Title
Segmentation of the proximal femur by the analysis of X-ray imaging using statistical models of shape and appearance
Date Issued
01 January 2018
Access level
metadata only access
Resource Type
conference paper
Author(s)
Universidad Nacional de San Agustín de Arequipa
Universidad Nacional de San Agustín de Arequipa
Publisher(s)
Springer Verlag
Abstract
Using image processing to assist in the diagnostic of diseases is a growing challenge. Segmentation is one of the relevant stages in image processing. We present a strategy of complete segmentation of the proximal femur (right and left) in anterior-posterior pelvic radiographs using statistical models of shape and appearance for assistance in the diagnostics of diseases associated with femurs. Quantitative results are provided using the DICE coefficient and the processing time, on a set of clinical data that indicate the validity of our proposal.
Start page
25
End page
35
Volume
10842 LNAI
Language
English
OCDE Knowledge area
Biotecnología relacionada con la salud
Subjects
Scopus EID
2-s2.0-85048060813
ISBN
9783319912615
Resource of which it is part
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN of the container
03029743
ISBN of the container
978-331991261-5
Conference
17th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2018
Sources of information:
Directorio de Producción Científica
Scopus