Taking measurement in every direction: Implicit scene representation for accurately estimating target dimensions under monocular endoscope.

Autor: Zhou Y; The College of Artificial Intelligence, Nankai University, Tianjin 300350, China; The Institute of Robotics and Automatic Information System, Tianjin Key Laboratory of Intelligent Robotics, Tianjin 300350, China., Li R; The College of Artificial Intelligence, Nankai University, Tianjin 300350, China; The Institute of Robotics and Automatic Information System, Tianjin Key Laboratory of Intelligent Robotics, Tianjin 300350, China., Dai Y; The College of Artificial Intelligence, Nankai University, Tianjin 300350, China; The Institute of Robotics and Automatic Information System, Tianjin Key Laboratory of Intelligent Robotics, Tianjin 300350, China. Electronic address: daiyu@nankai.edu.cn., Chen G; The College of Artificial Intelligence, Nankai University, Tianjin 300350, China; The Institute of Robotics and Automatic Information System, Tianjin Key Laboratory of Intelligent Robotics, Tianjin 300350, China., Zhang J; The College of Artificial Intelligence, Nankai University, Tianjin 300350, China; The Institute of Robotics and Automatic Information System, Tianjin Key Laboratory of Intelligent Robotics, Tianjin 300350, China., Cui L; Department of Urology, Civil Aviation General Hospital, Beijing 100123, China., Yin X; Department of Urology, Fourth Medical Center of Chinese, PLA General Hospital, Beijing 10048, China.
Jazyk: angličtina
Zdroj: Computer methods and programs in biomedicine [Comput Methods Programs Biomed] 2024 Nov; Vol. 256, pp. 108380. Date of Electronic Publication: 2024 Aug 19.
DOI: 10.1016/j.cmpb.2024.108380
Abstrakt: Background and Objectives: In endoscopy, measurement of target size can assist medical diagnosis. However, limited operating space, low image quality, and irregular target shape pose great challenges to traditional vision-based measurement methods.
Methods: In this paper, we propose a novel approach to measure irregular target size under monocular endoscope using image rendering. Firstly synthesize virtual poses on the same main optical axis as known camera poses, and use implicit neural representation module that considers brightness and target boundaries to render images corresponding to virtual poses. Then, Swin-Unet and rotating calipers are utilized to obtain maximum pixel length of the target in image pairs with the same main optical axis. Finally, the similarity triangle relationship of the endoscopic imaging model is used to measure the size of the target.
Results: The evaluation is conducted using renal stone fragments of patients which are placed in the kidney model and the isolated porcine kidney. The mean error of measurement is 0.12 mm.
Conclusions: The approached method can automatically measure object size within narrow body cavities in any visible direction. It improves the effectiveness and accuracy of measurement in limited endoscopic space.
Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Yu Dai reports financial support was provided by National Key Research and Development Program of China. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024 Elsevier B.V. All rights reserved.)
Databáze: MEDLINE
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