Medical Image Segmentation
PCA, Deep learning, Digital filters, HMM, Alexnet, Attention models
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One of the most popular AI techniques in healthcare segment is medical image processing. The core idea is to use the advance computer vision, statistical and machine learning algorithms to extract information from various types of medical images such as X-rays, MRT, etc. and bring it to a human-readable format for further estimation.
To develop an algorithm for medical image segmentation to enable an automatic phenotypes detection.
The advanced computer vision and machine learning algorithms for image processing and recognition including rescaling, normalization, cascade filtering, convolutional neural networks, deep learning, etc were used. The algorithms results were analyzed and confirmed by highly qualified medical specialists.
A user-friendly API model development for various image processing tasks with a possibility of getting a clear code documentation and a report with the experiment details and the results analysis.
Our latest challenges where technology meets creativity
Hardware development for biosignal acquisition and algorithms for data processing and pattern recognition
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