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Joshua Stough COMP 238 December 17, 2002

A Software Tool for the Enhanced Display of High-Dynamic-Range Medical Images using Bilateral Filtering. Joshua Stough COMP 238 December 17, 2002. Display of HDR Images Requires Contrast Enhancement. Goals: - Build a tool for the interactive, enhanced display of HDR medical images.

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Joshua Stough COMP 238 December 17, 2002

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  1. A Software Tool for the Enhanced Display ofHigh-Dynamic-Range Medical Images using Bilateral Filtering Joshua Stough COMP 238 December 17, 2002

  2. Display of HDR Images Requires Contrast Enhancement Goals: -Build a tool for the interactive, enhanced display of HDR medical images. -Use bilateral filtering [Durand, Dorsey 2002]. Why: -Opine on the usefulness of BF. -Clinical diagnostic tool.

  3. Outline • Introduction • Clinical Apps • Global Schemes • Histogram Windowing, GHE • Local Schemes • Unsharp Masking, BF, AHE, CLAHE, SHAHE • Studies of diagnostic efficacy • Demo

  4. Contrast Enhancement • Contrast Enhancement – not optional • Mapping: Recorded Intensities  Display Scale • Optimal – w/r to characteristics useful to clinicians • Example: segmentation, texture

  5. Histogram Windowing • Idea: Limited Footprint • Problems: • Distinct footprints • Isoboundries move with windowing

  6. Global Histogram Equalization • Mapping: recorded i gets mapped to its rank percentile of the maximum displayable intensity. • Result: peaks are dedicated a larger range. • Problem – contextual region too large.

  7. Unsharp Masking • New image is linear combination of background and detail (difference with original). • Key: background image • Example uses BF for background image 

  8. Bilateral Filtering • Two Gaussians: • One in the spatial domain (higher weights to closer pixels) • Other in the intensity domain (giving higher weights to pixels of intensity similar to i).

  9. Adaptive Histogram Equalization • Square contextual region, local histogram equalization • Problems • Not all regions are equal • Shadowing at sharp high-contrast boundaries

  10. Contrast Limited AHE • Clip histogram peaks • Redistribute cutoff pixels • Display by rank of pixel w/r to redistributed histogram

  11. Sharpened AHE • Simply, Unsharp Masking followed by CLAHE

  12. Clinical Efficacy of Image Enhancement • Seems obvious, but proof is rare • Study One: Portal film field isocenter correction • UNC, Duke. SHAHE. (first try, unpublished, CLAHE) • Conclusion: Enhancement makes bad a little better • Study Two: Simulated mass detection in dense mammograms, enhanced with IW or CLAHE • Conclusion: Compared to nothing (linear mapping) • IW slightly better • CLAHE no different

  13. Bibliography • Hemminger BM, S Zong, KE Muller, CS Coffey, MC DeLuca, RE Johnston, ED Pisano (2001). Improving the Detection of Simulated Masses in Mammograms through two Different Image-Processing Techniques, Academic Radiology, 8 : 845-855. • Pizer SM, Hemminger BM, Johnston, “Display of Two Dimensional Images”, in Image-Processing Techniques for Tumor Detection, edited by Strickland. 2002 Marcel Deckker, Basel, Switzerland. ISBN 0-8247-0637-4. • Rosenman J, CA Roe, R Cromartie, KE Muller, SM Pizer (1993). Portal Film Enhancement: Technique and Clinical Utility. I. J. Radiation Oncology, 25 (2): 333-338.

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