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Updated: Aug 1, 2026

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

Published on: November 30, 2022

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通过预训练和自我监督的微调调节来适应低剂量CT的域名

Simiao Yuan1,2, Haipeng Lv3, Zhedian Zhou2

  • 1School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.

Journal of X-ray science and technology
|March 2, 2026
PubMed
概括

本研究引入了一种自我监督的方法,以改善不同数据集的低剂量CT (LDCT) 排斥. 该方法适应预训练模型而不需要新的标记数据,增强医疗成像的跨领域概括性.

关键词:
最少发达国家和地区.域名适应 域名适应图像去色化 图像去色化自主监督的微调.

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Computed Tomography01:10

Computed Tomography

Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...