Difference between revisions of "DBP1:Harvard"

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= Harvard PNL Projects =
 
= Harvard PNL Projects =
  
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== [[DBP:Harvard:Collaboration:MITDTI|Algorithms: Diffusion Tensor Imaging (PNL-MIT)]] ==  
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== [[Projects:DTIClustering|DTI Fiber Clustering and Fiber-Based Analysis]] ==
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This collaboration focuses on the analysis of diffusion tensor images of the brain, including clustering analysis of fiber tractography. [[DBP:Harvard:Collaboration:MITDTI|More...]]
 
  
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<font color="red">'''New: '''</font> Here we give something new and exciting about the project. The most recent publication on this project is very appropriate for this slot.
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The goal of this project is to provide structural description of the white matter architecture as a partition into coherent fiber bundles and clusters, and to use these bundles for quantitative measurement. [[Projects:DTIClustering|More...]]
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<font color="red">'''New:'''</font> Monica E. Lemmond, Lauren J. O'Donnell, Stephen Whalen, Alexandra J. Golby. Characterizing Diffusion Along White Matter Tracts Affected by Primary Brain Tumors. Accepted to HBM 2007.
  
 
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| | [[Image:Seg-MIT.jpg|200px]]
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| | [[Image:Progress_Registration_Segmentation_Shape.jpg|200px]]
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== [[Projects:ShapeBasedSegmentationAndRegistration|Shape Based Segmentation and Registration]] ==
  
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== [[DBP:Harvard:Collaboration:MIT|Algorithms: Anatomical Segmentation (PNL-MIT)]] ==
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This type of algorithm assigns a tissue type to each voxel in the volume. Incorporating prior shape information biases the label assignment towards contiguous regions that are consistent with the shape model. [[Projects:ShapeBasedSegmentationAndRegistration|More...]]
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Research in this area produces algorithms used to segment medical images, for example separating the brain into separate tissue classes and neuroanatomical structures. [[DBP:Harvard:Collaboration:MIT|More...]]
 
  
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<font color="red">'''New: '''</font> Here we give something new and exciting about the project. The most recent publication on this project is very appropriate for this slot.
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<font color="red">'''New: '''</font> K.M. Pohl, J. Fisher, S. Bouix, M. Shenton, R. W. McCarley, W.E.L. Grimson, R. Kikinis, and W.M. Wells. Using the Logarithm of Odds to Define a Vector Space on Probabilistic Atlases. Medical Image Analysis,11(6), pp. 465-477, 2007. <b>Best Paper Award MICCAI 2006 </b>
  
 
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| | [[Image:Striatum1.png|200px|]]
 
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== [[DBP:Harvard:Collaboration:GTech|Algorithms: Rule-based Segmentation (PNL-GaTech)]] ==  
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== [[Projects:RuleBasedStriatumSegmentation|Rule-Based Striatum Segmentation]] ==
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This project has produced a method for semi-automated parcellation of brain structures, including the dorsolateral prefrontal cortex and the basal ganglia of the human brain. [[DBP:Harvard:Collaboration:GTech|More...]]
 
  
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<font color="red">'''New: '''</font> Here we give something new and exciting about the project. The most recent publication on this project is very appropriate for this slot.
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In this work, we provide software to semi-automate the implementation of segmentation procedures based on expert neuroanatomist rules for the striatum. [[Projects:RuleBasedStriatumSegmentation|More...]]
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<font color="red">'''New: '''</font> Al-Hakim, et al. Parcellation of the Striatum. SPIE MI 2007.
  
 
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| | [[Image:DTIregistration200.png|200px]]
 
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== [[DBP:Harvard:Collaboration:Utah|Algorithms: Tensor Based Statistics (PNL-Utah)]] ==
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== [[Projects:DTIProcessingTools|Diffusion Tensor Image Processing Tools]] ==
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This collaboration has focused on improving the measurement of diffusion tensors and comparison between diagnostic groups. [[DBP:Harvard:Collaboration:Utah|More...]]
 
  
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We implement the diffusion weighted image (DWI) registration model from the paper of G.K.Rohde et al. Patient head motion and eddy currents distortion cause artifacts in maps of diffusion parameters computer from DWI. This model corrects these two distortions at the same time including brightness correction.
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<font color="red">'''New: '''</font> We have recently developed software for eddy current correction.
  
 
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== [[DBP:Harvard:Collaboration:Slicer|Engineering: Slicer Improvement and Testing]] ==
 
== [[DBP:Harvard:Collaboration:Slicer|Engineering: Slicer Improvement and Testing]] ==
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This ongoing work conducts testing and development of new features in Slicer and provides a bridge between developers and researchers using the software. [[DBP:Harvard:Collaboration:Slicer|More...]]
 
This ongoing work conducts testing and development of new features in Slicer and provides a bridge between developers and researchers using the software. [[DBP:Harvard:Collaboration:Slicer|More...]]
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== [[DBP:Harvard:Collaboration:Training|Training: Training Material and Expert Users Feedback]] ==
 
== [[DBP:Harvard:Collaboration:Training|Training: Training Material and Expert Users Feedback]] ==
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Work in this area has created training materials for Slicer software with the input of expert users. [[DBP:Harvard:Collaboration:Training|More...]]
 
Work in this area has created training materials for Slicer software with the input of expert users. [[DBP:Harvard:Collaboration:Training|More...]]
  
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== [[DBP:Harvard:Collaboration:Toronto|Biology: Genetics and Imaging (Toronto)]] ==
 
== [[DBP:Harvard:Collaboration:Toronto|Biology: Genetics and Imaging (Toronto)]] ==
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This collaboration is centered around a study of psychosis in schizophrenia and bipolar disorder, using a combination of genetics and diffusion tensor imaging. [[DBP:Harvard:Collaboration:Toronto|More...]]
 
This collaboration is centered around a study of psychosis in schizophrenia and bipolar disorder, using a combination of genetics and diffusion tensor imaging. [[DBP:Harvard:Collaboration:Toronto|More...]]
  

Latest revision as of 19:06, 11 July 2009

Home < DBP1:Harvard
Back to NA-MIC DBP 1

Overview of Harvard PNL DBP 1

The Harvard Driving Biological Project uses structural MRI, diffusion-weighted MRI, and fMRI to study the neural bases of schizophrenia and related psychiatric disorders. The DBP is centered in the Psychiatry Neuroimaging Laboratory (PNL) at Brigham and Women's Hospital in Boston, MA.

For more information about the PNL, please visit the lab website.


Harvard PNL Projects

Shapecaudate.png

Shape Analysis of Brain Structures

In this work, we present shape analysis algorithms for brain structures. More...

New: G Gerig, S Joshi, T Fletcher, K Gorczowski, S Xu, S M. Pizer, M Styner: Statistics of populations of images and its embedded objects: Driving applications in neuroimaging, IEEE Symposium on Biomedical Imaging ISBI 2006.

CingulumAllSubjectsFibers.png

DTI Fiber Clustering and Fiber-Based Analysis

The goal of this project is to provide structural description of the white matter architecture as a partition into coherent fiber bundles and clusters, and to use these bundles for quantitative measurement. More...

New: Monica E. Lemmond, Lauren J. O'Donnell, Stephen Whalen, Alexandra J. Golby. Characterizing Diffusion Along White Matter Tracts Affected by Primary Brain Tumors. Accepted to HBM 2007.

Progress Registration Segmentation Shape.jpg

Shape Based Segmentation and Registration

This type of algorithm assigns a tissue type to each voxel in the volume. Incorporating prior shape information biases the label assignment towards contiguous regions that are consistent with the shape model. More...

New: K.M. Pohl, J. Fisher, S. Bouix, M. Shenton, R. W. McCarley, W.E.L. Grimson, R. Kikinis, and W.M. Wells. Using the Logarithm of Odds to Define a Vector Space on Probabilistic Atlases. Medical Image Analysis,11(6), pp. 465-477, 2007. Best Paper Award MICCAI 2006

Striatum1.png

Rule-Based Striatum Segmentation

In this work, we provide software to semi-automate the implementation of segmentation procedures based on expert neuroanatomist rules for the striatum. More...

New: Al-Hakim, et al. Parcellation of the Striatum. SPIE MI 2007.

DTIregistration200.png

Diffusion Tensor Image Processing Tools

We implement the diffusion weighted image (DWI) registration model from the paper of G.K.Rohde et al. Patient head motion and eddy currents distortion cause artifacts in maps of diffusion parameters computer from DWI. This model corrects these two distortions at the same time including brightness correction.

New: We have recently developed software for eddy current correction.

Engineering: Slicer Improvement and Testing

This ongoing work conducts testing and development of new features in Slicer and provides a bridge between developers and researchers using the software. More...

Trainingslide.png

Training: Training Material and Expert Users Feedback

Work in this area has created training materials for Slicer software with the input of expert users. More...

Biology: Genetics and Imaging (Toronto)

This collaboration is centered around a study of psychosis in schizophrenia and bipolar disorder, using a combination of genetics and diffusion tensor imaging. More...

For more introductory information, follow this link.

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