Scale-space signatures for the detection of clustered microcalculations in digital mammograms

A method is described for the automated detection of microcalcifications in digitized mammograms. The method is based on the Laplacian scale-space representation of the mammogram only. First, possible locations of microcalcifications are identified as local maxima in the filtered image on a range of scales. For each finding, the size and local contrast is estimated, based on the Laplacian response denoted as the scale-space signature. A finding is marked as a microcalcification if the estimated contrast is larger than a predefined threshold which depends on the size of the finding. It is shown that the signature has a characteristic peak, revealing the corresponding image features. This peak can be robustly determined. The basic method is significantly improved by consideration of the statistical variation of the estimated contrast, which is the result of the complex noise characteristic of the mammograms. The method is evaluated with the Nijmegen database and compared to other methods using these mammograms. Results are presented as the free-response receiver operating characteristic (FROC) performance. At a rate of one false positive cluster per image the method reaches a sensitivity of 0.84, which is comparable to the best results achieved so far.     

A comprehensive approach to the analysis of contrast enhanced cardiac MR images

Current magnetic resonance imaging (MRI) technology allows the determination of patient-individual coronary tree structure, detection of infarctions, and assessment of myocardial perfusion. Joint inspection of these three aspects yields valuable information for therapy planning, e.g., through classification of myocardium into healthy tissue, regions showing a reversible hypoperfusion, and infarction with additional information on the corresponding supplying artery. Standard imaging protocols normally provide image data with different orientations, resolutions and coverages for each of the three aspects, which makes a direct comparison of analysis results difficult. The purpose of this work is to develop methods for the alignment and combined analysis of these images. The proposed approach is applied to 21 datasets of healthy and diseased patients from the clinical routine. The evaluation shows that, despite limitations due to typical MRI artifacts, combined inspection is feasible and can yield clinically useful information.     

Interactive 3D medical image segmentation with energy-minimizing implicit functions

We present an interactive segmentation method for 3D medical images that reconstructs the surface of an object using energy-minimizing, smooth, implicit functions. This reconstruction problem is called variational interpolation. For an intuitive segmentation of medical images, variational interpolation can be based on a set of user-drawn, planar contours that can be arbitrarily oriented in 3D space. This also allows an easy integration of the algorithm into the common manual segmentation workflow, where objects are segmented by drawing contours around them on each slice of a 3D image.Because variational interpolation is computationally expensive, we show how to speed up the algorithm to achieve almost real-time calculation times while preserving the overall segmentation quality. Moreover, we show how to improve the robustness of the algorithm by transforming it from an interpolation to an approximation problem and we discuss a local interpolation scheme.A first evaluation of our algorithm by two experienced radiology technicians on 15 liver metastases and 1 liver has shown that the segmentation times can be reduced by a factor of about 2 compared to a slice-wise manual segmentation and only about one fourth of the contours are necessary compared to the number of contours necessary for a manual segmentation.     

Morphological segmentation and partial volume analysis for volumetry of solid pulmonary lesions in thoracic CT scans

Volumetric growth assessment of pulmonary lesions is crucial to both lung cancer screening and oncological therapy monitoring. While several methods for small pulmonary nodules have previously been presented, the segmentation of larger tumors that appear frequently in oncological patients and are more likely to be complexly interconnected with lung morphology has not yet received much attention. We present a fast, automated segmentation method that is based on morphological processing and is suitable for both small and large lesions. In addition, the proposed approach addresses clinical challenges to volume assessment such as variations in imaging protocol or inspiration state by introducing a method of segmentation-based partial volume analysis (SPVA) that follows on the segmentation procedure. Accuracy and reproducibility studies were performed to evaluate the new algorithms. In vivo interobserver and interscan studies on low-dose data from eight clinical metastasis patients revealed that clinically significant volume change can be detected reliably and with negligible computation time by the presented methods. In addition, phantom studies were conducted. Based on the segmentation performed with the proposed method, the performance of the SPVA volumetry method was compared with the conventional technique on a phantom that was scanned with different dosages and reconstructed with varying parameters. Both systematic and absolute errors were shown to be reduced substantially by the SPVA method. The method was especially successful in accounting for slice thickness and reconstruction kernel variations, where the median error was more than halved in comparison to the conventional approach.     

Interactive Visualization of Multimodal Volume Data for Neurosurgical Tumor Treatment

We present novel interactive methods for the visualization of multimodal volume data as used in neurosurgical therapy planning. These methods allow surgeons to explore multimodal volumes and focus on functional data and lesions. Computer graphics techniques are proposed to create expressive visualizations at interactive frame rates to reduce time‐consuming and complex interaction with the medical data. Contributions of our work are the distance‐based enhancements of functional data and lesions which allows the surgeon to perceive functional and anatomical structures at once and relate them directly to the intervention. In addition we propose methods for the visual exploration of the path to the structures of interest, to enhance anatomical landmarks, and to provide additional depth indicators. These techniques have been integrated in a visualization prototype that provides interaction capabilities for finding the optimal therapeutic strategy for the neurosurgeon.     

Assessing the degree of osteoporosis in the axial skeleton using the dependence of the fractal dimension on the grey level threshold

Combining the measurement of bone mineral density (BMD) and the classification of the trabecular structure in cancellous bone improves the estimation of the degree of osteoporosis. A fractal method for the automatic quantitative classification of the trabecular structure in midvertebral slices of lumbar vertebrae is introduced. This method is based on the computation of the fractal dimension (box counting method) for varying binarization thresholds. Radiographic images from 30 lumbar vertebrae and CT images from an additional 16 lumbar vertebrae were analysed by calculating the dimension D in dependency of the threshold value T. The function D(T) was normalized by the average image grey value, eliminating the bone mineral density from the computations. The results show that the images of the lumbar vertebrae have fractal properties, and the function D(T) has a typical behaviour that allows the discrimination of the degree of osteoporosis. With two parameters extracted from the function D(T) the correlation coefficients with BMD were both -79% for the radiographic images, and -93% and -91% for the CT data, respectively.     

Bile duct lesions in laparoscopic cholecystectomy--methods of reconstruction and results

From 1/1991 to 1/1997 a total of 18 patients with major biliary lesions after laparoscopic cholecystectomy were treated. Besides 4 biliary strictures (Bismuth III, Siewert II), which were found between 20 and 180 days after laparoscopic cholecystectomy, large defects (Siewert III, IV) of the proximal parts of the hepatic duct (Bismuth III, IV) occurred in the majority of cases (n = 14). Except for 3 intraoperatively realized lesions, diagnosis was made during the first 3 weeks. Subsequent reinterventions resulted in a high morbidity rate and the need of further procedures to establish definitive biliary reconstruction. Selection criteria of the technique used for repair were the extension of the biliary lesion and the exposure of the distal stump of the common bile duct. A small defect was treated by direct suturing protected by a t-tube (n = 1). Large defects and biliary strictures were reconstructed using either a Roux-en-Y bilio-digestive anastomosis (n = 7) or jejunal interposition (n = 10). The results suggest, that early repair of biliary lesions after laparoscopic cholecystectomy should be achieved. Besides the standard procedure of bilio-digestive anastomosis, reconstruction of major biliary lesions should be performed by jejunal interposition in selected cases.     

Real-time illustration of vascular structures

We present real-time vascular visualization methods, which extend on illustrative rendering techniques to particularly accentuate spatial depth and to improve the perceptive separation of important vascular properties such as branching level and supply area. The resulting visualization can and has already been used for direct projection on a patient's organ in the operation theater where the varying absorption and reflection characteristics of the surface limit the use of color. The important contributions of our work are a GPU-based hatching algorithm for complex tubular structures that emphasizes shape and depth as well as GPU-accelerated shadow-like depth indicators, which enable reliable comparisons of depth distances in a static monoscopic 3D visualization. In addition, we verify the expressiveness of our illustration methods in a large, quantitative study with 160 subjects.     

Automatic maps in exotic numeration systems

We generalize the classical notion of ab-automatic sequence for a sequence indexed by the natural numbers. We replace the integers by a semiring and use a numeration system consisting of the powers of a baseb and an appropriate set of digits. For example, we define (−3)-automatic sequences (indexed by the ordinary integers or by the rational integers) and (−1 +i)-automatic sequences (indexed by the Gaussian integers). We show how these new notions are related to the old ones, and we study both the number-theoretic and automata-theoretic properties that permit the replacement of one numeration system by another.     

Analysis of vasculature for liver surgical planning

For liver surgical planning, the structure and morphology of the hepatic vessels and their relationship to tumors are of major interest. To achieve a fast and robust assistance with optimal quantitative and visual information, we present methods for a geometrical and structural analysis of vessel systems. Starting from the raw image data a sequence of image processing steps has to be carried out until a three-dimensional representation of the relevant anatomic and pathologic structures is generated. Based on computed tomography (CT) scans, the following steps are performed. 1) The volume data is preprocessed and the vessels are segmented. 2) The skeleton of the vessels is determined and transformed into a graph enabling a geometrical and structural shape analysis. Using this information the different intrahepatic vessel systems are identified automatically. 3) Based on the structural analysis of the branches of the portal vein, their vascular territories are approximated with different methods. These methods are compared and validated anatomically by means of corrosion casts of human livers. 4) Vessels are visualized with graphics primitives fitted to the skeleton to provide smooth visualizations without aliasing artifacts. The image analysis techniques have been evaluated in the clinical environment and have been used in more than 170 cases so far to plan interventions and transplantations.