Cargando…
Deep learning in CT colonography: differentiating premalignant from benign colorectal polyps
OBJECTIVES: To investigate the differentiation of premalignant from benign colorectal polyps detected by CT colonography using deep learning. METHODS: In this retrospective analysis of an average risk colorectal cancer screening sample, polyps of all size categories and morphologies were manually se...
Autores principales: | Wesp, Philipp, Grosu, Sergio, Graser, Anno, Maurus, Stefan, Schulz, Christian, Knösel, Thomas, Fabritius, Matthias P., Schachtner, Balthasar, Yeh, Benjamin M., Cyran, Clemens C., Ricke, Jens, Kazmierczak, Philipp M., Ingrisch, Michael |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9213389/ https://www.ncbi.nlm.nih.gov/pubmed/35083528 http://dx.doi.org/10.1007/s00330-021-08532-2 |
Ejemplares similares
-
Pneumothorax detection in chest radiographs: optimizing artificial intelligence system for accuracy and confounding bias reduction using in-image annotations in algorithm training
por: Rueckel, Johannes, et al.
Publicado: (2021) -
AI support for accurate and fast radiological diagnosis of COVID-19: an international multicenter, multivendor CT study
por: Meng, Fanyang, et al.
Publicado: (2022) -
End-to-End Deep Learning Approach for Perfusion Data: A Proof-of-Concept Study to Classify Core Volume in Stroke CT
por: Mittermeier, Andreas, et al.
Publicado: (2022) -
Application of a deep learning algorithm for detection and visualization of hip fractures on plain pelvic radiographs
por: Cheng, Chi-Tung, et al.
Publicado: (2019) -
Machine learning classifiers can predict Gleason pattern 4 prostate cancer with greater accuracy than experienced radiologists
por: Antonelli, Michela, et al.
Publicado: (2019)