http://www.cnr.it/ontology/cnr/individuo/prodotto/ID325530
Automatic segmentation of vertebral interfaces in echographic images (Contributo in atti di convegno)
- Type
- Label
- Automatic segmentation of vertebral interfaces in echographic images (Contributo in atti di convegno) (literal)
- Anno
- 2014-01-01T00:00:00+01:00 (literal)
- Alternative label
M. Aventaggiato, F. Conversano, E. Casciaro, R. Franchini, A. Lay-Ekuakille, M. Muratore, and S. Casciaro (2014)
Automatic segmentation of vertebral interfaces in echographic images
in 3rd Imeko TC13 Symposium on Measurements in Biology and Medicine "New Frontiers in Biomedical Measurements", Lecce, Italy, 17-18 Aprile 2014
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- M. Aventaggiato, F. Conversano, E. Casciaro, R. Franchini, A. Lay-Ekuakille, M. Muratore, and S. Casciaro (literal)
- Pagina inizio
- Pagina fine
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
- Proceedings of the 3rd Imeko TC13 Symposium on Measurements in Biology and Medicine \"New Frontiers in Biomedical Measurements\" (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- Echolight S.r.l., Lecce , Italy; National Research Council, Institute of Clinical Physiology, Lecce, Italy; University of Salento, Department of Innovation Engineering, Lecce, Italy; O.U. of Rheumatology, Galateo Hospital, San Cesario di Lecce, ASL-LE, Lecce, Italy. (literal)
- Titolo
- Automatic segmentation of vertebral interfaces in echographic images (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
- 978-92-990073-5-8 (literal)
- Abstract
- Quantitative ultrasound (QUS) methods for
osteoporosis diagnosis potentially provide information about
the bone quality and its elastic properties. In this context, a
novel ultrasound-based method for spinal and femoral
densitometry was developed by our research group. In order
to maximize its accuracy, it is very important to properly
detect the bone interfaces that will be analyzed as regions of
interest (ROIs). A fully automatic segmentation algorithm
was developed to select lumbar vertebral interfaces in
echographic images and its actual accuracy was assessed in
the present work by means of a visual checking carried out
by an expert operator. Abdominal US scans of lumbar spine
(from L1 to L4) were performed on 100 female subjects
(60.5±3.0 years old) with different ranges of body mass
index (BMI) (25.8±4.6 kg/m2). During each US scan, 100
frames of radiofrequency (RF) data were stored on a PC
hard disk for offline analysis. The operator scanned each
vertebra, moving the probe to the next vertebra after 20
seconds. For each acquired RF data frame, the implemented
algorithm generated a sectorial echographic image and, if a
vertebral interface was detected, it was highlighted on the
saved image. The validation procedure was performed by an
expert operator previously trained to detect the \"optimal\"
vertebral interfaces for osteoporosis diagnosis. Results
showed that the segmentation algorithm had a high
specificity (93.4%), which reached its maximum on subjects
with BMI < 25 kg/m2 (94.2%), thus avoiding the selection
of false vertebral interfaces and allowing a good accuracy of
osteoporosis diagnosis. (literal)
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