Bibliographic Details
| Title: |
Emidec: A Database Usable for the Automatic Evaluation of Myocardial Infarction from Delayed-Enhancement Cardiac MRI |
| Authors: |
Alain Lalande, Zhihao Chen, Thomas Decourselle, Abdul Qayyum, Thibaut Pommier, Luc Lorgis, Ezequiel de la Rosa, Alexandre Cochet, Yves Cottin, Dominique Ginhac, Michel Salomon, Raphaël Couturier, Fabrice Meriaudeau |
| Source: |
Data, Vol 5, Iss 4, p 89 (2020) |
| Publisher Information: |
MDPI AG, 2020. |
| Publication Year: |
2020 |
| Collection: |
LCC:Bibliography. Library science. Information resources |
| Subject Terms: |
MRI, heart, myocardial infarction, normal case, delayed-enhancement, segmentation, Bibliography. Library science. Information resources |
| More Details: |
One crucial parameter to evaluate the state of the heart after myocardial infarction (MI) is the viability of the myocardial segment, i.e., if the segment recovers its functionality upon revascularization. MRI performed several minutes after the injection of a contrast agent (delayed enhancement-MRI or DE-MRI) is a method of choice to evaluate the extent of MI, and by extension, to assess viable tissues after an injury. The Emidec dataset is composed of a series of exams with DE-MR images in short axis orientation covering the left ventricle from normal cases or patients with myocardial infarction, with the contouring of the myocardium and diseased areas (if present) from experts in the domains. Moreover, classical available clinical parameters when the patient is managed by an emergency department are provided for each case. To the best of our knowledge, the Emidec dataset is the first one where annotated DE-MRI are combined with clinical characteristics of the patient, allowing the development of methodologies for exam classification as for exam quantification. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
2306-5729 |
| Relation: |
https://www.mdpi.com/2306-5729/5/4/89; https://doaj.org/toc/2306-5729 |
| DOI: |
10.3390/data5040089 |
| Access URL: |
https://doaj.org/article/64cc46be7c7d45a4a5af899ed46638c3 |
| Accession Number: |
edsdoj.64cc46be7c7d45a4a5af899ed46638c3 |
| Database: |
Directory of Open Access Journals |
