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SynDiag – EARLIER ULTRASOUND Diagnosis OF CANCER

Artificial intelligenceautomatic medical analysisDecision supportEarlier diagnosisquantitative EchographyUltrasound scan

Introduction

Ultrasound scan (US) is worldwide the most performed medical images diagnosis exam. Despite its great potential, such a technique depends extensively on operator’s experience. SynDiag performs analysis of ultrasound scans and, through Artificial Intelligence algorithms, extrapolate features specific of cancer, in particular of ovarian cancer. In such a way, the physician receives real-time a decision support and accurate information about the cancer features to be evaluated for an earlier diagnosis.

Technical features

SynDiag is a software operating in cloud and based on Artificial Intelligence and Image Processing algorithms. It can be interfaces with all ultrasound machines already on the market and uses data in standard format.

The physicians can access the platform from browser in order to obtain an augmented ultrasound scan exam, that put in evidence the presence of cancer features and and quantitative informations like dimensions.

Today SynDiag is developed for ovarian cancer, sixth cancer by mortality in Europe and first among gynecologic cancers, and it is designed to identify features accordingly to international guidelines. In such a way, the software provides real-time informations useful for earlier diagnosis, favours the adoption of a standardized diagnosis procedure and provides an automatic and editable medical report.

Possible Applications

  • Developed for gynecologic oncology, ovarian cancer;
  • Applicable to all cancer pathologies;
  • Generation of quantitative large database available to physicians and healthcare institutions;
  • Allow automatic, editable medical reporting.

Advantages

  • Ultrasound quantitative analysis;
  • Features detection according to interantional guidelines;
  • Fully automatic process;
  • Easy to use without special training;
  • Embeddable on existing technology;
  • Real time support to the physician;
  • Fully working on the cloud.