Rapid diagnosis and continuous monitoring of intracerebral hemorrhage with magnetic induction tomography based on stacked autoencoder.

Magnetic induction tomography (MIT) is a promising approach in rapid diagnosis and continuous monitoring of cerebral hemorrhage. A new algorithm for the reconstruction of intracerebral hemorrhage with MIT, including the location and volume of hemorrhage, is proposed in this study. First, 2D magnetic resonance imaging and computed tomography images of patients with cerebral hemorrhage were used for the development of simulation models. The Stacked Autoencoder (SAE) network was then used to predict the location and volume of hemorrhage by conductivity reconstruction. Finally, the one-dimensional quantitative monitoring index is proposed as an auxiliary diagnostic indicator for assessment of real-time intracranial electrical characteristics. The 2D simulation results showed that the SAE was able to quickly image the location and volume of the hemorrhages. Compared with the back-projection algorithm, the prediction speed of each frame was improved 15-fold, and the accuracy improved by 90.53%. The extracted one-dimensional quantitative monitoring indicators can describe the bleeding status. The diagnostic accuracy and the imaging speed of cerebral hemorrhage were both improved by constructing a realistic head section model and using the proposed SAE network. This research provides a new alternative for dynamic monitoring of hemorrhages and shows the potential advantages of MIT in noninvasive detection.