Medical Image Segmentation

Bringing medical images to a human-readable format for further estimation

Hours total

1350

Technical Stack

PCA, Deep learning, Digital filters, HMM, Alexnet, Attention models

Services Involved

Dedicated Team

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OVERVIEW

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.

CHALLENGE

To develop an algorithm for medical image segmentation to enable an automatic phenotypes detection.

Solution

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.

Results

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.

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