Med-ImageNet: Creation of a Compendium of AI-Ready Medical Imaging Data for Deep Learning Analysis – Forum, July 21, 2023
https://malmic.ca/wp-content/uploads/2023/06/shutterstock_1741769819-1024x631.jpg 1024 631 MaLMIC - Machine Learning in Medical Imaging Consortium MaLMIC - Machine Learning in Medical Imaging Consortium https://malmic.ca/wp-content/uploads/2023/06/shutterstock_1741769819-1024x631.jpgArtificial Intelligence (AI) applied to medical images has the potential to transform patient care, especially in radiation oncology where radiological imaging is ubiquitous and treatment planning is time consuming.
AI models are data hungry but medical data are often insufficient for many applications. Building foundational models and fine-tuning them for specific medical tasks with only a few data points represents a new avenue of research with high translational potential. However, there is a lack of large compendia of radiological data that are sufficiently curated for building these foundational models.
In this session, the presenters will describe current work on implementing Med-ImageNet, a compendium of radiological images that have been standardised to develop deep learning models, such radiomics predictors or the foundational MedSAM model.