Literature DB >> 26625409

Standardized Evaluation System for Left Ventricular Segmentation Algorithms in 3D Echocardiography.

Olivier Bernard, Johan G Bosch, Brecht Heyde, Martino Alessandrini, Daniel Barbosa, Sorina Camarasu-Pop, Frederic Cervenansky, Sebastien Valette, Oana Mirea, Michel Bernier, Pierre-Marc Jodoin, Jaime Santo Domingos, Richard V Stebbing, Kevin Keraudren, Ozan Oktay, Jose Caballero, Wei Shi, Daniel Rueckert, Fausto Milletari, Seyed-Ahmad Ahmadi, Erik Smistad, Frank Lindseth, Maartje van Stralen, Chen Wang, Orjan Smedby, Erwan Donal, Mark Monaghan, Alex Papachristidis, Marcel L Geleijnse, Elena Galli, Jan D'hooge.   

Abstract

Real-time 3D Echocardiography (RT3DE) has been proven to be an accurate tool for left ventricular (LV) volume assessment. However, identification of the LV endocardium remains a challenging task, mainly because of the low tissue/blood contrast of the images combined with typical artifacts. Several semi and fully automatic algorithms have been proposed for segmenting the endocardium in RT3DE data in order to extract relevant clinical indices, but a systematic and fair comparison between such methods has so far been impossible due to the lack of a publicly available common database. Here, we introduce a standardized evaluation framework to reliably evaluate and compare the performance of the algorithms developed to segment the LV border in RT3DE. A database consisting of 45 multivendor cardiac ultrasound recordings acquired at different centers with corresponding reference measurements from three experts are made available. The algorithms from nine research groups were quantitatively evaluated and compared using the proposed online platform. The results showed that the best methods produce promising results with respect to the experts' measurements for the extraction of clinical indices, and that they offer good segmentation precision in terms of mean distance error in the context of the experts' variability range. The platform remains open for new submissions.

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Year:  2015        PMID: 26625409     DOI: 10.1109/TMI.2015.2503890

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  9 in total

1.  Deep learning for cardiovascular medicine: a practical primer.

Authors:  Chayakrit Krittanawong; Kipp W Johnson; Robert S Rosenson; Zhen Wang; Mehmet Aydar; Usman Baber; James K Min; W H Wilson Tang; Jonathan L Halperin; Sanjiv M Narayan
Journal:  Eur Heart J       Date:  2019-07-01       Impact factor: 29.983

2.  Spatio-Temporal Convolutional LSTMs for Tumor Growth Prediction by Learning 4D Longitudinal Patient Data.

Authors:  Ling Zhang; Le Lu; Xiaosong Wang; Robert M Zhu; Mohammadhadi Bagheri; Ronald M Summers; Jianhua Yao
Journal:  IEEE Trans Med Imaging       Date:  2019-09-25       Impact factor: 10.048

3.  The Role of Automated 3D Echocardiography for Left Ventricular Ejection Fraction Assessment.

Authors:  Ernest Spitzer; Ben Ren; Felix Zijlstra; Nicolas M Van Mieghem; Marcel L Geleijnse
Journal:  Card Fail Rev       Date:  2017-11

Review 4.  Harnessing Machine Intelligence in Automatic Echocardiogram Analysis: Current Status, Limitations, and Future Directions.

Authors:  Ghada Zamzmi; Li-Yueh Hsu; Wen Li; Vandana Sachdev; Sameer Antani
Journal:  IEEE Rev Biomed Eng       Date:  2021-01-22

5.  Why rankings of biomedical image analysis competitions should be interpreted with care.

Authors:  Lena Maier-Hein; Matthias Eisenmann; Annika Reinke; Sinan Onogur; Marko Stankovic; Patrick Scholz; Tal Arbel; Hrvoje Bogunovic; Andrew P Bradley; Aaron Carass; Carolin Feldmann; Alejandro F Frangi; Peter M Full; Bram van Ginneken; Allan Hanbury; Katrin Honauer; Michal Kozubek; Bennett A Landman; Keno März; Oskar Maier; Klaus Maier-Hein; Bjoern H Menze; Henning Müller; Peter F Neher; Wiro Niessen; Nasir Rajpoot; Gregory C Sharp; Korsuk Sirinukunwattana; Stefanie Speidel; Christian Stock; Danail Stoyanov; Abdel Aziz Taha; Fons van der Sommen; Ching-Wei Wang; Marc-André Weber; Guoyan Zheng; Pierre Jannin; Annette Kopp-Schneider
Journal:  Nat Commun       Date:  2018-12-06       Impact factor: 14.919

Review 6.  Artificial intelligence and echocardiography.

Authors:  M Alsharqi; W J Woodward; J A Mumith; D C Markham; R Upton; P Leeson
Journal:  Echo Res Pract       Date:  2018-12-01

Review 7.  Advanced Ultrasound and Photoacoustic Imaging in Cardiology.

Authors:  Min Wu; Navchetan Awasthi; Nastaran Mohammadian Rad; Josien P W Pluim; Richard G P Lopata
Journal:  Sensors (Basel)       Date:  2021-11-28       Impact factor: 3.576

8.  A Combined Fully Convolutional Networks and Deformable Model for Automatic Left Ventricle Segmentation Based on 3D Echocardiography.

Authors:  Suyu Dong; Gongning Luo; Kuanquan Wang; Shaodong Cao; Qince Li; Henggui Zhang
Journal:  Biomed Res Int       Date:  2018-09-10       Impact factor: 3.411

Review 9.  Deep Learning for Cardiac Image Segmentation: A Review.

Authors:  Chen Chen; Chen Qin; Huaqi Qiu; Giacomo Tarroni; Jinming Duan; Wenjia Bai; Daniel Rueckert
Journal:  Front Cardiovasc Med       Date:  2020-03-05
  9 in total

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