Automated multiclass segmentation, quantification, and visualization of the diseased aorta on hybrid PET/CT–SEQUOIA
Sign Up to like & getrecommendations! Published in 2024 at "Medical Physics"
DOI: 10.1002/mp.16967
Abstract: Cardiovascular disease is the most common cause of death worldwide, including infection and inflammation related conditions. Multiple studies have demonstrated potential advantages of hybrid positron emission tomography combined with computed tomography (PET/CT) as an adjunct… read more here.
Keywords: segmentation; automated multiclass; quantification visualization; multiclass segmentation ... See more keywords
Segmentation and quantification of infarction without contrast agents via spatiotemporal generative adversarial learning
Sign Up to like & getrecommendations! Published in 2020 at "Medical image analysis"
DOI: 10.1016/j.media.2019.101568
Abstract: Accurate and simultaneous segmentation and full quantification (all indices are required in a clinical assessment) of the myocardial infarction (MI) area are crucial for early diagnosis and surgical planning. Current clinical methods remain subject to… read more here.
Keywords: contrast; segmentation; infarction; segmentation quantification ... See more keywords
AxoDetect: an automated nerve image segmentation and quantification workflow for computational nerve modeling
Sign Up to like & getrecommendations! Published in 2024 at "Journal of Neural Engineering"
DOI: 10.1088/1741-2552/ad31c3
Abstract: Objective. Bioelectronic treatments targeting near-organ innervation have unprecedented clinical applications. Particularly in the spleen, the inhibition of the cholinergic inflammatory response by near-organ nerve stimulation has potential to replace pharmacological treatments in chronic and autoimmune… read more here.
Keywords: nerve; image; segmentation quantification; image segmentation ... See more keywords
CNN-Modified Encoders in U-Net for Nuclei Segmentation and Quantification of Fluorescent Images
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DOI: 10.1109/access.2024.3436509
Abstract: This research introduces an advanced approach to automate the segmentation and quantification of nuclei in fluorescent images through deep learning techniques. Overcoming inherent challenges such as variations in pixel intensities, noisy boundaries, and overlapping edges,… read more here.
Keywords: quantification; fluorescent images; fluorescent; quantification fluorescent ... See more keywords
Segmentation and Quantification of Surface Defects in 3D Reconstructions for Damage Assessment and Inspection
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Automation Science and Engineering"
DOI: 10.1109/tase.2025.3593967
Abstract: Detecting surface defects is crucial for maintaining the integrity of critical infrastructure. Traditional RGB image-based methods are limited by their reliance on 2D information, which impairs accurate damage assessment. This paper introduces a novel approach… read more here.
Keywords: quantification surface; quantification; damage assessment; segmentation quantification ... See more keywords