AI Radiology Platform

Your DICOM analysis boosted

AI Radiology Platform - faster and better treatment

Spend less time on single analyse and have more time to focus on truly challenging cases. See how AI Radiology Platforms works!

1. Image acquisition

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2. Safe storage

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3. Finding ROI

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4. Characterization

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5. Deep learning

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6. Diagnosis & staging

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7. Experts collaboration

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8. Reporting

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9. Faster and better treatment

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We won MICCAI 2015 and 2016

Challenge cup
Medical Image Computing and Computer Assisted 2015

Competitions in the field of “Imaging & Digital Pathology”

  • 1st place in the competition in the Combined Radiology and Pathology Classification (Classification based on images of radiological and histological examinations)
  • 3th place in Segmentation of Nuclei in Pathology Images (segmentation of cells in histological images).

Read more about MICCAI 2015 Workshop and Challenges in Imaging & Digital Pathology

Greater productivity thanks to AI Radiology Platform

Plentiful, personalised, reproducible and objective data


Visual analysis can extract only about 10% of the information contained in a digital medical image. Radiology Platform converts the digital image into a huge quantity of data. To clarify, they are computed with specific mathematical algorithms and could not be processed by human eye in the same time. The evaluated features describe imaging parameters as intensity, shape, size, volume, textures, etc. In other words, extracting an enormous wealth of quantitative data from medical images surpass humans possibilities.


Fisrtly Radiology Platform provides trained radiologists with pre-screened images and identified features, Secondly, data-driven approach allows for more abstract feature definitions, making it more informative and generalizable. In addition, diagnoses are more accurate thanks to built-in algorithms that reduce the risk of subjective description of tumour. What is more, decision supported by AI can be shared with other specialists to resolve any doubts. To sum up, diagnoses are double checked, more precise and less subjective.


Tumours variability provides valuable information on both the aggressiveness and therapeutic response. Radiology Platform can be used to investigate those characteristics. Data extracted from different spatial and temporal levels are used for the development of diagnostic and prognostic models. Thanks to that, specialists can predict the right treatment, for the right patient, at the right time. Certainly, the future of patient care is dependent on artificial intelligence.


Radiology Platform extracts qualitative and quantitative characteristics out of medical images. Experts provide details on size, location and morphology using built-in features. Complete confidentiality is ensured throughout the entire process. All extracted data are stored, viewed, shared and evaluated without data sharing and privacy concerns. Therefore, doctor to doctor cooperation within the organization as well as outside is highely improved.