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Myocardial Infarction Quantification From Late Gadolinium Enhancement MRI Using Top-hat Transforms and Neural Networks [article]

Ezequiel de la Rosa, Désiré Sidibé, Thomas Decourselle, Thibault Leclercq, Alexandre Cochet, Alain Lalande
2019 arXiv   pre-print
Significance: Late gadolinium enhanced magnetic resonance imaging (LGE-MRI) is the gold standard technique for myocardial viability assessment.  ...  The method is based on a cascade approach where firstly, diseased slices are identified by a convolutional neural network (CNN).  ...  The main contributions of this work are: i) the automatic myocardial lesion detection and quantification Myocardial Infarction Quantification From Late Gadolinium Enhancement MRI Using Top-hat Transforms  ... 
arXiv:1901.02911v1 fatcat:p7jhlzypxrffdaskrqi4ayvcpq

Cardiac Segmentation from LGE MRI Using Deep Neural Network Incorporating Shape and Spatial Priors [article]

Qian Yue, Xinzhe Luo, Qing Ye, Lingchao Xu, Xiahai Zhuang
2019 arXiv   pre-print
Cardiac segmentation from late gadolinium enhancement MRI is an important task in clinics to identify and evaluate the infarction of myocardium.  ...  The results show that the proposed SRSCN outperformed the conventional schemes, and obtained a Dice score of 0.758(std=0.227) for myocardial segmentation, which compares with 0.757(std=0.083) from the  ...  Late gadolinium enhancement (LGE) MRI is a valuable tool for MI assessment, because it can visualize the important pathological information.  ... 
arXiv:1906.07347v2 fatcat:pnfgkvloo5dvhlrrrgom3jb7qe

Myocardial Infarction Quantification from Late Gadolinium Enhancement MRI Using Top-Hat Transforms and Neural Networks

Ezequiel de la Rosa, Désiré Sidibé, Thomas Decourselle, Thibault Leclercq, Alexandre Cochet, Alain Lalande
2021 Algorithms  
Late gadolinium enhancement (LGE) MRI is the gold standard technique for myocardial viability assessment.  ...  The method is based on a cascade approach where firstly, diseased slices are identified by a convolutional neural network (CNN).  ...  Acknowledgments: EDLR received an Erasmus+ scholarship from the Erasmus Mundus Joint Master Degree in Medical Imaging and Applications (MAIA), a program funded by the European Union.  ... 
doi:10.3390/a14080249 fatcat:ejqop3fnczbqjkpgccezuog4zi

Recent Advances in Fibrosis and Scar Segmentation from Cardiac MRI: A State-of-the-Art Review and Future Perspectives [article]

Yinzhe Wu, Zeyu Tang, Binghuan Li, David Firmin, Guang Yang
2021 arXiv   pre-print
Late Gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) has been successful for its efficacy in guiding the clinical diagnosis and treatment reliably.  ...  Co-registration with other non-contrast-agent (non-CA) modalities, balanced steady-state free precession (bSSFP) and cine magnetic resonance imaging (MRI) for example, can further enhance the efficacy  ...  by sizes, variances and artefacts in testing image data as they utilise prior information learned.  ... 
arXiv:2106.15707v1 fatcat:tk4bz7nux5bhhb3s7bv5z64squ

An Improved 3D Deep Learning-Based Segmentation of Left Ventricular Myocardial Diseases from Delayed-Enhancement MRI with Inclusion and Classification Prior Information U-Net (ICPIU-Net)

Khawla Brahim, Tewodros Weldebirhan Arega, Arnaud Boucher, Stephanie Bricq, Anis Sakly, Fabrice Meriaudeau
2022 Sensors  
and microvascular-obstructed (MVO) tissues from late gadolinium enhancement magnetic resonance (LGE-MR) images.  ...  In this paper, we propose the architecture of inclusion and classification of prior information U-Net (ICPIU-Net) to efficiently segment the left ventricle (LV) myocardium, myocardial infarction (MI),  ...  Acknowledgments: This work was partly supported by the French "Investissements d'Avenir" program, ISITE-BFC project (number ANR-15-IDEX-0003).  ... 
doi:10.3390/s22062084 pmid:35336258 pmcid:PMC8954140 fatcat:46rpykoa75awppe5zvmvd335na

Cardiac Segmentation on Late Gadolinium Enhancement MRI: A Benchmark Study from Multi-Sequence Cardiac MR Segmentation Challenge [article]

Xiahai Zhuang, Jiahang Xu, Xinzhe Luo, Chen Chen, Cheng Ouyang, Daniel Rueckert, Victor M. Campello, Karim Lekadir, Sulaiman Vesal, Nishant RaviKumar, Yashu Liu, Gongning Luo (+11 others)
2021 arXiv   pre-print
Late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) provides an important protocol to visualize MI.  ...  The success of these methods was mainly attributed to the inclusion of the auxiliary sequences from the MS-CMR images, which provide important label information for the training of deep neural networks  ...  Acknowledgement This work was supported by the National Natural Science Foundation of China (61971142).  ... 
arXiv:2006.12434v2 fatcat:s4f3cchzhvhb3kyogwo3j5mmci

Automated Left Ventricle Ischemic Scar Detection in CT Using Deep Neural Networks

Hugh O'Brien, John Whitaker, Baldeep Singh Sidhu, Justin Gould, Tanja Kurzendorfer, Mark D. O'Neill, Ronak Rajani, Karine Grigoryan, Christopher Aldo Rinaldi, Jonathan Taylor, Kawal Rhode, Peter Mountney (+1 others)
2021 Frontiers in Cardiovascular Medicine  
Late gadolinium enhancement (LGE) magnetic resonance imaging (MRI) is the gold standard for scar imaging; however, there are common instances where it is contraindicated.  ...  200 patients, 83 with scar) was used to train and validate a CNN to detect ischemic scar slices using segmentation masks as input to the network.  ...  The network is trained using the dataset derived from the gold standard late gadolinium enhancement (LGE) magnetic resonance imaging (MRI) dataset.  ... 
doi:10.3389/fcvm.2021.655252 fatcat:vgmw3rajcbbi3h6nhvvp2wi6jy

Cardiac MRI—Update 2020
Kardiale MRT – Update 2020

Anke Busse, Rengarajan Rajagopal, Seyrani Yücel, Ebba Beller, Alper Öner, Felix Streckenbach, Daniel Cantré, Hüseyin Ince, Marc-André Weber, Felix G. Meinel
2020 Der Radiologe (Berlin. Print)  
, and reliability of information that can be obtained by CMR.  ...  Its role has been further strengthened by recent trials and guidelines.  ...  and late gadolinium enhancement sequences [9] .  ... 
doi:10.1007/s00117-020-00687-1 pmid:32385547 fatcat:tx4guuamfnfsdfnespbxpqaukm

Multiview Sequential Learning and Dilated Residual Learning for a Fully Automatic Delineation of the Left Atrium and Pulmonary Veins from Late Gadolinium-Enhanced Cardiac MRI Images

Guang Yang, Jun Chen, Zhifan Gao, Heye Zhang, Hao Ni, Elsa Angelini, Raad Mohiaddin, Tom Wong, Jennifer Keegan, David Firmin
2018 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)  
Late Gadolinium-Enhanced Cardiac MRI (LGE-CMRI) is an emerging imaging technology for myocardial infarction or scar detection based on the differences in the volume of residual gadolinium distribution  ...  An accurate, robust and reproducible method for LA segmentation is highly in demand because it can not only provide valuable information of the heart function but also be helpful for the further delineation  ...  Recently, Late Gadolinium-Enhanced Cardiac MRI (LGE-CMRI) has been established for visualizing and assessing myocardial infarction or fibrosis in the left ventricle [4] .  ... 
doi:10.1109/embc.2018.8512550 pmid:30440587 fatcat:hihm4h4otfbznaa7kxge54is3i

Radiomics and Machine Learning for Detecting Scar Tissue on CT Delayed Enhancement Imaging

Hugh O'Brien, Michelle C. Williams, Ronak Rajani, Steven Niederer
2022 Frontiers in Cardiovascular Medicine  
BackgroundDelayed enhancement CT (CT-DE) has been evaluated as a tool for the detection of myocardial scar and compares well to the gold standard of MRI with late gadolinium enhancement (MRI-LGE).  ...  Left ventricle segmentation was performed on both imaging modalities, along with scar segmentation on MRI-LGE.  ...  FIGURE 1 | 1 FIGURE 1 | Segmentation and registration. (A) Magnetic resonance imaging (MRI) segmentation using CINE MRI for anatomical 3D mesh and MRI late gadolinium enhancement (LGE) for scar mesh.  ... 
doi:10.3389/fcvm.2022.847825 pmid:35647044 pmcid:PMC9133416 fatcat:6maqkvnxa5dfhbzdf6ljx6uui4

Development and application of artificial intelligence in cardiac imaging

Beibei Jiang, Ning Guo, Yinghui Ge, Lu Zhang, Matthijs Oudkerk, Xueqian Xie
2020 British Journal of Radiology  
analysis, left ventricular myocardium analysis, diagnosis of myocardial infarction, prognosis of coronary artery disease, assessment of cardiac function, and diagnosis and prognosis of cardiomyopathy.  ...  As a result, 24 and 14 studies using CT and MRI, respectively, were included and summarized.  ...  At present, CNN and CNN-derived networks have been widely used in detection, segmentation, and classification in cardiac imaging. 10 Recurrent neural network (RNN) is another type of neural network, which  ... 
doi:10.1259/bjr.20190812 pmid:32017605 pmcid:PMC7465846 fatcat:kab3xoqh5vhyvcedntigw3aplm

Modified GAN Augmentation Algorithms for the MRI-Classification of Myocardial Scar Tissue in Ischemic Cardiomyopathy

Umesh C. Sharma, Kanhao Zhao, Kyle Mentkowski, Swati D. Sonkawade, Badri Karthikeyan, Jennifer K. Lang, Leslie Ying
2021 Frontiers in Cardiovascular Medicine  
For the initial training of the MobileNetV2 platform, we used the images generated from a high-field (9.4T) cardiac MRI of a mouse model of acute myocardial infarction (MI).  ...  Contrast-enhanced cardiac magnetic resonance imaging (MRI) is routinely used to determine myocardial scar burden and make therapeutic decisions for coronary revascularization.  ...  Representative images illustrating the TTCbased histological confirmation of myocardial infarction, and an abnormal gadolinium enhancement on contrast-enhanced cardiac MRI are shown in Figure 1 .  ... 
doi:10.3389/fcvm.2021.726943 pmid:34589528 pmcid:PMC8473636 fatcat:ggum2foktjb6np6fjk62olukeu

Optimized Automated Cardiac MR Scar Quantification with GAN-Based Data Augmentation [article]

Didier R.P.R.M. Lustermans, Sina Amirrajab, Mitko Veta, Marcel Breeuwer, Cian M. Scannell
2021 arXiv   pre-print
The clinical utility of late gadolinium enhancement (LGE) cardiac MRI is limited by the lack of standardization, and time-consuming postprocessing.  ...  Methods: A cascaded pipeline consisting of three consecutive neural networks is proposed, starting with a bounding box regression network to identify a region of interest around the left ventricular (LV  ...  Introduction Late gadolinium enhancement (LGE) cardiac MRI is the reference standard for the non-invasive assessment of myocardial viability, and is widely used in clinical routine (1) .  ... 
arXiv:2109.12940v1 fatcat:ybqacf2xxjfgxaprbahz3o7aqy

Segmentation of Multimodal Myocardial Images Using Shape-Transfer GAN [article]

Xumin Tao and Hongrong Wei and Wufeng Xue and Dong Ni
2019 arXiv   pre-print
Myocardium segmentation of late gadolinium enhancement (LGE) Cardiac MR images is important for evaluation of infarction regions in clinical practice.  ...  Given this fact, we propose a novel shape-transfer GAN for LGE images, which can 1) learn to generate realistic LGE images from bSSFP with the anatomical shape preserved, and 2) learn to segment the myocardium  ...  Introduction Late gadolinium enhancement (LGE) MRI technology can accurately identify myocardial infarction(MI), myocardial fibrosis and cardiac amyloid and other diseases.  ... 
arXiv:1908.05094v1 fatcat:ms6rzf2torgupk7m45ktj3rfum

Multi-Modality Pathology Segmentation Framework: Application to Cardiac Magnetic Resonance Images [article]

Zhen Zhang, Chenyu Liu, Wangbin Ding, Sihan Wang, Chenhao Pei, Mingjing Yang, Liqin Huang
2020 arXiv   pre-print
It mainly consists of two neural networks: an anatomical structure segmentation network (ASSN) and a pathological region segmentation network (PRSN).  ...  Experiments from the MyoPS2020 challenge dataset show that our framework can achieve promising performance for myocardial scar and edema segmentation.  ...  For pathology segmentation on left ventricular (LV) myocardium, Zabihollahy et al. proposed a CNN-based method to segment scar from late gadolinium enhancement (LGE) MRIs [14] .  ... 
arXiv:2008.05780v1 fatcat:mj74gdwrkzbv3l5eolmf6aevvu
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