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Center for Medical Image Science and Visualization, CMIV, and AIDA welcomes you to a course in deep learning with focus on you as a professional in medical imaging.

Sharing sensitive data, such as images of brain tumor patients, is complicated. This makes development of AI models for medical image analysis challenging. LiU researchers shows how such models can be trained without sharing sensitive information.

AI makes it possible to quickly and accurately mark areas to be eliminated with radiation when treating cancerous tumors. But due to lack of medical data to train AI models with, attempts are underway to train models with synthetic medical images.

Scientists plan to use the same technology as that used to create deepfake videos to build AI-generated medical images. The synthesised images will present data from the big SCAPIS study, and will be used for research into AI solutions in healthcare.

AIDA data hub has already facilitated sharing of data sets from Swedish researchers to six other research groups in four different countries (Spain, China, South Korea and United Kingdom) and more is in the pipeline.

The fact that a common drug against osteoporosis can also cause bone fractures created major concern following a study at Linköping University. LiU will now lead the Swedish part of an international project to gain more knowledge about this.

For artificial intelligence (AI) to be helpful within healthcare, people and machines must work effectively together. A new study shows that doctors who use AI when examining tissue samples can work faster while still doing high-quality work.

One of the world's most powerful systems for artificial intelligence (AI) computation has landed at Linköping University. The system will serve as a national resource for projects within AIDA.

The Center for Medical Image Science and Visualization participates in a major European collaboration for artificial intelligence in digital pathology. The project has received financing from the Innovative Medicines Initiative under Horizon 2020.