Ida Häggström

Associate Professor at Signal Processing and Biomedical Engineering

My research is focused on medical image analysis using machine learning techniques. I collaborate closely with medical doctors on projects to diagnose, predict and prognosticate different diseases, mainly cancer. I work mainly with images from positron emission tomography (PET), but also computed tomography (CT) and magnetic resonance imaging (MR).

Source: chalmers.se
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Showing 3 publications

2024

Deep Nearest Neighbors for Anomaly Detection in Chest X-Rays

Xixi Liu, Jennifer Alvén, Ida Häggström et al
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 14349 LNCS, p. 293-302
Paper in proceeding
2024
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Deep learning for [18F]fluorodeoxyglucose-PET-CT classification in patients with lymphoma: a dual-centre retrospective analysis

Ida Häggström, Doris Leithner, Jennifer Alvén et al
The Lancet Digital Health. Vol. 6 (2), p. e114-e125
Journal article
2023
Open Access icon

Early identification and characterisation of stroke to support prehospital decision-making using artificial intelligence: a scoping review protocol

Hoor Jalo, Mattias Seth, Minna Pikkarainen et al
BMJ Open. Vol. 13 (5), p. e069660-
Journal article

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Showing 1 research projects

2021–2022

Deep learning-based out of distribution detection of computed tomography images

Fredrik Kahl Imaging and Image Analysis
Ida Häggström Imaging and Image Analysis
VINNOVA

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