Sorry, you need to enable JavaScript to visit this website.

facebooktwittermailshare

PREDICTION OF MULTIPLE 3D TISSUE STRUCTURES BASED ON SINGLE-MARKER IMAGES USING CONVOLUTIONAL NEURAL NETWORKS

Abstract: 

A quantitative understanding of complex biological systems such as tissues requires reconstructing the structure of the different components of the system. Fluorescence microscopy provides the means to visualize simultaneously several tissue components. However, it can be time consuming and is limited by the number of fluorescent markers that can be used. In this study, we describe a toolbox of algorithms based on convolutional neural networks for the prediction of 3D tissue structures by learning features embedded within single-marker images. As proof of principle, we aimed to predict the network of bile canaliculi (BC) in liver tissue using images of the cortical actin mesh as input. The actin meshwork has a characteristic organization in specific cellular domains, such as BC. However, the use of manually selected features from images of actin is not sufficient to properly reconstruct BC structure. Our deep learning framework showed a remarkable accuracy for the prediction of BC network and was successfully adapted (i.e. transfer learning) to predict the sinusoidal network. This approach allows for a complete reconstruction of tissue microarchitecture using a single fluorescent marker.

up
0 users have voted:

Paper Details

Authors:
Hernan Morales-Navarrete, Fabian Segovia-Miranda, Marino Zerial and Yannis Kalaidzidis
Submitted On:
20 September 2019 - 7:25am
Short Link:
Type:
Poster
Event:
Presenter's Name:
Hernan Morales-Navarrete
Paper Code:
2314
Document Year:
2019
Cite

Document Files

PREDICTION OF MULTIPLE 3D TISSUE STRUCTURES BASED ON SINGLE-MARKER IMAGES USING CONVOLUTIONAL NEURAL NETWORKS

(12)

Subscribe

[1] Hernan Morales-Navarrete, Fabian Segovia-Miranda, Marino Zerial and Yannis Kalaidzidis, "PREDICTION OF MULTIPLE 3D TISSUE STRUCTURES BASED ON SINGLE-MARKER IMAGES USING CONVOLUTIONAL NEURAL NETWORKS", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4776. Accessed: Oct. 22, 2019.
@article{4776-19,
url = {http://sigport.org/4776},
author = {Hernan Morales-Navarrete; Fabian Segovia-Miranda; Marino Zerial and Yannis Kalaidzidis },
publisher = {IEEE SigPort},
title = {PREDICTION OF MULTIPLE 3D TISSUE STRUCTURES BASED ON SINGLE-MARKER IMAGES USING CONVOLUTIONAL NEURAL NETWORKS},
year = {2019} }
TY - EJOUR
T1 - PREDICTION OF MULTIPLE 3D TISSUE STRUCTURES BASED ON SINGLE-MARKER IMAGES USING CONVOLUTIONAL NEURAL NETWORKS
AU - Hernan Morales-Navarrete; Fabian Segovia-Miranda; Marino Zerial and Yannis Kalaidzidis
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4776
ER -
Hernan Morales-Navarrete, Fabian Segovia-Miranda, Marino Zerial and Yannis Kalaidzidis. (2019). PREDICTION OF MULTIPLE 3D TISSUE STRUCTURES BASED ON SINGLE-MARKER IMAGES USING CONVOLUTIONAL NEURAL NETWORKS. IEEE SigPort. http://sigport.org/4776
Hernan Morales-Navarrete, Fabian Segovia-Miranda, Marino Zerial and Yannis Kalaidzidis, 2019. PREDICTION OF MULTIPLE 3D TISSUE STRUCTURES BASED ON SINGLE-MARKER IMAGES USING CONVOLUTIONAL NEURAL NETWORKS. Available at: http://sigport.org/4776.
Hernan Morales-Navarrete, Fabian Segovia-Miranda, Marino Zerial and Yannis Kalaidzidis. (2019). "PREDICTION OF MULTIPLE 3D TISSUE STRUCTURES BASED ON SINGLE-MARKER IMAGES USING CONVOLUTIONAL NEURAL NETWORKS." Web.
1. Hernan Morales-Navarrete, Fabian Segovia-Miranda, Marino Zerial and Yannis Kalaidzidis. PREDICTION OF MULTIPLE 3D TISSUE STRUCTURES BASED ON SINGLE-MARKER IMAGES USING CONVOLUTIONAL NEURAL NETWORKS [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4776