Evaluation of Tomographic Brain Reconstruction Techniques: Case of the Shepp-Logan Phantom

Abstract

Carcinogenic tumors are the leading cause of death in the world. When clinicians have excellent shot, they are able to detect a tumor early and eradicate it easily by chemotherapy or by simple surgery. We propose in this paper to compare different methods of tomographic reconstruction of the brain from the point of view of the quality of the image provided, in order to propose to the physicians the algorithms which guarantee them the best image results. We use two comparison metrics based on the PSNR (Peak Signal to Noise Ratio) and the HVS (Human Visual System). The association of these two objective and subjective criteria show that the methods which exploit the reconstruction of the samples by subset provide images of better quality.

New Ecg Signal Compression Model Based on Set Theory Applied to Images

“…Scales with 5, 6, 7 or 100 levels of appreciation can be used. Table 1 presents an example of a scale, this method is very widely used to validate a quantitative or objective metric [20], and it is what was used in the context of this article.…”

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“…3-5 The deterministic iterative methods which allow a better quantification of the noise have been implemented in the framework of this work, the most successful methods are the ART method [6][7] in its variants ART-DS, 7 kaczmarz, 8 Sym-Kaczmarz, 9 and the SIRT method 10 in its SIRT-DS 11 and Cimmino 10 variants. These iterative methods consist in the correction of the reconstructed image f by successive iterations.…”