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A Fast and Accurate Tracking Algorithm of the Left Ventricle in 3D Echocardiography A Fast and Accurate Tracking Algorithm of the Left Ventricle in 3D.

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Presentation on theme: "A Fast and Accurate Tracking Algorithm of the Left Ventricle in 3D Echocardiography A Fast and Accurate Tracking Algorithm of the Left Ventricle in 3D."— Presentation transcript:

1 A Fast and Accurate Tracking Algorithm of the Left Ventricle in 3D Echocardiography A Fast and Accurate Tracking Algorithm of the Left Ventricle in 3D Echocardiography A Fast and Accurate Tracking Algorithm of the Left Ventricle in 3D Echocardiography Richard Socher Presenter: Richard Socher Author: Author: Lin Yang Bogdan Georgescu Yefeng Zheng David J. Foran Dorin Comaniciu TexPoint fonts used in EMF. Read the TexPoint manual before you delete this box.: AAAAAAAAAAAAAAA

2 A Fast and Accurate Tracking Algorithm of the Left Ventricle in 3D Echocardiography Human Heart End-diastolic volume (ED): end of filling End-systolic volume (ES): end of contraction Heart cycle: ED phase -> ES -> ED Stroke volume: SV = EDV − ESV, SV*heart rate = cardiac output

3 A Fast and Accurate Tracking Algorithm of the Left Ventricle in 3D Echocardiography System Overview (1) Learned Motion Pattern (Motion Modes) (3) Detection Tracker (MSL / PBT) (4) Template Tracker (Optical Flow) (2) Shape Priors from LV Shape Statistics (5) Robust Information Fusion Fast Motion Tracking (6) Experiments

4 A Fast and Accurate Tracking Algorithm of the Left Ventricle in 3D Echocardiography Motion Alignment 4D Procrustes analysis on the training sequence –16 frames are sampled from each sequence –Generalized Procrustes analysis (GPA) –Resulting motion vectors are decomposed into 3D shape vectors: –d = 289 points x 3 dim

5 A Fast and Accurate Tracking Algorithm of the Left Ventricle in 3D Echocardiography Learn Motion Patterns through Manifold Learning The actual number of freedoms that control the motion of LV is much smaller than its original dimensionality d Given the whole set of aligned 3D shape vectors there exist a mapping where denotes the sampling noise and represents the nonlinear embedding on the low dimensional manifold ISOMAP is used to map the data from the high dimensional space to low dimensional subspace

6 A Fast and Accurate Tracking Algorithm of the Left Ventricle in 3D Echocardiography ISOMAP Projection Results It is clear that each motion roughly form a cycle, Which starts from ED phase and come back to ED.

7 A Fast and Accurate Tracking Algorithm of the Left Ventricle in 3D Echocardiography Hierarchical Clustering First we cluster based on ED shapes on the manifold We then align the ED shapes in one group together and cluster based on their motion trajectories

8 A Fast and Accurate Tracking Algorithm of the Left Ventricle in 3D Echocardiography Automatic Initialization of Tracking Train rigid ED detector with MSL Dimensions of marginal parameter spaces increase -> restricted areas with high probability Train nonrigid PBT boundary classifiers for ED/ES

9 A Fast and Accurate Tracking Algorithm of the Left Ventricle in 3D Echocardiography One Step Forward Prediction Goal: find shape prior from motion modes Use thin plate spline (TPS) transform to find most suitable element in the aligned motion modes. w_i is 3d point in motion mode and b_i in testing 72 ~ 289 points for speed Use next following shape as a prior.

10 A Fast and Accurate Tracking Algorithm of the Left Ventricle in 3D Echocardiography One Step Forward Prediction There are N motion modes. At time t, the prediction is calculated based on the motion mode which minimizes the previous 1 to t − 1 accumulated TPS registration errors Motion Mode ED Time t ED+1 ES ES+1 Last estimate

11 A Fast and Accurate Tracking Algorithm of the Left Ventricle in 3D Echocardiography Collaborative Tracking Initialize with rigid detector to get first mesh (1) Detection tracker –Use one step forward prediction to generate the motion prior. –Active Shape Models to transform into real shape using two boundary classifiers: ED and ES (2) Template tracker – 3D optical flow –Preserve the temporal consistence –The template: 13*13*13 cube How are (1) and (2) combined?

12 A Fast and Accurate Tracking Algorithm of the Left Ventricle in 3D Echocardiography Data Fusion The data fusion curve –Fusion of the collaborative tracking is obtained by defining prior distribution –Blue line: 3D optical flow, red line: detection tracker

13 A Fast and Accurate Tracking Algorithm of the Left Ventricle in 3D Echocardiography Experimental Results The algorithm is tested on 67 LV sequences The imaging protocol is heterogeneous The resolution is around 0.9mm to 1.56mm –27 sequences have dimensionality of 160*144*208 –40 sequences have dimensionality of 160*144*128

14 A Fast and Accurate Tracking Algorithm of the Left Ventricle in 3D Echocardiography Experimental Results (Cont.) 1 6 8 10

15 A Fast and Accurate Tracking Algorithm of the Left Ventricle in 3D Echocardiography Demo – Original Data

16 A Fast and Accurate Tracking Algorithm of the Left Ventricle in 3D Echocardiography Demo – 3D Optical Flow

17 A Fast and Accurate Tracking Algorithm of the Left Ventricle in 3D Echocardiography Demo – Tracking by Detection

18 A Fast and Accurate Tracking Algorithm of the Left Ventricle in 3D Echocardiography Demo – Collaborative Tracking

19 A Fast and Accurate Tracking Algorithm of the Left Ventricle in 3D Echocardiography Contributions A fast, robust and accurate 3D tracking algorithm including: –Dynamic motion models: increase the accuracy and efficiency –Detection tracker: increase the robustness to noise and avoid the template drifting –3D optical flow tracker preserves the temporal consistency -> Combined All the major steps are based on learning –The algorithm can be extended to other medical tracking problems

20 A Fast and Accurate Tracking Algorithm of the Left Ventricle in 3D Echocardiography (1) Learned Motion Pattern (Motion Modes) (3) Detection Tracker (MSL / PBT) (4) Template Tracker (Optical Flow) (2) Shape Priors from LV Shape Statistics (5) Robust Information Fusion Fast Motion Tracking (6) Experiments Thank you!


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