282 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Karolinska InstitutetSE28 papers
- KTH Royal Institute of TechnologySE10 papers
- Stockholm South General HospitalSE4 papers
- University of BoråsSE4 papers
- King's College LondonGB3 papers
- Max Planck Institute for Developmental BiologyDE3 papers
- New York UniversityUS3 papers
- Stanford UniversityUS3 papers
- Uppsala UniversitySE3 papers
- Corporació Sanitària Parc TaulíES2 papers
- Gdańsk Medical UniversityPL2 papers
- Hospital Universitari Germans Trias i PujolES2 papers
6 papers · 1 filter
Potential and challenges of generative adversarial networks for super-resolution in 4D Flow MRI
Oliver Welin Odeback, Arivazhagan Geetha Balasubramanian, Jonas Schollenberger +9
4D Flow Magnetic Resonance Imaging (4D Flow MRI) enables non-invasive quantification of blood flow and hemodynamic parameters. However, its clinical application is limited by low s…
The ACROBAT 2022 Challenge: Automatic Registration Of Breast Cancer Tissue
Philippe Weitz, Masi Valkonen, Leslie Solorzano +38
The alignment of tissue between histopathological whole-slide-images (WSI) is crucial for research and clinical applications. Advances in computing, deep learning, and availability…
High-resolution synthesis of high-density breast mammograms: Application to improved fairness in deep learning based mass detection
Lidia Garrucho, Kaisar Kushibar, Richard Osuala +7
Computer-aided detection systems based on deep learning have shown good performance in breast cancer detection. However, high-density breasts show poorer detection performance sinc…
Generative Aging of Brain Images with Diffeomorphic Registration
Jingru Fu, Antonios Tzortzakakis, José Barroso +3
Analyzing and predicting brain aging is essential for early prognosis and accurate diagnosis of cognitive diseases. The technique of neuroimaging, such as Magnetic Resonance Imagin…
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…
A Deep Learning based Pipeline for Efficient Oral Cancer Screening on Whole Slide Images
Jiahao Lu, Nataša Sladoje, Christina Runow Stark +3
Oral cancer incidence is rapidly increasing worldwide. The most important determinant factor in cancer survival is early diagnosis. To facilitate large scale screening, we propose…