Edge enhancement

About: Edge enhancement is a research topic. Over the lifetime, 2324 publications have been published within this topic receiving 30962 citations.

Synchronized multiartifact reduction with tomographic reconstruction (SMART-RECON): A statistical model based iterative image reconstruction method to eliminate limited-view artifacts and to mitigate the temporal-average artifacts in time-resolved CT.

Abstract: Purpose: In x-ray computed tomography (CT), a violation of the Tuy data sufficiency condition leads to limited-view artifacts. In some applications, it is desirable to use data corresponding to a narrow temporal window to reconstruct images with reduced temporal-average artifacts. However, the need to reduce temporal-average artifacts in practice may result in a violation of the Tuy condition and thus undesirable limited-view artifacts. In this paper, the authors present a new iterative reconstruction method, synchronized multiartifact reduction with tomographic reconstruction (SMART-RECON), to eliminate limited-view artifacts using data acquired within an ultranarrow temporal window that severely violates the Tuy condition. Methods: In time-resolved contrast enhanced CT acquisitions, image contrast dynamically changes during data acquisition. Each image reconstructed from data acquired in a given temporal window represents one time frame and can be denoted as an image vector. Conventionally, each individual time frame is reconstructed independently. In this paper, all image frames are grouped into a spatial–temporal image matrix and are reconstructed together. Rather than the spatial and/or temporal smoothing regularizers commonly used in iterative image reconstruction, the nuclear norm of the spatial–temporal image matrix is used in SMART-RECON to regularize the reconstruction of all image time frames. This regularizer exploits the low-dimensional structure of the spatial–temporal image matrix to mitigate limited-view artifacts when an ultranarrow temporal window is desired in some applications to reduce temporal-average artifacts. Both numerical simulations in two dimensional image slices with known ground truth and in vivo human subject data acquired in a contrast enhanced cone beam CT exam have been used to validate the proposed SMART-RECON algorithm and to demonstrate the initial performance of the algorithm. Reconstruction errors and temporal fidelity of the reconstructed images were quantified using the relative root mean square error (rRMSE) and the universal quality index (UQI) in numerical simulations. The performance of the SMART-RECON algorithm was compared with that of the prior image constrained compressed sensing (PICCS) reconstruction quantitatively in simulations and qualitatively in human subject exam. Results: In numerical simulations, the 240∘ short scan angular span was divided into four consecutive 60∘ angular subsectors. SMART-RECON enables four high temporal fidelity images without limited-view artifacts. The average rRMSE is 16% and UQIs are 0.96 and 0.95 for the two local regions of interest, respectively. In contrast, the corresponding average rRMSE and UQIs are 25%, 0.78, and 0.81, respectively, for the PICCS reconstruction. Note that only one filtered backprojection image can be reconstructed from the same data set with an average rRMSE and UQIs are 45%, 0.71, and 0.79, respectively, to benchmark reconstruction accuracies. For in vivo contrast enhanced cone beam CT data acquired from a short scan angular span of 200∘, three 66∘ angular subsectors were used in SMART-RECON. The results demonstrated clear contrast difference in three SMART-RECON reconstructed image volumes without limited-view artifacts. In contrast, for the same angular sectors, PICCS cannot reconstruct images without limited-view artifacts and with clear contrast difference in three reconstructed image volumes. Conclusions: In time-resolved CT, the proposed SMART-RECON method provides a new method to eliminate limited-view artifacts using data acquired in an ultranarrow temporal window, which corresponds to approximately 60∘ angular subsectors.

Quantification of the effect of system and object parameters on edge enhancement in phase-contrast radiography.

Abstract: The purpose of this study was to evaluate the effects of system parameters (focal spot size, tube voltage, geometry, detector resolution, and imagenoise) and object characteristics (edge gradient/shape, composition, thickness, and overlying attenuating material) upon the edge enhancement effect in phase-contrast radiography. Each variable of interest was adjusted and images of a 3 mm lucite phantom were obtained with the other variables remaining constant. A microfocus x-ray source coupled to a CCD camera with an intensifying screen was used to acquire the digital images. Two parameters of image analysis were used to quantify the effects. The edge enhancement index (EEI) was used to measure the absolute degree of edge enhancement, while the edge enhancement to noise ratio (EE/N) was used to measure the conspicuity of the edge enhancement relative to imagenoise. Little effect on EEI was seen from tube voltage, object thickness, overlying attenuating material, while focal spot size and system geometry demonstrated measurable effects upon the degree of edge enhancement. It was also shown that while the edge enhancement effect over straight edges is highly dependent upon how the edge aligns with the x-ray beam, rounded edges, which better model biological objects, do not suffer from this dependence and the EEI reaches its maximal level at any alignment. Decreasing detector resolution diminished the EEI slightly, but even with pixel sizes of 0.360×0.360 mm edge enhancement effects were readily visible. The effect of imagenoise on EE/N was evaluated using different exposure times showing an expected improvement with longer exposure time with EE/N approaching a plateau at 5 min. Many of the parameters that will go into the design of a future PC-R imagingsystem have been quantified in terms of their effect on the degree of edge enhancement in the acquired image. These results, taken together, indicate that either a specimen or even clinical breast imagingsystem could be created with currently available technology. The major limitation to a clinical system would be the low x-ray flux from the microfocal x-ray source.

Edge enhancement of potential field data using the logistic function and the total horizontal gradient

Abstract: Locating the edges of anomalous bodies provides a fundamental tool in the geologic interpretation of potential field data. This paper compares the effectiveness of the commonly used edge detection methods such as the total horizontal gradient, analytic signal, tilt angle, theta map and their modified versions in terms of their accuracy on the determination of edges of source bodies. This paper also introduces an edge detector method for the enhancement of potential field anomalies, which is based on the logistic function of the total horizontal gradient. The new method is tested on synthetic data calculated using 3 models, and also on real magnetic and gravity data from Vietnam. The effectiveness of the method is evaluated by comparing the results with those of other popular methods. These results demonstrate that the method is a useful tool for the qualitative interpretation of potential field data.