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At least 613 records · Page 34Linked to original sources
PubMed2005

Compression and reconstruction of sorted PET listmode data.

BACKGROUND: In nuclear medicine data can be stored in histogram or listmode format. The most popular histogram format is the planar projection format. Due to the increase in detector blocks, the improved energy resolution and the trends towards time of flight, dynamic and gated imaging, it can be more appropriate to store the data in listmode format. The size of the storage in this format increases linearly with the number of properties (positions, energy, time info) while the histogram format increases exponentially. However, the datasize of listmode data also increases linearly with the number of coincidences. Due to the high number of counts in 3D PET this will lead to very large datasets. Therefore a good compression algorithm for listmode data is very important. METHODS: A sorting and compression method is proposed to reduce the amount of space needed to store the listmode dataset. One event is represented by one number without any information loss compared to the original listmode file. The next step is to sort all events into an array of increasing numbers. These data are compressed by the gzip routine. One of the advantages of 3D PET listmode reconstructions is that they result in a more uniform resolution across the field of view (FOV), which is not always true for other reconstruction algorithms. This improved resolution is shown for the listmode data of a gamma camera operating in PET mode. RESULTS: First the effect of positional accuracy in the listmode dataset is evaluated by comparing resolution in the reconstructions. It is shown that the highest accuracy is not necessary and a significant reduction in the size of the dataset can be obtained prior to lossless compression. A further reduction can be obtained by using the proposed sorting and compression techniques. It is shown that the storage space decreases linearly with the logarithm of the number of coincidences. The compression obtained by different acquisition matrices was compared. Finally it is shown that the 3D listmode reconstruction of sorted listmode data is faster because of improved cache behaviour. The method can be applied to any kind of listmode data. The compression factors will improve when the ratio of measured events to possible events increases.

Algorithms↗
PubMed2002

Irreversible compression of medical images.

The volume of data from medical imaging is growing at exponential rates, matching or exceeding the decline in the costs of digital data storage. While methods to reversibly compress image data do exist, current methods only achieve modest reductions in storage requirements. Irreversible compression can achieve substantially higher compression ratios without perceptible image degradation. These techniques are routinely applied in teleradiology, and often in Picture Archiving and Communications Systems. The practicing radiologist needs to understand how these compression techniques work and the nature of the degradation that occurs in order to optimize their medical practice. This paper describes the technology and artifacts commonly used in irreversible compression of medical images.

Artifacts↗
PubMed1994

Hydration and partial compressibility of biological compounds.

We review the results of compressibility studies on proteins, nucleic acids, and systematically altered low molecular weight compounds that model the constituents of these biopolymers. The model compound data allow one to define the compressibility properties of water surrounding charged, polar, and nonpolar groups. These results, in conjunction with compressibility data on proteins and nucleic acids, were used to define the properties of water that is perturbed by the presence of these biopolymers in aqueous solutions. Throughout this review, we emphasize the importance of compressibility data for characterizing the hydration properties of solutes (particularly, proteins, nucleic acids, and their constituents), while describing how such data can be interpreted to gain insight into role that hydration can play in modulating the stability of and recognition between biologically important compounds.

Animals↗
PubMed2006

Adaptive prediction trees for image compression.

This paper presents a complete general-purpose method for still-image compression called adaptive prediction trees. Efficient lossy and lossless compression of photographs, graphics, textual, and mixed images is achieved by ordering the data in a multicomponent binary pyramid, applying an empirically optimized nonlinear predictor, exploiting structural redundancies between color components, then coding with hex-trees and adaptive runlength/Huffman coders. Color palettization and order statistics prefiltering are applied adaptively as appropriate. Over a diverse image test set, the method outperforms standard lossless and lossy alternatives. The competing lossy alternatives use block transforms and wavelets in well-studied configurations. A major result of this paper is that predictive coding is a viable and sometimes preferable alternative to these methods.

Algorithms↗