Master EEAP
Systems and Images
Contributions to the Study of
Coronary Arteries in CTA Images
Supervisors: Maciej Orkisz, C...
Conservative Workflow
Challenges
Related Work
Introduction
Medical Context and Motivation
2
INTRODUCTION
PROPOSAL
RESULTS
...
3
HEALTHY STENOTIC
Left, Jeferson University Hospitals. Right, Schaap, 2010.
39%
30%
27%
4%
Deaths caused by non-
communic...
4
HEALTHY STENOTIC
Left, Jeferson University Hospitals. Right, Schaap, 2010.
39%
30%
27%
4%
Deaths caused by non-
communic...
5
HEALTHY STENOTIC
Left, Jeferson University Hospitals. Right, Schaap, 2010.
39%
30%
27%
4%
Deaths caused by non-
communic...
6
Workflow
INTRODUCTION
PROPOSAL
RESULTS
CONCLUSIONS
Contributions to the Study of Coronary Arteries in CTA Images
Challenges
- Size of data: 512 x 512 x 250 voxels
(Resolution 0.3 x 0.3 x 0.4 mm)
- Arteries diameters (1 – 7 mm)
- Image ...
- Complete synthetic review (Lesage et al., 2009 )
Related Work
- Recent doctoral studies (Zuluaga, 2011, Wang, 2011, Scha...
Related Work
Lumen segmentation
- Region growing (Bouraoui et al. 2008, Tek et. al. 2011, Metz et al. 2007)
- Deformable m...
Methods
Results
Proposal
Materials
10
INTRODUCTION
PROPOSAL
RESULTS
CONCLUSIONS
Contributions to the Study of Coronary Art...
Materials
11
Workshops
MICCAI 2008 - Coronary Artery Tracking
- 8 training annotated (axis + radius) datasets
MICCAI 2012 ...
Methods
12
-Radius Estimation
 Linear regression (MICCAI 2008 radius data)
- Axis Extraction (Tek + Dijkstra method) and ...
Methods
13
-Radius Estimation
 Linear regression (MICCAI 2008 radius data)
- Axis Extraction (Tek + Dijkstra method) and ...
Methods
14
- Validation scores
- Classical approaches
-Local region growing
-Variational Region Growing
-Active contours
-...
Methods
15
INTRODUCTION
PROPOSAL
RESULTS
CONCLUSIONS
Contributions to the Study of Coronary Arteries in CTA Images
VP:=tru...
Classical Approaches
16
Local region growing (Kappa – Sigma clipping)
( - k,  + k), k = 2, 2.5, 3
Variational region g...
Classical Approaches
17
Active contours
- Lankton approach (Lankton et. al. 2007) based on:
Geodesic active contours
Regio...
Classification Approaches
18
Lumen features
- Multi-scale analysis based on Gaussian filtering (Deriche et.al. 1993)
- Ele...
Classification Approaches
19
Support Vector Machines
- Kernel RBF (Chang et. al. 2011)
- C: regularization constant
- : k...
Classification Approaches
20
K-means clustering
- K = 2 classes
- Euclidean distance
- +1 feature: distance from ostia
Ext...
21
INTRODUCTION
PROPOSAL
RESULTS
CONCLUSIONS
Contributions to the Study of Coronary Arteries in CTA Images
VP:=true positi...
22
Results
Radius Estimation
Distance from ostia – RCA (mm)
Radius(mm)
INTRODUCTION
PROPOSAL
RESULTS
CONCLUSIONS
Contribut...
23
Results
Before correction After correction Wrong corrections in bifurcations and plaques
Axis correction
INTRODUCTION
P...
24
Results
Local region growing
Acceptable=9/15 Poor=4/15 Bad=2/15
VRG
D: Using Frangi in mask B (Dice: 68.1%, Accuracy: 8...
25
Results
Active contours
INTRODUCTION
PROPOSAL
RESULTS
CONCLUSIONS
Contributions to the Study of Coronary Arteries in CT...
26
Results
Low Dice score (45%)
Support Vector Machines
K-means clustering
Dice score: 66.48% (Thresholding Dice: 65.20%)
...
• Contributions in axis correction and lumen segmentation using five different
techniques.
• Additional problems found:
- ...
The end…
Questions ??
28Contributions to the Study of Coronary Arteries in CTA Images
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Contributions to the study of coronary arteries in CTA images

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Transcript of "Master's Project Defense"

  1. 1. Master EEAP Systems and Images Contributions to the Study of Coronary Arteries in CTA Images Supervisors: Maciej Orkisz, CREATIS Marcela Hernández, UniAndes Ricardo A. Corredor
  2. 2. Conservative Workflow Challenges Related Work Introduction Medical Context and Motivation 2 INTRODUCTION PROPOSAL RESULTS CONCLUSIONS Contributions to the Study of Coronary Arteries in CTA Images
  3. 3. 3 HEALTHY STENOTIC Left, Jeferson University Hospitals. Right, Schaap, 2010. 39% 30% 27% 4% Deaths caused by non- communicable diseases Cardiovascular system Respiratory and digestive systems Cancer Others Arterial diseases remain as one of the main causes of death in the world. Global status report on non-communicable diseases 2010 Medical Context and Motivation INTRODUCTION PROPOSAL RESULTS CONCLUSIONS Contributions to the Study of Coronary Arteries in CTA Images
  4. 4. 4 HEALTHY STENOTIC Left, Jeferson University Hospitals. Right, Schaap, 2010. 39% 30% 27% 4% Deaths caused by non- communicable diseases Cardiovascular system Respiratory and digestive systems Cancer Others Arterial diseases remain as one of the main causes of death in the world. Global status report on non-communicable diseases 2010 Aorta Ostia Lumen Medical Context and Motivation LCA LAD LCX RCA INTRODUCTION PROPOSAL RESULTS CONCLUSIONS Contributions to the Study of Coronary Arteries in CTA Images
  5. 5. 5 HEALTHY STENOTIC Left, Jeferson University Hospitals. Right, Schaap, 2010. 39% 30% 27% 4% Deaths caused by non- communicable diseases Cardiovascular system Respiratory and digestive systems Cancer Others Arterial diseases remain as one of the main causes of death in the world. Global status report on non-communicable diseases 2010 Medical Context and Motivation INTRODUCTION PROPOSAL RESULTS CONCLUSIONS Contributions to the Study of Coronary Arteries in CTA Images
  6. 6. 6 Workflow INTRODUCTION PROPOSAL RESULTS CONCLUSIONS Contributions to the Study of Coronary Arteries in CTA Images
  7. 7. Challenges - Size of data: 512 x 512 x 250 voxels (Resolution 0.3 x 0.3 x 0.4 mm) - Arteries diameters (1 – 7 mm) - Image artifacts (heart movement, noise,…) - Contrast attenuation, anomalies, presence of structures with similar intensities. - Shape variability (intra- and inter-patient) 7 Planes orthogonal to the central axis near the ostium (top), with a calcification (middle), and in a distal zone (bottom) INTRODUCTION PROPOSAL RESULTS CONCLUSIONS Contributions to the Study of Coronary Arteries in CTA Images
  8. 8. - Complete synthetic review (Lesage et al., 2009 ) Related Work - Recent doctoral studies (Zuluaga, 2011, Wang, 2011, Schaap, 2010, Lesage, 2009) + A priori knowledge about vessels + Vascular features + Lumen segmentation methods * With an axis * Without an axis INTRODUCTION PROPOSAL RESULTS CONCLUSIONS 8Contributions to the Study of Coronary Arteries in CTA Images
  9. 9. Related Work Lumen segmentation - Region growing (Bouraoui et al. 2008, Tek et. al. 2011, Metz et al. 2007) - Deformable models (shape prior, penalize leakages) (Nain et. al. 2004) - Linear and non-linear regression (Schaap et al. 2011) - Minimum cost-path (Zhu et.al. 2011) INTRODUCTION PROPOSAL RESULTS CONCLUSIONS 9 Preprocessing - Enhance vessels (Frangi et al. 1998, Zhou et. al., 2012, Zheng et al. 2011) - Define thresholds (Lesage et al. 2009, Tessmann et. al. 2011) - Define ROI and estimate artery radius (Carrillo et al. 2007, Zhou et. al. 2012, Xu et. al. 2012) Contributions to the Study of Coronary Arteries in CTA Images
  10. 10. Methods Results Proposal Materials 10 INTRODUCTION PROPOSAL RESULTS CONCLUSIONS Contributions to the Study of Coronary Arteries in CTA Images
  11. 11. Materials 11 Workshops MICCAI 2008 - Coronary Artery Tracking - 8 training annotated (axis + radius) datasets MICCAI 2012 - Stenoses Detection, Quantification and Lumen Segmentation - 18 training annotated (reference axes + stenoses information) datasets INTRODUCTION PROPOSAL RESULTS CONCLUSIONS Contributions to the Study of Coronary Arteries in CTA Images
  12. 12. Methods 12 -Radius Estimation  Linear regression (MICCAI 2008 radius data) - Axis Extraction (Tek + Dijkstra method) and Correction INTRODUCTION PROPOSAL RESULTS CONCLUSIONS Contributions to the Study of Coronary Arteries in CTA Images Preprocessing
  13. 13. Methods 13 -Radius Estimation  Linear regression (MICCAI 2008 radius data) - Axis Extraction (Tek + Dijkstra method) and Correction INTRODUCTION PROPOSAL RESULTS CONCLUSIONS Contributions to the Study of Coronary Arteries in CTA Images Preprocessing
  14. 14. Methods 14 - Validation scores - Classical approaches -Local region growing -Variational Region Growing -Active contours - Classification approaches - Support Vector Machines - K-means clustering INTRODUCTION PROPOSAL RESULTS CONCLUSIONS Contributions to the Study of Coronary Arteries in CTA Images Segmentation
  15. 15. Methods 15 INTRODUCTION PROPOSAL RESULTS CONCLUSIONS Contributions to the Study of Coronary Arteries in CTA Images VP:=true positives VN:=true negatives FP :=false positives FN:=false negatives Segmentation Reference FN VP VN FP Validation scores
  16. 16. Classical Approaches 16 Local region growing (Kappa – Sigma clipping) ( - k,  + k), k = 2, 2.5, 3 Variational region growing (VRG) + vesselness (Pacureanu et al. 2010) Sphere Axis - Chan & Vese approach (homogeneous regions) Frangi et. al. 1998 Sato et. al. 1998 INTRODUCTION PROPOSAL RESULTS CONCLUSIONS Contributions to the Study of Coronary Arteries in CTA Images
  17. 17. Classical Approaches 17 Active contours - Lankton approach (Lankton et. al. 2007) based on: Geodesic active contours Region-based active contours + = INTRODUCTION PROPOSAL RESULTS CONCLUSIONS Contributions to the Study of Coronary Arteries in CTA Images
  18. 18. Classification Approaches 18 Lumen features - Multi-scale analysis based on Gaussian filtering (Deriche et.al. 1993) - Eleven scales according to arteries radius - Hessian matrix eigenvalues - Gradient magnitude - Intensity TOTAL: 55 features by voxel INTRODUCTION PROPOSAL RESULTS CONCLUSIONS Contributions to the Study of Coronary Arteries in CTA Images
  19. 19. Classification Approaches 19 Support Vector Machines - Kernel RBF (Chang et. al. 2011) - C: regularization constant - : kernel parameter Extraction of 3D features Classification strategy Annotated data Supervised learning Binary image White = artery CTA Image http://ccforum.com/content/11/4/R83/figure/F1 INTRODUCTION PROPOSAL RESULTS CONCLUSIONS Contributions to the Study of Coronary Arteries in CTA Images
  20. 20. Classification Approaches 20 K-means clustering - K = 2 classes - Euclidean distance - +1 feature: distance from ostia Extraction of 3D features in spheres Classification strategy Unsupervised learning Binary image White = artery Axis extracted Spheres (Carrillo et. al. 2007) INTRODUCTION PROPOSAL RESULTS CONCLUSIONS Contributions to the Study of Coronary Arteries in CTA Images
  21. 21. 21 INTRODUCTION PROPOSAL RESULTS CONCLUSIONS Contributions to the Study of Coronary Arteries in CTA Images VP:=true positives VN:=true negatives FP :=false positives FN:=false negatives Segmentation Reference FN VP VN FP Validation scores Results
  22. 22. 22 Results Radius Estimation Distance from ostia – RCA (mm) Radius(mm) INTRODUCTION PROPOSAL RESULTS CONCLUSIONS Contributions to the Study of Coronary Arteries in CTA Images
  23. 23. 23 Results Before correction After correction Wrong corrections in bifurcations and plaques Axis correction INTRODUCTION PROPOSAL RESULTS CONCLUSIONS Contributions to the Study of Coronary Arteries in CTA Images
  24. 24. 24 Results Local region growing Acceptable=9/15 Poor=4/15 Bad=2/15 VRG D: Using Frangi in mask B (Dice: 68.1%, Accuracy: 84.0%, Specificity: 85.6%, Sensitivity: 78.5%) E: Using Frangi in mask C -> High increase in FP INTRODUCTION PROPOSAL RESULTS CONCLUSIONS Contributions to the Study of Coronary Arteries in CTA Images
  25. 25. 25 Results Active contours INTRODUCTION PROPOSAL RESULTS CONCLUSIONS Contributions to the Study of Coronary Arteries in CTA Images
  26. 26. 26 Results Low Dice score (45%) Support Vector Machines K-means clustering Dice score: 66.48% (Thresholding Dice: 65.20%) Reference Mask K-means result XOR INTRODUCTION PROPOSAL RESULTS CONCLUSIONS Contributions to the Study of Coronary Arteries in CTA Images
  27. 27. • Contributions in axis correction and lumen segmentation using five different techniques. • Additional problems found: - Lumen intensity can increase in a distal zone, specially after a plaque. - It can be higher than calcified plaques intensity. • Axis correction algorithm is sensitive to bifurcations and calcified plaques -> it can be used in detection of bifurcations. • Best results were obtained with region growing, clustering, and active contours. Poor results with SVM. A more detailed analysis of selected features is required. • Explicit modeling of coronary arteries and intensity profiles is still a challenging task. • A complete validation framework for coronary segmentation is required. Conclusions 27 INTRODUCTION PROPOSAL RESULTS CONCLUSIONS Contributions to the Study of Coronary Arteries in CTA Images
  28. 28. The end… Questions ?? 28Contributions to the Study of Coronary Arteries in CTA Images

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