1. Initial Progress Report
Daniel Donenfeld

2. Contents
Goal
Approach
Timeline
Super-Voxels
Progress

3. Full CT with Bounding Volumes
Project Goal
Generate organ Bounding Boxes
Detect Heart, Kidney, Liver
Full CT scan
Full CT with Bounding Volumes

4. Approach - Training Training Train Random Forest on super-voxels
Train organ displacement

5. Approach - Testing Reduce Search space with location priors
Segment into supervoxels
Run each super-voxel through random forest
Improve estimates using inter-organ displacement
Return bounding boxes

6. Initial Timeline
Research supervoxel implementations and uses in medical imaging
Over-segment scans with supervoxel
Train and test random forest on supervoxels
Extract inter-organ displacement
Integrate organ displacement data

7. Super-Voxel Over-Segmentation
Pixels are an artifact of digital sampling
Useful to extract more relevant regions from image
Reduce computation
One of the best superpixel algorithms is SLIC
Also extendable to supervoxels

8. Super-Voxel using SLIC
Initialize cluster centers

9. Super-Voxel using SLIC
Move each cluster center to the lowest nearby gradient position
For each cluster center
Do k-means clustering in a small region surrounding the cluster
Repeat until error threshold is reached

10. Why SLIC? CRCV lab researches motion in videos using supervoxels
Algorithms would not work effectively for CT images
Ex: Spatio-Temporal Object Detection Proposals, uses SLIC on image slices, then optical flow between slices
Ex: LIBSVX, Uses color information

11. Why SLIC?
Literature reveals its one of the prefered methods for segmenting medical images
Useful for CT scans
Graph cut based Automatic Prostate Segmentation
Near-optimal Keypoint Sampling for Fast Pathological Lung Segmentation
Edge- and detail-preserving sparse image representations for deformable registration of chest MRI and CT volumes

12. Progress Find SLIC implementation to generate supervoxels
Lots of implementations of SLIC for superpixel (in general and matlab)
Fewer implementations of SLIC for supervoxel

13. Progress Implementations exist in python and C++
Can call python from matlab
Have used Scikit (python) implementation of SLIC
problems interfacing, cannot enforce connectivity
Plan - write small wrapper to easily call C++ implementation
Use results in matlab

14. Using Python