366 citations
- University of OsloNO44 papers
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7 papers · 1 filter
Treatment-aware Diffusion Probabilistic Model for Longitudinal MRI Generation and Diffuse Glioma Growth Prediction
Qinghui Liu, Elies Fuster-Garcia, Ivar Thokle Hovden +9
Diffuse gliomas are malignant brain tumors that grow widespread through the brain. The complex interactions between neoplastic cells and normal tissue, as well as the treatment-ind…
An explainable three dimension framework to uncover learning patterns: A unified look in variable sulci recognition
Michail Mamalakis, Heloise de Vareilles, Atheer AI-Manea +8
The significant features identified in a representative subset of the dataset during the learning process of an artificial intelligence model are referred to as a 'global' explanat…
An ADMM approach for multi-response regression with overlapping groups and interaction effects
Theophilus Quachie Asenso, Manuela Zucknick
In this paper, we consider the regularized multi-response regression problem where there exists some structural relation within the responses and also between the covariates and a…
Accurate Real-time Polyp Detection in Videos from Concatenation of Latent Features Extracted from Consecutive Frames
Hemin Ali Qadir, Younghak Shin, Jacob Bergsland +1
An efficient deep learning model that can be implemented in real-time for polyp detection is crucial to reducing polyp miss-rate during screening procedures. Convolutional neural n…
Towards Understanding the Survival of Patients with High-Grade Gastroenteropancreatic Neuroendocrine Neoplasms: An Investigation of Ensemble Feature Selection in the Prediction of Overall Survival
Anna Jenul, Henning Langen Stokmo, Stefan Schrunner +3
Determining the most informative features for predicting the overall survival of patients diagnosed with high-grade gastroenteropancreatic neuroendocrine neoplasms is crucial to im…
Simple U-net Based Synthetic Polyp Image Generation: Polyp to Negative and Negative to Polyp
Hemin Ali Qadir, Ilangko Balasingham, Younghak Shin
Synthetic polyp generation is a good alternative to overcome the privacy problem of medical data and the lack of various polyp samples. In this study, we propose a deep learning-ba…