ReFit: A Framework for Refinement of Weakly Supervised Semantic Segmentation using Object Border Fitting for Medical Images

• URL: http://arxiv.org/abs/2303.07853v4
• Date: Wed, 20 Sep 2023 11:06:23 GMT
• Title: ReFit: A Framework for Refinement of Weakly Supervised Semantic Segmentation using Object Border Fitting for Medical Images
• Authors: Bharath Srinivas Prabakaran and Erik Ostrowski and Muhammad Shafique
• Abstract summary: Weakly Supervised Semantic (WSSS) relying only on image-level supervision is a promising approach to deal with the need for networks. We propose our novel ReFit framework, which deploys state-of-the-art class activation maps combined with various post-processing techniques. By applying our method to WSSS predictions, we achieved up to 10% improvement over the current state-of-the-art WSSS methods for medical imaging.
• Score: 4.945138408504987
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Weakly Supervised Semantic Segmentation (WSSS) relying only on image-level supervision is a promising approach to deal with the need for Segmentation networks, especially for generating a large number of pixel-wise masks in a given dataset. However, most state-of-the-art image-level WSSS techniques lack an understanding of the geometric features embedded in the images since the network cannot derive any object boundary information from just image-level labels. We define a boundary here as the line separating an object and its background, or two different objects. To address this drawback, we are proposing our novel ReFit framework, which deploys state-of-the-art class activation maps combined with various post-processing techniques in order to achieve fine-grained higher-accuracy segmentation masks. To achieve this, we investigate a state-of-the-art unsupervised segmentation network that can be used to construct a boundary map, which enables ReFit to predict object locations with sharper boundaries. By applying our method to WSSS predictions, we achieved up to 10% improvement over the current state-of-the-art WSSS methods for medical imaging. The framework is open-source, to ensure that our results are reproducible, and accessible online at https://github.com/bharathprabakaran/ReFit.

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