Biomedical Image and Signal Computing (BISC 2013)

Organisation (Ansprechpartner)

Prof. Dr. C. Palm (Regensburg): christoph.palm(at)hs-regensburg.de
Prof. Dr. Thomas Schanze (Gießen): thomas.schanze(at)kmub.thm.de

Weitere wichtige Informationen u.a. zur Beitragseinreichung finden Sie auf der separaten Workshop-Webseite www.workshop.re-mic.de.



Biomedical signals and images are observations of physiological processes and their impact for healthcare applications is still rising. Examples are time series like ECG, EEG or intracortical multi-electrode recordings. At the other end of the spectrum we have image data recorded by microscopy, magnetic resonance imaging (MRI), computed tomography (CT) or ultrasound systems. Of particular importance are combinations of various measurement methods and the subsequent processing of the high dimensional data sets.

Processing of signals as well of images is divided into several methodological parts like pre-processing, noise reduction, fusion, analysis and pattern recognition. Although the requirements for biomedical image and signal processing are very similar, both have developed to different and autonomous disciplines of research and development.

The main goal of the newly established workshop Biomedical Image and Signal Processing (BISC) is to bridge the gap between image and signal processing. We aim to enhance the methodological exchange, identify areas of overlap, find new trends especially at the edge between both areas and foster personal communication across disciplines and special interest groups. We thank especially the following associations for their support:
- Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (GMDS)
- Gesellschaft für Informatik (GI)
- Deutsche Gesellschaft für Biomedizinische Technik im VDE (DGMT).


The content range of accepted abstracts is wide in terms of information sources, focus of application as well as methodology. Images and signals result from MRI, functional MRI, x-ray, microscopy, ultrasound, CT and ECG. Methods to deal with these information sources start with pre-processing, semi-classical signal analysis and signal analysis in the time-frequency domain. They are carried forward with texture analysis, reconstruction and filtering, visualization and parallelization to end up with segmentation, classification and registration methods. Some approaches are formulated for general purpose applications in the biomedical domain, some others are developed specifically for diseases like brain tumors, breast cancer, major depressive disorder and gastro-esophageal reflux disease or for body parts like lungs or ventricles.

Interestingly, the majority of abstracts focus on combinations of different disciplines, methods or imaging modalities. The processing of ultrasound images interpreting the time course as signal results in a spatio-temporal analysis. The application of image processing filters to the visualization of ECG signals combines image and signal processing methods for improved analysis. The combination of registration and segmentation methods aims to benefit from both methods. In addition, data recorded at different points in time allow follow-up diagnosis and novel time-course analyses. The fusion of different imaging modalities provides more insight into the relationship of structures and, thus, improves diagnosis.

Hence, the BISC workshop - combining the disciplines biomedical image and signal processing - points in the right direction where innovations can be expected.

Programme (Tu, 3.9.2013):

09:00 Christoph Palm: Welcome/Introduction

09:05 Viola Borchardt: Impact of preprocessing of resting-state fMRI time series on group classification in Major Depressive Disorder
09:20 Galina Ivanova: New Methodical Developments for Dynamic Analysis in Time-Frequency Domain
09:35 Joachim Weber: Parallelization of FSL-Fast segmentation of MRI brain data
09:50 Kai Ritschel: Spatio-Temporal Analysis of Contrast Enhanced Ultrasound Perfusion Imaging Data
10:05 Marc Fournelle: Advanced channel-data signal processing in multimodal ultrasound imaging
10:20 Thomas Schanze: Extension of a semi-classical signal analysis method

10:35 Coffee Break

11:00 Tim Becker: Geometric hashing to fuse microscopical data and fluorescence images: on the way to functional immunofluorescence
11:15 Claudia Dach: CAD4GERD - Computer-Assisted Diagnostic for Gastroesophageal Reflux Disease – First Results
11:30 Thomas Polzin: Lung Registration using Automatically Detected Landmarks
11:45 Timo Kepp: Combined Registration and Segmentation of the Left Ventricle in Cine MR Image Data
12:00 Torsten Hopp: Interactive multimodal breast cancer diagnosis based on a registration of X-ray mammograms and 3D volume data
12:15 Sebastian Zaunseder: Camera-based monitoring of cardio-respiratory signals – combining image and signal processing
12:30 Stephan Jonas: Integrated Processing and Visualization Framework for Signal and Signal-to-Image Data

12:45 Thomas Schanze: Conclusions/Farewell