Pseudocolor enhancement of mammogram texture abnormalities
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F19%3A00505448" target="_blank" >RIV/67985556:_____/19:00505448 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/article/10.1007%2Fs00138-019-01028-6" target="_blank" >https://link.springer.com/article/10.1007%2Fs00138-019-01028-6</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s00138-019-01028-6" target="_blank" >10.1007/s00138-019-01028-6</a>
Alternative languages
Result language
angličtina
Original language name
Pseudocolor enhancement of mammogram texture abnormalities
Original language description
We present a novel method for enhancing texture irregularities, both lesions and microcalcifications, in digital X-ray mammograms. It can be implemented in computer-aided diagnostic systems to help improve radiologists’ diagnosis precision. The method provides three different outputs aimed at enhancing three different sizes of mammogram abnormalities. Our approach uses a two-dimensional adaptive causal autoregressive texture model to represent local texture characteristics. Based on these, we enhance suspicious breast tissue abnormalities, such as microcalcifications and masses, to make signs of developing cancer better visually discernible. We extract over 200 local textural features from different frequency bands, which are then combined into a single multichannel image using the Karhunen–Loeve transform. We propose an extension to existing contrast measures for the evaluation of contrast around regions of interest. Our method was extensively tested on the INbreast database and compared both visually and numerically with three state-of-the-art enhancement methods, with favorable results.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20205 - Automation and control systems
Result continuities
Project
<a href="/en/project/GA19-12340S" target="_blank" >GA19-12340S: Surface material recognition under variable optical observation conditions</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Machine Vision and Applications
ISSN
0932-8092
e-ISSN
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Volume of the periodical
30
Issue of the periodical within the volume
4
Country of publishing house
DE - GERMANY
Number of pages
10
Pages from-to
785-794
UT code for WoS article
000469483000017
EID of the result in the Scopus database
2-s2.0-85064633416