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Progress Report: Week 8 Alvaro Velasquez

Progress Report: Week 8 Alvaro Velasquez. Framework. Create data matrix of all non-overlapping 4x4x4 cuboids in image volume. Learn dictionary for the data matrix using KSVD. Obtain sparse coefficient matrix using graph regularization. Cluster coefficient matrix using K-means.

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Progress Report: Week 8 Alvaro Velasquez

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  1. Progress Report: Week 8 Alvaro Velasquez

  2. Framework • Create data matrix of all non-overlapping 4x4x4 cuboids in image volume. • Learn dictionary for the data matrix using KSVD. • Obtain sparse coefficient matrix using graph regularization. • Cluster coefficient matrix using K-means. • Display clusters on image volume for segmentation.

  3. Things Tried this Week • Append all three RGB channels to vectorized cuboids as opposed to using gray-scale • Use Pearson correlation for the distance measure when clustering as opposed to Euclidean distance. • Choose initial centroid locations when clustering as opposed to choosing random locations. • Use Max-Voting for initial centroid locations. • Perform Quick-shift as a preprocessing step.

  4. Last Week's Segmentation

  5. Choosing Initial Centroid Locations

  6. Centroid Locations Through Max-Voting

  7. Work for this Week • Add Gaussian smoothing as a pre-processing step. • Make sparsity rate larger. • Try different dictionary sizes (We have tried 1000 and 2000 atom dictionaries).

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