ArticleSensors (Basel, Switzerland)2021
Encoder-Decoder Architecture for Ultrasound IMC Segmentation and cIMT Measurement.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A 25-Year Retrospective of the Use of AI for Diagnosing Acute Stroke: Systematic Review.Journal of medical Internet research · 2024Pooled it
- Twelve Fused Models by Fusing Four Types of Transformer-Based Tuners on Three Base UNet Architectures for Carotid Wall Segmentation and Plaque Burden/Intima-Media Thickness Measurements in Ultrasound Scans: A Scientific Validation Study.Diagnostics (Basel, Switzerland) · 2026Article
- Computer vision applications in vascular surgery: a systematic review and critical appraisal.NPJ digital medicine · 2026Article
- GAN-Based Approach for Diabetic Retinopathy Retinal Vasculature Segmentation.Bioengineering (Basel, Switzerland) · 2023Article
- Ultrasound-Based Image Analysis for Predicting Carotid Artery Stenosis Risk: A Comprehensive Review of the Problem, Techniques, Datasets, and Future Directions.Diagnostics (Basel, Switzerland) · 2023Review
- Cardiovascular disease/stroke risk stratification in deep learning framework: a review.Cardiovascular diagnosis and therapy · 2023Review
- A Survey on Deep-Learning-Based Diabetic Retinopathy Classification.Diagnostics (Basel, Switzerland) · 2023Review
- Special Issue "Computer Aided Diagnosis Sensors".Sensors (Basel, Switzerland) · 2022Article
- BEMD-3DCNN-based method for COVID-19 detection.Computers in biology and medicine · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Cardiovascular diseases (CVDs) have shown a huge impact on the number of deaths in the world. Thus, common carotid artery (CCA) segmentation and intima-media thickness (IMT) measurements have been significantly implemented to perform early diagnosis of CVDs by analyzing IMT features. Using computer vision algorithms on CCA images is not widely used for this type of diagnosis, due to the complexity and the lack of dataset to do it. The advancement of deep learning techniques has made accurate early diagnosis from images possible. In this paper, a deep-learning-based approach is proposed to apply semantic segmentation for intima-media complex (IMC) and to calculate the cIMT measurement. In order to overcome the lack of large-scale datasets, an encoder-decoder-based model is proposed using multi-image inputs that can help achieve good learning for the model using different features. The obtained results were evaluated using different image segmentation metrics which demonstrate the effectiveness of the proposed architecture. In addition, IMT thickness is computed, and the experiment showed that the proposed model is robust and fully automated compared to the state-of-the-art work.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.