- Tytuł:
- Application of an artificial neural network and morphing techniques in the redesign of dysplastic trochlea
- Autorzy:
-
Cho, K. J.
Müller, J. H.
Erasmus, P. J.
Dejour, D.
Scheffer, C. - Powiązania:
- https://bibliotekanauki.pl/articles/307312.pdf
- Data publikacji:
- 2014
- Wydawca:
- Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
- Tematy:
-
artificial neural network
trochlea redesign
trochlear dysplasia
trochleoplasty
trochlea morphing
sztuczna sieć neuronowa
bloczek
biomechanika - Opis:
- Segmentation and computer assisted design tools have the potential to test the validity of simulated surgical procedures, e.g., trochleoplasty. A repeatable measurement method for three dimensional femur models that enables quantification of knee parameters of the distal femur is presented. Fifteen healthy knees are analysed using the method to provide a training set for an artificial neural network. The aim is to use this artificial neural network for the prediction of parameter values that describe the shape of a normal trochlear groove geometry. This is achieved by feeding the artificial neural network with the unaffected parameters of a dysplastic knee. Four dysplastic knees (Type A through D) are virtually redesigned by way of morphing the groove geometries based on the suggested shape from the artificial neural network. Each of the four resulting shapes is analysed and compared to its initial dysplastic shape in terms of three anteroposterior dimensions: lateral, central and medial. For the four knees the trochlear depth is increased, the ventral trochlear prominence reduced and the sulcus angle corrected to within published normal ranges. The results show a lateral facet elevation inadequate, with a sulcus deepening or a depression trochleoplasty more beneficial to correct trochlear dysplasia.
- Źródło:
-
Acta of Bioengineering and Biomechanics; 2014, 16, 2; 75-84
1509-409X
2450-6303 - Pojawia się w:
- Acta of Bioengineering and Biomechanics
- Dostawca treści:
- Biblioteka Nauki