Hugo Aerts


Dr. Aerts is Associate Professor at Harvard Medical School and Director of the Computational Imaging and Bioinformatics Laboratory (CIBL) at the Dana-Farber Cancer Institute. Dr. Aerts’ group focuses on the development and application of Artificial Intelligence (AI) methods applied to medical imaging data, pathology, and genomic data. Furthermore, he is a PI-member of the Quantitative Imaging Network (QIN) and Informatics Technology for Cancer Research (ITCR) initiatives of the NIH.

Artificial Intelligence in Radiology

Artificial Intelligence (AI) algorithms, deep learning in particular, have recently spurred remarkable progress in image recognition tasks. This has lead to a myriad of applications in the medical image analysis field, propelling it forward at a rapid pace. Historically in the radiology practice, trained physicians visually assess medical images for diagnosis, treatment planning, and response assessment. AI methods excel in automatically recognizing complex patterns in imaging data and provide quantitative, rather than qualitative, assessments of radiographic characteristics. This process is also referred to as ‘radiomics’. In this talk, Dr. Aerts will discuss recent developments from his group and collaborators performing research at the intersection of radiology, bioinformatics, and data science. Also, he will discuss recent work of building a computational image analysis system to extract a rich radiomics set and use these features to build radiomic signatures. The presentation will conclude with a discussion of future work on building integrative systems incorporating both molecular and phenotypic data to improve cancer therapies.