1. Quantitative Comparison of Conventional and Oblique MRI for Detection of Herniated Discs Automatic Herniation Detection A collaborative project with Doug Dean Erin Hannen

2. Purpose Development of an algorithm for: ▫ Segmentation of individual spinal disks ▫Determination of specific, quantitative properties of each disc ▫Use properties to determine if a disc is herniated or normal

3. Approach Modify methods from “Desiccation diagnosis in lumbar discs from clinical MRI with a probabilistic model” 1.Intensity: Obtain histogram. Herniated discs typically have lower intensity profile due to spreading of the nucleus pulposus over a larger area. Individual intensity values and the average intensity value are obtained

4. Approach

5. Current Progress Lumbar discs segmented Semi-automated Edge detection, MATLAB image processing tools Disc location defined Centroid of segmentation boundary calculated Overlay of segmentation boundary onto original image Average intensity over entire segmented disk

6. I = 80.400 I = 86.4614 I = 84.6678 I = 70.1894

7. Project timeline April 12: First project presentation ▫April 13-27: Continue reading literature articles comparing methods for disc quantification. Begin writing MATLAB code for herniation detection using data from class labs or phantom images. April 28: Mid project presentation ▫April 28-May 15:  Refine segmentation methods, where needed  Finish developing herniation detection code  Ensure successful implementation using acquired MRI data May 16 & 17: Final project presentation