With an increase in deep learning-based methods, the call for explainability of such methods
grows, especially in high-stakes decision making areas such as medical image analysis …

The extensive growth of data in the health domain has increased the utility of Deep Learning
in health. Deep learning is a highly advanced successor of artificial neural networks, having …

Advancements in digital pathology and computing resources have made a significant impact
in the field of computational pathology for breast cancer diagnosis and treatment. However …

Background: Multispectral autofluorescence lifetime imaging systems have recently been
developed to quickly and non-invasively assess tissue properties for applications in oral …

Conventional biomedical measurement and tests used for patient diagnosis are increasingly
digitized in the current clinical practice, which provides great opportunities for researchers to …

Artificial intelligence can play an important role in healthcare by analysing medical images
to provide diagnostic decision support to medical professionals. This thesis explores novel …