Toward a More Quantitative and Specific Representation of Normality
Author:
Affiliation:
1. From the Department of Medical Imaging, CISSS Lanaudière, affiliated with Laval University, 1000 Blvd St-Anne, Saint-Charles-Borromée, QC, Canada J6E 6J2.
Publisher
Radiological Society of North America (RSNA)
Subject
Artificial Intelligence,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology
Link
http://pubs.rsna.org/doi/pdf/10.1148/ryai.2021210005
Reference12 articles.
1. Defining Normality – Art or Science?
2. How to Create a Great Radiology Report
3. Bone age in the 21st century: is Greulich and Pyle’s atlas accurate for Israeli children?
4. Rethinking Greulich and Pyle: A Deep Learning Approach to Pediatric Bone Age Assessment Using Pediatric Trauma Hand Radiographs
5. Automated Segmentation of Abdominal Skeletal Muscle on Pediatric CT Scans Using Deep Learning
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