Artificial intelligence: Advances and new frontiers in medical imaging

Table 1 Areas of radiology workflow with current artificial intelligence implementation

Workflow target	Application examples
Nonpixel-based
Triage	Risk stratification for aortic pathology and generation of ‘aortic calcification score’ to assess for disease severity[15,16]
PACS display	Automated hanging protocol and comparison image generation[11]
Order verification	Patient medical record mining with built-in appropriateness criteria guidelines to approve or flag study orders[17,18,19,20,21]
Reporting	Automated data insertion into templates for standardized reporting of chest radiograph findings[23,24]
Pixel-based
Segmentation	Segmentation of simple lung nodules on chest CT images[43]
Disease registration	PI-RADS lesion classification based on MRI image characteristics[25,26]
Screening	Algorithmic interpretation and classification of screening mammograms[27,28]

PACS: Picture Archiving and Communication Systems; CT: Computed tomography; MRI: magnetic resonance imaging.