Stacked sparse autoencoder networks and statistical shape models for automatic staging of distal femur trochlear dysplasia

Background The quantitative morphological analysis of the trochlear region in the distal femur and the precise staging of the potential dysplastic condition constitute a key point for the use of personalized treatment options for the patella‐femoral joint. In this paper, we integrated statistical sh...

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Vydané v:	The international journal of medical robotics + computer assisted surgery Ročník 14; číslo 6; s. e1947 - n/a
Hlavní autori:	Cerveri, Pietro, Belfatto, Antonella, Baroni, Guido, Manzotti, Alfonso
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	England Wiley Subscription Services, Inc 01.12.2018
Predmet:	Abnormalities Accuracy Aged Bone Diseases - diagnostic imaging Bone Diseases - surgery Cadaver Classification Computed tomography Databases, Factual Discriminant analysis Femur Femur - diagnostic imaging Femur - surgery Humans Image Processing, Computer-Assisted Imaging, Three-Dimensional Joint Instability Knee Knee Joint - diagnostic imaging Knee Joint - surgery Machine learning Mathematical models Mathematical morphology Middle Aged Models, Statistical Morphing Parameters Retrospective Studies Set theory sparse autoencoder networks statistical shape modelling Tomography, X-Ray Computed trochlear dysplasia trochlear morphology sparse autoencoder networks trochlear morphology trochlear dysplasia statistical shape modelling
ISSN:	1478-5951, 1478-596X, 1478-596X
On-line prístup:	Získať plný text
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