computer-vision-1

Landmark-based segmentation

3260 papers • 126 benchmarks • 313 datasets

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Most implemented papers

Hybrid graph convolutional neural networks for landmark-based anatomical segmentation

Nicolás Gaggion, Lucas Mansilla, Diego H. Milone, Enzo Ferrante•Wed Jun 16 2021

The experimental results suggest that HybridGNet produces accurate and anatomically plausible landmark-based segmentations, by naturally incorporating shape constraints within the decoding process via spectral convolutions.

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Multi-Center Anatomical Segmentation with Heterogeneous Labels Via Landmark-Based Models

Maria Vakalopoulou, Nicolás Gaggion, Diego H. Milone, Enzo Ferrante•Sun Nov 13 2022

It is shown how state-of-the-art pixel-level segmentation models fail in naively learning this task, and proposed is HybridGNet, a landmark-based segmentation model which learns the available anatomical structures using graph-based representations.

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