Artificial intelligence Lab

Competence Center of Innopolis University in the field of machine learning, computer vision and data analysis. The main goal of the laboratory is the implementation of scientific and technical projects in various applied industries: medicine, geographic information systems, energy industry, industrial production using artificial intelligence technologies.

Team

Ramil
Kuleev

Head of the AI Lab
Head of the AI Lab

Ibragim
Mergaliev

Developer
Developer

Bulat
Zagidullin

Data Scientist
Data Scientist

Scientific activity

The laboratory of artificial intelligence analyzes computer-generated medical images. The laboratory team is currently working on methods for the segmentation of the pulmonary field, heart and collar bones, ribs suppression on x-ray images of thoracic organs.

Large area is a study aimed to solving the problem of X-ray chest screening (classification of norms and pathologies), accurate differential diagnostics and localization of pathology in the picture. In addition, with X-ray images the research team also performing other types of visual diagnostics, such as computer tomography: the segmentation of kidney and tumors.

The prime tools are methods of machine and deep learning: deep neural networks for classification, encoder-decoder architecture for segmentation, denoising autoencoders for ribcage suppression.

The research group participates in public competitions, collaborates with international universities and leading medical organizations (Republican clinical anti-tuberculosis dispensary, Republican Clinical Hospital No. 1, Republican Clinical Oncology Center, etc.).

Activities

  1. Implementation of industrial projects for commercial and state customers.
  2. R&D for the development of scientific competence of the laboratory, grants and support from institutions and research funds.

Publications

Conference
2019

Data augmentation for chest pathologies classification

Authors: Ilyas Sirazitdinov, Maksym Kholiavchenko, Ramil Kuleev, Bulat Ibragimov
Publisher: IEEE
Source: 2019 IEEE International Symposium on Biomedical Imaging
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Conference
2017

Deep learning models for bone suppression in chest radiographs

Authors: Gusarev Maxim, Kuleev Ramil, Khan Adil, Rivera Adin Ramirez and Khattak Asad Masood
Publisher: IEEE
Source: 2017 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)
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Projects

Artificial intelligence

Development of algorithms and software for automatic filtering of thoracic organs x-ray images


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Artificial intelligence

The development of new mathematical methods and algorithms for the analysis of intrathoracic organs x-ray images for the lung diseases diagnostic automation by solving the problem of classifying images with high intraclass and low interclass dispersion


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Contact us

+7 (843) 203 92 53

robotics@innopolis.ru