Difference between revisions of "2016 Winter Project Week/Projects/BatchImageAnalysis"
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| + | [[File:LungCT-3DSIFT.png|200px|thumb|left|3D SIFT Lung Features]] | ||
==Key Investigators== | ==Key Investigators== | ||
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* Kalli Retzepi (MGH) | * Kalli Retzepi (MGH) | ||
* Yangming Ou (MGH) | * Yangming Ou (MGH) | ||
| − | * Matt Toews ( | + | * Matt Toews (ETS) |
| + | * Lilla Zollei (MGH) | ||
| + | * Lauren O'Donnell (BWH) | ||
* Steve Pieper (BWH) | * Steve Pieper (BWH) | ||
* Sandy Wells (BWH) | * Sandy Wells (BWH) | ||
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==Project Description== | ==Project Description== | ||
{| class="wikitable" | {| class="wikitable" | ||
| + | ! style="text-align: left; width:27%" | Objective | ||
| + | ! style="text-align: left; width:27%" | Approach and Plan | ||
| + | ! style="text-align: left; width:27%" | Progress and Next Steps | ||
|- style="vertical-align:top;" | |- style="vertical-align:top;" | ||
| − | ! | + | | |
| + | <!-- Objective bullet points --> | ||
| + | * Run feature detection code over a collection of medical images pulled from PACS | ||
| + | * Investigate a collection of ADC maps of neonates (diffusion MR) | ||
| + | * Patients labeled with age and health status (normal, mildly abnormal, severely abnormal) | ||
| + | * Use 3D SIFT code to see if health status can be detected in images | ||
| + | * (if time) try text analysis of radiology reports | ||
| + | | | ||
<!-- Add a bulleted list of key points --> | <!-- Add a bulleted list of key points --> | ||
| − | * | + | * Use deidentified cohort of neonate images collected from MGH |
| + | * Install data and software on AWS, try StarCluster | ||
| + | * Explore visualization options | ||
| + | * (if time) integrate image features with analysis of radiology report text | ||
| + | | | ||
| + | <!-- Fill this out at the end of Project Week; describe what you did this week and what you plan to do next --> | ||
| + | |||
| + | Algorithm | ||
| + | |||
| + | * feature extraction (20 seconds per image) | ||
| + | |||
| + | * Feature matching O(log N) indexing (< 1 second per image) | ||
| + | |||
| + | * 3D SIFT-Rank code (Windows, Linux, Max) and read me | ||
| + | http://www.matthewtoews.com/fba/featExtract1.5.zip | ||
| + | |||
| + | Result | ||
| + | Baseline HIE classification rate: 73%, leave-one-out moderate vs normal. | ||
| − | |||
| − | |||
| − | |||
| − | + | Data | |
| − | + | 231 subjects, Apparent Diffusion Coefficient (ADC) images. | |
| − | |||
|} | |} | ||
| − | == | + | ==Features Extracted in ADC MRI Volume == |
| − | + | ||
| + | http://wiki.na-mic.org/Wiki/images/b/b2/Image_%282%29.png | ||
Latest revision as of 15:54, 8 January 2016
Home < 2016 Winter Project Week < Projects < BatchImageAnalysis
Key Investigators
- Kalli Retzepi (MGH)
- Yangming Ou (MGH)
- Matt Toews (ETS)
- Lilla Zollei (MGH)
- Lauren O'Donnell (BWH)
- Steve Pieper (BWH)
- Sandy Wells (BWH)
- Randy Gollub (MGH)
Project Description
| Objective | Approach and Plan | Progress and Next Steps |
|---|---|---|
|
|
Algorithm
http://www.matthewtoews.com/fba/featExtract1.5.zip Result Baseline HIE classification rate: 73%, leave-one-out moderate vs normal.
|
Features Extracted in ADC MRI Volume
