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High‐resolution depth measurements in digital microscopic surgery

Babilon, Sebastian ; Myland, Paul ; Schlestein, Lucas ; Klabes, Julian ; Khanh, Tran Quoc (2024)
High‐resolution depth measurements in digital microscopic surgery.
In: Engineering Reports, 2020, 3 (4)
doi: 10.26083/tuprints-00017446
Article, Secondary publication, Publisher's Version

Copyright Information: CC BY 4.0 International - Creative Commons, Attribution.

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Item Type: Article
Type of entry: Secondary publication
Title: High‐resolution depth measurements in digital microscopic surgery
Language: English
Date: 5 January 2024
Place of Publication: Darmstadt
Year of primary publication: 2020
Place of primary publication: Hoboken
Publisher: John Wiley & Sons
Journal or Publication Title: Engineering Reports
Volume of the journal: 3
Issue Number: 4
Collation: 15 Seiten
DOI: 10.26083/tuprints-00017446
Corresponding Links:
Origin: Secondary publication DeepGreen

Fully digital microscopes are becoming more and more common in surgical applications. In addition to high‐resolution stereoscopic images of the operating field, which can be transmitted over long distances or stored directly, these systems offer further potentials by supporting the surgical workflow based on their fully digital image processing chain. For example, the image display can be adapted to the respective surgical scenario by adaptive color reproduction optimization or image overlays with additional information, such as the tissue topology. Knowledge of this topology can be used for computer‐assisted or augmented‐reality‐guided microsurgical treatments and enables additional features such as spatially resolved spectral reconstruction of surface reflectance. In this work, a new method for high‐resolution depth measurements in digital microsurgical applications is proposed, which is based on the principle of laser triangulation. Part of this method is a sensor data fusion procedure to properly match the laser scanner and camera data. In this context, a strategy based on radial basis function interpolation techniques is presented to handle missing or corrupt data, which, due to the measuring principle, can occur on steep edges and through occlusion. The proposed method is used for the acquisition of high‐resolution depth profiles of various organic tissue samples, proving the feasibility of the proposed concept as a supporting technology in a digital microsurgical workflow.

Uncontrolled Keywords: AR‐guided microsurgical treatments, depth measurements, digital image processing, laser sensor, medical imaging, tissue topology
Identification Number: e12311
Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-174468
Classification DDC: 600 Technology, medicine, applied sciences > 621.3 Electrical engineering, electronics
Divisions: 18 Department of Electrical Engineering and Information Technology > Adaptive Lighting Systems and Visual Processing
Date Deposited: 05 Jan 2024 14:02
Last Modified: 10 Jan 2024 07:09
SWORD Depositor: Deep Green
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/17446
PPN: 514549963
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