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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  
This network incorporates the inclusion and classification information of the LGE-MRI to maintain topological constraints of pathological areas.  ...  Importantly, compared to various deep learning-based methods participating in the EMIDEC challenge, the results of our approach have a more significant agreement with manual contouring in segmenting myocardial  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/s22062084 pmid:35336258 pmcid:PMC8954140 fatcat:46rpykoa75awppe5zvmvd335na

Medical Image Analysis on Left Atrial LGE MRI for Atrial Fibrillation Studies: A Review [article]

Lei Li and Veronika A. Zimmer and Julia A. Schnabel and Xiahai Zhuang
2022 arXiv   pre-print
This paper aims to provide a systematic review on computing methods for LA cavity, wall, scar and ablation gap segmentation and quantification from LGE MRI, and the related literature for AF studies.  ...  Hence, LA scar segmentation and quantification from LGE MRI can be useful in computer-assisted diagnosis and treatment stratification of AF patients.  ...  Acknowledgment This work was supported by the National Natural Science Foundation of China (61971142, 62111530195 and 62011540404) and the development fund for Shanghai talents (2020015).  ... 
arXiv:2106.09862v3 fatcat:y7gk5bjqirgotbx3bwfq62rnqy

CARS 2020—Computer Assisted Radiology and Surgery Proceedings of the 34th International Congress and Exhibition, Munich, Germany, June 23–27, 2020

2020 International Journal of Computer Assisted Radiology and Surgery  
A hybrid (analogue and digital) CARS 2020 has therefore been envisaged to take place at the University Hospital in Munich, with a balanced combination of analogue/personal and digital presentations and  ...  In the times of COVID-19 overshadowing CARS 2020 and what the future may hold, a CARS meeting with these numbers of participants is not feasible anymore and new ways have to be explored to still fulfill  ...  In order to reduce the radiation exposure, a 4 DOF robot system that controls the guidewire and the catheter and offers haptic feedback function for the guidewire insertion has been developed by Cha et  ... 
doi:10.1007/s11548-020-02171-6 pmid:32514840 fatcat:lyhdb2zfpjcqbf4mmbunddwroq

DeepHealth: Review and challenges of artificial intelligence in health informatics [article]

Gloria Hyunjung Kwak, Pan Hui
2020 arXiv   pre-print
The demand for it in health informatics is also increasing, and we can expect to see the potential benefits of its applications in healthcare.  ...  This article presents a comprehensive review of research applying artificial intelligence in health informatics, focusing on the last seven years in the fields of medical imaging, electronic health records  ...  And the application of these methods does pervasive, from brain MRI to retinal imaging and digital pathology to lung CT. (1) Transfer Learning Transfer learning is a popular method in which a model developed  ... 
arXiv:1909.00384v2 fatcat:sy7pm2c2uvdd3pal2russn4xri

A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges [article]

Moloud Abdar, Farhad Pourpanah, Sadiq Hussain, Dana Rezazadegan, Li Liu, Mohammad Ghavamzadeh, Paul Fieguth, Xiaochun Cao, Abbas Khosravi, U Rajendra Acharya, Vladimir Makarenkov, Saeid Nahavandi
2021 arXiv   pre-print
It can be applied to solve a variety of real-world applications in science and engineering.  ...  Uncertainty quantification (UQ) plays a pivotal role in reduction of uncertainties during both optimization and decision making processes.  ...  [43] modified U-Net [44] , which is a CNN-based deep model, to segment myocardial arterial spin labeling and estimate uncertainty.  ... 
arXiv:2011.06225v4 fatcat:wwnl7duqwbcqbavat225jkns5u

Full Issue PDF

2020 JACC Cardiovascular Imaging  
OBJECTIVES The authors investigated ideal acoustic conditions on a clinical scanner custom-programmed for ultrasound (US) cavitation-mediated flow augmentation in preclinical models.  ...  High line density and long pulse duration resulted in the greatest release of ATP in the cavitation zone.  ...  After QC1, a 17-layer CNN (CNN segment ) was used to segment the left ventricle (LV) and right ventricle (RV), including the LV myocardium, in all frames of the cine CMR.  ... 
doi:10.1016/s1936-878x(20)30146-7 fatcat:4lngerhk4ngkfpdi6ddinbl4te

Learning Neural Textual Representations for Citation Recommendation

Binh Thanh Kieu, Inigo Jauregi Unanue, Son Bao Pham, Hieu Xuan Phan, Massimo Piccardi
2021 2020 25th International Conference on Pattern Recognition (ICPR)  
; Papathanassiou, Dimitri; Passat, Nicolas 1847 PS T5.8 Segmentation of Axillary and Supraclavicular Tumoral Lymph Nodes in PET/CT: A Hybrid CNN/Component-Tree Approach DAY 4 -Jan 15, 2021 -DAY  ...  Deep Learning Approach for the Segmentation of Myocardial Diseases DAY 3 -Jan 14, 2021 Ghose, Shuvozit; Chowdhury, Pinaki Nath; Roy, Partha Pratim; Pal, Umapada 1305 Modeling Extent-Of-Texture  ... 
doi:10.1109/icpr48806.2021.9412725 fatcat:3vge2tpd2zf7jcv5btcixnaikm

Proceedings of the World Molecular Imaging Congress 2021, October 5-8, 2021: General Abstracts

2022 Molecular Imaging and Biology  
For most clinical MRI cases, the total number of iterations for enhanced image quality is around 8 with a total number of resolution subsets around 4.  ...  The uncertainty caused in the system was modeled as an iterative deconvolution with resolution subsets to denoise and enhance image resolution.  ...  The nanocluster system with a high selectivity showed the potential for fluorescence imaging and the integrating of gold and MMAE demonstrated excellent concurrent chemotherapy-radiotherapy efficacy, which  ... 
doi:10.1007/s11307-021-01693-y pmid:34982365 pmcid:PMC8725635 fatcat:4sfb3isoyfdhfbiwxfr55gvqym

Opportunities and obstacles for deep learning in biology and medicine

Travers Ching, Daniel S. Himmelstein, Brett K. Beaulieu-Jones, Alexandr A. Kalinin, Brian T. Do, Gregory P. Way, Enrico Ferrero, Paul-Michael Agapow, Michael Zietz, Michael M. Hoffman, Wei Xie, Gail L. Rosen (+24 others)
2018 Journal of the Royal Society Interface  
Furthermore, the limited amount of labelled data for training presents problems in some domains, as do legal and privacy constraints on work with sensitive health records.  ...  These algorithms have recently shown impressive results across a variety of domains. Biology and medicine are data-rich disciplines, but the data are complex and often ill-understood.  ...  We thank Aaron Sheldon, who contributed text but did not formally approve the manuscript; Anna Greene for a careful proofreading of the manuscript in advance of the first submission; Sebastian Raschka  ... 
doi:10.1098/rsif.2017.0387 pmid:29618526 pmcid:PMC5938574 fatcat:65o4xmp53nc6zmj37srzuht6tq

Proceedings of the World Molecular Imaging Congress 2020, October 7-9, 2020: General Abstracts

2022 Molecular Imaging and Biology  
Conclusion: Tumor specific uptake of pan800 provided remarkable contrast and a flexible imaging window for fluorescence-guided identification of HGGs despite modest EGFR expression.  ...  Results: In HGG xenografts, intratumoral distribution of pan800 correlated with the EGFR expression and the fluorescence signal.  ...  We believe that our miniature microscope will herald a new era in preclinical brain disease research by enabling novel insights into the dysfunction of multiple neurobiological variables over the disease  ... 
doi:10.1007/s11307-021-01691-0 pmid:34982363 pmcid:PMC8725637 fatcat:ipn7hwekzzh6nbsk6dr2mzuhhm

Application of AI and IoT in Clinical Medicine: Summary and Challenges

Zhao-xia Lu, Peng Qian, Dan Bi, Zhe-wei Ye, Xuan He, Yu-hong Zhao, Lei Su, Si-liang Li, Zheng-long Zhu
2021 Current Medical Science  
In addition, the in-depth integration of AI and IoT technology enables the gradual improvement of medical diagnosis and treatment capabilities so as to provide services to the public in a more effective  ...  The application of artificial intelligence (AI) technology in the medical field has experienced a long history of development.  ...  Gaussian Mixture Models (GMMs), etc.  ... 
doi:10.1007/s11596-021-2486-z pmid:34939144 pmcid:PMC8693843 fatcat:3g3qpksktjhv5koqs3i7ylco7y

2021 AIUM Award Winners

2021 Journal of ultrasound in medicine  
A S82 Moreno M S102 Morgan T S68, S107 Morris R S65 Muhtadi S S5 Munjal H S97, S104 Murrett J S74, S77 Mutambuze J S44, S45, S47 N Nagarajan E S34, S35 Nagdev A S145 Naief A S16 Narayanamoorthy S S65  ...  S133 McWhirter A S123 Mehta-Lee S S55, S64 Melniker L S71 Mendez A S105 Mendez K S74 Mengsteab P S132 Messina M S33 Meteer S S138 Meyer M S54, S63 Michael S S139 Michel B S167 Miller D S11 Miller H S125  ...  For purposes of comparison among the 3 models, the risk threshold below which a lesion would be considered at "low risk for malignancy" was set at <10% for the ADNEX Model.  ... 
doi:10.1002/jum.15752 fatcat:v4nx5fvjwndrzfppaiaylgon64

Oral Talks

2019 European Journal of Clinical Investigation  
The aim of this study was to elucidate whether PE during pregnancy influences liver mitochondrial function in a GDM-associated NAFLD model.  ...  However, 3 weeks of PE during pregnancy was able to attenuate the effects of HFHS and/ or pregnancy on liver mitochondrial function on this animal model of NAFLD.  ...  S3-O6 | Hypercholesterolemic HDL particles lose their atheroprotective potential and become deleterious further enhancing atherosclerotic plaque burden studies in an animal model by MRI S3-O7 | Erythropoietin  ... 
doi:10.1111/eci.13108 fatcat:i6bd4xxgvjc53lebt4ykh6ncuq

Bioimpedance measurement based evaluation of wound healing

Atte Kekonen, Mikael Bergelin, Jan-Erik Eriksson, Annikki Vaalasti, Heimo Ylänen, Jari Viik
2017 Physiological Measurement  
There is a need for an objective and quantitative method for determining the status of a wound without removing the wound dressings.  ...  In this study, we present a geometry-based computational model of an astrocyte that is used to simulate the stimulation and propagation of intracellular astrocytic Ca2+ waves.  ...  Cancer research in the era of next-generation sequencing and big data calls for intelligent modeling We examine the role of big data and machine learning in cancer research.  ... 
doi:10.1088/1361-6579/aa63d6 pmid:28248191 fatcat:sjqhpdu7ubb2fgbgbyyu6hawxm

Learning anatomical image representations for cardiac imaging

Ozan Oktay, Daniel Rueckert
2018
Additionally, a novel image super-resolution framework is introduced for the enhancement of cardiac cine MR images and we show that high resolution image representation can be useful and informative for  ...  To tackle these limitations and enhance the accuracy and robustness of the automated image analysis, this thesis focuses on the development and application of state-of-the-art machine learning (ML) techniques  ...  He has been a constant source of support and inspiration for me, and it has been a great pleasure and privilege to carry out my  ... 
doi:10.25560/56633 fatcat:beqzfg34v5bgpat2ktplfk7hna
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