Computerized analysis of coronary artery disease: Performance evaluation of segmentation and tracking of coronary arteries in CT angiograms

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134780/1/mp0294.pd

Variational methods and its applications to computer vision

Many computer vision applications such as image segmentation can be formulated in a ''variational'' way as energy minimization problems. Unfortunately, the computational task of minimizing these energies is usually difficult as it generally involves non convex functions in a space with thousands of dimensions and often the associated combinatorial problems are NP-hard to solve. Furthermore, they are ill-posed inverse problems and therefore are extremely sensitive to perturbations (e.g. noise). For this reason in order to compute a physically reliable approximation from given noisy data, it is necessary to incorporate into the mathematical model appropriate regularizations that require complex computations. The main aim of this work is to describe variational segmentation methods that are particularly effective for curvilinear structures. Due to their complex geometry, classical regularization techniques cannot be adopted because they lead to the loss of most of low contrasted details. In contrast, the proposed method not only better preserves curvilinear structures, but also reconnects some parts that may have been disconnected by noise. Moreover, it can be easily extensible to graphs and successfully applied to different types of data such as medical imagery (i.e. vessels, hearth coronaries etc), material samples (i.e. concrete) and satellite signals (i.e. streets, rivers etc.). In particular, we will show results and performances about an implementation targeting new generation of High Performance Computing (HPC) architectures where different types of coprocessors cooperate. The involved dataset consists of approximately 200 images of cracks, captured in three different tunnels by a robotic machine designed for the European ROBO-SPECT project.Open Acces

Computer assisted surgery for fracture reduction and deformity correction of the pelvis and long bones

Many orthopaedic operations, for example osteotomies, are not preoperative planned. The operation result depends on the experience of the operating surgeon. In the industry new developments are not longer curried out without CAD planning or computer simulations. Only in medicine the operation technology of corrective osteotomies are still in their infant stage in the last 30 years. Two dimensional analysis is not accurate that results in operation errors in the operating room. The surgeon usually obtains the preoperative information about the current bone state by radiographs. In case of complex operations (also inserting implants) planning is required. Planning based on radiographs has some system-dependent disadvantages like small accuracy, requirement of time for corrections ( distortions due to the projection) and restrictions, if complex corrections are necessary. Today the computer tomography is used as a solution. It is the only modality that allows to reach the accuracy and the resolution required for a good 3D-planning. However its a high dose rate for the patient is the serious disadvantage. Therefore in dilemma between the low dose rate and an adequate planning the first is often preferred. However in future it is expected that good operation results are guarantied only with implementation of 3D-planung. MR systems provide image information too, from which indirectly bones can be extracted. But due to their large distortions (susceptibility, non non-homogeneity of magnetic field), small spatial dissolution and the high costs, it is not expected that MRI represents an alternative in next time. The solution is the use of other image modalities. Ultrasound is here a good compromise both of the costs of the accuracy. In this work I developed an algorithm, which can produce 3D bone models from ultrasonic data. They have good resolution and accuracy compared with CT, and therefore can be used for 3D planning. In the work an improved procedure for segmenting bone surfaces is realised in combination with methods for the fusion for a three-dimensional model. The novelty of the presented work is in new approaches to realising an operation planning system, based on 3D computations, and implementing the intraoperative control by a guided ultrasound system for bone tracking. To realise these ideas the following tasks are solved: - bone modelling from CT data; - real-time extraction of bone surfaces from ultrasound imaging; - tracking the bone with respect to CT bone model. - integrating and implementing the above results in the development of an operation planning system for osteotomy corrections that supports on-line measurements, different types of deformity correction, a bone geometry design and a high level of automation. The developed osteotomy planning system allows to investigate the pathology, makes its analysis, finds an optimal way to realise surgery and provides visual and quantitative information about the results of the virtual operation. Therefore, the implementation of the proposed system can be considered as an additional significant tool for the diagnosis and orthopaedic surgery. The major parts of the planning system are: bone modelling from 3D data derived from CT, MRI or other modalities, visualisation of the elements of the 3D scene in real-time, and the geometric design of bone elements. A high level of automation allows the surgeon to reduce significantly the time of the operation plane development