Journal article icon

Journal article

Trainable segmentation for transmission electron microscope images of inorganic nanoparticles

Abstract:

We present a trainable segmentation method implemented within the python package ParticleSpy. The method takes user labelled pixels, which are used to train a classifier and segment images of inorganic nanoparticles from transmission electron microscope images. This implementation is based on the trainable Waikato Environment for Knowledge Analysis (WEKA) segmentation, but is written in python, allowing a large degree of flexibility and meaning it can be easily expanded using other python pac...

Expand abstract
Publication status:
Published
Peer review status:
Peer reviewed

Actions


Access Document


Files:
Publisher copy:
10.1111/jmi.13110

Authors


More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Materials
Role:
Author
ORCID:
0000-0003-1513-9964
Publisher:
Wiley
Journal:
Journal of Microscopy More from this journal
Volume:
288
Issue:
3
Pages:
169-184
Publication date:
2022-05-11
Acceptance date:
2022-04-26
DOI:
EISSN:
1365-2818
ISSN:
0022-2720
Pmid:
35502816
Language:
English
Keywords:
Pubs id:
1255422
Local pid:
pubs:1255422
Deposit date:
2022-05-13

Terms of use


Views and Downloads






If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP