Biomedical subjects

E Keeve

Publications and source records attributed to E Keeve.

9 recordsLinked to original sources

PubMed2002

Julius--a software framework for computer-aided-surgery.

In the paper we introduce Julius--an extendable cross-platform software framework for medical visualization and surgical planning. Julius features a modular, cross-platform design using Qt and Vtk libraries and comes with a set of image analysis components, like semi-automatic segmentation, registration, visualization and navigation. We also present a 3D surface generation pipeline used in Julius for generating surfaces from volume data. The pipeline consists of image based filtering, marching cubes surface extraction algorithm, surface decimation and surface smoothing steps. We use this approach within different medical applications like craniofacial surgical planning and will also show the overall software framework within the paper.

Computer Graphics↗

PubMed2002

Haptic interaction with highly detailed objects.

Haptic exploration of detailed models from patient specific anatomical structures places high demands on computational resources. Constant collision detection and correct calculation of forces fed back to the operator quickly exceed available processing power with increasing level of detail of the represented objects. To alleviate the strain on computational resources optimisation schemes are employed to speed up processing and guarantee glitch-free operation as well as smooth haptic feedback. Among these are the generation of a local haptic model, a look-ahead strategy to increase its range of validity, small world-shift operations and force extrapolation algorithms for smooth feedback.

Algorithms↗

PubMed2002

Interactive 3D segmentation and inspection of volumetric medial datasets.

We propose an interactive method providing 3D real-time visualization of segmentation results while tuning some of the algorithmic parameters. Visual inspection in volume reduces the time spent in tuning cumbersome parameters and may increase accuracy in medical applications. To allow fast interaction, volume rendering is achieved by using 3D texture mapping. The output of the segmentation stage is then dynamically updated in the graphic pipeline through a color lookup table related to the tuned parameters. This technique enables our approach with immediate rendering of the user interaction during the segmentation. Isosurface methods and connectivity filters have been implemented with this technique. CT and MR modalities have been tested for anatomical structures extraction. For application in craniofacial surgical planning, measurements present improvement in accuracy and efficiency for 7 pathological cases. However, manual refinement is still necessary in order to realize clinical applicable 3D models.

Computer Simulation↗

PubMed2002

Automatic generation of hexahedral and tetrahedral meshes.

In this paper we present in depth one of the preprocessing steps of our software system for the simulation of soft tissue behaviour and biomechanical processes. The entire system can be used by surgeons for preoperative planning and prediction of postoperative results. The software creates a pipeline to automatically construct meshed datasets for finite element modelling from presegmented patient data.

Algorithms↗

PubMed2002

Fast generation of stereolithographic models.

In this paper we present a work-in-progress method for fast and efficient generation of stereolithographic models. The overall approach is embedded in our general software framework Julius, which runs on high-end-graphic systems as well as on low-level PCs. The design of the support structures needed for the stereolithographic process will allow semiautomatic generation of the model. We did produce support structures for stereolithographic models with this fast data processing pipeline and will show future perspectives in this paper.

Computer Graphics↗

PubMed2002

Surgery planning tools for the osseous grafting treatment.

This paper presents a method for computer assisted selection of optimal donor sites for autologous grafts in the craniofacial surgery planning. The method consists of two stages. The non-automatic graft design step is followed by a fully automatic procedure to find the best harvesting site in the predefined donor region. The main idea of the proposed method is based on the registration paradigm. The optimal donor site is identified by performing an optimization of the surface based similarity measure between the donor region and the designed graft template. An efficient optimization method based on the Levenberg-Marquardt algorithm has been implemented. It enables, once the preprocessing step has been performed, selection of the optimal donor site in time less than one minute.

Algorithms↗

PubMed1998

Deformable modeling of facial tissue for craniofacial surgery simulation.

While deformable object modeling has been studied by computer graphics specialists for more than two decades, only a few applications in the field of surgical simulation have been developed which provide both real-time and physically realistic modeling of complex, nonlinear tissue deformations. Particularly in craniofacial surgery, the prediction of soft-tissue changes--which result from alterations in the underlying bone structure--is critical to the surgical outcome. The prediction these tissue changes and, therefore, the prognosis of the postoperative appearance of the patient, is still based on empirical studies of the relationship between bone and tissue movements: There exists no physical model which takes into account the individual patient anatomy to simulate the resulting tissue changes during craniofacial surgery. In this article we present two different deformable tissue models which are intergrated in an interactive surgical simulation test bed. Both techniques allow precise preoperative simulation of the resulting soft tissue changes during craniofacial surgery and visualization of the patient's postoperative appearance. The different deformable models are described in detail and both are applied to the same craniofacial case study. The simulation results are shown and compared with regard to the speed and accuracy of the prediction of the patient's postoperative appearance.

Computer Simulation↗

PubMed1997

Three-dimensional reconstruction and surgical navigation in pediatric epilepsy surgery.

We have used MRI-based three-dimensional (3D) reconstruction and a real-time, frameless, stereotactic navigation device to facilitate the removal of seizure foci in children suffering from intractable epilepsy. Using this system, the location of subdural grid and strip electrodes is recorded on the 3D model to facilitate focus localization and resection. Ten operations were performed, including 2 girls and 8 boys ranging in age from 3 to 17, during which 3D reconstruction and surgical instrument tracking navigation was used. In all the cases, the patients tolerated the procedure well and showed no postoperative neurological deficits. We believe this to be a valuable tool for a complete and safe resection of seizure foci, thereby reducing the incidence of postoperative neurological deficits and significantly improving the overall quality of life of the patients.

Adolescent↗

PubMed1995

Advances in interactive craniofacial surgery planning by 3D simulation and visualization.

In craniofacial surgery careful preoperative planning is essential. Traditional preoperative work-up consists of cast model surgery, cephalometric prediction tracing and analysis of photographs. Recently, we introduced 3-dimensional (3D) computed tomography (CT) model surgery in our preoperative work-up and presurgical prediction of the postoperative result. However, only limited information can be extracted concerning soft tissue changes which are most important for the patients' postoperative appearance. We propose a new system which will allow a precise preoperative visualization of not only bony structures but also the soft tissue surfaces. 3D CT data of the skull are integrated with 3D surface data acquired by laser scanning. Based on the 3D CT data the bony structures are segmented automatically and processed interactively to simulate the planned surgical procedure. Afterwards, the 3D soft tissue changes resulting from the shifting of bony segments are computed. The postoperative appearance of the patient is visualized using computer animation techniques.

Algorithms↗