Difference between revisions of "DBP1:Harvard"

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= Overview of Harvard PNL DBP 1 =
 
= Overview of Harvard PNL DBP 1 =
  
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<Overview here>
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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.
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For more information about the PNL, please visit the [http://pnl.bwh.harvard.edu| lab website.]
  
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For more introductory information, follow this [[DBP:Harvard|link]].
 
  
 
= Harvard PNL Projects =
 
= Harvard PNL Projects =
  
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{| cellpadding="10"
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{| cellpadding="10" style="text-align:left;"
  
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| style="width:15%" | [[Image:Shapeanalysis-UNC.jpg|200px]]
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| style="width:15%" | [[Image:Shapecaudate.png|200px]]
 
| style="width:85%" |
 
| style="width:85%" |
  
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== [[DBP:Harvard:Collaboration:UNC|Algorithms: Shape Analysis (PNL-UNC)]] ==
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== [[Projects:ShapeAnalysisOfBrainStructures|Shape Analysis of Brain Structures]] ==
  
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Here we write a very brief description of this project.  Notice a representative image is chosen from the project and places in the left column. [[DBP:Harvard:Collaboration:UNC|More...]]
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In this work, we present shape analysis algorithms for brain structures. [[Projects:ShapeAnalysisOfBrainStructures|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> 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.  
  
 
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| | [[Image:Dti-UNC.jpg|200px]]
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| | [[Image:CingulumAllSubjectsFibers.png|200px]]
 
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== [[DBP:Harvard:Collaboration:UNC|Algorithms: Diffusion Tensor Imaging (PNL-UNC)]] ==
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== [[Projects:DTIClustering|DTI Fiber Clustering and Fiber-Based Analysis]] ==
  
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Here we write a very brief description of this project.  Notice a representative image is chosen from the project and places in the left column. [[DBP:Harvard:Collaboration:UNC|More...]]
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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> 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> 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:Dti-MIT.jpg|200px]]
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| | [[Image:Progress_Registration_Segmentation_Shape.jpg|200px]]
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== [[DBP:Harvard:Collaboration:MITDTI|Algorithms: Diffusion Tensor Imaging (PNL-MIT)]] ==  
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== [[Projects:ShapeBasedSegmentationAndRegistration|Shape Based Segmentation and Registration]] ==
  
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Here we write a very brief description of this project. Notice a representative image is chosen from the project and places in the left column. [[DBP:Harvard:Collaboration:MITDTI|More...]]
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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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<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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|-
  
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| | [[Image:Seg-MIT.jpg|200px]]
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| | [[Image:Striatum1.png|200px|]]
 
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== [[DBP:Harvard:Collaboration:MIT|Algorithms: Anatomical Segmentation (PNL-MIT)]] ==
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== [[Projects:RuleBasedStriatumSegmentation|Rule-Based Striatum Segmentation]] ==
  
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Here we write a very brief description of this project.  Notice a representative image is chosen from the project and places in the left column. [[DBP:Harvard:Collaboration:MIT|More...]]
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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> 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> Al-Hakim, et al. Parcellation of the Striatum. SPIE MI 2007.
  
 
|-
 
|-
  
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| | [[Image:Striatum-GAT.jpg|200px]]
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| | [[Image:DTIregistration200.png|200px]]
 
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== [[DBP:Harvard:Collaboration:GTech|Algorithms: Rule-based Segmentation (PNL-GaTech)]] ==  
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== [[Projects:DTIProcessingTools|Diffusion Tensor Image Processing Tools]] ==
  
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Here we write a very brief description of this project.  Notice a representative image is chosen from the project and places in the left column. [[DBP:Harvard:Collaboration:GTech|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> 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> We have recently developed software for eddy current correction.
  
 
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| | [[Image:Placeholder.jpg|200px]]
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== [[DBP:Harvard:Collaboration:Utah|Algorithms: Tensor Based Statistics (PNL-Utah)]] ==
 
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Here we write a very brief description of this project.  Notice a representative image is chosen from the project and places in the left column. [[DBP:Harvard:Collaboration:Utah|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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|-
 
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| | [[Image:Placeholder.jpg|200px]]
 
 
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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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Here we write a very brief description of this project.  Notice a representative image is chosen from the project and places in the left column. [[DBP:Harvard:Collaboration:Slicer|More...]]
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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...]]
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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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| | [[Image:Placeholder.jpg|200px]]
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| | [[Image:Trainingslide.png|200px]]
 
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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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Here we write a very brief description of this project.  Notice a representative image is chosen from the project and places in the left column. [[DBP:Harvard:Collaboration:Training|More...]]
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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...]]
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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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|-
  
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| | [[Image:Placeholder.jpg|200px]]
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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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Here we write a very brief description of this project.  Notice a representative image is chosen from the project and places in the left column. [[DBP:Harvard:Collaboration:Toronto|More...]]
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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...]]
  
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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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|}
  
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|}
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For more introductory information, follow this [[DBP:Harvard|link]].

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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