Abstract #2981

Automatic bullseye analysis of myocardial T1 values: a segmentation approach based on deep learning

Yu-Nian Ou¹, Tsai-Ling Yang¹, Teng-Yi Huang¹, and Ming-Ting Wu²

¹Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, ²Department of Radiology, Kao-Hsiung Veterans General Hospital, Kao-Hsiung, Taiwan

The study presents an automatic segmentation method for short-axis MOLLI data sets. We used a deep learning method based on convolutional neural network to accurately extract walls and blood pool regions of left and right ventricle. We compared the results with a layer-growing method presented in ISMRM 2017 and found that the accuracy of segmentation was significantly improved when using the deep learning method.

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