1 / 12

Robust Cerebrum and Cerebellum Segmentation for Neuroimage Analysis

Robust Cerebrum and Cerebellum Segmentation for Neuroimage Analysis. Jerry L. Prince, Aaron Carass, Lotta Ellingsen, and Min Chen Johns Hopkins University Ron Kikinis and Nicole Aucoin Brigham and Women’s Hospital.

trevor
Download Presentation

Robust Cerebrum and Cerebellum Segmentation for Neuroimage Analysis

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Robust Cerebrum and Cerebellum Segmentation for Neuroimage Analysis Jerry L. Prince, Aaron Carass, Lotta Ellingsen, and Min Chen Johns Hopkins University Ron Kikinis and Nicole Aucoin Brigham and Women’s Hospital National Institute on Biomedical Imaging and Bioengineering 1 R21 EB009900-01

  2. “Skull Stripping” • Isolate the brain in MR images • Existing algorithms yield inconsistent results •  human rater is still gold standard • SPECTRE is a “hybrid” technique (top-down and bottom-up) that preserves cortical gray matter and yields high Dice coefficients Typical SPECTRE result SPECTRE Result on patient

  3. Features • Do not be overly aggressive: • affects quantification (thickness) of cortical gray matter • affects determination of pial layer • Provide added flexibility: • separate hemispheres, cerebrum, cerebellum and brain stem • Rigorously validate: • evaluate on thousands of highly varied data sets • compare with existing algorithms Manual Result Some cortex is “stripped” away

  4. Project Overview Goal: Develop and augment the SPECTRE algorithm as a module within the NA-MIC Kit software environment—e.g., 3DSlicer. (Funded NIBIB R21) SPECTRE = Simple Paradigm for Extra Cerebral Tissue REmoval Specific aims: • Rewrite SPECTRE using the Free Open Source Software Development Methodology of NA-MIC. [Hopkins, BWH, Mostly Year 1]* • Complete the algorithms necessary for isolating and establishing a coordinate system on the cerebellum. [Hopkins, Years 1 and 2] • Parameters will be optimized in order for SPECTRE to perform well with a variety of differently acquired data. [Hopkins, Years 1 and 2] • Compare SPECTRE against all available publicly available (source or binary) skullstripping software. [Hopkins, BWH, Mostly Year 2] *Or: Make SPECTRE a module within 3DSlicer

  5. SPECTRE Basics • A watershed principle is at the core of SPECTRE • Works according to intensity ordering of WM, GM, CSF in MR images • Initial masks are found by multiple atlas registration • cerebrum, cerebellum, brain stem, and whole brain • classification, morphology, topology, and watershed algorithms are then applied • sanity checks are applied

  6. History and Status • SPECTRE was originally implemented in C/C++ • ISBI conference paper in 2007 • SPECTRE was ported to JAVA in order to operate within the Java Image Science Toolkit (JIST environment) • JIST is an open source pipeline and medical image processing environment: http://www.nitrc.org/projects/jist/ • Further development and testing has been carried out on the Java code within JIST • a journal paper is in the final preparation stage

  7. Algorithm Progress • Cerebellum isolation • Hemisphere separation

  8. Performance Evaluation • Data sets and results • 25 older subjects, cerebrum, two raters • 3 subjects, repeat scans • 1046 scans, older subjects, cerebrum, one rater Worst result

  9. What is JIST? • It is a visual interface, pipeline tool, and collection of 3D image analysis modules • It works in concert with MIPAV • Modules can run from a command line interface • Java  platform independent • Designed for large-scale runs

  10. Early Integration Status • Java SPECTRE requires Java Runtime environment (JRE) and JIST and MIPAV •  3DSlicer is being extended to load JRE [BWH] •  SPECTRE and libraries are being rolled up in a comprehensive JAR file [JHU] • The SPECTRE module is described by an XML file that is scanned by 3DSlicer and incorporated as a command line module •  XML descriptor is being written [JHU]

  11. SPECTRE 2009 • Creation of SPECTRE 2009 graphical interface in 3DSlicer is automatic • Required JIST CLI mods • Done this week, shown in right • Limitations • no shared memory between SPECTRE and 3DSlicer • memory requirements overall are large: 1-1.5GB for SPECTRE • Benefits • Mechanism permits other modules to become available to 3DSlicer • Future SPECTRE development works in JIST, MIPAV, and NA-MIC

  12. Future Work • Release initial version as 3DSlicer plugin • Complete CLI support for JIST/Java in 3DSlicer • Fix Windows Java problem • Incorporate MGDM for joint cerebrum, cerebellum, and brainstem isolation • Validate MGDM in Java • Augment OASIS atlases with additional labels • Carry out extensive validations • cerebellum, 20 subject repeat scans, tumor cases • Optimize SPECTRE speed, flexibility, visualization interactivity

More Related