Difference between revisions of "Project Week/Template"

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__NOTOC__
 
__NOTOC__
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= Spine Segmentation & Osteoporosis Detection In CT Imaging Studies =
 
<gallery>
 
<gallery>
 
Image:PW-MIT2013.png|[[2013_Summer_Project_Week#Projects|Projects List]]
 
Image:PW-MIT2013.png|[[2013_Summer_Project_Week#Projects|Projects List]]
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Image:genuFAp.jpg|Scatter plot of the original FA data through the genu of the corpus callosum of a normal brain.
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Image:spine.png|CT Spine
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Image:genuFA.jpg|Regression of FA data; solid line represents the mean and dotted lines the standard deviation.
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Image:SegmentedSpine.png|Automated Segmentation
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Image:Radnostics64-3.png|Osteoporosis Detection
 
</gallery>
 
</gallery>
  
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==Instructions for Use of this Template==
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<b>Osteoporosis</b>
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#Please create a new wiki page with an appropriate title for your project using the convention 2013_Summer_Project_Week:<Project Name>
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#Copy the entire text of this page into the page created above
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A condition of bone mineral loss affecting the aging population
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#Link the created page into the list of projects for the project event
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* Impacts 200 million people WW
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#Delete this section from the created page
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* Leads to 9 million fractures each year
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#Send an email to tkapur at bwh.harvard.edu if you are stuck
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* Inflicts pain, morbidity, and mortality
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* Direct annual costs: close to $20 billion in the US, €30+ billion in Europe
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* Fractures and complications are preventable with lifestyle changes, diet, and medication
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* However, <b>Osteoporosis is largely underdiagnosed</b>
  
 
==Key Investigators==
 
==Key Investigators==
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* UNC: Isabelle Corouge, Casey Goodlett, Guido Gerig
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* Radnostics: Anthony Blumfield
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* Utah: Tom Fletcher, Ross Whitaker
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* Albert Einstein College of Medicine: Einat Blumfield, MD
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* Jacobi Medical Center: Jay Leb, MD
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* BWH: Ron Kikinis, MD
  
 
<div style="margin: 20px;">
 
<div style="margin: 20px;">
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<h3>Objective</h3>
 
<h3>Objective</h3>
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We are developing methods for analyzing diffusion tensor data along fiber tracts. The goal is to be able to make statistical group comparisons with fiber tracts as a common reference frame for comparison.
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Radnostics Osteoporosis Detection is a solution for early detection of osteoporosis in CT scans performed for other clinical indications
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*Tens of millions of CT scans are performed annually for various medical conditions
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*We measure osteoporosis biomarkers and detect patients at risk
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*100% automated & integrated into the clinical workflow
  
  
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<h3>Approach, Plan</h3>
 
<h3>Approach, Plan</h3>
  
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Our approach for analyzing diffusion tensors is summarized in the IPMI 2007 reference below.  The main challenge to this approach is <foo>.
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Create a 3D Slicer v4 command line module for Radnostics Beta2.
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Our plan for the project week is to first try out <bar>,...
 
  
 
</div>
 
</div>
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<h3>Progress</h3>
 
<h3>Progress</h3>
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Software for the fiber tracking and statistical analysis along the tracts has been implemented. The statistical methods for diffusion tensors are implemented as ITK code as part of the [[NA-MIC/Projects/Diffusion_Image_Analysis/DTI_Software_and_Algorithm_Infrastructure|DTI Software Infrastructure]] project. The methods have been validated on a repeated scan of a healthy individual. This work has been published as a conference paper (MICCAI 2005) and a journal version (MEDIA 2006). Our recent IPMI 2007 paper includes a nonparametric regression method for analyzing data along a fiber tract.
 
  
  
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==Delivery Mechanism==
 
==Delivery Mechanism==
  
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This work will be delivered to the NA-MIC Kit as a (please select the appropriate options by noting YES against them below)
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This work will be delivered to the NA-MIC Kit as a
  
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#ITK Module
 
 
#Slicer Module
 
#Slicer Module
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##Built-in
 
 
##Extension -- commandline
 
##Extension -- commandline
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##Extension -- loadable
 
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#Other (Please specify)
 
  
 
==References==
 
==References==
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*Fletcher P, Tao R, Jeong W, Whitaker R. [http://www.na-mic.org/publications/item/view/634 A volumetric approach to quantifying region-to-region white matter connectivity in diffusion tensor MRI.] Inf Process Med Imaging. 2007;20:346-358. PMID: 17633712.
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*http://wiki.na-mic.org/Wiki/index.php/2011-Challenge:Segment-a-spine
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* Corouge I, Fletcher P, Joshi S, Gouttard S, Gerig G. [http://www.na-mic.org/publications/item/view/292 Fiber tract-oriented statistics for quantitative diffusion tensor MRI analysis.] Med Image Anal. 2006 Oct;10(5):786-98. PMID: 16926104.
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*http://www.radnostics.com
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* Corouge I, Fletcher P, Joshi S, Gilmore J, Gerig G. [http://www.na-mic.org/publications/item/view/1122 Fiber tract-oriented statistics for quantitative diffusion tensor MRI analysis.] Int Conf Med Image Comput Comput Assist Interv. 2005;8(Pt 1):131-9. PMID: 16685838.
 
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* Goodlett C, Corouge I, Jomier M, Gerig G, A Quantitative DTI Fiber Tract Analysis Suite, The Insight Journal, vol. ISC/NAMIC/ MICCAI Workshop on Open-Source Software, 2005, Online publication: http://hdl.handle.net/1926/39 .
 

Revision as of 21:35, 11 June 2013

Home < Project Week < Template

Spine Segmentation & Osteoporosis Detection In CT Imaging Studies

  • CT Spine

  • Automated Segmentation

  • Osteoporosis Detection

Osteoporosis

A condition of bone mineral loss affecting the aging population

  • Impacts 200 million people WW
  • Leads to 9 million fractures each year
  • Inflicts pain, morbidity, and mortality
  • Direct annual costs: close to $20 billion in the US, €30+ billion in Europe
  • Fractures and complications are preventable with lifestyle changes, diet, and medication
  • However, Osteoporosis is largely underdiagnosed

Key Investigators

  • Radnostics: Anthony Blumfield
  • Albert Einstein College of Medicine: Einat Blumfield, MD
  • Jacobi Medical Center: Jay Leb, MD
  • BWH: Ron Kikinis, MD

Objective

Radnostics Osteoporosis Detection is a solution for early detection of osteoporosis in CT scans performed for other clinical indications

  • Tens of millions of CT scans are performed annually for various medical conditions
  • We measure osteoporosis biomarkers and detect patients at risk
  • 100% automated & integrated into the clinical workflow


Approach, Plan

Create a 3D Slicer v4 command line module for Radnostics Beta2.

Progress


Delivery Mechanism

This work will be delivered to the NA-MIC Kit as a

  1. Slicer Module
    1. Extension -- commandline

References

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