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FuseNet: Self-Supervised Dual-Path Network for Medical Image Segmentation

arXiv (Cornell University)

Abstract

Semantic segmentation, a crucial task in computer vision, often relies on labor-intensive and costly annotated datasets for training. In response to this challenge, we introduce FuseNet, a dual-stream framework for self-supervised semantic segmentation that eliminates the need for manual annotation. FuseNet leverages the shared semantic dependencies between the original and augmented images to create a clustering space, effectively assigning pixels to semantically related clusters, and ultimately generating the segmentation map. Additionally, FuseNet incorporates a cross-modal fusion technique that extends the principles of CLIP by replacing textual data with augmented images. This approach enables the model to learn complex visual representations, enhancing robustness against variations similar to CLIP's text invariance. To further improve edge alignment and spatial consistency between neighboring pixels, we introduce an edge refinement loss. This loss function considers edge information to enhance spatial coherence, facilitating the grouping of nearby pixels with similar visual features. Extensive experiments on skin lesion and lung segmentation datasets demonstrate the effectiveness of our method. \href{https://github.com/xmindflow/FuseNet}{Codebase.}

Authors 6

  1. Iran University of Science and Technology

    Affiliation as printed

    School of Electrical Engineering , Iran University of Science and Technology , Iran

  2. University of Regensburg

    Affiliation as printed

    Faculty of Informatics and Data Science , University of Regensburg , Germany

  3. RWTH Aachen University

    Affiliation as printed

    Faculty of Electrical Engineering and Information Technology , RWTH Aachen University , Germany

  4. Northwestern University · Northwestern University · Northwestern Medicine

    Affiliation as printed

    Department of Radiology , Northwestern University , Chicago , IL , USA

  5. Northwestern University · Northwestern University · Northwestern Medicine

    Affiliation as printed

    Department of Radiology , Northwestern University , Chicago , IL , USA

  6. Fraunhofer Institute for Digital Medicine · University of Regensburg

    Affiliation as printed

    Faculty of Informatics and Data Science , University of Regensburg , Germany

    Fraunhofer Institute for Digital Medicine MEVIS , Germany

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