An Extra Set of Intelligent Eyes: Application of Artificial Intelligence in Imaging of Abdominopelvic Pathologies in Emergency Radiology
Imaging in the emergent setting carries high stakes. With increased demand for dedicated on-site service, emergency radiologists face increasingly large image volumes that require rapid turnaround times. However, novel artificial intelligence (AI) algorithms may assist trauma and emergency radiologi...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-05-01
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| Series: | Diagnostics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-4418/12/6/1351 |
| _version_ | 1797488326817611776 |
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| author | Jeffrey Liu Bino Varghese Farzaneh Taravat Liesl S. Eibschutz Ali Gholamrezanezhad |
| author_facet | Jeffrey Liu Bino Varghese Farzaneh Taravat Liesl S. Eibschutz Ali Gholamrezanezhad |
| author_sort | Jeffrey Liu |
| collection | DOAJ |
| description | Imaging in the emergent setting carries high stakes. With increased demand for dedicated on-site service, emergency radiologists face increasingly large image volumes that require rapid turnaround times. However, novel artificial intelligence (AI) algorithms may assist trauma and emergency radiologists with efficient and accurate medical image analysis, providing an opportunity to augment human decision making, including outcome prediction and treatment planning. While traditional radiology practice involves visual assessment of medical images for detection and characterization of pathologies, AI algorithms can automatically identify subtle disease states and provide quantitative characterization of disease severity based on morphologic image details, such as geometry and fluid flow. Taken together, the benefits provided by implementing AI in radiology have the potential to improve workflow efficiency, engender faster turnaround results for complex cases, and reduce heavy workloads. Although analysis of AI applications within abdominopelvic imaging has primarily focused on oncologic detection, localization, and treatment response, several promising algorithms have been developed for use in the emergency setting. This article aims to establish a general understanding of the AI algorithms used in emergent image-based tasks and to discuss the challenges associated with the implementation of AI into the clinical workflow. |
| first_indexed | 2024-03-10T00:01:29Z |
| format | Article |
| id | doaj.art-920ded8637024c3c8e7c38391a20d09a |
| institution | Directory Open Access Journal |
| issn | 2075-4418 |
| language | English |
| last_indexed | 2024-03-10T00:01:29Z |
| publishDate | 2022-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diagnostics |
| spelling | doaj.art-920ded8637024c3c8e7c38391a20d09a2023-11-23T16:16:43ZengMDPI AGDiagnostics2075-44182022-05-01126135110.3390/diagnostics12061351An Extra Set of Intelligent Eyes: Application of Artificial Intelligence in Imaging of Abdominopelvic Pathologies in Emergency RadiologyJeffrey Liu0Bino Varghese1Farzaneh Taravat2Liesl S. Eibschutz3Ali Gholamrezanezhad4Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USAKeck School of Medicine, University of Southern California, Los Angeles, CA 90033, USAKeck School of Medicine, University of Southern California, Los Angeles, CA 90033, USAKeck School of Medicine, University of Southern California, Los Angeles, CA 90033, USAKeck School of Medicine, University of Southern California, Los Angeles, CA 90033, USAImaging in the emergent setting carries high stakes. With increased demand for dedicated on-site service, emergency radiologists face increasingly large image volumes that require rapid turnaround times. However, novel artificial intelligence (AI) algorithms may assist trauma and emergency radiologists with efficient and accurate medical image analysis, providing an opportunity to augment human decision making, including outcome prediction and treatment planning. While traditional radiology practice involves visual assessment of medical images for detection and characterization of pathologies, AI algorithms can automatically identify subtle disease states and provide quantitative characterization of disease severity based on morphologic image details, such as geometry and fluid flow. Taken together, the benefits provided by implementing AI in radiology have the potential to improve workflow efficiency, engender faster turnaround results for complex cases, and reduce heavy workloads. Although analysis of AI applications within abdominopelvic imaging has primarily focused on oncologic detection, localization, and treatment response, several promising algorithms have been developed for use in the emergency setting. This article aims to establish a general understanding of the AI algorithms used in emergent image-based tasks and to discuss the challenges associated with the implementation of AI into the clinical workflow.https://www.mdpi.com/2075-4418/12/6/1351artificial intelligenceradiologyimagingcomputed tomographyabdominal painGI trauma |
| spellingShingle | Jeffrey Liu Bino Varghese Farzaneh Taravat Liesl S. Eibschutz Ali Gholamrezanezhad An Extra Set of Intelligent Eyes: Application of Artificial Intelligence in Imaging of Abdominopelvic Pathologies in Emergency Radiology Diagnostics artificial intelligence radiology imaging computed tomography abdominal pain GI trauma |
| title | An Extra Set of Intelligent Eyes: Application of Artificial Intelligence in Imaging of Abdominopelvic Pathologies in Emergency Radiology |
| title_full | An Extra Set of Intelligent Eyes: Application of Artificial Intelligence in Imaging of Abdominopelvic Pathologies in Emergency Radiology |
| title_fullStr | An Extra Set of Intelligent Eyes: Application of Artificial Intelligence in Imaging of Abdominopelvic Pathologies in Emergency Radiology |
| title_full_unstemmed | An Extra Set of Intelligent Eyes: Application of Artificial Intelligence in Imaging of Abdominopelvic Pathologies in Emergency Radiology |
| title_short | An Extra Set of Intelligent Eyes: Application of Artificial Intelligence in Imaging of Abdominopelvic Pathologies in Emergency Radiology |
| title_sort | extra set of intelligent eyes application of artificial intelligence in imaging of abdominopelvic pathologies in emergency radiology |
| topic | artificial intelligence radiology imaging computed tomography abdominal pain GI trauma |
| url | https://www.mdpi.com/2075-4418/12/6/1351 |
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