scholarly journals Automatic detection and classification of dental fluorosis in vivo using white light and fluorescence imaging

2018 ◽  
Vol 74 ◽  
pp. S34-S41 ◽  
Author(s):  
Zhao Liu ◽  
Michaela Goodwin ◽  
Roger P. Ellwood ◽  
Iain A. Pretty ◽  
Michael McGrady
2020 ◽  
Vol 13 ◽  
pp. 175628482091065 ◽  
Author(s):  
Tsuyoshi Ozawa ◽  
Soichiro Ishihara ◽  
Mitsuhiro Fujishiro ◽  
Youichi Kumagai ◽  
Satoki Shichijo ◽  
...  

Background: Recently the American Society for Gastrointestinal Endoscopy addressed the ‘resect and discard’ strategy, determining that accurate in vivo differentiation of colorectal polyps (CP) is necessary. Previous studies have suggested a promising application of artificial intelligence (AI), using deep learning in object recognition. Therefore, we aimed to construct an AI system that can accurately detect and classify CP using stored still images during colonoscopy. Methods: We used a deep convolutional neural network (CNN) architecture called Single Shot MultiBox Detector. We trained the CNN using 16,418 images from 4752 CPs and 4013 images of normal colorectums, and subsequently validated the performance of the trained CNN in 7077 colonoscopy images, including 1172 CP images from 309 various types of CP. Diagnostic speed and yields for the detection and classification of CP were evaluated as a measure of performance of the trained CNN. Results: The processing time of the CNN was 20 ms per frame. The trained CNN detected 1246 CP with a sensitivity of 92% and a positive predictive value (PPV) of 86%. The sensitivity and PPV were 90% and 83%, respectively, for the white light images, and 97% and 98% for the narrow band images. Among the correctly detected polyps, 83% of the CP were accurately classified through images. Furthermore, 97% of adenomas were precisely identified under the white light imaging. Conclusions: Our CNN showed promise in being able to detect and classify CP through endoscopic images, highlighting its high potential for future application as an AI-based CP diagnosis support system for colonoscopy.


1996 ◽  
Vol 24 (3) ◽  
pp. 325-331
Author(s):  
Iain F. H. Purchase

The title of this paper is challenging, because the question of how in vitro methods and results contribute to human health risk assessment is rarely considered. The process of risk assessment usually begins with hazard assessment, which provides a description of the inherent toxicological properties of the chemical. The next step is to assess the relevance of this to humans, i.e. the human hazard assessment. Finally, information on exposure is examined, and risk can then be assessed. In vitro methods have a limited, but important, role to play in risk assessment. The results can be used for classification and labelling; these are methods of controlling exposure, analogous to risk assessment, but without considering exposure. The Ames Salmonella test is the only in vitro method which is incorporated into regulations and used widely. Data from this test can, at best, lead to classification of a chemical with regard to genotoxicity, but cannot be used for classification and labelling on their own. Several in vitro test systems which assess the topical irritancy and corrosivity of chemicals have been reasonably well validated, and the results from these tests can be used for classification. The future development of in vitro methods is likely to be slow, as it depends on the development of new concepts and ideas. The in vivo methods which currently have reasonably developed in vitro alternatives will be the easiest to replace. The remaining in vivo methods, which provide toxicological information from repeated chronic dosing, with varied endpoints and by mechanisms which are not understood, will be more difficult to replace.


Author(s):  
Pengrui Zhuang ◽  
Ke Xiang ◽  
Xiangxi Meng ◽  
Guohe Wang ◽  
Ziyuan Li ◽  
...  

A facile and green method was developed to fabricate Nd-DTPA on a large scale without byproducts for CT/spectral CT and NIR II fluorescence imaging of the gastrointestinal tract in vivo.


2021 ◽  
Author(s):  
Bo Sun ◽  
Xu Zhen ◽  
Xiqun Jiang

This review mainly introduced the MSNs-based nanoprobes for in vivo bioimaging applications including fluorescence imaging and photoacoustic imaging.


Cancers ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 428
Author(s):  
Emma Renard ◽  
Estel Collado Camps ◽  
Coline Canovas ◽  
Annemarie Kip ◽  
Martin Gotthardt ◽  
...  

Variable domains of heavy chain only antibodies (VHHs) are valuable agents for application in tumor theranostics upon conjugation to both a diagnostic probe and a therapeutic compound. Here, we optimized site-specific conjugation of the chelator DTPA and the photosensitizer IRDye700DX to anti-epidermal growth factor receptor (EGFR) VHH 7D12, for applications in nuclear imaging and photodynamic therapy. 7D12 was site-specifically equipped with bimodal probe DTPA-tetrazine-IRDye700DX using the dichlorotetrazine conjugation platform. Binding, internalization and light-induced toxicity of DTPA-IRDye700DX-7D12 were determined using EGFR-overexpressing A431 cells. Finally, ex vivo biodistribution of DTPA-IRDye700DX-7D12 in A431 tumor-bearing mice was performed, and tumor homing was visualized with SPECT and fluorescence imaging. DTPA-IRDye700DX-7D12 was retrieved with a protein recovery of 43%, and a degree of labeling of 0.56. Spectral properties of the IRDye700DX were retained upon conjugation. 111In-labeled DTPA-IRDye700DX-7D12 bound specifically to A431 cells, and they were effectively killed upon illumination. DTPA-IRDye700DX-7D12 homed to A431 xenografts in vivo, and this could be visualized with both SPECT and fluorescence imaging. In conclusion, the dichlorotetrazine platform offers a feasible method for site-specific dual-labeling of VHH 7D12, retaining binding affinity and therapeutic efficacy. The flexibility of the described approach makes it easy to vary the nature of the probes for other combinations of diagnostic and therapeutic compounds.


Immunobiology ◽  
2015 ◽  
Vol 220 (12) ◽  
pp. 1328-1336 ◽  
Author(s):  
Hua He ◽  
Xiaojie Tu ◽  
Juan Zhang ◽  
Desmond Omane Acheampong ◽  
Li Ding ◽  
...  

2008 ◽  
Vol 13 (1) ◽  
pp. 011006 ◽  
Author(s):  
Zhihong Zhang ◽  
Jie Yang ◽  
Jinling Lu ◽  
Juqiang Lin ◽  
Shaoqun Zeng ◽  
...  

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