3D Right Ventricle Reconstruction from 2D U-Net Segmentation of Sparse Short-Axis and 4-Chamber Cardiac Cine MRI Views

Tautz, Lennart; Walczak, Lars; Manini, Chiara; Hennemuth, Anja; Hüllebrand, Markus

doi:10.1007/978-3-030-93722-5_38

Cited by 2 publications

(1 citation statement)

References 14 publications

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“…The model was generated from a 3D b-SSFP MRI sequence and the measurement results showed a good correlation compared to those generated from 3D echocardiography. Tautz et al [40] proposed a 3D model of the right ventricle using 2D U-Net. Similarly, Küstner et al [41] developed a new algorithm based on deep learning for 3D reconstruction of the right ventricle using cine MRI images.…”

Section: Cardiac Cine Mri Segmentation Methodsmentioning

confidence: 99%

Ventricular segmentation and modeling using topological watershed transformation and harmonic state model

Mahmoudi

2022

Int J Imaging Syst Tech

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This paper proposes an adapted ventricular segmentation method based on topological watershed transform. Segmentation will allow spatio-temporal modeling of trajectories of the different points belonging to the borders of the ventricle using a harmonic motion model that is able to describe such motion over the entire cardiac cycle. In addition, extraction of the adopted canonical state vector and the corresponding state equations guarantees an optimal efficacy and a gradual transition from order n to order n+1. To validate the proposed approach, an intern-image base was used. Our results show a promising ability to discern whether subjects are healthy or pathological with an 80% success rate.

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Section: Cardiac Cine Mri Segmentation Methodsmentioning

confidence: 99%

Ventricular segmentation and modeling using topological watershed transformation and harmonic state model

Mahmoudi

2022

Int J Imaging Syst Tech

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Deep Learning Segmentation of the Right Ventricle in Cardiac MRI: The M&Ms Challenge

Martín-Isla

Campello

Izquierdo

et al. 2023

IEEE J. Biomed. Health Inform.

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3D Right Ventricle Reconstruction from 2D U-Net Segmentation of Sparse Short-Axis and 4-Chamber Cardiac Cine MRI Views

Cited by 2 publications

References 14 publications

Ventricular segmentation and modeling using topological watershed transformation and harmonic state model

Ventricular segmentation and modeling using topological watershed transformation and harmonic state model

Deep Learning Segmentation of the Right Ventricle in Cardiac MRI: The M&Ms Challenge

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