IDPsPage

Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

IDPs

Running IDPs

Efficient Interpolation Methods for Physical Models in Medical X-ray Computed Tomography

X-Ray Computed Tomography (CT) is one of the cornerstones of medical imaging for many decades now. The tomographic reconstruction of CT is quite well understood theoretically and practically, but many open research issues remain. A central point for any reconstruction method is the projector and back-projector pair, which models the interaction process of X-rays with matter, the detection process in the detector and the acquisition geometry. Several standard methods for this are described in the literature, each with specific advantages and disadvantages. Common to all these methods are high computational requirements, necessitating the use of parallel computing.
supervisor:Tobias Lasser
professor:Nassir Navab
student:Christoph Hahn
start-end:2017/05/10 - 2017/09/15
Regularization of spherical functions in medical imaging of X-ray anisotropic dark-field signals

Medical imaging modalities such as X-ray Computed Tomography (X-ray CT) or Positron Emission Computed Tomography (PET) have been the basis of accurate diagnosis in clinical practice for decades, one particular example being the detection of tumors. But medical imaging also plays a central role during the therapy, for example when planning complex surgeries or when planning and monitoring radiation therapy treatments. New X-ray contrast modalities, such as phase-contrast and dark-field contrast, are being developed in the last few years, based on a break-through in grating interferometry, with many promising clinical applications, ranging from breast cancer detection to diagnosis of osteoporosis.
supervisor:Tobias Lasser
professor:Nassir Navab
student:Stefan Haninger
start-end:2017/02/15 - 2017/06/15
Detectability Indices in Directional X-ray Dark-field Tomography

Medical imaging modalities such as X-ray Computed Tomography (X-ray CT) or Positron Emission Computed Tomography (PET) have been the basis of accurate diagnosis in clinical practice for decades, one particular example being the detection of tumors. But medical imaging also plays a central role during the therapy, for example when planning complex surgeries or when planning and monitoring radiation therapy treatments. Advanced X-ray imaging contrast modalities, such as phase-contrast or dark-field contrast, have recently demonstrated very promising fields of application both in diagnosis and therapy. The dark-field contrast in particular promises advanced imaging capabilities that are unprecedented and not available in other medical imaging modalities. Thanks to its directional dependence, it enables resolving micro structure orientations below the detector resolution, allowing insights into various anatomical and physiological processes, such as the connectivity of the brain. However, for practical clinical application several technical issues still have to be addressed in order to reach feasibility in terms of experimental setup, acquisition and processing times as well as dose considerations. While the directional dependence and anisotropy of the X-ray dark-field signal enables new applications, it also requires more acquisitions sampled all around the object, and thus longer acquisition times, higher dose and longer processing times compared to traditional tomographic imaging modalities.
supervisor:Tobias Lasser
professor:Nassir Navab
student:Theodor Cheslerean Boghiu
start-end:2017/04/15 - 2017/08/15
Bringing a robotic SPECT/CT prototype into the OR

The objective of this project is the refinement and preparation for its first clinical use of an interventional robotic SPECT/CT prototype. This entails the development of a user-friendly GUI and the optimization of the core data processing module.
supervisor:Marco Esposito, Dr. Benjamin Frisch
professor:Prof. Dr. Nassir Navab
student:
start-end: -
Instrument Detection from External Cameras in the OR

Knowledge about the instruments in use at every point in time during a surgery allows a very detailed analysis and recognition of the surgical workflow, and therefore predictions and numerous other applications. Several approaches exist to detect instrument usage in the OR, often involving additional sensors attached to the instruments. This has additional hard constraints due to the surgical sterility requirements, but is also prone to noise due to its makeshift nature. One approach currently under research by several groups is the detection of instruments from the laparoscopic view directly, but with the extreme optical challenges, that this method poses, more work is still required before reliable results can be expected. The goal of this work is to detect the instruments on the mayo stand through an external, ceiling-mounted camera. No additional sensors or markers are to be attached to the instruments or the surgical staff. The developed method should be able to detect multiple instruments in the same image, possibly several individual instruments of the same type. The approach should be robust against partial occlusions (e.g. by the hands of the scrub nurse) or overlapping instruments. Real-time capabilities up to 1Hz are beneficial, but not a requirement of this project.
supervisor:Ralf Stauder
professor:Prof. Nassir Navab
student:Richard Voigt
start-end:2015-07-15 - 2016-01-15
Coronary Arteries

supervisor:Dr. Stefanie Demirci,Dr. Pascal Fallavollita
professor:Prof. Nassir Navab
student:Sai Gokul Hariharan
start-end:1.8.2013 -

Finished IDPs



Edit | Attach | Refresh | Diffs | More | Revision r1.9 - 09 Jun 2005 - 12:00 - AxelMoeller

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