Difference between revisions of "2014 Summer Project Week:Cardiac-Congenital"
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Image:PW-MIT2014.png|[[2014_Summer_Project_Week#Projects|Projects List]] | Image:PW-MIT2014.png|[[2014_Summer_Project_Week#Projects|Projects List]] | ||
| − | Image: | + | Image:CongenitalHeartModelsSlicer.png|Results of patch-based segmentation |
| − | Image: | + | Image:CongenitalHeartModels.png|Patient-specific heart model |
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<h3>Progress</h3> | <h3>Progress</h3> | ||
| − | * | + | * Did manual initial segmentations and and ran patch-based segmentation on additional datasets. |
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Latest revision as of 04:32, 27 June 2014
Home < 2014 Summer Project Week:Cardiac-Congenital
Results of patch-based segmentation
Patient-specific heart model
Printed model
Key Investigators
- Danielle Pace, MIT
- Adrian Dalca, MIT
- Polina Golland, MIT
Project Description
This project involves semi-automatic segmentation of gated 3D magnetic resonance images of hearts with congenital heart defects. Our aim is to create patient-specific heart models for surgical planning, which can be viewed either graphically on a computer, or with a 3D printer to create a physical model for surgeons.
We have had initial success in significantly reducing segmentation time with the following pipeline: 1) User manually segments ~10 axial slices 2) Segment the remaining slices using patch-based majority voting.
Objective
- Continue testing the patch based methods on an additional five datasets.
- Address main remaining challenge: segmenting thin interior heart walls.
Approach, Plan
- Manually segment ~10 axial slices for each of the five additional datasets.
- Explore remaining parameters for the patch-based segmentation: e.g. weighted voting, varying k in k-nearest neighbors patch lookup
Progress
- Did manual initial segmentations and and ran patch-based segmentation on additional datasets.
