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Differentiating pediatric brain tumors based on MR spectroscopy with machine learning

Brasz, M.F. (2020) Differentiating pediatric brain tumors based on MR spectroscopy with machine learning.

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Abstract:The attainment of an accurate diagnosis is key in treatment planning in pediatric neuro-oncology, because treatment and prognosis are based on tumor location, histopathology and staging. Magnetic resonance (MR) spectroscopy during routine scanning could improve diagnostic value of imaging and aid in differentiation of pediatric brain tumors earlier in the diagnostic stage. Imaging at cellular level remains impossible, but MR spectroscopy provides direct insight into biochemical processes in cells. Metabolism in cancer cells differs for different tumor types. Several studies showed the added value of MR spectroscopy in differentiating tumors types. Therefore we aim at developing a tool based on machine learning (ML) that can help radiologists with assessing brain tumor type.
Item Type:Essay (Master)
Faculty:TNW: Science and Technology
Programme:Technical Medicine MSc (60033)
Link to this item:https://purl.utwente.nl/essays/83119
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