A revisit on correlation between Tabár and Birads based risk assessment schemes with full field digital mammography

Wenda He, Minnie Kibiro, Arne Juette, Erika R. E. Denton, Reyer Zwiggelaar

Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion CynhadleddTrafodion Cynhadledd (Nid-Cyfnodolyn fathau)

2 Dyfyniadau (Scopus)

Crynodeb

Mammographic risk assessment is used to determine the probability of a woman developing breast cancer and it plays an important role in the early detection and disease prevention within screening mammography. Tabár and Birads are two fundamentally different risk schemes, one is assessed based on mixtures of breast parenchyma and the other one is assessed based on the percentage of dense breast tissue. This paper presents findings on the correlation between these two mammographic risk assessment schemes; aspects with respect to reader experience and related inter reader variability were also investigated. As a follow up (revisit) investigation to a previously published paper, the new results have shown a strong correlation between Tabár and Birads with the highest Spearman’s correlation coefficient > 0.92 and κ = 0.86% (almost perfect agreement). The statistical results vary with readers’ mammographic reading experience, which also indicated subtle information such as that some mixture of breast parenchma (Tabár specific mammographic building blocks) may be more likely to cause inter reader variability.

Iaith wreiddiolSaesneg
TeitlBreast Imaging - 12th International Workshop, IWDM 2014, Proceedings
Is-deitl12th International Workshop, IWDM 2014, Gifu City, Japan, June 29 - July 2, 2014, Proceedings
GolygyddionHiroshi Fujita, Takeshi Hara, Chisako Muramatsu
CyhoeddwrSpringer Nature
Tudalennau327-333
Nifer y tudalennau7
ISBN (Electronig)978-3-319-07887-8
ISBN (Argraffiad)978-3-319-07886-1
Dynodwyr Gwrthrych Digidol (DOIs)
StatwsCyhoeddwyd - 06 Meh 2014

Cyfres gyhoeddiadau

EnwLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Cyfrol8539 LNCS
ISSN (Argraffiad)0302-9743
ISSN (Electronig)1611-3349

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