A Systematic Mapping Study of Low-Grade Tumor of Brain Cancer and CSF Fluid Detecting in MRI Images Through Multi-Algorithm Techniques

S. Saeed, Habibullah Bin Haroon, N. Jhanjhi, M. Naqvi, Muneer Ahmad
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引用次数: 3

Abstract

Low-grade tumor or CSF fluid, the symptoms of brain tumour and CSF liquid, usually requires image segmentation to evaluate tumour detection in brain images. This research uses systematic literature review (SLR) process for analysis of the different segmentation approach for detecting the low-grade tumor and CSF fluid presence in the brain. This research work investigated how to evaluate and detect the tumor and CSF fluid, supervised machine learning algorithm and segmentation method (3D and 4D segmentation process, supervised segmentation process, Fourier transformation, and Laplace transformation), and mentioned the details of publication selection with the publishing digital libraries bodies. Furthermore, this research discusses selected segmentation techniques to detect the low-grade tumor and CSF fluid in systematic mapping through systematic literature review (SLR) process.
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多算法技术在脑癌低分级肿瘤及脑脊液MRI图像检测中的系统定位研究
低级别肿瘤或脑脊液,脑肿瘤和脑脊液的症状,通常需要图像分割来评估脑图像中的肿瘤检测。本研究采用系统文献回顾(SLR)的方法,对检测颅内低级别肿瘤和脑脊液存在的不同分割方法进行分析。本课题研究了肿瘤和脑脊液的评估检测、监督机器学习算法和分割方法(三维和四维分割过程、监督分割过程、傅立叶变换和拉普拉斯变换),并与出版数字图书馆机构讨论了出版物选择的细节。此外,本研究通过系统文献回顾(SLR)过程讨论了在系统制图中检测低级别肿瘤和脑脊液的选择分割技术。
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