| 邓刊,梁栋,黄莉斐,肖焕辉,黄炳升,邱明,孟祥红,陈富勇.基于计算机的医学影像后处理技术定位癫痫致痫灶研究进展[J].中国介入影像与治疗学,2019,16(5):315-319 |
| 基于计算机的医学影像后处理技术定位癫痫致痫灶研究进展 |
| Research progress of medical image post-processing techniques based on computer in localization of epileptogenic zone in epilepsy patients |
| 投稿时间：2018-10-19 修订日期：2019-03-26 |
| DOI：10.13929/j.1672-8475.201810027 |
| 中文关键词: 癫痫 机器学习 定位 磁共振成像 |
| 英文关键词:epilepsy machine learning localization magnetic resonance imaging |
| 基金项目:深圳市科创委学科布局项目（JCYJ20160428164548896）、深圳市科技创新委员会高端人才科研启动费（000048）、深圳市基础研究项目（JCYJ20170303160116960）。 |
|
| 摘要点击次数: 1410 |
| 全文下载次数: 889 |
| 中文摘要: |
| 约30%~40%癫痫患者无法通过药物控制发作，需要手术治疗。癫痫外科术前评估的关键在于结合多模态信息的综合分析评估定位致痫灶，但目前多模态神经影像学综合分析主要依赖人工解读，主观性强，耗时费力。为提高对于常规影像学MRI阴性致痫灶定位的准确性，已有研究将医学影像后处理技术应用于分析癫痫影像，结果表明医学影像后处理技术具有能客观、精细分析大脑结构和功能异常等优点，从而有可能为致痫灶定位提供准确、有效的解决方案。本文就医学影像后处理技术在癫痫致痫灶定位中的应用进展予以综述。 |
| 英文摘要: |
| About 30%-40% of patients with epilepsy remain medically intractable and may be considered as candidates for surgical treatment. Precise localization of the epileptogenic zone (EZ) through comprehensive presurgical evaluations is crucial for achieving good outcome. However, currently the interpretation of neuroimaging relies immensely on clinicians' experience, which is subjective and time-consuming. In order to improve the accuracy of EZ localization, medical image post-processing techniques have been applied. The results indicated that post-processing techniques have the advantages of identifying subtle abnormalities in brain structure and function objectively and precisely, thus may provide an accurate and effective solution for EZ localization. The advancements of existing medical image post-processing methods used in EZ localization were reviewed in this article. |
| 查看全文 查看/发表评论 下载PDF阅读器 |
| 关闭 |
