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Analysis of Trabecular Bone Microstructure Using Contour Tree Connectivity




TekijätAydogan DB, Moritz N, Aro HT, Hyttinen J

ToimittajaMori K., Sakuma I., Sato Y., Barillot C., Navab N.

Konferenssin vakiintunut nimiInternational Conference on Medical Image Computing and Computer-Assisted Intervention

KustantajaSPRINGER-VERLAG BERLIN

KustannuspaikkaNagoya, Japan

Julkaisuvuosi2013

JournalLecture Notes in Computer Science

Kokoomateoksen nimiMedical Image Computing and Computer-Assisted Intervention – MICCAI 2013

Sarjan nimiLecture Notes in Computer Science

Vuosikerta8150

Aloitussivu428

Lopetussivu435

ISBN978-3-642-40762-8

eISBN978-3-642-40763-5

ISSN0302-9743

DOIhttps://doi.org/10.1007/978-3-642-40763-5_53


Tiivistelmä
Millions of people worldwide suffer from fragility fractures, which cause significant morbidity, financial costs and even mortality. The gold standard to quantify structural properties of trabecular bone is based on the morphometric parameters obtained from mu CT images of clinical bone biopsy specimens. The currently used image processing approaches are not able to fully explain the variation in bone strength. In this study, we introduce the contour tree connectivity (CTC) as a novel morphometric parameter to study trabecular bone quality. With CTC, we calculate a new connectivity measure for trabecular bone by using contour tree representation of binary images and algebraic graph theory. To test our approach, we use trabecular bone biopsies obtained from 55 female patients. We study the correlation of CTC with biomechanical test results as well as other morphometric parameters obtained from mu CT. The results based on our dataset show that CTC is the 3rd best predictive feature of ultimate bone strength after bone volume fraction and degree of anisotropy.



Last updated on 2024-26-11 at 14:24