Kristoffer K. Wickstrom

Tromso, Norway

Last Updated: 09/26/2026

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Found 9 publications

AdaptCMVC++: Robust and Flexible Adaptation to Incremental Views in Continual Multi-view Clustering.

AdaptCMVC++: Robust and Flexible Adaptation to Incremental Views in Continual Multi-view Clustering.

Journal: IEEE transactions on pattern analysis and machine intelligence

Published: July 14, 2026

A robust and versatile deep learning model for prediction of the arterial input function in dynamic small animal [18F] FDG PET imaging.

A robust and versatile deep learning model for prediction of the arterial input function in dynamic small animal [18F] FDG PET imaging.

Journal: EJNMMI research

Published: November 05, 2025

Analysis of Deep Convolutional Neural Networks Using Tensor Kernels and Matrix-Based Entropy.

Analysis of Deep Convolutional Neural Networks Using Tensor Kernels and Matrix-Based Entropy.

Journal: Entropy (Basel, Switzerland)

Published: April 25, 2023

A clinically motivated self-supervised approach for content-based image retrieval of CT liver images.

A clinically motivated self-supervised approach for content-based image retrieval of CT liver images.

Journal: Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society

Published: June 06, 2022

Cerebral blood flow measurements with 15O-water PET using a non-invasive machine-learning-derived arterial input function.

Cerebral blood flow measurements with 15O-water PET using a non-invasive machine-learning-derived arterial input function.

Journal: Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism

Published: February 09, 2021

Machine learning derived input-function in a dynamic 18F-FDG PET study of mice.

Machine learning derived input-function in a dynamic 18F-FDG PET study of mice.

Journal: Biomedical physics & engineering express

Published: January 13, 2021

Uncertainty-Aware Deep Ensembles for Reliable and Explainable Predictions of Clinical Time Series.

Uncertainty-Aware Deep Ensembles for Reliable and Explainable Predictions of Clinical Time Series.

Journal: IEEE journal of biomedical and health informatics

Published: December 07, 2020

Understanding Convolutional Neural Networks With Information Theory: An Initial Exploration.

Understanding Convolutional Neural Networks With Information Theory: An Initial Exploration.

Journal: IEEE transactions on neural networks and learning systems

Published: February 20, 2020

Uncertainty and interpretability in convolutional neural networks for semantic segmentation of colorectal polyps.

Uncertainty and interpretability in convolutional neural networks for semantic segmentation of colorectal polyps.

Journal: Medical image analysis

Published: May 10, 2019

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Last Updated: 09/26/2026