MCBR-CDS'09

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 five 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, we will provide access to the medical databases and tasks of ImageCLEF 2009 which has obtained rights from RSNA to use over 70,000 images of the journals Radiology and Radiographics.

Topics of interests include but are not limited to:

Mining of multimodal medical data (X-ray, MRI, CT, echo videos, time series data)
Machine learning of disease correlations from mining 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
Practical applications of clinical decision support using multimodal data retrieval or analysis
Algorithms for medical image retrieval or classification using the ImageCLEF collection

Paper Formatting: Papers are limited to eight pages. Please use the MICCAI author kit to format the papers. The workshop chairs reserve the right to reject papers violating the paper length and the formatting instructions outright, without review.

Blind Review: MCBR-CDS reviewing is double blind: authors do not know the names of the reviewers of their papers, and reviewers do not know the names of the authors. Please see the author kit for detailed explanations of how to ensure this.

Submission: MCBR-CDS is using an online submission system. Participants who would like to obtain the ImageCLEF data set would need to register for CLEF at http://www.clef-campaign.org. More on the data set is also available on the ImageCLEF web pages if needed.

Supplemental Material: Supplemental material submission is optional. This material may include: videos of results that cannot be included in the main paper, anonymized related submissions to other conferences and journals, and appendices or technical reports containing extended proofs and mathematical derivations that are not essential for understanding of the paper. Contents of the supplemental material should be referred to appropriately in the paper and that reviewers are not obliged to look at it. For further details refer to MICCAI author guidelines.

Camera-ready Submission: Please follow the instructions from the MICCAI website to prepare your final submission. Each author needs to upload a zip file including the following material: 1. copyright form ; 2. pdf of the camera ready; 3. source files of the camera ready, namely the .tex file plus all style files, special fonts, .eps, .bib etc.

8:45am - 9:00am Opening Remarks

9:00am - 11:00am Oral Session 1: Medical Image Retrieval

Introducing space and time in local feature-based endomicroscopic image retrieval,
Barbara ANDRE*(MKT, France), Tom Vercauteren (MKT, France), Aymeric Perchant (MKT, France), Anna Buchner (Mayo Clinic), Michael Wallace (Mayo Clinic), and Nicholas Ayache (INRIA, France)
A Query-by-Example Content-Based Image Retrieval System of Non-Melanoma Skin Lesions,
Lucia Ballerini*, Robert Fisher, and Jonathan Rees (Univ. of Edinburgh)
3D Case-Based Retrieval for Interstitial Lung Diseases,
Adrien Depeursinge*(Univ. Hospitals of Geneva), Alejandro Vargas, Alexandra Platon, Antoine Geissbuhler, Pierre-Alexandre Poletti, and Henning Muller (Univ. Hospitals & Univ. of Geneva)
Image Retrieval for Alzheimer's Disease Detection,
Mayank Agarwal*, and Javed Mostafa (UNC Chapel Hill)

11:00am-11:20am Coffee Break

11:20am-12:10pm Invited Talk: Prof. Dimitris N. Metaxas , Rutgers University

12:10pm-1:45pm Lunch

1:45pm-3:15pm Oral Session 2: Clinical Decision Making

Statistical Analysis of Gait Data to Assist Clinical Decision Making,
Nigar SEN KÖKTAS*(CANKAYA UNIVERSITY), and Robert R.P.W DUIN (Delft University of Technology)
Using BI-RADS Descriptors and Ensemble Learning for Classifying Masses in Mammograms,
Yu Zhang*, Noriko Tomuro, Jacob Furst, and Daniela Stan Raicu (DePaul University)
Robust Learning based Annotation of Medical Radiographs,
Yimo Tao (Virginia Tech.), Zhigang Peng (Siemens Healthcare), Bing Jian (Siemens Healthcare), Jianhua Xuan (Virginia Tech.), Arun Krishnan (Siemens Healthcare), Xiang Sean Zhou*(Siemens Healthcare)

3:15pm-3:30pm Coffee Break

3:30pm-4:20pm Invited Talk: Dr. Scott Adelman, Kaiser Permanente Healthcare

4:20pm -5:50pm Oral Session 3: Multimodal Fusion

Knowledge-based discrimination in Alzheimer's disease,
Simon Duchesne* (CRULRG), Burt Cr¨¦peaut (Universit¨¦ Laval), Giovanni Frisoni (IRCCS Fatebenefratelli di Dio)
Automatic annotation of X-ray images: A study on attribute selection,
Devrim Unay*, Octavian Soldea, Ahmet Ekin, Mujdat Cetin, and Aytul Ercill (Sabanci University)
Multi-Modal Query Expansion Based on Local Analysis for Medical Image Retrieval,
Mahmudur Rahman* (NIH)

General chairs

Tanveer Syeda-Mahmood, IBM Almaden Research Center, USA.

James Duncan, Yale University, USA.

Program chairs

Henning Müller, Univ. Hospitals & Univ. of Geneva, Switzerland.

Fei Wang, IBM Almaden Research Center, USA.

Publicity chair

Jayashree Kalpathy-Cramer , Oregon Health and Science University, USA

Media chairs

Barbara Caputo, Idiap Research Institute, Centre du Parc, Switzerland

Program Committee

Amir Amini, Univ. of Louisville, USA

Barbara Andre, INRIA, France

Sameer Antani, National Library of Medicine, USA

Nicholas Ayache, INRIA, France

David Beymer, IBM Almaden Research Center, USA

Albert Chung, Hong Kong University of Sc. and Tech.

Dorin Comaniciu, SIEMENS, USA

Alejandro F. Frangi, Universitat Pompeu Fabra, Spain

Guido Gerig, UNC, USA

Hayit Greenspan, Tel Aviv University, Israel

Ghassan Hamarneh, Simon Fraser University, Canada

Nico Karssemeijer, Radboud Univ. Nijmegen,The Netherlands

Ron Kikinis, M.D. Harvard, USA

Richard Leahy, USC, USA

Yanxi Liu, UPENN, USA

Martin London, M.D. UCSF, USA

Peter Macfarlane, Univ. of Glasgow, UK

Sandy Napel, Stanford University, USA

Daniel Racoceanu, National University of Singapore, Singapore

Linda Shapiro, University of Washington, USA

Milan Sonka, Univ. of Iowa, USA

Hemant Tagare, Yale, USA

Chris Taylor, Univ. of Manchester, UK

Russ Taylor, JHU, USA

Joe Terdiman, M.D. Kaiser Permanente Division of Research, USA

Tatiana Tommasi, IDIAP Research Institute, Switzerland

Agma Traina, Sao Paulo University, Brazil

Max Viergewer, Utrecht University, The Netherlands

Pingkun Yan, Philips Research, USA