Estimating Bacterial Load in FCFM Imaging

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We address the task of detecting bacteria and estimating bacterial load in the human distal lung with fibered confocal fluorescence microscopy (FCFM) and a targeted smartprobe. Bacteria appear as bright dots in the image when exposed to a smartprobe, but they are often diffcult to detect due to the presence of background auto fluorescence inherent to human lungs. In this study, we create a database of annotated image frames where a clinician has labelled bacteria, and use this database for supervised learning to build a suitable bacterial load
estimation software.
Original languageEnglish
Title of host publicationMedical Image Understanding and Analysis. MIUA 2017.
PublisherSpringer, Cham
Pages909-921
Number of pages12
ISBN (Electronic)978-3-319-60964-5
ISBN (Print)978-3-319-60963-8
DOIs
Publication statusPublished - 22 Jun 2017
EventMedical Image Understanding and Analysis (MIUA 2017) - Edinburgh, United Kingdom
Duration: 11 Jul 201713 Jul 2017

Publication series

NameCommunications in Computer and Information Science
PublisherSpringer, Cham
Volume723
ISSN (Print)1865-0929

Conference

ConferenceMedical Image Understanding and Analysis (MIUA 2017)
Country/TerritoryUnited Kingdom
CityEdinburgh
Period11/07/1713/07/17

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