<div class="gmail_quote"><br>Dear Researchers,<br><br>***** Apologies for multiple postings ******<br><br>We are pleased to announce that we are organizing a tutorial<br>on: "Shape Models for Biomedical Image Segmentation" in conjunction with MICCAI 2011 on September 18, 2011 at Toronto, Canada.<br>
<br>Shape models have recently attracted much attention due to their successful role in many medical image segmentation tasks. Many of the most successful automatic segmentation algorithms evaluated during the previous MICCAI Grand Challenge competitions made effective use of shape models to provide prior knowledge for these various segmentation tasks. An increasingly wider range of methodologies have emerged for the construction, representation, and application of these shape models. Often, the shape models are only briefly presented in the context of specific segmentation algorithms. A thorough, detailed discussion focusing upon shape model construction and its uses is often missing.<br>
<br>The goal of this tutorial is to address shape models for segmentation and to provide a unified framework for in-depth discussion of the construction and application of shape models in medical image segmentation. The tutorial will review different methodologies for the use of shape models in medical image segmentation algorithms. The main focus will be on describing different approaches to building shape models that are used as prior knowledge for image segmentation algorithms and the different techniques to use these models for segmentation. The tutorial will consist of three main themes: 1) Recent clinical applications that require segmentation as a pre-requisite, 2) Mesh and Image based atlas construction methodologies, and; 3) Integration of shape-models into image segmentation algorithms.<br>
<br><br>Invited speakers:<br>Dr. Tobias Heimann, Dr. Olivier Commowick, and Prof. Daniel Cremers.<br><br><br>For more information, please go to <a href="http://crl.med.harvard.edu/research/MICCAI_Tutorial/index.php" target="_blank">http://crl.med.harvard.edu/research/MICCAI_Tutorial/index.php</a><br>
<br><br>Registration:<br>MICCAI'2011 registration website: <a href="http://www.miccai2011.org/registration" target="_blank">http://www.miccai2011.org/registration</a><br><br>Best regards:<br><br>Moti Freiman, Simon Warfield and Leo Joskowicz<br>
<br>-------------<br><br><br>Program (details at <a href="http://crl.med.harvard.edu/research/MICCAI_Tutorial/index.php" target="_blank">http://crl.med.harvard.edu/research/MICCAI_Tutorial/index.php</a> )<br><br>Part 1: Introduction - clinical applications<br>
9:00-9:30: Introduction, Recent clinical advances and new applications for medical image segmentation (L.J.).<br><br>Part 2: Mesh and Image based atlas construction methodologies<br>9:30-10:45: Mesh-based atlas construction methodologies (T.H.).<br>
10:45-11:15: Coffee break.<br>11:45-13:00: Methodologies for inferring a shape model from multiple template images (S.W.). <br>13:00-14:00: Lunch break<br>14:00-15:15: Registration and template selection strategies (O.C.). <br>
15:15-15:45: Coffee break<br><br>Part 3: Segmentation techniques with shape priors<br>15:45-16:45: Shape prior integration in discrete optimization segmentation algorithms (M. F.).<br>16:45-17:45: Algorithmic solutions for shape priors in image segmentation (D.C.). <br>
17:45-18:00: Questions, discussion, and concluding remarks.<br><br><br><br><br><br>
</div><br><br clear="all"><br>-- <br>__<br>Moti Freiman, Ph.D.<br>Postdoctoral Associate, Harvard Medical School.<br>Research Fellow, Computational Radiology Laboratory.<br>Dept. of Radiology, Children's hospital,<br>
300 Longwood Ave. Boston, MA 02115.<br>Tel: +1 617-355-2755<br>Fax: +1 617-730-4644 <br>Lab website: <a href="http://crl.med.harvard.edu/" target="_blank">http://crl.med.harvard.edu</a><br><br><br><br><br>