Computer-aided diagnosis (CAD) systems are software algorithms designed to assist radiologists (or other practitioners) in solving a diagnostic problem by using a visual prompt (or "CAD mark") to direct the observer towards potential pathology. CT colonography is a recent arrival to CAD, but could represent one of its most fruitful applications in the future. In contrast to other organs, where a variety of different pathologies are equally represented, significant colorectal pathologies other than polyps and cancer are relatively uncommon. As we shall see, this simplifies the diagnostic task for artificial intelligence developers and also for radiologists who, ultimately, must make the final decision. This review aims to present the current state-of-the-art for CAD applied to CT colonography. A brief overview of the technical essentials and of the diagnostic performance of CAD in isolation, is followed by an explanation of how CAD is used in day-to-day practice. The last section will deal with the most controversial issues affecting CAD performance in clinical practice, with a focus on the interaction between human and artificial intelligence.

CAD: How it works, how to use it, performance

REGGE, Daniele;
2013-01-01

Abstract

Computer-aided diagnosis (CAD) systems are software algorithms designed to assist radiologists (or other practitioners) in solving a diagnostic problem by using a visual prompt (or "CAD mark") to direct the observer towards potential pathology. CT colonography is a recent arrival to CAD, but could represent one of its most fruitful applications in the future. In contrast to other organs, where a variety of different pathologies are equally represented, significant colorectal pathologies other than polyps and cancer are relatively uncommon. As we shall see, this simplifies the diagnostic task for artificial intelligence developers and also for radiologists who, ultimately, must make the final decision. This review aims to present the current state-of-the-art for CAD applied to CT colonography. A brief overview of the technical essentials and of the diagnostic performance of CAD in isolation, is followed by an explanation of how CAD is used in day-to-day practice. The last section will deal with the most controversial issues affecting CAD performance in clinical practice, with a focus on the interaction between human and artificial intelligence.
2013
82
8
1171
1176
https://www.sciencedirect.com/science/article/pii/S0720048X12001970?via=ihub
Colorectal cancer; Computer Aided Diagnosis (CAD); CT colonography (CTC); Colonography, Computed Tomographic; Colorectal Neoplasms; Humans; Pattern Recognition, Automated; Radiographic Image Enhancement; Radiographic Image Interpretation, Computer-Assisted; Reproducibility of Results; Sensitivity and Specificity; Algorithms; Artificial Intelligence; Radiology, Nuclear Medicine and Imaging; Medicine (all)
Regge, Daniele; Halligan, Steve
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1548800
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