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European Conference on Computer Vision

ECCV 2020: Computer Vision – ECCV 2020 Workshops pp 251–266Cite as

Attention Deeplabv3+: Multi-level Context Attention Mechanism for Skin Lesion Segmentation

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12535))

Abstract

Skin lesion segmentation is a challenging task due to the large variation of anatomy across different cases. In the last few years, deep learning frameworks have shown high performance in image segmentation. In this paper, we propose Attention Deeplabv3+, an extended version of Deeplabv3+ for skin lesion segmentation by employing the idea of attention mechanism in two stages. We first capture the relationship between the channels of a set of feature maps by assigning a weight for each channel (i.e., channels attention). Channel attention allows the network to emphasize more on the informative and meaningful channels by a context gating mechanism. We also exploit the second level attention strategy to integrate different layers of the atrous convolution. It helps the network to focus on the more relevant field of view to the target. The proposed model is evaluated on three datasets ISIC 2017, ISIC 2018, and \(PH^2\), achieving state-of-the-art performance.

R. Azad and M. Asadi-Aghbolaghi—Contributed equally to this work.

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Notes

  1. 1.

    Source code is available on https://github.com/rezazad68/AttentionDeeplabv3p.

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Acknowledgment

This work has been partially supported by the Spanish project PID2019-105093GB-I00 (MINECO/FEDER, UE) and CERCA Programme/Generalitat de Catalunya, and ICREA under the ICREA Academia programme. We gratefully acknowledge the support of NVIDIA Corporation with the donation of the GPU used for this research.

Author information

Authors and Affiliations

  1. Computer Engineering Department, Sharif University of Technology, Tehran, Iran

    Reza Azad

  2. Computer Science School, Institute for Research in Fundamental Science (IPM), Tehran, Iran

    Maryam Asadi-Aghbolaghi & Mahmood Fathy

  3. Universitat de Barcelona and Computer Vision Center, Barcelona, Spain

    Sergio Escalera

Authors
  1. Reza Azad
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  2. Maryam Asadi-Aghbolaghi
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  3. Mahmood Fathy
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  4. Sergio Escalera
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Corresponding author

Correspondence to Maryam Asadi-Aghbolaghi .

Editor information

Editors and Affiliations

  1. University of Clermont Auvergne, Clermont Ferrand, France

    Adrien Bartoli

  2. Università degli Studi di Udine, Udine, Italy

    Andrea Fusiello

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Azad, R., Asadi-Aghbolaghi, M., Fathy, M., Escalera, S. (2020). Attention Deeplabv3+: Multi-level Context Attention Mechanism for Skin Lesion Segmentation. In: Bartoli, A., Fusiello, A. (eds) Computer Vision – ECCV 2020 Workshops. ECCV 2020. Lecture Notes in Computer Science(), vol 12535. Springer, Cham. https://doi.org/10.1007/978-3-030-66415-2_16

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  • DOI: https://doi.org/10.1007/978-3-030-66415-2_16

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  • Online ISBN: 978-3-030-66415-2

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