Automated Bone Segmentation and Surface Evaluation of a Small Animal Model of Post-Traumatic Osteoarthritis.
Ann Biomed Eng
; 45(5): 1227-1235, 2017 05.
Article
en En
| MEDLINE
| ID: mdl-28097525
ABSTRACT
MicroCT imaging allows for noninvasive microstructural evaluation of mineralized bone tissue, and is essential in studies of small animal models of bone and joint diseases. Automatic segmentation and evaluation of articular surfaces is challenging. Here, we present a novel method to create knee joint surface models, for the evaluation of PTOA-related joint changes in the rat using an atlas-based diffeomorphic registration to automatically isolate bone from surrounding tissues. As validation, two independent raters manually segment datasets and the resulting segmentations were compared to our novel automatic segmentation process. Data were evaluated using label map volumes, overlap metrics, Euclidean distance mapping, and a time trial. Intraclass correlation coefficients were calculated to compare methods, and were greater than 0.90. Total overlap, union overlap, and mean overlap were calculated to compare the automatic and manual methods and ranged from 0.85 to 0.99. A Euclidean distance comparison was also performed and showed no measurable difference between manual and automatic segmentations. Furthermore, our new method was 18 times faster than manual segmentation. Overall, this study describes a reliable, accurate, and automatic segmentation method for mineralized knee structures from microCT images, and will allow for efficient assessment of bony changes in small animal models of PTOA.
Palabras clave
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Densidad Ósea
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Osteoartritis de la Rodilla
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Microtomografía por Rayos X
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Traumatismos de la Rodilla
Tipo de estudio:
Etiology_studies
Límite:
Animals
Idioma:
En
Año:
2017
Tipo del documento:
Article