Portal de investigación
Performance and educational training of radiographers in lung nodule or mass detection Retrospective comparison with different deep learning algorithms
Fecha de publicación:
Autores de IIS La Fe
Participantes ajenos a IIS La Fe
- Teng, PH
- Liang, CH
- Lin, Y
- Li, PW
- Weng, YH
- Chen, YT
- Lin, CH
- Chou, KJ
- Chen, YS
- Wu, FZ
Grupos
Abstract
The aim of this investigation was to compare the diagnostic performance of radiographers and deep learning algorithms in pulmonary nodule/mass detection on chest radiograph. A test set of 100 chest radiographs containing 53 cases with no pathology (normal) and 47 abnormal cases (pulmonary nodules/masses) independently interpreted by 6 trained radiographers and deep learning algorithems in a random order. The diagnostic performances of both deep learning algorithms and trained radiographers for pulmonary nodules/masses detection were compared. QUIBIM Chest X-ray Classifier, a deep learning through mass algorithm that performs superiorly to practicing radiographers in the detection of pulmonary nodules/masses (AUC(Mass): 0.916 vs AUC(Trained radiographer:) 0.778, P < .001). In addition, heat-map algorithm could automatically detect and localize pulmonary nodules/masses in chest radiographs with high specificity. In conclusion, the deep-learning based computer-aided diagnosis system through 4 algorithms could potentially assist trained radiographers by increasing the confidence and access to chest radiograph interpretation in the age of digital age with the growing demand of medical imaging usage and radiologist burnout.
Datos de la publicación
- ISSN/ISSNe:
- 0025-7974, 1536-5964
- Tipo:
- Article
- Páginas:
- -
- PubMed:
- 34115023
- Factor de Impacto:
- 0,470 SCImago ℠
- Cuartil:
- Q3 SCImago ℠
MEDICINE LIPPINCOTT WILLIAMS & WILKINS
Citas Recibidas en Web of Science: 5
Documentos
- No hay documentos
Filiaciones
Keywords
- chest radiograph; deep-learning diagnosis; diagnostic performance; radiographers
Campos de Estudio
Cita
Teng PH,Liang CH,Lin Y,ALBERICH A,GONZALEZ RL,Li PW,Weng YH,Chen YT,Lin CH,Chou KJ,Chen YS,Wu FZ. Performance and educational training of radiographers in lung nodule or mass detection Retrospective comparison with different deep learning algorithms. Medicine (Baltimore). 2021. 100. (23):e26270. IF:1,817. (3).