2008 Winter Project Week:microslicer 3

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The Cingulum Bundle Anchor Tract

Key Investigators

• The Ohio State University: Kishore Mosaliganti, Raghu Machiraju
• Kitware: Brad Davis, Stephen Aylward
• Harvard: Steve Pieper

Objective

We have developed techniques to achieve cell/nuclei segmentations in microscopic images. Often, nuclei and cells appear as overlapping structures and splitting them apart is a non-trivial problem in image analysis. The microscopy modalities of interest include light, confocal and phase-contrast microscopy.

We have also work on characterizing biological micro-structure in terms of micro-components. This helps us to perform tissue segmentations, clonal population segmentation and tracking. Once again, we propose to incorporate such techniques borrowed from material science and spatial statistics into the microscopy image analysis workflows.

The objectives of this project are to port the ITK-based cell segmentation and micro-structure characterization code to Slicer3 framework.

Approach, Plan

Our approach is based upon using image tessellations and micro-structure characterization algorithms widely used in the material science community. These algorithms help us understand biological organization in terms of component packing densities, arrangements and spatial distributions. The algorithms are detailed in the references provided below. Our main purpose at the Project Week is to work with our collaborators in order to define the scope of this project, decide upon the details of the microSlicer framework in Slicer3, and implement our current developed code into the Slicer3 framework.

Progress

June 2007 Project Week

During this Project Week, we did a lot of algorithmic design work, focusing on leveraging optimal or geodesic path information to provide for volumetric segmentations of fiber bundles. Working with Marek Kubicki and the Harvard DBP, we were able to begin the process of applying our algorithm to the full cingulum bundle with new labelmaps and to a new fiber bundle - Arcuate. We have recently achieved significant results in volumetric segmentations using a locally-constrained region-based technique (see the images above).

Jan 2007 Project Half Week

We finished the itkDirectionalIterator which will be needed in the Fast Sweeping implementation. Furthermore, we made progress in porting our Matlab code to ITK.

References

• J. Melonakos, M. Niethammer, V. Mohan, M. Kubicki, J. Miller, A. Tannenbaum. Locally-Constrained Region-Based Methods for DW-MRI Segmentation. Submitted to MMBIA 2007.
• V. Mohan, J. Melonakos, M. Niethammer, M. Kubicki, and A. Tannenbaum. Finsler Level Set Segmentation for Imagery in Oriented Domains. BMVC 2007.
• J. Melonakos, V. Mohan, M. Niethammer, K. Smith, M. Kubicki, and A. Tannenbaum. Finsler Tractography for White Matter Connectivity Analysis of the Cingulum Bundle. MICCAI 2007.
• J. Melonakos, E. Pichon, S. Angenet, and A. Tannenbaum. Finsler Active Contours. IEEE Transactions on Pattern Analysis and Machine Intelligence, to appear in 2007.
• E. Pichon and A. Tannenbaum. Curve segmentation using directional information, relation to pattern detection. In IEEE International Conference on Image Processing (ICIP), volume 2, pages 794-797, 2005.
• E. Pichon, C-F Westin, and A. Tannenbaum. A Hamilton-Jacobi-Bellman approach to high angular resolution diffusion tractography. In International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), pages 180-187, 2005.