Celebrating the defence
Stine Hansen defended her PhD thesis “Leveraging Supervoxels for Medical Image Volume Segmentation With Limited Supervision” on Dec. 16th at UiT The Arctic University of Norway.
The focus of Stine Hansens thesis is on the development of new ML algorithms for medical image segmentation with limited supervision. In particular, completely unsupervised solutions to lung tumor segmentation and solutions that only require a few labeled samples to perform organ segmentation (few-shot learning) are proposed. To exploit the data-specific opportunities of medical images, automatically generated supervoxels are exploited in various ways to solve key challenges related to the task.
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Evaluation Committee
Supervisors
The majority of existing methods for machine learning-based medical image segmentation are supervised models that require large amounts of fully annotated images. These types of datasets are typically not available in the medical domain and are difficult and expensive to generate. A wide-spread use of machine learning based models for medical image segmentation therefore requires the development of data-efficient algorithms that only require limited supervision. To address these challenges, this thesis presents new machine learning methodology for unsupervised lung tumor segmentation and few-shot learning based organ segmentation. When working in the limited supervision paradigm, exploiting the available information in the data is key. The methodology developed in this thesis leverages automatically generated supervoxels in various ways to exploit the structural information in the images. The work on unsupervised tumor segmentation explores the opportunity of performing clustering on a population-level in order to provide the algorithm with as much information as possible. To facilitate this population-level across-patient clustering, supervoxel representations are exploited to reduce the number of samples, and thereby the computational cost. In the work on few-shot learning-based organ segmentation, supervoxels are used to generate pseudo-labels for self-supervised training. Further, to obtain a model that is robust to the typically large and inhomogeneous background class, a novel anomaly detection-inspired classifier is proposed to ease the modelling of the background. To encourage the resulting segmentation maps to respect edges defined in the input space, a supervoxel-informed feature refinement module is proposed to refine the embedded feature vectors during inference. Finally, to improve trustworthiness, an architecture-agnostic mechanism to estimate model uncertainty in few-shot segmentation is developed. Results demonstrate that supervoxels are versatile tools for leveraging structural information in medical data when training segmentation models with limited supervision.
Visual Intelligence researchers featured in "Abels Tårn"Visual Intelligence researchers from UiT Machine Learning Group and the University Hospital of North Norway (UNN) were recently featured in the "Abels Tårn" spin-off show "Den store serien om KI".
While visiting Tromsø, Fua held two talks on the topics of "Deep Uncertainty" and "Deep 3D Surface Meshes" for students and researchers at UiT The Arctic University of Norway.
The report showcases Visual Intelligence's activities, results, staff and funding throughout the past year, serving as a detailed compilation of our researchers' efforts towards further development within the centre's four main innovation areas and solving our four research chall
Kunstig intelligens treffer dårligere på kvinner enn menn. Skjevhet i dataene er hovedutfordringen, mener Suaiba Salahuddin, som peker på tre forbedringsmuligheter.
Visual Intelligence Director Robert Jenssen recently gave an invited talk at the CatchID conference organized in Tromsø from 19th-20th March 2024 by the Norwegian Directorate of Fisheries.
The exclusive Lindau Nobel Laureate Meetings gather 650 distinguished scientists and 30 Nobel Prize winners from across the world and places strict requirements in terms of academic and scientific quality. – A great honor, says associate professor Elisabeth Wetzer.
Director Robert Jenssen gave a talk on the uses and misuses of artificial intelligence for members of the seniors association at UiT The Arctic University of Norway. The UiT seniors association consists of former academic and administrative employees at the university.
Researcher Anders U. Waldeland from The Norwegian Computing Center gave a talk at The Biennial Geophysical Seminar in Kristiansand presenting work from Visual Intelligence on seismic structure search using a neural network trained with self-supervised learning.
State secretary Tomas Norvoll visited Visual Intelligence and was given a tour at the PET center at The University Hospital of North Norway by centre director Robert Jenssen and associate professor Samuel Kuttner to learn more about research and innovation within PET and AI.
We are thrilled to announce that the paper "Interrogating Sea Ice Predictability With Gradients", a collaborative paper between Visual Intelligence, The Alan Turing Institute and the British Antarctic Survey, has been accepted in IEEE Geoscience and Remote Sensing Letters.
We congratulate Srishti Gautam for successfully defending her PhD thesis and achieving the PhD degree in Science at UiT The Arctic University of Norway.
Thank you to all students and invited presenters who participated in the Pitch Day at UiT The Arctic University of Norway.
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We were happy to host a school class from Kongsbakken upper secondary school at UiT Norges arktiske universitet on March 13th.
Visual Intelligence director Robert Jenssen recently met with State Secretary Ellen Rønning-Arnesen of Ministry of Health and Care Services.
Det sier førsteamanuensis Kristoffer Wickstrøm. På NHO Arktis sin årskonferanse i Alta delte han innsikt om KI-potensialet og argumenterte for hvorfor nordnorske bedrifter bør investere i denne teknologien. (Norwegian article).
Congratulations to Visual Intelligence co-director Line Eikvil, who was featured on the Abelia and ODA Network's list of the fifty most influential tech women in Norway!
Artificial intelligence tends to perform worse on women, but why? What can be done to ensure that AI-related technologies work well for everyone?
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Our Visual Intelligence researchers had a delightful time talking about the AI study programme to high school pupils at this year's Open Day events at UiT.
Associate professor Michael Kampffmeyer and centre director Robert Jenssen gave two exciting talks for students at the UiT Career Days 2024
Visual Intelligence congratulates associate professors Elisabeth Wetzer, Ali Ramezani-Kebrya, and Kristoffer Wickstrøm with their recently promoted roles as principal investigators at the research centre.