MultiNet 2.0: A lightweight attention-based deep learning network for stenosis measurement in carotid ultrasound scans and cardiovascular risk assessment.

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Title: MultiNet 2.0: A lightweight attention-based deep learning network for stenosis measurement in carotid ultrasound scans and cardiovascular risk assessment.
Authors: Biswas M; School of Computer Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar, India., Saba L; Department of Radiology, Azienda Ospedaliero Universitaria di Cagliari, Cagliari, Monserrato, Italy., Kalra M; Department of Radiology, Massachusetts General Hospital, Boston, MA 02115, USA., Singh R; Department of Research and Innovation, Uttaranchal Institute of Technology, Uttaranchal University, Dehradun 248007, India., Fernandes E Fernandes J; Cardiovascular Institute and the Lisbon University Medical School, Hospital de SantaMaria, Lisbon 1600 190, Portugal., Viswanathan V; MV Diabetes Centre, Royapuram, Chennai, Tamil Nadu, India., Laird JR; Cardiology Department, St. Helena Hospital, St. Helena, CA, USA., Mantella LE; Department of Biomedical and Molecular Sciences, Queen's University, Kingston, ON, Canada., Johri AM; Department of Biomedical and Molecular Sciences, Queen's University, Kingston, ON, Canada., Fouda MM; Department of Electrical and Computer Engineering, Idaho State University, Pocatello, ID, 83209, USA., Suri JS; Department of Electrical and Computer Engineering, Idaho State University, Pocatello, ID, 83209, USA; Department of CS, Graphics Era University, Dehradun, India; University Center for Research & Development, Chandigarh University, Mohali, India; Symbiosis Institute of Technology, Nagpur Campus, Symbiosis International (Deemed University), Pune, India; Stroke Monitoring Division, AtheroPoint™ LLC, Roseville, CA, USA. Electronic address: jasjit.suri@atheropoint.com.
Source: Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society [Comput Med Imaging Graph] 2024 Oct; Vol. 117, pp. 102437. Date of Electronic Publication: 2024 Oct 05.
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Science Country of Publication: United States NLM ID: 8806104 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-0771 (Electronic) Linking ISSN: 08956111 NLM ISO Abbreviation: Comput Med Imaging Graph Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1879-0771
DOI:10.1016/j.compmedimag.2024.102437