cause some forgeries by adding or removing some information on the digital images. In order to detect these types of forgeries such as region duplication, we present an effective algorithm based on fixed-size block computation and discrete wavelet transform (DWT). In this approach, the original image is divided into fixed-size blocks, and then wavelet transform is applied for dimension reduction. Each block is processed by Fourier Transform and represented by circle regions. Four features are extracted from each block. Finally, the feature vectors are lexicographically sorted, and duplicated image blocks are detected according to comparison metric results. The experimental results show that the proposed algorithm presents computational efficiency due to fixed-size circle block architecture.

A Time-Domain Structural Damage Detection Method Based on Improved Multiparticle Swarm Coevolution Optimization Algorithm

Directory of Open Access Journals (Sweden)

Shao-Fei Jiang

2014-01-01

Full Text Available Optimization techniques have been applied to structural health monitoring and damage detection of civil infrastructures for two decades. The standard particle swarm optimization (PSO is easy to fall into the local optimum and such deficiency also exists in the multiparticle swarm coevolution optimization (MPSCO. This paper presents an improved MPSCO algorithm (IMPSCO firstly and then integrates it with Newmark’s algorithm to localize and quantify the structural damage by using the damage threshold proposed. To validate the proposed method, a numerical simulation and an experimental study of a seven-story steel frame were employed finally, and a comparison was made between the proposed method and the genetic algorithm (GA. The results show threefold: (1 the proposed method not only is capable of localization and quantification of damage, but also has good noise-tolerance; (2 the damage location can be accurately detected using the damage threshold proposed in this paper; and (3 compared with the GA, the IMPSCO algorithm is more efficient and accurate for damage detection problems in general. This implies that the proposed method is applicable and effective in the community of damage detection and structural health monitoring.

The Automated Assessment of Postural Stability: Balance Detection Algorithm.

Science.gov (United States)

Napoli, Alessandro; Glass, Stephen M; Tucker, Carole; Obeid, Iyad

2017-12-01

Impaired balance is a common indicator of mild traumatic brain injury, concussion and musculoskeletal injury. Given the clinical relevance of such injuries, especially in military settings, it is paramount to develop more accurate and reliable on-field evaluation tools. This work presents the design and implementation of the automated assessment of postural stability (AAPS) system, for on-field evaluations following concussion. The AAPS is a computer system, based on inexpensive off-the-shelf components and custom software, that aims to automatically and reliably evaluate balance deficits, by replicating a known on-field clinical test, namely, the Balance Error Scoring System (BESS). The AAPS main innovation is its balance error detection algorithm that has been designed to acquire data from a Microsoft Kinect ® sensor and convert them into clinically-relevant BESS scores, using the same detection criteria defined by the original BESS test. In order to assess the AAPS balance evaluation capability, a total of 15 healthy subjects (7 male, 8 female) were required to perform the BESS test, while simultaneously being tracked by a Kinect 2.0 sensor and a professional-grade motion capture system (Qualisys AB, Gothenburg, Sweden). High definition videos with BESS trials were scored off-line by three experienced observers for reference scores. AAPS performance was assessed by comparing the AAPS automated scores to those derived by three experienced observers. Our results show that the AAPS error detection algorithm presented here can accurately and precisely detect balance deficits with performance levels that are comparable to those of experienced medical personnel. Specifically, agreement levels between the AAPS algorithm and the human average BESS scores ranging between 87.9% (single-leg on foam) and 99.8% (double-leg on firm ground) were detected. Moreover, statistically significant differences in balance scores were not detected by an ANOVA test with alpha equal to 0

A Robust Vision-based Runway Detection and Tracking Algorithm for Automatic UAV Landing

KAUST Repository

Abu Jbara, Khaled F.

2015-05-01

This work presents a novel real-time algorithm for runway detection and tracking applied to the automatic takeoff and landing of Unmanned Aerial Vehicles (UAVs). The algorithm is based on a combination of segmentation based region competition and the minimization of a specific energy function to detect and identify the runway edges from streaming video data. The resulting video-based runway position estimates are updated using a Kalman Filter, which can integrate other sensory information such as position and attitude angle estimates to allow a more robust tracking of the runway under turbulence. We illustrate the performance of the proposed lane detection and tracking scheme on various experimental UAV flights conducted by the Saudi Aerospace Research Center. Results show an accurate tracking of the runway edges during the landing phase under various lighting conditions. Also, it suggests that such positional estimates would greatly improve the positional accuracy of the UAV during takeoff and landing phases. The robustness of the proposed algorithm is further validated using Hardware in the Loop simulations with diverse takeoff and landing videos generated using a commercial flight simulator.

Detecting Hijacked Journals by Using Classification Algorithms.

Science.gov (United States)

Andoohgin Shahri, Mona; Jazi, Mohammad Davarpanah; Borchardt, Glenn; Dadkhah, Mehdi

2018-04-01

Invalid journals are recent challenges in the academic world and many researchers are unacquainted with the phenomenon. The number of victims appears to be accelerating. Researchers might be suspicious of predatory journals because they have unfamiliar names, but hijacked journals are imitations of well-known, reputable journals whose websites have been hijacked. Hijacked journals issue calls for papers via generally laudatory emails that delude researchers into paying exorbitant page charges for publication in a nonexistent journal. This paper presents a method for detecting hijacked journals by using a classification algorithm. The number of published articles exposing hijacked journals is limited and most of them use simple techniques that are limited to specific journals. Hence we needed to amass Internet addresses and pertinent data for analyzing this type of attack. We inspected the websites of 104 scientific journals by using a classification algorithm that used criteria common to reputable journals. We then prepared a decision tree that we used to test five journals we knew were authentic and five we knew were hijacked.

Robust and unobtrusive algorithm based on position independence for step detection

Science.gov (United States)

Qiu, KeCheng; Li, MengYang; Luo, YiHan

2018-04-01

Running is becoming one of the most popular exercises among the people, monitoring steps can help users better understand their running process and improve exercise efficiency. In this paper, we design and implement a robust and unobtrusive algorithm based on position independence for step detection under real environment. It applies Butterworth filter to suppress high frequency interference and then employs the projection based on mathematics to transform system to solve the problem of unknown position of smartphone. Finally, using sliding window to suppress the false peak. The algorithm was tested for eight participants on the Android 7.0 platform. In our experiments, the results show that the proposed algorithm can achieve desired effect in spite of device pose.

The Efficacy of Epidemic Algorithms on Detecting Node Replicas in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Narasimha Shashidhar

2015-12-01

Full Text Available A node replication attack against a wireless sensor network involves surreptitious efforts by an adversary to insert duplicate sensor nodes into the network while avoiding detection. Due to the lack of tamper-resistant hardware and the low cost of sensor nodes, launching replication attacks takes little effort to carry out. Naturally, detecting these replica nodes is a very important task and has been studied extensively. In this paper, we propose a novel distributed, randomized sensor duplicate detection algorithm called Discard to detect node replicas in group-deployed wireless sensor networks. Our protocol is an epidemic, self-organizing duplicate detection scheme, which exhibits emergent properties. Epidemic schemes have found diverse applications in distributed computing: load balancing, topology management, audio and video streaming, computing aggregate functions, failure detection, network and resource monitoring, to name a few. To the best of our knowledge, our algorithm is the first attempt at exploring the potential of this paradigm to detect replicas in a wireless sensor network. Through analysis and simulation, we show that our scheme achieves robust replica detection with substantially lower communication, computational and storage requirements than prior schemes in the literature.

Spatial-time-state fusion algorithm for defect detection through eddy current pulsed thermography

Science.gov (United States)

Xiao, Xiang; Gao, Bin; Woo, Wai Lok; Tian, Gui Yun; Xiao, Xiao Ting

2018-05-01

Eddy Current Pulsed Thermography (ECPT) has received extensive attention due to its high sensitive of detectability on surface and subsurface cracks. However, it remains as a difficult challenge in unsupervised detection as to identify defects without knowing any prior knowledge. This paper presents a spatial-time-state features fusion algorithm to obtain fully profile of the defects by directional scanning. The proposed method is intended to conduct features extraction by using independent component analysis (ICA) and automatic features selection embedding genetic algorithm. Finally, the optimal feature of each step is fused to obtain defects reconstruction by applying common orthogonal basis extraction (COBE) method. Experiments have been conducted to validate the study and verify the efficacy of the proposed method on blind defect detection.

Algorithms for detection of objects in image sequences captured from an airborne imaging system

Science.gov (United States)

Kasturi, Rangachar; Camps, Octavia; Tang, Yuan-Liang; Devadiga, Sadashiva; Gandhi, Tarak

1995-01-01

This research was initiated as a part of the effort at the NASA Ames Research Center to design a computer vision based system that can enhance the safety of navigation by aiding the pilots in detecting various obstacles on the runway during critical section of the flight such as a landing maneuver. The primary goal is the development of algorithms for detection of moving objects from a sequence of images obtained from an on-board video camera. Image regions corresponding to the independently moving objects are segmented from the background by applying constraint filtering on the optical flow computed from the initial few frames of the sequence. These detected regions are tracked over subsequent frames using a model based tracking algorithm. Position and velocity of the moving objects in the world coordinate is estimated using an extended Kalman filter. The algorithms are tested using the NASA line image sequence with six static trucks and a simulated moving truck and experimental results are described. Various limitations of the currently implemented version of the above algorithm are identified and possible solutions to build a practical working system are investigated.

Spectral CT with metal artifacts reduction software for improvement of tumor visibility in the vicinity of gold fiducial markers.

Science.gov (United States)

Brook, Olga R; Gourtsoyianni, Sofia; Brook, Alexander; Mahadevan, Anand; Wilcox, Carol; Raptopoulos, Vassilios

2012-06-01

To evaluate spectral computed tomography (CT) with metal artifacts reduction software (MARS) for reduction of metal artifacts associated with gold fiducial seeds. Thirteen consecutive patients with 37 fiducial seeds implanted for radiation therapy of abdominal lesions were included in this HIPAA-compliant, institutional review board-approved prospective study. Six patients were women (46%) and seven were men (54%). The mean age was 61.1 years (median, 58 years; range, 29-78 years). Spectral imaging was used for arterial phase CT. Images were reconstructed with and without MARS in axial, coronal, and sagittal planes. Two radiologists independently reviewed reconstructions and selected the best image, graded the visibility of the tumor, and assessed the amount of artifacts in all planes. A linear-weighted κ statistic and Wilcoxon signed-rank test were used to assess interobserver variability. Histogram analysis with the Kolmogorov-Smirnov test was used for objective evaluation of artifacts reduction. Fiducial seeds were placed in pancreas (n = 5), liver (n = 7), periportal lymph nodes (n = 1), and gallbladder bed (n = 1). MARS-reconstructed images received a better grade than those with standard reconstruction in 60% and 65% of patients by the first and second radiologist, respectively. Tumor visibility was graded higher with standard versus MARS reconstruction (grade, 3.7 ± 1.0 vs 2.8 ± 1.1; P = .001). Reduction of blooming was noted on MARS-reconstructed images (P = .01). Amount of artifacts, for both any and near field, was significantly smaller on sagittal and coronal MARS-reconstructed images than on standard reconstructions (P MARS-reconstructed images than on standard reconstructions (P MARS than with standard reconstruction in 35 of 37 patients (P MARS improved tumor visibility in the vicinity of gold fiducial seeds.

Cable Damage Detection System and Algorithms Using Time Domain Reflectometry

Energy Technology Data Exchange (ETDEWEB)

Clark, G A; Robbins, C L; Wade, K A; Souza, P R

2009-03-24

This report describes the hardware system and the set of algorithms we have developed for detecting damage in cables for the Advanced Development and Process Technologies (ADAPT) Program. This program is part of the W80 Life Extension Program (LEP). The system could be generalized for application to other systems in the future. Critical cables can undergo various types of damage (e.g. short circuits, open circuits, punctures, compression) that manifest as changes in the dielectric/impedance properties of the cables. For our specific problem, only one end of the cable is accessible, and no exemplars of actual damage are available. This work addresses the detection of dielectric/impedance anomalies in transient time domain reflectometry (TDR) measurements on the cables. The approach is to interrogate the cable using time domain reflectometry (TDR) techniques, in which a known pulse is inserted into the cable, and reflections from the cable are measured. The key operating principle is that any important cable damage will manifest itself as an electrical impedance discontinuity that can be measured in the TDR response signal. Machine learning classification algorithms are effectively eliminated from consideration, because only a small number of cables is available for testing; so a sufficient sample size is not attainable. Nonetheless, a key requirement is to achieve very high probability of detection and very low probability of false alarm. The approach is to compare TDR signals from possibly damaged cables to signals or an empirical model derived from reference cables that are known to be undamaged. This requires that the TDR signals are reasonably repeatable from test to test on the same cable, and from cable to cable. Empirical studies show that the repeatability issue is the 'long pole in the tent' for damage detection, because it is has been difficult to achieve reasonable repeatability. This one factor dominated the project. The two-step model

Automatic QRS complex detection algorithm designed for a novel wearable, wireless electrocardiogram recording device

DEFF Research Database (Denmark)

Saadi, Dorthe Bodholt; Egstrup, Kenneth; Branebjerg, Jens

2012-01-01

We have designed and optimized an automatic QRS complex detection algorithm for electrocardiogram (ECG) signals recorded with the DELTA ePatch platform. The algorithm is able to automatically switch between single-channel and multi-channel analysis mode. This preliminary study includes data from ...

Detection of Esophageal Fiducial Marker Displacement During Radiation Therapy With a 2-dimensional On-board Imager: Analysis of Internal Margin for Esophageal Cancer

International Nuclear Information System (INIS)

Fukada, Junichi; Hanada, Takashi; Kawaguchi, Osamu; Ohashi, Toshio; Takeuchi, Hiroya; Kitagawa, Yuko; Seki, Satoshi; Shiraishi, Yutaka; Ogata, Haruhiko; Shigematsu, Naoyuki

2013-01-01

Purpose: To quantify the interfraction displacement of esophageal fiducial markers for primary esophageal cancer radiation therapy. Methods and Materials: Orthogonal 2-dimensional (2D) matching records fused to vertebrae were analyzed in clinically staged T1/2N0 esophageal cancer patients undergoing endoscopic clipping as fiducial metal markers. Displacement of the markers between the digitally reconstructed radiographs and on-board kilovoltage images during radiation therapy was analyzed according to direction and esophageal site. Results: Forty-four patients, with 81 markers (10 proximal, 42 middle, and 29 distal), underwent 367 2D matching sessions during radiation therapy. The mean (SD) absolute marker displacement was 0.26 (0.30) cm in the right–left (RL), 0.50 (0.39) cm in the superior–inferior (SI), and 0.24 (0.21) cm in the anterior–posterior (AP) direction. Displacement was significantly larger in the SI than in the RL and AP directions (P<.0001). In the SI direction, mean absolute displacements of the distal, middle, and proximal esophagus were 0.67 (0.45) cm, 0.42 (0.32) cm, and 0.36 (0.30) cm, respectively. Distal esophagus displacement was significantly larger than those of the middle and proximal esophagus (P<.0001). The estimated internal margin to cover 95% of the cases was 0.75 cm in the RL and AP directions. In the SI direction, the margin was 1.25 cm for the proximal and middle esophagus and 1.75 cm for the distal esophagus. Conclusions: The magnitude of interfraction displacement of esophageal clips was larger in the SI direction, particularly in the distal esophagus, but substantial displacement was observed in other directions and at other esophageal sites. It is practical to take estimated movements into account with internal margins, even if vertebrae-based 2D matching is performed

Detection of esophageal fiducial marker displacement during radiation therapy with a 2-dimensional on-board imager: analysis of internal margin for esophageal cancer.

Science.gov (United States)

Fukada, Junichi; Hanada, Takashi; Kawaguchi, Osamu; Ohashi, Toshio; Takeuchi, Hiroya; Kitagawa, Yuko; Seki, Satoshi; Shiraishi, Yutaka; Ogata, Haruhiko; Shigematsu, Naoyuki

2013-03-15

To quantify the interfraction displacement of esophageal fiducial markers for primary esophageal cancer radiation therapy. Orthogonal 2-dimensional (2D) matching records fused to vertebrae were analyzed in clinically staged T1/2N0 esophageal cancer patients undergoing endoscopic clipping as fiducial metal markers. Displacement of the markers between the digitally reconstructed radiographs and on-board kilovoltage images during radiation therapy was analyzed according to direction and esophageal site. Forty-four patients, with 81 markers (10 proximal, 42 middle, and 29 distal), underwent 367 2D matching sessions during radiation therapy. The mean (SD) absolute marker displacement was 0.26 (0.30) cm in the right-left (RL), 0.50 (0.39) cm in the superior-inferior (SI), and 0.24 (0.21) cm in the anterior-posterior (AP) direction. Displacement was significantly larger in the SI than in the RL and AP directions (Pdisplacements of the distal, middle, and proximal esophagus were 0.67 (0.45) cm, 0.42 (0.32) cm, and 0.36 (0.30) cm, respectively. Distal esophagus displacement was significantly larger than those of the middle and proximal esophagus (Pinternal margin to cover 95% of the cases was 0.75 cm in the RL and AP directions. In the SI direction, the margin was 1.25 cm for the proximal and middle esophagus and 1.75 cm for the distal esophagus. The magnitude of interfraction displacement of esophageal clips was larger in the SI direction, particularly in the distal esophagus, but substantial displacement was observed in other directions and at other esophageal sites. It is practical to take estimated movements into account with internal margins, even if vertebrae-based 2D matching is performed. Copyright © 2013 Elsevier Inc. All rights reserved.

Airport Traffic Conflict Detection and Resolution Algorithm Evaluation

Science.gov (United States)

Jones, Denise R.; Chartrand, Ryan C.; Wilson, Sara R.; Commo, Sean A.; Ballard, Kathryn M.; Otero, Sharon D.; Barker, Glover D.

2016-01-01

Two conflict detection and resolution (CD&R) algorithms for the terminal maneuvering area (TMA) were evaluated in a fast-time batch simulation study at the National Aeronautics and Space Administration (NASA) Langley Research Center. One CD&R algorithm, developed at NASA, was designed to enhance surface situation awareness and provide cockpit alerts of potential conflicts during runway, taxi, and low altitude air-to-air operations. The second algorithm, Enhanced Traffic Situation Awareness on the Airport Surface with Indications and Alerts (SURF IA), was designed to increase flight crew awareness of the runway environment and facilitate an appropriate and timely response to potential conflict situations. The purpose of the study was to evaluate the performance of the aircraft-based CD&R algorithms during various runway, taxiway, and low altitude scenarios, multiple levels of CD&R system equipage, and various levels of horizontal position accuracy. Algorithm performance was assessed through various metrics including the collision rate, nuisance and missed alert rate, and alert toggling rate. The data suggests that, in general, alert toggling, nuisance and missed alerts, and unnecessary maneuvering occurred more frequently as the position accuracy was reduced. Collision avoidance was more effective when all of the aircraft were equipped with CD&R and maneuvered to avoid a collision after an alert was issued. In order to reduce the number of unwanted (nuisance) alerts when taxiing across a runway, a buffer is needed between the hold line and the alerting zone so alerts are not generated when an aircraft is behind the hold line. All of the results support RTCA horizontal position accuracy requirements for performing a CD&R function to reduce the likelihood and severity of runway incursions and collisions.

Evaluation of an infrared camera and X-ray system using implanted fiducials in patients with lung tumors for gated radiation therapy

International Nuclear Information System (INIS)

Willoughby, Twyla R.; Forbes, Alan R.; Buchholz, Daniel; Langen, Katja M.; Wagner, Thomas H.; Zeidan, Omar A.; Kupelian, Patrick A.; Meeks, Sanford L.

2006-01-01

Purpose: To report on the initial clinical use of a commercially available system to deliver gated treatment using implanted fiducials, in-room kV X-rays, and an infrared camera tracking system. Methods and Materials: ExacTrac Adaptive Gating from BrainLab is a localization system using infrared cameras and X-rays. Gating signals are the patient's breathing pattern obtained from infrared reflectors on the patient. kV X-rays of an implanted fiducial are synchronized to the breathing pattern. After localization and shift of the patient to isocenter, the breathing pattern is used to gate Radiation. Feasibility tests included localization accuracy, radiation output constancy, and dose distributions with gating. Clinical experience is reported on treatment of patients with small lung lesions. Results: Localization accuracy of a moving target with gating was 1.7 mm. Dose constancy measurements showed insignificant change in output with gating. Improvements of dose distributions on moving targets improved with gating. Eleven patients with lung lesions were implanted with 20 mm x 0.7 mm gold coil (Visicoil). The implanted fiducial was used to localize and treat the patients with gating. Treatment planning and repeat computed tomographic scans showed that the change in center of gross target volume (GTV) to implanted marker averaged 2.47 mm due in part to asymmetric tumor shrinkage. Conclusion: ExacTrac Adaptive Gating has been used to treat lung lesions. Initial system evaluation verified its accuracy and usability. Implanted fiducials are visible in X-rays and did not migrate

Autopiquer - a Robust and Reliable Peak Detection Algorithm for Mass Spectrometry.

Science.gov (United States)

Kilgour, David P A; Hughes, Sam; Kilgour, Samantha L; Mackay, C Logan; Palmblad, Magnus; Tran, Bao Quoc; Goo, Young Ah; Ernst, Robert K; Clarke, David J; Goodlett, David R

2017-02-01

We present a simple algorithm for robust and unsupervised peak detection by determining a noise threshold in isotopically resolved mass spectrometry data. Solving this problem will greatly reduce the subjective and time-consuming manual picking of mass spectral peaks and so will prove beneficial in many research applications. The Autopiquer approach uses autocorrelation to test for the presence of (isotopic) structure in overlapping windows across the spectrum. Within each window, a noise threshold is optimized to remove the most unstructured data, whilst keeping as much of the (isotopic) structure as possible. This algorithm has been successfully demonstrated for both peak detection and spectral compression on data from many different classes of mass spectrometer and for different sample types, and this approach should also be extendible to other types of data that contain regularly spaced discrete peaks. Graphical Abstract ᅟ.

An adaptive algorithm for the detection of microcalcifications in simulated low-dose mammography

Science.gov (United States)

Treiber, O.; Wanninger, F.; Führ, H.; Panzer, W.; Regulla, D.; Winkler, G.

2003-02-01

This paper uses the task of microcalcification detection as a benchmark problem to assess the potential for dose reduction in x-ray mammography. We present the results of a newly developed algorithm for detection of microcalcifications as a case study for a typical commercial film-screen system (Kodak Min-R 2000/2190). The first part of the paper deals with the simulation of dose reduction for film-screen mammography based on a physical model of the imaging process. Use of a more sensitive film-screen system is expected to result in additional smoothing of the image. We introduce two different models of that behaviour, called moderate and strong smoothing. We then present an adaptive, model-based microcalcification detection algorithm. Comparing detection results with ground-truth images obtained under the supervision of an expert radiologist allows us to establish the soundness of the detection algorithm. We measure the performance on the dose-reduced images in order to assess the loss of information due to dose reduction. It turns out that the smoothing behaviour has a strong influence on detection rates. For moderate smoothing, a dose reduction by 25% has no serious influence on the detection results, whereas a dose reduction by 50% already entails a marked deterioration of the performance. Strong smoothing generally leads to an unacceptable loss of image quality. The test results emphasize the impact of the more sensitive film-screen system and its characteristics on the problem of assessing the potential for dose reduction in film-screen mammography. The general approach presented in the paper can be adapted to fully digital mammography.

An adaptive algorithm for the detection of microcalcifications in simulated low-dose mammography

International Nuclear Information System (INIS)

Treiber, O; Wanninger, F; Fuehr, H; Panzer, W; Regulla, D; Winkler, G

2003-01-01

This paper uses the task of microcalcification detection as a benchmark problem to assess the potential for dose reduction in x-ray mammography. We present the results of a newly developed algorithm for detection of microcalcifications as a case study for a typical commercial film-screen system (Kodak Min-R 2000/2190). The first part of the paper deals with the simulation of dose reduction for film-screen mammography based on a physical model of the imaging process. Use of a more sensitive film-screen system is expected to result in additional smoothing of the image. We introduce two different models of that behaviour, called moderate and strong smoothing. We then present an adaptive, model-based microcalcification detection algorithm. Comparing detection results with ground-truth images obtained under the supervision of an expert radiologist allows us to establish the soundness of the detection algorithm. We measure the performance on the dose-reduced images in order to assess the loss of information due to dose reduction. It turns out that the smoothing behaviour has a strong influence on detection rates. For moderate smoothing, a dose reduction by 25% has no serious influence on the detection results, whereas a dose reduction by 50% already entails a marked deterioration of the performance. Strong smoothing generally leads to an unacceptable loss of image quality. The test results emphasize the impact of the more sensitive film-screen system and its characteristics on the problem of assessing the potential for dose reduction in film-screen mammography. The general approach presented in the paper can be adapted to fully digital mammography

Rapid Change Detection Algorithm for Disaster Management

Science.gov (United States)

Michel, U.; Thunig, H.; Ehlers, M.; Reinartz, P.

2012-07-01

This paper focuses on change detection applications in areas where catastrophic events took place which resulted in rapid destruction especially of manmade objects. Standard methods for automated change detection prove not to be sufficient; therefore a new method was developed and tested. The presented method allows a fast detection and visualization of change in areas of crisis or catastrophes. While often new methods of remote sensing are developed without user oriented aspects, organizations and authorities are not able to use these methods because of absence of remote sensing know how. Therefore a semi-automated procedure was developed. Within a transferable framework, the developed algorithm can be implemented for a set of remote sensing data among different investigation areas. Several case studies are the base for the retrieved results. Within a coarse dividing into statistical parts and the segmentation in meaningful objects, the framework is able to deal with different types of change. By means of an elaborated Temporal Change Index (TCI) only panchromatic datasets are used to extract areas which are destroyed, areas which were not affected and in addition areas where rebuilding has already started.

Identifying Time Measurement Tampering in the Traversal Time and Hop Count Analysis (TTHCA Wormhole Detection Algorithm

Directory of Open Access Journals (Sweden)

Jonny Karlsson

2013-05-01

Full Text Available Traversal time and hop count analysis (TTHCA is a recent wormhole detection algorithm for mobile ad hoc networks (MANET which provides enhanced detection performance against all wormhole attack variants and network types. TTHCA involves each node measuring the processing time of routing packets during the route discovery process and then delivering the measurements to the source node. In a participation mode (PM wormhole where malicious nodes appear in the routing tables as legitimate nodes, the time measurements can potentially be altered so preventing TTHCA from successfully detecting the wormhole. This paper analyses the prevailing conditions for time tampering attacks to succeed for PM wormholes, before introducing an extension to the TTHCA detection algorithm called ∆T Vector which is designed to identify time tampering, while preserving low false positive rates. Simulation results confirm that the ∆T Vector extension is able to effectively detect time tampering attacks, thereby providing an important security enhancement to the TTHCA algorithm.

Fiducial and differential cross sections of Higgs boson production measured in the four-lepton decay channel in $\\boldsymbol{pp}$ collisions at $\\boldsymbol{\\sqrt{s}}$ = 8 TeV  with the ATLAS detector

CERN Document Server

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Gianotti, Fabiola; Gibbard, Bruce; Gibson, Stephen; Gilchriese, Murdock; Gillam, Thomas; Gillberg, Dag; Gilles, Geoffrey; Gingrich, Douglas; Giokaris, Nikos; Giordani, MarioPaolo; Giordano, Raffaele; Giorgi, Filippo Maria; Giorgi, Francesco Michelangelo; Giraud, Pierre-Francois; Giugni, Danilo; Giuliani, Claudia; Giulini, Maddalena; Gjelsten, Børge Kile; Gkaitatzis, Stamatios; Gkialas, Ioannis; Gladilin, Leonid; Glasman, Claudia; Glatzer, Julian; Glaysher, Paul; Glazov, Alexandre; Glonti, George; Goblirsch-Kolb, Maximilian; Goddard, Jack Robert; Godlewski, Jan; Goeringer, Christian; Goldfarb, Steven; Golling, Tobias; Golubkov, Dmitry; Gomes, Agostinho; Gomez Fajardo, Luz Stella; Gonçalo, Ricardo; Goncalves Pinto Firmino Da Costa, Joao; Gonella, Laura; González de la Hoz, Santiago; Gonzalez Parra, Garoe; Gonzalez-Sevilla, Sergio; Goossens, Luc; Gorbounov, Petr Andreevich; Gordon, Howard; Gorelov, Igor; Gorini, Benedetto; Gorini, Edoardo; Gorišek, Andrej; Gornicki, Edward; Goshaw, Alfred; Gössling, Claus; Gostkin, Mikhail Ivanovitch; Gouighri, Mohamed; Goujdami, Driss; Goulette, Marc Phillippe; Goussiou, Anna; Goy, Corinne; Gozpinar, Serdar; Grabas, Herve Marie Xavier; Graber, Lars; Grabowska-Bold, Iwona; Grafström, Per; Grahn, Karl-Johan; Gramling, Johanna; Gramstad, Eirik; Grancagnolo, Sergio; Grassi, Valerio; Gratchev, Vadim; Gray, Heather; Graziani, Enrico; Grebenyuk, Oleg; Greenwood, Zeno Dixon; Gregersen, Kristian; Gregor, Ingrid-Maria; Grenier, Philippe; Griffiths, Justin; Grillo, Alexander; Grimm, Kathryn; Grinstein, Sebastian; Gris, Philippe Luc Yves; Grishkevich, Yaroslav; Grivaz, Jean-Francois; Grohs, Johannes Philipp; Grohsjean, Alexander; Gross, Eilam; Grosse-Knetter, Joern; Grossi, Giulio Cornelio; Groth-Jensen, Jacob; Grout, Zara Jane; Guan, Liang; Guenther, Jaroslav; Guescini, Francesco; Guest, Daniel; Gueta, Orel; Guicheney, Christophe; Guido, Elisa; Guillemin, Thibault; Guindon, Stefan; Gul, Umar; Gumpert, Christian; Guo, Jun; Gupta, Shaun; Gutierrez, Phillip; Gutierrez Ortiz, Nicolas Gilberto; Gutschow, Christian; Guttman, Nir; Guyot, Claude; Gwenlan, Claire; Gwilliam, Carl; Haas, Andy; Haber, Carl; Hadavand, Haleh Khani; Haddad, Nacim; Haefner, Petra; Hageböck, Stephan; Hajduk, Zbigniew; Hakobyan, Hrachya; Haleem, Mahsana; Hall, David; Halladjian, Garabed; Hamacher, Klaus; Hamal, Petr; Hamano, Kenji; Hamer, Matthias; Hamilton, Andrew; Hamilton, Samuel; Hamity, Guillermo Nicolas; Hamnett, Phillip George; Han, Liang; Hanagaki, Kazunori; Hanawa, Keita; Hance, Michael; Hanke, Paul; Hanna, Remie; Hansen, Jørgen Beck; Hansen, Jorn Dines; Hansen, Peter Henrik; Hara, Kazuhiko; Hard, Andrew; Harenberg, Torsten; Hariri, Faten; Harkusha, Siarhei; Harper, Devin; Harrington, Robert; Harris, Orin; Harrison, Paul Fraser; Hartjes, Fred; Hasegawa, Makoto; Hasegawa, Satoshi; Hasegawa, Yoji; Hasib, A; Hassani, Samira; Haug, Sigve; Hauschild, Michael; Hauser, Reiner; Havranek, Miroslav; Hawkes, Christopher; Hawkings, Richard John; Hawkins, Anthony David; Hayashi, Takayasu; Hayden, Daniel; Hays, Chris; Hayward, Helen; Haywood, Stephen; Head, Simon; Heck, Tobias; Hedberg, Vincent; Heelan, Louise; Heim, Sarah; Heim, Timon; Heinemann, Beate; Heinrich, Lukas; Hejbal, Jiri; Helary, Louis; Heller, Claudio; Heller, Matthieu; Hellman, Sten; Hellmich, Dennis; Helsens, Clement; Henderson, James; Henderson, Robert; Heng, Yang; Hengler, Christopher; Henrichs, Anna; Henriques Correia, Ana Maria; Henrot-Versille, Sophie; Herbert, Geoffrey Henry; Hernández Jiménez, Yesenia; Herrberg-Schubert, Ruth; Herten, Gregor; Hertenberger, Ralf; Hervas, Luis; Hesketh, Gavin Grant; Hessey, Nigel; Hickling, Robert; Higón-Rodriguez, Emilio; Hill, Ewan; Hill, John; Hiller, Karl Heinz; Hillert, Sonja; Hillier, Stephen; Hinchliffe, Ian; Hines, Elizabeth; Hirose, Minoru; Hirschbuehl, Dominic; Hobbs, John; Hod, Noam; Hodgkinson, Mark; Hodgson, Paul; Hoecker, Andreas; Hoeferkamp, Martin; Hoenig, Friedrich; Hoffman, Julia; Hoffmann, Dirk; Hofmann, Julia Isabell; Hohlfeld, Marc; Holmes, Tova Ray; Hong, Tae Min; Hooft van Huysduynen, Loek; Hopkins, Walter; Horii, Yasuyuki; Hostachy, Jean-Yves; Hou, Suen; Hoummada, Abdeslam; Howard, Jacob; Howarth, James; Hrabovsky, Miroslav; Hristova, Ivana; Hrivnac, Julius; Hryn'ova, Tetiana; Hsu, Catherine; Hsu, Pai-hsien Jennifer; Hsu, Shih-Chieh; Hu, Diedi; Hu, Xueye; Huang, Yanping; Hubacek, Zdenek; Hubaut, Fabrice; Huegging, Fabian; Huffman, Todd Brian; Hughes, Emlyn; Hughes, Gareth; Huhtinen, Mika; Hülsing, Tobias Alexander; Hurwitz, Martina; Huseynov, Nazim; Huston, Joey; Huth, John; Iacobucci, Giuseppe; Iakovidis, Georgios; Ibragimov, Iskander; Iconomidou-Fayard, Lydia; Ideal, Emma; Idrissi, Zineb; Iengo, Paolo; Igonkina, Olga; Iizawa, Tomoya; Ikegami, Yoichi; Ikematsu, Katsumasa; Ikeno, Masahiro; Ilchenko, Iurii; Iliadis, Dimitrios; Ilic, Nikolina; Inamaru, Yuki; Ince, Tayfun; Ioannou, Pavlos; Iodice, Mauro; Iordanidou, Kalliopi; Ippolito, Valerio; Irles Quiles, Adrian; Isaksson, Charlie; Ishino, Masaya; Ishitsuka, Masaki; Ishmukhametov, Renat; Issever, Cigdem; Istin, Serhat; Iturbe Ponce, Julia Mariana; Iuppa, Roberto; Ivarsson, Jenny; Iwanski, Wieslaw; Iwasaki, Hiroyuki; Izen, Joseph; Izzo, Vincenzo; Jackson, Brett; Jackson, Matthew; Jackson, Paul; Jaekel, Martin; Jain, Vivek; Jakobs, Karl; Jakobsen, Sune; Jakoubek, Tomas; Jakubek, Jan; Jamin, David Olivier; Jana, Dilip; Jansen, Eric; Jansen, Hendrik; Janssen, Jens; Janus, Michel; Jarlskog, Göran; Javadov, Namig; Javůrek, Tomáš; Jeanty, Laura; Jejelava, Juansher; Jeng, Geng-yuan; Jennens, David; Jenni, Peter; Jentzsch, Jennifer; Jeske, Carl; Jézéquel, Stéphane; Ji, Haoshuang; Jia, Jiangyong; Jiang, Yi; Jimenez Belenguer, Marcos; Jin, Shan; Jinaru, Adam; Jinnouchi, Osamu; Joergensen, Morten Dam; Johansson, Erik; Johansson, Per; Johns, Kenneth; Jon-And, Kerstin; Jones, Graham; Jones, Roger; Jones, Tim; Jongmanns, Jan; Jorge, Pedro; Joshi, Kiran Daniel; Jovicevic, Jelena; Ju, Xiangyang; Jung, Christian; Jungst, Ralph Markus; Jussel, Patrick; Juste Rozas, Aurelio; Kaci, Mohammed; Kaczmarska, Anna; Kado, Marumi; Kagan, Harris; Kagan, Michael; Kajomovitz, Enrique; Kalderon, Charles William; Kama, Sami; Kamenshchikov, Andrey; Kanaya, Naoko; Kaneda, Michiru; Kaneti, Steven; Kantserov, Vadim; Kanzaki, Junichi; Kaplan, Benjamin; Kapliy, Anton; Kar, Deepak; Karakostas, Konstantinos; Karastathis, Nikolaos; Kareem, Mohammad Jawad; Karnevskiy, Mikhail; Karpov, Sergey; Karpova, Zoya; Karthik, Krishnaiyengar; Kartvelishvili, Vakhtang; Karyukhin, Andrey; Kashif, Lashkar; Kasieczka, Gregor; Kass, Richard; Kastanas, Alex; Kataoka, Yousuke; Katre, Akshay; Katzy, Judith; Kaushik, Venkatesh; Kawagoe, Kiyotomo; Kawamoto, Tatsuo; Kawamura, Gen; Kazama, Shingo; Kazanin, Vassili; Kazarinov, Makhail; Keeler, Richard; Kehoe, Robert; Keil, Markus; Keller, John; Kempster, Jacob Julian; Keoshkerian, Houry; Kepka, Oldrich; Kerševan, Borut Paul; Kersten, Susanne; Kessoku, Kohei; Keung, Justin; Khalil-zada, Farkhad; Khandanyan, Hovhannes; Khanov, Alexander; Khodinov, Alexander; Khomich, Andrei; Khoo, Teng Jian; Khoriauli, Gia; Khoroshilov, Andrey; Khovanskiy, Valery; Khramov, Evgeniy; Khubua, Jemal; Kim, Hee Yeun; Kim, Hyeon Jin; Kim, Shinhong; Kimura, Naoki; Kind, Oliver; King, Barry; King, Matthew; King, Robert Steven Beaufoy; King, Samuel Burton; Kirk, Julie; Kiryunin, Andrey; Kishimoto, Tomoe; Kisielewska, Danuta; Kiss, Florian; Kittelmann, Thomas; Kiuchi, Kenji; Kladiva, Eduard; Klein, Max; Klein, Uta; Kleinknecht, Konrad; Klimek, Pawel; Klimentov, Alexei; Klingenberg, Reiner; Klinger, Joel Alexander; Klioutchnikova, Tatiana; Klok, Peter; Kluge, Eike-Erik; Kluit, Peter; Kluth, Stefan; Kneringer, Emmerich; Knoops, Edith; Knue, Andrea; Kobayashi, Dai; Kobayashi, Tomio; Kobel, Michael; Kocian, Martin; Kodys, Peter; Koevesarki, Peter; Koffas, Thomas; Koffeman, Els; Kogan, Lucy Anne; Kohlmann, Simon; Kohout, Zdenek; Kohriki, Takashi; Koi, Tatsumi; Kolanoski, Hermann; Koletsou, Iro; Koll, James; Komar, Aston; Komori, Yuto; Kondo, Takahiko; Kondrashova, Nataliia; Köneke, Karsten; König, Adriaan; König, Sebastian; Kono, Takanori; Konoplich, Rostislav; Konstantinidis, Nikolaos; Kopeliansky, Revital; Koperny, Stefan; Köpke, Lutz; Kopp, Anna Katharina; Korcyl, Krzysztof; Kordas, Kostantinos; Korn, Andreas; Korol, Aleksandr; Korolkov, Ilya; Korolkova, Elena; Korotkov, Vladislav; Kortner, Oliver; Kortner, Sandra; Kostyukhin, Vadim; Kotov, Vladislav; Kotwal, Ashutosh; Kourkoumelis, Christine; Kouskoura, Vasiliki; Koutsman, Alex; Kowalewski, Robert Victor; Kowalski, Tadeusz; Kozanecki, Witold; Kozhin, Anatoly; Kral, Vlastimil; Kramarenko, Viktor; Kramberger, Gregor; Krasnopevtsev, Dimitriy; Krasznahorkay, Attila; Kraus, Jana; Kravchenko, Anton; Kreiss, Sven; Kretz, Moritz; Kretzschmar, Jan; Kreutzfeldt, Kristof; Krieger, Peter; Kroeninger, Kevin; Kroha, Hubert; Kroll, Joe; Kroseberg, Juergen; Krstic, Jelena; Kruchonak, Uladzimir; Krüger, Hans; Kruker, Tobias; Krumnack, Nils; Krumshteyn, Zinovii; Kruse, Amanda; Kruse, Mark; Kruskal, Michael; Kubota, Takashi; Kuday, Sinan; Kuehn, Susanne; Kugel, Andreas; Kuhl, Andrew; Kuhl, Thorsten; Kukhtin, Victor; Kulchitsky, Yuri; Kuleshov, Sergey; Kuna, Marine; Kunkle, Joshua; Kupco, Alexander; Kurashige, Hisaya; Kurochkin, Yurii; Kurumida, Rie; Kus, Vlastimil; Kuwertz, Emma Sian; Kuze, Masahiro; Kvita, Jiri; La Rosa, Alessandro; La Rotonda, Laura; Lacasta, Carlos; Lacava, Francesco; Lacey, James; Lacker, Heiko; Lacour, Didier; Lacuesta, Vicente Ramón; Ladygin, Evgueni; Lafaye, Remi; Laforge, Bertrand; Lagouri, Theodota; Lai, Stanley; Laier, Heiko; Lambourne, Luke; Lammers, Sabine; Lampen, Caleb; Lampl, Walter; Lançon, Eric; Landgraf, Ulrich; Landon, Murrough; Lang, Valerie Susanne; Lankford, Andrew; Lanni, Francesco; Lantzsch, Kerstin; Laplace, Sandrine; Lapoire, Cecile; Laporte, Jean-Francois; Lari, Tommaso; Lasagni Manghi, Federico; Lassnig, Mario; Laurelli, Paolo; Lavrijsen, Wim; Law, Alexander; Laycock, Paul; Le Dortz, Olivier; Le Guirriec, Emmanuel; Le Menedeu, Eve; LeCompte, Thomas; Ledroit-Guillon, Fabienne Agnes Marie; Lee, Claire Alexandra; Lee, Hurng-Chun; Lee, Jason; Lee, Shih-Chang; Lee, Lawrence; Lefebvre, Guillaume; Lefebvre, Michel; Legger, Federica; Leggett, Charles; Lehan, Allan; Lehmacher, Marc; Lehmann Miotto, Giovanna; Lei, Xiaowen; Leight, William Axel; Leisos, Antonios; Leister, Andrew Gerard; Leite, Marco Aurelio Lisboa; Leitner, Rupert; Lellouch, Daniel; Lemmer, Boris; Leney, Katharine; Lenz, Tatjana; Lenzen, Georg; Lenzi, Bruno; Leone, Robert; Leone, Sandra; Leonidopoulos, Christos; Leontsinis, Stefanos; Leroy, Claude; Lester, Christopher; Lester, Christopher Michael; Levchenko, Mikhail; Levêque, Jessica; Levin, Daniel; Levinson, Lorne; Levy, Mark; Lewis, Adrian; Lewis, George; Leyko, Agnieszka; Leyton, Michael; Li, Bing; Li, Bo; Li, Haifeng; Li, Ho Ling; Li, Lei; Li, Liang; Li, Shu; Li, Yichen; Liang, Zhijun; Liao, Hongbo; Liberti, Barbara; Lichard, Peter; Lie, Ki; Liebal, Jessica; Liebig, Wolfgang; Limbach, Christian; Limosani, Antonio; Lin, Simon; Lin, Tai-Hua; Linde, Frank; Lindquist, Brian Edward; Linnemann, James; Lipeles, Elliot; Lipniacka, Anna; Lisovyi, Mykhailo; Liss, Tony; Lissauer, David; Lister, Alison; Litke, Alan; Liu, Bo; Liu, Dong; Liu, Jianbei; Liu, Kun; Liu, Lulu; Liu, Miaoyuan; Liu, Minghui; Liu, Yanwen; Livan, Michele; Livermore, Sarah; Lleres, Annick; Llorente Merino, Javier; Lloyd, Stephen; Lo Sterzo, Francesco; Lobodzinska, Ewelina; Loch, Peter; Lockman, William; Loddenkoetter, Thomas; Loebinger, Fred; Loevschall-Jensen, Ask Emil; Loginov, Andrey; Lohse, Thomas; Lohwasser, Kristin; Lokajicek, Milos; Lombardo, Vincenzo Paolo; Long, Brian Alexander; Long, Jonathan; Long, Robin Eamonn; Lopes, Lourenco; Lopez Mateos, David; Lopez Paredes, Brais; Lopez Paz, Ivan; Lorenz, Jeanette; Lorenzo Martinez, Narei; Losada, Marta; Loscutoff, Peter; Lou, XinChou; Lounis, Abdenour; Love, Jeremy; Love, Peter; Lowe, Andrew; Lu, Feng; Lu, Nan; Lubatti, Henry; Luci, Claudio; Lucotte, Arnaud; Luehring, Frederick; Lukas, Wolfgang; Luminari, Lamberto; Lundberg, Olof; Lund-Jensen, Bengt; Lungwitz, Matthias; Lynn, David; Lysak, Roman; Lytken, Else; Ma, Hong; Ma, Lian Liang; Maccarrone, Giovanni; Macchiolo, Anna; Machado Miguens, Joana; Macina, Daniela; Madaffari, Daniele; Madar, Romain; Maddocks, Harvey Jonathan; Mader, Wolfgang; Madsen, Alexander; Maeno, Mayuko; Maeno, Tadashi; Maevskiy, Artem; Magradze, Erekle; Mahboubi, Kambiz; Mahlstedt, Joern; Mahmoud, Sara; Maiani, Camilla; Maidantchik, Carmen; Maier, Andreas Alexander; Maio, Amélia; Majewski, Stephanie; Makida, Yasuhiro; Makovec, Nikola; Mal, Prolay; Malaescu, Bogdan; Malecki, Pawel; Maleev, Victor; Malek, Fairouz; Mallik, Usha; Malon, David; Malone, Caitlin; Maltezos, Stavros; Malyshev, Vladimir; Malyukov, Sergei; Mamuzic, Judita; Mancini, Giada; Mandelli, Beatrice; Mandelli, Luciano; Mandić, Igor; Mandrysch, Rocco; Maneira, José; Manfredini, Alessandro; Manhaes de Andrade Filho, Luciano; Manjarres Ramos, Joany Andreina; Mann, Alexander; Manning, Peter; Manousakis-Katsikakis, Arkadios; Mansoulie, Bruno; Mantifel, Rodger; Mapelli, Livio; March, Luis; Marchand, Jean-Francois; Marchiori, Giovanni; Marcisovsky, Michal; Marino, Christopher; Marjanovic, Marija; Marques, Carlos; Marroquim, Fernando; Marsden, Stephen Philip; Marshall, Zach; Marti, Lukas Fritz; Marti-Garcia, Salvador; Martin, Brian; Martin, Brian Thomas; Martin, Tim; Martin, Victoria Jane; Martin dit Latour, Bertrand; Martinez, Homero; Martinez, Mario; Martin-Haugh, Stewart; Martyniuk, Alex; Marx, Marilyn; Marzano, Francesco; Marzin, Antoine; Masetti, Lucia; Mashimo, Tetsuro; Mashinistov, Ruslan; Masik, Jiri; Maslennikov, Alexey; Massa, Ignazio; Massa, Lorenzo; Massol, Nicolas; Mastrandrea, Paolo; Mastroberardino, Anna; Masubuchi, Tatsuya; Mättig, Peter; Mattmann, Johannes; Maurer, Julien; Maxfield, Stephen; Maximov, Dmitriy; Mazini, Rachid; Mazzaferro, Luca; Mc Goldrick, Garrin; Mc Kee, Shawn Patrick; McCarn, Allison; McCarthy, Robert; McCarthy, Tom; McCubbin, Norman; McFarlane, Kenneth; Mcfayden, Josh; Mchedlidze, Gvantsa; McMahon, Steve; McPherson, Robert; Mechnich, Joerg; Medinnis, Michael; Meehan, Samuel; Mehlhase, Sascha; Mehta, Andrew; Meier, Karlheinz; Meineck, Christian; Meirose, Bernhard; Melachrinos, Constantinos; Mellado Garcia, Bruce Rafael; Meloni, Federico; Mengarelli, Alberto; Menke, Sven; Meoni, Evelin; Mercurio, Kevin Michael; Mergelmeyer, Sebastian; Meric, Nicolas; Mermod, Philippe; Merola, Leonardo; Meroni, Chiara; Merritt, Frank; Merritt, Hayes; Messina, Andrea; Metcalfe, Jessica; Mete, Alaettin Serhan; Meyer, Carsten; Meyer, Christopher; Meyer, Jean-Pierre; Meyer, Jochen; Middleton, Robin; Migas, Sylwia; Mijović, Liza; Mikenberg, Giora; Mikestikova, Marcela; Mikuž, Marko; Milic, Adriana; Miller, David; Mills, Corrinne; Milov, Alexander; Milstead, David; Milstein, Dmitry; Minaenko, Andrey; Minami, Yuto; Minashvili, Irakli; Mincer, Allen; Mindur, Bartosz; Mineev, Mikhail; Ming, Yao; Mir, Lluisa-Maria; Mirabelli, Giovanni; Mitani, Takashi; Mitrevski, Jovan; Mitsou, Vasiliki A; Mitsui, Shingo; Miucci, Antonio; Miyagawa, Paul; Mjörnmark, Jan-Ulf; Moa, Torbjoern; Mochizuki, Kazuya; Mohapatra, Soumya; Mohr, Wolfgang; Molander, Simon; Moles-Valls, Regina; Mönig, Klaus; Monini, Caterina; Monk, James; Monnier, Emmanuel; Montejo Berlingen, Javier; Monticelli, Fernando; Monzani, Simone; Moore, Roger; Morange, Nicolas; Moreno, Deywis; Moreno Llácer, María; Morettini, Paolo; Morgenstern, Marcus; Morii, Masahiro; Moritz, Sebastian; Morley, Anthony Keith; Mornacchi, Giuseppe; Morris, John; Morvaj, Ljiljana; Moser, Hans-Guenther; Mosidze, Maia; Moss, Josh; Motohashi, Kazuki; Mount, Richard; Mountricha, Eleni; Mouraviev, Sergei; Moyse, Edward; Muanza, Steve; Mudd, Richard; Mueller, Felix; Mueller, James; Mueller, Klemens; Mueller, Thibaut; Mueller, Timo; Muenstermann, Daniel; Munwes, Yonathan; Murillo Quijada, Javier Alberto; Murray, Bill; Musheghyan, Haykuhi; Musto, Elisa; Myagkov, Alexey; Myska, Miroslav; Nackenhorst, Olaf; Nadal, Jordi; Nagai, Koichi; Nagai, Ryo; Nagai, Yoshikazu; Nagano, Kunihiro; Nagarkar, Advait; Nagasaka, Yasushi; Nagel, Martin; Nairz, Armin Michael; Nakahama, Yu; Nakamura, Koji; Nakamura, Tomoaki; Nakano, Itsuo; Namasivayam, Harisankar; Nanava, Gizo; Narayan, Rohin; Nattermann, Till; Naumann, Thomas; Navarro, Gabriela; Nayyar, Ruchika; Neal, Homer; Nechaeva, Polina; Neep, Thomas James; Nef, Pascal Daniel; Negri, Andrea; Negri, Guido; Negrini, Matteo; Nektarijevic, Snezana; Nellist, Clara; Nelson, Andrew; Nelson, Timothy Knight; Nemecek, Stanislav; Nemethy, Peter; Nepomuceno, Andre Asevedo; Nessi, Marzio; Neubauer, Mark; Neumann, Manuel; Neves, Ricardo; Nevski, Pavel; Newman, Paul; Nguyen, Duong Hai; Nickerson, Richard; Nicolaidou, Rosy; Nicquevert, Bertrand; Nielsen, Jason; Nikiforou, Nikiforos; Nikiforov, Andriy; Nikolaenko, Vladimir; Nikolic-Audit, Irena; Nikolics, Katalin; Nikolopoulos, Konstantinos; Nilsson, Paul; Ninomiya, Yoichi; Nisati, Aleandro; Nisius, Richard; Nobe, Takuya; Nodulman, Lawrence; Nomachi, Masaharu; Nomidis, Ioannis; Norberg, Scarlet; Nordberg, Markus; Novgorodova, Olga; Nowak, Sebastian; Nozaki, Mitsuaki; Nozka, Libor; Ntekas, Konstantinos; Nunes Hanninger, Guilherme; Nunnemann, Thomas; Nurse, Emily; Nuti, Francesco; O'Brien, Brendan Joseph; O'grady, Fionnbarr; O'Neil, Dugan; O'Shea, Val; Oakham, Gerald; Oberlack, Horst; Obermann, Theresa; Ocariz, Jose; Ochi, Atsuhiko; Ochoa, Ines; Oda, Susumu; Odaka, Shigeru; Ogren, Harold; Oh, Alexander; Oh, Seog; Ohm, Christian; Ohman, Henrik; Okamura, Wataru; Okawa, Hideki; Okumura, Yasuyuki; Okuyama, Toyonobu; Olariu, Albert; Olchevski, Alexander; Olivares Pino, Sebastian Andres; Oliveira Damazio, Denis; Oliver Garcia, Elena; Olszewski, Andrzej; Olszowska, Jolanta; Onofre, António; Onyisi, Peter; Oram, Christopher; Oreglia, Mark; Oren, Yona; Orestano, Domizia; Orlando, Nicola; Oropeza Barrera, Cristina; Orr, Robert; Osculati, Bianca; Ospanov, Rustem; Otero y Garzon, Gustavo; Otono, Hidetoshi; Ouchrif, Mohamed; Ouellette, Eric; Ould-Saada, Farid; Ouraou, Ahmimed; Oussoren, Koen Pieter; Ouyang, Qun; Ovcharova, Ana; Owen, Mark; Ozcan, Veysi Erkcan; Ozturk, Nurcan; Pachal, Katherine; Pacheco Pages, Andres; Padilla Aranda, Cristobal; Pagáčová, Martina; Pagan Griso, Simone; Paganis, Efstathios; Pahl, Christoph; Paige, Frank; Pais, Preema; Pajchel, Katarina; Palacino, Gabriel; Palestini, Sandro; Palka, Marek; Pallin, Dominique; Palma, Alberto; Palmer, Jody; Pan, Yibin; Panagiotopoulou, Evgenia; Panduro Vazquez, William; Pani, Priscilla; Panikashvili, Natalia; Panitkin, Sergey; Pantea, Dan; Paolozzi, Lorenzo; Papadopoulou, Theodora; Papageorgiou, Konstantinos; Paramonov, Alexander; Paredes Hernandez, Daniela; Parker, Michael Andrew; Parodi, Fabrizio; Parsons, John; Parzefall, Ulrich; Pasqualucci, Enrico; Passaggio, Stefano; Passeri, Antonio; Pastore, Fernanda; Pastore, Francesca; Pásztor, Gabriella; Pataraia, Sophio; Patel, Nikhul; Pater, Joleen; Patricelli, Sergio; Pauly, Thilo; Pearce, James; Pedersen, Lars Egholm; Pedersen, Maiken; Pedraza Lopez, Sebastian; Pedro, Rute; Peleganchuk, Sergey; Pelikan, Daniel; Peng, Haiping; Penning, Bjoern; Penwell, John; Perepelitsa, Dennis; Perez Codina, Estel; Pérez García-Estañ, María Teresa; Perez Reale, Valeria; Perini, Laura; Pernegger, Heinz; Perrella, Sabrina; Perrino, Roberto; Peschke, Richard; Peshekhonov, Vladimir; Peters, Krisztian; Peters, Yvonne; Petersen, Brian; Petersen, Troels; Petit, Elisabeth; Petridis, Andreas; Petridou, Chariclia; Petrolo, Emilio; Petrucci, Fabrizio; Pettersson, Nora Emilia; Pezoa, Raquel; Phillips, Peter William; Piacquadio, Giacinto; Pianori, Elisabetta; Picazio, Attilio; Piccaro, Elisa; Piccinini, Maurizio; Piegaia, Ricardo; Pignotti, David; Pilcher, James; Pilkington, Andrew; Pina, João Antonio; Pinamonti, Michele; Pinder, Alex; Pinfold, James; Pingel, Almut; Pinto, Belmiro; Pires, Sylvestre; Pitt, Michael; Pizio, Caterina; Plazak, Lukas; Pleier, Marc-Andre; Pleskot, Vojtech; Plotnikova, Elena; Plucinski, Pawel; Pluth, Daniel; Poddar, Sahill; Podlyski, Fabrice; Poettgen, Ruth; Poggioli, Luc; Pohl, David-leon; Pohl, Martin; Polesello, Giacomo; Policicchio, Antonio; Polifka, Richard; Polini, Alessandro; Pollard, Christopher Samuel; Polychronakos, Venetios; Pommès, Kathy; Pontecorvo, Ludovico; Pope, Bernard; Popeneciu, Gabriel Alexandru; Popovic, Dragan; Poppleton, Alan; Portell Bueso, Xavier; Pospisil, Stanislav; Potamianos, Karolos; Potrap, Igor; Potter, Christina; Potter, Christopher; Poulard, Gilbert; Poveda, Joaquin; Pozdnyakov, Valery; Pralavorio, Pascal; Pranko, Aliaksandr; Prasad, Srivas; Pravahan, Rishiraj; Prell, Soeren; Price, Darren; Price, Joe; Price, Lawrence; Prieur, Damien; Primavera, Margherita; Proissl, Manuel; Prokofiev, Kirill; Prokoshin, Fedor; Protopapadaki, Eftychia-sofia; Protopopescu, Serban; Proudfoot, James; Przybycien, Mariusz; Przysiezniak, Helenka; Ptacek, Elizabeth; Puddu, Daniele; Pueschel, Elisa; Puldon, David; Purohit, Milind; Puzo, Patrick; Qian, Jianming; Qin, Gang; Qin, Yang; Quadt, Arnulf; Quarrie, David; Quayle, William; Queitsch-Maitland, Michaela; Quilty, Donnchadha; Qureshi, Anum; Radeka, Veljko; Radescu, Voica; Radhakrishnan, Sooraj Krishnan; Radloff, Peter; Rados, Pere; Ragusa, Francesco; Rahal, Ghita; Rajagopalan, Srinivasan; Rammensee, Michael; Randle-Conde, Aidan Sean; Rangel-Smith, Camila; Rao, Kanury; Rauscher, Felix; Rave, Tobias Christian; Ravenscroft, Thomas; Raymond, Michel; Read, Alexander Lincoln; Readioff, Nathan Peter; Rebuzzi, Daniela; Redelbach, Andreas; Redlinger, George; Reece, Ryan; Reeves, Kendall; Rehnisch, Laura; Reisin, Hernan; Relich, Matthew; Rembser, Christoph; Ren, Huan; Ren, Zhongliang; Renaud, Adrien; Rescigno, Marco; Resconi, Silvia; Rezanova, Olga; Reznicek, Pavel; Rezvani, Reyhaneh; Richter, Robert; Ridel, Melissa; Rieck, Patrick; Rieger, Julia; Rijssenbeek, Michael; Rimoldi, Adele; Rinaldi, Lorenzo; Ritsch, Elmar; Riu, Imma; Rizatdinova, Flera; Rizvi, Eram; Robertson, Steven; Robichaud-Veronneau, Andree; Robinson, Dave; Robinson, James; Robson, Aidan; Roda, Chiara; Rodrigues, Luis; Roe, Shaun; Røhne, Ole; Rolli, Simona; 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Salihagic, Denis; Salnikov, Andrei; Salt, José; Salvatore, Daniela; Salvatore, Pasquale Fabrizio; Salvucci, Antonio; Salzburger, Andreas; Sampsonidis, Dimitrios; Sanchez, Arturo; Sánchez, Javier; Sanchez Martinez, Victoria; Sandaker, Heidi; Sandbach, Ruth Laura; Sander, Heinz Georg; Sanders, Michiel; Sandhoff, Marisa; Sandoval, Tanya; Sandoval, Carlos; Sandstroem, Rikard; Sankey, Dave; Sansoni, Andrea; Santoni, Claudio; Santonico, Rinaldo; Santos, Helena; Santoyo Castillo, Itzebelt; Sapp, Kevin; Sapronov, Andrey; Saraiva, João; Sarrazin, Bjorn; Sartisohn, Georg; Sasaki, Osamu; Sasaki, Yuichi; Sauvage, Gilles; Sauvan, Emmanuel; Savard, Pierre; Savu, Dan Octavian; Sawyer, Craig; Sawyer, Lee; Saxon, David; Saxon, James; Sbarra, Carla; Sbrizzi, Antonio; Scanlon, Tim; Scannicchio, Diana; Scarcella, Mark; Scarfone, Valerio; Schaarschmidt, Jana; Schacht, Peter; Schaefer, Douglas; Schaefer, Ralph; Schaepe, Steffen; Schaetzel, Sebastian; Schäfer, Uli; Schaffer, Arthur; Schaile, Dorothee; Schamberger, R~Dean; 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Simonyan, Margar; Sinervo, Pekka; Sinev, Nikolai; Sipica, Valentin; Siragusa, Giovanni; Sircar, Anirvan; Sisakyan, Alexei; Sivoklokov, Serguei; Sjölin, Jörgen; Sjursen, Therese; Skottowe, Hugh Philip; Skovpen, Kirill; Skubic, Patrick; Slater, Mark; Slavicek, Tomas; Slawinska, Magdalena; Sliwa, Krzysztof; Smakhtin, Vladimir; Smart, Ben; Smestad, Lillian; Smirnov, Sergei; Smirnov, Yury; Smirnova, Lidia; Smirnova, Oxana; Smith, Kenway; Smizanska, Maria; Smolek, Karel; Snesarev, Andrei; Snidero, Giacomo; Snyder, Scott; Sobie, Randall; Socher, Felix; Soffer, Abner; Soh, Dart-yin; Solans, Carlos; Solar, Michael; Solc, Jaroslav; Soldatov, Evgeny; Soldevila, Urmila; Solodkov, Alexander; Soloshenko, Alexei; Solovyanov, Oleg; Solovyev, Victor; Sommer, Philip; Song, Hong Ye; Soni, Nitesh; Sood, Alexander; Sopczak, Andre; Sopko, Bruno; Sopko, Vit; Sorin, Veronica; Sosebee, Mark; Soualah, Rachik; Soueid, Paul; Soukharev, Andrey; South, David; Spagnolo, Stefania; Spanò, Francesco; Spearman, William Robert; Spettel, Fabian; Spighi, Roberto; Spigo, Giancarlo; Spiller, Laurence Anthony; Spousta, Martin; Spreitzer, Teresa; Spurlock, Barry; St Denis, Richard Dante; Staerz, Steffen; Stahlman, Jonathan; Stamen, Rainer; Stamm, Soren; Stanecka, Ewa; Stanek, Robert; Stanescu, Cristian; Stanescu-Bellu, Madalina; Stanitzki, Marcel Michael; Stapnes, Steinar; Starchenko, Evgeny; Stark, Jan; Staroba, Pavel; Starovoitov, Pavel; Staszewski, Rafal; Stavina, Pavel; Steinberg, Peter; Stelzer, Bernd; Stelzer, Harald Joerg; Stelzer-Chilton, Oliver; Stenzel, Hasko; Stern, Sebastian; Stewart, Graeme; Stillings, Jan Andre; Stockton, Mark; Stoebe, Michael; Stoicea, Gabriel; Stolte, Philipp; Stonjek, Stefan; Stradling, Alden; Straessner, Arno; Stramaglia, Maria Elena; Strandberg, Jonas; Strandberg, Sara; Strandlie, Are; Strauss, Emanuel; Strauss, Michael; Strizenec, Pavol; Ströhmer, Raimund; Strom, David; Stroynowski, Ryszard; Strubig, Antonia; Stucci, Stefania Antonia; Stugu, Bjarne; Styles, Nicholas Adam; Su, Dong; Su, Jun; Subramaniam, Rajivalochan; Succurro, Antonella; Sugaya, Yorihito; Suhr, Chad; Suk, Michal; Sulin, Vladimir; Sultansoy, Saleh; Sumida, Toshi; Sun, Siyuan; Sun, Xiaohu; Sundermann, Jan Erik; Suruliz, Kerim; Susinno, Giancarlo; Sutton, Mark; Suzuki, Yu; Svatos, Michal; Swedish, Stephen; Swiatlowski, Maximilian; Sykora, Ivan; Sykora, Tomas; Ta, Duc; Taccini, Cecilia; Tackmann, Kerstin; Taenzer, Joe; Taffard, Anyes; Tafirout, Reda; Taiblum, Nimrod; Takai, Helio; Takashima, Ryuichi; Takeda, Hiroshi; Takeshita, Tohru; Takubo, Yosuke; Talby, Mossadek; Talyshev, Alexey; Tam, Jason; Tan, Kong Guan; Tanaka, Junichi; Tanaka, Reisaburo; Tanaka, Satoshi; Tanaka, Shuji; Tanasijczuk, Andres Jorge; Tannenwald, Benjamin Bordy; Tannoury, Nancy; Tapprogge, Stefan; Tarem, Shlomit; Tarrade, Fabien; Tartarelli, Giuseppe Francesco; Tas, Petr; Tasevsky, Marek; Tashiro, Takuya; Tassi, Enrico; Tavares Delgado, Ademar; Tayalati, Yahya; Taylor, Frank; Taylor, Geoffrey; Taylor, Wendy; Teischinger, Florian Alfred; Teixeira Dias Castanheira, Matilde; Teixeira-Dias, Pedro; Temming, Kim Katrin; Ten Kate, Herman; Teng, Ping-Kun; Teoh, Jia Jian; Terada, Susumu; Terashi, Koji; Terron, Juan; Terzo, Stefano; Testa, Marianna; Teuscher, Richard; Therhaag, Jan; Theveneaux-Pelzer, Timothée; Thomas, Juergen; Thomas-Wilsker, Joshuha; Thompson, Emily; Thompson, Paul; Thompson, Peter; Thompson, Ray; Thompson, Stan; Thomsen, Lotte Ansgaard; Thomson, Evelyn; Thomson, Mark; Thong, Wai Meng; Thun, Rudolf; Tian, Feng; Tibbetts, Mark James; Tikhomirov, Vladimir; Tikhonov, Yury; Timoshenko, Sergey; Tiouchichine, Elodie; Tipton, Paul; Tisserant, Sylvain; Todorov, Theodore; Todorova-Nova, Sharka; Toggerson, Brokk; Tojo, Junji; Tokár, Stanislav; Tokushuku, Katsuo; Tollefson, Kirsten; Tolley, Emma; Tomlinson, Lee; Tomoto, Makoto; Tompkins, Lauren; Toms, Konstantin; Topilin, Nikolai; Torrence, Eric; Torres, Heberth; Torró Pastor, Emma; Toth, Jozsef; Touchard, Francois; Tovey, Daniel; Tran, Huong Lan; Trefzger, Thomas; Tremblet, Louis; 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Zwalinski, Lukasz

2014-11-10

Measurements of fiducial and differential cross sections of Higgs boson production in the ${H \\rightarrow ZZ ^{*}\\rightarrow 4\\ell}$ decay channel are presented. The cross sections are determined within a fiducial phase space and corrected for detection efficiency and resolution effects. They are based on 20.3 fb$^{-1}$ of $pp$ collision data, produced at $\\sqrt{s}$=8 TeV centre-of-mass energy at the LHC and recorded by the ATLAS detector. The differential measurements are performed in bins of transverse momentum and rapidity of the four-lepton system, the invariant mass of the subleading lepton pair and the decay angle of the leading lepton pair with respect to the beam line in the four-lepton rest frame,  as well as the number of jets and the transverse momentum of the leading jet. The measured cross sections are compared to selected theoretical calculations of the Standard Model expectations. No significant deviation from any of the tested predictions is found.

An improved algorithm for automatic detection of saccades in eye movement data and for calculating saccade parameters.

Science.gov (United States)

Behrens, F; Mackeben, M; Schröder-Preikschat, W

2010-08-01

This analysis of time series of eye movements is a saccade-detection algorithm that is based on an earlier algorithm. It achieves substantial improvements by using an adaptive-threshold model instead of fixed thresholds and using the eye-movement acceleration signal. This has four advantages: (1) Adaptive thresholds are calculated automatically from the preceding acceleration data for detecting the beginning of a saccade, and thresholds are modified during the saccade. (2) The monotonicity of the position signal during the saccade, together with the acceleration with respect to the thresholds, is used to reliably determine the end of the saccade. (3) This allows differentiation between saccades following the main-sequence and non-main-sequence saccades. (4) Artifacts of various kinds can be detected and eliminated. The algorithm is demonstrated by applying it to human eye movement data (obtained by EOG) recorded during driving a car. A second demonstration of the algorithm detects microsleep episodes in eye movement data.

Anomaly Detection using the "Isolation Forest" algorithm

CERN Multimedia

CERN. Geneva

2015-01-01

Anomaly detection can provide clues about an outlying minority class in your data: hackers in a set of network events, fraudsters in a set of credit card transactions, or exotic particles in a set of high-energy collisions. In this talk, we analyze a real dataset of breast tissue biopsies, with malignant results forming the minority class. The "Isolation Forest" algorithm finds anomalies by deliberately “overfitting” models that memorize each data point. Since outliers have more empty space around them, they take fewer steps to memorize. Intuitively, a house in the country can be identified simply as “that house out by the farm”, while a house in the city needs a longer description like “that house in Brooklyn, near Prospect Park, on Union Street, between the firehouse and the library, not far from the French restaurant”. We first use anomaly detection to find outliers in the biopsy data, then apply traditional predictive modeling to discover rules that separate anomalies from normal data...

Plagiarism Detection Algorithm for Source Code in Computer Science Education

Science.gov (United States)

Liu, Xin; Xu, Chan; Ouyang, Boyu

2015-01-01

Nowadays, computer programming is getting more necessary in the course of program design in college education. However, the trick of plagiarizing plus a little modification exists among some students' home works. It's not easy for teachers to judge if there's plagiarizing in source code or not. Traditional detection algorithms cannot fit this…

Towards Real-Time Detection of Gait Events on Different Terrains Using Time-Frequency Analysis and Peak Heuristics Algorithm.

Science.gov (United States)

Zhou, Hui; Ji, Ning; Samuel, Oluwarotimi Williams; Cao, Yafei; Zhao, Zheyi; Chen, Shixiong; Li, Guanglin

2016-10-01

Real-time detection of gait events can be applied as a reliable input to control drop foot correction devices and lower-limb prostheses. Among the different sensors used to acquire the signals associated with walking for gait event detection, the accelerometer is considered as a preferable sensor due to its convenience of use, small size, low cost, reliability, and low power consumption. Based on the acceleration signals, different algorithms have been proposed to detect toe off (TO) and heel strike (HS) gait events in previous studies. While these algorithms could achieve a relatively reasonable performance in gait event detection, they suffer from limitations such as poor real-time performance and are less reliable in the cases of up stair and down stair terrains. In this study, a new algorithm is proposed to detect the gait events on three walking terrains in real-time based on the analysis of acceleration jerk signals with a time-frequency method to obtain gait parameters, and then the determination of the peaks of jerk signals using peak heuristics. The performance of the newly proposed algorithm was evaluated with eight healthy subjects when they were walking on level ground, up stairs, and down stairs. Our experimental results showed that the mean F1 scores of the proposed algorithm were above 0.98 for HS event detection and 0.95 for TO event detection on the three terrains. This indicates that the current algorithm would be robust and accurate for gait event detection on different terrains. Findings from the current study suggest that the proposed method may be a preferable option in some applications such as drop foot correction devices and leg prostheses.

Algorithms Development in Detection of the Gelatinization Process during Enzymatic ‘Dodol’ Processing

Directory of Open Access Journals (Sweden)

Azman Hamzah

2013-09-01

Full Text Available Computer vision systems have found wide application in foods processing industry to perform quality evaluation. The systems enable to replace human inspectors for the evaluation of a variety of quality attributes. This paper describes the implementation of the Fast Fourier Transform and Kalman filtering algorithms to detect the glutinous rice flour slurry (GRFS gelatinization in an enzymatic „dodol. processing. The onset of the GRFS gelatinization is critical in determining the quality of an enzymatic „dodol.. Combinations of these two algorithms were able to detect the gelatinization of the GRFS. The result shows that the gelatinization of the GRFS was at the time range of 11.75 minutes to 14.75 minutes for 24 batches of processing. This paper will highlight the capability of computer vision using our proposed algorithms in monitoring and controlling of an enzymatic „dodol. processing via image processing technology.

Algorithms Development in Detection of the Gelatinization Process during Enzymatic ‘Dodol’ Processing

Directory of Open Access Journals (Sweden)

Azman Hamzah

2007-11-01

Full Text Available Computer vision systems have found wide application in foods processing industry to perform the quality evaluation. The systems enable to replace human inspectors for the evaluation of a variety of quality attributes. This paper describes the implementation of the Fast Fourier Transform and Kalman filtering algorithms to detect the glutinous rice flour slurry (GRFS gelatinization in an enzymatic ‘dodol’ processing. The onset of the GRFS gelatinization is critical in determining the quality of an enzymatic ‘dodol’. Combinations of these two algorithms were able to detect the gelatinization of the GRFS. The result shows that the gelatinization of the GRFS was at the time range of 11.75 minutes to 15.33 minutes for 20 batches of processing. This paper will highlight the capability of computer vision using our proposed algorithms in monitoring and controlling of an enzymatic ‘dodol’ processing via image processing technology.

A novel ship CFAR detection algorithm based on adaptive parameter enhancement and wake-aided detection in SAR images

Science.gov (United States)

Meng, Siqi; Ren, Kan; Lu, Dongming; Gu, Guohua; Chen, Qian; Lu, Guojun

2018-03-01

Synthetic aperture radar (SAR) is an indispensable and useful method for marine monitoring. With the increase of SAR sensors, high resolution images can be acquired and contain more target structure information, such as more spatial details etc. This paper presents a novel adaptive parameter transform (APT) domain constant false alarm rate (CFAR) to highlight targets. The whole method is based on the APT domain value. Firstly, the image is mapped to the new transform domain by the algorithm. Secondly, the false candidate target pixels are screened out by the CFAR detector to highlight the target ships. Thirdly, the ship pixels are replaced by the homogeneous sea pixels. And then, the enhanced image is processed by Niblack algorithm to obtain the wake binary image. Finally, normalized Hough transform (NHT) is used to detect wakes in the binary image, as a verification of the presence of the ships. Experiments on real SAR images validate that the proposed transform does enhance the target structure and improve the contrast of the image. The algorithm has a good performance in the ship and ship wake detection.

Evaluating and Improving Automatic Sleep Spindle Detection by Using Multi-Objective Evolutionary Algorithms

Directory of Open Access Journals (Sweden)

Min-Yin Liu

2017-05-01

Full Text Available Sleep spindles are brief bursts of brain activity in the sigma frequency range (11–16 Hz measured by electroencephalography (EEG mostly during non-rapid eye movement (NREM stage 2 sleep. These oscillations are of great biological and clinical interests because they potentially play an important role in identifying and characterizing the processes of various neurological disorders. Conventionally, sleep spindles are identified by expert sleep clinicians via visual inspection of EEG signals. The process is laborious and the results are inconsistent among different experts. To resolve the problem, numerous computerized methods have been developed to automate the process of sleep spindle identification. Still, the performance of these automated sleep spindle detection methods varies inconsistently from study to study. There are two reasons: (1 the lack of common benchmark databases, and (2 the lack of commonly accepted evaluation metrics. In this study, we focus on tackling the second problem by proposing to evaluate the performance of a spindle detector in a multi-objective optimization context and hypothesize that using the resultant Pareto fronts for deriving evaluation metrics will improve automatic sleep spindle detection. We use a popular multi-objective evolutionary algorithm (MOEA, the Strength Pareto Evolutionary Algorithm (SPEA2, to optimize six existing frequency-based sleep spindle detection algorithms. They include three Fourier, one continuous wavelet transform (CWT, and two Hilbert-Huang transform (HHT based algorithms. We also explore three hybrid approaches. Trained and tested on open-access DREAMS and MASS databases, two new hybrid methods of combining Fourier with HHT algorithms show significant performance improvement with F1-scores of 0.726–0.737.

Interactions between pacing and arrhythmia detection algorithms in the dual chamber implantable cardioverter defibrillator.

Science.gov (United States)

Dijkman, B; Wellens, H J

2001-09-01

Dual chamber implantable cardioverter defibrillator (ICD) combines the possibility to detect and treat ventricular and atrial arrhythmias with the possibility of modern heart stimulation techniques. Advanced pacing algorithms together with extended arrhythmia detection capabilities can give rise to new types of device-device interactions. Some of the possible interactions are illustrated by four cases documented in four models of dual chamber ICDs. Functioning of new features in dual chamber devices is influenced by the fact that the pacemaker is not a separate device but a part of the ICD system and that both are being used in a patient with arrhythmia. Programming measures are suggested to optimize use of new pacing algorithms while maintaining correct arrhythmia detection.

An Algorithm for Real-Time Pulse Waveform Segmentation and Artifact Detection in Photoplethysmograms.

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Fischer, Christoph; Domer, Benno; Wibmer, Thomas; Penzel, Thomas

2017-03-01

Photoplethysmography has been used in a wide range of medical devices for measuring oxygen saturation, cardiac output, assessing autonomic function, and detecting peripheral vascular disease. Artifacts can render the photoplethysmogram (PPG) useless. Thus, algorithms capable of identifying artifacts are critically important. However, the published PPG algorithms are limited in algorithm and study design. Therefore, the authors developed a novel embedded algorithm for real-time pulse waveform (PWF) segmentation and artifact detection based on a contour analysis in the time domain. This paper provides an overview about PWF and artifact classifications, presents the developed PWF analysis, and demonstrates the implementation on a 32-bit ARM core microcontroller. The PWF analysis was validated with data records from 63 subjects acquired in a sleep laboratory, ergometry laboratory, and intensive care unit in equal parts. The output of the algorithm was compared with harmonized experts' annotations of the PPG with a total duration of 31.5 h. The algorithm achieved a beat-to-beat comparison sensitivity of 99.6%, specificity of 90.5%, precision of 98.5%, and accuracy of 98.3%. The interrater agreement expressed as Cohen's kappa coefficient was 0.927 and as F-measure was 0.990. In conclusion, the PWF analysis seems to be a suitable method for PPG signal quality determination, real-time annotation, data compression, and calculation of additional pulse wave metrics such as amplitude, duration, and rise time.

Computer algorithms for automated detection and analysis of local Ca2+ releases in spontaneously beating cardiac pacemaker cells.

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Alexander V Maltsev

Full Text Available Local Ca2+ Releases (LCRs are crucial events involved in cardiac pacemaker cell function. However, specific algorithms for automatic LCR detection and analysis have not been developed in live, spontaneously beating pacemaker cells. In the present study we measured LCRs using a high-speed 2D-camera in spontaneously contracting sinoatrial (SA node cells isolated from rabbit and guinea pig and developed a new algorithm capable of detecting and analyzing the LCRs spatially in two-dimensions, and in time. Our algorithm tracks points along the midline of the contracting cell. It uses these points as a coordinate system for affine transform, producing a transformed image series where the cell does not contract. Action potential-induced Ca2+ transients and LCRs were thereafter isolated from recording noise by applying a series of spatial filters. The LCR birth and death events were detected by a differential (frame-to-frame sensitivity algorithm applied to each pixel (cell location. An LCR was detected when its signal changes sufficiently quickly within a sufficiently large area. The LCR is considered to have died when its amplitude decays substantially, or when it merges into the rising whole cell Ca2+ transient. Ultimately, our algorithm provides major LCR parameters such as period, signal mass, duration, and propagation path area. As the LCRs propagate within live cells, the algorithm identifies splitting and merging behaviors, indicating the importance of locally propagating Ca2+-induced-Ca2+-release for the fate of LCRs and for generating a powerful ensemble Ca2+ signal. Thus, our new computer algorithms eliminate motion artifacts and detect 2D local spatiotemporal events from recording noise and global signals. While the algorithms were developed to detect LCRs in sinoatrial nodal cells, they have the potential to be used in other applications in biophysics and cell physiology, for example, to detect Ca2+ wavelets (abortive waves, sparks and

An optimized outlier detection algorithm for jury-based grading of engineering design projects

DEFF Research Database (Denmark)

Thompson, Mary Kathryn; Espensen, Christina; Clemmensen, Line Katrine Harder

2016-01-01

This work characterizes and optimizes an outlier detection algorithm to identify potentially invalid scores produced by jury members while grading engineering design projects. The paper describes the original algorithm and the associated adjudication process in detail. The impact of the various...... (the base rule and the three additional conditions) play a role in the algorithm's performance and should be included in the algorithm. Because there is significant interaction between the base rule and the additional conditions, many acceptable combinations that balance the FPR and FNR can be found......, but no true optimum seems to exist. The performance of the best optimizations and the original algorithm are similar. Therefore, it should be possible to choose new coefficient values for jury populations in other cultures and contexts logically and empirically without a full optimization as long...

Validation of vision-based obstacle detection algorithms for low-altitude helicopter flight

Science.gov (United States)

Suorsa, Raymond; Sridhar, Banavar

1991-01-01

A validation facility being used at the NASA Ames Research Center is described which is aimed at testing vision based obstacle detection and range estimation algorithms suitable for low level helicopter flight. The facility is capable of processing hundreds of frames of calibrated multicamera 6 degree-of-freedom motion image sequencies, generating calibrated multicamera laboratory images using convenient window-based software, and viewing range estimation results from different algorithms along with truth data using powerful window-based visualization software.

Performance of target detection algorithm in compressive sensing miniature ultraspectral imaging compressed sensing system

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Gedalin, Daniel; Oiknine, Yaniv; August, Isaac; Blumberg, Dan G.; Rotman, Stanley R.; Stern, Adrian

2017-04-01

Compressive sensing theory was proposed to deal with the high quantity of measurements demanded by traditional hyperspectral systems. Recently, a compressive spectral imaging technique dubbed compressive sensing miniature ultraspectral imaging (CS-MUSI) was presented. This system uses a voltage controlled liquid crystal device to create multiplexed hyperspectral cubes. We evaluate the utility of the data captured using the CS-MUSI system for the task of target detection. Specifically, we compare the performance of the matched filter target detection algorithm in traditional hyperspectral systems and in CS-MUSI multiplexed hyperspectral cubes. We found that the target detection algorithm performs similarly in both cases, despite the fact that the CS-MUSI data is up to an order of magnitude less than that in conventional hyperspectral cubes. Moreover, the target detection is approximately an order of magnitude faster in CS-MUSI data.

An Improved Fruit Fly Optimization Algorithm and Its Application in Heat Exchange Fouling Ultrasonic Detection

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Xia Li

2018-01-01

Full Text Available Inspired by the basic theory of Fruit Fly Optimization Algorithm, in this paper, cat mapping was added to the original algorithm, and the individual distribution and evolution mechanism of fruit fly population were improved in order to increase the search speed and accuracy. The flowchart of the improved algorithm was drawn to show its procedure. Using classical test functions, simulation optimization results show that the improved algorithm has faster and more reliable optimization ability. The algorithm was then combined with sparse decomposition theory and used in processing fouling detection ultrasonic signals to verify the validity and practicability of the improved algorithm.

A Plane Target Detection Algorithm in Remote Sensing Images based on Deep Learning Network Technology

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Shuxin, Li; Zhilong, Zhang; Biao, Li

2018-01-01

Plane is an important target category in remote sensing targets and it is of great value to detect the plane targets automatically. As remote imaging technology developing continuously, the resolution of the remote sensing image has been very high and we can get more detailed information for detecting the remote sensing targets automatically. Deep learning network technology is the most advanced technology in image target detection and recognition, which provided great performance improvement in the field of target detection and recognition in the everyday scenes. We combined the technology with the application in the remote sensing target detection and proposed an algorithm with end to end deep network, which can learn from the remote sensing images to detect the targets in the new images automatically and robustly. Our experiments shows that the algorithm can capture the feature information of the plane target and has better performance in target detection with the old methods.

Experimental Validation of Advanced Dispersed Fringe Sensing (ADFS) Algorithm Using Advanced Wavefront Sensing and Correction Testbed (AWCT)

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Wang, Xu; Shi, Fang; Sigrist, Norbert; Seo, Byoung-Joon; Tang, Hong; Bikkannavar, Siddarayappa; Basinger, Scott; Lay, Oliver

2012-01-01

Large aperture telescope commonly features segment mirrors and a coarse phasing step is needed to bring these individual segments into the fine phasing capture range. Dispersed Fringe Sensing (DFS) is a powerful coarse phasing technique and its alteration is currently being used for JWST.An Advanced Dispersed Fringe Sensing (ADFS) algorithm is recently developed to improve the performance and robustness of previous DFS algorithms with better accuracy and unique solution. The first part of the paper introduces the basic ideas and the essential features of the ADFS algorithm and presents the some algorithm sensitivity study results. The second part of the paper describes the full details of algorithm validation process through the advanced wavefront sensing and correction testbed (AWCT): first, the optimization of the DFS hardware of AWCT to ensure the data accuracy and reliability is illustrated. Then, a few carefully designed algorithm validation experiments are implemented, and the corresponding data analysis results are shown. Finally the fiducial calibration using Range-Gate-Metrology technique is carried out and a <10nm or <1% algorithm accuracy is demonstrated.

Defect-detection algorithm for noncontact acoustic inspection using spectrum entropy

Science.gov (United States)

Sugimoto, Kazuko; Akamatsu, Ryo; Sugimoto, Tsuneyoshi; Utagawa, Noriyuki; Kuroda, Chitose; Katakura, Kageyoshi

2015-07-01

In recent years, the detachment of concrete from bridges or tunnels and the degradation of concrete structures have become serious social problems. The importance of inspection, repair, and updating is recognized in measures against degradation. We have so far studied the noncontact acoustic inspection method using airborne sound and the laser Doppler vibrometer. In this method, depending on the surface state (reflectance, dirt, etc.), the quantity of the light of the returning laser decreases and optical noise resulting from the leakage of light reception arises. Some influencing factors are the stability of the output of the laser Doppler vibrometer, the low reflective characteristic of the measurement surface, the diffused reflection characteristic, measurement distance, and laser irradiation angle. If defect detection depends only on the vibration energy ratio since the frequency characteristic of the optical noise resembles white noise, the detection of optical noise resulting from the leakage of light reception may indicate a defective part. Therefore, in this work, the combination of the vibrational energy ratio and spectrum entropy is used to judge whether a measured point is healthy or defective or an abnormal measurement point. An algorithm that enables more vivid detection of a defective part is proposed. When our technique was applied in an experiment with real concrete structures, the defective part could be extracted more vividly and the validity of our proposed algorithm was confirmed.

Fluoroscopic gating without implanted fiducial markers for lung cancer radiotherapy based on support vector machines

International Nuclear Information System (INIS)

Cui Ying; Dy, Jennifer G; Alexander, Brian; Jiang, Steve B

2008-01-01

Various problems with the current state-of-the-art techniques for gated radiotherapy have prevented this new treatment modality from being widely implemented in clinical routine. These problems are caused mainly by applying various external respiratory surrogates. There might be large uncertainties in deriving the tumor position from external respiratory surrogates. While tracking implanted fiducial markers has sufficient accuracy, this procedure may not be widely accepted due to the risk of pneumothorax. Previously, we have developed a technique to generate gating signals from fluoroscopic images without implanted fiducial markers using template matching methods (Berbeco et al 2005 Phys. Med. Biol. 50 4481-90, Cui et al 2007b Phys. Med. Biol. 52 741-55). In this note, our main contribution is to provide a totally different new view of the gating problem by recasting it as a classification problem. Then, we solve this classification problem by a well-studied powerful classification method called a support vector machine (SVM). Note that the goal of an automated gating tool is to decide when to turn the beam ON or OFF. We treat ON and OFF as the two classes in our classification problem. We create our labeled training data during the patient setup session by utilizing the reference gating signal, manually determined by a radiation oncologist. We then pre-process these labeled training images and build our SVM prediction model. During treatment delivery, fluoroscopic images are continuously acquired, pre-processed and sent as an input to the SVM. Finally, our SVM model will output the predicted labels as gating signals. We test the proposed technique on five sequences of fluoroscopic images from five lung cancer patients against the reference gating signal as ground truth. We compare the performance of the SVM to our previous template matching method (Cui et al 2007b Phys. Med. Biol. 52 741-55). We find that the SVM is slightly more accurate on average (1-3%) than

A Low-Complexity Joint Synchronization and Detection Algorithm for Single-Band DS-CDMA UWB Communications

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Christensen Lars PB

2005-01-01

Full Text Available The problem of asynchronous direct-sequence code-division multiple-access (DS-CDMA detection over the ultra-wideband (UWB multipath channel is considered. A joint synchronization, channel-estimation, and multiuser detection scheme based on the adaptive linear minimum mean square error (LMMSE receiver is presented and evaluated. Further, a novel nonrecursive least-squares algorithm capable of reducing the complexity of the adaptation in the receiver while preserving the advantages of the recursive least-squares (RLS algorithm is presented.

A New Algorithm for Detecting Cloud Height using OMPS/LP Measurements

Science.gov (United States)

Chen, Zhong; DeLand, Matthew; Bhartia, Pawan K.

2016-01-01

The Ozone Mapping and Profiler Suite Limb Profiler (OMPS/LP) ozone product requires the determination of cloud height for each event to establish the lower boundary of the profile for the retrieval algorithm. We have created a revised cloud detection algorithm for LP measurements that uses the spectral dependence of the vertical gradient in radiance between two wavelengths in the visible and near-IR spectral regions. This approach provides better discrimination between clouds and aerosols than results obtained using a single wavelength. Observed LP cloud height values show good agreement with coincident Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) measurements.

Sum of the Magnitude for Hard Decision Decoding Algorithm Based on Loop Update Detection

Science.gov (United States)

Meng, Jiahui; Zhao, Danfeng; Tian, Hai; Zhang, Liang

2018-01-01

In order to improve the performance of non-binary low-density parity check codes (LDPC) hard decision decoding algorithm and to reduce the complexity of decoding, a sum of the magnitude for hard decision decoding algorithm based on loop update detection is proposed. This will also ensure the reliability, stability and high transmission rate of 5G mobile communication. The algorithm is based on the hard decision decoding algorithm (HDA) and uses the soft information from the channel to calculate the reliability, while the sum of the variable nodes’ (VN) magnitude is excluded for computing the reliability of the parity checks. At the same time, the reliability information of the variable node is considered and the loop update detection algorithm is introduced. The bit corresponding to the error code word is flipped multiple times, before this is searched in the order of most likely error probability to finally find the correct code word. Simulation results show that the performance of one of the improved schemes is better than the weighted symbol flipping (WSF) algorithm under different hexadecimal numbers by about 2.2 dB and 2.35 dB at the bit error rate (BER) of 10−5 over an additive white Gaussian noise (AWGN) channel, respectively. Furthermore, the average number of decoding iterations is significantly reduced. PMID:29342963

Sum of the Magnitude for Hard Decision Decoding Algorithm Based on Loop Update Detection.

Science.gov (United States)

Meng, Jiahui; Zhao, Danfeng; Tian, Hai; Zhang, Liang

2018-01-15

In order to improve the performance of non-binary low-density parity check codes (LDPC) hard decision decoding algorithm and to reduce the complexity of decoding, a sum of the magnitude for hard decision decoding algorithm based on loop update detection is proposed. This will also ensure the reliability, stability and high transmission rate of 5G mobile communication. The algorithm is based on the hard decision decoding algorithm (HDA) and uses the soft information from the channel to calculate the reliability, while the sum of the variable nodes' (VN) magnitude is excluded for computing the reliability of the parity checks. At the same time, the reliability information of the variable node is considered and the loop update detection algorithm is introduced. The bit corresponding to the error code word is flipped multiple times, before this is searched in the order of most likely error probability to finally find the correct code word. Simulation results show that the performance of one of the improved schemes is better than the weighted symbol flipping (WSF) algorithm under different hexadecimal numbers by about 2.2 dB and 2.35 dB at the bit error rate (BER) of 10 -5 over an additive white Gaussian noise (AWGN) channel, respectively. Furthermore, the average number of decoding iterations is significantly reduced.

Sum of the Magnitude for Hard Decision Decoding Algorithm Based on Loop Update Detection

Directory of Open Access Journals (Sweden)

Jiahui Meng

2018-01-01

Full Text Available In order to improve the performance of non-binary low-density parity check codes (LDPC hard decision decoding algorithm and to reduce the complexity of decoding, a sum of the magnitude for hard decision decoding algorithm based on loop update detection is proposed. This will also ensure the reliability, stability and high transmission rate of 5G mobile communication. The algorithm is based on the hard decision decoding algorithm (HDA and uses the soft information from the channel to calculate the reliability, while the sum of the variable nodes’ (VN magnitude is excluded for computing the reliability of the parity checks. At the same time, the reliability information of the variable node is considered and the loop update detection algorithm is introduced. The bit corresponding to the error code word is flipped multiple times, before this is searched in the order of most likely error probability to finally find the correct code word. Simulation results show that the performance of one of the improved schemes is better than the weighted symbol flipping (WSF algorithm under different hexadecimal numbers by about 2.2 dB and 2.35 dB at the bit error rate (BER of 10−5 over an additive white Gaussian noise (AWGN channel, respectively. Furthermore, the average number of decoding iterations is significantly reduced.

An improved reconstruction algorithm based on multi-user detection for uplink grant-free NOMA

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Hou Chengyan

2017-01-01

Full Text Available For the traditional orthogonal matching pursuit(OMP algorithm in multi-user detection(MUD for uplink grant-free NOMA, here is a poor BER performance, so in this paper we propose an temporal-correlation orthogonal matching pursuit algorithm(TOMP to realize muli-user detection. The core idea of the TOMP is to use the time correlation of the active user sets to achieve user activity and data detection in a number of continuous time slots. We use the estimated active user set in the current time slot as a priori information to estimate the active user sets for the next slot. By maintaining the active user set Tˆl of size K(K is the number of users, but modified in each iteration. Specifically, active user set is believed to be reliable in one iteration but shown error in another iteration, can be added to the set path delay Tˆl or removed from it. Theoretical analysis of the improved algorithm provide a guarantee that the multi-user can be successfully detected with a high probability. The simulation results show that the proposed scheme can achieve better bit error rate (BER performance in the uplink grant-free NOMA system.

Accuracy of Ultrasound-Based (BAT) Prostate-Repositioning: A Three-Dimensional On-Line Fiducial-Based Assessment With Cone-Beam Computed Tomography

International Nuclear Information System (INIS)

Boda-Heggemann, Judit; Koehler, Frederick Marc; Kuepper, Beate; Wolff, Dirk; Wertz, Hansjoerg; Mai, Sabine; Hesser, Juergen; Lohr, Frank; Wenz, Frederik

2008-01-01

Purpose: To assess the accuracy of ultrasound-based repositioning (BAT) before prostate radiation with fiducial-based three-dimensional matching with cone-beam computed tomography (CBCT). Patients and Methods: Fifty-four positionings in 8 patients with 125 I seeds/intraprostatic calcifications as fiducials were evaluated. Patients were initially positioned according to skin marks and after this according to bony structures based on CBCT. Prostate position correction was then performed with BAT. Residual error after repositioning based on skin marks, bony anatomy, and BAT was estimated by a second CBCT based on user-independent automatic fiducial registration. Results: Overall mean value (MV ± SD) residual error after BAT based on fiducial registration by CBCT was 0.7 ± 1.7 mm in x (group systematic error [M] = 0.5 mm; SD of systematic error [Σ] = 0.8 mm; SD of random error [σ] = 1.4 mm), 0.9 ± 3.3 mm in y (M = 0.5 mm, Σ = 2.2 mm, σ = 2.8 mm), and -1.7 ± 3.4 mm in z (M = -1.7 mm, Σ = 2.3 mm, σ = 3.0 mm) directions, whereas residual error relative to positioning based on skin marks was 2.1 ± 4.6 mm in x (M = 2.6 mm, Σ = 3.3 mm, σ = 3.9 mm), -4.8 ± 8.5 mm in y (M = -4.4 mm, Σ = 3.7 mm, σ = 6.7 mm), and -5.2 ± 3.6 mm in z (M = -4.8 mm, Σ = 1.7 mm, σ = 3.5mm) directions and relative to positioning based on bony anatomy was 0 ± 1.8 mm in x (M = 0.2 mm, Σ = 0.9 mm, σ = 1.1 mm), -3.5 ± 6.8 mm in y (M = -3.0 mm, Σ = 1.8 mm, σ = 3.7 mm), and -1.9 ± 5.2 mm in z (M = -2.0 mm, Σ = 1.3 mm, σ = 4.0 mm) directions. Conclusions: BAT improved the daily repositioning accuracy over skin marks or even bony anatomy. The results obtained with BAT are within the precision of extracranial stereotactic procedures and represent values that can be achieved with several users with different education levels. If sonographic visibility is insufficient, CBCT or kV/MV portal imaging with implanted fiducials are recommended

A new automated quantification algorithm for the detection and evaluation of focal liver lesions with contrast-enhanced ultrasound.

Science.gov (United States)

Gatos, Ilias; Tsantis, Stavros; Spiliopoulos, Stavros; Skouroliakou, Aikaterini; Theotokas, Ioannis; Zoumpoulis, Pavlos; Hazle, John D; Kagadis, George C

2015-07-01

Detect and classify focal liver lesions (FLLs) from contrast-enhanced ultrasound (CEUS) imaging by means of an automated quantification algorithm. The proposed algorithm employs a sophisticated segmentation method to detect and contour focal lesions from 52 CEUS video sequences (30 benign and 22 malignant). Lesion detection involves wavelet transform zero crossings utilization as an initialization step to the Markov random field model toward the lesion contour extraction. After FLL detection across frames, time intensity curve (TIC) is computed which provides the contrast agents' behavior at all vascular phases with respect to adjacent parenchyma for each patient. From each TIC, eight features were automatically calculated and employed into the support vector machines (SVMs) classification algorithm in the design of the image analysis model. With regard to FLLs detection accuracy, all lesions detected had an average overlap value of 0.89 ± 0.16 with manual segmentations for all CEUS frame-subsets included in the study. Highest classification accuracy from the SVM model was 90.3%, misdiagnosing three benign and two malignant FLLs with sensitivity and specificity values of 93.1% and 86.9%, respectively. The proposed quantification system that employs FLLs detection and classification algorithms may be of value to physicians as a second opinion tool for avoiding unnecessary invasive procedures.

Development and testing of an algorithm to detect implantable cardioverter-defibrillator lead failure.

Science.gov (United States)

Gunderson, Bruce D; Gillberg, Jeffrey M; Wood, Mark A; Vijayaraman, Pugazhendhi; Shepard, Richard K; Ellenbogen, Kenneth A

2006-02-01

Implantable cardioverter-defibrillator (ICD) lead failures often present as inappropriate shock therapy. An algorithm that can reliably discriminate between ventricular tachyarrhythmias and noise due to lead failure may prevent patient discomfort and anxiety and avoid device-induced proarrhythmia by preventing inappropriate ICD shocks. The goal of this analysis was to test an ICD tachycardia detection algorithm that differentiates noise due to lead failure from ventricular tachyarrhythmias. We tested an algorithm that uses a measure of the ventricular intracardiac electrogram baseline to discriminate the sinus rhythm isoelectric line from the right ventricular coil-can (i.e., far-field) electrogram during oversensing of noise caused by a lead failure. The baseline measure was defined as the product of the sum (mV) and standard deviation (mV) of the voltage samples for a 188-ms window centered on each sensed electrogram. If the minimum baseline measure of the last 12 beats was algorithm to detect lead failures. The minimum baseline measure for the 24 lead failure episodes (0.28 +/- 0.34 mV-mV) was smaller than the 135 ventricular tachycardia (40.8 +/- 43.0 mV-mV, P <.0001) and 55 ventricular fibrillation episodes (19.1 +/- 22.8 mV-mV, P <.05). A minimum baseline <0.35 mV-mV threshold had a sensitivity of 83% (20/24) with a 100% (190/190) specificity. A baseline measure of the far-field electrogram had a high sensitivity and specificity to detect lead failure noise compared with ventricular tachycardia or fibrillation.

An algorithm of local earthquake detection from digital records

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A. PROZOROV

1978-06-01

Full Text Available The problem of automatical detection of earthquake signals in seismograms
and definition of first arrivals of p and s waves is considered.
The algorithm is based on the analysis of t(A function which represents
the time of first appearence of a number of going one after another
swings of amplitudes greather than A in seismic signals. It allows to explore
such common features of seismograms of earthquakes as sudden
first p-arrivals of amplitude greater than general amplitude of noise and
after the definite interval of time before s-arrival the amplitude of which
overcomes the amplitude of p-arrival. The method was applied to
3-channel recods of Friuli aftershocks, ¿'-arrivals were defined correctly
in all cases; p-arrivals were defined in most cases using strict criteria of
detection. Any false signals were not detected. All p-arrivals were defined
using soft criteria of detection but less reliability and two false events
were obtained.

An algorithm for leak point detection of underground pipelines

International Nuclear Information System (INIS)

Lee, Young Sup; Yoon, Dong Jin

2004-01-01

Leak noise is a good source to identify the exact location of a leak point of underground water pipelines. Water leak generates broadband noise from a leak location and can be propagated to both directions of water pipes. However, the necessity of long-range detection of this leak location makes to identify low-frequency acoustic waves rather than high frequency ones. Acoustic wave propagation coupled with surrounding boundaries including cast iron pipes is theoretically analyzed and the wave velocity was confirmed with experiment. The leak locations were identified both by the acoustic emission (AE) method and the cross-correlation method. In a short-range distance, both the AE method and cross-correlation method are effective to detect leak position. However, the detection for a long-range distance required a lower frequency range accelerometers only because higher frequency waves were attenuated very quickly with the increase of propagation paths. Two algorithms for the cross-correlation function were suggested, and a long-range detection has been achieved at real underground water pipelines longer than 300 m.

[A cloud detection algorithm for MODIS images combining Kmeans clustering and multi-spectral threshold method].

Science.gov (United States)

Wang, Wei; Song, Wei-Guo; Liu, Shi-Xing; Zhang, Yong-Ming; Zheng, Hong-Yang; Tian, Wei

2011-04-01

An improved method for detecting cloud combining Kmeans clustering and the multi-spectral threshold approach is described. On the basis of landmark spectrum analysis, MODIS data is categorized into two major types initially by Kmeans method. The first class includes clouds, smoke and snow, and the second class includes vegetation, water and land. Then a multi-spectral threshold detection is applied to eliminate interference such as smoke and snow for the first class. The method is tested with MODIS data at different time under different underlying surface conditions. By visual method to test the performance of the algorithm, it was found that the algorithm can effectively detect smaller area of cloud pixels and exclude the interference of underlying surface, which provides a good foundation for the next fire detection approach.

Comparative Study of Outlier Detection Algorithms via Fundamental Analysis Variables: An Application on Firms Listed in Borsa Istanbul

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Senol Emir

2016-04-01

Full Text Available In a data set, an outlier refers to a data point that is considerably different from the others. Detecting outliers provides useful application-specific insights and leads to choosing right prediction models. Outlier detection (also known as anomaly detection or novelty detection has been studied in statistics and machine learning for a long time. It is an essential preprocessing step of data mining process. In this study, outlier detection step in the data mining process is applied for identifying the top 20 outlier firms. Three outlier detection algorithms are utilized using fundamental analysis variables of firms listed in Borsa Istanbul for the 2011-2014 period. The results of each algorithm are presented and compared. Findings show that 15 different firms are identified by three different outlier detection methods. KCHOL and SAHOL have the greatest number of appearances with 12 observations among these firms. By investigating the results, it is concluded that each of three algorithms makes different outlier firm lists due to differences in their approaches for outlier detection.

SHADOW DETECTION FROM VERY HIGH RESOLUTON SATELLITE IMAGE USING GRABCUT SEGMENTATION AND RATIO-BAND ALGORITHMS

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N. M. S. M. Kadhim

2015-03-01

Full Text Available Very-High-Resolution (VHR satellite imagery is a powerful source of data for detecting and extracting information about urban constructions. Shadow in the VHR satellite imageries provides vital information on urban construction forms, illumination direction, and the spatial distribution of the objects that can help to further understanding of the built environment. However, to extract shadows, the automated detection of shadows from images must be accurate. This paper reviews current automatic approaches that have been used for shadow detection from VHR satellite images and comprises two main parts. In the first part, shadow concepts are presented in terms of shadow appearance in the VHR satellite imageries, current shadow detection methods, and the usefulness of shadow detection in urban environments. In the second part, we adopted two approaches which are considered current state-of-the-art shadow detection, and segmentation algorithms using WorldView-3 and Quickbird images. In the first approach, the ratios between the NIR and visible bands were computed on a pixel-by-pixel basis, which allows for disambiguation between shadows and dark objects. To obtain an accurate shadow candidate map, we further refine the shadow map after applying the ratio algorithm on the Quickbird image. The second selected approach is the GrabCut segmentation approach for examining its performance in detecting the shadow regions of urban objects using the true colour image from WorldView-3. Further refinement was applied to attain a segmented shadow map. Although the detection of shadow regions is a very difficult task when they are derived from a VHR satellite image that comprises a visible spectrum range (RGB true colour, the results demonstrate that the detection of shadow regions in the WorldView-3 image is a reasonable separation from other objects by applying the GrabCut algorithm. In addition, the derived shadow map from the Quickbird image indicates

Shadow Detection from Very High Resoluton Satellite Image Using Grabcut Segmentation and Ratio-Band Algorithms

Science.gov (United States)

Kadhim, N. M. S. M.; Mourshed, M.; Bray, M. T.

2015-03-01

Very-High-Resolution (VHR) satellite imagery is a powerful source of data for detecting and extracting information about urban constructions. Shadow in the VHR satellite imageries provides vital information on urban construction forms, illumination direction, and the spatial distribution of the objects that can help to further understanding of the built environment. However, to extract shadows, the automated detection of shadows from images must be accurate. This paper reviews current automatic approaches that have been used for shadow detection from VHR satellite images and comprises two main parts. In the first part, shadow concepts are presented in terms of shadow appearance in the VHR satellite imageries, current shadow detection methods, and the usefulness of shadow detection in urban environments. In the second part, we adopted two approaches which are considered current state-of-the-art shadow detection, and segmentation algorithms using WorldView-3 and Quickbird images. In the first approach, the ratios between the NIR and visible bands were computed on a pixel-by-pixel basis, which allows for disambiguation between shadows and dark objects. To obtain an accurate shadow candidate map, we further refine the shadow map after applying the ratio algorithm on the Quickbird image. The second selected approach is the GrabCut segmentation approach for examining its performance in detecting the shadow regions of urban objects using the true colour image from WorldView-3. Further refinement was applied to attain a segmented shadow map. Although the detection of shadow regions is a very difficult task when they are derived from a VHR satellite image that comprises a visible spectrum range (RGB true colour), the results demonstrate that the detection of shadow regions in the WorldView-3 image is a reasonable separation from other objects by applying the GrabCut algorithm. In addition, the derived shadow map from the Quickbird image indicates significant performance of

Fast iterative censoring CFAR algorithm for ship detection from SAR images

Science.gov (United States)

Gu, Dandan; Yue, Hui; Zhang, Yuan; Gao, Pengcheng

2017-11-01

Ship detection is one of the essential techniques for ship recognition from synthetic aperture radar (SAR) images. This paper presents a fast iterative detection procedure to eliminate the influence of target returns on the estimation of local sea clutter distributions for constant false alarm rate (CFAR) detectors. A fast block detector is first employed to extract potential target sub-images; and then, an iterative censoring CFAR algorithm is used to detect ship candidates from each target blocks adaptively and efficiently, where parallel detection is available, and statistical parameters of G0 distribution fitting local sea clutter well can be quickly estimated based on an integral image operator. Experimental results of TerraSAR-X images demonstrate the effectiveness of the proposed technique.

Consequences of fiducial marker error on three-dimensional computer animation of the temporomandibular joint

Science.gov (United States)

Leader, J. Ken, III; Boston, J. Robert; Rudy, Thomas E.; Greco, Carol M.; Zaki, Hussein S.

2001-05-01

Jaw motion has been used to diagnose jaw pain patients, and we have developed a 3D computer animation technique to study jaw motion. A customized dental clutch was worn during motion, and its consistent and rigid placement was a concern. The experimental protocol involved mandibular movements (vertical opening) and MR imaging. The clutch contained three motion markers used to collect kinematic data and four MR markers used as fiducial markers in the MR images. Fiducial marker misplacement was mimicked by analytically perturbing the position of the MR markers +/- 2, +/- 4, and +/- 6 degrees in the three anatomical planes. The percent difference between the original and perturbed MR marker position was calculated for kinematic parameters. The maximum difference across all perturbations for axial rotation, coronal rotation, sagittal rotation, axial translation, coronal translation, and sagittal translation were 176.85%, 191.84%, 0.64%, 9.76%, 80.75%, and 8.30%, respectively, for perturbing all MR markers, and 86.47%, 93.44%, 0.23%, 7.08%, 42.64%, and 13.64%, respectively, for perturbing one MR marker. The parameters representing movement in the sagittal plane, the dominant plane in vertical opening, were determined to be reasonably robust, while secondary movements in the axial and coronal planes were not considered robust.