LIDACS: A Lightweight Domain Adaptive Cell Segmentation Framework
Article No.: 9, Pages 1 - 6
Abstract
This paper presents a LIghtweight Domain Adaptive Cell Segmentation (LIDACS) framework that achieves state-of-the-art results (0.9505 mIoU) in instance segmentation on the SegPC-21 challenge dataset featured in ISBI 2021, while being significantly parameter efficient than the existing methods. LIDACS is a hierarchical multi-stage approach that utilizes prior domain-specific information to perform statistical and empirical analysis. It also employs task-specific augmentations and improved transfer learning via shared representation to enable better data representation. LIDACS also applies a novel cell structure-based contrastive augmentation paired with cell cloning, increasing annotation density and promoting better stain color in-variance. Effectively, LIDACS is a lightweight architecture, efficient for practical deployment, that provides optimal generalization.
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Index Terms
- LIDACS: A Lightweight Domain Adaptive Cell Segmentation Framework
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Published In
September 2023
133 pages
ISBN:9798400708312
DOI:10.1145/3625343
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Association for Computing Machinery
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Published: 11 November 2023
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AIMLR 2023
AIMLR 2023: 2023 Asia Conference on Artificial Intelligence, Machine Learning and Robotics
September 15 - 17, 2023
Bangkok, Thailand
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