Biomedical subjects

Claus Derz

Publications and source records attributed to Claus Derz.

3 recordsLinked to original sources

PubMed2004

XML knowledge database of MRI-derived eye models.

In a model-based approach, MR images were used to build a database of individual eye models. In order to store the features of the specific eye morphology in an extensible, structured and Internet-accessible database, an appropriate XML structure was implemented. A document type definition was developed that managed the data of the correlated feature space and defined associations via training data sets. The classification and retrieval system has been implemented in Java and successfully applied to classify data sets. Classified data were then added to the database. The presented approach can be easily transferred to similar classification implementations.

Eye↗

PubMed2004

Feature extraction and supervised classification of MR images to support proton radiation therapy of eye tumors.

Proton therapy has the potential for high-precision radiotherapy of retinal tumors. However, the standardized eye models currently used do not fully account for the patient's individual anatomy. To better exploit the data provided by MR images, a model-based approach was used based on a database of eye models. A face recognition algorithm was advanced to define similarity criteria between the reference image and the actual image. After building a high-dimensional feature vector and using a training data set, the reference model was selected by using the minimum Mahalanobis distance between the image to be classified and the reference images.

Eye Neoplasms↗

PubMed2003

3D reconstruction of organ surfaces using model-based snakes.

In this article a new segmentation approach is described that is based on case-based reasoning and a combination of various established image processing concepts described in the current literature. Previously segmented data sets are used as anatomical models that represent the cases, called reference models. They describe the expected surface shape and representation of the organ in the data material. The segmentation task is solved by finding a reference model that is similar to the current data set and then by adapting the reference segmentation to the current data set. Image segmentation can be divided into the steps "determination of the image context", "selection and adjustment of the reference model", and "application of the model-based snake". The necessary interaction time was reduced by more than 60%, including postprocessing to correct for possible segmentation errors.

Computer Simulation↗