A fully automatic target detection and quantification strategy based on object detection convolutional neural network YOLOv3 for one-step X-ray image grading
Nan Chen, Zhichao Feng, Fei Li, Haibo Wang, Ru‐Qin Yu, Jian‐Hui Jiang, Lijuan Tang, Pengfei Rong, Wei Wang
Abstract
score and diagnostic accuracy of knee OA as well. Because of the fully automatic target detection and quantification, the time of handling an image is merely 40 ms from inputting the image to getting its label, supporting quick clinic decisions. It, thus, affords convenient and efficient image analysis for daily clinical diagnosis.
Topics & Concepts
Convolutional neural networkArtificial intelligenceComputer scienceGrading (engineering)Computer visionObject detectionPattern recognition (psychology)EngineeringCivil engineeringInfrared Thermography in MedicineMedical Imaging and AnalysisRadiomics and Machine Learning in Medical Imaging