УДК: 004.932.2

Geometrical normalization of three-dimensional biomedical images for efficient presentation and compression by means of octrees

Zhdanov, I.N., Kapliev N.N., Potapov, A.S., Shcherbakov, O.V.

Publication in Journal of Optical Technology

For Russian citation (Opticheskii Zhurnal):

Жданов И.Н., Каплиев Н.Н., Потапов А.С., Щербаков О.В. Геометрическая нормализация трехмерных биомедицинских изображений для эффективного представления и сжатия с помощью октодеревьев // Оптический журнал. 2012. Т. 79. № 11. С. 36–40.

Zhdanov I. N., Kapliev N. N., Potapov A. S., Shcherbakov O. V. Geometrical normalization of three-dimensional biomedical images for efficient presentation and compression by means of octrees [in English] // Opticheskii Zhurnal. 2012. V. 79. № 11. P. 36–40.

For citation (Journal of Optical Technology):

I. N. Zhdanov, N. N. Kapliev, A. S. Potapov, and O. V. Shcherbakov, "Geometrical normalization of three-dimensional biomedical images for efficient presentation and compression by means of octrees," Journal of Optical Technology. 79(11), 704-707 (2012). https://doi.org/10.1364/JOT.79.000704

Abstract:

This paper discusses a method of compressing three-dimensional biomedical images with losses, based on representing the data in the form of an octree. A modification of the method by geometrical normalization (equalization) of the image is proposed. It is shown that the proposed method has greater efficiency than the compression obtained when one exclusively uses the method based on an octree with losses but with a definite level of noise suppression.

Keywords:

image compression, biomedicine, octree, alignment images

OCIS codes: 100.6890, 100.6950

References:

1. L. Soares, C. Menier, B. Raffin, and J.-L. Roch, “Parallel adaptive octree carving for real-time 3D modeling,” in IEEE Virtual Reality Conference, 2007, pp. 273–274.
2. R. Szeliski, “Rapid octree construction from image sequences,” CVGIP: Image Understand. 58, No. 1, 23 (1993).
3. R. A. Siddiqui, I. Celasun, and U. Bayazit, “Octree-based compression of volumetric and surface 3D point cloud data,” in Proceedings of the 13th International Conference on Virtual Systems and Multimedia, VSMM, 2007, pp. 278–282.
4. P. V. Kochunov, J. L. Lancaster, and P. T. Fox, “Accurate high-speed spatial normalization using an octree method,” NeuroImage 10, 724 (1999).
5. I. N. Zhdanov, A. S. Potapov, and O. V. Shcherbakov, “Method of compressing three-dimensional biomedical images, based on the representation of information in the form of an octree,” Nauch. Tekhn. Vest. Informats. Tekh. Mekh. Optiki 79, No. 3, 100 (2012).