Abstract
Considering the current pandemic, caused by the spreading of the novel Coronavirus disease, there is the urgent need for methods to quickly and automatically diagnose infection. To assist pathologists and radiologists in the detection of the novel coronavirus, in this paper we propose a two-tiered method, based on formal methods (to the best of authors knowledge never previously introduced in this context), aimed to (i) detect whether the patient lungs are healthy or present a generic pulmonary infection; (ii) in the case of the previous tier, a generic pulmonary disease is detected to identify whether the patient under analysis is affected by the novel Coronavirus disease. The proposed approach relies on the extraction of radiomic features from medical images and on the generation of a formal model that can be automatically checked using the model checking technique. We perform an experimental analysis using a set of computed tomography medical images obtained by the authors, achieving an accuracy of higher than 81% in disease detection.
Highlights
IntroductionThe information is obtained using different techniques (such as X-rays) and thanks to analyses performed by specialists
In radiological examination, the information is obtained using different techniques and thanks to analyses performed by specialists
High resolution computerized tomography (HRCT) patterns of the Coronavirus disease are nonspecific; so, for the radiologist, is so difficult to express a diagnosis of certainty
Summary
The information is obtained using different techniques (such as X-rays) and thanks to analyses performed by specialists. This analysis can only be qualitative because it is performed by an experienced specialists These subjective elements can be affected by different allusions or perceptions on the basis of the morphology of the images and on personal life experience. It is well known that, if a feature is measurable, it will be managed: in the medical field, radiomic features can lead to a quick, low cost and accurate diagnosis In this case, we use these extracted values to create a patient profile and verify if their values belong to a certain medical status. Bugs could be turned into economic or life losses For these reasons, the correctness of a digital system is crucial and the security and safety tasks can be entrusted to formal methods; namely, mathematician techniques allowing one to have a formal proof of the correctness of concurrent systems. An operational semantic manages the possible steps to perform through axioms and transition rules
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