Right Ventricle Segmentation of Magnetic Resonance Image Using the Modified Convolutional Neural Network

In this paper, the segmentation model is developed using the convolutional neural network for automatic segmentation of a right ventricle MRI image. The proposed model is trained end-to-end using an RVSC dataset that contains the right ventricle magnetic resonance images. The proposed model gives state-of-art achievement for dice metric and also for the Jaccard index. The proposed model achieves an optimal model performance of dice metric performance with 0.91 (0.10) for the training dataset and 0.88 (0.12) for the validation dataset.