Probe-based rapid hybrid hyperspectral and tissue surface imaging aided by fully convolutional networks
File(s)1606.04766v1.pdf (445.68 KB)
Accepted version
Author(s)
Type
Conference Paper
Abstract
Tissue surface shape and reflectance spectra provide rich intraoperative information useful in surgical guidance. We propose a hybrid system which displays an endoscopic image with a fast joint inspection of tissue surface shape using structured light (SL) and hyperspectral imaging (HSI). For SL a miniature fibre probe is used to project a coloured spot pattern onto the tissue surface. In HSI mode standard endoscopic illumination is used,with the fibre probe collecting reflected light and encoding the spatial information into a linear format that can be imaged onto the slit of a spectrograph. Correspondence between the arrangement of fibres at the distal and proximal ends of the bundle was found using spectral encoding. Then during pattern decoding,a fully convolutional network (FCN) was used for spot detection,followed by a matching propagation algorithm for spot identification. This method enabled fast reconstruction (12 frames per second) using a GPU. The hyperspectral image was combined with the white light image and the reconstructed surface,showing the spectral information of different areas. Validation of this system using phantom and ex vivo experiments has been demonstrated.
Date Issued
2016-10-02
Date Acceptance
2016-10-01
Citation
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2016, 9902 LNCS, pp.414-422
ISBN
9783319467252
ISSN
0302-9743
Publisher
Springer International Publishing AG
Start Page
414
End Page
422
Journal / Book Title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume
9902 LNCS
Copyright Statement
© 2016 Springer International Publishing AG. The final publication is available at Springer via https://dx.doi.org/10.1007/978-3-319-46726-9_48
Sponsor
Commission of the European Communities
Grant Number
242991
Source
Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2016
Subjects
cs.CV
08 Information And Computing Sciences
Artificial Intelligence & Image Processing
Publication Status
Published
Start Date
2016-10-17
Coverage Spatial
Athens, Greece
Date Publish Online
2016-10-02