As Easy as 1, 2… 4? Uncertainty in Counting Tasks for Medical Imaging.
Journal
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Titre abrégé: Med Image Comput Comput Assist Interv
Pays: Germany
ID NLM: 101249582
Informations de publication
Date de publication:
2019
2019
Historique:
entrez:
24
6
2021
pubmed:
1
1
2019
medline:
1
1
2019
Statut:
ppublish
Résumé
Counting is a fundamental task in biomedical imaging and count is an important biomarker in a number of conditions. Estimating the uncertainty in the measurement is thus vital to making definite, informed conclusions. In this paper, we first compare a range of existing methods to perform counting in medical imaging and suggest ways of deriving predictive intervals from these. We then propose and test a method for calculating intervals as an output of a multi-task network. These predictive intervals are optimised to be as narrow as possible, while also enclosing a desired percentage of the data. We demonstrate the effectiveness of this technique on histopathological cell counting and white matter hyperintensity counting. Finally, we offer insight into other areas where this technique may apply.
Identifiants
pubmed: 34164630
doi: 10.1007/978-3-030-32251-9_39
pmc: PMC7611043
mid: EMS126274
doi:
Types de publication
Journal Article
Langues
eng
Pagination
356-364Subventions
Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 203148
Pays : United Kingdom
Références
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pubmed: 29544777
IEEE Trans Med Imaging. 2019 Feb;38(2):448-459
pubmed: 30716022
IEEE Trans Med Imaging. 2019 Nov;38(11):2556-2568
pubmed: 30908194
Neurocomputing. 2019 Sep 3;335:34-45
pubmed: 31595105