Automatic segmentation of human knee anatomy by a convolutional neural network applying a 3D MRI protocol

Automatic segmentation of human knee anatomy by a convolutional neural network applying a 3D MRI protocol

Abstract Background To study deep learning segmentation of knee anatomy with 13 anatomical classes by using a magnetic resonance (MR) protocol of four three-dimensional (3D) pulse sequences, and evaluate possible clinical usefulness. Methods The sample selection involved 40 healthy right knee volume...

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Bibliographic Details
Main Authors: Carl Petter Skaar Kulseng, Varatharajan Nainamalai, Endre Grøvik, Jonn-Terje Geitung, Asbjørn Årøen, Kjell-Inge Gjesdal
Format: Article
Language:English
Published: BMC 2023-01-01
Series:BMC Musculoskeletal Disorders
Subjects:
Magnetic Resonance Imaging
Musculoskeletal
Deep learning
Knee images segmentation
Visualization
Online Access:https://doi.org/10.1186/s12891-023-06153-y

Internet

https://doi.org/10.1186/s12891-023-06153-y

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