ISLES Challenge: U-Shaped Convolution Neural Network with Dilated Convolution for 3D Stroke Lesion Segmentation

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F19%3A63520856" target="_blank" >RIV/70883521:28140/19:63520856 - isvavai.cz</a>

Result on the web

<a href="https://link.springer.com/chapter/10.1007%2F978-3-030-11723-8_32" target="_blank" >https://link.springer.com/chapter/10.1007%2F978-3-030-11723-8_32</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-11723-8_32" target="_blank" >10.1007/978-3-030-11723-8_32</a>

Result language

angličtina

Original language name

ISLES Challenge: U-Shaped Convolution Neural Network with Dilated Convolution for 3D Stroke Lesion Segmentation

Original language description

In this paper, we propose the algorithm for stroke lesion segmentation based on a deep convolutional neural network (CNN). The model is based on U-shaped CNN, which has been applied successfully to other medical image segmentation tasks. The network architecture was derived from the model presented in Isensee et al. [1] and is capable of processing whole 3D images. The model incorporates the convolution layers through upsampled filters – also known as dilated convolution. This change enlarges filter’s field of the view and allows the net to integrate larger context into the computation. We add the dilated convolution into different parts of network architecture and study the impact on the overall model performance. The best model which uses the dilated convolution in the input of the net outperforms the original architecture in nearly all used evaluation metrics. The code and trained models can be found on the GitHub website: http://github.com/tureckova/ISLES2018/.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2019

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ISBN

978-3-030-11722-1

ISSN

0302-9743

e-ISSN

—

Number of pages

9

Pages from-to

319-327

Publisher name

Springer International Publishing AG

Place of publication

Basel

Event location

Granada

Event date

Sep 16, 2018

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

—