Isocitrate dehydrogenase (IDH) mutation status has emerged as an important prognostic marker in gliomas.Currently, reliable IDH mutation determination requires invasive surgical procedures. Various studies have demonstrated the efficacy of deep learning in classify IDH status using Magnetic resonance images（MRI）data.In this study we propose a multi-channel architecture of 3D convolutional neural networks (CNNs) based on deep learning to predict the IDH status.We utilize traditional structures imaging and various diffusivity metric maps derived from diffusion tensor imaging (DTI) as input to the network.The final model achieved the AUC value of 0.93.
How to access this content:
For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.
After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.
After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.
Keywords