eprintid: 32363
rev_number: 10
eprint_status: archive
userid: 4613
dir: disk0/00/03/23/63
datestamp: 2022-11-10 10:09:19
lastmod: 2022-11-10 10:09:19
status_changed: 2022-11-10 10:09:19
type: HD.PhdThesisAb
metadata_visibility: show
creators_name: Sforazzini, Francesco
title: Development of machine learning-based spatially and temporally
resolved 4D radiomics in radiation oncology
subjects: 610
divisions: 51001
adv_faculty: af-05
keywords: Deutsches Krebsforschungszentrum (DKFZ)
date: 2022
own_urn: urn:nbn:de:bsz:16-heidok-323635
date_accepted: 2022-10-10
advisor: HASH(0x564efd4b0370)
language: ger
bibsort: SFORAZZINIDEVELOPMEN2022
full_text_status: public
citation:   Sforazzini, Francesco  (2022) Development of machine learning-based spatially and temporally resolved 4D radiomics in radiation oncology.  [Kurzfassung einer medizinischen Dissertation]     
document_url: https://archiv.ub.uni-heidelberg.de/volltextserver/32363/1/Sforazzini_Francesco.pdf