Difference between revisions of "2011 Summer Project Week Segmentation TBI"

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(Created page with '__NOTOC__ <gallery> Image:PW-MIT2011.png|Projects List Image:notfound.png|Interesting picture to be added... </gallery> '''Full Title of P…')
 
 
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<gallery>
 
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Image:PW-MIT2011.png|[[2011_Summer_Project_Week#Projects|Projects List]]
 
Image:PW-MIT2011.png|[[2011_Summer_Project_Week#Projects|Projects List]]
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Image:notfound.png|Interesting picture to be added...  
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Image:ain1_69-tile_baseline.png | Result of supervised segmentation - acute images
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Image:ain1_69-tile_followup.png | Result of supervised segmentation - follow-up images
 
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<center>
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<gallery widths=120px heights=120px perrow=4 caption="Figure 1. Acute and follow-up images">
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File: Ori_base_Channel1_Slice_69.png| T1 - acute
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File: Ori_base_Channel2_Slice_69.png| T2 - acute
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File: Ori_base_Channel3_Slice_69.png| GRE - acute
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File: Ori_base_Channel4_Slice_69.png| Flair - acute
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File: Ori_follow_Channel1_Slice_69.png | T1 - follow-up
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File: Ori_follow_Channel2_Slice_69.png | T2 - follow-up
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File: Ori_follow_Channel3_Slice_69.png | GRE - follow-up
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File: Ori_follow_Channel4_Slice_69.png | Flair - follow-up
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</center>
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<center>
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<gallery widths=120px heights=120px perrow=5 caption="Figure 2. Supervised segmentation">
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File: Posterior_base_1_class.png | Posterior of WM - acute
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File: Posterior_base_2_class.png | Posterior of GM - acute
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File: Posterior_base_3_class.png | Posterior of CSF - acute
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File: Posterior_base_4_class.png | Posterior of Non-hemorrhagic lesion - acute
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File: Posterior_base_5_class.png | Posterior of Hemorrhagic lesion - acute
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File: Posterior_follow_class_1.png | Posterior of WM - follow-up
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File: Posterior_follow_class_2.png | Posterior of GM - follow-up
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File: Posterior_follow_class_3.png | Posterior of CSF - follow-up
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File: Posterior_follow_class_4.png | Posterior of lesion - follow-up
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'''Full Title of Project'''
 
'''Full Title of Project'''
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<h3>Objective</h3>
 
<h3>Objective</h3>
  
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Traumatic brain injury (TBI) occurs when an external force traumatically injures the brain. TBI is a major cause of death and disability worldwide, especially in children and young adults. TBI affects 1.4 million Americans annually. The UCLA medical school has been working on this topic for years.  
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Traumatic brain injury (TBI) is a driving biological problem (DBP) in NA-MIC. It occurs when an external force traumatically injures the brain. TBI is a major cause of death and disability worldwide, especially in children and young adults.  
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We're working on the supervised segmentation and atlas optimization of longitudinal TBI data.  
  
 
On anatomical MRI scans, to quantitatively analyze the cortical thickness, white matter changes, we need to have a good segmentation on TBI images. However, for TBI data, standard automated image analysis methods are not robust with respect to the TBI-related changes in image contrast, changes in brain shape, cranial fractures, white matter fiber alterations, and other signatures of head injury.  
 
On anatomical MRI scans, to quantitatively analyze the cortical thickness, white matter changes, we need to have a good segmentation on TBI images. However, for TBI data, standard automated image analysis methods are not robust with respect to the TBI-related changes in image contrast, changes in brain shape, cranial fractures, white matter fiber alterations, and other signatures of head injury.  
  
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We will work on an extension of ABC for TBI datasets with the clinical goal to investigate alterations in cortical thickness, subsequent ventricular, and white matter changes in patients with TBI.
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<h3>Approach, Plan</h3>
 
<h3>Approach, Plan</h3>
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ABC (Atlas-Based Classification) is a fully automatic segmentation method developed in Utah. It can process arbitrary number of channels/modalities by co-registration, it integrates brain stripping, bias correction and segmentation into one optimization framework. A brain atlas is used as spatial priors for tissue categories. We want to extend ABC to detect pathology categories, with tests on TBI images. In the first step, we want to add user interaction to the ABC framework.
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Our plan for the project week:
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* Test our preliminary code
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After the project meeting, we will do the following work in the next step.
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* Discuss with collaborators and try to refine the algorithm
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* Explanation of pathology (lesion, bleeding) for helping to design a better algorithm
 
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* Development of semi-automatic supervised ABC module
 
  
 
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<h3>Progress</h3>
 
<h3>Progress</h3>
  
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<!-- Fill this out before Friday's summary presentations - list what you did and how well it worked. -->
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* We applied the preliminary algorithm to current data and fixed some bugs in the code.
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* Our collaborators helped us to validate our current results of supervised segmentation. We got some comments and feedback from our collaborators, which are very important for us to improve the current algorithm.
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* After discussing with Andrei and Micah about the TBI data, we know more clearly about what the clinicians need.
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Latest revision as of 14:30, 24 June 2011

Home < 2011 Summer Project Week Segmentation TBI

  • Result of supervised segmentation - acute images

  • Result of supervised segmentation - follow-up images

  • Figure 1. Acute and follow-up images

  • T1 - acute

  • T2 - acute

  • GRE - acute

  • Flair - acute

  • T1 - follow-up

  • T2 - follow-up

  • GRE - follow-up

  • Flair - follow-up

  • Figure 2. Supervised segmentation

  • Posterior of WM - acute

  • Posterior of GM - acute

  • Posterior of CSF - acute

  • Posterior of Non-hemorrhagic lesion - acute

  • Posterior of Hemorrhagic lesion - acute

  • Posterior of WM - follow-up

  • Posterior of GM - follow-up

  • Posterior of CSF - follow-up

  • Posterior of lesion - follow-up

Full Title of Project

Key Investigators

  • Utah: Bo Wang, Marcel Prastawa, Guido Gerig
  • UCLA: Jack Van Horn, Andrei Irimia, Micah Chambers


Objective

Traumatic brain injury (TBI) is a driving biological problem (DBP) in NA-MIC. It occurs when an external force traumatically injures the brain. TBI is a major cause of death and disability worldwide, especially in children and young adults.

We're working on the supervised segmentation and atlas optimization of longitudinal TBI data.

On anatomical MRI scans, to quantitatively analyze the cortical thickness, white matter changes, we need to have a good segmentation on TBI images. However, for TBI data, standard automated image analysis methods are not robust with respect to the TBI-related changes in image contrast, changes in brain shape, cranial fractures, white matter fiber alterations, and other signatures of head injury.


Approach, Plan

Our plan for the project week:

  • Test our preliminary code
  • Discuss with collaborators and try to refine the algorithm

Progress

  • We applied the preliminary algorithm to current data and fixed some bugs in the code.
  • Our collaborators helped us to validate our current results of supervised segmentation. We got some comments and feedback from our collaborators, which are very important for us to improve the current algorithm.
  • After discussing with Andrei and Micah about the TBI data, we know more clearly about what the clinicians need.


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