title: Image-Processing Scheme to Detect Superficial Fungal Infections of the Skin.
abstract: The incidence of superficial fungal infections is assumed to be 20 to 25% of the global human population. Fluorescence microscopy of extracted skin samples is frequently used for a swift assessment of infections. To support the dermatologist, an image-analysis scheme has been developed that evaluates digital microscopic images to detect fungal hyphae. The aim of the study was to increase diagnostic quality and to shorten the time-to-diagnosis. The analysis, consisting of preprocessing, segmentation, parameterization, and classification of identified structures, was performed on digital microscopic images. A test dataset of hyphae and false-positive objects was created to evaluate the algorithm. Additionally, the performance for real clinical images was investigated using 415 images. The results show that the sensitivity for hyphae is 94% and 89% for singular and clustered hyphae, respectively. The mean exclusion rate is 91% for the false-positive objects. The sensitivity for clinical images was 83% and the specificity was 79%. Although the performance is lower for the clinical images than for the test dataset, a reliable and fast diagnosis can be achieved since it is not crucial to detect every hypha to conclude that a sample consisting of several images is infected. The proposed analysis therefore enables a high diagnostic quality and a fast sample assessment to be achieved.
authors.affiliation: Institute of Medical Physics and Radiation Protection, Technische Hochschule Mittelhessen - University of Applied Sciences, 35390 Giessen, Germany.
authors.forename: Ulf
authors.initials: U
authors.lastname: Mäder
authors.affiliation: Helmut Hund GmbH, Artur Herzog Straße 2, 35580 Wetzlar, Germany.
authors.forename: Niko
authors.initials: N
authors.lastname: Quiskamp
authors.affiliation: Institute of Bioprocess Engineering and Pharmaceutical Technology, Technische Hochschule Mittelhessen - University of Applied Sciences, 35390 Giessen, Germany.
authors.forename: Sören
authors.initials: S
authors.lastname: Wildenhain
authors.affiliation: Institute of Bioprocess Engineering and Pharmaceutical Technology, Technische Hochschule Mittelhessen - University of Applied Sciences, 35390 Giessen, Germany.
authors.forename: Thomas
authors.initials: T
authors.lastname: Schmidts
authors.affiliation: Department of Dermatology, Venereology and Allergology, Justus Liebig University Giessen, 35390 Giessen, Germany.
authors.forename: Peter
authors.initials: P
authors.lastname: Mayser
authors.affiliation: Institute of Bioprocess Engineering and Pharmaceutical Technology, Technische Hochschule Mittelhessen - University of Applied Sciences, 35390 Giessen, Germany.
authors.forename: Frank
authors.initials: F
authors.lastname: Runkel
authors.affiliation: Institute of Medical Physics and Radiation Protection, Technische Hochschule Mittelhessen - University of Applied Sciences, 35390 Giessen, Germany.
authors.forename: Martin
authors.initials: M
authors.lastname: Fiebich
mesh_terms: D000465:Algorithms; D019295:Computational Biology; D003881:Dermatomycoses / Q000175:diagnosis* / Q000382:microbiology; D005189:False Positive Reactions; D006801:Humans; D025301:Hyphae / Q000648:ultrastructure; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008856:Microscopy, Fluorescence / Q000379:methods / Q000706:statistics & numerical data