Holger Kunze

A Novel Approach for Filtered Backprojection in Tomosynthesis Based on Filter Kernels Determined by Iterative Reconstruction Techniques

Breast tomosynthesis is a new 3D imaging technique providing 3D slices of the breast. The computation of 3D slices from a set of 2D projections is performed with a reconstruction algorithm --- either a filtered backprojection (FBP) or an algebraic iterative reconstruction method. Both approaches yield different image characteristics of the reconstructed object. The algebraic method has the main disadvantage of a very long processing time. We experimentally developed a set of filter kernels for FBP, determined by iterative reconstruction providing similar image characteristics and quality as an algebraic reconstruction. Additionally we showed that it is possible to approximate these kernels by a polynomial function of order 4. Using clinical data sets we demonstrate how the image quality and the image impression can be varied by using different reconstruction methods.

Image features for misalignment correction in medical flat‐detector CT

PURPOSE Misalignment artifacts are a serious problem in medical flat-detector computed tomography. Generally, the geometrical parameters, which are essential for reconstruction, are provided by preceding calibration routines. These procedures are time consuming and the later use of stored parameters is sensitive toward external impacts or patient movement. The method of choice in a clinical environment would be a markerless online-calibration procedure that allows flexible scan trajectories and simultaneously corrects misalignment and motion artifacts during the reconstruction process. Therefore, different image features were evaluated according to their capability of quantifying misalignment. METHODS Projections of the FORBILD head and thorax phantoms were simulated. Additionally, acquisitions of a head phantom and patient data were used for evaluation. For the reconstruction different sources and magnitudes of misalignment were introduced in the geometry description. The resulting volumes were analyzed by entropy (based on the gray-level histogram), total variation, Gabor filter texture features, Haralick co-occurrence features, and Tamura texture features. The feature results were compared to the back-projection mismatch of the disturbed geometry. RESULTS The evaluations demonstrate the ability of several well-established image features to classify misalignment. The authors elaborated the particular suitability of the gray-level histogram-based entropy on identifying misalignment artifacts, after applying an appropriate window level (bone window). CONCLUSIONS Some of the proposed feature extraction algorithms show a strong correlation with the misalignment level. Especially, entropy-based methods showed very good correspondence, with the best of these being the type that uses the gray-level histogram for calculation. This makes it a suitable image feature for online-calibration.

Iterative extended field of view reconstruction

Incomplete data due to the object extent beyond the scanning field of view (SFOV) is a common problem in computed tomography. In these cases, there are parts of the object to be reconstructed for which only incomplete projections of less than 180o are available. Applying iterative algorithms like algebraic reconstruction technique (ART) or simultaneous algebraic reconstruction Technique (SART) onto the problem of truncated projections can not produce a satisfying solution unless special constraints are used. To regularize the reconstruction algorithm, we extend iterative reconstruction algorithms by introducing information regarding the statistics of the attenuation values of the reconstructed object in terms of the log likelihood function of attenuation values. This information can be taken from the regions of the image still inside the SFOV but close to the region where the object exceeds the SFOV. The information can be utilized in an algebraic reconstruction method by adding a constraint term to the cost function that shall be minimized. Experiments show that for not severely truncated projections, as they are common for CT applications, including this information yields good estimates about the object.

An online motion- and misalignment-correction method for medical flat-detector CT

Misalignment-Correction in C-arm-based flat-detector CT (FD-CT) is a frequently discussed problem. To avoid artifacts caused by geometrical instabilities, numerous methods for misalignment correction were investigated. Most of them make use of a foregoing calibration routine, based on scanning a specific phantom. The aim of this study is to develop and evaluate an online image-content-based calibration technique without using any kind of marker or calibration phantom. The introduced method is based on a gradient descent method, minimizing an entropy criterion which is used to optimize the underlying geometry parameters of the acquisition system. It is formed as multistep approach, including a global, local and projection wise optimization. This enables the elimination of general system misalignments, as well as a reduction of streak artifacts and the adjustment of patient motion artifacts. Phantom and patient measurements with the C-arm FD-CT system Artis Zeego (Siemens AG, Healthcare Sector, Forchheim, Germany) were used to validate the algorithm for realistic applications. It reduced most of the actual misalignment and increased image quality drastically. Phantom-studies, starting from the standard system geometry without a foregoing calibration showed very good results. Online-calibration is possible with our approach and therefore, the limitation to predefined scan-protocols is obsolete. The evaluation of patient datasets brought out the same conclusions and provides the implication of simultaneous patient motion compensation.

Cone-beam reconstruction from a variable-radius, planar source trajectory

In this paper, we present a practical Feldkamp-like algorithm for flat-panel cone-beam reconstruction from a planar source trajectory with varying radius. Along with the reconstruction, our algorithm simultaneously recovers the shape of the field-of-view, which can be of complex structure in variable-radius geometries. Numerical results of our algorithm are presented for a short-scan rectangular acquisition geometry as well a full-scan flower-shape geometry. Evaluation was carried out using simulated data of the FORBILD head phantom.

Filtered backprojection reconstruction with depth-dependent filtering

A direct filtered-backprojection (FBP) reconstruction algorithm is presented for circular cone-beam computed tomography (CB-CT) that allows the filter operation to be applied efficiently with shift-variant band-pass characteristics on the kernel function. Our algorithm is derived from the ramp-filter based FBP method of Feldkamp et al. and obtained by decomposing the ramp filtering into a convolution involving the Hilbert kernel (global operation) and a subsequent differentiation operation (local operation). The differentiation is implemented as a finite difference of two (Hilbert filtered) data samples and carried out as part of the backprojection step. The spacing between the two samples, which defines the low-pass characteristics of the filter operation, can thus be selected individually for each point in the image volume. We here define the sample spacing to follow the magnification of the divergent-beam geometry and thus obtain a novel, depth-dependent filtering algorithm for circular CB-CT. We evaluate this resulting algorithm using computer-simulated CB data and demonstrate that our algorithm yields results where spatial resolution and image noise are distributed much more uniformly over the field-of-view, compared to Feldkamps approach.

High Precision UWB-Based 3D Localization for Medical Environment

In recent years developments in medical interventions led to an increase in technical equipment and devices. By providing a spatio- temporal identification and localization framework beneficial applications can be realized in a crowded, dynamic and harsh environment. Ultra wideband using an impulse radio signaling scheme has attracted interest for applications where precise localization is needed. In this paper we present a high precision, real-time 3D localization system using commercially available UWB hardware modules that are compliant with the frequency and RF emission restrictions of the Federal Communications Commission. We implement a trilateration algorithm and three tracking filter to improve the raw UWB localization data. Results from our measurement campaign in medical environment show an accuracy of 35 mm and a precision of up to 1.5 mm in a static case with approximately 30 Hz position update rate. We also shed a light on the dynamic behavior of the implemented filter algorithms and give suggestions to improve them. The proposed UWB localization system shows an initial step of high precision localization in medical environment.

Investigation of an efficient short-scan C-arm reconstruction method with radon-based redundancy handling

The short-scan Feldkamp David Kress (FDK) method for C-arm CT reconstruction involves a heuristic raybased weighting scheme to handle data redundancies. This scheme is known to be approximate under general circumstances and it often creates low frequency image artifacts in regions away from the central axial plane. Alternative algorithms, such as the one proposed by Defrise and Clack (DC),1 can handle data redundancy in a theoretically exact manner and thus notably improve image quality. The DC algorithm, however, is computationally more complex than FDK, as it requires a shift-variant 2D filtering of the data instead of a efficient 1D filtering. In this paper, a modification of the original DC algorithm is investigated, which applies the efficient FDK filtering scheme whereever possible and the DC filtering scheme only where it is required. This modification leads to a more efficient implementation of the DC algorithm, in which filtering effort can be reduced by up to about 70%, dependent on the specific geometry set-up. This gain in computation speed makes the DC method even more attractive for use in an interventional environment, where fast and interactive X-ray imaging is a crucial requirement.