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This benchmark study evaluates four commercial depth sensors—stereo, structured-light, and time-of-flight—against complex medical phantoms to determine their accuracy in surgical contexts. The findings highlight that while the Zivid 2M+ 60 excelled across all metrics, performance varied significantly depending on surface properties like subsurface scattering and specular reflection. For AI developers integrating vision systems into robotic surgery, this data is critical for selecting hardware capable of handling real-world tissue challenges rather than idealized lab conditions.
Surse care acoperăarXiv, LessWrong, Quantum Computing Report, SiliconANGLE
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Comparing Commercial Depth Sensor Accuracy for Medical Applications

arXiv2 min de cititArticolul și perspectiva sunt în engleză.

arXiv:2606.13028v2 Announce Type: replace Abstract: Depth estimation has numerous medical and surgical applications. We benchmark four depth sensors on a porcine bone specimen, a porcine belly specimen, and a silicone kidney phantom using stylus-sampled references. These objects contain several real-world challenges, including homogeneous surfaces, specular surfaces, and subsurface scattering. The comparison includes stereo, structured-light, and time-of-flight sensors at a distance of approximately 50 cm. Specifically, the Intel RealSense D405 (Intel RealSense, United States), PMD Flexx2 (pmdtechnologies, Germany), Stereolabs ZED 2i (Stereolabs, France), and Zivid 2M+ 60 (Zivid, Norway) are compared. The Zivid 2M+ 60 performed best across all objects and metrics considered in this work. The ZED ranked second for real tissue, but last on the phantom.

Abstract:Depth estimation has numerous medical and surgical applications. We benchmark four depth sensors on a porcine bone specimen, a porcine belly specimen, and a silicone kidney phantom using stylus-sampled references. These objects contain several real-world challenges, including homogeneous surfaces, specular surfaces, and subsurface scattering. The comparison includes stereo, structured-light, and time-of-flight sensors at a distance of approximately 50 cm. Specifically, the Intel RealSense D405 (Intel RealSense, United States), PMD Flexx2 (pmdtechnologies, Germany), Stereolabs ZED 2i (Stereolabs, France), and Zivid 2M+ 60 (Zivid, Norway) are compared. The Zivid 2M+ 60 performed best across all objects and metrics considered in this work. The ZED ranked second for real tissue, but last on the phantom.

Robotics (cs.RO); Computer Vision and Pattern Recognition (cs.CV)

arXiv:2606.13028 [cs.RO]

(or arXiv:2606.13028v2 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2606.13028 Focus to learn more arXiv-issued DOI via DataCite

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