MISP

MeVisLab

MeVisLab represents a powerful, modular framework for the development of image processing algorithms and visualization and interaction methods, with a special focus on medical imaging. Besides basic image processing and visualization modules, MeVisLab includes advanced medical imaging algorithms for segmentation, registration, and quantitative morphological and functional image analysis.

MeVisLab is being developed and used by MeVis Medical Solutions AG and Fraunhofer MEVIS (formerly MeVis Research GmbH) in Bremen, Germany. MeVis Medical Solutions and Fraunhofer MEVIS develop scientific methods and software for computer assistance in medicine in general and radiology in particular, including computer aided diagnosis, therapy planning and monitoring, and computer aided teaching and training.

Workshop

During the workshop we will use MeVisLab to handle some advanced image processing tasks:

• Determine if a chest radiograph contains signs of tuberculosis

• Segment the peripheral zone in prostate MRI

We will also touch on calculating features from medical images, visualizing features and results, pattern recognition and scripting. During registration you will be asked if you could bring a laptop for the workshop, as limited PC’s are available at the symposium location.

Michiel Kallenberg

Michiel Kallenberg studied Biomedical Sciences (BSc) and Cognitive Neuroscience (MSc) at the Radboud University Nijmegen. In September 2006 he started his PhD project at the Diagnostic Image Analysis Group in Nijmegen, supervised by Nico Karssemeijer. He is currently working on breast density estimation in mammography. This project is funded by the Dutch Cancer Society and Matakina.

Petra van Houdt

Petra van Houdt studied Biomedical Engineering at Eindhoven University of Technology. She performed her Master’s project at Kempenhaehge (expertise center for epilepsy, sleep medicine, and neurocognition) in Heeze working on an algorithm for the automatic detection of obstructive sleep disordered breathing. In November 2007, she started her PhD project at Kempenhaeghe, but now with a focus on epilepsy. This project is in collaboration with VU Medical Center and University Medical Center of Utrecht. The aim of the project is to optimize and evaluate a relatively new technique, combined EEG and functional MRI. EEG-fMRI could reveal the brain regions that are associated with epileptic activity. We want to use this technique in the preoperative planning of patients who are candidates for epilepsy surgery. This project is funded by the Dutch Epilepsy Foundation. We are currently working on a follow-up study that focuses on the development of more data-driven approaches. This study is part of the Central Nervous System and Imaging (CSI) project that has received funding from the ENIAC Joint Undertaking.

Mitko Veta

Mitko Veta obtained his Diploma Engineer degree in electrical engineering (2008) and Master of Science degree in digital signal processing (2009) at the state university in Skopje, Macedonia. In February 2010 he started work on his PhD project at the Image Sciences Institute, UMC Utrecht, supervised by Josien Pluim. His work involves automatic image analysis of digital breast cancer histopathology slides.

Thessa Kockelkorn

Thessa Kockelkorn obtained her BSc summa cum laude in 2000 at University College Utrecht. She then studied Biomedical Sciences, specializing in Bioinformatics, at Utrecht University and graduated cum laude in 2002. Afterwards, Thessa worked as a researcher at the Tokyo Institute of Psychiatry and the University Medical Center Utrecht, as a health care consultant and as a graphic designer. In May 2008, she started her PhD research at the Image Sciences Institute, focusing on the detection of interstitial lung disease and on interactive lung segmentation in chest CT.

Vikas Gupta

Vikas Gupta graduated with a Bachelor of Engineering degree from Manipal University in 2005. From 2005 to 2006, he worked on cardiovascular image processing platforms at Siemens (India). In 2006, he quit Siemens to pursue further studies as a masters student at School of Chemical and Biomedical Engineering in Nanyang Technological University (Singapore). After finishing his masters studies in August 2008, he started his PhD studentship at the Division of image Processing (LKEB) in the Department of Radiology at Leiden University Medical Center. He is also a member of Computer Vision Lab at Delft University. The topic of his PhD research is multi-modality cardiac image analysis that involves the development of novel algorithms for the analysis and fusion of cardiac imaging data from multiple modalities such as computed tomography, magnetic resonance imaging, and single-photon emission computed tomography.

Ganesh Khedoe

Ganesh Khedoe studied Applied Physics at the Delft University of Technology and graduated from the Quantitative Imaging Group at the Department of Imaging Science and Technology (BSc 2006 and MSc 2007). In 2008 he started his PhD project to enable statistical analysis of Diffusion Tensor Images. The PhD research covers the Estimation of Diffusion Properties in Crossing Fibre Bundles, Regularized Parametric Registration and Template Creation of Diffusion Tensor Images and Statistical Analysis of Diffusion Properties in Clinical Dataseries.

Registration for the symposium is open until the 25th of May. Please indicate if you are able to bring a laptop, as this will make it easier for us to assess how many additional computers need to be provided for the workshop. We thank you for registering and see you in Nijmegen on June 7th!