Scientists from the Moscow Institute of Physics and Technology (MIPT) have created a computer model of the heart designed to treat atrial fibrillation. The developed automated system segments MRI images of the heart with high accuracy. In the future, this system can significantly facilitate the work of cardiologists.
Atrial fibrillation, also known as atrial fibrillation, is one of the most common heart rhythm disorders. According to scientists' estimates, about 2% of the population suffers from this disease. It is expected that over the next two decades, the prevalence of atrial fibrillation among people over 60 years of age will reach 60%.
With this disease, the atria contract chaotically and ineffectively, which leads to an uneven heartbeat. Patients with atrial fibrillation may experience shortness of breath, dizziness, and weakness.
One of the treatments for atrial fibrillation is catheter ablation. This is a surgical operation that aims to destroy areas of tissue that cause heart rhythm disturbances. This method can be effective, especially if the arrhythmia manifests periodically. However, the disease often returns.
A recent study conducted at MIPT showed that the use of digital heart models created based on magnetic resonance imaging data can help reduce the number of repeated cases of arrhythmia.
We have created a special dataset and standardized protocols for manual labeling to improve segmentation accuracy and make the process less time-consuming for doctors. To do this, we collected MRI heart data from two databases. After that, two specialists manually labeled them, following standard protocols, in order to reduce the number of errors. The nnU-Net and smpU-Net++ neural network models were used to automate the segmentation process.
Earlier, scientists from ITMO University and the V. A. Almazov National Medical Research Center developed an innovative algorithm that uses artificial intelligenceto quickly detect cardiac fibrosis. Thanks to this algorithm, the process of processing MRI images is significantly accelerated - from 1-2 hours to several minutes.
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