MCBR-CDS 2011: Medical Content-based Retrieval for Clinical Decision Support

Call for papers

Diagnostic decision making (using images and other clinical data) is still very much an art for many physicians in their practices today due to a lack of quantitative tools and measurements. Traditionally, decision making has involved using evidence provided by the patient's data coupled with a physician's a priori experience of a limited number of similar cases. With advances in electronic patient record systems, a large number of pre-diagnosed patient data sets are now becoming available. These datasets are often multimodal consisting of images (x-ray, CT, MRI), videos and other time series, and textual data (free text reports and structured clinical data). Analyzing these multimodal sources for disease-specific information across patients can reveal important similarities between patients and hence their underlying diseases and potential treatments. Researchers are now beginning to use techniques of content-based retrieval to search for disease-specific information in modalities to find supporting evidence for a disease or to automatically learn associations of symptoms and diseases. Benchmarking frameworks such as ImageCLEF (Image retrieval track in the Cross-Language Evaluation Forum) have expanded over the past eight years to include large medical image collections for testing various algorithms for medical image retrieval. This has made comparisons of several techniques for visual, textual, and mixed medical information retrieval as well as for visual classification of medical data possible based on the same data and tasks.

The goal of this workshop is to bring together researchers in medical imaging, medical image retrieval, data mining, text retrieval, and machine learning/AI communities to discuss new techniques of multimodal mining/retrieval and their use in clinical decision support. We are looking for original, high-quality submissions that address innovative research and development in the analysis, search and retrieval of multimodal medical data for use in clinical decision support. Further, to encourage a larger group of image analysis researchers to profit from the databases and evaluations created in the context of ImageCLEF, groups can get access to ImageCLEF 2011 images of the biomedical literature when registering.

Topics of interests include but are not limited to:

  • Image analysis of multimodal medical data (X-ray, MRI, CT, echo videos, time series data)
  • Machine learning of disease correlations in multimodal data
  • Algorithms for indexing and retrieval of data from multimodal medical databases
  • Disease model-building and clinical decision support systems based on multimodal analysis
  • Algorithms for medical image retrieval or classification
  • Systems of retrieval or classification using the ImageCLEF collection

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Posted on 29/03/2011