@inBook{
 title = {Fully automatic bone age estimation from left hand MR images},
 type = {inBook},
 year = {2014},
 identifiers = {[object Object]},
 pages = {220-227},
 volume = {17},
 websites = {http://link.springer.com/10.1007/978-3-319-10470-6_28},
 publisher = {Springer, Cham},
 city = {Boston},
 editors = {[object Object],[object Object],[object Object],[object Object],[object Object]},
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 abstract = {There has recently been an increased demand in bone age estimation (BAE) of living individuals and human remains in legal medicine applications. A severe drawback of established BAE techniques based on X-ray images is radiation exposure, since many countries prohibit scanning involving ionizing radiation without diagnostic reasons. We propose a completely automated method for BAE based on volumetric hand MRI images. On our database of 56 male caucasian subjects between 13 and 19 years, we are able to estimate the subjects age with a mean difference of 0.85 ?? 0.58 years compared to the chronological age, which is in line with radiologist results using established radiographic methods. We see this work as a promising first step towards a novel MRI based bone age estimation system, with the key benefits of lacking exposure to ionizing radiation and higher accuracy due to exploitation of volumetric data.},
 bibtype = {inBook},
 author = {Stern, Darko and Ebner, Thomas and Bischof, Horst and Grassegger, Sabine and Ehammer, Thomas and Urschler, Martin},
 book = {Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention}
}

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