Ivo Wolf

The Medical Imaging Interaction Toolkit

Thoroughly designed, open-source toolkits emerge to boost progress in medical imaging. The Insight Toolkit (ITK) provides this for the algorithmic scope of medical imaging, especially for segmentation and registration. But medical imaging algorithms have to be clinically applied to be useful, which additionally requires visualization and interaction. The Visualization Toolkit (VTK) has powerful visualization capabilities, but only low-level support for interaction. In this paper, we present the Medical Imaging Interaction Toolkit (MITK). The goal of MITK is to significantly reduce the effort required to construct specifically tailored, interactive applications for medical image analysis. MITK allows an easy combination of algorithms developed by ITK with visualizations created by VTK and extends these two toolkits with those features, which are outside the scope of both. MITK adds support for complex interactions with multiple states as well as undo-capabilities, a very important prerequisite for convenient user interfaces. Furthermore, MITK facilitates the realization of multiple, different views of the same data (as a multiplanar reconstruction and a 3D rendering) and supports the visualization of 3D+t data, whereas VTK is only designed to create one kind of view of 2D or 3D data. MITK reuses virtually everything from ITK and VTK. Thus, it is not at all a competitor to ITK or VTK, but an extension, which eases the combination of both and adds the features required for interactive, convenient to use medical imaging software. MITK is an open-source project (www.mitk.org).

A shape-guided deformable model with evolutionary algorithm initialization for 3D soft tissue segmentation

We present a novel method for the segmentation of volumetric images, which is especially suitable for highly variable soft tissue structures. Core of the algorithm is a statistical shape model (SSM) of the structure of interest. A global search with an evolutionary algorithm is employed to detect suitable initial parameters for the model, which are subsequently optimized by a local search similar to the Active Shape mechanism. After that, a deformable mesh with the same topology as the SSM is used for the final segmentation: While external forces strive to maximize the posterior probability of the mesh given the local appearance around the boundary, internal forces governed by tension and rigidity terms keep the shape similar to the underlying SSM. To prevent outliers and increase robustness, we determine the applied external forces by an algorithm for optimal surface detection with smoothness constraints. The approach is evaluated on 54 CT images of the liver and reaches an average surface distance of 1.6 +/- 0.5 mm in comparison to manual reference segmentations.

In vivo accuracy assessment of a needle-based navigation system for CT-guided radiofrequency ablation of the liver.

Computed tomography (CT)-guided percutaneous radiofrequency ablation (RFA) has become a commonly used procedure in the treatment of liver tumors. One of the main challenges related to the method is the exact placement of the instrument within the lesion. To address this issue, a system was developed for computer-assisted needle placement which uses a set of fiducial needles to compensate for organ motion in real time. The purpose of this study was to assess the accuracy of the system in vivo. Two medical experts with experience in CT-guided interventions and two nonexperts used the navigation system to perform 32 needle insertions into contrasted agar nodules injected into the livers of two ventilated swine. Skin-to-target path planning and real-time needle guidance were based on preinterventional 1 mm CT data slices. The lesions were hit in 97% of all trials with a mean user error of 2.4 +/- 2.1 mm, a mean target registration error (TRE) of 2.1 +/- 1.1 mm, and a mean overall targeting error of 3.7 +/- 2.3 mm. The nonexperts achieved significantly better results than the experts with an overall error of 2.8 +/- 1.4 mm (n=16) compared to 4.5 +/- 2.7 mm (n=16). The mean time for performing four needle insertions based on one preinterventional planning CT was 57 +/- 19 min with a mean setup time of 27 min, which includes the steps fiducial insertion (24 +/- 15 min), planning CT acquisition (1 +/- 0 min), and registration (2 +/- 1 min). The mean time for path planning and targeting was 5 +/- 4 and 2 +/- 1 min, respectively. Apart from the fiducial insertion step, experts and nonexperts performed comparably fast. It is concluded that the system allows for accurate needle placement into hepatic tumors based on one planning CT and could thus enable considerable improvement to the clinical treatment standard for RFA procedures and other CT-guided interventions in the liver. To support clinical application of the method, optimization of individual system modules to reduce intervention time is proposed.

Active shape models for a fully automated 3d segmentation of the liver – an evaluation on clinical data

This paper presents an evaluation of the performance of a three-dimensional Active Shape Model (ASM) to segment the liver in 48 clinical CT scans. The employed shape model is built from 32 samples using an optimization approach based on the minimum description length (MDL). Three different gray-value appearance models (plain intensity, gradient and normalized gradient profiles) are created to guide the search. The employed segmentation techniques are ASM search with 10 and 30 modes of variation and a deformable model coupled to a shape model with 10 modes of variation. To assess the segmentation performance, the obtained results are compared to manual segmentations with four different measures (overlap, average distance, RMS distance and ratio of deviations larger 5mm). The only appearance model delivering usable results is the normalized gradient profile. The deformable model search achieves the best results, followed by the ASM search with 30 modes. Overall, statistical shape modeling delivers very promising results for a fully automated segmentation of the liver.

Interactive segmentation framework of the Medical Imaging Interaction Toolkit

Interactive methods are indispensable for real world applications of segmentation in medicine, at least to allow for convenient and fast verification and correction of automated techniques. Besides traditional interactive tasks such as adding or removing parts of a segmentation, adjustment of contours or the placement of seed points, the relatively recent Graph Cut and Random Walker segmentation methods demonstrate an interest in advanced interactive strategies for segmentation. Though the value of toolkits and extensible applications is generally accepted for the development of new segmentation algorithms, the topic of interactive segmentation applications is rarely addressed by current toolkits and applications. In this paper, we present the extension of the Medical Imaging Interaction Toolkit (MITK) with a framework for the development of interactive applications for image segmentation. The framework provides a clear structure for the development of new applications and offers a plugin mechanism to easily extend existing applications with additional segmentation tools. In addition, the framework supports shape-based interpolation and multi-level undo/redo of modifications to binary images. To demonstrate the value of the framework, we also present a free, open-source application named InteractiveSegmentation for manual segmentation of medical images (including 3D+t), which is built based on the extended MITK framework. The application includes several features to effectively support manual segmentation, which are not found in comparable freely available applications. InteractiveSegmentation is fully developed and successfully and regularly used in several projects. Using the plugin mechanism, the application enables developers of new algorithms to begin algorithmic work more quickly.

Physical Models Aiding in Complex Congenital Heart Surgery

PURPOSE Our aim was to improve spatial imagination of complex congenital cardiac abnormalities for subsequent surgical intervention. DESCRIPTION Magnetic resonance imaging data of a patient with complex congenital heart malformations was post-processed with software developed at our institution. The resulting virtual surface data sets were printed out three-dimensionally by rapid prototyping techniques. EVALUATION We present the first patient operated on with intraoperative use of physical models representing the intracardiac volumes (RepliCast) or muscle and vessel walls (RepliCardio). The courses of the coronary arteries were visible on the RepliCast, whereas the RepliCardio showed intracardiac views a surgeon could never obtain intraoperatively in the relaxed heart. Other than on virtual reconstructions presented on computer screens, physical models vastly improve the spatial imagination and give precise information regarding localization and actual size of abnormal structures. The self-explanatory utility of these models shortened preparation and expedited orientation on the open heart. CONCLUSIONS The additional spatial information provided by RepliCast and RepliCardio models may enable even high-risk correction procedures in patients with complex congenital heart disease.

Quantification of glomerular number and size distribution in normal rat kidneys using magnetic resonance imaging

BACKGROUND Glomerular number and size are important risk factors for chronic kidney disease (CKD) and cardiovascular disease and have traditionally been estimated using invasive techniques. Here, we report a novel technique to count and size every glomerulus in the rat kidney using magnetic resonance imaging (MRI). METHODS The ferromagnetic nature of cationized ferritin allowed visualization of single glomeruli in high-resolution susceptibility-weighted MRI. A segmentation algorithm was used to identify and count all glomeruli within the whole kidney. To prove our concept, we estimated total glomerular number and mean glomerular volume of each kidney using design-based stereology. RESULTS The glomerular counts obtained with MRI agreed well with estimates obtained using traditional methods [MRI, 32 785 (3117); stereology, 35 132 (3123)]. For the first time, the glomerular volume distribution for the entire kidney is shown. Additionally, the method is substantially faster than the current methods. CONCLUSIONS MRI provides a new method for measuring these important microanatomical markers of disease risk and leads the way to in vivo analysis of these parameters, including longitudinal studies of animal models of CKD.

The Medical Imaging Interaction Toolkit (MITK) - a toolkit facilitating the creation of interactive software by extending VTK and ITK

The aim of the Medical Imaging Interaction Toolkit (MITK) is to facilitate the creation of clinically usable image-based software. Clinically usable software for image-guided procedures and image analysis require a high degree of interaction to verify and, if necessary, correct results from (semi-)automatic algorithms. MITK is a class library basing on and extending the Insight Toolkit (ITK) and the Visualization Toolkit (VTK). ITK provides leading-edge registration and segmentation algorithms and forms the algorithmic basis. VTK has powerful visualization capabilities, but only low-level support for interaction (like picking methods, rotation, movement and scaling of objects). MITK adds support for high level interactions with data like, for example, the interactive construction and modification of data objects. This includes concepts for interactions with multiple states as well as undo-capabilities. Furthermore, VTK is designed to create one kind of view on the data (either one 2D visualization or a 3D visualization). MITK facilitates the realization of multiple, different views on the same data (like multiple, multiplanar reconstructions and a 3D rendering). Hierarchically structured combinations of any number and type of data objects (image, surface, vessels, etc.) are possible. MITK can handle 3D+t data, which are required for several important medical applications, whereas VTK alone supports only 2D and 3D data. The benefit of MITK is that it supplements those features to ITK and VTK that are required for convenient to use, interactive and by that clinically usable image-based software, and that are outside the scope of both. MITK will be made open-source (http://www.mitk.org).

Stereolithographic reproduction of complex cardiac morphology based on high spatial resolution imaging

SammaryBackgroundPrecise knowledge of cardiac anatomy is mandatory for diagnosis and treatment of congenital heart disease. Modern imaging techniques allow high resolution three-dimensional (3D) imaging of the heart and great vessels. In this study stereolithography was evaluated for 3D reconstructions of multidetector computed tomography (MDCT) and magnetic resonance imaging (MRI) data.MethodsA plastinated heart specimen was scanned with MDCT and after segmentation a stereolithographic (STL) model was produced with laser sinter technique. After scanning the STL model with MDCT these data were compared with those of the original specimen after rigid registration using the iterative closest points algorithm (ICP). The two surfaces of the original specimen and STL model were matched and the symmetric mean distance was calculated. Additionally, the heart and great vessels of patients (age range 41 days–21 years) with congenital heart anomalies were imaged with MDCT (n = 2) or free breathing steady, state free-precession MRI (n = 3). STL models were produced from these datasets and the cardiac segments were analyzed by two independent observers.ResultsAll cardiac structures of the heart specimen were reconstructed as a STL model within sub-millimeter resolution (mean surface distance 0.27 ± 0.76 mm). Cardiac segments of the STL patient models were correctly analyzed by two independent observers compared to the original 3D datasets, echocardiography (n = 5), x-ray angiography (n = 5), and surgery (n = 4).ConclusionsHigh resolution MDCT or MRI 3D datasets can be accurately reconstructed using laser sinter technique. Teaching, research and preoperative planning may be facilitated in the future using this technique.

The practical clinical value of three-dimensional models of complex congenitally malformed hearts

OBJECTIVE Detailed 3-dimensional anatomic information is essential when planning strategies of surgical treatment for patients with complex congenitally malformed hearts. Current imaging techniques, however, do not always provide all the necessary anatomic information in a user-friendly fashion. We sought to assess the practical clinical value of realistic 3-dimensional models of complex congenitally malformed hearts. METHODS In 11 patients, aged from 0.8 to 27 years, all with complex congenitally malformed hearts, an unequivocal decision regarding the optimum surgical strategy had not been reached when using standard diagnostic tools. Therefore, we constructed 3-dimensional virtual computer and printed cast models of the heart on the basis of high-resolution whole-heart or cine magnetic resonance imaging or computed tomography. Anatomic descriptions were compared with intraoperative findings when surgery was performed. RESULTS Independently of age-related factors, images acquired in all patients using magnetic resonance imaging and computed tomography proved to be of sufficient quality for producing the models without major differences in the postprocessing and revealing the anatomy in an unequivocal 3-dimensional context. Examination of the models provided invaluable additional information that supported the surgical decision-making. The anatomy as shown in the models was confirmed during surgery. Biventricular corrective surgery was achieved in 5 patients, palliative surgery was achieved in 3 patients, and lack of suitable surgical options was confirmed in the remaining 3 patients. CONCLUSION Realistic 3-dimensional modeling of the heart provides a new means for the assessment of complex intracardiac anatomy. We expect this method to change current diagnostic approaches and facilitate preoperative planning.