2014 Project Week:AblationSuccessRatePredictionUsingJointImageAndShapeAnalysis
p-value between DCE-MRI between cured patiens and AFib recurrent patient.
Contents
Key Investigators
- Yi Gao, LiangJia Zhu, Josh Cates, Rob MacLeod, Sylvain Bouix, Ron Kikinis, Allen Tannenbaum
Objective
Among the AFib patients underwent RF ablation, the relative high AFib recurrence rate is a concern. We combine both the image and shape information for the purpose of predicting the RF ablation success rate.
Approach, Plan
The fibrosis distributions on the left atrium wall is imaged using the dynamic contrast enhanced MRI. Distributed on different anatomical structures, they are considered as "mass" defined on different domains. Under the framework of the optimal mass transport (OMT), the masses are transported to a common domain where the statistical analysis can then be applied. The significant different regions are then characterized by the low-p-value regions.
Progress
- Discussion with Josh about similar work. CARMA has also work on this using particle based shape analysis on surface. This module uses volumetric OMT for the wall volume.
- Next
- validation on particle/OMT based methods
- Test Extension and then Nightly build
Delivery Mechanism
This work will be delivered to the NA-MIC Kit as a commandline extension.
References
- Utah DBP
- Y Gao, Y Rathi, S Bouix, A Tannenbaum; Filtering in the Diffeomorphism Group and the Registration of Point Sets; IEEE Transactions on Image Processing 21 (10), 4383--4396
- Y. Gao and S. Bouix, Synthesis of realistic subcortical anatomy with known surface deformations; in MICCAI Workshop on Mesh Processing in Medical Image Analysis, 2012, pp. 80–88.
