Til Aach

Anisotropic spectral magnitude estimation filters for noise reduction and image enhancement

Describes an algorithm for noise reduction and enhancement of images which is able to take into account anisotropies of signal as well as of noise. Processing is based on subjecting each image to a block DFT, followed by comparing each observed magnitude coefficient to the expected noise standard deviation for it. Depending on this comparison, each coefficient is attenuated the more, the more likely it is that it contains only noise. In addition, the attenuation is made dependent on whether or not the observed coefficient contributes to an oriented prominent structure within the processed image block. Orientation as well as the distinctness with which it occurs are detected in the spectral domain by an inertia-like matrix. Orientation information is additionally exploited to selectively enhance oriented structures, thus only marginally increasing noise as compared to isotropic enhancement.

Digital image acquisition and processing in medical x-ray imaging

This contribution discusses a selection of today’s techniques and future concepts for digital x-ray imaging in medicine. Advantages of digital imaging over conventional analog methods include the possibility to archive and transmit images in digital information systems as well as to digitally process pictures before display, for example, to enhance low contrast details. After reviewing two digital x-ray radiography systems for the capture of still x-ray images, we examine the real time acquisition of dynamic x-ray images (x-ray fluoroscopy). Here, particular attention is paid to the implications of introducing charge-coupled device cameras. We then present a new unified radiography/fluoroscopy solid-state detector concept. As digital image quality is predominantly determined by the relation of signal and noise, aspects of signal transfer, noise, and noise-related quality measures like detective quantum efficiency feature prominently in our discussions. Finally, we describe a digital image processing algorithm for the reduction of noise in images acquired with low x-ray dose.

Performance of standard fluoroscopy antiscatter grids in flat-detector-based cone-beam CT

In this paper, the performance of focused lamellar anti-scatter grids, which are currently used in fluoroscopy, is studied in order to determine guidelines of grid usage for flat detector based cone beam CT. The investigation aims at obtaining the signal to noise ratio improvement factor by the use of anti-scatter grids. First, the results of detailed Monte Carlo simulations as well as measurements are presented. From these the general characteristics of the impinging field of scattered and primary photons are derived. Phantoms modeling the head, thorax and pelvis regions have been studied for various imaging geometries with varying phantom size, cone and fan angles and patient-detector distances. Second, simulation results are shown for ideally focused and vacuum spaced grids as best case approach as well as for grids with realistic spacing materials. The grid performance is evaluated by means of the primary and scatter transmission and the signal to noise ratio improvement factor as function of imaging geometry and grid parameters. For a typical flat detector cone beam CT setup, the grid selectivity and thus the performance of anti-scatter grids is much lower compared to setups where the grid is located directly behind the irradiated object. While for small object-to-grid distances a standard grid improves the SNR, the SNR for geometries as used in flat detector based cone beam CT is deteriorated by the use of an anti-scatter grid for many application scenarios. This holds even for the pelvic region. Standard fluoroscopy anti-scatter grids were found to decrease the SNR in many application scenarios of cone beam CT due to the large patient-detector distance and have, therefore, only a limited benefit in flat detector based cone beam CT.

Noise-resistant weak-structure enhancement for digital radiography

Todays digital radiography systems mostly use unsharp masking-like image enhancement techniques based on splitting input images into two or three frequency channels. This method allows to enhance very small structures (edge enhancement) as well as enhancement of global contrast (harmonization). However, structures of medium size are not accessible by such enhancement. We develop and test a nonlinear enhancement algorithm based on hierarchically repeated unsharp masking, resulting in a multiscale architecture allowing consistent access to structures of all sizes. The algorithm is noise- resistant in the sense that it prevents unacceptable noise amplification. Clinical tests performed in the radiology departments of two major German hospitals so far strongly indicate the superior performance and high acceptance of the new processing.

Nonlinear multiresolution gradient adaptive filter for medical images

We present a novel method for intra-frame image processing, which is applicable to a wide variety of medical imaging modalities, like X-ray angiography, X-ray fluoroscopy, magnetic resonance, or ultrasound. The method allows to reduce noise significantly - by about 4.5 dB and more - while preserving sharp image details. Moreover, selective amplification of image details is possible. The algorithm is based on a multi-resolution approach. Noise reduction is achieved by non-linear adaptive filtering of the individual band pass layers of the multi-resolution pyramid. The adaptivity is controlled by image gradients calculated from the next coarser layer of the multi-resolution pyramid representation, thus exploiting cross-scale dependencies. At sites with strong gradients, filtering is performed only perpendicular to the gradient, i.e. along edges or lines. The multi-resolution approach processes each detail on its appropriate scale so that also for low frequency noise small filter kernels are applied, thus limiting computational costs and allowing a real-time implementation on standard hardware. In addition, gradient norms are used to distinguish smoothly between “structure” and “noise only” areas, and to perform additional noise reduction and edge enhancement by selectively attenuating or amplifying the corresponding band pass coefficients.

Bayesian motion estimation for temporally recursive noise reduction in X-ray fluoroscopy

Abstract This paper develops a Bayesian motion estimation algorithm for motion-compensated temporally recursive filtering of moving low-dose X-ray images (X-ray fluoroscopy). These images often exhibit a very low signal-to-noise ratio. The described motion estimation algorithm is made robust against noise by spatial and temporal regularization. A priori expectations about the spatial and temporal smoothness of the motion vector field are expressed by a generalized Gauss-Markov random field. The advantage of using a generalized Gauss-Markov random field is that, apart from smoothness, it also captures motion edges without requiring an edge detection threshold. The costs of edges are controlled by a single parameter, by means of which the influence of the regularization can be tuned from a median-filter-like behaviour to a linear-filter-like one.

Soft-tissue contrast resolution within the head of human cadaver by means of flat-detector-based cone-beam CT

In this paper, soft tissue contrast visibility in neural applications is investigated for volume imaging based on flat X-ray detector cone-beam CT. Experiments have been performed on a high precision bench-top system with rotating object table and fixed X-ray tube-detector arrangement. Several scans of a post mortem human head specimen have been performed under various conditions. Hereby two different flat X-ray detectors with 366 x 298mm2 (Trixell Pixium 4700) and 176 x 176mm2 (Trixell Pixium 4800) active area have been employed. During a single rotation up to 720 projections have been acquired. For reconstruction of the 3D images a Feldkamp algorithm has been employed. Reconstructed images of the head of human cadaver demonstrate that added soft tissue contrast down to 10 HU is detectable for X-ray dose comparable to CT. However, the limited size of the smaller detector led to truncation artifacts, which were partly compensated by extrapolation of the projections outside the field of view. To reduce cupping artifacts resulting from scattered radiation and to improve visibility of low contrast details, a novel homogenization procedure based on segmentation and polynomial fitting has been developed and applied on the reconstructed voxel data. Even for narrow HU-Windows, limitations due to scatter induced cupping artifacts are no longer noticeable after applying the homogenization procedure.

Multiscale linear/median hybrid filters for noise reduction in low dose X-ray images

This contribution describes a new filtering technique for the reduction of noise in medical X-ray images acquired with very low doses, like fluoroscopy images. In such images, only between 10 and 200 X-ray quanta contribute to each pixel. The resulting Poisson statistic causes a strong deterioration of image quality by quantum noise, which, in the observed images, is signal-dependent and exhibits a lowpass-shaped power spectrum. The central part of our approach is a linear/median hybrid filter, which is well-known for its good detail preservation properties. Noise reduction by this filter, however, depends on the presence or absence of underlying signal slopes, and is limited to a small range of spatial frequencies. Also, like median filters this filter tends to generate streaking artifacts. We show how a combination of linear/median hybrid filtering with a multiscale pyramid avoids these shortcomings, while simultaneously improving noise reduction performance substantially.

Fast Detection and Processing of Arbitrary Contrast Agent Injections in Coronary Angiography and Fluoroscopy

Percutaneous transluminal coronary angioplasty (PTCA) requires both pre-interventional cine-angiograms showing the contrasted vessel tree over several heart cycles, and live X-ray monitoring (fluoroscopy) during the catheterization. Navigation during the intervention can be facilitated by fusing the automatically synchronized cineangiogram with the interventional images, e.g. by overlaying the synchronized angiogram over the interventional images. Clearly, this fusion should be limited to those frames of the angiogram which show the full contrasted vessel tree. Conversely, if contrast agent appears in the fluoroscopy images, overlay is not required and should be switched off. To these ends, we describe approaches for the detection and processing of contrast agent injections in cardiac X-ray image sequences.

Lapped directional transform: a new transform for spectral image analysis

We propose a new real-valued lapped transform for 2D-signal and image processing. Lapped transforms are particularly useful in block-based processing, since their intrinsically overlapping basis functions reduce or prevent block artifacts. Our transform is derived from the modulated lapped transform (MLT), which, as a real-valued and separable transform like the discrete cosine transform, does not allow to unambiguously identify oriented structures from modulus spectra. This is in marked contrast to the (complex-valued) discrete Fourier transform (DFT). The new lapped transform is real-valued, and at the same time allows unambiguous detection of spatial orientation. Furthermore, a fast algorithm for this transform exists. As an application example, we investigate the transforms performance in spectral approaches to image restoration and enhancement in comparison to the DFT.