1. De-identification of Facial Images by Use of Composites *Mark E. Engelstad MD, DDS, MHI Oregon Health & Science University Dept of Oral and Maxillofacial Surgery Dept Medical Informatics & Clinical Epidemiology Genevieve B. Melton, MD, MA University of Minnesota Institute for Health Informatics Department of Surgery Medbiquitous Annual Symposium, Baltimore MD May 10, 2011

5. =+ Pre-op De-identification Original injury Periorbital area

6. =+ Post-op De-identification

7. The Questions: Do composites de-identify faces? Even those that are well-known to an observer? Are facial composites realistic in appearance?

8. Figure 2: A comparison of two techniques for facial image de-identification. The middle image (B) is the original image. (A) black boxes only. (C) a facial composite, altered in the area of eyes and eyebrows only.

9. This is a PRE-operative patient This is a POST-operative patient I recognize this patient

10. Me Faces Subjects viewed the composite faces twice—first unaware that the faces were composites, and then primed to the presence of composites.

11. Subjects viewed 20 composite faces

12. 10/20 had a third of a familiar face (test face) Test Face

13. Results Subject ResponseUnprimed (1 st Viewing) Primed (2 nd Viewing) Facial Composites Total = 20 Composites of Unfamiliar Faces Total = 10 Did Not Identify (True Neg) 100% (120/120 ) * 42% (50/120) Identified Wrongly(False Pos) 0% (0/120)58% (70/120) Composites with Familiar (Test) Faces Total = 10 Identified Correctly (True Pos) 0% (0/120)62% (74/120) Identified Wrongly (False Pos) 0% (0/120)19% (23/120) Failed to Identify (False Neg) 100% (120/120 ) * 19% (23/120) No subjects identified test faces unless they were primed to their presence (* p < 0.001). Results

14. Familiar Face Composite A Region Visible Familiar Face Composite B Region Visible Faces A and BViews by region (n) 42% (5/12) 79% * (19/24) 67% (24/36) Upper 36 71% † (17/24) 38% † 9/24 54% (26/48) MidFace 48 67% (8/12) 67% 16/24 67% (24/36) Lower 36 Total Face A 63% (30/48) Total Face B 61% (44/72) Total Faces A and B 62% (74/120) Total 120 Table 2: Identification of Test faces after priming--compared by facial region. Percentages of subjects who correctly identified a familiar face when regions of that face were visible in the composite image are shown (true positives). In Test Face B, a significant difference (* p<0.01) in identification rate existed between Upper Face and Midface. Test Face A Midface was recognized correctly more often than Test Face B Midface (†p<0.01)

15. OriginalBlack BoxesComposite, Eyes only

16. Making a Facial Composite 1: Photoshop 2: A Library

17. Step 2,3: Remove Background, Change laterality

18. 4: Size all images to a standard (800 x1200) 5: Align the facial features 6: Create a Layer Mask 7: Use a Brush to reveal deeper layer 8: Blend the edges between the two layers 9: Correct Color Tones

19. Show Simulation/ Example