Which challenges are responded by sens.Ai?

  • Cancer diseases are one of the biggest threats facing modern medicine. Although brain tumors are relatively rare, poor prognosis for patients with a survival rate of 14-15 months after diagnosis makes them a significant health problem.
  • Limited processing capacity of radiologists. According to a report by the Brookings Institution, affordability and use of medical services will increase – it is estimated that there are about 4 billion people worldwide with limited access to radiological examinations. The solution may be modern technologies, automating the analysis of a large amount of data that man is not able to process and extracting information that the human eye does not see.
  • Objectivization of results – results of algorithm operation are free from human eye errors and always repeatable. This means that the same change will be segmented in the same way each time it is processed by the program. Sens.AI provides a qualitatively reproducible number.

Solution

Sens.AI enables effective and fully automated analysis of medical images obtained during head examination with magnetic resonance imaging in the T2-FLAIR 3D sequence.

Algorithms used to segment homogeneous pathological lesions and to calculate their volume were taught and validated on a data set of 281 medical MRI studies in the T2-FLAIR 3D sequence.

Sens.AI determines easy to interpret and analyze visualizations of cancer areas and calculates the volume of the largest, homogeneous lesion.

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Automation
User-free analysis process
Precision
Human error free
Diagnostic support
Possibility to assess risk in patients with cancer
Time saving
Automated segmentation and analysis of medical images

MAGNETIC RESONANCE

AUTOMATED SEGMENTATION AND ANALYSIS

ANALYSIS REPORT

INTERPRETATION OF RESULTS BY A RADIOLOGIST

How it works

The patient is subjected to a magnetic resonance examination performed in the T2 FLAIR 3D sequence. Then, the images obtained in this way are analyzed by the Sens.AI system, which, using specialized algorithms, performs segmentation and calculates the volume of the largest consistent pathological lesion.

What is important is that the whole process takes place automatically, without the need for user intervention.

Once the cycle is complete, Sens.AI generates a clear and easy to interpret report in the form of DICOM files. The report can be uploaded to a PACS database or saved on a desktop computer.

The operation of Sens.AI is based on algorithms using advanced Machine Learning techniques, especially Deep Learning.

The report contains:

  • Segmented LGG or HGG changes
  • Calculated volume of the largest homogeneous pathological lesion given in mm3

Did

you know...

1 minute
time needed for Sens.AI to process one complete scan
CE marking
certification is in progress
281 MRI studies
were used to train algorithm

Benefits

Fully automatic and very fast segmentation and analysis of medical images

Sens.AI processes one full scan in 1 minute and the process is fully automated.
Thanks to Sens.AI, image data processing is performed without user intervention.

Time saving

Did you know that during his career a radiologist looks at 10,000,000 pictures?
Sens.AI works fully automatically and reduces the time needed to analyze images. Sens.AI supports the work, but it is up to the radiologist to interpret the results.

Patient-centred approach

Sens.AI supports the process of image analysis in personalized oncology.
The system helps to objectively track the progress of the disease and the patient's response to therapy.

Repeatability of results

Sens.AI delivers reliable and repeatable results.
They are independent of the manufacturer of the hardware platform and the unreliable factor, which is the human eye.

Diagnostic process support

Sens.AI analyzes every pixel of a medical image in search of relevant diagnostic information.
Its operation is based on innovative algorithms in the field of Machine Learning, whose work is very precise.

DICOM files

In Sens.AI, the analysis and comparison of results is possible with public DICOM file viewers.

What do we offer?

Sens.AI is a solution tailored to the client’s needs. We offer:

  • Innovative algorithms for segmentation of LGG and HGG – for clinicians looking for a modern and reliable tool for segmentation.
  • Innovative algorithms precisely calculating the volume of the lesion.
  • Image analysis and automatic data processing services.

Our competences

MEDICAL STANDARDS

We operate under a certified ISO 13485 quality management system.

Future Processing specialists are also familiar with ISO 14971 and can develop software in compliance with IEC 62304. This enables us to cooperate with institutions and prominent figures in the field of medical diagnostics.

MEDICAL AUTHORITIES

Sens.AI has been created in close cooperation with Maria Skłodowska-Curie Institute Oncology Centre in Gliwice (Centrum Onkologii – Instytut im. Marii Skłodowskiej-Curie, Oddział w Gliwicach).

The Oncology Center is a multidisciplinary oncological center offering cancer patients specialised methods combination therapies for all types of cancer that are recognised in the world. It has experienced and expert staff, trained in the European and American centres, and in all areas of oncology.

The Sens.AI system is carried out with the Department of Radiology and Imaging Diagnostics of the Oncology Centre.

10+ YEARS OF EXPERIENCE
Future Processing has more than ten years of experience developing medical imaging solutions.
69 EXPERTS
We have 69 experts specialised in computer vision.
SPECIALISTS
We employ specialists in machine learning and medical imaging.
ALGORITHMS
Our professionals design and develop innovative algorithms.

Interdisciplinary team

We have three expert teams working on Sens.AI.

Sens.AI has been developed by the
Future Healthcare division comprising:

1. RESEARCH TEAM
Responsible for algorithm design and analysis. The team is made up of experienced researchers (doctors in physical and technical sciences).
2. DEVELOPMENT TEAM
Experienced software engineers and computer scientists responsible for implementation and integration.
3. BUSINESS TEAM
Experienced managers and business analysts bringing the Sens.AI system to market and making sure that the system meets high demands of healthcare professionals.

About us


Future Processing is a dynamically growing IT company that develops specialised computer software for the purposes of contemporary medicine and broad healthcare sector as well as international industry, trade and services.

We are a company whose mission is to meet the needs of individuals and communities in order to provide them with healthier and safer lives. With the mission in mind, we created a Healthcare unit that works on medical imaging projects to support the physician and the diagnostic process.

The company boasts years of experience in developing its own products and implementing R&D projects, also in the field of medicine. For many years, our specialists have been developing their competences in machine learning by applying their knowledge to diagnostic imaging, among others.

Products aimed for the medicine sector are developed by interdisciplinary teams whose members combine academic competences with technical skills. Our experts actively contribute to the growth of machine learning domain through scientific publications and cooperation with universities.

Future Processing and its Healthcare unit also boast cooperation with renowned academic and medical centres in Poland and abroad.

The company was established in 2000 by Jarosław Czaja, and currently employs more than 700 people. Future Processing is a team of top-class specialists who appreciate the opportunity to grow and work with ambitious projects, which often require solutions that combine multiple domains. This provides our clients with the software they need.

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Contact us

E-mail us and learn how Sens.AI can support you and your work.
Our experts will be happy to tell you about the system operation and demonstrate its possibilities.

The personal data controller is Future Processing Sp. z o.o. For more information on data processing, visit the Privacy policy tab.

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