Multi-dataset Training for Medical Image Segmentation as a Service

Javier Civit-Masot, Francisco Luna-Perejón, Lourdes Duran-Lopez, J. P. Domínguez-Morales, Saturnino Vicente-Díaz, Alejandro Linares-Barranco, Anton Civit

2019

Abstract

Deep Learning tools are widely used for medical image segmentation. The results produced by these techniques depend to a great extent on the data sets used to train the used network. Nowadays many cloud service providers offer the required resources to train networks and deploy deep learning networks. This makes the idea of segmentation as a cloud-based service attractive. In this paper we study the possibility of training, a generalized configurable, Keras U-Net to test the feasibility of training with images acquired, with specific instruments, to perform predictions on data from other instruments. We use, as our application example, the segmentation of Optic Disc and Cup which can be applied to glaucoma detection. We use two publicly available data sets (RIM-One V3 and DRISHTI) to train either independently or combining their data.

Paper Citation

in Harvard Style

Civit-Masot J., Luna-Perejón F., Duran-Lopez L., Domínguez-Morales J., Vicente-Díaz S., Linares-Barranco A. and Civit A. (2019). Multi-dataset Training for Medical Image Segmentation as a Service. In Proceedings of the 11th International Joint Conference on Computational Intelligence (IJCCI 2019) - Volume 1: NCTA; ISBN 978-989-758-384-1, SciTePress, pages 542-547. DOI: 10.5220/0008541905420547

in Bibtex Style

@conference{ncta19,
author={Javier Civit-Masot and Francisco Luna-Perejón and Lourdes Duran-Lopez and J. P. Domínguez-Morales and Saturnino Vicente-Díaz and Alejandro Linares-Barranco and Anton Civit},
title={Multi-dataset Training for Medical Image Segmentation as a Service},
booktitle={Proceedings of the 11th International Joint Conference on Computational Intelligence (IJCCI 2019) - Volume 1: NCTA},
year={2019},
pages={542-547},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008541905420547},
isbn={978-989-758-384-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Computational Intelligence (IJCCI 2019) - Volume 1: NCTA
TI - Multi-dataset Training for Medical Image Segmentation as a Service
SN - 978-989-758-384-1
AU - Civit-Masot J.
AU - Luna-Perejón F.
AU - Duran-Lopez L.
AU - Domínguez-Morales J.
AU - Vicente-Díaz S.
AU - Linares-Barranco A.
AU - Civit A.
PY - 2019
SP - 542
EP - 547
DO - 10.5220/0008541905420547
PB - SciTePress