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Software . 2021
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jlubbersgeo/ctpy: CTPy initial release

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 15 Feb 2021Publisher:Zenodo
Authors: Lubbers, Jordan;
Code repository: https://github.com/jlubbersgeo/ctpy/tree/v1.0.0

doi: 10.5281/zenodo.4540942 , 10.5281/zenodo.4540941

jlubbersgeo/ctpy: CTPy initial release

Abstract

This is the initial release for CTPy: a module that was created for the filtering and segmentation of CT data in Python. This is built on top of scikit-image and utilizes their non-local means filter and watershed segmentation algorithms to de-noise CT data and segment it into a specific number of user defined regions.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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