基于深度学习方法的脑肿瘤分析研究

Sheetal Prusty, Rutuparna Panda, Lingraj Dora, S. Agrawal
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引用次数: 1

摘要

大脑组织不受控制的快速生长导致肿瘤。如果不及早处理,可能会导致死亡。尽管进行了大量的努力并取得了可喜的成果,但有效的分割和分类仍然是一个挑战。肿瘤的位置、形状和大小的差异给脑肿瘤的识别带来了很大的困难。本文的目的是对使用各种扫描技术识别脑肿瘤进行描述性文献综述,以协助科学家。本文涵盖了大脑及其解剖学,公开可用的数据集,模式和基于深度学习的技术。本文展示了使用各种类型的深度学习方法进行大脑分割和分类。此外,本调查还包括检测脑肿瘤的所有相关材料。此外,还讨论了它们的优点和局限性。最后,对研究的进展和未来趋势进行了展望,提出了研究方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Study on Brain Tumor Analysis Using Deep Learning Methods
The unregulated and rapid growth of tissues in the brain causes a tumor. It may lead to death if not addressed in the early stages. Despite numerous considerable efforts and promising results, effective segmentation and classification remain a challenge. The differences in tumor location, shape, and size present a significant difficulty for brain tumor identification. The goal of this paper is to give a descriptive literature review about the identification of brain tumors using various scanning techniques to assist the scientists. The brain and its anatomy, publicly available datasets, modalities, and deep learning-based techniques are covered in this paper. This paper shows the use of various types of deep learning methods for brain segmentation and classification. Additionally, this survey includes all relevant material on detecting brain tumors. Moreover, their benefits, as well as limitations, are discussed. Finally, advancements and future trends are considered in our study to provide a research direction.
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