Transcript Medical Image Compression
Medical Image Compression
EECE 541 Multimedia Systems Harjot Pooni Ashish Uthama Victor Sanchez
What are medical images ?
Some examples MRI / FMRI (Function Magnetic Resonance) Department of Electrical Engineering and Computer Engineering
Medical Images
Dynamic 3D Ultrasound PET (Positron emission Tomography) CT (computerized Tomograhpy) Department of Electrical Engineering and Computer Engineering
Why compress medical images?
Growing need for storage Efficient data transmission Telemedicine Tele-radiology applications Real time Tele-consultation.
PACS (Picture archiving and communication systems) Department of Electrical Engineering and Computer Engineering
Challenges unique to medical images.
Compression Algorithms Lossy / Lossless Medical Images should always be stored in lossless format.
Erroneous Diagnostics and its legal implications.
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Techniques used
Compression techniques may be classified into: Lossy Lossless Moreover, compression algorithms may be applied in the spatial domain or frequency domain Compressed image e.g. WinZIP Transform to frequency domain Department of Electrical Engineering and Computer Engineering Compressed image e.g. JPEG, JPEG2000
JPEG 2000 and JPEG-LS
High compression efficiency Lossless color transformations Progressive by resolution and quality Multiple component images ROI coding (static and dynamic) Error resilience capabilities Object oriented functionalities (coding, information, embedding) Department of Electrical Engineering and Computer Engineering
Drawbacks of JPEG 2000 and JPEG-LS
Only looks for redundancy in the frame.
Does not exploit 3D and 4D redundancy
3D Redundancy
3D medical image Department of Electrical Engineering and Computer Engineering
4D Redundancy
Exploits temporal redundancy Time 3 4D medical image . . . . . . . . Time n Time 1 Time 2 Department of Electrical Engineering and Computer Engineering
Ordering the data to exploit redundancies
Transform the problem domain: Convert 4D data to a sequence of 2D data Volume Slice
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Slice
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Slice
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Time Volume 1 Slice
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Volume 2 . . . . .
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Volume
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Slice 1 Slice
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Volume 1 Slice 1 Slice
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Volume 2 . . . . .
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3D-JPEG 2000
Part 10 – JP3D
“Part 10 is still at the Working Draft stage. It is concerned with the coding of three-dimensional data, the extension of JPEG 2000 from planar to volumetric images” http://www.jpeg.org/jpeg2000/j2kpart10.html
Some commercial vendors have already come out with 3D extensions of JPEG 2000 http://www.aware.com/products/compression/J2K3D.html
Provides guidelines for the use of JPEG 2000 for 3D data Department of Electrical Engineering and Computer Engineering
3D-JPEG 2000 The basic approach
Wavelet transforms Department of Electrical Engineering and Computer Engineering
3D-JPEG 2000 The basic approach
Reorder the 4D data by
volume time
or For each set, apply a 1D wavelet transform along the z axis Apply JPEG transformed slice 2000 on each H1 H2 L2 LL2 HL2 LH2 HH2 HL1 HH1 LH1 1D wavelet transform + JPEG 2000 coding = 3D-JPEG 2000 Department of Electrical Engineering and Computer Engineering
Drawbacks
Does not effectively use the redundancy in the 4 th dimension (Temporal redundancy) Movement of object between two slices would adversely effect performance Object motion is significant in medical imaging Patient movement Organ movement (Heart, Lung) Department of Electrical Engineering and Computer Engineering
H.264/AVC
Latest video coding standard uses motion compensation and estimation .
Source: www.vcodex.com
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Why use H.264?
Better Intra frame compression Medical images have comparatively more
uniform
areas Motion estimation and compensation Address temporal redundancies Multiple frames may be used to predict a single frame.
Better performance Different block sizes for motion estimation (16x16, 16x8, 8x8) Better performance!
Improved entropy encoder Better performance!!
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Approach One: H.264-VOL
Slice
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Slice
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Slice
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. . . . .
Slice
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Slice
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Slice
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Volume 1 Volume 2 Apply H.264/AVC on slices arranged as shown above Volume
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Results:
Compression Technique
JPEG2000 JPEG-LS 3D-JPEG 2000(VOL) H.264-VOL Department of Electrical Engineering and Computer Engineering
Compression ratio
2.55:1 3.06:1 3.15:1 3.89:1
Approach Two: H.264-TIME
Slice 1 Slice 1 . . . . .
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Slice 1 Slice
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Volume 1 Volume 2 Apply H.264/AVC on slices arranged as shown above Volume
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Results:
Compression Technique
JPEG2000 JPEG-LS 3D-JPEG2000 (Time) H.264-TIME Department of Electrical Engineering and Computer Engineering
Compression ratio
2.55:1 3.06:1 7.37:1 12.38:1
Best compression performance
Slice 1 Slice
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Slice 1 . . . . .
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Slice 1 Slice
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Volume 1 Volume 2 H.264 applied across time H.264-TIME Volume
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How to improve compression efficiency?
Two ideas: • • Get the difference between consecutive image slices, then use H.264
Calculate the residual frames, then use H.264
Main objective: reduce the energy content of each image slice.
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Difference between slices
Volume 1 Reference slice Slice 1 Slice
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Volume 2 Reference slice
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Slice 1 Slice
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Difference Difference
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Difference
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Difference
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Difference
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Difference
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Volume
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Reference slice Slice 1 Slice
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Difference Difference
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Difference
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H.264
MC + entropy coder (CABAC)
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coded bit streams Slice 1 Slice 2 Department of Electrical Engineering and Computer Engineering Difference
Residual frames
Volume 1 Volume 2 Reference slice Slice 1 Slice
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H.264 MC + MVs Residual
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Residual
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H.264 MC Reference slice Slice 1 Slice
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+ MVs . . . . .
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Volume
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Residual
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H.264 MC Reference slice Slice 1 Slice
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H.264
MC + entropy coder (CABAC) + MVs Residual
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coded bit streams Original slice Predicted Department of Electrical Engineering and Computer Engineering Residual
Results
Compression Technique
3D-JPEG2000 H.264-TIME
Improvement
H.264
Difference 100% H.264
Residual 100% 20% 27% Department of Electrical Engineering and Computer Engineering
Future improvements
• Contextual encoding take into account characteristics of image High motion Low motion Department of Electrical Engineering and Computer Engineering
Future improvements
Low motion areas lossy High motion areas lossless Lossy Lossless Department of Electrical Engineering and Computer Engineering
Future improvements
Encoding using “slices” (group of macroblocks): First slice for high motion areas Second slice for low motion areas Slices may be encoded at different rates First slice Second slice Department of Electrical Engineering and Computer Engineering
Questions?
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