Classification of Breast Tumor from Ultrasound Images Using No-Reference Image Quality Assessment
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F23%3A50019298" target="_blank" >RIV/62690094:18450/23:50019298 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-981-19-0105-8_33" target="_blank" >https://link.springer.com/chapter/10.1007/978-981-19-0105-8_33</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-981-19-0105-8_33" target="_blank" >10.1007/978-981-19-0105-8_33</a>
Alternative languages
Result language
angličtina
Original language name
Classification of Breast Tumor from Ultrasound Images Using No-Reference Image Quality Assessment
Original language description
A computer-aided diagnosis (CAD) system can be helpful for the detection of malignant tumors in the breast. Ultrasound imaging is a type modality with low cost and lower health risk. In this paper, we have classified benign and malignant breast tumors from ultrasound images. We have used the image quality assessment approach for this purpose. No-reference image quality metrics have been used as features for the classification task. We have used a public database of ultrasound images of breast tumors containing 780 images. The classification of breast ultrasound images using image quality assessment is a very novel approach, producing significant results.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Lecture Notes in Networks and Systems
ISBN
978-981-19010-4-1
ISSN
2367-3370
e-ISSN
2367-3389
Number of pages
9
Pages from-to
341-349
Publisher name
Springer Science and Business Media Deutschland GmbH
Place of publication
Singapore
Event location
Shillong
Event date
Sep 30, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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