Deep learning and medical imaging - Jan Kukačka
Radiology is one of the main diagnostic tools in nowadays medicine. However, the growing shortage of trained medical personnel hinders its full utilization. Can deep learning fill in the gap?
This talk will briefly introduce the exciting domain of radiology—medical imaging—with its typical
opportunities and obstacles. A specific clinical scenario will be presented to demonstrate how
current deep learning progress in computer vision can help patients by discovering the risk of
developing a disease even before the symptoms appear, making use of opportunistic screening. Deep learning methods that will be covered in the talk are mainly fully-convolutional networks for image segmentation and object detectors such as Faster RCNN and Single Shot multibox Detector.
Speaker: Jan Kukačka
Jan Kukačka is a researcher at the Neuroradiology department of the Klinikum rechts der Isar in
Munich. He obtained his Bachelor’s degree in Theoretical informatics at Czech Technical University in Prague and later graduated as M.Sc. at Technical University Munich. His primary focus is
machine/deep learning and its applications in computer vision and medicine.
- 18:00 The talk
- 20:00 Networking
Machine Learning Meetups (MLMU) is an independent platform for people interested in Machine Learning, Information Retrieval, Natural Language Processing, Computer Vision, Pattern Recognition, Data Journalism, Artificial Intelligence, Agent Systems and all the related topics. MLMU is a regular community meeting usually consisting of a talk, a discussion and a subsequent networking allowing people to network, inspire each other and learn about exciting stuff. At the end of the year 2016, MLMU spread also to Brno and Bratislava. The beginning of 4th season brought MLMU Košice!