Primary and Metastatic Brain Tumours Assessed with the Brain and Torso [18F]FDG PET/CT Study Protocol—10 Years of Single-Institutional Experiences

According to the international societies’ recommendations, the 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography/computed tomography ([18F]FDG PET/CT) technique should not be used as the method of choice in brain tumour diagnosis. Therefore, the brain region can be omitted during standard [18F]FDG PET/CT scanning. We performed comprehensive literature research and analysed results from 14,222 brain and torso [18F]FDG PET/CT studies collected in 2010–2020. We found 131 clinically silent primary and metastatic brain tumours and 24 benign lesions. We concluded that the brain and torso [18F]FDG PET/CT study provides valuable data that may support therapeutic management by detecting clinically silent primary and metastatic brain tumours.

Automatic Brain Tumour Diagnosis and Segmentation: based on SVM Algorithm

Brain tumour is undesirable expansion of destructive cell in or around the cranium. It can directly attack our healthy brain cell within the skull or it might invasion indirectly from disparate organs of the body such as lung cancer, breast lump. Its size becomes double within 25-30 days. Brain tumour is one of the highest threatening illnesses among cancerous diseases. Unfortunately possibility of death patients from brain tumour is to a greater extent in contrast with other illness. If we didn’t treat the cerebrum tumour at near the beginning the possibility of patient death will be very high in just one half year. Hence it’s very important for the research to find away to automatically recognize brain tumour and classify it to cancerous and non-cancerous tumor.That’s why these day’s one of the most widely research zone in image processing is brain tumor recognition and categorization. This article present various phase involves in brain cancer recognition and categorization such as pre-processing, cleavage, characteristics extraction, and classification of brain tumour by utilizing SVM algorithm .The proposed system execution and analysis was examined which achieved favorable outcome, high accuracy at minimal time in contrast weigh the research completed previously.

Brain Tumour Detection using Fine-Tuning Mechanism for Magnetic Resonance Imaging

In this paper, new brain tumour detection method is discovered whereby the normal slices are disassembled from the abnormal ones. Three main phases are deployed including the extraction of the cerebral tissue, the detection of abnormal block and the mechanism of fine-tuning and finally the detection of abnormal slice according to the detected abnormal blocks. Through experimental tests, progress made by the suggested means is assessed and verified. As a result, in terms of qualitative assessment, it is found that the performance of proposed method is satisfactory and may contribute to the development of reliable MRI brain tumour diagnosis and treatments.