Keyword search (4,164 papers available)

"Multimodal" Keyword-tagged Publications:

Title Authors PubMed ID
1 Auditory and vibrotactile interactions in perception of timbre acoustic features Chauvette L; Sophie Grenier A; Albouy P; Coffey E; Zatorre R; Sharp A; 41168236
PSYCHOLOGY
2 Emerging Image-Guided Navigation Techniques for Cardiovascular Interventions: A Scoping Review Roshanfar M; Salimi M; Jang SJ; Sinusas AJ; Kim J; Mosadegh B; 40428106
ENCS
3 NIRSTORM: a Brainstorm extension dedicated to functional near-infrared spectroscopy data analysis, advanced 3D reconstructions, and optimal probe design Delaire É; Vincent T; Cai Z; Machado A; Hugueville L; Schwartz D; Tadel F; Cassani R; Bherer L; Lina JM; Pélégrini-Issac M; Grova C; 40375973
SOH
4 Analyses of microstructural variation in the human striatum using non-negative matrix factorization Robert C; Patel R; Blostein N; Steele CC; Mallar Chakravarty M; 34848302
PSYCHOLOGY
5 Pantomime (Not Silent Gesture) in Multimodal Communication: Evidence From Children's Narratives. Marentette P, Furman R, Suvanto ME, Nicoladis E 33329222
PSYCHOLOGY
6 Investigating microstructural variation in the human hippocampus using non-negative matrix factorization. Patel R, Steele CJ, Chen A, Patel S, Devenyi GA, Germann J, Tardif CL, Chakravarty MM 31715254
PSYCHOLOGY
7 Computer-Aided Diagnosis System of Alzheimer's Disease Based on Multimodal Fusion: Tissue Quantification Based on the Hybrid Fuzzy-Genetic-Possibilistic Model and Discriminative Classification Based on the SVDD Model. Lazli L, Boukadoum M, Ait Mohamed O 31652635
ENCS

 

Title:Emerging Image-Guided Navigation Techniques for Cardiovascular Interventions: A Scoping Review
Authors:Roshanfar MSalimi MJang SJSinusas AJKim JMosadegh B
Link:https://pubmed.ncbi.nlm.nih.gov/40428106/
DOI:10.3390/bioengineering12050488
Publication:Bioengineering (Basel, Switzerland)
Keywords:artificial intelligencecardiac imagingimage-guided navigationinterventional cardiologymultimodal imaging
PMID:40428106 Category: Date Added:2025-05-28
Dept Affiliation: ENCS
1 Department of Mechanical Engineering, Gina Cody School of Engineering, Concordia University, Montreal, QC H3G 1M8, Canada.
2 Department of Mechanical Engineering, York University, Toronto, ON M3J 1P3, Canada.
3 Section of Cardiovascular Medicine, Department of Medicine, Yale University, New Haven, CT 06519, USA.
4 Department of Medicine, Weill Cornell Medicine, New York, NY 10021, USA.
5 Dalio Institute of Cardiovascular Imaging, Department of Radiology, Weill Cornell Medicine, New York, NY 10021, USA.

Description:

Background: Image-guided navigation has revolutionized precision cardiac interventions, yet current technologies face critical limitations in real-time guidance and procedural accuracy. Method: Here, we comprehensively evaluate state-of-the-art imaging modalities, from conventional fluoroscopy to emerging hybrid systems, analyzing their applications across coronary, structural, and electrophysiological interventions. Results: We demonstrate that novel approaches combining optical coherence tomography with near-infrared spectroscopy or fluorescence achieve unprecedented plaque characterization and procedural guidance through simultaneous structural and molecular imaging. Our analysis reveals key challenges, including imaging artifacts and resolution constraints, while highlighting recent technological solutions incorporating artificial intelligence and robotics. We show that non-imaging alternatives, such as fiber optic real-shape sensing and electromagnetic tracking, complement traditional techniques by providing real-time navigation without radiation exposure. This paper also discusses the integration of image-guided navigation techniques into augmented reality systems and patient-specific modeling, highlighting initial clinical studies that demonstrate their significant promise in reducing procedural times and improving accuracy. These findings establish a framework for next-generation cardiac interventions, emphasizing the critical role of multimodal imaging platforms enhanced by AI-driven decision support. Conclusions: We conclude that continued innovation in hybrid imaging systems, coupled with advances in automation, will be essential for optimizing procedural outcomes and expanding access to complex cardiac interventions.





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