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ICIEA_3D_Bounding_Box_Review (1).pdf (1.54 MB)

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

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posted on 15.12.2020, 15:45 by Daria Kern, Andre Mastmeyer
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.

Funding

DFG MA 6791/1-1, EXPLOR-19AM

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Email Address of Submitting Author

amastmeyer@gmail.com

ORCID of Submitting Author

0000-0003-0561-8363

Submitting Author's Institution

Aalen University, Aalen

Submitting Author's Country

Germany

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