Automatic segmentation of multiple cardiovascular structures from cardiac computed tomography angiography images using deep learning

PLoS One

7 Maggio Mag 2020 20 days ago
  • Conte E, Andreini D, Pontone G

Segmentation of cardiovascular images is resource-intensive. We design an automated deep learning method for the segmentation of multiple structures from Coronary Computed Tomography Angiography (CCTA) images. Aim of this study is to develop, demonstrate and evaluate an automated deep learning method for multiple cardiovascular structure segmentation.

Reference

Baskaran L, Al'Aref SJ, Maliakal G, Lee BC, Xu Z, Choi JW, Lee SE, Sung JM, Lin FY, Dunham S, Mosadegh B, Kim YJ, Gottlieb I, Lee BK, Chun EJ, Cademartiri F, Maffei E, Marques H, Shin S, Choi JH, Chinnaiyan K, Hadamitzky M, Conte E, Andreini D, Pontone G, Budoff MJ, Leipsic JA, Raff GL, Virmani R, Samady H, Stone PH, Berman DS, Narula J, Bax JJ, Chang HJ, Min JK, Shaw LJ. Automatic segmentation of multiple cardiovascular structures from cardiac computed tomography angiography images using deep learning. PLoS One 2020 May 6;15(5):e0232573. doi: 10.1371/journal.pone.0232573

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