Video Compression for Medical Imaging

by David Gibsonby David Gibson

Contents Part 1: Compression BackgroundPart 1: Compression Background

Fundamentals of CompressionFundamentals of Compression Video & Motion CompensationVideo & Motion Compensation

Part 2: Medical ImagingPart 2: Medical Imaging Example of the data + JPEG /Wavelet encodingExample of the data + JPEG /Wavelet encoding Motion compensationMotion compensation Region of interest (ROI) codingRegion of interest (ROI) coding

Part 1

Video Compression ReviewVideo Compression Review

Foundations of Compression

The Foundations of Compression involves The Foundations of Compression involves looking at the data.looking at the data.

Foundations of Compression

Foundations of Compression

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DCT

Video Compression

Main Classification of Video Compression Methods

Intra-frame methodsIntra-frame methods

Uses single framesUses single frames e.g. MJPEG - JPEG e.g. MJPEG - JPEG

applied to videoapplied to video

Inter-frame methodsInter-frame methods

Uses temporal Uses temporal informationinformation

e.g. MPEG-1/2, H.263e.g. MPEG-1/2, H.263 Usual approach to Usual approach to

video compressionvideo compression

Inter-frame methods

Use Motion CompensationUse Motion Compensation

Motion Compensation

Exploitation of temporal redundancy.Exploitation of temporal redundancy.

Frame 30 Frame 31

Motion Compensation

How Do We Motion Compensate? Compensate each pixel separately with its own Compensate each pixel separately with its own

motion vector?motion vector?

Huge amount of motion data - More data than the Huge amount of motion data - More data than the original image!original image!

Can’t afford to motion compensate each Can’t afford to motion compensate each individual pixel.individual pixel.

ErrorData

MotionData

Solution

One motion vector for a group of pixels.One motion vector for a group of pixels. Based on looking at the data.Based on looking at the data.

Block Matching

Foundation of most current video coders Foundation of most current video coders (MPEG 1/2, H.261/3).(MPEG 1/2, H.261/3).

Conclusions (part 1)

Presented a brief summary of video Presented a brief summary of video compression methodscompression methods

Part 2

Video Compression of Medical Video Compression of Medical ImagesImages

Medical Imaging

Angiogram Video;Angiogram Video; Pictures taken of the heart at 30 frames/secondPictures taken of the heart at 30 frames/second 512x512 images - 8 bits/pixel512x512 images - 8 bits/pixel Typical procedure - 5 minutesTypical procedure - 5 minutes

Resulting in 2.5GBytes of data per patient.Resulting in 2.5GBytes of data per patient. @64Kbits/sec - 80 hours.@64Kbits/sec - 80 hours. @10Mb/sec - 30 minutes.@10Mb/sec - 30 minutes.

Summary

Going to look at 3 aspects of the research Going to look at 3 aspects of the research we’ve been doing:we’ve been doing: Example of the data + JPEG/Wavelet encodingExample of the data + JPEG/Wavelet encoding Motion compensationMotion compensation Region of interest (ROI) codingRegion of interest (ROI) coding

Example Angiogram Sequence

Example JPEG Coding

Still Frame Coding Methods : Wavelet

Similar Similar frequency approachfrequency approach to DCT. to DCT. But considered to give better results.But considered to give better results. Operation on the whole image.Operation on the whole image.

JPEG/Wavelet Comparison

0.2 0.4 0.6 0.8 1 1.20

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Resultant Bit Rate (Bits/Pixel)

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Inter-frame Prediction

Use an ‘off the shelf’ video coder?

Typical results for an Typical results for an angiogram image angiogram image @0.8bpp.@0.8bpp.

Comparison of intra- Comparison of intra- and inter-frame methods and inter-frame methods using DCT.using DCT.

Motion compensation performs badly for this Motion compensation performs badly for this type of data.type of data.

Key Point: Compression effectiveness Key Point: Compression effectiveness depends upon the datadepends upon the data

Motion Compensation - Failure?

Conventional motion compensation assumptionsConventional motion compensation assumptions:: Distinct, opaque objects moving simply.

Also, angiogram images contain high frequency uncorrelated texture.

Motion Compensation - Failure?

Objects in angiograms are partially Objects in angiograms are partially transparent.transparent.

Image is made up of several Image is made up of several layerslayers of bones of bones and tissue, all moving differently.and tissue, all moving differently.

Conventional motion compensation model Conventional motion compensation model doesn’t apply well.doesn’t apply well.

Region of Interest (ROI) Coder

Aim is to shift the allocation of bits from Aim is to shift the allocation of bits from uninteresting areas of the image to more uninteresting areas of the image to more interesting ones.interesting ones.

Makes more efficient use of the available Makes more efficient use of the available bits.bits.

ROI Example : Simple Case

Manual segmentation.Manual segmentation.

ROI non-ROI

Example ROI coder

Example of transferring bits from non-ROI Example of transferring bits from non-ROI to ROIto ROI

ROI : Simple Case - Results

Much lower error in the ROI at the expense Much lower error in the ROI at the expense of the non-ROI.of the non-ROI.

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RD Graph with ROI - DFD Data (Global MC - M.Black)

No ROI (baseline comparison)ROI Distortion Non-ROI Distortion

Key Aim

Reallocate bits from diagnostically Reallocate bits from diagnostically unimportant areas into diagnostically unimportant areas into diagnostically interesting onesinteresting ones

Eye Tracking (proof of concept) Experiment to identify Experiment to identify

key areas of an key areas of an angiogram image.angiogram image.

Example Results (Expert)

Example Results (Sandra)

Eye Tracking

Significant areas of Significant areas of the image are not the image are not directly examined.directly examined.

Methods of measuring image quality:Methods of measuring image quality: Classical RMS - Measure of intensity level Classical RMS - Measure of intensity level

difference for each pixel.difference for each pixel. Perceptual measure - Takes in to account the Perceptual measure - Takes in to account the

observer.observer.

Quality Measure and Results

Quality Measure and Results

Perceptual Perceptual measurement of measurement of image quality.image quality.11 22 33 44 55

PoorPoor PerfectPerfect

OriginalOriginal CompressedCompressed

What’s next for video compression research?

More efficient compression methods - to More efficient compression methods - to better take advantage of data (e.g. object better take advantage of data (e.g. object based)based)

Perceptual coding - introducing the viewer Perceptual coding - introducing the viewer into the equationinto the equation

Questions?