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Reducing acquisition time for MRI-based forensic age estimation.

Bernhard NeumayerMatthias SchloeglChristian PayerThomas WidekSebastian TschaunerThomas EhammerRudolf StollbergerMartin Urschler
Published in: Scientific reports (2018)
Radiology-based estimation of a living person's unknown age has recently attracted increasing attention due to large numbers of undocumented immigrants entering Europe. To avoid the application of X-ray-based imaging techniques, magnetic resonance imaging (MRI) has been suggested as an alternative imaging modality. Unfortunately, MRI requires prolonged acquisition times, which potentially represents an additional stressor for young refugees. To eliminate this shortcoming, we investigated the degree of reduction in acquisition time that still led to reliable age estimates. Two radiologists randomly assessed original images and two sets of retrospectively undersampled data of 15 volunteers (N = 45 data sets) applying an established radiological age estimation method to images of the hand and wrist. Additionally, a neural network-based age estimation method analyzed four sets of further undersampled images from the 15 volunteers (N = 105 data sets). Furthermore, we compared retrospectively undersampled and acquired undersampled data for three volunteers. To assess reliability with increasing degree of undersampling, intra-rater and inter-rater agreement were analyzed computing signed differences and intra-class correlation. While our findings have to be confirmed by a larger prospective study, the results from both radiological and automatic age estimation showed that reliable age estimation was still possible for acquisition times of 15 seconds.
Keyphrases
  • magnetic resonance imaging
  • high resolution
  • deep learning
  • contrast enhanced
  • electronic health record
  • big data
  • computed tomography
  • machine learning
  • magnetic resonance
  • photodynamic therapy
  • middle aged
  • high speed