3D imaging techniques for improved colonoscopy

Colonoscopy screening with a conventional 2D colonoscope is known to reduce mortality due to colorectal cancer by half. Unfortunately, the protective value of this procedure is limited by missed lesions. To improve the sensitivity of colonoscopy to precancerous lesions, 3D imaging techniques could be used to highlight their characteristic morphology. While 3D imaging has proved beneficial for laparoscopic procedures, more research is needed to assess how it will improve applications of flexible endoscopy. In this editorial, we discuss the possible uses of 3D technologies in colonoscopy and factors that have hindered the translation of 3D imaging to flexible endoscopy. Emerging 3D imaging technologies for flexible endoscopy have the potential to improve sensitivity, lesion resection, training and automated lesion detection. To maximize the likelihood of clinical adoption, these technologies should require minimal hardware modification while maintaining the robustness and quality of regular 2D imaging.

[1]  計測自動制御学会,et al.  MFI '96, 1996 IEEE/SICE/RSJ International Conference on Multisensor Fusion and Integration for Intelligent Systems, December 8-11, 1996, Washington, D.C., U.S.A , 1996 .

[2]  J. Johanson,et al.  Colonoscopic withdrawal times and adenoma detection during screening colonoscopy. , 2006, The New England journal of medicine.

[3]  Benjamin J Vakoc,et al.  Photometric stereo endoscopy , 2013, Journal of biomedical optics.

[4]  K. Deguchi.  Shape reconstruction from endoscope image by its shadings , 1996, 1996 IEEE/SICE/RSJ International Conference on Multisensor Fusion and Integration for Intelligent Systems (Cat. No.96TH8242).

[5]  Armin Schneider,et al.  Time-of-Flight 3-D Endoscopy , 2009, MICCAI.

[6]  Walter Park,et al.  Prevalence of nonpolypoid (flat and depressed) colorectal neoplasms in asymptomatic and symptomatic adults. , 2008, JAMA.

[7]  D. Heresbach,et al.  Miss rate for colorectal neoplastic polyps: a prospective multicenter study of back-to-back video colonoscopies , 2008, Endoscopy.

[8]  Jung-Hwan Oh,et al.  Colon fold contour estimation for 3D visualization of colon structure from 2D colonoscopy images , 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[9]  Yuan-Fang Wang,et al.  Toward automated model building from video in computer-assisted diagnoses in colonoscopy , 2007, SPIE Medical Imaging.

[10]  Christoph Schmalz,et al.  An endoscopic 3D scanner based on structured light , 2012, Medical Image Anal..

[11]  Geoffrey McLennan,et al.  3D pulmonary airway color image reconstruction via shape from shading and virtual bronchoscopy imaging techniques , 2005, SPIE Medical Imaging.

[12]  Guang-Zhong Yang,et al.  A stereoscopic fibroscope for camera motion and 3D depth recovery during Minimally Invasive Surgery , 2009, 2009 IEEE International Conference on Robotics and Automation.

[13]  Gerhard F. Buess,et al.  3D HD versus 2D HD: surgical task efficiency in standardised phantom tasks , 2012, Surgical Endoscopy.

[14]  Mingui Sun,et al.  3D Construction of Endoscopic Images Based on Computational Stereo , 2006, Proceedings of the IEEE 32nd Annual Northeast Bioengineering Conference.

[15]  Arie E. Kaufman,et al.  3D Surface Reconstruction from Endoscopic Videos , 2008, Visualization in Medicine and Life Sciences.

[16]  Adrien Bartoli,et al.  Shape-from-Polarization in laparoscopy , 2013, 2013 IEEE 10th International Symposium on Biomedical Imaging.