Somsubhra Saha , Rajdip Mitra , Md. Mohi Uddin , Md. Akhtaruzzaman , Hamad Al Mohamadi , Joydeep Chowdhury
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引用次数: 0
Abstract
The multifractal study of tumorous and normal brain MRI images has been reported. The brain MRI images recorded at the axial, colonal, and sagittal planes were used to perform the Multifractal Detrended Fluctuation Analysis (MFDFA) study. The nonlinear graphs of h(q) vs. q and τ(q) vs. q primarily depict that the tumorous MRI images are multifractal, while the normal brain MRI images don't show any sign of multifractal features. The tumorous brain MRI images are multifractal since their singularity spectra exhibit a bell-curve pattern with finite spectral widths (W) in each of the three planes. Interestingly, the MRI images of normal brain does not exhibit such phenomenon. The presence of multifractality in tumor cells as concluded from this manuscript will definitely provide a leeway for other researchers to explore the calculations further in order to identify the benign and malignant tumors, which we believe may exhibit different degrees of multifractalities. For both the tumorous and non-tumorous images, the MF-DFA tool was also used to find their asymmetry indices (B) and correlation coefficients (γ). These investigations lead us to conclude that, multifractality may be used to differentiate between the tumorous and non-tumorous brain MRI images in the Axial, Colonal and Sagittal planes. Furthermore, the findings of this study might encourage other researchers to execute MFDFA analyses at different phases of tumor growth and radiation.
肿瘤和正常脑MRI图像的多重分形研究已被报道。在轴、结肠和矢状面记录的脑MRI图像用于进行多重分形去趋势波动分析(MFDFA)研究。h(q) vs. q和τ(q) vs. q的非线性图主要描述了肿瘤MRI图像具有多重分形特征,而正常脑MRI图像没有显示任何多重分形特征的迹象。肿瘤脑MRI图像是多重分形的,因为它们的奇异光谱在三个平面上都表现出有限光谱宽度(W)的钟形曲线模式。有趣的是,正常大脑的核磁共振成像并没有显示出这种现象。本文总结的肿瘤细胞多重分形的存在,必将为其他研究人员进一步探索计算提供余地,以识别良性和恶性肿瘤,我们认为这些肿瘤可能表现出不同程度的多重分形。对于肿瘤和非肿瘤图像,也使用MF-DFA工具找到它们的不对称指数(B)和相关系数(γ)。这些研究使我们得出结论,多重分形可以用于区分轴位、结肠位和矢状位的肿瘤和非肿瘤脑MRI图像。此外,本研究的发现可能会鼓励其他研究人员在肿瘤生长和放疗的不同阶段进行MFDFA分析。
期刊介绍:
Physica A: Statistical Mechanics and its Applications
Recognized by the European Physical Society
Physica A publishes research in the field of statistical mechanics and its applications.
Statistical mechanics sets out to explain the behaviour of macroscopic systems by studying the statistical properties of their microscopic constituents.
Applications of the techniques of statistical mechanics are widespread, and include: applications to physical systems such as solids, liquids and gases; applications to chemical and biological systems (colloids, interfaces, complex fluids, polymers and biopolymers, cell physics); and other interdisciplinary applications to for instance biological, economical and sociological systems.