output
20192025
most citedDouble diffusion encoding and applications for biomedical imaging

49 citations

10 papers

astro-ph.EP20251 cited

Interstellar Ices as Carriers of Supernova Material to the Early Solar System

Martin Bizzarro, Martin Schiller, Jesper Holst +10

Planetary materials show systematic variations in their nucleosynthetic isotope compositions that resonate with orbital distance. The origin of this pattern remains debated, limiti…

physics.med-ph20252 cited

Millennium Pathways for Tractography: 40 grand challenges to shape the future of tractography

Maxime Descoteaux, Kurt G. Schilling, Dogu Baran Aydogan +44

In the spirit of the historic Millennium Prize Problems that heralded a new era for mathematics, the newly formed International Society for Tractography (IST) has launched the Mill…

cs.HC202412 cited

"It depends": Configuring AI to Improve Clinical Usefulness Across Contexts

Hubert D. Zając, Jorge M. N. Ribeiro, Silvia Ingala +6

Artificial Intelligence (AI) repeatedly match or outperform radiologists in lab experiments. However, real-world implementations of radiological AI-based systems are found to provi…

eess.IV20243 cited

Building an AI Support Tool for Real-time Ulcerative Colitis Diagnosis

Bjørn Leth Møller, Bobby Zhao Sheng Lo, Johan Burisch +4

Ulcerative Colitis (UC) is a chronic inflammatory bowel disease decreasing life quality through symptoms such as bloody diarrhoea and abdominal pain. Endoscopy is a cornerstone of…

physics.med-ph20243 cited

Data harvesting vs data farming: A study of the importance of variation vs sample size in deep learning-based auto-segmentation for breast cancer patients

ES Buhl, E Maae, LW Matthiessen +7

The aim of this study was to investigate the difference in output, when training a model in three different scenarios: a large clinical delineated data set (with 700/78 patients fo…

eess.IV2024

Local Gamma Augmentation for Ischemic Stroke Lesion Segmentation on MRI

Jon Middleton, Marko Bauer, Kaining Sheng +5

The identification and localisation of pathological tissues in medical images continues to command much attention among deep learning practitioners. When trained on abundant datase…