Title
Multispectral band selection and spatial characterization: Application to mitosis detection in breast cancer histopathology
Date Issued
01 January 2014
Access level
metadata only access
Resource Type
journal article
Author(s)
Irshad H.
Gouaillard A.
Roux L.
Sorbonne Université
Publisher(s)
Elsevier Ltd
Abstract
Breast cancer is the second most frequent cancer. The reference process for breast cancer prognosis is Nottingham grading system. According to this system, mitosis detection is one of the three important criteria required for grading process and quantifying the locality and prognosis of a tumor. Multispectral imaging, as relatively new to the field of histopathology, has the advantage, over traditional RGB imaging, to capture spectrally resolved information at specific frequencies, across the electromagnetic spectrum. This study aims at evaluating the accuracy of mitosis detection on histopathological multispectral images. The proposed framework includes: selection of spectral bands and focal planes, detection of candidate mitotic regions and computation of morphological and multispectral statistical features. A state-of-the-art of the methods for mitosis classification is also provided. This framework has been evaluated on MITOS multispectral dataset and achieved higher detection rate (67.35%) and F-Measure (63.74%) than the best MITOS contest results (Roux et al., 2013). Our results indicate that the selected multispectral bands have more discriminant information than a single spectral band or all spectral bands for mitotic figures, validating the interest of using multispectral images to improve the quality of the diagnostic in histopathology. © 2014 Elsevier Ltd.
Start page
390
End page
402
Volume
38
Issue
5
Language
English
OCDE Knowledge area
Oncología Radiología, Medicina nuclear, Imágenes médicas Ciencias de la computación
Scopus EID
2-s2.0-84902107127
PubMed ID
Source
Computerized Medical Imaging and Graphics
ISSN of the container
08956111
Sponsor(s)
This work is supported by the French National Research Agency ANR , project MICO, reference ANR-10-TECS-015 .
Sources of information: Directorio de Producción Científica Scopus