Max Schöbinger

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).

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).

Branching patterns and drainage territories of the middle hepatic vein in computer-simulated right living-donor hepatectomies.

Full right hepatic grafts are most frequently used for adult‐to‐adult living donor liver transplantation (LDLT). One of the major problems is venous drainage of segments 5 and 8. Thus, this study was designed to provide information on venous drainage of right liver lobes for operation‐planning. Fifty‐six CT data sets from routine clinical imaging were evaluated retrospectively using a liver operation‐planning system. We defined and analyzed venous drainage segments and the impact of anatomic variations of the middle hepatic vein (MHV) on venous outflow from segments 5 and 8. MHV variations led to significant shifts of segment 5 drainage between the middle and right hepatic vein. In cases with the most frequent MHV branching pattern (n = 33), a virtual hepatectomy closely right to the MHV intersected drainage vessels that provided drainage for 30% of the potential graft, not taking into account potential veno‐venous shunts. In individuals with inferior MHV branches that extend far into segments 5 and 6 (n = 10), the overall graft volume at risk of impaired venous drainage increased by 5% (p < 0.001). If this is confirmed in clinical trials and correlated with intraoperative findings, the use of liver operation‐planning systems would be beneficial to improve overall outcome after right lobe LDLT.

An interactive system for volume segmentation in computer-assisted surgery

Computer-assisted surgery aims at a decreased surgical risk and a reduced recovery time of patients. However, its use is still limited to complex cases because of the high effort. It is often caused by the extensive medical image analysis. Especially, image segmentation requires a lot of manual work. Surgeons and radiologists are suffering from usability problems of many workstations. In this work, we present a dedicated workplace for interactive segmentation integratd within the CHILI (tele-)radiology system. The software comes with a lot of improvements with respect to its graphical user interface, the segmentation process and the segmentatin methods. We point out important software requirements and give insight into the concepts which were implemented. Further examples and applications illustrate the software system.

Implementation and evaluation of a new workflow for registration and segmentation of pulmonary MRI data for regional lung perfusion assessment

Recently it has been shown that regional lung perfusion can be assessed using time-resolved contrast-enhanced magnetic resonance (MR) imaging. Quantification of the perfusion images has been attempted, based on definition of small regions of interest (ROIs). Use of complete lung segmentations instead of ROIs could possibly increase quantification accuracy. Due to the low signal-to-noise ratio, automatic segmentation algorithms cannot be applied. On the other hand, manual segmentation of the lung tissue is very time consuming and can become inaccurate, as the borders of the lung to adjacent tissues are not always clearly visible. We propose a new workflow for semi-automatic segmentation of the lung from additionally acquired morphological HASTE MR images. First the lung is delineated semi-automatically in the HASTE image. Next the HASTE image is automatically registered with the perfusion images. Finally, the transformation resulting from the registration is used to align the lung segmentation from the morphological dataset with the perfusion images. We evaluated rigid, affine and locally elastic transformations, suitable optimizers and different implementations of mutual information (MI) metrics to determine the best possible registration algorithm. We located the shortcomings of the registration procedure and under which conditions automatic registration will succeed or fail. Segmentation results were evaluated using overlap and distance measures. Integration of the new workflow reduces the time needed for post-processing of the data, simplifies the perfusion quantification and reduces interobserver variability in the segmentation process. In addition, the matched morphological data set can be used to identify morphologic changes as the source for the perfusion abnormalities.

Semiautomatic assessment of respiratory motion in dynamic MRI - Comparison with simultaneously acquired spirometry

PURPOSE Supplementing global spirometry with regional information could allow for earlier and more specific diagnosis of lung disease. Dynamic magnetic resonance imaging (dMRI) makes it possible to derive functional parameters from the visualization of the pulmonary motion of single lungs. The aim of this study was to compare high temporal resolution measurements of left and right thoracic diameters to simultaneously acquired spirometry. MATERIALS AND METHODS 10 healthy volunteers underwent 2-dimensional dMRI of both lungs at 1.5 T. Spirometry was performed simultaneously with an MRI-compatible spirometer. Thoracic diameters were measured semiautomatically and compared to simultaneously measured spirometric volumes. A dMRI surrogate for the Tiffeneau Index was compared to the spirometric Tiffeneau. RESULTS The volume-time and flow-volume curves from dMRI were very similar to the spirometric curves. The semiautomatically measured diameters correlated well with the spirometric volumes (r > = 0.8, p < 10 - 15). Agreement between the methods at full temporal resolution was not as convincing (width of 95 % limits of agreement interval up to 56 %). Good agreement was found between the Tiffenau surrogate and spirometry (width of 95 % limits of agreement interval of 14.5 %). CONCLUSION DMRI with semiautomatic measurement of thoracic diameters makes measurement of realistic volume-time and flow-volume curves from single lungs possible. The derived single lung Tiffeneau Index shows good agreement to spirometry and could be valuable to supplement global spirometric measurements with functional data from single lungs.

How many CT detector rows are necessary to perform adequate three dimensional visualization

INTRODUCTION The technical development of computer tomography (CT) imaging has experienced great progress. As consequence, CT data to be used for 3D visualization is not only based on 4 row CTs and 16 row CTs but also on 64 row CTs, respectively. The main goal of this study was to examine whether the increased amount of CT detector rows is correlated with improved quality of the 3D images. MATERIAL AND METHODS All CTs were acquired during routinely performed preoperative evaluation. Overall, there were 12 data sets based on 4 detector row CT, 12 data sets based on 16 detector row CT, and 10 data sets based on 64 detector row CT. Imaging data sets were transferred to the DKFZ Heidelberg using the CHILI teleradiology system. For the analysis all CT scans were examined in a blinded fashion, i.e. both the name of the patient as well as the name of the CT brand were erased. For analysis, the time for segmentation of liver, both portal and hepatic veins as well as the branching depth of portal veins and hepatic veins was recorded automatically. In addition, all results were validated in a blinded fashion based on given quality index. RESULTS Segmentation of the liver was performed in significantly shorter time (p<0.01, Kruskal-Wallis test) in the 16 row CT (median 479 s) compared to 4 row CT (median 611 s), and 64 row CT (median 670 s), respectively. The branching depth of the portal vein did not differ significantly among the 3 different data sets (p=0.37, Kruskal-Wallis test). However, the branching depth of the hepatic veins was significantly better (p=0.028, Kruskal-Wallis test) in the 4 row CT and 16 row CT compared to 64 row CT. The grading of the quality index was not statistically different for portal veins and hepatic veins (p=0.80, Kruskal-Wallis test). Even though the total quality index was better for the vessel tree based on 64 row CT data sets (mean scale 2.6) compared to 4 CT row data (mean scale 3.25) and 16 row CT data (mean scale 3.0), these differences did not reach statistical difference (p=0.53, Kruskal-Wallis test). CONCLUSION Even though 3D visualization is useful in operation planning, the quality of the 3D images appears to be not dependent of the number of CT detector rows.

Generation of attributed relational vessel graphs from three-dimensional freehand ultrasound for intraoperative registration in image-guided liver surgery

We propose a procedure for the intraoperative generation of attributed relational vessel graphs. It builds the prerequisite for a vessel-based registration of a virtual, patient-individual, preoperative, three-dimensional liver model with the intraopeatively deformed liver by graph matching. An image processing pipeline is proposed to extract an abstract representation of the vascular anatomy from intraoperatively acquired three-dimensional ultrasound. The procedure is transferable to other vascularized soft tissues like the brain or the kidneys. We believe that our approach is suitable for intraoperative application as basis for efficient vessel-based registration of the surgical volume of interest. By reducing the problem of intraoperative registration in visceral surgery to the mapping of corresponding attributed relational vessel graphs a fast and reliable registration seems feasible even in the depth of deformed vascularized soft tissues like in human livers.

Robuste Analyse von Gefäßstrukturen auf Basis einer 3D-Skelettierung

In dieser Arbeit wird ein Verfahren vorgestellt, welches es erlaubt, eine symbolische Beschreibung aus segmentierten Blutgefasen zu erzeugen. Im resultierenden Graphen ist der Verlauf der Gefasaste, deren Durchmesser und die Lage von Verzweigungen gespeichert. Der Algorithmus wurde auf Basis eines existierenden Ansatzes entwickelt, der in Bezug auf die Rotationsinvarianz verbessert und um ein neues Grapherzeugungsverfahren erweitert wurde. Zusatzlich werden Methoden bereitgestellt, die es erlauben, die Enstehung von fehlerhaften Asten zu vermeiden, oder sie im nachhinein ausschlieslich auf Basis der Information im Gefasgraphen zu identifizieren und zu loschen.

Computer-Based Liver Volumetry in the Liver Perfusion Simulator

BACKGROUND An exact preoperative liver volume calculation is important prior to liver surgery and living-related liver transplantation. However, CT or MRI assessment of preoperative liver volume is associated with an estimation error of 1.2% to 36%, and little data is available on its accuracy on the segmental level. The aim of this study was to validate arterial and portal venous flow rates and gain information on liver volumetry, including liver segments, in the liver perfusion simulator and compare it to in vivo measurements in a porcine model. MATERIAL AND METHODS The arterial and portal venous flow rates and liver volumes of 10 pigs were measured in vivo and compared with the flow rates and volumes ex vivo. CT scans were performed and the volume of the liver and its lobes calculated by water displacement or computer-assistance based on the CT scans. The right lateral lobe was plasticized and reconstructed for the volume calculation. RESULTS In the liver perfusion simulator, arterial and portal venous flow rates comparable to the in vivo rates were achieved. The liver volume had a mean difference of 10.3% between in vivo and ex vivo measurements. In the liver perfusion simulator, the mean deviation in liver volume between the computer calculation and water displacement was 2.8%. On the segmental level, the Heidelberg algorithm provided an accuracy of 97.7%. CONCLUSION The liver perfusion simulator is an excellent device for studies in liver perfusion and volumetry. Furthermore, the simulator is applicable for teaching and performing interventions and surgeries in livers.