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Biomedical subjects

K W Leszczynski

Publications and source records attributed to K W Leszczynski.

13 recordsLinked to original sources
PubMed2001

Application of anisotropic diffusion to digital enhancement of portal images.

We propose the use of anisotropic diffusion filtering to remedy difficulties in analysis of electronic portal images, stemming from their low contrast and high noise levels. Anisotropic diffusion is a nonlinear filter based on the numerical solution to the partial differential equation describing the process of diffusion. In this study we show that this filter is capable of greatly reducing noise in homogeneous areas of portal images while preserving the edges and contrast associated with anatomical features. We also demonstrate that the application of anisotropic diffusion leads to more consistent and reproducible visual extraction of features from portal images.

Anisotropy↗
PubMed2001

On few-view tomographic reconstruction with megavoltage photon beams.

Currently portal imaging devices are used to obtain information on patient localization during radiation therapy treatments. Such obtained information is two dimensional in nature, limited to the plane of the captured image. It has been proposed that megavoltage computed tomography images be reconstructed to overcome this limitation. This study explores the feasibility of reconstructing tomographic images from fan-beam projection data acquired with a commercial portal imaging device on a standard radiotherapy linear accelerator. Several CT reconstruction algorithms are examined as to their performance and suitability for applications in radiation therapy verification. The results show that it is possible, using some of the iterative reconstruction techniques, to obtain an image useful for patient localization from only several (< or =10) projection views.

Algorithms↗
PubMed2000

Independent corroboration of monitor unit calculations performed by a 3D computerized planning system.

The checking of monitor unit calculations is recognized as a vital component of quality assurance in radiotherapy. Using straightforward but detailed computer-based verification calculations it is possible to achieve a precision of 1% when compared with a three-dimensional (3D) treatment planning system monitor unit calculation. The method is sufficiently sensitive to identify significant errors and is consistent with current recommendations on the magnitude of uncertainties in clinical dosimetry. Moreover, the approach is accurate in the sense of being highly consistent with the validated 3D treatment planning system's calculations.

Humans↗
PubMed1998

Computer-aided radiation therapy simulation: image intensifier spatial distortion correction for large field of view digital fluoroscopy.

An accurate method of correcting spatial distortion in digital fluoroscopy images has been developed for generating fluoroscopy-based large field of view images for computer-aided radiation therapy simulation. This method is applicable to arbitrary gantry rotations and arbitrary shifts of the image intensifier relative to the central axis of the x-ray beam. It is therefore suitable for conventional radiation therapy simulation techniques that involve the arbitrary positioning of the image intensifier by the operator. Spatial distortion is modelled as two image intensifier orientation-dependent components, the first resulting from the projection of the x-ray image onto the curved surface of the image intensifier front end, and the second produced by the image intensifier electron optics, interactions with external magnetic fields and the video system. A geometrical model approximates the first component. The second component is modelled by a third-order polynomial transformation. A weighted mean approach is employed to achieve accurate distortion correction when the image intensifier is oriented differently from the calibration orientations. Mean and maximum residual errors (measured in the plane of the isocentre) of 0.4 mm and 1.0 mm respectively have been achieved with just 48 calibration orientations in four dimensions (gantry rotation and lateral, longitudinal and vertical shifts of the image intensifier).

Calibration↗
PubMed1998

An image registration scheme applied to verification of radiation therapy.

The introduction of modern conformal radiation therapy techniques requires high geometric precision in treatment delivery which must be verified. For that purpose we have developed an automated system based on registration of portal and simulation (or planning) image pairs. The image registration is performed on anatomical features which are automatically extracted from the portal image. The portal image is then registered with a planning or simulation radiographic image which represents the geometric prescription for the treatment, using an optimized version of the chamfer matching algorithm. Subsequently, the magnitude of the radiation field displacement during treatment is measured by registering the prescribed and treated field boundaries. Algorithms based on chamfer matching and polygon matching have been used for the field boundary registration. Performance of the entire scheme was evaluated on a series of 15 portal images of a pelvic phantom representing various known degrees of the radiation field displacement. The measurements of the radiation field displacements performed by the automated system proved very reliable and after correction for systematic bias agreed to within 1.5 mm or 1 degree with the displacements applied. Second test series involved comparisons between the automated registrations and those performed manually/visually by an experienced human observer, on 31 portal images acquired during treatments of 18 pelvic patients. These tests showed close agreement (in 80% of cases discrepancies were smaller than 1.5 mm or 1.5 degrees) between the automated scheme and the human observer. It is concluded that the developed scheme would be suitable for online geometric verification of radiation therapy treatments.

Algorithms↗
PubMed1994

Optimization of metal/phosphor screens for on-line portal imaging.

Studies were conducted to determine the optimal metal/phosphor screen for on-line video verification of radiation treatment portals. Screens were evaluated for luminance and spatial resolution as a function of composition and thickness at 6- and 23-MV x-ray energies. A new video technique was used to determine modulation transfer functions. Gd2O2S was found to be the most efficient (brightest) phosphor for this application. Luminance was found to vary linearly with phosphor thickness up to a thickness of 500 mg/cm2. Metal plates made of iron, brass, copper, lead, and sintered tungsten of various thicknesses were also tested for luminance and resolution with Gd2O2S phosphor. Brightness peaked at about 2-mm thickness for most metals. Significant contributions to the brightness were found to come from x rays interacting with the phosphor itself.

Evaluation Studies as Topic↗
PubMed1990

An adaptive technique for digital noise suppression in on-line portal imaging.

Two complementary approaches to the noise suppression problem in on-line portal imaging have been analysed. Temporal filtering by image summation can substantially reduce the amount of noise in an image. In many cases, however, movements of the patient or the radiation source limit the time period over which the averaging can be done. Any remaining noise has to be dealt with by applying spatial filtering. The adaptive Lee filter is particularly suitable for portal imaging applications. It preserves a crisp definition of edges while removing noise in flat regions of the image. It can be used to obtain images of satisfactory quality with short radiation exposure of the patient. We have proposed a modification to the basic Lee technique which permits the calculation of the noise variance locally by utilising the information contained in intermediate images acquired during frame averaging. Unlike the original Lee formulation, no a priori knowledge of the noise variance is required, and in contrast to Mastin's approach (Mastin 1985), the variance may vary with position in the image. The tests of performance of the modified Lee filter, carried out using on-line images, have shown its superiority in comparison with the original Lee technique as well as with conventional averaging and median filters.

Filtration↗
PubMed1989

Digital contrast enhancement for online portal imaging.

Seven digital contrast enhancement algorithms were implemented and evaluated for application to images obtained with an online video portal imaging system. An objective quantitative comparison shows that superior contrast enhancement is obtained using histogram modification techniques. Additional tests made on an image of a humanoid phantom indicate that local (adaptive) histogram modification methods can produce a better contrast in detail than their global counterparts, if the original image is nonuniform in intensity.

Algorithms↗
PubMed1987

On the dimension of the cortical EEG.

A correlation dimension was estimated for the EEG recorded from the rabbit's thalamus. The calculations carried out with use of two different algorithms led to equivocal results. The dominant, deterministic nature of the EEG was ascertained.

Algorithms↗
PubMedDate not supplied

A study on the efficacy of digital enhancement of on-line portal images.

A novel method for evaluation of observer performance with portal images has been developed, in which the observer is required to identify and localize predefined anatomical landmarks in digital portal images. The method was employed to compare the spatial accuracy and decision time for landmark localization in unenhanced on-line portal images and images enhanced digitally by selective adaptive histogram modification. The results indicate that anatomical landmarks were more readily identified in the enhanced images, leading to significantly higher accuracy in landmark localization.

Evaluation Studies as Topic↗
PubMedDate not supplied

The enhancement of radiotherapy verification images by an automated edge detection technique.

Adaptive histogram equalization techniques are known to be effective for the enhancement of contrast in portal images acquired during radiotherapy treatments. A significant drawback is the loss of definition on the edges of the treatment field. Analysis of this problem shows that it can be remedied by separating the treatment field from the background prior to the enhancement, and using only the pixels within the field boundary in the enhancement procedure. An edge extraction algorithm has been developed for delineating the treatment field in portal images, and consists of four modules that are applied to the original portal image in sequence. In the first step, edges are enhanced with a derivative of Gaussian operator that assures high response to the field edges relative to anatomical or other edges in the image. Pixels for which the response of the edge operator was the strongest are subsequently connected by an edge following algorithm to produce a raw contour of the field. In the last two steps the contour is refined by converting it into straight line segments and appending to the contour any parts of the field edge that might have been missed out during the initial edge following. The final contour encloses exclusively those pixels that belong to the treatment field, and the adaptive histogram equalization is applied selectively to this region. The combination of edge detection and selective enhancement was shown to produce images of superior contrast on the patient's anatomical features as well as accurate definition of treatment field edges.

Algorithms↗
PubMedDate not supplied

Verification of radiotherapy treatments: computerized analysis of the size and shape of radiation fields.

An automated technique has been developed for the verification of treatment field size and shape in external beam radiation therapy. Portal images from film or digital on-line imaging system are analyzed, and basic parameters are derived to describe the field size and shape from the contour points on the field boundary. The initial set of parameters included length of the perimeter, area, aspect ratio, and orientation angle. The parameters found for the actual field in the portal image are compared against those calculated for the prescribed field and any discrepancies indicated to the operator. The accuracy of the field parameterization scheme has been tested on a number of on-line portal images with varying fields. The relative error did not exceed a few percent in perimeter and area or 2 degrees in the angle, which should be sufficiently low for the detection of major errors in field shaping.

Computer Simulation↗