Accelerating 3D Medical Image Segmentation by Adaptive Small-Scale Target Localization

Accelerating 3D Medical Image Segmentation by Adaptive Small-Scale Target Localization

The prevailing approach for three-dimensional (3D) medical image segmentation is to use convolutional networks. Recently, deep learning methods have achieved human-level performance in several important applied problems, such as volumetry for lung-cancer diagnosis or delineation for radiation therap...

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Bibliographic Details
Main Authors: Boris Shirokikh, Alexey Shevtsov, Alexandra Dalechina, Egor Krivov, Valery Kostjuchenko, Andrey Golanov, Victor Gombolevskiy, Sergey Morozov, Mikhail Belyaev
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Journal of Imaging
Subjects:
deep learning
medical image segmentation
computed tomography (CT)
magnetic resonance imaging (MRI)
Online Access:https://www.mdpi.com/2313-433X/7/2/35

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