Biomedical subjects

Jürgen Hesser

Publications and source records attributed to Jürgen Hesser.

7 recordsLinked to original sources

PubMed2006

3D Live-Wires on mosaic volumes.

The paper discusses the first evaluation of a 3D Live-Wire technique that operates on over-segmented 3D mosaic volumes. Pre-processing normalizes data by histogram spreading followed by over-segmentation with region growing. This leads to a robust and intuitive parameter selection for various tissues and image modalities without requiring problem specific knowledge. During interactive segmentation from a set of user-defined seed points a triangle mesh using Delaunay triangulation is generated. For each triangle, defined by three seed points, a closed surface patch is generated by the 3D Live-Wire method. For evaluation purpose white cerebral matter from MRI images is to be segmented. A mean deviation from the correct object boundary extracted from available model data of about 0.60 pixels (+/- 0.23) is observed while the required time was about 229.5 seconds (+/- 173.2).

Image Interpretation, Computer-Assisted↗

PubMed2006

Fast rigid registration in radiation therapy.

Based on a stochastic mutual information type matching and RPROP as stochastic optimizer, an interactive image-based registration of a CT volume onto two 2D images provided by a megavoltage system is presented. The matching process is based on semi-automatic pre-segmentation, an approximate 2D-2D matching with precomputed virtual projections (DRRs) followed by an accurate 3D-2D matching step. Our sample-based approach requires only a fraction of computed DRRs for 3D-2D. A simultaneous computation of the DRR rays and their perturbations in 6 dimensions speeds up the rendering process by a factor of 6.8. The complete registration process takes 5.6 +/- 2.3 seconds on a 3 GHz Pentium IV PC, being the fastest non-parallel approach for this sort of application the authors are aware of.

Data Display↗

PubMed2006

Analysis and prediction of helix shift errors in homology modeling.

High sequence identity between two proteins (e.g. > 60%) is a strong evidence for high structural similarity. However, internal shifts in one of the two proteins can sometimes give rise to unexpectedly high structural differences. This, in turn, causes unreliable structure predictions when two such proteins are used in homology modeling. Here, we perform a computational analysis of helix shifts and we show that their occurrence can be predicted with statistical learning methods. Our results indicate that helix shifts increase the RMS error by factor 2.6 compared to those protein pairs without a helix shift. Although helix shifts are rare (1.6% of helices and a commensurately higher number of proteins are affected), they therefore pose a significant problem for reliable structure prediction systems. In this paper, we prototype a new approach for model quality assessment and demonstrate that it can successfully warn against helix shifts. A support vector machine trained on a wide range of sequence and structure properties predicts the occurrence of helix shifts with a sensitivity of 74.2% and a specificity of 83.6%. On an equalized test dataset, this corresponds to an accuracy of 78.9%. Projected to the full dataset, it translates to an accuracy of 83.4%. Our analysis shows that helix shift detection is a valuable building block for highly reliable structure prediction systems. Furthermore, the statistical learning based approach to helix shift detection that we employ here is orthogonal to well-established model quality assessment methods (which use geometric constraint checking or mean force potentials). Therefore, a further increase of prediction accuracy is expected from the combination of these methods.

Computational Biology↗

PubMed2004

Catheter simulation system CathI: from patient data generation to cardiological training systems.

In this paper we discuss a new approach to generate 3D models for a simulation system for training an angioplasty. The underlying data for these models are obtained from angiograms that are captured during routine interventions in cardiology. For the extraction of the arteries we use a non-linear classificatory with features based on vesselness information (using a scale-space approach), the gray value, and motion information of the arteries. As result we can correctly find 80% of the arteries in the image and we have 4% pixels incorrectly classified as arteries. These models serve for a virtual catheter laboratory that is based on original instruments like catheters, wires, control instruments for the X-ray, syringes, and pressure pumps for the balloon catheter but instead of a patient an input instrument is used. This instrument sends positional and pressure data to a PC that simulates the patient. The cardiologist then obtains the visual and haptic feedback as if we operated a real patient.

Cardiac Catheterization↗

PubMed2003

MANIFOLD: protein fold recognition based on secondary structure, sequence similarity and enzyme classification.

We present a protein fold recognition method, MANIFOLD, which uses the similarity between target and template proteins in predicted secondary structure, sequence and enzyme code to predict the fold of the target protein. We developed a non-linear ranking scheme in order to combine the scores of the three different similarity measures used. For a difficult test set of proteins with very little sequence similarity, the program predicts the fold class correctly in 34% of cases. This is an over twofold increase in accuracy compared with sequence-based methods such as PSI-BLAST or GenTHREADER, which score 13-14% correct first hits for the same test set. The functional similarity term increases the prediction accuracy by up to 3% compared with using the combination of secondary structure similarity and PSI-BLAST alone. We argue that using functional and secondary structure information can increase the fold recognition beyond sequence similarity.

Algorithms↗

PubMed2002

A divide and conquer approach to fast loop modeling.

We describe a fast ab initio method for modeling local segments in protein structures. The algorithm is based on a divide and conquer approach and uses a database of precalculated look-up tables, which represent a large set of possible conformations for loop segments of variable length. The target loop is recursively decomposed until the resulting conformations are small enough to be compiled analytically. The algorithm, which is not restricted to any specific loop length, generates a ranked set of loop conformations in 20-180 s on a desktop PC. The prediction quality is evaluated in terms of global RMSD. Depending on loop length the top prediction varies between 1.06 A RMSD for three-residue loops and 3.72 A RMSD for eight-residue loops. Due to its speed the method may also be useful to generate alternative starting conformations for complex simulations.

Algorithms↗

PubMed2002

Ultrasound, a new tool for surface matching in computer-navigated surgery.

OBJECTIVE: The object of this study was to investigate the feasibility of generating a bone surface from data provided by an ultrasound examination and to match this surface with the previous computed tomography (CT) scan. METHODS: From a CT data set of a training model of the pelvis, a three-dimensional surface was extracted by global thresholding-based segmentation. The same model was placed in a water basin, and ultrasound images were taken with a guided ultrasound transducer. The three-dimensional surface was generated from the ultrasound data set, and the two surfaces were matched in a semiautomatic mode. RESULTS: With special segmentation methods, a surface could be extracted automatically from the CT and the ultrasound data set. From these segmented ultrasound slices, a volume data set of the model was generated. After approximate initial matching, the local matching process was completed automatically. CONCLUSION: One of the limitations in computer-assisted surgery is the complicated matching process. Using special algorithms, a surface was extracted from the data set of an ultrasound examination and matched in a semiautomatic mode with the surface of a CT data set, facilitating the matching process.

Algorithms↗