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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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