Statistical atlases (with applications in cardiac imaging)

Transcription

1 GRIC Statistical atlases (with applications in cardiac imaging) Nicolas Duchateau CREATIS, Université Lyon 1, UMR CNRS 5220, Lyon, FR

2 Healthy cardiac function? Shape / anatomy: Global / local Functional descriptors: Synchrony + timings Global ejection Local motion/deformation Valves aperture/closure Other variables and their variability 1

3 Diseased cardiac function? LBBB #3 Inter-subjects differences LBBB #1 Intra-subjects differences LBBB #2 Pre-CRT Follow-up (6 months) 2

4 Statistical atlases ATLAS =??? 1) Geometry = shape information 2) Labels = functional information 3) Built from a population 3

5 Statistical atlases ATLAS =??? 1) Geometry = shape information 2) Labels = functional information 3) Built from a population Hart et al., STIA-MICCAI, 2010 Young and Frangi, EP, 2009 Ordas et al., ISPA, 2006 Peyrat et al., IEEE TMI,

6 Statistical atlases ATLAS =??? 1) Geometry = shape information 2) Labels = functional information 3) Built from a population Shape Ordas et al., ISPA, 2006 Fiber structure Peyrat et al., IEEE TMI, 2007 Lombaert et al., IEEE TMI, Velocities Duchateau et al., MedIA, 2011 Strain De Craene et al., MedIA + ISBI,

7 Statistical atlases ATLAS =??? 1) Geometry = shape information 2) Labels = functional information 3) Built from a population! Average + variability! Principal axes of variation (of what?)! Dimensionality reduction Different subjects Different phases ORL database 6

8 Statistical atlases ATLAS =??? 1) Geometry = shape information 2) Labels = functional information 3) Built from a population First dimension Second dimension Duchateau et al. Med Image Anal 2012 inward outward Mode 2 a abnormality Mode 1 Second dimension Hoogendoorn et al., IEEE TMI, 2013 First dimension 7

9 How to proceed? Subject 1 Subject 2... Subject N... Statistics on shape and/or function shape & pattern Temporal alignment Spatial correspondence Area strain (%) Reference timescale Reference geometry 8

10 Practical recommendations

11 Practical recommendations: temporal alignment Identify temporal landmarks: ECG events Valve events Piece-wise linear interpolation Perperidis et al., MedIA, 2005 Duchateau et al., MedIA,

12 Practical recommendations: temporal alignment Identify temporal landmarks: ECG events Valve events Piece-wise linear interpolation Perperidis et al., MedIA, 2005 Duchateau et al., MedIA, 2011 De Craene et al., ISBI, ESSENTIAL!!! Duchateau et al., UMB,

13 Practical recommendations: spatial alignment! Correspondences available: OK 10

14 Practical recommendations: spatial alignment! Correspondences available: OK! No segmentation available: registration + push-forward 10

15 Practical recommendations: spatial alignment! Correspondences available: OK! No segmentation available: registration + push-forward Duchateau et al. STIA-MICCAI, 2012 What to put inside?! Rotation only?! Scaling?! Lagrangian / Eulerian? OPEN QUESTION 10

16 Practical recommendations: which reference? Average reference image Given template (preferentially central) Registration template samples Average transformations Guimond et al., CVIU, 2000 Hoogendoorn et al., TMI,

17 Practical recommendations: which reference? Average reference image Given template (preferentially central) Registration template samples Average transformations Iterate Guimond et al., CVIU, 2000 Hoogendoorn et al., TMI,

18 Practical recommendations: which reference? Average reference image Given template (preferentially central) Registration template samples Average transformations Iterate Guimond et al., CVIU, 2000 Hoogendoorn et al., TMI,

19 Practical recommendations: which reference? Average reference image Given template (preferentially central) Registration template samples Average transformations Iterate Guimond et al., CVIU, 2000 Hoogendoorn et al., TMI,

20 Practical recommendations: which reference? Average reference image Given template (preferentially central) Registration template samples Average transformations Iterate Guimond et al., CVIU, 2000 Hoogendoorn et al., IEEE TMI,

21 Practical recommendations: statistics Linear or non-linear? A B A B Trouvé, SAMSI

22 Practical recommendations: statistics Linear or non-linear? A B A B Trouvé, SAMSI 2007 Pennec et al., IJCV, 2006 Known data structure Duchateau, PhD, 2012 Displacements = LARGE transformations (vectors) = is the diffeomorphic property preserved? Deformation / strain = tensors = are the tensor properties preserved? 12

23 Practical recommendations: statistics Linear or non-linear? A B A B Duchateau et al., MedIA, 2012 Trouvé, SAMSI 2007 «Learnable» data structure 13

24 Conclusions ATLAS =??? 1) Geometry = shape information 2) Labels = functional information 3) Built from a population Specific tools before comparing data Temporal alignment Choice of a reference Spatial alignment Careful statistics FULLY conditioned by the APPLICATION 14

25 Acknowledgements 2D/3D atlas of cardiac motion/deformation Mathieu De Craene Gemma Piella Duchateau et al., MedIA, 2012 De Craene et al., ISBI, D atlas of cardiac shape Corné Hoogendoorn Federico Sukno Hoogendoorn et al., IEEE TMI 2013 Available code: