Automatic joint inflammation estimation based on regression neural networks

Results show that ADMIRA provides accurate, expert-level inflammation estimation, particularly for synovitis and tenosynovitis, offering a fast, reliable alternative to manual methods for RA monitoring and analysis. We expect that this automatic method could help to reduce labor costs and improve the efficiency of diagnosis in the future.

Authors

Institutions

Publication Details

Journal
Medical Physics
Published
2025-09-22
DOI
https://doi.org/10.1002/mp.70010
Primary Topic
Rheumatoid Arthritis Research and Therapies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Automatic joint inflammation estimation based on regression neural networks

Annette H M van der Helm–van Mil, Berend C. Stoel, Yanli Li, M. Reijnierse et al.
Medical Physics
Rheumatoid Arthritis Research and Therapies
article

Automatic joint inflammation estimation based on regression neural networks

Annette H M van der Helm–van Mil, Berend C. Stoel, Yanli Li, M. Reijnierse, Denis P. Shamonin, Dennis A Ton
article en

Abstract

Results show that ADMIRA provides accurate, expert-level inflammation estimation, particularly for synovitis and tenosynovitis, offering a fast, reliable alternative to manual methods for RA monitoring and analysis. We expect that this automatic method could help to reduce labor costs and improve the efficiency of diagnosis in the future.

Medical PhysicsVol. 52(10)
Leiden University Medical Center (NL)
Openalex Percentile: Top 62%
Rheumatoid Arthritis Research and Therapies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.