Shape acquisition and registration for 3D endoscope based on grid pattern projection

Ryo Furukawa, Hiroki Morinaga, Yoji Sanomura, Shinji Tanaka, Shigeto Yoshida, Hiroshi Kawasaki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

23 Citations (Scopus)


For effective endoscopic diagnosis and treatment, size measurement and shape characterization of lesions, such as tumors, is important. For this purpose, 3D endoscopic systems based on active stereo to measure the shape and size of living tissue have recently been proposed. In those works, a large problem is the degree of reconstruction instability due to image blurring caused by the strong subsurface scattering common to internal tissue. To reduce this instability problem, using a coarse pattern for structured light is an option, however it reduces the resolution of the acquired shape information. In this paper, we tackle these shortcomings by developing a new micro pattern laser projector to be inserted in the scope tool channel. There are hardware and software contributions in the paper. First, the new projector uses a Diffractive Optical Element (DOE) instead of a single lens which we proposed to solve the off-focus blur. Second, we propose a new line-based grid pattern with gap coding to counter the subsurface scattering effect. The proposed pattern is a coarse grid pattern so that the grid features are not blurred out by the subsurface scattering. Third, to increase shape resolution of line-based grid pattern, we propose to use a multiple shape data registration technique for the grid-structured shapes, which are acquired sequentially by small motions, is proposed. Quantitative experiments are conducted to show the effectiveness of the method followed by a demonstration using real endoscopic system.

Original languageEnglish
Title of host publicationComputer Vision - 14th European Conference, ECCV 2016, Proceedings
EditorsBastian Leibe, Jiri Matas, Nicu Sebe, Max Welling
PublisherSpringer Verlag
Number of pages17
ISBN (Print)9783319464657
Publication statusPublished - 2016
Externally publishedYes
Event14th European Conference on Computer Vision, ECCV 2016 - Amsterdam, Netherlands
Duration: Oct 8 2016Oct 16 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9910 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference14th European Conference on Computer Vision, ECCV 2016

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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