Clinical Artificial Intelligence Applications in Radiology : Chest and Abdomen - 22/10/21
Résumé |
Organ segmentation, chest radiograph classification, and lung and liver nodule detections are some of the popular artificial intelligence (AI) tasks in chest and abdominal radiology due to the wide availability of public datasets. AI algorithms have achieved performance comparable to humans in less time for several organ segmentation tasks, and some lesion detection and classification tasks. This article introduces the current published articles of AI applied to chest and abdominal radiology, including organ segmentation, lesion detection, classification, and predicting prognosis.
Le texte complet de cet article est disponible en PDF.Keywords : Deep learning, Artificial intelligence, Radiology, Chest, Thorax, Abdomen, Pelvic
Plan
| Funding: Not applicable. |
|
| Conflicts of interest: Author R.M. Summers receives royalties from iCAD, ScanMed, Philips, Translation Holdings, and Ping An. His laboratory received research support from Ping An and NVIDIA. |
Vol 59 - N° 6
P. 987-1002 - novembre 2021 Retour au numéro
Article précédent
- Upstream Machine Learning in Radiology
- Christopher M. Sandino, Elizabeth K. Cole, Cagan Alkan, Akshay S. Chaudhari, Andreas M. Loening, Dongwoon Hyun, Jeremy Dahl, Abdullah-Al-Zubaer Imran, Adam S. Wang, Shreyas S. Vasanawala
- Clinical Artificial Intelligence Applications in Radiology : Neuro
- Felipe Campos Kitamura, Ian Pan, Suely Fazio Ferraciolli, Kristen W. Yeom, Nitamar Abdala
Bienvenue sur EM-consulte, la référence des professionnels de santé.
L’accès au texte intégral de cet article nécessite un abonnement.
Déjà abonné à cette revue ?