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At least 1,729 records · Page 96
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DOE OSTI2019

Functional and Anatomical Imaging in Patients with Ischemic Symptoms and Known Coronary Artery Disease

Purpose of Review: This review is aimed at summarizing recent advances in functional, anatomical, and hybrid imaging techniques used in the assessment of ischemic complaints in patients with known coronary artery disease (CAD). Recent Findings: Cardiovascular imaging has seen significant growth over the last decade in the fields of coronary computed tomography angiography (CCTA), FFR derived from CCTA, cardiac magnetic resonance, radionuclide myocardial perfusion imaging, and hybrid imaging for the purposes of evaluating symptoms concerning for ischemia. This growth stems from refinement of imaging techniques and hardware and software advances that have made current techniques more accurate with less acquisition time. However, every anatomic and functional imaging modality has important technical and patient-specific limitations. This review assesses these issues, guides a patient-centered imaging approach, and identifies important research questions to resolve. Summary: Recent advances in non-invasive cardiovascular imaging can provide important information in patients with known CAD beyond traditional imaging techniques; the use of these novel tools refines the clinical management of complex patients with ischemic symptoms and known CAD.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

A combined static-dynamic single-dose imaging protocol to compare quantitative dynamic SPECT with static conventional SPECT

Background: SPECT myocardial perfusion imaging (MPI) is a clinical mainstay that is typically performed with static imaging protocols and visually or semi-quantitatively assessed for perfusion defects based upon the relative intensity of myocardial regions. Dynamic cardiac SPECT presents a new imaging technique based on time-varying information of radiotracer distribution, which permits the evaluation of regional myocardial blood flow (MBF) and coronary flow reserve (CFR). In this work, a preliminary feasibility study was conducted in a small patient sample designed to implement a unique combined static-dynamic single-dose one-day visit imaging protocol to compare quantitative dynamic SPECT with static conventional SPECT for improving the diagnosis of coronary artery disease (CAD). Methods: Fifteen patients (11 males, four females, mean age 71 ± 9 years) were enrolled for a combined dynamic and static SPECT (Infinia Hawkeye 4, GE Healthcare) imaging protocol with a single dose of {sup 99m}Tc-tetrofosmin administered at rest and a single dose administered at stress in a one-day visit. Out of 15 patients, eleven had selective coronary angiography (SCA), 8 within 6 months and the rest within 24 months of SPECT imaging, without intervening symptoms or interventions. The extent and severity of perfusion defects in each myocardial region was graded visually. Dynamically acquired data were also used to estimate the MBF and CFR. Both visually graded images and estimated CFR were tested against SCA as a reference to evaluate the validity of the methods. Results: Overall, conventional static SPECT was normal in ten patients and abnormal in five patients, dynamic SPECT was normal in 12 patients and abnormal in three patients, and CFR from dynamic SPECT was normal in nine patients and abnormal in six patients. Among those 11 patients with SCA, conventional SPECT was normal in 5, 3 with documented CAD on SCA with an overall accuracy of 64%, sensitivity of 40% and specificity of 83%. Dynamic SPECT image analysis also produced a similar accuracy, sensitivity, and specificity. CFR was normal in 6, each with CAD on SCA with an overall accuracy of 91%, sensitivity of 80%, and specificity of 100%. The mean CFR was significantly lower for SCA detected abnormal than for normal patients (3.86±1.06 vs 1.94±0. 0.67, P < 0.001). Conclusions: The visually assessed image findings in static and dynamic SPECT are subjective, and may not reflect direct physiologic measures of coronary lesion based on SCA. The CFR measured with dynamic SPECT is fully objective, with better sensitivity and specificity, available only with the data generated from the dynamic SPECT method.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

A New Workflow of X-ray CT Image Processing and Data Analysis of Structural Features in Rock Using Open-Source Software

X-ray computed tomography (CT) images of rock specimens often contain artifacts which must be corrected before scientific analyses are performed. Here, we present a new workflow of automated image processing to utilize poor-quality X-ray CT scan images. The workflow runs on the open-source image analysis software and efficiently separates desired features from low-contrast scanned images. The new workflow is a two-step technique using contrast enhancement and automated feature segmentation to generate noise-free binary images. The results of binary images using the proposed workflow and using a conventional thresholding technique are analyzed to show the quality of the proposed method. The paper also presents a workflow of estimating the structural geometries of features in two and three dimensions. The results of the structural feature analyses and computational time were compared between the open-source (ImageJ) and commercial image analysis software (Bruker Computed Tomography Analyzer). The commercial software was more computationally efficient, but the task-specific macros in open-source software enabled the user-desired automation in image processing and data extraction of desired structural features of comparable quality.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Paw-Net: Stacking ensemble deep learning for segmenting scanning electron microscopy images of fine-grained shale samples

Segmentation of scanning electron microscopy (SEM) images is critical yet time-consuming for geological analyses, as it needs to differentiate the boundaries for different mineral objects to facilitate subsequent analyses, such as porosity calculation. Recently, various machine learning methods, especially convolutional neural networks (CNNs), have been explored to segment SEM images of fine-grained shale samples. However, we found that general CNNs do not yield optimal performance due to insufficient training data and imbalanced objects in SEM images. This work has revised the U-Net architecture, a popular approach for biomedical image analyses, by incorporating a loss function that addresses the imbalance issue. Furthermore, we used the ensemble learning method to train multiple models and combined the results to improve the overall performance of segmentation. We prepared 2162 sub-images from raw SEM images in our experiments and divided them into training, validation, and testing datasets. The overall results show that our method improves the average Intersection over Union (IOU) of mineral objects from 0.49 to 0.58, compared to the original U-Net model. Our method can clearly distinguish each object from others with boundaries, even in highly imbalanced images. Training our models takes less than three minutes using a single GPU, while manual labeling can take up to three hours for each image. Furthermore, the method helps geoscientists gain insights quickly and effectively by building neural network models from a small dataset of SEM images.

58 GEOSCIENCES↗
DOE OSTI2013

Automatic Prostate Tracking and Motion Assessment in Volumetric Modulated Arc Therapy With an Electronic Portal Imaging Device

Purpose: To assess the prostate intrafraction motion in volumetric modulated arc therapy treatments using cine megavoltage (MV) images acquired with an electronic portal imaging device (EPID). Methods and Materials: Ten prostate cancer patients were treated with volumetric modulated arc therapy using a Varian TrueBeam linear accelerator equipped with an EPID for acquiring cine MV images during treatment. Cine MV images acquisition was scheduled for single or multiple treatment fractions (between 1 and 8). A novel automatic fiducial detection algorithm that can handle irregular multileaf collimator apertures, field edges, fast leaf and gantry movement, and MV image noise and artifacts in patient anatomy was used. All sets of images (approximately 25,000 images in total) were analyzed to measure the positioning accuracy of implanted fiducial markers and assess the prostate movement. Results: Prostate motion can vary greatly in magnitude among different patients. Different motion patterns were identified, showing its unpredictability. The mean displacement and standard deviation of the intrafraction motion was generally less than 2.0 ± 2.0 mm in each of the spatial directions. In certain patients, however, the percentage of the treatment time in which the prostate is displaced more than 5 mm from its planned position in at least 1 spatial direction was 10% or more. The maximum prostate displacement observed was 13.3 mm. Conclusion: Prostate tracking and motion assessment was performed with MV imaging and an EPID. The amount of prostate motion observed suggests that patients will benefit from its real-time monitoring. Megavoltage imaging can provide the basis for real-time prostate tracking using conventional linear accelerators.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Accelerating Dynamic Magnetic Resonance Imaging (MRI) for Lung Tumor Tracking Based on Low-Rank Decomposition in the Spatial–Temporal Domain: A Feasibility Study Based on Simulation and Preliminary Prospective Undersampled MRI

Purpose: To evaluate a low-rank decomposition method to reconstruct down-sampled k-space data for the purpose of tumor tracking. Methods and Materials: Seven retrospective lung cancer patients were included in the simulation study. The fully-sampled k-space data were first generated from existing 2-dimensional dynamic MR images and then down-sampled by 5 × -20 × before reconstruction using a Cartesian undersampling mask. Two methods, a low-rank decomposition method using combined dynamic MR images (k-t SLR based on sparsity and low-rank penalties) and a total variation (TV) method using individual dynamic MR frames, were used to reconstruct images. The tumor trajectories were derived on the basis of autosegmentation of the resultant images. To further test its feasibility, k-t SLR was used to reconstruct prospective data of a healthy subject. An undersampled balanced steady-state free precession sequence with the same undersampling mask was used to acquire the imaging data. Results: In the simulation study, higher imaging fidelity and low noise levels were achieved with the k-t SLR compared with TV. At 10 × undersampling, the k-t SLR method resulted in an average normalized mean square error <0.05, as opposed to 0.23 by using the TV reconstruction on individual frames. Less than 6% showed tracking errors >1 mm with 10 × down-sampling using k-t SLR, as opposed to 17% using TV. In the prospective study, k-t SLR substantially reduced reconstruction artifacts and retained anatomic details. Conclusions: Magnetic resonance reconstruction using k-t SLR on highly undersampled dynamic MR imaging data results in high image quality useful for tumor tracking. The k-t SLR was superior to TV by better exploiting the intrinsic anatomic coherence of the same patient. The feasibility of k-t SLR was demonstrated by prospective imaging acquisition and reconstruction.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Evaluation of Online/Offline Image Guidance/Adaptation Approaches for Prostate Cancer Radiation Therapy

Purpose: To evaluate online/offline image-guided/adaptive treatment techniques for prostate cancer radiation therapy with daily cone-beam CT (CBCT) imaging. Methods and Materials: Three treatment techniques were evaluated retrospectively using daily pre- and posttreatment CBCT images on 22 prostate cancer patients. Prostate, seminal vesicles (SV), rectal wall, and bladder were delineated on all CBCT images. For each patient, a pretreatment intensity modulated radiation therapy plan with clinical target volume (CTV) = prostate + SV and planning target volume (PTV) = CTV + 3 mm was created. The 3 treatment techniques were as follows: (1) Daily Correction: The pretreatment intensity modulated radiation therapy plan was delivered after online CBCT imaging, and position correction; (2) Online Planning: Daily online inverse plans with 3-mm CTV-to-PTV margin were created using online CBCT images, and delivered; and (3) Hybrid Adaption: Daily Correction plus an offline adaptive inverse planning performed after the first week of treatment. The adaptive plan was delivered for all remaining 15 fractions. Treatment dose for each technique was constructed using the daily posttreatment CBCT images via deformable image registration. Evaluation was performed using treatment dose distribution in target and critical organs. Results: Treatment equivalent uniform dose (EUD) for the CTV was within [85.6%, 100.8%] of the pretreatment planned target EUD for Daily Correction; [98.7%, 103.0%] for Online Planning; and [99.2%, 103.4%] for Hybrid Adaptation. Eighteen percent of the 22 patients in Daily Correction had a target dose deficiency >5%. For rectal wall, the mean ± SD of the normalized EUD was 102.6% ± 2.7% for Daily Correction, 99.9% ± 2.5% for Online Planning, and 100.6% ± 2.1% for Hybrid Adaptation. The mean ± SD of the normalized bladder EUD was 108.7% ± 8.2% for Daily Correction, 92.7% ± 8.6% for Online Planning, and 89.4% ± 10.8% for Hybrid Adaptation. Conclusions: Both Online Planning and Hybrid Adaptation can achieve comparable target coverage and normal tissue sparing and are superior to the Daily Correction technique. The Daily Correction technique using a 3-mm target margin in the pretreatment plan is not appropriate to compensate for residual variations in CBCT image-guided prostate cancer radiation therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

SREMI: Super-resolution electromagnetic imaging with single-channel ground-penetrating radar

High-resolution near-surface imaging has important applications in civil engineering, infrastructure inspection, military threat detection, geological characterization, and lunar and planetary exploration. Zero-offset, singlechannel ground penetrating radar (GPR) imaging is an established technique for near-surface target imaging and sensing but often suffers from low spatial resolution and imaging artifacts, especially of deep structures. In response, we formulate the GPR imaging as a dual-sparsity optimization problem, and develop a super-resolution electromagnetic imaging method based on a fast iterative shrinkage-thresholding algorithm. We develop our GPR imaging method in the framework of electromagnetic exploding-reflectors simulation theory, therefore the imaging method is computationally efficient. In this work, we demonstrate through synthetic and field data examples that our method can produce sharper, more reliable images with fewer artifacts compared with single-pass reverse-time migration GPR method, thus leading to improved near-surface interpretation and object identification.

58 GEOSCIENCES↗
DOE OSTI2021

Converting tabular data into images for deep learning with convolutional neural networks

Abstract Convolutional neural networks (CNNs) have been successfully used in many applications where important information about data is embedded in the order of features, such as speech and imaging. However, most tabular data do not assume a spatial relationship between features, and thus are unsuitable for modeling using CNNs. To meet this challenge, we develop a novel algorithm, image generator for tabular data (IGTD), to transform tabular data into images by assigning features to pixel positions so that similar features are close to each other in the image. The algorithm searches for an optimized assignment by minimizing the difference between the ranking of distances between features and the ranking of distances between their assigned pixels in the image. We apply IGTD to transform gene expression profiles of cancer cell lines (CCLs) and molecular descriptors of drugs into their respective image representations. Compared with existing transformation methods, IGTD generates compact image representations with better preservation of feature neighborhood structure. Evaluated on benchmark drug screening datasets, CNNs trained on IGTD image representations of CCLs and drugs exhibit a better performance of predicting anti-cancer drug response than both CNNs trained on alternative image representations and prediction models trained on the original tabular data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Synthetic aperture microwave imaging with active probing for fusion plasma diagnostics

A Synthetic Aperture Microwave Imaging (SAMI) system has been designed and built to obtain 2-D images at several frequencies from fusion plasmas. SAMI uses a phased array of linearly polarised antennas. The array configuration has been optimised to achieve maximum synthetic aperture beam efficiency. The signals received by antennas are down-converted to the intermediate frequency range and then recorded in a full vector form. Full vector signals allow beam focusing and image reconstruction in both real time and a post-processing mode. SAMI can scan over 16 pre-programmed frequencies in the range of 10-35GHz with a switching time of 300ns. The system operates in 2 different modes simultaneously: both a 'passive' imaging of plasma emission and also an 'active' imaging of the back-scattered signal of the radiation launched by one of the antennas from the same array. This second mode is similar to so-called Doppler backscattering (DBS) reflectometry with 2-D resolution of the propagation velocity of turbulent structures. Both modes of operation show good performance in fusion plasma experiments on Mega Amp Spherical Tokamak (MAST). We have obtained the first ever 2-D images of BXO mode conversion windows. With active probing, first ever turbulence velocity maps have been obtained. We present an overview of the diagnostic and discuss recent results. In contrast to quasi-optical microwave imaging systems SAMI requires neither big aperture viewing ports nor large 2-D detector arrays to achieve the desired imaging resolution. The number of effective 'pixels' of the synthesized image is proportional to the number of receiving antennas squared. Thus only a small number of optimised antennas is sufficient for the majority of applications. Possible implementation of SAMI on ITERand DEMO is discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Short-circuit current density imaging of crystalline silicon solar cells via lock-in thermography: Robustness and simplifications

Spatially resolved determination of solar cell parameters is beneficial for loss analysis and optimization of conversion efficiency. One key parameter that has been challenging to access by an imaging technique on solar cell level is short-circuit current density. This work discusses the robustness of a recently suggested approach to determine short-circuit current density spatially resolved based on a series of lock-in thermography images and options for a simplified image acquisition procedure. For an accurate result, one or two emissivity-corrected illuminated lock-in thermography images and one dark lock-in thermography image have to be recorded. The dark lock-in thermography image can be omitted if local shunts are negligible. Furthermore, it is shown that omitting the correction of lock-in thermography images for local emissivity variations only leads to minor distortions for standard silicon solar cells. Hence, adequate acquisition of one image only is sufficient to generate a meaningful map of short-circuit current density. Beyond that, this work illustrates the underlying physics of the recently proposed method and demonstrates its robustness concerning varying excitation conditions and locally increased series resistance. Experimentally gained short-circuit current density images are validated for monochromatic illumination in comparison to the reference method of light-beam induced current.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Three dimensional full-wave nonlinear acoustic simulations: Applications to ultrasound imaging

Characterization of acoustic waves that propagate nonlinearly in an inhomogeneous medium has significant applications to diagnostic and therapeutic ultrasound. The generation of an ultrasound image of human tissue is based on the complex physics of acoustic wave propagation: diffraction, reflection, scattering, frequency dependent attenuation, and nonlinearity. The nonlinearity of wave propagation is used to the advantage of diagnostic scanners that use the harmonic components of the ultrasonic signal to improve the resolution and penetration of clinical scanners. One approach to simulating ultrasound images is to make approximations that can reduce the physics to systems that have a low computational cost. Here a maximalist approach is taken and the full three dimensional wave physics is simulated with finite differences. This paper demonstrates how finite difference simulations for the nonlinear acoustic wave equation can be used to generate physically realistic two and three dimensional ultrasound images anywhere in the body. A specific intercostal liver imaging scenario for two cases: with the ribs in place, and with the ribs removed. This configuration provides an imaging scenario that cannot be performed in vivo but that can test the influence of the ribs on image quality. Several imaging properties are studied, in particular the beamplots, the spatial coherence at the transducer surface, the distributed phase aberration, and the lesion detectability for imaging at the fundamental and harmonic frequencies. The results indicate, counterintuitively, that at the fundamental frequency the beamplot improves due to the apodization effect of the ribs but at the same time there is more degradation from reverberation clutter. At the harmonic frequency there is significantly less improvement in the beamplot and also significantly less degradation from reverberation. It is shown that even though simulating the full propagation physics is computationally challenging it is necessary to quantify ultrasound image quality and its sources of degradation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Dual wavelength imaging of a scrape-off layer in an advanced beam-driven field-reversed configuration

A dual wavelength imaging system has been developed and installed on C-2U to capture 2D images of a He jet in the Scrape-Off Layer (SOL) of an advanced beam-driven Field-Reversed Configuration (FRC) plasma. The system was designed to optically split two identical images and pass them through 1 nm FWHM filters. Dual wavelength images are focused adjacent on a large format CCD chip and recorded simultaneously with a time resolution down to 10 μs using a gated micro-channel plate. The relatively compact optical system images a 10 cm plasma region with a spatial resolution of 0.2 cm and can be used in a harsh environment with high electro-magnetic noise and high magnetic field. The dual wavelength imaging system provides 2D images of either electron density or temperature by observing spectral line pairs emitted by He jet atoms in the SOL. A large field of view, combined with good space and time resolution of the imaging system, allows visualization of macro-flows in the SOL. First 2D images of the electron density and temperature observed in the SOL of the C-2U FRC are presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Reconstructing magnetic deflections from sets of proton images using differential evolution

Proton imaging is a powerful technique for imaging electromagnetic fields within an experimental volume, in which spatial variations in proton fluence are a result of deflections to proton trajectories due to interaction with the fields. When deflections are large, proton trajectories can overlap, and this nonlinearity creates regions of greatly increased proton fluence on the image, known as caustics. The formation of caustics has been a persistent barrier to reconstructing the underlying fields from proton images. We have developed a new method for reconstructing the path-integrated magnetic fields, which begins to address the problem posed by caustics. Our method uses multiple proton images of the same object, each image at a different energy, to fill in the information gaps and provide some uniqueness when reconstructing caustic features. We use a differential evolution algorithm to iteratively estimate the underlying deflection function, which accurately reproduces the observed proton fluence at multiple proton energies simultaneously. We test this reconstruction method using synthetic proton images generated for three different, cylindrically symmetric field geometries at various field amplitudes and levels of proton statistics and present reconstruction results from a set of experimental images. Here, the method we propose requires no assumption of deflection linearity and can reliably solve for fields underlying linear, nonlinear, and caustic proton image features for the selected geometries and is shown to be fairly robust to noise in the input proton intensity.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Fresnel diffraction imaging of surface nanostructure using coherent resonant x-ray scattering

We investigated surface nanostructures on an antiferromagnet MnBi 2 Te 4 using a novel imaging technique, direct (real)-space and real time coherent x-ray imaging (direct-CXI). This technique has provided new insights into antiferromagnetic textures, including the formation of anti-phase antiferromagnetic (AFM) domains and thermal dynamics of AFM domains and domain walls. While this method produces real-space images of AFM textures without requiring a complex imaging retrieval process, its underlying imaging mechanism has not been fully understood, limiting a deep understanding of AFM textures and the information they contain. By investigating the well-defined structural characteristics of the nanostructures fabricated on MnBi 2 Te 4 ⁠, we elucidate the imaging principle of this novel technique. We find that the observed images can be well explained by the Fresnel diffraction integral. Using a simple model from classical optics, our calculations successfully reproduce the experimentally observed images of the nanostructures. This demonstrates that direct-CXI not only provides straightforward real-space imaging but also contains phase information through its Fresnel diffraction integral.

36 MATERIALS SCIENCE↗
DOE OSTI2014

The Potential for Bayesian Compressive Sensing to Significantly Reduce Electron Dose in High Resolution STEM Images

The use of high resolution imaging methods in the scanning transmission electron microscope (STEM) is limited in many cases by the sensitivity of the sample to the beam and the onset of electron beam damage (for example in the study of organic systems, in tomography and during in-situ experiments). To demonstrate that alternative strategies for image acquisition can help alleviate this beam damage issue, here we apply compressive sensing via Bayesian dictionary learning to high resolution STEM images. These experiments successively reduce the number of pixels in the image (thereby reducing the overall dose while maintaining the high resolution information) and show promising results for reconstructing images from this reduced set of randomly collected measurements. We show that this approach is valid for both atomic resolution images and nanometer resolution studies, such as those that might be used in tomography datasets, by applying the method to images of strontium titanate and zeolites. As STEM images are acquired pixel by pixel while the beam is scanned over the surface of the sample, these post acquisition manipulations of the images can, in principle, be directly implemented as a low-dose acquisition method with no change in the electron optics or alignment of the microscope itself.

compressive sensing↗
DOE OSTI2018

Lens design challenges for scintillator-based neutron imaging

Neutron imaging is an important diagnostic to study inertial confinement fusion (ICF) implosions at the National Ignition Facility (NIF) using neutrons emitted in the fusion reactions. Analysis of time-gated images of the primary fusion (14.1 MeV) and down-scattered (6-12 MeV) neutrons based on their time-of-flight allows for the reconstruction of the burning hot spot undergoing fusion and the surrounding cold fuel. The Los Alamos National Laboratory (LANL) Advanced Imaging team has been providing these images since 2011. Currently, two additional lines of sight are being designed and built for NIF to allow three-dimensional reconstructions. Neutron imaging relies on the conversion of neutrons into light to be captured by an imaging system through the use of a scintillator. Although the current neutron imaging system utilizes a fiber scintillator array, a newly designed imaging system will consist of a thick monolithic scintillator and custom-designed lenses to collect the light. The custom lens has to resolve an image produced in the thick volume of the scintillator and therefore needs a large depth of field.

42 ENGINEERING↗
DOE OSTI2014

A statistical method for retrospective cardiac and respiratory motion gating of interventional cardiac x-ray images

Purpose: Image-guided cardiac interventions involve the use of fluoroscopic images to guide the insertion and movement of interventional devices. Cardiorespiratory gating can be useful for 3D reconstruction from multiple x-ray views and for reducing misalignments between 3D anatomical models overlaid onto fluoroscopy. Methods: The authors propose a novel and potentially clinically useful retrospective cardiorespiratory gating technique. The principal component analysis (PCA) statistical method is used in combination with other image processing operations to make our proposed masked-PCA technique suitable for cardiorespiratory gating. Unlike many previously proposed techniques, our technique is robust to varying image-content, thus it does not require specific catheters or any other optically opaque structures to be visible. Therefore, it works without any knowledge of catheter geometry. The authors demonstrate the application of our technique for the purposes of retrospective cardiorespiratory gating of normal and very low dose x-ray fluoroscopy images. Results: For normal dose x-ray images, the algorithm was validated using 28 clinical electrophysiology x-ray fluoroscopy sequences (2168 frames), from patients who underwent radiofrequency ablation (RFA) procedures for the treatment of atrial fibrillation and cardiac resynchronization therapy procedures for heart failure. The authors established end-systole, end-expiration, and end-inspiration success rates of 97.0%, 97.9%, and 97.0%, respectively. For very low dose applications, the technique was tested on ten x-ray sequences from the RFA procedures with added noise at signal to noise ratio (SNR) values of√(5)0, √(1)0, √(8), √(6), √(5), √(2), and √(1) to simulate the image quality of increasingly lower dose x-ray images. Even at the low SNR value of √(2), representing a dose reduction of more than 25 times, gating success rates of 89.1%, 88.8%, and 86.8% were established. Conclusions: The proposed technique can therefore extract useful information from interventional x-ray images while minimizing exposure to ionizing radiation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗