Target-specified reference-based deep learning network for joint image deblurring and resolution enhancement in surgical zoom lens camera calibration

For the augmented reality of surgical navigation, which overlays a 3D model of the surgical target on an image, accurate camera calibration is imperative. However, when the checkerboard images for calibration are captured using a surgical microscope having high magnification, blur owing to the narro...

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Veröffentlicht in:	Computers in biology and medicine 2024-12, Vol.183, p.109309, Article 109309
Hauptverfasser:	Ha, Ho-Gun, Jeung, Deokgi, Ullah, Ihsan, Tokuda, Junichi, Hong, Jaesung, Lee, Hyunki
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Artificial neural networks Augmented reality Blurring Calibration Cameras Coding Deep Learning Deep learning network Depth of field Edge joints Efficiency Humans Image enhancement Image Processing, Computer-Assisted - methods Image resolution Imaging, Three-Dimensional - methods Localization Machine learning Motion simulation Navigation Neural networks Neural Networks, Computer Spatial discrimination learning Spatial resolution Surgeons Surgery, Computer-Assisted - methods Surgical microscopic image Surgical navigation Three dimensional models Zoom lens camera calibration Zoom lenses
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