Abstract #1594

Intracranial aneurysms (IA) segmentation from 3D TOF-MRA and black-blood MRI (BB-MRI) using a deep convolutional neural network

Miaoqi Zhang¹, Shuo Han², Aaron Carass², Fei Peng³, Aihua Liu³, Jerry L. Prince², and Rui Li¹

¹Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing, China, ²The Johns Hopkins University, Baltimore, MD, United States, ³Department of Interventional Neuroradiology, Beijing Neurosurgical Institute and Beijing Tiantan Hospital, Capital Medical University, Beijing, China

In this work, we proposed an automatic segmentation algorithm of intracranial aneurysms from dual input 3D TOF-MRA and black-blood MRI (BB-MRI) using a deep convolutional neural network to study its clinical potential for assisting intracranial aneurysm detection. The positioning of an intracranial aneurysm can benefit from the TOF-MRA, and the BB-MRI image can be used to accurately trace its boundary and measure its size. The average Dice coefficients are 0.69 and 0.73 for the TOF-MRA and the BB-MRI images, respectively.

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