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Controlling cancer requires comprehensive understanding of the molecular, cellular, and organizational properties of tumor tissue. While clinical pathology has served as [...]

Magnetic Resonance Imaging (MRI) allows for the noninvasive exploration of animal and human anatomy. The focus of this project was to evaluate automatic segmentation rout [...]

The goal of this project was to evaluate the feasibility of machine learning methods based on feature extraction and classification for differentiating benign and maligna [...]

This thesis presents a suite of deep learning frameworks designed to address key challenges in the analysis of Electron Microscopy (EM) images of cancer cells, which are [...]

The detection of cancer at its early stages requires the analysis of new biomarkers that are specific to the tumor and have less background than conventional biomarkers. [...]

Attenuation correction (AC) in PET/MR imaging significantly alters the displayed PET signal. Modern AC methods forgo the process of directly calculating attenuation throu [...]

Patient stratification is essential for addressing breast cancer's inter- and intra-heterogeneity. While the PAM50 classifier is widely regarded to be the gold standard f [...]

Medical images provide a non-invasive means of assessing structural and functional changes within the human body. They are a rich source of information on the internal bo [...]