Literature DB >> 26970592

Online tracking and retargeting with applications to optical biopsy in gastrointestinal endoscopic examinations.

Menglong Ye1, Stamatia Giannarou2, Alexander Meining3, Guang-Zhong Yang2.   

Abstract

With recent advances in biophotonics, techniques such as narrow band imaging, confocal laser endomicroscopy, fluorescence spectroscopy, and optical coherence tomography, can be combined with normal white-light endoscopes to provide in vivo microscopic tissue characterisation, potentially avoiding the need for offline histological analysis. Despite the advantages of these techniques to provide online optical biopsy in situ, it is challenging for gastroenterologists to retarget the optical biopsy sites during endoscopic examinations. This is because optical biopsy does not leave any mark on the tissue. Furthermore, typical endoscopic cameras only have a limited field-of-view and the biopsy sites often enter or exit the camera view as the endoscope moves. In this paper, a framework for online tracking and retargeting is proposed based on the concept of tracking-by-detection. An online detection cascade is proposed where a random binary descriptor using Haar-like features is included as a random forest classifier. For robust retargeting, we have also proposed a RANSAC-based location verification component that incorporates shape context. The proposed detection cascade can be readily integrated with other temporal trackers. Detailed performance evaluation on in vivo gastrointestinal video sequences demonstrates the performance advantage of the proposed method over the current state-of-the-art.
Copyright © 2015 Elsevier B.V. All rights reserved.

Keywords:  Gastrointestinal endoscopy; Optical biopsy retargeting; Random binary descriptor; Structured SVM; Tissue tracking

Mesh:

Year:  2015        PMID: 26970592     DOI: 10.1016/j.media.2015.10.003

Source DB:  PubMed          Journal:  Med Image Anal        ISSN: 1361-8415            Impact factor:   8.545


  5 in total

1.  Soft tissue motion tracking with application to tablet-based incision planning in laser surgery.

Authors:  Andreas Schoob; Max-Heinrich Laves; Lüder Alexander Kahrs; Tobias Ortmaier
Journal:  Int J Comput Assist Radiol Surg       Date:  2016-06-01       Impact factor: 2.924

Review 2.  Surgical data science - from concepts toward clinical translation.

Authors:  Lena Maier-Hein; Matthias Eisenmann; Duygu Sarikaya; Keno März; Toby Collins; Anand Malpani; Johannes Fallert; Hubertus Feussner; Stamatia Giannarou; Pietro Mascagni; Hirenkumar Nakawala; Adrian Park; Carla Pugh; Danail Stoyanov; Swaroop S Vedula; Kevin Cleary; Gabor Fichtinger; Germain Forestier; Bernard Gibaud; Teodor Grantcharov; Makoto Hashizume; Doreen Heckmann-Nötzel; Hannes G Kenngott; Ron Kikinis; Lars Mündermann; Nassir Navab; Sinan Onogur; Tobias Roß; Raphael Sznitman; Russell H Taylor; Minu D Tizabi; Martin Wagner; Gregory D Hager; Thomas Neumuth; Nicolas Padoy; Justin Collins; Ines Gockel; Jan Goedeke; Daniel A Hashimoto; Luc Joyeux; Kyle Lam; Daniel R Leff; Amin Madani; Hani J Marcus; Ozanan Meireles; Alexander Seitel; Dogu Teber; Frank Ückert; Beat P Müller-Stich; Pierre Jannin; Stefanie Speidel
Journal:  Med Image Anal       Date:  2021-11-18       Impact factor: 13.828

3.  Pose estimation of a markerless fiber bundle for endoscopic optical biopsy.

Authors:  Omar Zenteno; Sylvie Treuillet; Yves Lucas
Journal:  J Med Imaging (Bellingham)       Date:  2021-03-01

4.  An image retrieval framework for real-time endoscopic image retargeting.

Authors:  Menglong Ye; Edward Johns; Benjamin Walter; Alexander Meining; Guang-Zhong Yang
Journal:  Int J Comput Assist Radiol Surg       Date:  2017-06-02       Impact factor: 2.924

5.  Enhanced Image-Based Endoscopic Pathological Site Classification Using an Ensemble of Deep Learning Models.

Authors:  Dat Tien Nguyen; Min Beom Lee; Tuyen Danh Pham; Ganbayar Batchuluun; Muhammad Arsalan; Kang Ryoung Park
Journal:  Sensors (Basel)       Date:  2020-10-22       Impact factor: 3.576

  5 in total

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