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Estimation of Height, Weight, Sex and Age from Magnetic Resonance Images using 3D Convolutional Neural Networks / Estimering av längd, vikt, kön och ålder från MR-bilder med 3D neurala faltningsnät

Magnetic resonance imagining is a non-invasive 3D imaging technology widely used in the medical field for partial and full body scans. AMRA Medical AB is a medical company which combines MRI images with additional patient attributes such as height, weight, sex and age to perform analysis such as body composition profiling. However, the additional information required is not always available or accurate. Manual measurements are proneto human error, and retrieving them from patient journals is complicated due to the sensitivenature of the information. This thesis investigates technologies to instead estimate height, weight, sex and age automatically from only the MR images by the use of deep learning. If successful, such methods could eliminate the reliance on additional subject information. Alternatively they could serve as an error detection mechanism to flag possibleinaccuracies in the data, which could be of use for both AMRA as well as for operators in a clinical scenario.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-185766
Date January 2022
CreatorsNimhed, Carl
PublisherLinköpings universitet, Institutionen för medicinsk teknik
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

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