Literature DB >> 29462601

Novel Developments in Endoscopic Mucosal Imaging.

Fons van der Sommen1, Wouter L Curvers2, Wouter B Nagengast3.   

Abstract

Endoscopic techniques such as high-definition and optical-chromoendoscopy have had enormous impact on endoscopy practice. Since these techniques allow assessment of most subtle morphological mucosal abnormalities, further improvements in endoscopic practice lay in increasing the detection efficacy of endoscopists. Several new developments could assist in this. First, web based training tools could improve the skills of the endoscopist for enhancing the detection and classification of lesions. Secondly, incorporation of computer aided detection will be the next step to raise endoscopic quality of the captured data. These systems will aid the endoscopist in interpreting the increasing amount of visual information in endoscopic images providing real-time objective second reading. In addition, developments in the field of molecular imaging open opportunities to add functional imaging data, visualizing biological parameters, of the gastrointestinal tract to white-light morphology imaging. For the successful implementation of abovementioned techniques, a true multi-disciplinary approach is of vital importance.
Copyright © 2018 AGA Institute. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Computer Aided Detection; Endoscopy; Molecular Imaging

Mesh:

Year:  2018        PMID: 29462601     DOI: 10.1053/j.gastro.2018.01.070

Source DB:  PubMed          Journal:  Gastroenterology        ISSN: 0016-5085            Impact factor:   22.682


  7 in total

Review 1.  Today's Mistakes and Tomorrow's Wisdom in Endoscopic Imaging of Barrett's Esophagus.

Authors:  Lisanne E van Heijst; Xiaojuan Zhao; Ruben Y Gabriëls; Wouter B Nagengast
Journal:  Visc Med       Date:  2022-03-30

Review 2.  Clinically Available Optical Imaging Technologies in Endoscopic Lesion Detection: Current Status and Future Perspective.

Authors:  Zhongyu He; Peng Wang; Yuelong Liang; Zuoming Fu; Xuesong Ye
Journal:  J Healthc Eng       Date:  2021-02-09       Impact factor: 2.682

3.  Molecular Imaging of Ulex Europaeus Agglutinin in Colorectal Cancer Using Confocal Laser Endomicroscopy (With Video).

Authors:  Weijun Wang; Shuxin Tian; Xin Jiang; Suya Pang; Huiying Shi; Mengke Fan; Zeyu Wang; Weiwei Jiang; Weiqian Hu; Xueyan Xiao; Rong Lin
Journal:  Front Oncol       Date:  2021-12-20       Impact factor: 6.244

4.  The use of deep learning on endoscopic images to assess the response of rectal cancer after chemoradiation.

Authors:  Hester E Haak; Xinpei Gao; Monique Maas; Selam Waktola; Sean Benson; Regina G H Beets-Tan; Geerard L Beets; Monique van Leerdam; Jarno Melenhorst
Journal:  Surg Endosc       Date:  2021-10-12       Impact factor: 4.584

5.  Real-time colorectal cancer diagnosis using PR-OCT with deep learning.

Authors:  Yifeng Zeng; Shiqi Xu; William C Chapman; Shuying Li; Zahra Alipour; Heba Abdelal; Deyali Chatterjee; Matthew Mutch; Quing Zhu
Journal:  Theranostics       Date:  2020-02-03       Impact factor: 11.556

6.  A Facile and Reproducible Synthesis of Near-Infrared Fluorescent Conjugates with Small Targeting Molecules for Microbial Infection Imaging.

Authors:  Friederike Reeßing; Mafalda Bispo; Marina López-Álvarez; Marleen van Oosten; Ben L Feringa; Jan Maarten van Dijl; Wiktor Szymański
Journal:  ACS Omega       Date:  2020-08-26

Review 7.  Machine learning in GI endoscopy: practical guidance in how to interpret a novel field.

Authors:  Fons van der Sommen; Jeroen de Groof; Maarten Struyvenberg; Joost van der Putten; Tim Boers; Kiki Fockens; Erik J Schoon; Wouter Curvers; Peter de With; Yuichi Mori; Michael Byrne; Jacques J G H M Bergman
Journal:  Gut       Date:  2020-05-11       Impact factor: 23.059

  7 in total

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