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. 2026 Jan 9;5:1733003. doi: 10.3389/fradi.2025.1733003

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© 2026 Matsuzaka and Iyoda.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Flowchart of deep learning-based segmentation algorithms. It categorizes into three types: Semantic Segmentation, Instance Segmentation, and Panoptic Segmentation. Semantic Segmentation includes methods like CNN + CRF, FCN (VGG16), U-Net, and DeepLab V3. Instance Segmentation features DeepMask, Instance-Aware, Mask R-CNN, and CenterMask. Panoptic Segmentation involves Panoptic FPN, DetectoRS, UPS-Net, and Panoptic Deeplab. — Deep learning-based segmentation algorithm. Three algorithms of the segmentation, semantic instance, and panoptic are included.