Results 71 to 80 of about 12,060,028 (242)

Artificial Intelligence in Systemic Sclerosis: Clinical Applications, Challenges, and Future Directions

Arthritis Care &Research, EarlyView.
Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos, José Miguel Sequí‐Sabater, Diego Benavent   +2 more
wiley   +1 more source

EDRN/slide-image-registration: 1.0.0

, 2021
This is the initial "general availability" (GA) or "first customer ship" (FCS) of Slide Image ...
Sean Kelly
core   +1 more source

Deep learning-based affine medical image registration for multimodal minimal-invasive image-guided interventions – A comparative study on generalizability

Zeitschrift für Medizinische Physik
Multimodal image registration is applied in medical image analysis as it allows the integration of complementary data from multiple imaging modalities.
Anika Strittmatter, Lothar R. Schad, Frank G. Zöllner   +2 more
doaj   +1 more source

Health Care Use Among Patients Presenting to Emergency Department for Gout Flares in Ontario, Canada: A Population‐Based Health Systems Analysis

Arthritis Care &Research, EarlyView.
Objective We characterized emergency department (ED) gout visits and identified patient characteristics and health services patterns contributing to ED presentations. Methods We conducted a population‐based study of ED gout visits in Ontario, Canada, between 2014 and 2023.
Timothy S. H. Kwok, Samantha Morais, William K. Silverstein, Clare L. Atzema, Gregory Choy, Priyanka Chandratre, Ping Li, Jessica Widdifield   +7 more
wiley   +1 more source

Can Representation Learning for Multimodal Image Registration be Improved by Supervision of Intermediate Layers?

, 2023
Multimodal imaging and correlative analysis typically require image alignment. Contrastive learning can generate representations of multimodal images, reducing the challenging task of multimodal image registration to a monomodal one.
Lindblad, Joakim,, Sladoje, Nataša,, Wetzer, Elisabeth,   +2 more
core   +1 more source

Anorectal Dysfunction in Systemic Sclerosis: Clinical Phenotypes and Functional Patterns

Arthritis Care &Research, EarlyView.
Objective The aim of this study was to characterize specific physiologic defects in anorectal dysfunction in systemic sclerosis (SSc) using anorectal manometry (ARM), evaluate associations with gastrointestinal (GI) and extraintestinal clinical phenotypes, and explore potential serologic markers for risk stratification.
Timothy Kaniecki, Alireza Amindarolzarbi, Tsion Abdi, John Clarke, Michael Hughes, Ami A. Shah, Zsuzsanna H. McMahan   +6 more
wiley   +1 more source

Registration of High Resolution SAR and Optical Satellite Imagery in Urban Areas [PDF]

, 2009
With the launch of high resolution remote sensing satellites in different modalities like TerraSAR-X, WorldView-1 and Ikonos, the contribution of remote sensing for various applications has received a tremendous boost. Specifically, the combined analysis
Uwe, Stilla, Reinartz, Peter, Peter, Reinartz, Stilla, Uwe, Suri, Sahil, Sebastian, Türmer, Türmer, Sebastian   +6 more
core  

Modifications in the SIFT operator for effective SAR image matching [PDF]

, 2010
With the increasing availability and rapidly improving spatial resolution of SAR images from latest and future satellites like TerraSAR-X and TanDEM-X, their applicability in remote sensing applications is set to be paramount.
Sahil Suri, Reinartz, Peter, Peter Schwind, Johannes Uhl, Schwind, Peter, Suri, Sahil, Peter Reinartz, Uhl, Johannes   +7 more
core   +1 more source

Self-Similarity and Symmetry With SIFT for Multi-Modal Image Registration

IEEE Access, 2019
This paper presents a novel feature-based multi-modal image registration technique called self-similarity and symmetry with a scale invariant feature transform (3S-SIFT). The proposed technique has the following two main components.
Guohua Lv
doaj   +1 more source

Field Report from Collaborative Research Center 1625: Heterogeneous Research Data Management Using Ontology Representations

Advanced Engineering Materials, EarlyView.
A unified research data management framework for heterogeneous materials data is presented. The system integrates multimodal datasets using ontologies and knowledge graphs, enabling interoperability and FAIR (findable, accessible, interoperable, reusable) data principles. By linking data across scales and workflows, it supports reproducible, Artifitial
Doaa Mohamed, Samuel García Vázquez, Behnam Mardani, Victor Dudarev, Alfred Ludwig, Maribel Acosta, Markus Stricker   +6 more
wiley   +1 more source