In this talk, I will overview our progress in the INSILEX Programme.

We envision a paradigm shift in medical device innovation where quantitative sciences are exploited to carefully engineer medical device designs, explicitly optimize clinical outcomes, and thoroughly test side effects before being marketed.
INSILEX is underpinned by Computational Medicine, an emerging discipline devoted to developing quantitative approaches for understanding the mechanisms, diagnoses, and treatment of human disease through the systematic application of mathematics, engineering, and computational science.
Dealing with the extraordinary multi-scale complexity and variability intrinsic to human biological systems and health data demands radically new approaches compared to methods for manufactured systems. Within this framework, INSILEX extensively uses medical image computing, a mature field challenged by the progress made across all medical imaging technologies and more recent breakthroughs in biological imaging.

We advocate for “Precision Imaging”, not as a new discipline but as a distinct emphasis in medical imaging, unifying the efforts behind mechanistic and phenomenological model-based imaging. This talk summarizes and formalizes our vision of Precision Imaging for Precision Medicine and highlights connections with past research and our current focus on large-scale computational phenomics and in silico clinical trials.

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Medical Image analysis has grown into a matured field challenged by the progress made across all medical imaging technologies and more recent breakthroughs in biological imaging. the cross-fertilisation between medical image analysis, medical imaging physics and technology, and domain knowledge from medicine and biology has spurred a truly interdisciplinary effort that stretched outside the original boundaries of the disciplines that gave birth to this field and created stimulating and enriching synergies.

Precision imaging is not a new discipline but rather a distinct emphasis in medical imaging born at the crossroads between and unifying the efforts behind mechanistic and phenomenological model-based imaging. Precision imaging is characterised by being descriptive, predictive and integrative. It captures three main directions in the effort to deal with information deluge in imaging sciences and thus achieves wisdom from data, information and knowledge. Precision imagin can lead to carefully and mechanistically engineered imaging biomarkers and the use of medical imaging-based computational modelling and simulation for improved regulatory science and innovation of medical products.

This talk summarises and formalises our vision of Precision Imaging for Precision Medicine and highlights some connections with past research and our current focus on large-scale computational phenomics and in silico clinical trials.