Deep Learning in Spinal Endoscopy: U-Net Models for Neural Tissue Detection

Biportal endoscopic spine surgery (BESS) is minimally invasive and therefore benefits both surgeons and patients. However, concerning complications include dural tears and neural tissue injuries. In this study, we aimed to develop a deep learning model for neural tissue segmentation to enhance the s...

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Veröffentlicht in:	Bioengineering (Basel) Jg. 11; H. 11; S. 1082
Hauptverfasser:	Lee, Hyung Rae, Rhee, Wounsuk, Chang, Sam Yeol, Chang, Bong-Soon, Kim, Hyoungmin
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland MDPI AG 01.11.2024 MDPI
Schlagworte:	Back surgery Bone surgery computer vision Datasets Deep learning Effectiveness endoscopic spine surgery Endoscopy Equipment and supplies Frames (data processing) Frames per second Image enhancement Image processing Image segmentation Injuries Learning curves Medical imaging Neural networks neural tissue Patients Performance evaluation Recall Segmentation Spine Surgeons Surgery Training deep learning endoscopic spine surgery image segmentation computer vision neural tissue
ISSN:	2306-5354, 2306-5354
Online-Zugang:	Volltext
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