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Attention-Based UNet Deep Learning Model for Plaque Segmentation in Carotid Ultrasound for Stroke Risk Stratification: An Artificial Intelligence Paradigm
This study proposes an attention-channel-based UNet deep learning (DL) model that identifies the carotid plaques in the internal carotid artery (ICA) and common carotid artery (CCA) images. Our experiments consist of 970 ICA images from the UK, 379 CCA images from diabetic Japanese patients, and 300 CCA images from post-menopausal women from Hong Kong. We combined both CCA images to form an integrated database of 679 images. A rotation transformation technique was applied to 679 CCA images, doubling the database for the experiments. The cross-validation K5 (80% training: 20% testing) protocol was applied for accuracy deter...
Source: Atherosclerosis - October 26, 2022 Category: Cardiology Authors: Pankaj K Jain Abhishek Dubey Luca Saba Narender N Khanna John R Laird Andrew Nicolaides Mostafa M Fouda Jasjit S Suri Neeraj Sharma Source Type: research

Far wall plaque segmentation and area measurement in common and internal carotid artery ultrasound using U-series architectures: An unseen Artificial Intelligence paradigm for stroke risk assessment
Comput Biol Med. 2022 Aug 28;149:106017. doi: 10.1016/j.compbiomed.2022.106017. Online ahead of print.ABSTRACTStroke risk assessment using deep learning (DL) requires automated, accurate, and real-time risk assessment while ensuring compact model size. Previous DL paradigms suffered from challenges like memory size, low speed, and complex in nature lacking multi-ethnic, and multi-institution databases. This research segments and measures the area of the plaque far wall of the common carotid (CCA) and internal carotid arteries (ICA) in B-mode ultrasound using four types of solo, namely, UNet, UNet+, UNet++, and UNet+++, and...
Source: Atherosclerosis - September 5, 2022 Category: Cardiology Authors: Pankaj K Jain Neeraj Sharma Mannudeep K Kalra Amer Johri Luca Saba Jasjit S Suri Source Type: research

Automated deep learning-based paradigm for high-risk plaque detection in B-mode common carotid ultrasound scans: an asymptomatic Japanese cohort study
CONCLUSIONS: The proposed study demonstrates a fast, accurate, and reliable solution for early detection and quantification of plaque lesions in common carotid artery ultrasound scans. The system runs on a test US image in < 1 second, proving overall performance to be clinically reliable.PMID:34825801 | DOI:10.23736/S0392-9590.21.04771-4
Source: International Angiology - November 26, 2021 Category: Cardiology Authors: Pankaj K Jain Neeraj Sharma Luca Saba Kosmas I Paraskevas Mandeep K Kalra Amer Johri Andrew N Nicolaides Jasjit S Suri Source Type: research

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