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Deep Learning methods for automatic evaluation of delayed enhancement-MRI. The results of the EMIDEC challenge [article]

Alain Lalande, Zhihao Chen, Thibaut Pommier, Thomas Decourselle, Abdul Qayyum, Michel Salomon, Dominique Ginhac, Youssef Skandarani, Arnaud Boucher, Khawla Brahim, Marleen de Bruijne, Robin Camarasa (+21 others)
2021 arXiv   pre-print
First, to evaluate if deep learning methods can distinguish between normal and pathological cases. Second, to automatically calculate the extent of myocardial infarction.  ...  To automatically assess myocardial status, the results of the EMIDEC challenge that focused on this task are presented in this paper. The challenge's main objectives were twofold.  ...  Acknowledgment This work was supported by the ADVANCES project founded by ISITE-BFC project (number ANR-15-IDEX-0003) and by the EIPHI Graduate School (contract ANR-17-EURE-0002).  ... 
arXiv:2108.04016v2 fatcat:2kxgjecvrrc3norhcq26t722we

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  
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  ...  The proposed method was validated by comparing its results to manual drawings by experts from 50 LGE-MR images.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/s22062084 pmid:35336258 pmcid:PMC8954140 fatcat:46rpykoa75awppe5zvmvd335na

Multi-center, multi-vendor automated segmentation of left ventricular anatomy in contrast-enhanced MRI [article]

Carla Sendra-Balcells, Víctor M. Campello, Carlos Martín-Isla, David Vilades Medel, Martín Luís Descalzo, Andrea Guala, José F. Rodríguez Palomares, Karim Lekadir
2021 arXiv   pre-print
Many deep-learning techniques have been proposed to perform automatic segmentations of the left ventricle (LV) in LGE-MRI showing segmentations as accurate as those obtained by expert cardiologists.  ...  The results obtained based on a new multi-center LGE-MRI dataset acquired in four clinical centers in Spain, France and China, show that the combination of data augmentation and transfer learning can lead  ...  EMIDEC dataset: University Hospital Dijon, France This dataset was compiled as part of the automatic Evaluation of Myocardial Infarction from Delayed-Enhancement Cardiac MRI challenge (EMIDEC) [14] .  ... 
arXiv:2110.07360v2 fatcat:6udrjjyurra6va6lnywtlrtpay

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.  ...  The models were trained on the data from the EMIDEC challenge, supplemented with an extensive synthetic dataset generated with a conditional GAN.  ...  Acknowledgments The authors would like to thank the EMIDEC challenge organizers for the evaluation of the test set results.  ... 
arXiv:2109.12940v1 fatcat:ybqacf2xxjfgxaprbahz3o7aqy

A Collaborative Approach for the Development and Application of Machine Learning Solutions for CMR-Based Cardiac Disease Classification

Markus Huellebrand, Matthias Ivantsits, Lennart Tautz, Sebastian Kelle, Anja Hennemuth
2022 Frontiers in Cardiovascular Medicine  
The presented solution supports an iterative training, evaluation, and exploration of machine-learning-based multimodal data interpretation methods considering cardiac MRI data.  ...  We test the presented concept with two use cases from the ACDC and EMIDEC cardiac MRI image analysis challenges.  ...  FUNDING This work was partially funded by the BMBF project Berlin Institute for the Foundations of Learning and Data (Grant Number 01IS18037E) and by the Deutsche Forschungsgemeinschaft (DFG, German Research  ... 
doi:10.3389/fcvm.2022.829512 pmid:35360025 pmcid:PMC8960112 fatcat:i5724wrqz5gxzmjv67vivp2via

Automatic Left Ventricle Segmentation from Short-Axis Cardiac MRI Images Based on Fully Convolutional Neural Network

Zakarya Farea Shaaf, Muhammad Mahadi Abdul Jamil, Radzi Ambar, Ahmed Abdu Alattab, Anwar Ali Yahya, Yousef Asiri
2022 Diagnostics  
The segmentation models were trained and tested on a public dataset, namely the evaluation of myocardial infarction from the delayed-enhancement cardiac MRI (EMIDEC) dataset.  ...  Method: This paper proposes a fully convolutional network (FCN) architecture for automatic LV segmentation from short-axis MRI images.  ...  Deep learning methods have lately obtained excellent results in the segmentation of medical images.  ... 
doi:10.3390/diagnostics12020414 pmid:35204504 pmcid:PMC8871002 fatcat:vvcwdd34uzhktiq6dmybk5hzye

Uncertainty-Guided Mutual Consistency Learning for Semi-Supervised Medical Image Segmentation [article]

Yichi Zhang, Qingcheng Liao, Rushi Jiao, Jicong Zhang
2021 arXiv   pre-print
The framework is guided by the estimated segmentation uncertainty of models to select out relatively certain predictions for consistency learning, so as to effectively exploit more reliable information  ...  Semi-supervised learning has been widely applied to medical image segmentation tasks since it alleviates the heavy burden of acquiring expert-examined annotations and takes the advantage of unlabeled data  ...  delayed enhancement-mri. the results of the emidec challenge,” arXiv the effectiveness and generalization ability of our proposed preprint arXiv:2108.04016, 2021. method, we conduct experiments  ... 
arXiv:2112.02508v1 fatcat:ofgv42dygvhyxphgh2wbcgdvoy

In this issue-Mitochondrial Dynamics as a Potential Therapeutic Target for Parkinson¹s Disease?

Kim Tieu, Jennifer Imm, Sian Alexander, Tony Holland
unpublished
Our attendance in this conference would not have been possible without the support of the ASPiH Travel Bursary and the Department of Neurology, University Hospital Wales.  ...  Tom Hughes for his advice and support in writing this report.  ...  Abstract LBA 40 These results illustrate the challenging behaviour of primary brain cancer.  ... 
fatcat:rvxklktuxvejbo7kgokajo4tb4