That’s the border – inside the body
This year’s Forskningstorget at Festplassen was arranged by the National Research Council. Pupils from 6th and 7th class in the primary school were invited to participate on Friday, whereas Saturday stands were open to the public. The tent at Festplassen was quite crowded both days. The general topic this year was “borders” and MedViz’ chosen theme was “That’s the border – inside the body”.
The Friday crew from the left: Lionel Giriteka, Ragnar Nortvedt, Stajer Gabor, Rodrigo Vilaca, Kiniena Tekie, Alexander Lundervold, Jonas Lundervold and Arvid Lundervold. Per Refsnes also participated on Saturday (not present at the picture).
We illustrated this theme by two different angles of approach, in close cooperation with the Engineer Department at Bergen University College:
- A visualization of automatic classification of different brain tissues
- A visualization of the similarity (or border) between a life science and an engineer science approach in analyzing images, e.g. during image segmentation of brain (life science) and car traffic (engineer science) and how both approaches can be implemented in machine learning and eventually robotics
Where is the border between life science and engineer science(?) on the left monitor, -and automatic face tracking on the right monitor.
MedViz is continuously working to improve image acquisition, image analysis and visualization of different organs (e.g. kidneys and brain), the cardiovascular system and muscle tissue in the body. The images often originate from microscopy, ultrasound, x-ray tomography (CT), magnetic resonance imaging (MRI), nuclear medicine imaging (PET) or combinations of those.
Image based and automatic classification of brain tissue.
The first approach above was visualized by showing how MRI could be applied to automatically draw borders in images of different brain tissues (colour coded classes of tissue).
Visualization is a set of methods to interpret and show the images, reconstruct 3-D models of an organ and to convey the advanced image information together with other physiologic or anatomic data in an understandable manner to health personnel and to patients.
A dynamic image of the movable kidney during breathing or other body movements. The border to the surrounding tissues and all tissue inside the border must be kept fixed through mathematic movement correction, in order for calculation of the kidney’s function shall be possible.
The second approach above was visualized by a video showing how computers and eventually robots can be trained to perform predefined tasks in the health sector. Will we see robots in the hospitals in the near future? To catch the attention of the children, the Bergen University College also had installed lego cars (robots) that were programmed to drive at a table, however, to stop and turn when they reached the border of the table, noted by a sensor under the car.
We also arranged a Kahoot based questionnaire that was very engaging and successful in activating the kids and the general public to learn more about image analysis.
Kahoot based questionnaire engaged the pupils.