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arXiv 2012.057452020-12-10eess.IVcs.CVcs.LG

3D Bounding Box Detection in Volumetric Medical Image Data: A Systematic Literature Review

Aalen University（阿伦大学）

Daria Kern, Andre Mastmeyer

备注：: 10 pages, 5 figures, 1 table
发表信息：: IEEE ICIEA / JOIG 2021

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英文摘要：

This paper discusses current methods and trends for 3D bounding box detection in volumetric medical image data. For this purpose, an overview of relevant papers from recent years is given. 2D and 3D implementations are discussed and compared. Multiple identified approaches for localizing anatomical structures are presented. The results show that most research recently focuses on Deep Learning methods, such as Convolutional Neural Networks vs. methods with manual feature engineering, e.g. Random-Regression-Forests. An overview of bounding box detection options is presented and helps researchers to select the most promising approach for their target objects.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

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