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CHAP: Perturbación adversarial jerárquica canala-espacial para segmentación médica semi-supervisada

Si-Ping Zhou1, Zhi-Fang Gong1, Kai-Ni Wang1

  • 1School of Biological Science and Medical Engineering, Southeast University, Nanjing, China.

Medical image analysis
|December 27, 2025
PubMed
Resumen

Este estudio presenta un nuevo método de perturbación adversarial canala-espacial para mejorar la segmentación médica semi-supervisada. Reduce el sesgo de confirmación y mejora la eficiencia del aprendizaje para una mayor precisión en la segmentación.

Palabras clave:
Aprendizaje adversarialRegularización de consistenciaGradienteSegmentación de imágenes médicasPerturbaciónAprendizaje semi-supervisado

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