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Medical Image Compression EECE 541 Multimedia
Systems
Harjot Pooni
Ashish Uthama
Victor Sanchez
Department of Electrical Engineering and Computer
Engineering
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.
Department of Electrical Engineering and Computer
Engineering
Techniques usedCompression 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
Compressed image e.g. JPEG, JPEG2000
Department of Electrical Engineering and Computer
Engineering
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
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Engineering
4D Redundancy
Exploits temporal redundancy
. . . . . . . .
Time 1 Time 2 Time 3 Time n
4D medical image
Department of Electrical Engineering and Computer
Engineering
Ordering the data to exploit redundanciesTransform the problem domain: Convert 4D data to a sequence of 2D data
Volume
Time
Volume 1 Volume 2 Volume n
. . . . .
. . . . .
. . . . .
Slice 1
Slice 1
Slice 1
Slice s Slice s Slice s
Volume 1
Slice s
Volume 2 Volume n
. . . . .
Slice s Slice s
Slice 1 Slice 1 Slice 1
Department of Electrical Engineering and Computer
Engineering
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 time or
volume
For each set, apply a 1D wavelet transform along the z axis
Apply JPEG 2000 on each transformed slice
H1
H2
L2
1D wavelet transform + JPEG 2000 coding = 3D-JPEG 2000
HL1
HH1LH1
HL2
HH2
LL2
LH2
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Engineering
Drawbacks
Does not effectively use the redundancy in the 4th 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/AVCLatest video coding standard uses motion compensation and estimation.
Source: www.vcodex.com
Department of Electrical Engineering and Computer
Engineering
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!!
Department of Electrical Engineering and Computer
Engineering
Approach One: H.264-VOL
Volume 1
Slice s
Volume 2 Volume n
. . . . .
Slice s Slice s
Slice 1 Slice 1 Slice 1
Apply H.264/AVC on slices arranged as shown above
Results:
Compression Technique Compression ratio
JPEG2000 2.55:1
JPEG-LS 3.06:1
3D-JPEG 2000(VOL) 3.15:1
H.264-VOL 3.89:1
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Engineering
Approach Two: H.264-TIME
Volume 1 Volume 2 Volume n
. . . . .
. . . . .
. . . . .
Slice 1 Slice 1 Slice 1
Slice s Slice s Slice s
Apply H.264/AVC on slices arranged as shown above
Results:
Compression Technique Compression ratio
JPEG2000 2.55:1
JPEG-LS 3.06:1
3D-JPEG2000 (Time) 7.37:1
H.264-TIME 12.38:1
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H.264 applied across time H.264-TIMEVolume 1 Volume 2 Volume n
. . . . .
. . . . .
. . . . .
Slice 1 Slice 1 Slice 1
Slice s Slice s Slice s
Best compression performance
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Engineering
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 eachimage slice.
Department of Electrical Engineering and Computer
Engineering
Difference between slices
DifferenceH.264
MC+
entropycoder
(CABAC)
. . . . .
. . . . .
. . . . .
. . .
Difference Difference
Slice 1
Slice s
Difference 2
Difference s
Difference 2
Difference s
Difference 2
Difference s
Volume 1 Volume 2 Volume n
Reference slice Reference slice
Slice 1
Slice s
Reference slice
Slice 1
Slice s
s coded bit-streams
Slice 1 Slice 2 Difference
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Engineering
Residual frames
H.264 MC H.264 MC H.264 MC
H.264MC+
entropy coder
(CABAC)
. . . . .
. . . . .
. . . . .
MVs+ MVs+ MVs+
Volume 1 Volume 2 Volume n
Residual 2 Residual 2
Residual s Residual s
s coded bit-
streams
Slice 1
Slice s
Reference slice
Slice 1
Slice s
Reference slice
Slice 1
Slice s
Reference slice
Original slice Predicted Residual
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Engineering
Results
CompressionTechnique
Improvement
H.264Difference
H.264Residual
3D-JPEG2000 100% 100%
H.264-TIME 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
Low motion areas lossy
High motion areas lossless
Future improvements
Lossless
Lossy
Department of Electrical Engineering and Computer
Engineering
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
Future improvements
First slice
Second slice
Department of Electrical Engineering and Computer
Engineering
Questions?