721 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of AmsterdamNL22 papers
- Radboud University NijmegenNL11 papers
- Radboud University Medical CenterNL9 papers
- Instituto de Astrofísica de CanariasES7 papers
- Universidad de La LagunaES7 papers
- Heidelberg UniversityDE6 papers
- KU LeuvenBE6 papers
- Oncode InstituteNL6 papers
- Utrecht UniversityNL6 papers
- Johns Hopkins UniversityUS5 papers
- University of BonnDE5 papers
- University of SheffieldGB5 papers
54 papers
Leveraging Adversarial Learning for Pathological Fidelity in Virtual Staining
José Teixeira, Pascal Klöckner, Diana Montezuma +5
In addition to evaluating tumor morphology using H&E staining, immunohistochemistry is used to assess the presence of specific proteins within the tissue. However, this is a costly…
A Multicentric Dataset for Training and Benchmarking Breast Cancer Segmentation in H&E Slides
Carlijn Lems, Leslie Tessier, John-Melle Bokhorst +18
Automated semantic segmentation of whole-slide images (WSIs) stained with hematoxylin and eosin (H&E) is essential for large-scale artificial intelligence-based biomarker analysis…
GANs vs. Diffusion Models for virtual staining with the HER2match dataset
Pascal Klöckner, José Teixeira, Diana Montezuma +3
Virtual staining is a promising technique that uses deep generative models to recreate histological stains, providing a faster and more cost-effective alternative to traditional ti…
The Science of the Einstein Telescope
Adrian Abac, Raul Abramo, Simone Albanesi +485
Einstein Telescope (ET) is the European project for a gravitational-wave (GW) observatory of third-generation. In this paper we present a comprehensive discussion of its science ob…
Multimodal Integration of Longitudinal Noninvasive Diagnostics for Survival Prediction in Immunotherapy Using Deep Learning
Melda Yeghaian, Zuhir Bodalal, Daan van den Broek +4
Purpose: Immunotherapies have revolutionized the landscape of cancer treatments. However, our understanding of response patterns in advanced cancers treated with immunotherapy rema…
Multi-task Learning Approach for Intracranial Hemorrhage Prognosis
Miriam Cobo, Amaia Pérez del Barrio, Pablo Menéndez Fernández-Miranda +3
Prognosis after intracranial hemorrhage (ICH) is influenced by a complex interplay between imaging and tabular data. Rapid and reliable prognosis are crucial for effective patient…
CIBRA identifies genomic alterations with a system-wide impact on tumor biology
Soufyan Lakbir, Caterina Buranelli, Gerrit A. Meijer +3
Background: Genomic instability is a hallmark of cancer, leading to many somatic alterations. Identifying which alterations have a system-wide impact is a challenging task. Neverth…
DIAS: A Dataset and Benchmark for Intracranial Artery Segmentation in DSA sequences
Wentao Liu, Tong Tian, Lemeng Wang +11
The automated segmentation of Intracranial Arteries (IA) in Digital Subtraction Angiography (DSA) plays a crucial role in the quantification of vascular morphology, significantly c…
Joint machine learning and analytic track reconstruction for X-ray polarimetry with gas pixel detectors
Nicoló Cibrario, Michela Negro, Nikita Moriakov +9
We present our study on the reconstruction of photoelectron tracks in gas pixel detectors used for astrophysical X-ray polarimetry. Our work aims to maximize the performance of con…
The VLT-FLAMES Tarantula Survey: Observational evidence for two distinct populations of massive runaway stars in 30 Doradus
H. Sana, O. H. Ramírez-Agudelo, V. Hénault-Brunet +17
Two main scenarios have been proposed for origin of massive runaway stars -- dynamical ejection or release from a binary at the first core collapse -- but their relative contributi…
The Trial within Cohorts (TwiCs) study design in oncology: Experience and methodological reflections
Rob Kessels, Anne M. May, Miriam Koopman +1
A Trial within Cohorts (TwiCs) study design is a trial design that uses the infrastructure of an observational cohort study to initiate a randomized trial. Upon cohort enrollment,…
End-to-end Memory-Efficient Reconstruction for Cone Beam CT
Nikita Moriakov, Jan-Jakob Sonke, Jonas Teuwen
Cone Beam CT plays an important role in many medical fields nowadays, but the potential of this imaging modality is hampered by lower image quality compared to the conventional CT.…
Preoperative brain tumor imaging: models and software for segmentation and standardized reporting
D. Bouget, A. Pedersen, A. S. Jakola +27
For patients suffering from brain tumor, prognosis estimation and treatment decisions are made by a multidisciplinary team based on a set of preoperative MR scans. Currently, the l…
Federated Learning Enables Big Data for Rare Cancer Boundary Detection
Sarthak Pati, Ujjwal Baid, Brandon Edwards +276
Although machine learning (ML) has shown promise in numerous domains, there are concerns about generalizability to out-of-sample data. This is currently addressed by centrally shar…
Acceleration and cooling of the corona during X-ray flares from the Seyfert galaxy I Zw 1
D. R. Wilkins, L. C. Gallo, E. Costantini +2
We report on X-ray flares that were observed from the active galactic nucleus I Zwicky 1 (I Zw 1) in 2020 January by the NuSTAR and XMM-Newton observatories. The X-ray spectrum is…
Subpixel object segmentation using wavelets and multi resolution analysis
Ray Sheombarsing, Nikita Moriakov, Jan-Jakob Sonke +1
We propose a novel deep learning framework for fast prediction of boundaries of two-dimensional simply connected domains using wavelets and Multi Resolution Analysis (MRA). The bou…
Deep MRI Reconstruction with Radial Subsampling
George Yiasemis, Chaoping Zhang, Clara I. Sánchez +2
In spite of its extensive adaptation in almost every medical diagnostic and examinatorial application, Magnetic Resonance Imaging (MRI) is still a slow imaging modality which limit…
DeepSMILE: Contrastive self-supervised pre-training benefits MSI and HRD classification directly from H&E whole-slide images in colorectal and breast cancer
Yoni Schirris, Efstratios Gavves, Iris Nederlof +2
We propose a Deep learning-based weak label learning method for analyzing whole slide images (WSIs) of Hematoxylin and Eosin (H&E) stained tumor tissue not requiring pixel-level or…
Sparse-shot Learning with Exclusive Cross-Entropy for Extremely Many Localisations
Andreas Panteli, Jonas Teuwen, Hugo Horlings +1
Object localisation, in the context of regular images, often depicts objects like people or cars. In these images, there is typically a relatively small number of objects per class…
Automatic Breast Lesion Detection in Ultrafast DCE-MRI Using Deep Learning
Fazael Ayatollahi, Shahriar B. Shokouhi, Ritse M. Mann +1
Purpose: We propose a deep learning-based computer-aided detection (CADe) method to detect breast lesions in ultrafast DCE-MRI sequences. This method uses both the three-dimensiona…
Interpretable deep learning regression for breast density estimation on MRI
Bas H. M. van der Velden, Max A. A. Ragusi, Markus H. A. Janse +2
Breast density, which is the ratio between fibroglandular tissue (FGT) and total breast volume, can be assessed qualitatively by radiologists and quantitatively by computer algorit…
2D kinematics of massive stars near the Galactic Center
Mattia Libralato, Daniel J. Lennon, Andrea Bellini +12
The presence of massive stars (MSs) in the region close to the Galactic Center (GC) poses several questions about their origin. The harsh environment of the GC favors specific form…
The R136 star cluster dissected with Hubble Space Telescope/STIS. II. Physical properties of the most massive stars in R136
Joachim M. Bestenlehner, Paul A. Crowther, Saida M. Caballero-Nieves +11
We present an optical analysis of 55 members of R136, the central cluster in the Tarantula Nebula of the Large Magellanic Cloud. Our sample was observed with STIS aboard the Hubble…
A NICER look at the state transitions of the black hole candidate MAXI J1535-571 during its reflares
V. A. Cúneo, K. Alabarta, L. Zhang +18
The black hole candidate and X-ray binary MAXI J1535-571 was discovered in September 2017. During the decay of its discovery outburst, and before returning to quiescence, the sourc…