Lung cancer represents one of the main public health issues and the first cause of cancer-related deaths in developed countries. Most of lung cancers are diagnosed in the last-stage, when the survival rate is very low if compared to the early-stage of the disease. Big technological effort has been put to improve the early diagnosis of lung cancer. Screening high risk population with low-dose Computed Tomography (CT) has been shown to reduce cancer mortality. These improvements have brought with them lots of clinical challenges. One of the biggest is that radiologists have to deal with a high number of images to be analyzed as faster as possible. This big issue has motivated a very deep and heterogeneous research community to develop algorithms to support radiologists in the detection. These algorithms were given the name of Computer-aided Diagnosis (CAD) systems. Despite proved benefits, we are far from a daily usage of these systems in clinical practice. This chapter has the aim to present to readers the motivations / issues underlying the scarce application of CAD systems in clinical practice. Some possible approaches to tackle previous issues are proposed. Special attention is given to achieved results by the author during his PhD project.

Development and application in clinical in clinica routine of Computer-aided Diagnosis systems for the early detection of lung cancer: state-of-art and future challenges / Traverso, Alberto. - ELETTRONICO. - European Project Space on Intelligent Technologies, Software engineering, Computer Vision, Graphics, Optics and Photonics:(In corso di stampa).

Development and application in clinical in clinica routine of Computer-aided Diagnosis systems for the early detection of lung cancer: state-of-art and future challenges

TRAVERSO, ALBERTO
In corso di stampa

Abstract

Lung cancer represents one of the main public health issues and the first cause of cancer-related deaths in developed countries. Most of lung cancers are diagnosed in the last-stage, when the survival rate is very low if compared to the early-stage of the disease. Big technological effort has been put to improve the early diagnosis of lung cancer. Screening high risk population with low-dose Computed Tomography (CT) has been shown to reduce cancer mortality. These improvements have brought with them lots of clinical challenges. One of the biggest is that radiologists have to deal with a high number of images to be analyzed as faster as possible. This big issue has motivated a very deep and heterogeneous research community to develop algorithms to support radiologists in the detection. These algorithms were given the name of Computer-aided Diagnosis (CAD) systems. Despite proved benefits, we are far from a daily usage of these systems in clinical practice. This chapter has the aim to present to readers the motivations / issues underlying the scarce application of CAD systems in clinical practice. Some possible approaches to tackle previous issues are proposed. Special attention is given to achieved results by the author during his PhD project.
European Project Space on Intelligent Technologies, Software engineering, Computer Vision, Graphics, Optics and Photonics
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2658990
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