Anum Masood

I am part of 180 ̊ N Project: Clinical PET/MRI in collaboration with St Olav’s Hospital. In Work Package-5, we aim to develop and validate new machine learning methods that exploit the quantitative nature of the PET and MR images. We will develop a pipeline for pre-processing and quality assurance of the acquired images, as well as a toolbox with machine learning algorithms focusing on region classification and detection of change over time. These methods will be applied to answer open clinical questions in various types of cancer i.e., prostate, lymphoma, breast, lung, and dementia. Currently, I am developing a deep learning model for automated segmentation and localization of lymph nodes using FDG PET/MRI Images and radiomics data. My research is in the interdisciplinary fields of medical image analysis, bioinformatics, and artificial intelligence, with an impact on advancing cancer detection and computer-assisted diagnosis using machine learning.