Three-dimensional encoding/two-dimensional decoding of medical data

Menegaz, Gloria; Thiran, Jean-Philippe

doi:10.1109/tmi.2003.809689

Cited by 41 publications

(16 citation statements)

References 27 publications

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“…The minimum residual block, , is then defined as the element of with the minimum SAD value (4) We then compute the energy of block and the energy of block . The energy of a block is defined as (5) where is the value of the coefficient at position in block . If the energy of block is less than the energy of block , we employ the reference block , associated to to predict ; otherwise no prediction is employed.…”

Section: A Block-based Intraband Prediction Methodsmentioning

confidence: 99%

“…Most of these methods exploit correlations between slices within the data volume to improve the compression performance by either employing a 3D discrete wavelet transform (3D-DWT) [1]- [5] or motion compensation and estimation [6]. Although these methods attain the three desired properties listed before, they do not exploit some of the inherent characteristics of medical image data, such as the symmetry of the depicted region of interest (ROI); thus leaving room for further improvement.…”

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confidence: 99%

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Symmetry-Based Scalable Lossless Compression of 3D Medical Image Data

Sánchez

Abugharbieh

Nasiopoulos

2009

IEEE Trans. Med. Imaging

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Abstract-We propose a novel symmetry-based technique for scalable lossless compression of 3D medical image data. The proposed method employs the 2D integer wavelet transform to decorrelate the data and an intraband prediction method to reduce the energy of the sub-bands by exploiting the anatomical symmetries typically present in structural medical images. A modified version of the embedded block coder with optimized truncation (EBCOT), tailored according to the characteristics of the data, encodes the residual data generated after prediction to provide resolution and quality scalability. Performance evaluations on a wide range of real 3D medical images show an average improvement of 15% in lossless compression ratios when compared to other state-of-the art lossless compression methods that also provide resolution and quality scalability including 3D-JPEG2000, JPEG2000, and H.264/AVC intra-coding.

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Section: A Block-based Intraband Prediction Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

Symmetry-Based Scalable Lossless Compression of 3D Medical Image Data

Sánchez

Abugharbieh

Nasiopoulos

2009

IEEE Trans. Med. Imaging

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“…Therefore, coding systems should be devised while keeping in mind the device in which they will be executed [29], [30]. There are many works concerned with the computational complexity of techniques and algorithms [31], [32] deployed to code 3D images [11], [14], [19], [20], [22], [33]- [36].…”

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confidence: 99%

Lossy-to-lossless 3D image coding through prior coefficient lookup tables

Aulí-Llinís

Marcellin

Serra-Sagristí

et al. 2013

Information Sciences

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Abstract-This paper describes a low-complexity, highefficiency, lossy-to-lossless 3D image coding system. The proposed system is based on a novel probability model for the symbols that are emitted by bitplane coding engines. This probability model uses partially reconstructed coefficients from previous components together with a mathematical framework that captures the statistical behavior of the image. An important aspect of this mathematical framework is its generality, which makes the proposed scheme suitable for different types of 3D images. The main advantages of the proposed scheme are competitive coding performance, low computational load, very low memory requirements, straightforward implementation, and simple adaptation to most sensors.

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“…The most important and fundamental problem is that wavelets are not suitable descriptors of images with sharp edges [7]. Since coronary angiographic images are highly contrasted, very sharp edges are juxtaposed to a smooth background.…”

Section: Introductionmentioning

confidence: 99%