OBJECTIVES: Automatic slice alignment is important for easier operation and shorter examination times in cardiac magnetic resonance imaging (MRI) examinations. We propose a new automatic slice alignment method for six cardiac planes (short-axis, vertical long-axis, horizontal long-axis, 4-chamber, 2-chamber, and 3-chamber views). MATERIALS AND METHODS: ECG-gated 2D steady-state free precession axial multislice images were acquired using a 1.5-T MRI scanner during a single breath-hold. The scanning time was set to <20 s in 23 volumes from 23 healthy volunteers. In this method, the positions of the mitral valve, cardiac apex, left ventricular outflow tract, tricuspid valve, anterior wall of the heart, and right ventricular corner are detected to determine the positions of six reference planes by combining knowledge-based recognition and image processing techniques. In order to evaluate the results of automatic slice alignment for the short-axis, 4-chamber, 2-chamber, and 3-chamber views, the angular and positional errors between the results obtained by our proposed method and by manual annotation were measured. RESULTS: The average angular errors for the short-axis, 4-chamber, 2-chamber, and 3-chamber views were 3.05°, 4.52°, 7.28°, and 5.79°, respectively. The average positional errors for the short-axis (base), short-axis (apex), 4-chamber, 2-chamber, and 3-chamber views were 6.61°, 3.80°, 1.55°, 1.52°, and 1.48°, respectively. CONCLUSION: The experimental results showed that our proposed method can detect the cardiac planes quickly and accurately. Our method is therefore beneficial to both patients and operators.
OBJECTIVES: Automatic slice alignment is important for easier operation and shorter examination times in cardiac magnetic resonance imaging (MRI) examinations. We propose a new automatic slice alignment method for six cardiac planes (short-axis, vertical long-axis, horizontal long-axis, 4-chamber, 2-chamber, and 3-chamber views). MATERIALS AND METHODS: ECG-gated 2D steady-state free precession axial multislice images were acquired using a 1.5-T MRI scanner during a single breath-hold. The scanning time was set to <20 s in 23 volumes from 23 healthy volunteers. In this method, the positions of the mitral valve, cardiac apex, left ventricular outflow tract, tricuspid valve, anterior wall of the heart, and right ventricular corner are detected to determine the positions of six reference planes by combining knowledge-based recognition and image processing techniques. In order to evaluate the results of automatic slice alignment for the short-axis, 4-chamber, 2-chamber, and 3-chamber views, the angular and positional errors between the results obtained by our proposed method and by manual annotation were measured. RESULTS: The average angular errors for the short-axis, 4-chamber, 2-chamber, and 3-chamber views were 3.05°, 4.52°, 7.28°, and 5.79°, respectively. The average positional errors for the short-axis (base), short-axis (apex), 4-chamber, 2-chamber, and 3-chamber views were 6.61°, 3.80°, 1.55°, 1.52°, and 1.48°, respectively. CONCLUSION: The experimental results showed that our proposed method can detect the cardiac planes quickly and accurately. Our method is therefore beneficial to both patients and operators.
Authors: Adriana Argentiero; Giuseppe Muscogiuri; Mark G Rabbat; Chiara Martini; Nicolò Soldato; Paolo Basile; Andrea Baggiano; Saima Mushtaq; Laura Fusini; Maria Elisabetta Mancini; Nicola Gaibazzi; Vincenzo Ezio Santobuono; Sandro Sironi; Gianluca Pontone; Andrea Igoren Guaricci Journal: J Clin Med Date: 2022-05-19 Impact factor: 4.964
Authors: Francisco Contijoch; Yuchi Han; Srikant Kamesh Iyer; Peter Kellman; Gene Gualtieri; Mark A Elliott; Sebastian Berisha; Joseph H Gorman; Robert C Gorman; James J Pilla; Walter R T Witschey Journal: PLoS One Date: 2020-12-29 Impact factor: 3.752