On the Use of Standards for Microarray Lossless

ImageCompression

Author :Armando J. Pinho*, Antonio R. C.Paiva, and Antonio J. R. NevesSource :IEEE TRANSACTIONS ON

BIOMEDICAL ENGINEERING,VOL.53, NO. 3, MARCH 2006Speaker: Ren-Li Shen1

Outline

Introduction Specialized Methods Standard Methods

Experimental Results Sensitivity to Noise

Conclusion

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Introduction Standard image coding techniques

applied to the lossless compression of microarray images JPEG2000 JBIG JPEG-LS

Try to overcome some of the drawbacks Image sources

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Introduction

Trying to identify compression technologies Provide efficient lossless compression

results Offer relevant features for the

microarray image compression problem

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Outline

Introduction Specialized Methods Standard Methods

Experimental Results Sensitivity to Noise

Conclusion

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Specialized Methods

Four published methods Jornsten et al.

Gridding and segmentation Using a low complexity lossless compression

algorithm SLOCO

Hua et al. Transform-based coding technique Segmentation is using the Mann-Whitney

algorithm Separately spots and background

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Specialized Methods Faramarzpour et al.

Locating and extracting the microarray spots Transforming the ROI(region of interest) into

an one-dimensional signal Lonardi et al.

Lossless and lossy compression algorithms for microarray images

Fully automatic gridding procedure Similar to Faramarzpour’s method

Split into two channels Foreground Background

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Outline

Introduction Specialized Methods Standard Methods

Experimental Results Sensitivity to Noise

Conclusion

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Standard Methods

JBIG Context-based arithmetic coding Focused on bi-level imagery

JPEG-LS Predictive coding Lossless compression of continuous-tone

images JPEG2000

Transform based Providing a wide range of functionalities

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Standard Methods(Experimental Results)

Three different publicly available sources Apo AI set (32) ISREC set (14) MicroZip (3)

Image size ranges from 1000 × 1000 to 5496 × 1956 pixels

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Standard Methods(Experimental Results)

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Standard Methods(Sensitivity to Noise)

8bit-planes of cDNA microarray images are close to random and incompressible Result in some degradation in the

compression performance Separated the images

8bit-planes 16bit-planes

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Standard Methods(Sensitivity to Noise)

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Outline

Introduction Specialized Methods Standard Methods

Experimental Results Sensitivity to Noise

Conclusion

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Conclusion

JPEG-LS gives the best lossless compression performance

JBIG was consistently better than JPEG2000

The future of microarray image compression depends on special-purpose

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