a region of interest approach for medical image compression salih burak gokturk stanford university
Post on 19-Dec-2015
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![Page 1: A Region of Interest Approach For Medical Image Compression Salih Burak Gokturk Stanford University](https://reader036.vdocuments.site/reader036/viewer/2022062313/56649d2a5503460f949ff623/html5/thumbnails/1.jpg)
A Region of Interest Approach For Medical Image Compression
Salih Burak Gokturk
Stanford University
![Page 2: A Region of Interest Approach For Medical Image Compression Salih Burak Gokturk Stanford University](https://reader036.vdocuments.site/reader036/viewer/2022062313/56649d2a5503460f949ff623/html5/thumbnails/2.jpg)
OVERVIEW
• Motivation
• Previous Work
• Comparison Study of Compression Schemes
• ROI based System Design
• Conclusion
![Page 3: A Region of Interest Approach For Medical Image Compression Salih Burak Gokturk Stanford University](https://reader036.vdocuments.site/reader036/viewer/2022062313/56649d2a5503460f949ff623/html5/thumbnails/3.jpg)
Motivation
• Medical images are huge.(300x512x512x2)
• High quality imaging is required in diagnostically important regions.
• ROI based approach is the only solution:– Lossless compression in ROI.– Very lossy compression in non-ROI.
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OVERVIEW
• Motivation
• Previous Work
• Comparison Study of Compression Schemes
• ROI based System Design
• Conclusion
![Page 5: A Region of Interest Approach For Medical Image Compression Salih Burak Gokturk Stanford University](https://reader036.vdocuments.site/reader036/viewer/2022062313/56649d2a5503460f949ff623/html5/thumbnails/5.jpg)
Previous Work• Lossless Compression Schemes (Takaya95,
Assche00)• DCT based Compression Schemes
(Vlaciu95) • PCA based Compression(Tao96)• Wavelet Transformation(2D and 3D)
(Baskurt93)• ROI based coding (Cosman 94,95)
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OVERVIEW
• Motivation
• Previous Work
• Comparison Study of Compression Schemes
• ROI based System Design
• Conclusion
![Page 7: A Region of Interest Approach For Medical Image Compression Salih Burak Gokturk Stanford University](https://reader036.vdocuments.site/reader036/viewer/2022062313/56649d2a5503460f949ff623/html5/thumbnails/7.jpg)
Lossless Compression• Entropy of images – 7.93bpp
• Predictive Coding – 5.9bpp
• Entropy of difference images – 5.76bpp
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DCT Compression (1)
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DCT Compression (2)
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DCT Compression (3)
Quantization Step Size 1 2 4 8 16 32 64 128 256 512 1024
MSE in dB -11.7 -5.7 0.34 6.26 11.9 17.1 21.8 25.7 29.3 32.6 35.9
Rate (without RLC) (bpp)
5.74 4.97 4.09 3.20 2.34 1.57 0.96 0.55 0.31 0.16 0.09
Rate (with RLC) (bpp)
8.04 7.09 5.87 4.51 3.15 1.95 1.07 0.55 0.28 0.14 0.07
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PCA Compression - Treat each image block as a vector
MSE ~ 30 dB
Rate ~ 0.54 bpp
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Blockwise Vector Quantization(1)
- A simpler decoder is required
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Blockwise Vector Quantization(2)
MSE ~ 38 dB MSE ~ 39 dB
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Motion Compensated Hybrid Coding (1)
- Lukas Kanade Tracker was used by 0.1 pixel accuracy
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Lukas-Kanade Tracker
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Motion Compensated Hybrid Coding (2)
- Entropy of the motion vector is 2.28 and 2.45 in x and y.- This brings 0.018 bpp.
MSE ~ 35 dB
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OVERVIEW
• Motivation
• Previous Work
• Comparison Study of Compression Schemes
• ROI based System Design
• Conclusion
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Segmentation- Thresholding to find the air- Gradient magnitude to extract the colon wall- Grassfire operation to find the ROI around the colon wall
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ROI Based System
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Experiment with 16 by 16 Blocks- The ratio of ROI ~ %12.2- Entropy of motion vector is 2.28 in x and 2.45 in y- The entropy of the error image is ~ 4.38- average RMS error 33.7 dB with lossless in ROI- Overall rate 0.552 bps
MSE ~ 33.7 dB
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Experiment with 8 by 8 Blocks- The ratio of ROI ~ %7.3- Entropy of motion vector is 1.82 in x and 1.96 in y- The entropy of the error image is ~ 4.31- average RMS error 30.3 dB with lossless in ROI- Overall rate 0.37 bps
MSE ~ 30.3 dBMSE ~ 33.7 dB
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OVERVIEW
• Motivation
• Previous Work
• Comparison Study of Compression Schemes
• ROI based System Design
• Conclusion
![Page 23: A Region of Interest Approach For Medical Image Compression Salih Burak Gokturk Stanford University](https://reader036.vdocuments.site/reader036/viewer/2022062313/56649d2a5503460f949ff623/html5/thumbnails/23.jpg)
Conclusion
• Effective System (compression rate of %2.3)• Accurate System (lossless in ROI)• Results of ROI based compression over performs
standard compression schemes.• Future work includes lossy compression in ROI.• Case study with the radiologist for determining
rate-diagnosis performance curve.