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Three-dimensional segmentation of computed tomography data using Drishti Paint : new tools and developments
Author(s) -
Yuzhi Hu,
Ajay Limaye,
Jing Lü
Publication year - 2020
Publication title -
royal society open science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.84
H-Index - 51
ISSN - 2054-5703
DOI - 10.1098/rsos.201033
Subject(s) - thresholding , segmentation , computer science , software , workflow , artificial intelligence , computer vision , volume rendering , computed tomography , rendering (computer graphics) , image segmentation , computer graphics (images) , image (mathematics) , radiology , medicine , database , programming language
Computed tomography (CT) has become very widely used in scientific and medical research and industry for its non-destructive and high-resolution means of detecting internal structure. Three-dimensional segmentation of computed tomography data sheds light on internal features of target objects. Three-dimensional segmentation of CT data is supported by various well-established software programs, but the powerful functionalities and capabilities of open-source software have not been fully revealed. Here, we present a new release of the open-source volume exploration, rendering and three-dimensional segmentation software, Drishti v. 2.7. We introduce a new tool for thresholding volume data (i.e. gradient thresholding) and a protocol for performing three-dimensional segmentation using the 3D Freeform Painter tool. These new tools and workflow enable more accurate and precise digital reconstruction, three-dimensional modelling and three-dimensional printing results. We use scan data of a fossil fish as a case study, but our procedure is widely applicable in biological, medical and industrial research.

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