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ROI-Based Compression Strategy of 3D MRI Brain Datasets for Wireless Communications - 20/05/20

Doi : 10.1016/j.irbm.2020.05.001 
D. Dhouib a, , A. Naït-Ali b , C. Olivier c , M.S. Naceur d
a École Nationale des Sciences de l'Informatique, Université de la Manouba, Laboratoire CRISTAL (GRIFT), 2010 La Manouba, Tunisia 
b Université Paris-Est Créteil (UPEC), Université de Paris 12, LiSSi, EA 3956, 122 rue Paul Armangot, 94400 Vitry sur Seine, France 
c Equipe RESYST (REseaux et SYStèmes de Télécommunication), Université de Poitiers, Institut XLIM UMR CNRS n°7252, 86962 Futuroscope Cedex, France 
d Institut National des Sciences Appliquées et de Technologie, Tunisia 

Corresponding author.
Sous presse. Épreuves corrigées par l'auteur. Disponible en ligne depuis le mercredi 20 mai 2020

Graphical abstract

Le texte complet de cet article est disponible en PDF.

Highlights

We propose a new strategy for the compression of 3D images.
It is a new compression scheme based on region of interest with an unequal protection.
The regions are compressed with different bitrates according to their relevance.

Le texte complet de cet article est disponible en PDF.

Abstract

Objectives

Because of the large amount of medical imaging data, the transmission process becomes complicated in telemedicine applications. Thus, in order to adapt the data bit streams to the constraints related to the limitation of the bandwidths a reduction of the size of the data by compression of the images is essential. Despite the improvements in the field of compression, the transmission itself can also introduce errors. For this reason, it is important to develop an adequate strategy which will help reduce this volume of data without having to introduce some distortion and resist the errors introduced by the channel noise during transmission. Thus, in this paper, we propose a ROI-based coding strategy and unequal bit stream protection to meet this dual constraint.

Material and methods

The proposed ROI-based compression strategy with unequal bit stream protection is composed of three parts: the first one allows the extraction of the ROI region, the second one consists of a ROI-based coding and the third one allows an unequal protection of the ROI bit stream.

First, the Regions Of Interest (ROI) are extracted by hierarchical segmentation of these regions according to a segmentation method based on the technique of Marker-based-watershed combined with the technique of active contours by level set. The resulting regions are selectively encoded by a 3D coder based on a shape adaptive discrete wavelet transform 3D-BISK, where the compression ratio of each region depends on its relevance in diagnosis. These obtained regions of interest are protected with an error-correcting code of Reed-Solomon type with a code rate that varies according to the relevance of the region by an unequal protection strategy (UEP).

Results

The performance of the proposed compression scheme is evaluated in several ways. First, tests are performed to study the impact of errors on the different bit streams. In the first place, these tests are carried out in order to study the effect of the variation of the compression rates on the different bit streams. Secondly, different Reed Solomon error-correcting codes of different code rates are tested at different compression rates on a BSC channel. Finally, the performances of this coding strategy are compared with those of SPIHT 3D in the case of transmission on a BSC channel.

Conclusion

The obtained results show that the proposed method is quite efficient in transmission time reduction. Therefore, our proposed scheme will reduce the volume of data without having to introduce some distortion and resist the errors introduced by the channel noise in the case of telemedicine.

Le texte complet de cet article est disponible en PDF.

Keywords : Image compression, Medical imaging, Wavelet transform, Wireless transmission, Regions of interest


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