2018
Geometrical study of astrocytomas through fractals and scaling analysis
F. Torres Hoyos. R. Baena Navarro, J.Vergara Villadiego, M. Guerrero-Martelo
Applied Radiation and Isotopes, Volume 141, November 2018, Pages 250-256
The tumor growth is a complex process characterized by the proliferation of uncontrollable cells which invade neighbor tissues. The understanding process of this type of phenomena is very relevant in order to establish diagnosis and proper therapy strategies and to start the valorization of its complexity with proper descriptors produced by the scaling analysis, which define the tumor growth geometry. In this work, obtained results through the scaling analysis for pilocytic astrocytomas, anaplastic and diffuse, are shown, which tumors of primary origin are. On them, it is calculated the fractal dimension and critical exponents of local roughness to characterize in vivo 3-D tumor growth. The acquisition of the images for this type of injuries was carried out according to the standard protocol used for brain radiotherapy and radiosurgery, i.e., axial, coronal and sagittal magnetic resonance T1 weighted images and comprising the brain volume for image registration. Image segmentation was performed by the application the k-means procedure upon contrasted images. The results show significant variations of the parameters depending on the tumor stage and its histological origin.
On complexity of post-processing in analyzing GATE-driven X-ray spectrum
arXiv:1807.09063v1 [cs.ET], 24 Jul 2018
Purpose: Computed Tomography (CT) imaging is one of the most influential diagnostic methods. In clinical reconstruction, an effective energy is used instead of total X-ray spectrum. This approximation causes an accuracy decline. To increase the contrast, single source or dual source dual energy CT can be used to reach optimal values of tissue differentiation. However, these infrastructures are still at the laboratory level, and their safeties for patients are still yet to mature. Therefore, computer modelling of DECT could be used.
Methods: We propose a novel post-processing approach for converting a total X-ray spectrum into irregular intervals of quantized energy. We simulate a phantom in GATE/GEANT4 and irradiate it based on CT configuration. Inverse Radon transform is applied to the acquired sinogram to construct the Pixel-based Attenuation Matrix (PAM). To construct images represented by each interval, water attenuation coefficient of the interval is extracted from NIST and used in the Hounsfield unit (HU) scale in conjunction with PAM. The CT image is modified by using of an associated normalized photon flux
and calculated HU corresponding to the interval.
Results: We demonstrate the proposed method efficiency via complexity analysis, using absolute and relative complexities, entropy measures, Kolmogorov complexity, morphological richness, and quantitative segmentation criteria associated with standard fuzzy C-means.
Conclusions: The irregularity of the modified CT images decreases over the simulated ones.
