628 citations
- KTH Royal Institute of TechnologySE34 papers
- Karolinska University HospitalSE28 papers
- Stockholm UniversitySE18 papers
- Science for Life LaboratorySE14 papers
- Uppsala UniversitySE12 papers
- University of OxfordGB11 papers
- Centre National de la Recherche ScientifiqueFR10 papers
- King's College LondonGB8 papers
- Universidad de SevillaES8 papers
- University of CambridgeGB8 papers
- University of NamurBE8 papers
- King Abdullah University of Science and TechnologySA7 papers
6 papers · 2 filters
Soft thresholding schemes for multiple signal classification algorithm
Sebastian Acuña, Ida S. Opstad, Fred Godtliebsen +2
Multiple signal classification algorithm (MUSICAL) exploits temporal fluctuations in fluorescence intensity to perform super-resolution microscopy by computing the value of a super…
CG-SENSE revisited: Results from the first ISMRM reproducibility challenge
Oliver Maier, Steven H. Baete, Alexander Fyrdahl +11
Purpose: The aim of this work is to shed light on the issue of reproducibility in MR image reconstruction in the context of a challenge. Participants had to recreate the results of…
Decoupling Inherent Risk and Early Cancer Signs in Image-based Breast Cancer Risk Models
Yue Liu, Hossein Azizpour, Fredrik Strand +1
The ability to accurately estimate risk of developing breast cancer would be invaluable for clinical decision-making. One promising new approach is to integrate image-based risk mo…
A deep learning-based pipeline for error detection and quality control of brain MRI segmentation results
Irene Brusini, Daniel Ferreira Padilla, José Barroso +4
Brain MRI segmentation results should always undergo a quality control (QC) process, since automatic segmentation tools can be prone to errors. In this work, we propose two deep le…
Detection of Perineural Invasion in Prostate Needle Biopsies with Deep Neural Networks
Peter Ström, Kimmo Kartasalo, Pekka Ruusuvuori +6
Background: The detection of perineural invasion (PNI) by carcinoma in prostate biopsies has been shown to be associated with poor prognosis. The assessment and quantification of P…
Artificial Intelligence Assistance Significantly Improves Gleason Grading of Prostate Biopsies by Pathologists
Wouter Bulten, Maschenka Balkenhol, Jean-Joël Awoumou Belinga +17
While the Gleason score is the most important prognostic marker for prostate cancer patients, it suffers from significant observer variability. Artificial Intelligence (AI) systems…