CBA Day – May 21, 2024
Date and time: 21 May 2024, 09:00 - 16:20
Place: Ångström laboratories, House 10, First floor
The Centre for Image Analysis is organizing a one-day event - a CBA day.
Our aim is to bring together researchers from Uppsala University who are working with images as research data and therefore need, develop, and/or use image analysis methods. In particular, we aim to present diverse application areas and to attract participants from all the UU disciplinary domains.
We wish to increase awareness of mutual interests and available resources, facilitate interactions, and discuss possible collaborations and diverse ways we could support each other.
The programme combines short oral presentations, poster presentations, software demo-sessions, and thematic discussions - all focusing on image data and image analysis.
We hope to see you at the CBA day!
It is no longer possible to register, the day has passed. See you next time!
There are no registration fees, registration is required for organization purposes.
Programme:
(check for updates)
Oral presetations are in Room Å101195 'Heinz-Otto Kreiss'
Fika, mingle and Software demos are in Room Å101132
Poster presentations are in the hallway in front of Room Å101195
8:45 - 9:00 | Registration & coffee | |
9:00 - 9:15 Room: 101195 | Opening & welcome | Nataša Sladoje (Director of Centre for Image Analysis) |
9:15 - 10:00 | Oral presentations | Johan Wikström (Dept of Surgical Sciences/Neuroradiology) |
Jan von Bonsdorff (Dept of Art History) | ||
Sophie Sanchez (Dept of Organismal Biology, EBC) | ||
10:00 - 10:30 | Poster/Software pitches | |
10:30 - 11:30 | Fika & mingle & Poster presentations | |
11:35 - 12:20 | Oral presentations | Tobias Sjöblom (Dept of Immunology, Genetics and Pathology - Cancer Precision Medicine) |
Orcun Göksel (Dept of Information Technology, MedTech Science & Innovation Centre) | ||
Ingela Nyström (Dept of Information Technology, InfraVis) | ||
12:30 - 13:30 | Lunch | |
13:30 - 14:15 | Oral presentations | Joel Kullberg (Dept of Surgical Sciences/Radiology - Radiological Image Analysis) |
Jacob Orrje (Dept of History of Science and Ideas) | ||
Anna Klemm (Dept of Information Technology, BioImage Informatics Facility - BIIF, SciLifeLab/NBIS) | ||
14:15 - 15:15 | Fika & mingle, Posters and Software demos | |
| 15:15 - 16:00 Room: 101195 | Oral presentations | Maria Ulvmar (Dept of Medical Biochemistry and Microbiology, BMC) |
Klaus Leifer (Dept of Materials Science and Engineering) | ||
Ingela Lanekoff (Dept of Chemistry, BMC) | ||
16:00 - 16:20 | Wrap up and closing | |
Poster presenters:
- Hanna Lif (Dept of Surgical Sciences; Plastic Surgery)
Image analysis in craniofacial surgery for improved surgical outcomes - Leonardo Olivetti (Dept of Earth Sciences; Environmental Analysis)
Advances and prospects of deep learning for extreme weather forecasting - Johan Öfverstedt (Dept of Surgical Sciences; Radiological Image Analysis)
Integration of imaging and non-imaging cardiac data with Imiomics and Deep Regression - Matias Piqueras (Dept of Information Technology; Computing Science)
A visual structural topic model with applications in political communication - Sara Florisson (Dept of Materials Science and Engineering; Applied Mechanics)
Computed tomography aided finite element modeling to understand the hygromechanical behaviour of wood - Nasrin Mostofian (Dept of ALM)
Bias mitigation in image recognition in heritage - Samah Abousharieha (Dept of Materials Science and Engineering; Biomedical Engineering)
Characterization of 3D-printed device providing strain to organoids - Nicholas Hoad (Dept of Earth Sciences; Natural Resources and Sustainable Development)
Images for a better understanding of the ocean - Amin Allalou (Dept of Information Technology)
DanioReadout, Uppsala Zebrafish service facility - Nadezhda Koriakina (Dept of Information Technology)
Explainable artificial intelligence to interpret automated oral cancer detection - Erik Hallström (Dept of Information Technology)
Rapid bacterial species identification using microfluidics and deep learning - Eduard Chelebian (Dept of Information Technology)
DEPICTER: Deep representation clustering for histology annotation - Marc Fraile (Dept of Information Technology)
Are We Friends? Child Rapport Analysis in Guided Play - Can Deniz Bezek (Dept of Information Technology)
Speed-of-Sound as a novel quantitative imaging and characterization method - Swarnadip Chatterjee (Dept of Information Technology)
Towards abnormal cell detection in whole slide cytology images - Jacob Henningsson (Master's programme in Image Analysis and Machine Learning, Dept of Information Technology)
Continuous synthetic data generation for deep learning - Jens Baumann (Master's programme in Image Analysis and Machine Learning, Dept of Information Technology)
Cell-Graph based lung cancer survival prediction - Wenyi Lian (Master's programme in Image Analysis and Machine Learning, Dept of Information Technology)
Multimodal information fusion for improved AI-based cancer detection
Software presenters:
- Joakim Lindblad (Dept of Information Technology)
CytoBrowser, lightweight collaborative annotation of gigapixel images in your web browser - Andrea Behanova (Dept of Information Technology)
TissUUmaps: a browser-based tool for fast visualization and exploration of millions of data points overlaying a tissue sample - Filip Malmberg (Dept of Information Technology)
SmartPaint - a freely available software tool for interactive segmentation of medical 3D imagesTBA
For more information, please contact:
Nataša Sladoje natasa.sladoje@it.uu.se