TotIA

Support Systems for the Diagnosis with Radiological Images through Artificial Intelligence

The quick expansion in the number of A.I based methodologies, which can be successfully applied to the analysis of patterns in radiographic images, has caused a revolution in the Medicine area in general, and particularly in Dentistry.

An interdisciplinary group of professionals which includes dentists, physics and engineers, all of them being PhDs, have created TotIA with the aim of providing the expert (Dentist or Radiologist) a very precise tool that can aid in the interpretation, analysis and characterization of radiographic images. Thus accomplishing not only a substantial reduction of the time dedicated to these aspects of the daily routine, but more importantly decreasing the margin of error which exists when the images are interpreted, with the benefits this implies for the patient.

Until this moment, and as an initial stage in the project, we have developed and implemented a friendly and practical software that can be easily integrated in all of the different work platforms that odontogists and radiologists use on a daily basis. This software is capable of detecting and highlighting treatments (e.g crowns, implants, root canals and fillings) and pathologies (e.g caries and periapical lesions) present in an orthopantomography image.

We have currently decided to initiate the development of software that can detect a wide number of pathological lesions, including cancerous lesions, cysts, ameloblastomas, cementoblastomas, cementofibromas, TMJ pathologies (erosions, inflammation), etc. Furthermore, another version of the software will be optimized in order to be used in younger patients.

Our Application

With the software we have created so far, with only a “click” the original image can be exported to the work environment. Once it's there, in a matter of a few seconds and using a wide database that compiles thousands of orthopantomographies that have been extensively reviewed by expert endodontists, an automatic report detailing all of the treatments and pathologies detected by our device is generated.

Our Team

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Francesc Pérez Pastor
PhD Medicina, Dentista Servicio de Salud de las Islas Baleares
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Juan Jiménez Recaredo
PhD Física, ADEMA-Universidad de las Islas Baleares
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Laura López Fuentes
PhD Tecnologías de la Información y Comunicación, Universidad de Luxemburgo
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Fermin Arturo Dalmagro
PhD Física, Universidad Central de Venezuela
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Gustavo Ramírez Galavís
Lic Física, Universidad Central de Venezuela
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Antonio Crespi Tobeña
Master en Big Data, Universidad de las Islas Baleares