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Neuroimaging in Nuclear Medicine
Published in Michael Ljungberg, Handbook of Nuclear Medicine and Molecular Imaging for Physicists, 2022
Anne Larsson Strömvall, Susanna Jakobson Mo
A common type of benign brain tumour is meningioma, arising from cells in one of the membranes (meninges) around the brain. There are several types of malignant primary brain tumours. These may arise from any cell type in the brain. For example, a type of malignant tumour occurring in children and called medulloblastoma, arises from nerve cells. However, the largest group of brain tumours in adults are called gliomas, arising from different kind of supporting cells in the brain, the glia cells. There are different types of gliomas. For example, a subtype of glioma called astrocytoma and glioblastoma multiforme arise from astroglia cells, and oligodendrogliomas arise from glia cells called oligodentrocytes. Gliomas may also be classified according to malignancy, as in the WHO-classification [1], which by characterization of specific features in the tumour cells separates them into four grades of malignancy; a WHO grade I tumour is benign and a grade IV tumour is highly malignant.
Image Edge Detection Using Fractional Conformable Derivatives in Liouville-Caputo Sense for Medical Image Processing
Published in Devendra Kumar, Jagdev Singh, Fractional Calculus in Medical and Health Science, 2020
J. E. Lavín-Delgado, J. E. Solís-Pérez, J. F. Gómez-Aguilar, R. F. Escobar-Jiménez
A meningioma is a tumour that arises from a layer of tissue (the meninges) that covers the brain and spine [54]. Although most meningiomas are encapsulated benign tumours with limited numbers of genetic aberrations, their intracranial location often leads to serious and potentially lethal consequences [55]. By using an MRI image, it is possible to determine the location of meningiomas; however, the detection and accurate diagnosis of meningiomas can be drastically improved with the use of the proposed operator due to its high capacity to detect edges and textures. The T1-weighed MRIs shown in Figures 1.10through 1.13 were taken from [56-59], respectively. In these figures, the boundaries of the meningiomas are correctly defined even in noisy images. By using the fractional conformable Gaussian edge, it is possible to make a better identification of the meningiomas achieving a more accurate diagnosis. On the other hand, with the boundaries of the meningiomas being well-defined, it is possible to obtain a better estimate of their size. In conclusion, the fractional conformable operator is able to identify much better the edges in MRI images for meningioma identification than classic operators such as Sobel, Prewitt, Roberts, LoG, and Canny.
The Role of Multiparametric MR Imaging—Advanced MR Techniques in the Assessment of Cerebral Tumors
Published in Ioannis Tsougos, Advanced MR Neuroimaging, 2018
A meningioma is a tumor that arises from the meninges, that is the membranous layers surrounding the central nervous system. Although not technically a brain tumor (it is situated on the brain), it is included in this category because it may compress or squeeze the adjacent brain. Therefore, meningiomas are the most common extra-axial cerebral tumors, and due to their characteristic location a relatively straightforward diagnosis is achieved. However, although the majority of meningiomas are benign, they can have malignant transformations. According to the WHO classification system, there are three types of meningiomas. The majority of meningiomas (up to 90%) are benign or Grade I and usually full recovery is achieved with surgical resection. Grade II (atypical) and Grade III (malignant) meningiomas are less common but more aggressive than Grade I, thus they are more likely to recur even after complete resection. The differences between benign and atypical/malignant meningiomas relate to the number of mitoses, cellularity, and nucleus-to-cytoplasm ratio as well as their histologic patterns (Perry et al., 2007). Conventional MR imaging provides useful information regarding their localization and morphology, however there can be cases where meningiomas may have atypical imaging findings, like heterogeneous contrast enhancement and necrotic areas mimicking high-grade tumors. Hence, a correct diagnosis and accurate histologic grading is of great importance for beneficial treatment planning. An atypical/malignant meningioma with a large heterogeneous enhancement and intense mass effect is illustrated in Figure 9.8.
A novel triple-level combinational framework for brain anomaly segmentation to augment clinical diagnosis
Published in Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 2022
Senthilkumar Natarajan, Vishnuvarthanan Govindaraj, Ravipudi Venkata Rao Narayana, Yu-Dong Zhang, Pallikonda Rajasekaran Murugan, Karunanithi Kandasamy, Khurram Ejaz
Figure 4 shows the segmented output of the MR brain images with meningioma carcinoma. This type of tumour is majorly benign and occurs in the outer membrane of the brain and the spinal cord (meninges). The proposed algorithm has been tested on the real patient MR brain image from our collected clinical dataset. The final results exhibited in Figure 4 show the efficiency of the suggested JA-FCM algorithm and reveal the superiority over the other algorithms.