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Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

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A Data-Centric Augmentation Approach for Disturbed Sensor Image Segmentation.

Andreas Roth¹, Konstantin Wüstefeld¹, Frank Weichert¹

¹Department of Computer Science, TU Dortmund University, 44227 Dortmund, Germany.

Journal of Imaging

|October 22, 2021

Summary

This summary is machine-generated.

This study introduces a novel data augmentation method using generative adversarial networks to create synthetic image artifacts. This approach enhances deep learning models for sensor data analysis, improving artifact compensation and detection accuracy without requiring extra labeling.

Failed At:

2026-06-19T13:39:12.381547+00:00

Keywords:

data augmentation deep learning generative adversarial network imaging artifacts sensor images

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