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!

Please, register here (not later than May 13).
There are no registration fees, registration is required for organization purposes.


(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
In front of 101195

Registration & coffee

9:00 - 9:15

Room: 101195

Opening & welcome

Nataša Sladoje (Director of Centre for Image Analysis)

9:15 - 10:00
Room: 101195

Oral presentations

Johan Wikström (Dept of Surgical Sciences/Neuroradiology)
Image Analysis - the Radiologist’s best friend

Jan von Bonsdorff (Dept of Art History)
AI Tools for Art History - and for all cultural image analysis

Sophie Sanchez (Dept of Organismal Biology, EBC)
The secret of bones revealed by 3D virtual histology

10:00 - 10:30
Room: 101195

Poster/Software pitches

10:30 - 11:30
Room: 101132

Fika & mingle & Poster presentations

11:35 - 12:20
Room: 101195

Oral presentations

Tobias Sjöblom (Dept of Immunology, Genetics and Pathology - Cancer Precision Medicine)
Automated Evaluation of Volume Images in CT Pulmonary Angiography

Orcun Göksel (Dept of Information Technology, MedTech Science & Innovation Centre)
Imaging and Image-Guided Applications in Medtech

Ingela Nyström (Dept of Information Technology, InfraVis)
InfraVis – We make the invisible visible

12:30 - 13:30
Rullan restaurant


13:30 - 14:15
Room: 101195

Oral presentations

Joel Kullberg (Dept of Surgical Sciences/Radiology - Radiological Image Analysis)
Reseach Group Radiological Image Analysis - Overview on Ongoing Projects

Jacob Orrje (Dept of History of Science and Ideas)
Computer vision and early modern history. Image restoration, segmentation and HTR

Anna Klemm (Dept of Information Technology, BioImage Informatics Facility - BIIF, SciLifeLab/NBIS)
BioImage Informatics Facility (BIIF): Providing support on image analysis to researchers all over Sweden

14:15 - 15:15
Room: 101132

Fika & mingle, Posters and Software demos

15:15 - 16:00
Room: 101195

Oral presentations

Maria Ulvmar (Dept of Medical Biochemistry and Microbiology, BMC)
Understanding structural and functional tissue changes in cancer - Creation of the HEV-finder deep learning tool

Klaus Leifer (Dept of Materials Science and Engineering)
Needs for statistical data analysis in transmission electron microscopy

Ingela Lanekoff (Dept of Chemistry, BMC)
Mass spectrometry imaging provides insights into chemical processes in biological systems

16:00 - 16:20
Room: 101195

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