Lene: I am a researcher in the fish health group at Nofima (an institute for applied research within the fields of fisheries, aquaculture and food research).
In Aiforia we have developed a model that recognizes the successive tissues in Atlantic salmon skin.
We have analyzed skin from Atlantic salmon with bacterial diseases, parasites and how the skin responds to handling operations such as mechanical de-lousing and transportation.
There are many advantages with Aiforia. We can measure and count tissue, which is impossible to do manually. We can have large sample sets, which makes the analysis more accurate, and continuous data is also a big advantage.
My expectations were not too high. Last year we decided to give Aiforia a try, however I am very impressed with the platform and what it can learn!
No.
We stained our skin sections with AB/PAS. Now we have 200 slides in our project. The AI-model worked very well with fewer slides, but whenever we have experiments with different fish sizes, infection, wound healing trial, or batches that stain in different shades of the AB/PAS color we add some more training in order to make the AI-model even more efficient.
The AI-model is in continuous work. We are about to publish results from one trial, however, the AI-model will have to evolve with the input samples and staining.
During my work developing the AI-model I have spent many hours drawing annotation regions, this has given me a deeper understanding of the tissue that I work with, and maybe we even have discovered some new functions of the skin which we plan to look at closer in future projects.