Interactive Whole-Heart Segmentation in Congenital Heart Disease
Open Access
- 18 November 2015
- book chapter
- conference paper
- Published by Springer Science and Business Media LLC in Lecture Notes in Computer Science
- Vol. 9351, 80-88
- https://doi.org/10.1007/978-3-319-24574-4_10
Abstract
We present an interactive algorithm to segment the heart chambers and epicardial surfaces, including the great vessel walls, in pediatric cardiac MRI of congenital heart disease. Accurate whole-heart segmentation is necessary to create patient-specific 3D heart models for surgical planning in the presence of complex heart defects. Anatomical variability due to congenital defects precludes fully automatic atlas-based segmentation. Our interactive segmentation method exploits expert segmentations of a small set of short-axis slice regions to automatically delineate the remaining volume using patch-based segmentation. We also investigate the potential of active learning to automatically solicit user input in areas where segmentation error is likely to be high. Validation is performed on four subjects with double outlet right ventricle, a severe congenital heart defect. We show that strategies asking the user to manually segment regions of interest within short-axis slices yield higher accuracy with less user input than those querying entire short-axis slices.Keywords
This publication has 12 references indexed in Scilit:
- An active learning approach for stroke lesion segmentation on multimodal MRI dataNeurocomputing, 2015
- Reusability of Statistical Shape Models for the Segmentation of Severely Abnormal HeartsLecture Notes in Computer Science, 2015
- Three-dimensional printing in cardiac surgery and interventional cardiology: a single-centre experienceEuropean Journal of Cardio-Thoracic Surgery, 2014
- Three-dimensional patient-specific cardiac model for surgical planning in Nikaidoh procedureCardiology in the Young, 2014
- Challenges and Methodologies of Fully Automatic Whole Heart Segmentation: A ReviewJournal of Healthcare Engineering, 2013
- Semi-Supervised and Active Learning for Automatic Segmentation of Crohn’s DiseaseLecture Notes in Computer Science, 2013
- Patch-based segmentation using expert priors: Application to hippocampus and ventricle segmentationNeuroImage, 2011
- Active Learning for Interactive 3D Image SegmentationLecture Notes in Computer Science, 2011
- Automatic Segmentation of Different Pathologies from Cardiac Cine MRI Using Registration and Multiple Component EM EstimationLecture Notes in Computer Science, 2011
- 3D-Imaging of cardiac structures using 3D heart models for planning in heart surgery: a preliminary studyInteractive CardioVascular and Thoracic Surgery, 2008