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Linear-regression convolutional neural network for fully automated coronary lumen segmentation in intravascular optical coherence tomography

Yan Ling Yong, Li Kuo Tan, Robert A. McLaughlin, Kok Han Chee, Yih Miin Liew
2017 Journal of Biomedical Optics  
We propose a linearregression convolutional neural network to automatically perform vessel lumen segmentation, parameterized in terms of radial distances from the catheter centroid in polar space.  ...  The processing rate is 40.6 ms per image, suggesting the potential to be incorporated into a clinical workflow and to provide quantitative assessment of vessel lumen in an intraoperative time frame.  ...  Table 2 2 Accuracy of CNN segmentation with 45 training pullbacks (n ¼ 13;342). The values are obtained based on the segmentation on 19 test pullbacks (n ¼ 5685).  ... 
doi:10.1117/1.jbo.22.12.126005 pmid:29274144 fatcat:5i3qrzxw5remdfinsdjoybck54

Deep neural networks for A-line-based plaque classification in coronary intravascular optical coherence tomography images

Chaitanya Kolluru, David Prabhu, Yazan Gharaibeh, Hiram Bezerra, Giulio Guagliumi, David Wilson
2018 Journal of Medical Imaging  
We develop neural-network-based methods for classifying plaque types in clinical intravascular optical coherence tomography (IVOCT) images of coronary arteries.  ...  The enhanced performance of the CNN was likely due to spatial invariance of the convolution operation over the input A-line.  ...  This research was conducted in space renovated using funds from an NIH construction grant (C06 RR12463) awarded to Case Western Reserve University.  ... 
doi:10.1117/1.jmi.5.4.044504 pmid:30525060 pmcid:PMC6275844 fatcat:mydq4qzyifcfpiti3hn6jrmgc4

Automated plaque characterization using deep learning on coronary intravascular optical coherence tomographic images

Juhwan Lee, David Prabhu, Chaitanya Kolluru, Yazan Gharaibeh, Vladislav N. Zimin, Hiram G. Bezerra, David L. Wilson
2019 Biomedical Optics Express  
We developed fully-automated semantic segmentation of plaque in intravascular OCT images. We trained/tested a deep learning model on a folded, large, manually annotated clinical dataset.  ...  This research was conducted in space renovated using funds from an NIH construction grant (C06 RR12463) awarded to Case Western Reserve University.  ...  This work made use of the High-Performance Computing Resource in the Core Facility for Advanced Research Computing at Case Western Reserve University.  ... 
doi:10.1364/boe.10.006497 pmid:31853413 pmcid:PMC6913416 fatcat:tjvettjdrrbpfioejyyi3yqvdi

Automated A-line coronary plaque classification of intravascular optical coherence tomography images using handcrafted features and large datasets

David Prabhu, Hiram G. Bezerra, Chaitanya Kolluru, Yazan Gharaibeh, Emile Mehanna, Hao Wu, David L. Wilson
2019 Journal of Biomedical Optics  
In addition, we included vascular lumen morphology and three-dimensional (3-D) digital edge and texture features.  ...  We developed machine learning methods to identify fibrolipidic and fibrocalcific A-lines in intravascular optical coherence tomography (IVOCT) images using a comprehensive set of handcrafted features.  ...  [25] [26] [27] 46 In addition, we developed features based on vascular lumen morphology and 2-D/3-D digital edge and texture.  ... 
doi:10.1117/1.jbo.24.10.106002 pmid:31586357 pmcid:PMC6784787 fatcat:4u3cxjzmmvdprgvmgbbx5zhw24

Coronary calcification segmentation in intravascular OCT images using deep learning: application to calcification scoring

Yazan Gharaibeh, David Prabhu, Chaitanya Kolluru, Juhwan Lee, Vladislav Zimin, Hiram Bezerra, David Wilson
2019 Journal of Medical Imaging  
We created a comprehensive software to segment calcifications in intravascular optical coherence tomography (IVOCT) images and to calculate their impact using the stent-deployment calcification score,  ...  We evaluated the method on manually annotated IVOCT volumes of interest (VOIs) without lesions and with calcifications, lipidous, or mixed lesions.  ...  This work made use of the High-Performance Computing Resource in the Core Facility for Advanced Research Computing at Case Western Reserve University.  ... 
doi:10.1117/1.jmi.6.4.045002 pmid:31903407 pmcid:PMC6934132 fatcat:ec6d45aaxrhg3fl6t3afcl6sva

Automatic Classification of A-Lines in Intravascular OCT Images Using Deep Learning and Estimation of Attenuation Coefficients

Grigorios-Aris Cheimariotis, Maria Riga, Kostas Haris, Konstantinos Toutouzas, Aggelos K. Katsaggelos, Nicos Maglaveras
2021 Applied Sciences  
The method employed convolutional neural networks (CNNs) for classification in its core and comprised the following pre-processing steps: arterial wall segmentation and an OCT-specific (depth-resolved)  ...  transformation and a post-processing step based on the majority of classifications.  ...  Specifically, accurate methods in A-line classification in IVOCT images [22, 23] are using CNNs.  ... 
doi:10.3390/app11167412 fatcat:vmbzpsov4fdqjmzxpy2dtcay6u

Interplay between Artificial Intelligence and Biomechanics Modeling in the Cardiovascular Disease Prediction

Xiaoyin Li, Xiao Liu, Xiaoyan Deng, Yubo Fan
2022 Biomedicines  
Then we summarized some ML applications in cardiovascular diseases, including ML−based models to directly predict CVD based on risk factors or medical imaging findings and the ML−based hemodynamics with  ...  In this review, we first briefly introduced the overview development of artificial intelligence.  ...  In addition, Tang et al. [113] proposed a deep neural network based on multi−scale features for automatic lumen segmentation for IVOCT images. Athanasiou et al.  ... 
doi:10.3390/biomedicines10092157 pmid:36140258 pmcid:PMC9495955 fatcat:z33hj6z2cnf5vbbtgm63ig2o5a

Coronary Plaque Characterization From Optical Coherence Tomography Imaging With a Two-Pathway Cascade Convolutional Neural Network Architecture

Yifan Yin, Chunliu He, Biao Xu, Zhiyong Li
2021 Frontiers in Cardiovascular Medicine  
The method is based on a novel CNN architecture called TwopathCNN, which is utilized in a cascaded structure.  ...  On average, the method achieves 0.86 in F1-score and 0.88 in accuracy. The TwopathCNN architecture and cascaded structure show significant improvement in performance (p < 0.05).  ...  FIGURE 4 | 4 The procedure of fully automated lumen segmentation based on dynamic programming. (A) shows the original image in polar coordinate.  ... 
doi:10.3389/fcvm.2021.670502 fatcat:old6s3sgz5huvaztenwqokdn3a

Histopathology-Based Deep-Learning Predicts Atherosclerotic Lesions in Intravascular Imaging

Olle Holmberg, Tobias Lenz, Valentin Koch, Aseel Alyagoob, Léa Utsch, Andreas Rank, Emina Sabic, Masaru Seguchi, Erion Xhepa, Sebastian Kufner, Salvatore Cassese, Adnan Kastrati (+3 others)
2021 Frontiers in Cardiovascular Medicine  
An automated decision-support tool based on DeepAD could help in risk prediction and guide interventional treatment decisions.  ...  which manual annotations were based on clinical expertise only.  ...  contour) within each part of the segment.  ... 
doi:10.3389/fcvm.2021.779807 pmid:34970608 pmcid:PMC8713728 fatcat:llcqi7mtcvfivcteg4wbozn3a4

2021 Index IEEE/ACM Transactions on Computational Biology and Bioinformatics Vol. 18

2022 IEEE/ACM Transactions on Computational Biology & Bioinformatics  
-that appeared in this periodical during 2021, and items from previous years that were commented upon or corrected in 2021.  ...  Note that the item title is found only under the primary entry in the Author Index.  ...  -Oct. 2021 1801-1810 A Deep Segmentation Network of Multi-Scale Feature Fusion Based on Attention Mechanism for IVOCT Lumen Contour. Huang, C., +, TCBB Jan.  ... 
doi:10.1109/tcbb.2021.3136340 fatcat:bjvb334webfovh4nsc7oeds3di

Ανάλυση ιατρικών δεδομένων από πολλαπλές απεικονιστικές τεχνολογίες με τεχνικές μηχανικής μάθησης, επεξεργασίας εικόνας και στατιστικού μοντέλου σχήματος

Γρηγόριος Άρης Κ. Χειμαριώτης
OCT images (to highlight the optical properties of the different types of atherosclerotic tissues) and classification of them in two level bases: textural and regional, using the appropriate CNNs network  ...  We developed the ARC-OCT method which enables accurate and fully automatic detection of lumen-endothelial borders even in OCT images containing artifacts, arterial stented segments and lateral branches  ...  Abstract Objectives: The analysis of intracoronary optical coherence tomography (OCT) images is based on manual identification of the lumen contours and relevant structures.  ... 
doi:10.26262/ fatcat:q5yn4kuddvgl3dnpgk73j67ubm