Automatic calculation of left ventricular volume in magnetic resonance imaging using an image-based clustering approach

被引：2
|
作者：
Ivanov, Ilia [1 ]
Lomaev, Yuri [1 ]
Barkovskaya, Alexandra [1 ]
机构：
[1] Reshetnev Siberian State Univ Sci & Technol, 31 Krasnoyarsky Rabochy Av, Krasnoyarsk 660037, Russia
来源：
INTERNATIONAL WORKSHOP ADVANCED TECHNOLOGIES IN MATERIAL SCIENCE, MECHANICAL AND AUTOMATION ENGINEERING - MIP: ENGINEERING - 2019 | 2019年 / 537卷
关键词：
SEGMENTATION; MODEL;
D O I：
10.1088/1757-899X/537/4/042046
中图分类号：
TH [机械、仪表工业];
学科分类号：
0802 ;
摘要：
In this work we propose an algorithm to automate the process of left ventricular (LV) volume calculation during magnetic resonance imaging (MRI) analysis. The proposed algorithm does the LV segmentation, volume calculation, finds the time frames where the heart is in systole and diastole phase, and calculates LV ejection fraction. The proposed approach has been tested on a dataset containing MRI study results of 500 patients. According to experimental results the root mean square error of LV systolic volume calculation is 21.64 ml, LV diastolic volume - 44.92 ml, ejection fraction - 7.96 %.
引用
收藏
页数：7
相关论文
共 50 条
  • [41] Preprocedural magnetic resonance imaging for image-guided catheter ablation of scar-related ventricular tachycardia
    Tao, Qian
    Piers, Sebastiaan R. D.
    Lamb, Hildo J.
    Zeppenfeld, Katja
    van der Geest, Rob J.
    INTERNATIONAL JOURNAL OF CARDIOVASCULAR IMAGING, 2015, 31 (02) : 369 - 377
  • [42] Advances in population-based imaging using cardiac magnetic resonance
    Beyer, Sebastian E.
    Petersen, Steffen E.
    PROGRESS IN BIOMEDICAL ENGINEERING, 2019, 1 (01):
  • [43] Development and validation of a new automatic algorithm for quantification of left ventricular volumes and function in gated myocardial perfusion SPECT using cardiac magnetic resonance as reference standard
    Soneson, Helen
    Hedeer, Fredrik
    Arevalo, Carmen
    Carlsson, Marcus
    Engblom, Henrik
    Ubachs, Joey F. A.
    Arheden, Hakan
    Heiberg, Einar
    JOURNAL OF NUCLEAR CARDIOLOGY, 2011, 18 (05) : 874 - 885
  • [44] Accuracy and Time-Efficiency of an Automated Software Tool to Assess Left Ventricular Parameters in Cardiac Magnetic Resonance Imaging
    Bartolome, Pablo
    Caballeros, Meylin
    Quilez-Larragan, Almudena
    Nunez-Cordoba, Jorge M.
    Fernandez Gonzalez, Oscar
    Ezponda, Ana
    Bastarrika, Gorka
    JOURNAL OF THORACIC IMAGING, 2020, 35 (01) : 64 - 70
  • [45] Using Convolutional Encoder Networks to Determine the Optimal Magnetic Resonance Image for the Automatic Segmentation of Multiple Sclerosis
    Ghosh, Shaurnav
    Huo, Marc
    Shawkat, Mst Shamim Ara
    McCalla, Serena
    APPLIED SCIENCES-BASEL, 2021, 11 (18):
  • [46] Automatic magnetic resonance image segmentation by fuzzy intercluster hostility index based genetic algorithm: An application
    De, Sourav
    Bhattacharyya, Siddhartha
    Dutta, Paramartha
    APPLIED SOFT COMPUTING, 2016, 47 : 669 - 683
  • [47] Application of deep learning for automatic segmentation of brain tumors on magnetic resonance imaging: a heuristic approach in the clinical scenario
    Antonio Di Ieva
    Carlo Russo
    Sidong Liu
    Anne Jian
    Michael Y. Bai
    Yi Qian
    John S. Magnussen
    Neuroradiology, 2021, 63 : 1253 - 1262
  • [48] Application of deep learning for automatic segmentation of brain tumors on magnetic resonance imaging: a heuristic approach in the clinical scenario
    Di Ieva, Antonio
    Russo, Carlo
    Liu, Sidong
    Jian, Anne
    Bai, Michael Y.
    Qian, Yi
    Magnussen, John S.
    NEURORADIOLOGY, 2021, 63 (08) : 1253 - 1262
  • [49] Radiotherapy of Hodgkin and Non-Hodgkin Lymphoma: A Nonrigid Image-Based Registration Method for Automatic Localization of Prechemotherapy Gross Tumor Volume
    Zaffino, P.
    Ciardo, D.
    Piperno, G.
    Travaini, L. L.
    Comi, S.
    Ferrari, A.
    Alterio, D.
    Jereczek-Fossa, B. A.
    Orecchia, R.
    Baroni, G.
    Spadea, M. F.
    TECHNOLOGY IN CANCER RESEARCH & TREATMENT, 2016, 15 (02) : 355 - 364
  • [50] Automatic Detection of White Matter Hyperintensities in Healthy Aging and Pathology Using Magnetic Resonance Imaging: A Review
    Caligiuri, Maria Eugenia
    Perrotta, Paolo
    Augimeri, Antonio
    Rocca, Federico
    Quattrone, Aldo
    Cherubini, Andrea
    NEUROINFORMATICS, 2015, 13 (03) : 261 - 276
12345