Abstract
Cerebral subdural hematomas due to trauma can easily worsen suddenly due to the rupture of blood vessels in the brain after the condition is stabilized. Therefore, continuous monitoring of the size of cerebral subdural hematomas has important clinical significance. To achieve fast, real-time, noninvasive, and accurate monitoring of subdural hematomas, a cerebral subdural hematoma monitoring method combining brain magnetic resonance imaging (MRI) image guidance, diffusion optical tomography technology, and deep learning is proposed in this manuscript. First, an MRI brain image is segmented to obtain a three-dimensional multi-layer brain model with structures and parameters matching a real brain. Then, a near-infrared light source and detectors (source-detector separations ranging from 0.5 to 6.5 cm) were placed on the model to achieve fast, real-time and noninvasive acquisition of intracranial hematoma information. Finally, a deep learning method is used to obtain accurate reconstructed images of cerebral subdural hematomas. The experimental results show that the reconstruction effect of stacked auto-encoder with the mean volume error of 0.1 ml is better than the result reconstructed by algebraic reconstruction techniques with the mean volume error of 0.9 ml. Under different signal-to-noise ratios, the curve fitting R2 between the actual blood volume of a simulated hematoma and a reconstructed hematoma is more than 0.95. We conclude that the proposed monitoring method can realize fast, noninvasive, real-time, and accurate monitoring of subdural hematomas, and can provide a technical basis for continuous wearable subdural hematoma monitoring equipment.
Highlights
External forces acting on the head can often cause intracranial hemorrhage leading to subdural hematomas
This study conducted a comparison experiment to review the accuracy of subdural hematoma reconstruction based on the stacked auto-encoder (SAE) network versus the traditional algebraic reconstruction technique (ART) algorithm
On a CPU configured with an Intel (R) Core (TM) i5-8400 computer, the subdural hematoma reconstruction of the two algorithms takes about 15s and about 3 minutes, respectively
Summary
External forces acting on the head can often cause intracranial hemorrhage leading to subdural hematomas. A typical feature of consciousness changes in patients with a cerebral subdural hematoma is the process of losing consciousness, waking and losing consciousness again i.e. there is an intermediate period when the patient is awake. Patients with cerebral subdural hematomas should firstly undergo magnetic resonance imaging (MRI) or computerized tomography (CT) examinations, and stay in hospital for a week for observation. During this time, real-time monitoring of subdural hematoma patients is required. For real-time monitoring requirements of cerebral subdural hematoma patients, current clinical imaging technology cannot continuously monitor the condition of cerebral subdural hematoma patients for a long time
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