Are you a new(ish) Graduate or a super-enthusiastic Undergraduate student working with Medical Image data, and pondering over how to get that Deep Learning model to train with it? If so, we invite you to watch the BENDER video series that track the life and times of a new student who has just started working with AI technologies for medical imaging applications, and goes through the ups and downs of the journey to build a State-of-The-Art A.I model.
We hope through the experience of this student, you learn not to make the same mistakes, and get a head-start in your own exploration.
Abstract:
The BENDER series of videos is a high-level overview of Best Practices in Deep Learning for Medical Imaging, intended as a guide for a newcomer to this rapidly evolving field.
The premise is that of a new graduate student Satish, who is supported by a senior graduate student, Mike, through various steps in the process of building a state-of-the-art model to solve a medical image analysis problem. We start with a checklist of what to do when one receives clinical data, dealing with issues like data curation, anonymisation, exploratory statistics, etc. Then we move on to a short discussion on clinical terminology – how it is important for all the stakeholders in these interdisciplinary projects to communicate effectively. Next, we cover some tips and tricks around actually building a model: how one can go from a naive implementation to a state-of-the-art benchmark beating model on a publicly available data set. This also includes some practical advice on tools to use. Finally, we cover some under-appreciated topics like external test set evaluation, clinical relevance and robustness, and also bonus content on dealing with ‘reviewer 2’.
This short video series is complemented with a more thorough and updatable GitHub repository where we include more details, references, useful links and code snippets, where we invite the community to contribute.
We hope this would be a great learning companion for a new student venturing into this field, with everything covered in a fun and engaging manner.
Our upcoming season for BENDER is in preparation and the team is excited about the new topics and feedback from the community!
Contact: mauricio.reyes@unibe.ch
Website: https://github.com/ubern-mia/bender
Satish, a new PhD student, embarking his journey in A.I. technologies for medical imaging applications
Meeting the experts and understanding the clinical terminology and meaning of the underlying disease as displayed in medical image
BENDER tips when dealing with clinical imaging data
Meet the auditor, the unexpected visitor who challenges Satish and Mike!
