Cancelled/moved to other date (TBD, in autumn 2022). MRI networking event (in person). A satellite event of the MRI workshop. Meet MRI people in Kuopio region.
Machine Learning in Medical Imaging UEF-SIG first meeting 30 June 2022 at 10 am (virtual). We will explain the intended concept and agree about the times and format of the future meetings. Register here.
From mid-February. KUBIAC will organize short (about 15 min) presentations on varied topics on image analysis. We will start by posting few educational videos (about very basic topics for starters) and then organizing a possibility for discussion about these videos. We will start by describing some very basic image analysis techniques. If you have a topic in mind that you would like us to cover in this series, please email Olivier Rukundo or Jussi Tohka . Any feedback is appreciated!
The first “visiting hour” will take place March 18 at 2 p.m. on zoom . Olivier Rukundo will be there for at least 15 minutes (not necessarily full hour, so come early).
The next meetings will take place March 24, April 1, April 6, April 8, April 12, April 14, April 19 (2.30 p.m.), April 22, April 26, April 29, May 3, May 6, May 10, May 20, May 24 (4.30 p.m.), May 26, May 31 (4:45), June 3, June 7 (4:45). Always at 2 p.m. and always on zoom .
16th June 2022, 13:00 onward. The final seminar (in-person/hybrid). We will present the most important results of the KUBIAC project, concentrating on pilots. Coffee will be served.
13:00 – 13:20 Jussi Tohka: Educational and networking events of KUBIAC (and few words about the future)
13:20 – 13:35 Olivier Rukundo: Pilot 1: Automatic segmentation of adenoviruses from MiniTEM images
13:35 – 13:50: Riccardo De Feo: Pilot 2: Automatic segmentation of mouse brain MRIs with MU-Net
13:50 – 14:05 Riccardo De Feo: Pilot 3: Segmentation of intracranial aneurysms – The ADAM challenge
14:05 – 14:20: Raimo Salo: BIDS data structure in Kuopio Biomedical Imaging Unit – A necessity for re-using the animal imaging data
14:20 – 14:40 Coffee and discussion
14:40 onward: Steering group meeting
May 17 and 24 2022 (9 – 14): KUBIAC will organize a course on brain image analysis (webinar). It will consist of 8 hours of lectures on the basics of brain image analysis concentrating on human and animal MRI. We realize that this will be packed, so there will be a lot of self-study material in addition to lectures/demonstrations.
April 27 2022 (14 – 16): Big data in medical imaging. New innovations in artificial intelligence/machine learning combined with the possibility to utilize imaging data in PACS systems of the hospitals for their training is thought to be transformative for healthcare. At the same time, new AI-based tools are urgently needed in clinic to cope with increasing volume of imaging. However, there are several hurdles related to both legal (incl. contractual/ethical/privacy) and technical aspects of the implementation/training of AI (annotation of the data, computation). In this webinar, we host several experts discussing the possibilities and difficulties in Big Medical Imaging Data.
14:00 – 14:05 Opening and welcome
14:05 – 14:30: Juha Pajula, VTT for Smart Health Technologies, “Health data utilization challenges: legislation, data security and researcher access”
14:30 – 14:55 Sami Väänänen, “How a radiological image dataset is delivered to researcher in Kuopio University Hospital? ” Kuopio University Hospital and University of Eastern Finland,
14:55 – 15:20 Patrik Pollare, AIdoc, ” Value contribution of automatic image analysis within radiology for acute and time-sensitive findings”
15:20 – 15:45 Harri Pölönen, VTT, “Practical experiences on training huge GAN networks”
15:45 – 16:10 Sampsa Lohi , Kuopio University Hospital, “Collaborative, web-based annotation of medical imaging data”
26 January 2022 14 – 16. Image analysis in cancer research and clinical practice – Webinar/online networking event.
Novel imaging techniques and image analysis methods are transforming oncology and cancer research. In this webinar, we will hear from the experts in development and application of novel image analysis tools for cancer research. The webinar will be held on Zoom. Please register here to get an email link to the webinar. The link will be sent day before the webinar.
14.00 – 14.05 Opening and welcome
14.05 – 14.35. Dr. Ivan Jambor. University of Turku and Yale University School of Medicine: ” Modeling of Diffusion Weighted Imaging of Prostate Cancer”.
14.35 – 15.05. Dr. Pekka Ruusuvuori. University of Turku. “Towards AI-enabled computational pathology”
15.05 – 15.35 Raju Gudhe, University of Eastern Finland. ” Explainable deep learning models in breast cancer image analysis”
15.35 – 16.00 Auni Lindgren, Kuopio University Hospital, “Imaging in Ovarian Cancer”
11th October and 14th October (10 – 14) 2021: Short course on evaluation of machine learning algorithms.
Data driven research has seen strongly growing interest in biomedicine in recent years. This development is thanks to the increase in data availability as well as to advances in artificial intelligence and machine learning research and access to computational resources. Highly promising research examples are published daily. However, at the same time, there are some unrealistic, often overly optimistic, expectations and assumptions with regard to the development, validation and acceptance of such methods. Reliable, objective, and generalisable validation and performance assessment of developed data-analysis methods is one particular pain-point. This online short-course, based on a recent tutorial article, tries to build an understanding of the basic principles of the performance evaluation with lectures and hands-on demonstrations, with a focus to imaging applications.
14th June and 17th June (10 – 13) 2021: Hands-on convolutional neural networks for image analysis
During this course we will introduce the theory of convolutional neural networks and demonstrate their implementation. We will start from toy examples of image classification during which we will introduce the PyTorch framework. In the second lesson, we will follow up with an application in medical imaging segmentation in rat brain MRI, starting from freely available data and ending with a trained neural network. While this course assumes students are familiar with the python language, every implementation step is explained in detail.
We will hear perspectives to biomedical image analysis method development – from companies, research organizations and the universities. Target applications include preclinical ocular research, diagnostic decision support systems, and quantitative biology. We have an outstading line-up of speakers illuminating key challenges from various viewpoints. We are living truly intriguing times for biomedical image analysis, which, powered by recent advances in AI has become a central tool in several application areas also outside the academia. Welcome!
9th and 16th November 2020: Introduction to Data-Analysis in Python online course (free-of-charge, a limited number of participants from the target groups).
14th May 2020 12.00 – 14.30. (Moved from April due to coronavirus situation) Deep Learning for Medical and Industrial Imaging. An online seminar/networking event organized by KUBIAC in collaboration with Computational Physics and Inverse Problems group at UEF.