scholarly journals Usefulness of Autofluorescence Video-Monitoring to Enhanced Localization of Parathyroid Glands

2020 ◽  
Vol 63 (12) ◽  
pp. 586-593
Author(s):  
Sung Won Kim ◽  
Yoon Soo Seo ◽  
Hyoung Shin Lee ◽  
Yikeun Kim ◽  
Yeh-Chan Ahn ◽  
...  
Keyword(s):  
Real Time ◽  
Parathyroid Gland ◽  
Parathyroid Glands ◽  
Video Monitoring ◽  
High Signal ◽  
Lateral Side ◽  
Fluorescence Signal ◽  
Video Monitor ◽  
Room Light ◽  
Monitoring Technique

Background and Objectives Near-infrared (NIR) fluorescence photo imaging provides real time parathyroid anatomy enhancement. Moreover, autofluorescence enables intraoperative virtual reality parathyroid exploration of the optical characteristics of the parathyroid gland. This study was performed to demonstrate the new technique of visualizing the parathyroid gland using video-guided autofluorescence during thyroid and parathyroid surgery and to evaluate the outcomes. This is the first study that introduces the video-monitoring technique for intraoperative parathyroid mapping.Subjects and Method A total of 26 patients underwent 18 total thyroidectomies and 8 hemithyroidectomies in 2016. Fifty-six parathyroid glands were enrolled in this study. Surgery was performed by NIR video-monitoring via thyroid lateral side dissection to find the parathyroid tissues and extract the thyroid glands. With the operation room light turned on, the parathyroid glands were identified by the video-guided autofluorescence detection technique carried out in 3 stages (P1, P2, and P3), which are imaging with surgeon’s eyes before parathyroids exposure (P1), after identification (P2), and in extracted specimen (P3).Results The parathryoid autofluorescence could be video-monitored in real time by our NIR camera system with the indoor room light turned on. Of the total 56 parathyroids, 52 were detected by fluorescence. Of these, the location of 43 glands were predicted by using the high signal in a before-exposure state and the glands were confirmed as containing parathyroid tissues [in P1, sensitivity=82.69%, positive predictive value (PPV)=100.00%]. Of the nine glands that did not show high signals in P1, seven glands visually showed fluorescence signals (in P1 and P2, sensitivity=96.15%, PPV=100.00%). One of the two glands that showed high signals in the extracted tissue was identified as parathyroid, but the other one was proved not by histologic examination by despite high intensity fluorescence signal (in P1-P3, sensitivity=100.00%, PPV=98.08%). The accuracy of video-guided parathyroid mapping in P1, P2, and P3 were 83.93%, 96.43%, and 96.43%, respectively.Conclusion This is the first study that demonstrates the parathyroid gland autofluorescence as a real-time video-monitoring technique and shows that it could be applied to real surgery. Although parathyroid autofluorescence is a phenomenon seen in the invisible wavelength, our data suggest that the operator can see the parathyroid fluorescent signal in real time on the video-monitor. This technique could help the operator to predict the gland location and preserve them safely.

scholarly journals Near-infrared auto-fluorescence spectroscopy combining with Fisher’s linear discriminant analysis improves intraoperative real-time identification of normal parathyroid in thyroidectomy

BMC Surgery ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Junsong Liu ◽  
Xiaoxia Wang ◽  
Rui Wang ◽  
Chongwen Xu ◽  
Ruimin Zhao ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
Fluorescence Spectroscopy ◽  
Linear Discriminant Analysis ◽  
Real Time ◽  
Parathyroid Gland ◽  
Near Infrared ◽  
Parathyroid Glands ◽  
Linear Discriminant ◽  
Auto Fluorescence ◽  
Fisher’S Linear Discriminant

Abstract Background To evaluate the efficacy of a sensitive, real-time tool for identification and protection for parathyroid glands during thyroidectomy. Methods Near-infrared (NIR) auto-fluorescence was measured intraoperatively from 20 patients undergoing thyroidectomy. Spectra were measured from suspicious parathyroid glands and surrounding neck tissues during the operation with a NIR fluorescence system. Fast frozen sections were performed on the suspicious parathyroid glands. Accuracy was evaluated by comparison with histology and NIR identification. Data were attracted for Fisher’s linear discriminant analysis. Results The auto-fluorescence intensity of parathyroid was significantly higher than that of thyroid, fat and lymph node. The peak intensity of auto-fluorescence from parathyroid was 5.55 times of that from thyroid at the corresponding wave number. Of the 20 patients, the parathyroid was accurately detected and identified in 19 patients by NIR system, compared with their histologic results. One suspicious parathyroid did not exhibit typical spectra, and was proved to be fat tissue by histology. The NIR auto-fluorescence method had a 100% sensitivity of parathyroid glands identification and a high accuracy of 95%. The positive predictive value was 95%. The parathyroid gland have specific auto-fluorescence spectrum and can be separated from the other three samples through the Fisher’s linear discriminant analysis. Conclusions NIR auto-fluorescence spectroscopy can accurately identify normal parathyroid gland during thyroidectomy. The Fisher’s linear discriminant analysis demonstrated the specificity of the NIR auto-fluorescence of parathyroid tissue and its efficacy in parathyroid discrimination.

scholarly journals Near-infrared auto-fluorescence spectroscopy combining with Fisher’s linear discriminant analysis improves intraoperative real-time identification of normal parathyroid in thyroidectomy

2019 ◽  
Author(s):  
Junsong Liu ◽  
Xiaoxia Wang ◽  
Rui Wang ◽  
Chongwen Xu ◽  
Ruimin Zhao ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
Fluorescence Spectroscopy ◽  
Linear Discriminant Analysis ◽  
Real Time ◽  
Parathyroid Gland ◽  
Parathyroid Glands ◽  
Linear Discriminant ◽  
Nir Fluorescence ◽  
Auto Fluorescence ◽  
Fisher’S Linear Discriminant

Abstract Background To evaluate the efficacy of a sensitive, real-time tool for identification and protection for parathyroid glands during thyroidectomy.Methods NIR fluorescence was measured intraoperatively from 20 patients undergoing thyroidectomy. Spectra were measured from suspicious parathyroid glands and surrounding neck tissues during the operation with a NIR fluorescence system. Fast frozen sections were performed on the suspicious parathyroid glands. Accuracy was evaluated by comparison with histology or NIR recognition. Data were attracted for Fisher’s linear discriminant analysis.Results The auto-fluorescence intensity of parathyroid was significantly higher than that of thyroid, fat and lymph node. The peak intensity of auto-fluorescence from parathyroid was 5.55 times of that from thyroid at the corresponding wave number. Of the 20 patients, the parathyroid was accurately detected and identified in 19 patients by NIR system, compared with their pathologic findings. One suspicious parathyroid did not exhibit typical spectra, and was proved to be fat tissue by pathology. The parathyroid gland have specific auto-fluorescence spectrum and can be separated from the other three samples through the Fisher’s linear discriminant analysis.Conclusions NIR auto-fluorescence spectroscopy can accurately identify normal parathyroid gland during thyroidectomy. The Fisher’s linear discriminant analysis demonstrated the specificity of the NIR auto-fluorescence of parathyroid tissue and its efficacy in parathyroid discrimination.

A NEW REAL-TIME MONITORING TECHNIQUE OF THE BIOCHEMICAL CONSTITUENTS OF THE ENVIRONMENT

2010 ◽  
Vol 9 (1) ◽  
pp. 133-140
Author(s):  
Petrisor Zamora Iordache ◽  
Nicoleta Petrea ◽  
Vasile Somoghi ◽  
Mihaela Muresan ◽  
Gabriel Epure ◽  
...  
Keyword(s):  
Real Time ◽  
Real Time Monitoring ◽  
Biochemical Constituents ◽  
Monitoring Technique

scholarly journals Development of Real-Time Time Gated Digital (TGD) OFDR Method and Its Performance Verification

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4865
Author(s):  
Kinzo Kishida ◽  
Artur Guzik ◽  
Ken’ichi Nishiguchi ◽  
Che-Hsien Li ◽  
Daiji Azuma ◽  
...  
Keyword(s):  
Real Time ◽  
Optical Fibers ◽  
High Speed ◽  
Oil And Gas ◽  
Scattered Light ◽  
Oil And Gas Industry ◽  
High Signal ◽  
Chirp Pulse ◽  
Sound Waves ◽  
Industry Applications

Distributed acoustic sensing (DAS) in optical fibers detect dynamic strains or sound waves by measuring the phase or amplitude changes of the scattered light. This contrasts with other distributed (and more conventional) methods, such as distributed temperature (DTS) or strain (DSS), which measure quasi-static physical quantities, such as intensity spectrum of the scattered light. DAS is attracting considerable attention as it complements the conventional distributed measurements. To implement DAS in commercial applications, it is necessary to ensure a sufficiently high signal-noise ratio (SNR) for scattered light detection, suppress its deterioration along the sensing fiber, achieve lower noise floor for weak signals and, moreover, perform high-speed processing within milliseconds (or sometimes even less). In this paper, we present a new, real-time DAS, realized by using the time gated digital-optical frequency domain reflectometry (TGD-OFDR) method, in which the chirp pulse is divided into overlapping bands and assembled after digital decoding. The developed prototype NBX-S4000 generates a chirp signal with a pulse duration of 2 μs and uses a frequency sweep of 100 MHz at a repeating frequency of up to 5 kHz. It allows one to detect sound waves at an 80 km fiber distance range with spatial resolution better than a theoretically calculated value of 2.8 m in real time. The developed prototype was tested in the field in various applications, from earthquake detection and submarine cable sensing to oil and gas industry applications. All obtained results confirmed effectiveness of the method and performance, surpassing, in conventional SM fiber, other commercially available interrogators.

Real-time tracking of lipid droplets interactions with other organelles by a high signal/noise probe

2021 ◽  
pp. 109366
Author(s):  
Wei Ren ◽  
Dong Wang ◽  
Wei Huang ◽  
Jiajia Li ◽  
Xiaohe Tian ◽  
...  
Keyword(s):  
Real Time ◽  
Lipid Droplets ◽  
High Signal ◽  
Signal Noise ◽  
Real Time Tracking

scholarly journals A Sensitive Potentiometric Sensor for Isothermal Amplification-Coupled Detection of Nucleic Acids

Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2277
Author(s):  
Kang-Ho Lee ◽  
Dongkyu Lee ◽  
Jongsu Yoon ◽  
Ohwon Kwon ◽  
Jaejong Lee
Keyword(s):  
Nucleic Acids ◽  
Real Time ◽  
Surface Potential ◽  
Pathogenic Bacteria ◽  
Field Effect Transistors ◽  
Potentiometric Sensor ◽  
Isothermal Amplification ◽  
Ring Oscillator ◽  
Oxide Semiconductor ◽  
High Signal

A disposable potentiometric sensor was newly developed for the amplification-coupled detection of nucleic acids. The hydrogen-ion is generally released during isothermal amplification of nucleic acids. The surface potential on the oxide-functionalized electrode of the extended gate was directly measured using full electrical circuits with the commercial metal-oxide semiconductor field-effect transistors (MOSFETs) and ring oscillator components, which resulted in cost-effective, portable and scalable real-time nucleic acid analysis. The current-starved ring oscillator changes surface potential to its frequency depending on the square of the variation in pH with a high signal-to-noise ratio during isothermal amplification. The device achieves a conversion rate of 20.5 kHz/mV and a detection resolution of 200 µV for the surface potential. It is demonstrated that the sensor successfully monitors in real-time isothermal amplification of the extracted nucleic acids from Salmonella pathogenic bacteria. The in situ variations in the frequency of the pH-sensitive sensor were compared with the results of both a conventional optical device and pH-meter during isothermal amplification.

Contrast Enhancement and Optimization for Image with Fog

2013 ◽  
Vol 380-384 ◽  
pp. 3778-3781
Author(s):  
Wei Na Huang ◽  
Zheng Xiang Xie
Keyword(s):  
Contrast Enhancement ◽  
Real Time ◽  
Visual Quality ◽  
Experimental Results ◽  
Video Monitoring ◽  
Adaptive Model ◽  
Absorption Effect ◽  
Atmospheric Visibility ◽  
Normal Work ◽  
Computing Speed

Aiming at the absorption effect of fog suspended in the atmosphere on light, the paper established the removing-fog compensation adaptive model which can improve the atmospheric visibility and restore the normal work of outdoor system. The experimental results show that the removing fog image processed by the method of removing-fog compensation optimization can accord with the requirement of human visual, and it can be used in real-time video monitoring as the fast computing speed. The method not only can be used in foggy video which the fog distributed uniformly, and can assess the visual quality for the images processed.

Research of Bus Video Monitoring System Based on WCDMA

2014 ◽  
Vol 543-547 ◽  
pp. 891-894
Author(s):  
Lian Jun Zhang ◽  
Shi Jie Liu
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Transmission System ◽  
Video Data ◽  
Video Monitoring ◽  
Video Server ◽  
Real Time Transmission ◽  
Monitoring Center ◽  
Server System ◽  
Transmission Ability

The bus video monitoring system is composed by WCDMA transmission system, video server system, system monitoring center and outreach system. By WCDMA wireless transmission module achieving real time video data return, while using VPDN network technology. Using of the DVS video server and by WCDMA transmission system, the monitoring videos information will be transmitted to the monitoring center rapidly and in real time. The monitoring center can remotely monitor, manage, and dispatch the bus. The results demonstrating this system has good real time transmission ability.

scholarly journals A Multiobjective Piglet Image Segmentation Method Based on an Improved Noninteractive GrabCut Algorithm

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Feilong Kang ◽  
Chunguang Wang ◽  
Jia Li ◽  
Zheying Zong
Keyword(s):  
Image Segmentation ◽  
Real Time ◽  
Monitoring System ◽  
Structural Similarity ◽  
Morphological Processing ◽  
Video Monitoring ◽  
Segmentation Method ◽  
Time Requirements ◽  
And Behavior ◽  
Grabcut Algorithm

In the video monitoring of piglets in pig farms, study of the precise segmentation of foreground objects is the work of advanced research on target tracking and behavior recognition. In view of the noninteractive and real-time requirements of such a video monitoring system, this paper proposes a method of image segmentation based on an improved noninteractive GrabCut algorithm. The functions of preserving edges and noise reduction are realized through bilateral filtering. An adaptive threshold segmentation method is used to calculate the local threshold and to complete the extraction of the foreground target. The image is simplified by morphological processing; the background interference pixels, such as details in the grille and wall, are filtered, and the foreground target marker matrix is established. The GrabCut algorithm is used to split the pixels of multiple foreground objects. By comparing the segmentation results of various algorithms, the results show that the segmentation algorithm proposed in this paper is efficient and accurate, and the mean range of structural similarity is [0.88, 1]. The average processing time is 1606 ms, and this method satisfies the real-time requirement of an agricultural video monitoring system. Feature vectors such as edges and central moments are calculated and the database is well established for feature extraction and behavior identification. This method provides reliable foreground segmentation data for the intelligent early warning of a video monitoring system.

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