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At least 811 records · Page 45

A Rotor Tip Vortex Tracing Algorithm for Image Post-Processing

A neurite tracing algorithm, originally developed for medical image processing, was used to trace the location of the rotor tip vortex in density gradient flow visualization images. The tracing algorithm was applied to several representative test images to form case studies. The accuracy of the tracing algorithm was compared to two current methods including a manual point and click method and a cross-correlation template method. It is shown that the neurite tracing algorithm can reduce the post-processing time to trace the vortex by a factor of 10 to 15 without compromising the accuracy of the tip vortex location compared to other methods presented in literature.

Overmeyer, Austin D.↗

TH-CD-206-01: Expectation-Maximization Algorithm-Based Tissue Mixture Quantification for Perfusion MRI

Purpose: To investigate the feasibility of estimating the tissue mixture perfusions and quantifying cerebral blood flow change in arterial spin labeled (ASL) perfusion MR images. Methods: The proposed perfusion MR image analysis framework consists of 5 steps: (1) Inhomogeneity correction was performed on the T1- and T2-weighted images, which are available for each studied perfusion MR dataset. (2) We used the publicly available FSL toolbox to strip off the non-brain structures from the T1- and T2-weighted MR images. (3) We applied a multi-spectral tissue-mixture segmentation algorithm on both T1- and T2-structural MR images to roughly estimate the fraction of each tissue type - white matter, grey matter and cerebral spinal fluid inside each image voxel. (4) The distributions of the three tissue types or tissue mixture across the structural image array are down-sampled and mapped onto the ASL voxel array via a co-registration operation. (5) The presented 4-dimensional expectation-maximization (4D-EM) algorithm takes the down-sampled three tissue type distributions on perfusion image data to generate the perfusion mean, variance and percentage images for each tissue type of interest. Results: Experimental results on three volunteer datasets demonstrated that the multi-spectral tissue-mixture segmentation algorithm was effective to initialize tissue mixtures from T1- and T2-weighted MR images. Compared with the conventional ASL image processing toolbox, the proposed 4D-EM algorithm not only generated comparable perfusion mean images, but also produced perfusion variance and percentage images, which the ASL toolbox cannot obtain. It is observed that the perfusion contribution percentages may not be the same as the corresponding tissue mixture volume fractions estimated in the structural images. Conclusion: A specific application to brain ASL images showed that the presented perfusion image analysis method is promising for detecting subtle changes in tissue perfusions, which is valuable for the early diagnosis of certain brain diseases, e.g. multiple sclerosis.

60 APPLIED LIFE SCIENCES↗

Synchronized Docking System

A synchronized target subsystem for use in an automated docking system for docking a chase vehicle with a target vehicle wherein the chase vehicle is provided with a video camera for feeding digitized frames to an image processing unit which feeds signals to a control circuit. The control circuit turns on the video camera to digitize a background frame which will include the target vehicle. After the camera grabs the background frame the control circuit turns on a light, which is carried by carried on the chase vehicle and aimed at the target vehicle, and signals the video camera to digitize a foreground frame. A light sensing circuit on the target vehicle receives the light from the chase vehicle and connects a power supply to lights on the target vehicle such that when the foreground frame is digitized the Lights on the target vehicle will show in the foreground frame. Die image processing unit subtracts the background frame from the foreground frame and provides a docking signal.

Richard T Howard↗

SU-E-J-219: A Dixon Based Pseudo-CT Generation Method for MR-Only Radiotherapy Treatment Planning of the Pelvis and Head and Neck

Purpose: To develop an image processing method for MRI-based generation of electron density maps, known as pseudo-CT (pCT), without usage of model- or atlas-based segmentation, and to evaluate the method in the pelvic and head-neck region against CT. Methods: CT and MRI scans were obtained from the pelvic region of four patients in supine position using a flat table top only for CT. Stratified CT maps were generated by classifying each voxel based on HU ranges into one of four classes: air, adipose tissue, soft tissue or bone.A hierarchical region-selective algorithm, based on automatic thresholding and clustering, was used to classify tissues from MR Dixon reconstructed fat, In-Phase (IP) and Opposed-Phase (OP) images. First, a body mask was obtained by thresholding the IP image. Subsequently, an automatic threshold on the Dixon fat image differentiated soft and adipose tissue. K-means clustering on IP and OP images resulted in a mask that, via a connected neighborhood analysis, allowing the user to select the components corresponding to bone structures.The pCT was estimated through assignment of bulk HU to the tissue classes. Bone-only Digital Reconstructed Radiographs (DRR) were generated as well. The pCT images were rigidly registered to the stratified CT to allow a volumetric and voxelwise comparison. Moreover, pCTs were also calculated within the head-neck region in two volunteers using the same pipeline. Results: The volumetric comparison resulted in differences <1% for each tissue class. A voxelwise comparison showed a good classification, ranging from 64% to 98%. The primary misclassified classes were adipose/soft tissue and bone/soft tissue. As the patients have been imaged on different table tops, part of the misclassification error can be explained by misregistration. Conclusion: The proposed approach does not rely on an anatomy model providing the flexibility to successfully generate the pCT in two different body sites. This research is founded by ZonMw IMDI Programme, project name: “RASOR sharp: MRI based radiotherapy planning using a single MRI sequence”, project number: 10-104003010.

60 APPLIED LIFE SCIENCES↗

Hybrid Image-Plane/Stereo Manipulation

Hybrid Image-Plane/Stereo (HIPS) manipulation is a method of processing image data, and of controlling a robotic manipulator arm in response to the data, that enables the manipulator arm to place an end-effector (an instrument or tool) precisely with respect to a target (see figure). Unlike other stereoscopic machine-vision-based methods of controlling robots, this method is robust in the face of calibration errors and changes in calibration during operation. In this method, a stereoscopic pair of cameras on the robot first acquires images of the manipulator at a set of predefined poses. The image data are processed to obtain image-plane coordinates of known visible features of the end-effector. Next, there is computed an initial calibration in the form of a mapping between (1) the image-plane coordinates and (2) the nominal three-dimensional coordinates of the noted end-effector features in a reference frame fixed to the main robot body at the base of the manipulator. The nominal three-dimensional coordinates are obtained by use of the nominal forward kinematics of the manipulator arm that is, calculated by use of the currently measured manipulator joint angles and previously measured lengths of manipulator arm segments under the assumption that the arm segments are rigid, that the arm lengths are constant, and that there is no backlash. It is understood from the outset that these nominal three-dimensional coordinates are likely to contain possibly significant calibration errors, but the effects of the errors are progressively reduced, as described next. As the end-effector is moved toward the target, the calibration is updated repeatedly by use of data from newly acquired images of the end-effector and of the corresponding nominal coordinates in the manipulator reference frame. By use of the updated calibration, the coordinates of the target are computed in manipulator-reference-frame coordinates and then used to the necessary manipulator joint angles to position and orient the end-effector at the target with respect to the same kinematic model from the calibration step. As the end-effector/target distance decreases, the computed coordinates of the end-effector and target become more nearly affected by the same errors, so that the differences between their coordinates become increasingly precise. When the end-effector reaches the target, the remaining effective position error is the distance that corresponds to more than about one pixel in the stereoscopic images of the target.

Baumgartner, Eric↗

Effect of Bath Depth and Nozzle Geometry on Spout Height in Submerged Gas Injection at Bottom

Spout height is a widely used parameter to quantitatively analyze the performance of the submerged gas injection in industrial applications. However, the effect of bath depth and nozzle geometry on spout height in submerged gas injection is still unclear. In this work, the effect of bath depth and nozzle geometry on spout height in submerged gas injection at bottom was experimentally investigated. Circular-shaped, three-leaf-shaped, four-leaf-shaped, and four-flower-shaped nozzles were used for this study. Spout height was extracted from the images captured by high-speed camera and analyzed by digital image processing. The results indicate that the effect of nozzle geometry on spout height is as important as gas flow rate and bath depth. Through dimensional analysis, predictive correlations of spout height from circular shape and four-leaf shape were developed with dimensionless bath depth and a modified Froude number using orifice perimeter and opening area as characteristic parameters. Experimental data were compared with the correlations from literature and good agreement was found.

36 MATERIALS SCIENCE↗

SU-E-J-191: Motion Prediction Using Extreme Learning Machine in Image Guided Radiotherapy

Purpose: Real-time motion tracking is a critical issue in image guided radiotherapy due to the time latency caused by image processing and system response. It is of great necessity to fast and accurately predict the future position of the respiratory motion and the tumor location. Methods: The prediction of respiratory position was done based on the positioning and tracking module in ARTS-IGRT system which was developed by FDS Team (www.fds.org.cn). An approach involving with the extreme learning machine (ELM) was adopted to predict the future respiratory position as well as the tumor’s location by training the past trajectories. For the training process, a feed-forward neural network with one single hidden layer was used for the learning. First, the number of hidden nodes was figured out for the single layered feed forward network (SLFN). Then the input weights and hidden layer biases of the SLFN were randomly assigned to calculate the hidden neuron output matrix. Finally, the predicted movement were obtained by applying the output weights and compared with the actual movement. Breathing movement acquired from the external infrared markers was used to test the prediction accuracy. And the implanted marker movement for the prostate cancer was used to test the implementation of the tumor motion prediction. Results: The accuracy of the predicted motion and the actual motion was tested. Five volunteers with different breathing patterns were tested. The average prediction time was 0.281s. And the standard deviation of prediction accuracy was 0.002 for the respiratory motion and 0.001 for the tumor motion. Conclusion: The extreme learning machine method can provide an accurate and fast prediction of the respiratory motion and the tumor location and therefore can meet the requirements of real-time tumor-tracking in image guided radiotherapy.

60 APPLIED LIFE SCIENCES↗

Characterization and correction of charge-induced pixel shifts in DECam

Interaction of charges in CCDs with the already accumulated charge distribution causes both a flux dependence of the point-spread function (an increase of observed size with flux, also known as the brighter/fatter effect) and pixel-to-pixel correlations of the Poissonian noise in flat fields. We describe these effects in the Dark Energy Camera (DECam) with charge dependent shifts of effective pixel borders, i.e. the Antilogus et al. (2014) model, which we fit to measurements of flat-field Poissonian noise correlations. The latter fall off approximately as a power-law r -2.5 with pixel separation r, are isotropic except for an asymmetry in the direct neighbors along rows and columns, are stable in time, and are weakly dependent on wavelength. They show variations from chip to chip at the 20% level that correlate with the silicon resistivity. The charge shifts predicted by the model cause biased shape measurements, primarily due to their effect on bright stars, at levels exceeding weak lensing science requirements. We measure the flux dependence of star images and show that the effect can be mitigated by applying the reverse charge shifts at the pixel level during image processing. Differences in stellar size, however, remain significant due to residuals at larger distance from the centroid.

79 ASTRONOMY AND ASTROPHYSICS↗

SU-F-I-45: An Automated Technique to Measure Image Contrast in Clinical CT Images

Purpose: To develop and validate an automated technique for measuring image contrast in chest computed tomography (CT) exams. Methods: An automated computer algorithm was developed to measure the distribution of Hounsfield units (HUs) inside four major organs: the lungs, liver, aorta, and bones. These organs were first segmented or identified using computer vision and image processing techniques. Regions of interest (ROIs) were automatically placed inside the lungs, liver, and aorta and histograms of the HUs inside the ROIs were constructed. The mean and standard deviation of each histogram were computed for each CT dataset. Comparison of the mean and standard deviation of the HUs in the different organs provides different contrast values. The ROI for the bones is simply the segmentation mask of the bones. Since the histogram for bones does not follow a Gaussian distribution, the 25th and 75th percentile were computed instead of the mean. The sensitivity and accuracy of the algorithm was investigated by comparing the automated measurements with manual measurements. Fifteen contrast enhanced and fifteen non-contrast enhanced chest CT clinical datasets were examined in the validation procedure. Results: The algorithm successfully measured the histograms of the four organs in both contrast and non-contrast enhanced chest CT exams. The automated measurements were in agreement with manual measurements. The algorithm has sufficient sensitivity as indicated by the near unity slope of the automated versus manual measurement plots. Furthermore, the algorithm has sufficient accuracy as indicated by the high coefficient of determination, R2, values ranging from 0.879 to 0.998. Conclusion: Patient-specific image contrast can be measured from clinical datasets. The algorithm can be run on both contrast enhanced and non-enhanced clinical datasets. The method can be applied to automatically assess the contrast characteristics of clinical chest CT images and quantify dependencies that may not be captured in phantom data.

60 APPLIED LIFE SCIENCES↗

Wavelet Denoising of Radio Observations of Rotating Radio Transients (RRATs): Improved Timing Parameters for Eight RRATs

Rotating radio transients (RRATs) are sporadically emitting pulsars detectable only through searches for single pulses. While over 100 RRATs have been detected, only a small fraction (roughly 20%) have phase-connected timing solutions, which are critical for determining how they relate to other neutron star populations. Detecting more pulses in order to achieve solutions is key to understanding their physical nature. Astronomical signals collected by radio telescopes contain noise from many sources, making the detection of weak pulses difficult. Applying a denoising method to raw time series prior to performing a single-pulse search typically leads to a more accurate estimation of their times of arrival (TOAs). Taking into account some features of RRAT pulses and noise, we present a denoising method based on wavelet data analysis, an image-processing technique. Assuming that the spin period of an RRAT is known, we estimate the frequency spectrum components contributing to the composition of RRAT pulses. This allows us to suppress the noise, which contributes to other frequencies. We apply the wavelet denoising method including selective wavelet reconstruction and wavelet shrinkage to the de-dispersed time series of eight RRATs with existing timing solutions. The signal-to-noise ratio (S/N) of most pulses are improved after wavelet denoising. Compared to the conventional approach, we measure 12%–69% more TOAs for the eight RRATs. The new timing solutions for the eight RRATs show 16%–90% smaller estimation error of most parameters. Thus, we conclude that wavelet analysis is an effective tool for denoising RRATs signal.

79 ASTRONOMY AND ASTROPHYSICS↗

SU-F-T-70: A High Dose Rate Total Skin Electron Irradiation Technique with A Specific Inter-Film Variation Correction Method for Very Large Electron Beam Fields

Purpose: Rotational total skin electron irradiation (RTSEI) is used in the treatment of cutaneous T-cell lymphoma. Due to inter-film uniformity variations the dosimetry measurement of a large electron beam of a very low energy is challenging. This work provides a method to improve the accuracy of flatness and symmetry for a very large treatment field of low electron energy used in dual beam RTSEI. Methods: RTSEI is delivered by dual angles field a gantry of ±20 degrees of 270 to cover the upper and the lower halves of the patient body with acceptable beam uniformity. The field size is in the order of 230cm in vertical height and 120 cm in horizontal width and beam energy is a degraded 6 MeV (6 mm of PMMA spoiler). We utilized parallel plate chambers, Gafchromic films and OSLDs as a measuring devices for absolute dose, B-Factor, stationary and rotational percent depth dose and beam uniformity. To reduce inter-film dosimetric variation we introduced a new specific correction method to analyze beam uniformity. This correction method uses some image processing techniques combining film value before and after radiation dose to compensate the inter-variation dose response differences among films. Results: Stationary and rotational depth of dose demonstrated that the Rp is 2 cm for rotational and the maximum dose is shifted toward the surface (3mm). The dosimetry for the phantom showed that dose uniformity reduced to 3.01% for the vertical flatness and 2.35% for horizontal flatness after correction thus achieving better flatness and uniformity. The absolute dose readings of calibrated films after our correction matched with the readings from OSLD. Conclusion: The proposed correction method for Gafchromic films will be a useful tool to correct inter-film dosimetric variation for the future clinical film dosimetry verification in very large fields, allowing the optimizations of other parameters.

60 APPLIED LIFE SCIENCES↗

MO-DE-BRA-04: The CREATE Medical Physics Research Training Network: Training of New Generation Innovators

Purpose: Over the past century, physicists have played a major role in transforming scientific discovery into everyday clinical applications. However, with the increasingly stringent requirements to regulate medical physics as a health profession, the role of physicists as scientists and innovators has become at serious risk of erosion. These challenges trigger the need for a new, revolutionized training program at the graduate level that respects scientific rigor, attention for medical physics-relevant developments in basic sciences, innovation and entrepreneurship. Methods: A grant proposal was funded by the Collaborative REsearch and Training Experience program (CREATE) of the Natural Sciences and Engineering Research Council (NSERC) of Canada. This enabled the creation of the Medical Physics Research Training Network (MPRTN) around two CAMPEP-accredited medical physics programs. Members of the network consist of medical device companies, government (research and regulatory) and academia. The MPRTN/CREATE program proposes a curriculum with three main themes: (1) radiation physics, (2) imaging & image processing and (3) radiation response, outcomes and modeling. Results: The MPRTN was created mid 2013 (mprtn.com) and features (1) four new basic Ph.D. courses; (2) industry participation in research projects; (3) formal job-readiness training with involvement of guest faculty from academia, government and industry. MPRTN activities since 2013 include 22 conferences; 7 workshops and 4 exchange travels. Three patents were filed or issued, nine awards/best papers were won. Fifteen journal publications were accepted/published, 102 conference abstracts. There are now 13 industry partners. Conclusion: A medical physics research training network has been set up with the goal to harness graduate student’s job-readiness for industry, government and academia in addition to the conventional clinical role. Two years after inception, significant successes have been booked, but the true challenge will be to demonstrate that with this training philosophy CREATE scholars gain access to a much broader job market. Supported by the Natural Sciences and Engineering Research Council (NSERC) Canada.

60 APPLIED LIFE SCIENCES↗

Enhancement of the jets in NGC 1097

Plates of NGC 1097 taken in four spectral bands have been digitized and processed at JPL's Image Processing Laboratory. The processing has revealed that (1) there is a fourth jet, R4, counter to the L-shaped jet, R1; (2) the area density of point sources in the jets is no different from that found on the sky; (3) two of the jets, R1 and R2, are bluer than the night sky, while one of the jets, R3, is redder than the night sky; (4) the nonstellar objects situated on the jets are noticeably bluer than the night sky; and (5) color-enhanced images of the spiral structure illustrate the distribution of both gaseous and spiral-arm stellar population disrupted from symmetry by an apparent companion elliptical.

Lorre, J. J.↗

SU-F-J-190: Time Resolved Range Measurement System Using Scintillator and CCD Camera for the Slow Beam Extraction

Purpose: To investigate the time structure of the range, we have verified the rang shift due to the betatron tune shift with several synchrotron parameters. Methods: A cylindrical plastic scintillator block and a CCD camera were installed on the black box. Using image processing, the range was determined the 80 percent of distal dose of the depth light distribution. The root mean square error of the range measurement using the scintillator and CCD system is about 0.2 mm. Range measurement was performed at interval of 170 msec. The chromaticity of the synchrotron was changed in the range of plus or minus 1% from reference chromaticity in this study. All of the particle inside the synchrotron ring were extracted with the output beam intensity 1.8×10{sup 8} and 5.0×10{sub 7} particle per sec. Results: The time strictures of the range were changed by changing of the chromaticity. The reproducibility of the measurement was sufficient to observe the time structures of the range. The range shift was depending on the number of the residual particle inside the synchrotron ring. Conclusion: In slow beam extraction for scanned carbon-ion therapy, the range shift is undesirable because it causes the dose uncertainty in the target. We introduced the time-resolved range measurement using scintillator and CCD system. The scintillator and CCD system have enabled to verify the range shift with sufficient spatial resolution and reproducibility.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A General Framework for Monitoring Image Acquisition Workflow in the Radiology Environment: Timeliness for Acute Stroke CT Imaging

Many facets of an image acquisition workflow leave a digital footprint, making workflow analysis amenable to an informatics-based solution. This paper describes a detailed framework for analyzing workflow and uses acute stroke response timeliness in CT as a practical demonstration. We review methods for accessing the digital footprints resulting from common technologist/device interactions. This overview lays a foundation for obtaining data for workflow analysis. We demonstrate the method by analyzing CT imaging efficiency in the setting of acute stroke. We successfully used digital footprints of CT technologists to analyze their workflow. We presented an overview of other digital footprints including but not limited to contrast administration, patient positioning, billing, reformat creation, and scheduling. A framework for analyzing image acquisition workflow was presented. This framework is transferable to any modality, as the key steps of image acquisition, image reconstruction, image post processing, and image transfer to PACS are common to any imaging modality in diagnostic radiology.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Eliciting the impacts of cellular noise on metabolic trade-offs by quantitative mass imaging

Metabolic trade-offs between growth and productivity are key constraints in metabolic engineering and adaptive evolution; however, how cellular noise impacts these trade offs and drives the emergence of subpopulations with distinct resource allocation strategies, remains largely unknown. Here, we introduce a single-cell strategy for quantifying the trade-offs between triacylglycerol production and growth in the oleaginous microorganism Yarrowia lipolytica. The strategy relies on high-throughput quantitative-phase imaging and, enabled by nanoscale secondary ion mass spectrometry analyses and dedicated image processing, allows us to image how resources are partitioned between growth and productivity. Enhanced precision over population-averaging biotechnologies and conventional microscopy demonstrates how cellular noise impacts growth and productivity differently. As such, subpopulations with distinct metabolic trade-offs emerge, with notable impacts on strain performance and robustness. By quantifying autophagic catabolic fluxes under nutrient-limiting conditions, we discover an underlying cell-to-cell heterogeneity in protein and fatty-acid recycling, unmasking a potential bet-hedging survival strategy under starvation.

59 BASIC BIOLOGICAL SCIENCES↗

Spatiotemporal Learning in Power Modules: Wavelet-Enhanced Forecasting of Thermomechanical Degradation

Detecting internal defects in power electronics packages is critical for their performance and reliability, especially under extreme operating conditions, as these defects can lead to catastrophic failure if not properly addressed. Confocal scanning acoustic microscopy (C-SAM) plays a key role in the nondestructive evaluation of bond layer degradation within a power electronics package by detecting defects such as delamination, voids, and cracks. However, accurately quantifying and predicting these defects from C-SAM images remains a significant challenge due to the low noise-to-signal ratio, which typically arises from both imaging process and bond patterns itself. In this paper, we explore machine learning strategies for processing C-SAM images and providing predictive models of defect growth. We use C-SAM images of sintered copper and sintered silver samples, which are obtained under accelerated thermal experiments, as the representative dataset for our study. We investigate the effect of Fourier transforms and wavelet transforms on these datasets to remove high-frequency noise and address noise across multiple scales with histogram equalization to enhance the contrast and improve the visibility of defects. As a result, defect boundaries can be clearly distinguished, enabling more accurate tracking of their growth over time. We then employ different time-series forecasting algorithms on the denoised images to formulate an image-based lifetime prediction model. Statistical models and deep-learning techniques are trained on images obtained in the early stages of thermal shock, and defect growth in the later stages is predicted. Our work serves as a preliminary attempt to improve the accuracy of lifetime prediction models of power electronics packages, which is critical under extreme operating environments.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Searching for Subsecond Stellar Variability with Wide-field Star Trails and Deep Learning

We present here a method that enables wide-field ground-based telescopes to scan the sky for subsecond stellar variability. The method has operational and image processing components. The operational component takes star trail images. Each trail serves as a light curve for its corresponding source and facilitates subexposure photometry. We train a deep neural network to identify stellar variability in wide-field star trail images. We use the Large Synoptic Survey Telescope Photon Simulator to generate simulated star trail images and include transient bursts as a proxy for variability. The network identifies transient bursts on timescales down to 10 ms. We argue that there are multiple fields of astrophysics that can be advanced by the unique combination of time resolution and observing throughput that our method offers.

79 ASTRONOMY AND ASTROPHYSICS↗