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Updated: May 2, 2026

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
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多类脑瘤分级分类使用基于深度学习的多数投票算法及其使用可解释AI的验证

Gopal Singh Tandel1, Ashish Tiwari2, Omprakash G Kakde2

  • 1Department of Computer Science, Allahabad Degree College, University of Allahabad, Prayagraj, India. gtandel@gmail.com.

Journal of imaging informatics in medicine
|January 8, 2025
PubMed
概括

这项研究介绍了一种基于MRI的非侵入性工具,使用集体深度学习来准确分类脑瘤. 开发的系统显著优于传统方法,为瘤诊断提供了侵入性活检的可靠替代方案.

关键词:
大脑瘤是什么?分类 分类 分类 分类.深度学习是一种深度学习.合唱团组合在一起.可解释的人工智能磁共振成像技术 磁共振成像技术转移学习转移学习

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Aggregates Classification01:29

Aggregates Classification

Aggregate classification is generally based on its size, petrographic characteristics, weight, and source. Size classification ranges from coarse to fine aggregates, defined by the size of the particles. Coarse aggregates are particles that do not pass through ASTM sieve No. 4, and aggregates that pass through the sieve are fine aggregates.
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
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