The latest advances in artificial intelligence techniques are making it increasingly relate more to the world of medicine and health. Although they have been achieved automate difficult taskscurrent techniques require large databases to learn from.
In many cases, it is difficult to collect databases with thousands of images of each thing that the method to be developed needs to know, either because the images are difficult to obtain or because an expert is needed to spend a lot of time labeling them.[banner-DFP_1]
In this regard, a study carried out by researchers from the group of Visilab researchfrom the Higher Technical School of Industrial Engineering of the University of Castilla-La Mancha (UCLM) and published in the journal “Computer Methods and Programs in Biomedicine”through applications based on computer vision and image processing for diagnosis, has proposed a method that will improve biomedicine.
They have created a new system to generate new images by mixing two of those already available in a small database
To solve the problem of no data in medicine or biology by creating artificial images, they have created a new system for generate new images by mixing two of those already available in a small database.
The work written by the responsible researchers Noelia Vállez, Gloria Bueno and Óscar Déniz, members of the Visilab group and professors from the Higher Technical School of Industrial Engineering; Y Saul Blanco Lanzafrom the Institute of Environment, Natural Resources and Biodiversity of the University of León, shows a developed method that is inspired in the life cycle followed by diatomsmicroscopic algae found in rivers and seas.[banner-DFP_4]
The researchers give an example to understand this new discovery: “It is easy for a person to learn what a chair is by seeing two or threebut for a computer to learn the same thing, it needs to see photos of thousands of different chairs and someone to “teach” it and teach it that these are chairs.
When augmented databases are used with the proposed method, based on the morphing and image registration, the results obtained by artificial intelligence techniques show a clear improvement in accuracy
“It would be like taking two images that we know contain chairs and mix them to obtain a chair of an intermediate size and shape”, says the researcher Vállez.
The work shows that when augmented databases are used with the proposed methodbased on the morphing and image recordingthe results obtained by artificial intelligence techniques show a clear improvement in accuracy.
In this way, the improvement was measured in different databases related to medicine and biology to demonstrate their applicability in different fields and problems.
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