Webbläsaren som du använder stöds inte av denna webbplats. Alla versioner av Internet Explorer stöds inte längre, av oss eller Microsoft (läs mer här: * https://www.microsoft.com/en-us/microsoft-365/windows/end-of-ie-support).

Var god och använd en modern webbläsare för att ta del av denna webbplats, som t.ex. nyaste versioner av Edge, Chrome, Firefox eller Safari osv.

HEp-2 Staining Pattern Classification

Författare

  • Petter Strandmark
  • Johannes Ulén
  • Fredrik Kahl

Summary, in English

Classifying images of HEp-2 cells from indirect immunofluorescence has important clinical applications. We have developed an automatic method based on random forests that classifies an HEp-2 cell image into one of six classes. The method is applied to the data set of the ICPR 2012 contest. The previously obtained best accuracy is 79.3% for this data set, whereas we obtain an accuracy of 97.4%. The key to our result is due to carefully designed feature descriptors for multiple level sets of the image intensity. These features characterize both the appearance and the shape of the cell image in a robust manner.

Publiceringsår

2012

Språk

Engelska

Publikation/Tidskrift/Serie

Pattern Recognition (ICPR), 2012 21st International Conference on

Dokumenttyp

Konferensbidrag

Förlag

IEEE - Institute of Electrical and Electronics Engineers Inc.

Ämne

  • Computer Vision and Robotics (Autonomous Systems)
  • Mathematics

Conference name

21st International Conference on Pattern Recognition (ICPR 2012)

Conference date

2012-11-11 - 2012-11-15

Conference place

Tsukuba, Japan

Status

Published

Forskningsgrupp

  • Mathematical Imaging Group

ISBN/ISSN/Övrigt

  • ISBN: 978-1-4673-2216-4