Post on 03-Jan-2016
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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