scholarly journals Coherent anti-Stokes Raman scattering rigid endoscope toward robot-assisted surgery

2018 ◽  
Vol 9 (2) ◽  
pp. 387 ◽  
Author(s):  
K. Hirose ◽  
T. Aoki ◽  
T. Furukawa ◽  
S. Fukushima ◽  
H. Niioka ◽  
...  
Keyword(s):  
Raman Scattering ◽  
Robot Assisted ◽  
Rigid Endoscope ◽  
Anti Stokes ◽  
Robot Assisted Surgery

scholarly journals Invited Article: Label-free nerve imaging with a coherent anti-Stokes Raman scattering rigid endoscope using two optical fibers for laser delivery

APL Photonics ◽  
2018 ◽  
Vol 3 (9) ◽  
pp. 092407 ◽  
Author(s):  
Keigo Hirose ◽  
Shuichiro Fukushima ◽  
Taichi Furukawa ◽  
Hirohiko Niioka ◽  
Mamoru Hashimoto
Keyword(s):  
Raman Scattering ◽  
Optical Fibers ◽  
Label Free ◽  
Rigid Endoscope ◽  
Nerve Imaging ◽  
Anti Stokes

scholarly journals Author Correction: Improvement of nerve imaging speed with coherent anti-Stokes Raman scattering rigid endoscope using deep-learning noise reduction

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Naoki Yamato ◽  
Hirohiko Niioka ◽  
Jun Miyake ◽  
Mamoru Hashimoto
Keyword(s):  
Deep Learning ◽  
Raman Scattering ◽  
Noise Reduction ◽  
Rigid Endoscope ◽  
Nerve Imaging ◽  
Anti Stokes ◽  
Imaging Speed

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

scholarly journals Improvement of nerve imaging speed with coherent anti-Stokes Raman scattering rigid endoscope using deep-learning noise reduction

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Naoki Yamato ◽  
Hirohiko Niioka ◽  
Jun Miyake ◽  
Mamoru Hashimoto
Keyword(s):  
Deep Learning ◽  
Raman Scattering ◽  
Noise Reduction ◽  
Fine Tuning ◽  
Nerve Sparing ◽  
Learning Models ◽  
Rigid Endoscope ◽  
Nerve Imaging ◽  
Anti Stokes ◽  
Imaging Speed

Abstract A coherent anti-Stokes Raman scattering (CARS) rigid endoscope was developed to visualize peripheral nerves without labeling for nerve-sparing endoscopic surgery. The developed CARS endoscope had a problem with low imaging speed, i.e. low imaging rate. In this study, we demonstrate that noise reduction with deep learning boosts the nerve imaging speed with CARS endoscopy. We employ fine-tuning and ensemble learning and compare deep learning models with three different architectures. In the fine-tuning strategy, deep learning models are pre-trained with CARS microscopy nerve images and retrained with CARS endoscopy nerve images to compensate for the small dataset of CARS endoscopy images. We propose using the equivalent imaging rate (EIR) as a new evaluation metric for quantitatively and directly assessing the imaging rate improvement by deep learning models. The highest EIR of the deep learning model was 7.0 images/min, which was 5 times higher than that of the raw endoscopic image of 1.4 images/min. We believe that the improvement of the nerve imaging speed will open up the possibility of reducing postoperative dysfunction by intraoperative nerve identification.

Do People Trust in Robot-Assisted Surgery? Evidence from Europe (Preprint)

2020 ◽  
Author(s):  
Joan Torrent-Sellens ◽  
Ana Jiménez-Zarco ◽  
Francesc Saigí-Rubió
Keyword(s):  
Technology Acceptance ◽  
Surgical Intervention ◽  
Negative Relationship ◽  
Predictor Variable ◽  
Major Change ◽  
Ease Of Use ◽  
The European Union ◽  
Robot Assisted ◽  
Surgical Interventions ◽  
Robot Assisted Surgery

BACKGROUND Increasingly intelligent and autonomous robots are destined to have a huge impact on our society. Their adoption, however, represents a major change to the healthcare sector’s traditional practices, which, in turn, poses certain challenges. To what extent is it possible to foresee a near-future scenario in which minor routine surgery is directed by robots? And what are the patients’ or general public’s perceptions of having surgical procedures performed on them by robots, be it totally or partially? A patient’s trust in robots and AI may facilitate the spread and use of such technologies. OBJECTIVE The goal of our study was to establish the factors that influence how people feel about having a medical operation performed on them by a robot. METHODS We used data from a 2017 Flash Eurobarometer (number 460) of European Commission with 27,901 citizens aged 15 years and over in the 28 countries of the European Union. The research designs and tests a technology acceptance model (TAM). Logistic regression (odds ratios, OR) to model the predictors of trust in robot-assisted surgery was calculated through motivational factors, robots using experience and sociodemographic independent variables. RESULTS The negative relationship between most of the predictors of ease of use, expected benefits and attitude towards robots, and confidence in robot-assisted surgery was contrasted. The only non-sociodemographic predictor variable that has a positive relationship with trust in robots participating in a surgical intervention is previous experience in the use of robots. In this context, we analyze the confidence predictors for three different levels of robot use experience (zero use, average use, and high use). The results obtained indicate that, as the experience of using robots increases, the predictive coefficients related to information, attitude and perception of robots become more negative. Research results also determined that variables of a sociodemographic nature played an important predictive role. It was confirmed that the effect of experience on trust in robots for surgical interventions was greater among men, people between 40 and 54 years old, and those with higher educational levels. CONCLUSIONS Despite the considerable benefits for the patient that the use of robots can bring in a surgical intervention, the results obtained show that trust in robots goes beyond rational decision-making. By contrasting the reasons that generate trust and mistrust in robots, especially by highlighting the experience of use as a key element, the research makes a new contribution to the state of the art and draws practical implications of the use of robots for health policy and practice.

scholarly journals Telemanipulation of an Articulated Robotic Arm using a Commercial Virtual Reality Controller

2020 ◽  
Vol 6 (3) ◽  
pp. 127-130
Author(s):  
Max B. Schäfer ◽  
Kent W. Stewart ◽  
Nico Lösch ◽  
Peter P. Pott
Keyword(s):  
Virtual Reality ◽  
Real Time ◽  
Robotic Arm ◽  
Input Device ◽  
Robot Assisted ◽  
Promising Alternative ◽  
Input Devices ◽  
Current Input ◽  
Current Systems ◽  
Robot Assisted Surgery

AbstractAccess to systems for robot-assisted surgery is limited due to high costs. To enable widespread use, numerous issues have to be addressed to improve and/or simplify their components. Current systems commonly use universal linkage-based input devices, and only a few applicationoriented and specialized designs are used. A versatile virtual reality controller is proposed as an alternative input device for the control of a seven degree of freedom articulated robotic arm. The real-time capabilities of the setup, replicating a system for robot-assisted teleoperated surgery, are investigated to assess suitability. Image-based assessment showed a considerable system latency of 81.7 ± 27.7 ms. However, due to its versatility, the virtual reality controller is a promising alternative to current input devices for research around medical telemanipulation systems.

scholarly journals Selective Imaging of Microplastic and Organic Particles in Flow by Multimodal Coherent Anti-Stokes Raman Scattering and Two-Photon Excited Autofluorescence Analysis

2021 ◽  
Vol 93 (12) ◽  
pp. 5234-5240
Author(s):  
Tomoko Takahashi ◽  
Krzysztof Pawel Herdzik ◽  
Konstantinos Nikolaos Bourdakos ◽  
James Arthur Read ◽  
Sumeet Mahajan
Keyword(s):  
Raman Scattering ◽  
Two Photon ◽  
Organic Particles ◽  
Anti Stokes
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