Analyze microscopic images
These days most of the SEM and optical microscopes create digital images. This development makes it easier to automate and process images. The detection can be used for scientific research to generate a large amount of data or to semi automate a diagnosis. When there is a large amount of annotated data available, we can use deep learning techniques to analyse new images as well. If there is less data available we can also recognize images with the use of classic image recognition techniques.
3D image recognition on volumes
A lot of medical imagery techniques result in volumetric data by creating depth from several images. These 3D images are suitable to automatically categorize certain areas. Specific tissues or structures can be recognized via a scan by recognizing their signatures. When data is available over time, we can even see the movement of different objects related to each other.
3D image recognition on volumes
A lot of medical imagery techniques result in volumetric data by creating depth from several images. These 3D images are suitable to automatically categorize certain areas. Specific tissues or structures can be recognized via a scan by recognizing their signatures. When data is available over time, we can even see the movement of different objects related to each other.
Artificial Intelligence for medical use
The last few years there have been several examples of medical developments with the use of artificial intelligence. Many of these developments are within the area of medical imaging, especially to automate the segmentation or to identify different parts of the human body in 2D or even 3D images (for example in DICOM format). The purpose of many of these developments is to save time and give a specialist a correct insight of what is needed to make the right diagnosis. Within the medical research it is important to have a large amount of data that can be annotated automatically to come up with a correct conclusion and AI can save enormous of time doing this.
Thermal image recognition
Thermal imaging is not often used within medical context. There are several possibilities to automate the detection of body temperatures or to detect anomalies with the use of thermal cameras. This way whenever there is a large stream of people it is possible to automatically see whoever has got a high temperature or fever. It can also detect if, and on what body part the temperature is spreading.
Thermal image recognition
Thermal imaging is not often used within medical context. There are several possibilities to automate the detection of body temperatures or to detect anomalies with the use of thermal cameras. This way whenever there is a large stream of people it is possible to automatically see whoever has got a high temperature or fever. It can also detect if, and on what body part the temperature is spreading.
Apps as medical devices
In healthcare we see a tendency to move towards the use of apps or software to support regular care programs. These are for instance apps that help in diagnosing over distance, but also measuring health or tracking progress over time. We have experience in developing image recognition modules that can be integrated in medical apps. We have built the back end of computer vision app that determines the length of a person, but also software that is able to detect physical test results. During development we always take the legislation for medical devices in account to get the required CE marking. We are acquainted with the demand in reproducibility and documentation for the different classes in this process as well as privacy legislation for medical data.
