Dose management in CT is an increasingly important issue as the number of CT scans per capita continues to rise. One proposed approach for enhanced dose management is to allow the spatial pattern of x-ray fluence delivered to the patient to change dynamically as the x-ray tube rotates about the patient. The changes in incident fluence could be guided using a patient model and optimization method in order to deliver user-defined image quality criteria while minimizing dose. This approach is referred to as fluence field modulated CT (FFMCT). In this work, a framework and optimization method was developed for evaluating the dose and image quality benefits of FFMCT, both in simulated and experimental data. Modulated fluence profiles were optimized for different objects and image quality criteria using a simulated annealing algorithm. Analysis involved comparing predicted image quality maps and dose outcomes to those using conventional methods. Results indicated that image quality distributions using FFMCT agreed better with prescribed image qualities than conventional techniques allow. Dose reductions ranged depending on the task and object of interest. Simulation studies using a simulated anthropomorphic phantom of the chest suggest an average dose reduction of at least 20% compared to conventional techniques is possible, where local dose reductions may be greater than 60%. Across different imaging tasks and objects, integral dose reductions ranged from 20-50% when compared to a conventional bowtie filter. The results of this study suggest that given a suitable collimator approach, FFMCT could reap significant benefits in terms of reducing dose and optimizing image quality. Though the tradeoff between image quality and imaging dose may not be eliminated, it may be better managed using an FFMCT approach.

No description available.

Dose management in CT is an increasingly important issue as the number of CT scans per capita continues to rise. One proposed approach for enhanced dose management is to allow the spatial pattern of x-ray fluence delivered to the patient to change dynamically as the x-ray tube rotates about the patient. The changes in incident fluence could be guided using a patient model and optimization method in order to deliver user-defined image quality criteria while minimizing dose. This approach is referred to as fluence field modulated CT (FFMCT). In this work, a framework and optimization method was developed for evaluating the dose and image quality benefits of FFMCT, both in simulated and experimental data. Modulated fluence profiles were optimized for different objects and image quality criteria using a simulated annealing algorithm. Analysis involved comparing predicted image quality maps and dose outcomes to those using conventional methods. Results indicated that image quality distributions using FFMCT agreed better with prescribed image qualities than conventional techniques allow. Dose reductions ranged depending on the task and object of interest. Simulation studies using a simulated anthropomorphic phantom of the chest suggest an average dose reduction of at least 20% compared to conventional techniques is possible, where local dose reductions may be greater than 60%. Across different imaging tasks and objects, integral dose reductions ranged from 20-50% when compared to a conventional bowtie filter. The results of this study suggest that given a suitable collimator approach, FFMCT could reap significant benefits in terms of reducing dose and optimizing image quality. Though the tradeoff between image quality and imaging dose may not be eliminated, it may be better managed using an FFMCT approach.

This purpose of this work was to investigate the patient radiation doses and image quality of a Philips/Agfa computed radiographic (CR) system and a Philips indirect-capture digital radiographic (DR) system in a paediatric setting. A CDRAD digital radiographic contrast-detail phantom was used to assess radiographic image quality. Perspex slabs of three different thicknesses (6, 11 and 16 cm) were used to simulate paediatric patients of three arbitrary ages. These phantoms, in conjunction with the CDRAD digital radiographic contrast-detail phantom, were imaged under three different conditions. The CDRAD Analyser software package was used to assess the quality of each image. The first experiment conducted was a comparison of the two systems under standard conditions, with beam filtration of aluminium and copper, as recommended in European Guidelines on Quality Criteria for Diagnostic Radiographic Images in Paediatrics (European Commission 1996b). Image quality was compared for each phantom size at three doses with the same entrance exposure used for both systems. A visual comparison of the resulting contrast detail curves showed the DR system generally outperformed the CR system, especially at the lowest two doses. A chi-square analysis of the targets detected generally confirmed this visual impression. The second experiment performed was to compare the two systems under the conditions used in routine clinical practice at PMH. As a result of additional beam filtration not generally being employed, the image quality of the CR system was similar to the DR system for the two smaller phantom sizes but with a major dose cost - effective doses higher by between 38% and 100%. A chi-square analysis of the targets detected showed the CR system to be significantly better than the DR system at two of three doses for the thinnest phantom and no significant difference at any doses for the intermediate phantom size. For the largest phantom size, additional filtration - although different - was used for the CR and DR systems and so the X-ray beam spectra were more similar. Consequently, the results for this phantom size reflected those from the experiment conducted under standard conditions, ie the effective doses for both systems were similar and the image quality of the DR system superior. The chi-square analysis s howed the DR system to be significantly better than the CR at all three dose levels. A third experiment was undertaken to compare doses between the two systems at 'equal' image quality. The CDRAD Analyser software specific image quality parameter, IQFinv, was held constant for both systems. The entrance exposures required to achieve this image quality were measured and then converted to effective doses using the dose calculation software package PCXMC 1.5. The DR system offered effective dose savings of between 28 and 42% for the three phantom sizes. Overall, this work suggests that a Philips flat-panel system is superior to an Agfa CR system in paediatric radiography. This result generally reflects the findings of other authors who have conducted similar studies in adult patient settings.

Diss. (sammanfattning) Linköping : Univ., 2001. / Härtill 5 uppsatser.

abstract: Computed tomography (CT) is one of the essential imaging modalities for medical diagnosis. Since its introduction in 1972, CT technology has been improved dramatically, especially in terms of its acquisition speed. However, the main principle of CT which consists in acquiring only density information has not changed at all until recently. Different materials may have the same CT number, which may lead to uncertainty or misdiagnosis. Dual-energy CT (DECT) was reintroduced recently to solve this problem by using the additional spectral information of X-ray attenuation and aims for accurate density measurement and material differentiation. However, the spectral information lies in the difference between two low and high energy images or measurements, so that it is difficult to acquire the accurate spectral information due to amplification of high pixel noise in the resulting difference image. In this work, a new model and an image enhancement technique for DECT are proposed, based on the fact that the attenuation of a high density material decreases more rapidly as X-ray energy increases. This fact has been previously ignored in most of DECT image enhancement techniques. The proposed technique consists of offset correction, spectral error correction, and adaptive noise suppression. It reduced noise, improved contrast effectively and showed better material differentiation in real patient images as well as phantom studies. / Dissertation/Thesis / Ph.D. Bioengineering 2011

No description available.

In X-ray computed tomography, motion of the object (breathing, for example) while X-ray projections are acquired for tomographic reconstruction leads to mo- tion artifacts in the reconstructed image. Object motion (such as that of breathing lungs) during acquisition of a computed tomography scan causes artifacts in the reconstructed image due to the reason that the source and detectors require a finite amount of time to rotate around the object while acquiring measurements even as the object is changing with time. With traditional reconstruction algorithms, the object is assumed to be stationary while data is acquired. However, in the case of dynamic tomography, the projection data that is acquired is not consistent, as it is data measured from an object that is deformed at each view angle of measurement. In this work, we propose a method for estimation of general (non-rigid) small motion for dynamic tomography from motion-corrupted projection data. For a static object, the Helgason-Ludwig consistency conditions impose some structure on the moments of the projections. However in the case of dynamic object (result- ing in motion-corrupted projections) this is violated. In the proposed method, we estimate motion parameters of the general motion model from the moments of the dynamic projections. The dynamic object can be modeled as f (g(x, t)) where g is a time-dependent warping function. The non-linear problem of solving a system involving composition of functions is dealt with in the Fourier transform space where it simplifies into a problem involving multiplicatively separable functions. The system is then linearized to solve for object motion. We assume a general basis function in our model. For numerical simulations, we use polynomial and B-spline basis functions as special cases of the basis functions. Simulation is performed by applying known deformations to the Shepp-Logan phantom, to a head slice of the Visible Human phantom and a thorax slice of the Zubal phantom. Simulations are performed for projections generated by parallel- beam and fan-beam geometry. Simulation for fan-beam geometry are performed by rebinning the motion corrupted fan beam projections to parallel beam projections, followed by the proposed motion estimation method. Simulation for the Visible Human phantom and the thorax slice of the Zubal phantom are performed for fan- beam geometry. Poisson noise is also added to the generated dynamic projections before motion estimation is performed. To solve the ill-posed problem of motion estimation by the proposed method, we use a Tikhonov type regularization that involves minimizing an objective function that is the sum of a data discrepancy term, a term that penalizes temporal variation of motion, and another term to penalize large magnitudes of motion. Using the estimated motion, the original image has been reconstructed from the motion corrupted projection data, with the knowledge of the underlying motion which is estimated by the proposed algorithm, by an algebraic technique similar to the dynamic SART algorithm from the literature. Here, a SART-type coefficient matrix is computed using ray tracing with rays whose paths are warped according to the estimated motion. The dynamic image at t = 0 is then reconstructed with using the computed dynamic SART matrix.

The use of computed tomography in patients with gastrointestinal disease is increasing. However, the triple-phase computed tomographic angiographic appearance of the canine small intestine and the effects that phase of contrast enhancement and plane of reconstruction have on the appearance of the small intestine have not been fully evaluated. The purposes of this study were to investigate these effects on the appearance of the small intestinal wall. The minimal and maximal small intestinal diameter, wall thickness, number of wall layers identified, and degree of mucosal enhancement were recorded. The plane of reconstruction did not have any significant effects on wall thickness, diameter, degree of mucosal enhancement, or number of wall layers identified. There was a positive association between body weight and intestinal diameter. The arterial phase demonstrated the greatest mucosal enhancement and number of wall layers identified. The transverse plane was subjectively the most useful for evaluation of the small intestines.

Purpose: Patient centred care and the ‘patient voice’ are core components of UK healthcare policy and practice guidance. This study explores how care is perceived and experienced within the high technology environment of CT. Methods and Materials: A two-phase approach of Critical Discourse Analysis (CDA) and adapted Grounded Theory (GT) methodology using semi structured interviews, was used to obtain primary data from CT radiographers and patients. Recruitment and data collection were performed at a 1200 bed teaching hospital over a 6-month period. Results: The radiographer patient relationship and the radiographer’s role in providing care within CT are complex and multifaceted. Both patients and radiographer’s perceive CT imaging to be an integral part of the overall patient care and treatment pathway. As such, the act of being imaged is perceived as a care process and while image acquisition is recognised as a task orientated and technical process, the human element of providing care is cognitive, dynamic and responsive to individual need. Importantly, patient confidence in the care received was influenced by the radiographer’s ability to build a trusting relationship and display technical competence and this in turn facilitated active compliance resulting in a technically accurate examination. Despite previous literature suggesting that the technical environment created a barrier to patient care, patients within this study confirmed that radiographers provide care commensurate to the nursing ideals represented by the 6C’s (Care; Compassion; Competence; Communication; Courage; Commitment). Conclusions: A co-constructed model of care encompassing both technical components and patient-centeredness has been identified. This model promotes a new vision of patient centred care based on care perceptions within the high technology environment of CT.