Research contributions introduce technological innovations to address the main challenges in the cancer care cycle. Timely diagnosis is crucial for successful treatment. In this area, we are developing novel signal and image analysis techniques for early localization and grading (prognostic assessment of aggressiveness) of cancer. To this end, a broad spectrum of technologies is investigated, ranging from ultrasound to MRI and CT up to optical coherence tomography for accessible tumors. Along with advanced machine and deep learning algorithms for the interpretation of the data, new patient-specific models for prediction of cancer growth and response to treatment are developed that can support with the optimal treatment choice. Altogether this technology provides new clinical tools for accurate and effective planning and image guidance of advanced focal treatments. Treatment and follow-up can be further improved by real-time histological analysis based on dedicated optical imaging.