Dynamic CT perfusion image data compression for efficient parallel processing

Barros, Renan Sales; Olabarriaga, Sílvia D.; Borst, Jordi; Walderveen, Marianne A.A. van; Posthuma, Jorrit S.; Streekstra, Geert J.; Herk, Marcel van; Majoie, Charles B. L. M.; Marquering, Henk A.

doi:10.1007/s11517-015-1331-6

Cited by 6 publications

(2 citation statements)

References 16 publications

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“…Being dynamic means the temporal (time series) information is included in the traditional images which requires even more powerful processing capabilities or even more aggressive compression techniques without dramatically degrading the image quality. A representative work of such subject is Barros et al 42 . This work integrated the parallel GPU architecture into a direct random access to the compressed CT perfusion data in the memory, minimizing the processing time of data reading/writing.…”

Section: Review Of Compression Techniquesmentioning

confidence: 99%

Software and algorithms for high-throughput multimodal experiments at advanced synchrotron light sources

Li¹,

Zhang²,

Liu³

et al. 2023

Conference on Infrared, Millimeter, Terahertz Waves and Applications (IMT2022)

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With advancements on synchrotron radiation instrumentations particularly the emergence of next-generation light sources with ultra-low emittance and high intensity, scientific experiments have shifted from 2D static to multidimensional dynamic characterizations with multimodal approaches, enabling new capabilities of probing structural and functional changes across multiple length scales with extreme spatial and temporal resolution. However, such advancement on synchrotron hardware imposes tremendous challenges on the data processing end. Effective software tools and algorithms addressing image denoising, segmentation and data compression problems can be of great use to alleviate the burden, fully releasing the power of advanced instrumentations. Instead of separately utilizing modular image processing algorithms, this review suggests a unified experimental control and data acquisition software framework that naturally interfaces and integrates advanced software and algorithms with extensive AI assistance would be best suitable for next-generation beamlines. The review will also discuss prospective applications artificial intelligence and large-scale high performance computing infrastructures could bring about to facilitate scientific discoveries at next-generation synchrotron light sources.

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Section: Review Of Compression Techniquesmentioning

confidence: 99%

Software and algorithms for high-throughput multimodal experiments at advanced synchrotron light sources

Li¹,

Zhang²,

Liu³

et al. 2023

Conference on Infrared, Millimeter, Terahertz Waves and Applications (IMT2022)

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“…In the literature, the lossless coding techniques have been preferred than lossy compression technique for medical image coding over the last decade 6‐8 …”

Section: Introductionmentioning

confidence: 99%

Volumetric medical image compression using inter‐slice correlation switched prediction approach

Sharma

Sood²,

Puthooran³

2020

Int J Imaging Syst Tech

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With the advancement in medical data acquisition and telemedicine systems, image compression has become an important tool for image handling, as the tremendous amount of data generated in medical field needs to be stored and transmitted effectively. Volumetric MRI and CT images comprise a set of image slices that are correlated to each other. The prediction of the pixels in a slice depends not only upon the spatial information of the slice, but also the inter‐slice information to achieve compression. This article proposes an inter‐slice correlation switched predictor (ICSP) with block adaptive arithmetic encoding (BAAE) technique for 3D medical image data. The proposed ICSP exploits both inter‐slice and intra‐slice redundancies from the volumetric images efficiently. Novelty of the proposed technique is in selecting the correlation coefficient threshold (Tϒ) for switching of ICSP. Resolution independent gradient edge detector (RIGED) at optimal prediction threshold value is proposed for intra‐slice prediction. Use of RIGED, which is modality and resolution independent, brings the novelty and improved performance for 3D prediction of volumetric images. BAAE is employed for encoding of prediction error image to resulting in higher compression efficiency. The proposed technique is also extended for higher bit depth volumetric medical images (16‐bit depth) presenting significant compression gain of 3D images. The performance of the proposed technique is compared with the state‐of‐the art techniques in terms of bits per pixel (BPP) for 8‐bit depth and was found to be 31.21%, 27.55%, 21.89%, and 2.39% better than the JPEG‐2000, CALIC, JPEG‐LS, M‐CALIC, and 3D‐CALIC respectively. The proposed technique is 11.86%, 8.56%, 7.97%, 6.80%, and 4.86% better than the M‐CALIC, 3D CALIC, JPEG‐2000, JPEG‐LS and CALIC respectively for 16‐bit depth image datasets. The average value of compression ratio for 8‐bit and 16‐bit image dataset is obtained as 3.70 and 3.11 respectively by the proposed technique.

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Numerical Modeling for 4-D Self-Potential Resistivity Model

Xie

Cui

et al. 2022

Pure Appl. Geophys.

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Dynamic CT perfusion image data compression for efficient parallel processing

Cited by 6 publications

References 16 publications

Software and algorithms for high-throughput multimodal experiments at advanced synchrotron light sources

Software and algorithms for high-throughput multimodal experiments at advanced synchrotron light sources

Volumetric medical image compression using inter‐slice correlation switched prediction approach

Numerical Modeling for 4-D Self-Potential Resistivity Model

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