Fusion of whole and part features for the classification of histopathological image of breast tissue

Sitaula, Chiranjibi and Aryal, Sunil 2020, Fusion of whole and part features for the classification of histopathological image of breast tissue, Health Information Science and Systems, vol. 8, pp. 1-12, doi: 10.1007/s13755-020-00131-7.

Attached Files
Name Description MIMEType Size Downloads

Title Fusion of whole and part features for the classification of histopathological image of breast tissue
Author(s) Sitaula, ChiranjibiORCID iD for Sitaula, Chiranjibi orcid.org/0000-0002-4564-2985
Aryal, SunilORCID iD for Aryal, Sunil orcid.org/0000-0002-6639-6824
Journal name Health Information Science and Systems
Volume number 8
Article ID 38
Start page 1
End page 12
Total pages 12
Publisher Springer Science and Business Media LLC
Place of publication New York, N.Y.
Publication date 2020
ISSN 2047-2501
Keyword(s) Histopathological images
Breast cancer
Histology
Image classifcation
Deep learning
Computer-aided diagnosis
Language eng
DOI 10.1007/s13755-020-00131-7
Indigenous content off
HERDC Research category C1 Refereed article in a scholarly journal
Persistent URL http://hdl.handle.net/10536/DRO/DU:30145232

Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in TR Web of Science
Scopus Citation Count Cited 0 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 42 Abstract Views, 0 File Downloads  -  Detailed Statistics
Created: Thu, 12 Nov 2020, 06:43:12 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.