Análisis del Filtro FPGA en Imágenes de Tomografía Computarizada para la Reducción de Dosis Radiactiva

[EN] X-Ray or CT (computed tomography) images may have noise due to image acquisition process. As contaminated images complicate diagnosis many filters have been developed to overcome this problem. In this work we study the behavior of a Fuzzy method called FPGA, which detect and correct impulsive and Gaussian noise, used over a medical image obtained from the mini-MIAS database that has been altered with impulsive and/or Gaussian noise. The aim of the study is verify if FPGA is a candidate to be used as a method to reduce the radiation dose in CT. Results show that FPGA outperforms the rest of the methods studied and it reveals itself as a good candidate to be employed in CT images to reduce the radiation dose.[ES] Las imágenes de Rayos-X o de tomografía computarizada (CT) pueden contener ruido debido al proceso de adquisición. Este ruido complica sustancialmente el proceso diagnóstico, por lo que será necesario el desarrollo de filtros efectivos. En este trabajo se estudia el comportamiento del filtro Fuzzy Peer Group Averaging (FPGA) sobre una colección de imágenes mamográficas que ha sido previamente contaminada con ruido impulsivo y gaussiano. El objetivo del trabajo es averiguar si FPGA es adecuado para la mejora de imágenes CT obtenidas con una dosis de radiación reducida. Los resultados indican que FPGA se comporta, efectivamente, mejor que el resto de métodos estudiados en este trabajo y por tanto resulta un candidato adecuado.This work was partially funded by ANITRAN PROMETEO/2010/039, the Spanish Ministry of Science and Innovation (Project TIN2008-06570-C04-04), and the spin-off Titania (Grupo Dominguis).Parcero Iglesias, E.; Vidal Gimeno, VE.; Verdú Martín, GJ.; Josep Arnal García; Mayo Nogueira, P. (2014). Análisis del Filtro FPGA en Imágenes de Tomografía Computarizada para la Reducción de Dosis Radiactiva. Sociedad Nuclear Española. http://hdl.handle.net/10251/70824

Focal Spot, Fall/Winter 1997

https://digitalcommons.wustl.edu/focal_spot_archives/1077/thumbnail.jp

Analysis of FPGA filter in computed tomography images for radioactive dose reduction

[EN] X-Ray or CT (computed tomography) images may have noise due to image acquisition process. As contaminated images complicate diagnosis many filters have been developed to overcome this problem. In this work we study the behavior of a Fuzzy method called FPGA, which detect and correct impulsive and Gaussian noise, used over a medical image obtained from the mini-MIAS database that has been altered with impulsive and/or Gaussian noise. The aim of the study is verify if FPGA is a candidate to be used as a method to reduce the radiation dose in CT. Results show that FPGA outperforms the rest of the methods studied and it reveals itself as a good candidate to be employed in CT images to reduce the radiation dose.[ES] Las imágenes de Rayos-X o de tomografía computarizada (CT) pueden contener ruido debido al proceso de adquisición. Este ruido complica sustancialmente el proceso diagnóstico, por lo que será necesario el desarrollo de filtros efectivos. En este trabajo se estudia el comportamiento del filtro Fuzzy Peer Group Averaging (Fuzzy PGA) sobre una colección de imágenes mamográficas que ha sido previamente contaminada con ruido impulsivo y gaussiano. El objetivo del trabajo es averiguar si Fuzzy PGA es adecuado para la mejora de imágenes CT obtenidas con una dosis de radiación reducida. Los resultados indican que Fuzzy PGA se comporta, efectivamente, mejor que el resto de métodos estudiados en este trabajo y por tanto resulta un candidato adecuado.Parcero Iglesias, E.; Vidal Gimeno, VE.; Verdú Martín, GJ.; Arnal García, J. (2014). Analysis of FPGA filter in computed tomography images for radioactive dose reduction. Grupo Senda. http://hdl.handle.net/10251/49701

Hand X-ray absorptiometry for measurement of bone mineral density on a slot-scanning X-ray imaging system

Includes bibliographical references.Bone mineral density (BMD) is an indicator of bone strength. While femoral and spinal BMDs are traditionally used in the management of osteoporosis, BMD at peripheral sites such as the hand has been shown to be useful in evaluating fracture risk for axial sites. These peripheral locations have been suggested as alternatives to the traditional sites for BMD measurement. Dual-energy X-ray absorptiometry (DXA) is the gold standard for measuring BMD due to low radiation dose, high accuracy and proven ability to evaluate fracture risk. Computed digital absorptiometry (CDA) has also been shown to be very effective at measuring the bone mass in hand bones using an aluminium step wedge as a calibration reference. In this project, the aim was to develop algorithm s for accurate measurement of BMD in hand bones on a slot - scanning digital radiography system. The project assess e d the feasibility of measuring bone mineral mass in hand bones using CDA on the current system. Images for CDA - based measurement were acquired using the default settings on the system for a medium sized patient. A method for automatic processing of the hand images to detect the aluminium step wedge, included in the scan for calibration, was developed and the calibration accuracy of the step wedge was evaluated. The CDA method was used for computation of bone mass with units of equivalent aluminium thickness (mmA1). The precision of the method was determined by taking three measurements in each of 1 6 volunteering subjects and computing the root - mean - square coefficient of variation (CV) of the measurements. The utility of the method was assessed by taking measurements of excised bones and assessing the correlation between the measured bone mass and ash weight obtained by incinerating the bones. The project also assessed the feasibility of implementing a DXA technique using two detectors in a slot-scanning digital radiography system to acquire dual-energy X-ray images for measuring areal and volumetric BMD of the middle phalanx of the middle finger. The dual-energy images were captured in two consecutive scans. The first scan captured the low- energy image using the detector in its normal set-up. The second scan captured the high- energy image with the detector modified to include an additional scintillator to simulate the presence of a second detector that would capture the low-energy image in a two-detector system. Scan parameters for acquisition of the dual-energy images were chosen to optimise spectral separation, entrance dose and image quality. Simulations were carried out to evaluate the spectral separation of the low- and high-energy spectra

Virtual clinical trials in medical imaging: a review

The accelerating complexity and variety of medical imaging devices and methods have outpaced the ability to evaluate and optimize their design and clinical use. This is a significant and increasing challenge for both scientific investigations and clinical applications. Evaluations would ideally be done using clinical imaging trials. These experiments, however, are often not practical due to ethical limitations, expense, time requirements, or lack of ground truth. Virtual clinical trials (VCTs) (also known as in silico imaging trials or virtual imaging trials) offer an alternative means to efficiently evaluate medical imaging technologies virtually. They do so by simulating the patients, imaging systems, and interpreters. The field of VCTs has been constantly advanced over the past decades in multiple areas. We summarize the major developments and current status of the field of VCTs in medical imaging. We review the core components of a VCT: computational phantoms, simulators of different imaging modalities, and interpretation models. We also highlight some of the applications of VCTs across various imaging modalities

Quantitative Evaluation of Pulmonary Emphysema Using Magnetic Resonance Imaging and x-ray Computed Tomography

Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality affecting at least 600 million people worldwide. The most widely used clinical measurements of lung function such as spirometry and plethysmography are generally accepted for diagnosis and monitoring of the disease. However, these tests provide only global measures of lung function and they are insensitive to early disease changes. Imaging tools that are currently available have the potential to provide regional information about lung structure and function but at present are mainly used for qualitative assessment of disease and disease progression. In this thesis, we focused on the application of quantitative measurements of lung structure derived from 1H magnetic resonance imaging (MRI) and high resolution computed tomography (CT) in subjects diagnosed with COPD by a physician. Our results showed that significant and moderately strong relationship exists between 1H signal intensity (SI) and 3He apparent diffusion coefficient (ADC), as well as between 1H SI and CT measurements of emphysema. This suggests that these imaging methods may be quantifying the same tissue changes in COPD, and that pulmonary 1H SI may be used effectively to monitor emphysema as a complement to CT and noble gas MRI. Additionally, our results showed that objective multi-threshold analysis of CT images for emphysema scoring that takes into account the frequency distribution of each Hounsfield unit (HU) threshold was effective in correctly classifying the patient into COPD and healthy subgroups. Finally, we found a significant correlation between whole lung average subjective and objective emphysema scores with high inter-observer agreement. It is concluded that 1H MRI and high resolution CT can be used to quantitatively evaluate lung tissue alterations in COPD subjects

Correlated Polarity Noise Reduction: Development, Analysis, and Application of a Novel Noise Reduction Paradigm

<p>Image noise is a pervasive problem in medical imaging. It is a property endemic to all imaging modalities and one especially familiar in those modalities that employ ionizing radiation. Statistical uncertainty is a major limiting factor in the reduction of ionizing radiation dose; patient exposure must be minimized but high image quality must also be achieved to retain the clinical utility of medical images. One way to achieve the goal of radiation dose reduction is through the use of image post processing with noise reduction algorithms. By acquiring images at lower than normal exposure followed by algorithmic noise reduction, it is possible to restore image noise to near normal levels. However, many denoising algorithms degrade the integrity of other image quality components in the process. </p><p>In this dissertation, a new noise reduction algorithm is investigated: Correlated Polarity Noise Reduction (CPNR). CPNR is a novel noise reduction technique that uses a statistical approach to reduce noise variance while maintaining excellent resolution and a "normal" noise appearance. In this work, the algorithm is developed in detail with the introduction of several methods for improving polarity estimation accuracy and maintaining the normality of the residual noise intensity distribution. Several image quality characteristics are assessed in the production of this new algorithm including its effects on residual noise texture, residual noise magnitude distribution, resolution effects, and nonlinear distortion effects. An in-depth review of current linear methods for medical imaging system resolution analysis will be presented along with several newly discovered improvements to existing techniques. This is followed by the presentation of a new paradigm for quantifying the frequency response and distortion properties of nonlinear algorithms. Finally, the new CPNR algorithm is applied to computed tomography (CT) to assess its efficacy as a dose reduction tool in 3-D imaging.</p><p>It was found that the CPNR algorithm can be used to reduce x ray dose in projection radiography by a factor of at least two without objectionable degradation of image resolution. This is comparable to other nonlinear image denoising algorithms such as the bilateral filter and wavelet denoising. However, CPNR can accomplish this level of dose reduction with few edge effects and negligible nonlinear distortion of the anatomical signal as evidenced by the newly developed nonlinear assessment paradigm. In application to multi-detector CT, XCAT simulations showed that CPNR can be used to reduce noise variance by 40% with minimal blurring of anatomical structures under a filtered back-projection reconstruction paradigm. When an apodization filter was applied, only 33% noise variance reduction was achieved, but the edge-saving qualities were largely retained. In application to cone-beam CT for daily patient positioning in radiation therapy, up to 49% noise variance reduction was achieved with as little as 1% reduction in the task transfer function measured from reconstructed data at the cutoff frequency. </p><p>This work concludes that the CPNR paradigm shows promise as a viable noise reduction tool which can be used to maintain current standards of clinical image quality at almost half of normal radiation exposure This algorithm has favorable resolution and nonlinear distortion properties as measured using a newly developed set of metrics for nonlinear algorithm resolution and distortion assessment. Simulation studies and the initial application of CPNR to cone-beam CT data reveal that CPNR may be used to reduce CT dose by 40%-49% with minimal degradation of image resolution.</p>Dissertatio