深度学习用于放射治疗治疗规划的自分化:最先进的技术和新的视角

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Updated: Jun 22, 2026

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

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Ayhan Can Erdur1,2, Daniel Rusche3, Daniel Scholz4,5

  • 1Institute for Artificial Intelligence and Informatics in Medicine, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str., 81675, Munich, Bavaria, Germany. can.erdur@tum.de.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
|August 6, 2024
PubMed
概括

人工智能 (AI) 通过自动化风险器官 (OAR) 和瘤体积细分来增强放射治疗计划. 这种人工智能驱动的方法提高了个性化癌症治疗的效率,一致性和精度.

关键词:
自动细分系统 自动细分系统深度学习是一种深度学习.辐射瘤学 辐射瘤学放射治疗规划 放射治疗规划

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