title: Automated region of interest retrieval and classification using spectral analysis.
abstract: Efficient use of whole slide imaging in pathology needs automated region of interest (ROI) retrieval and classification, through the use of image analysis and data sorting tools. One possible method for data sorting uses Spectral Analysis for Dimensionality Reduction. We present some interesting results in the field of histopathology and cytohematology. In histopathology, we developed a Computer-Aided Diagnosis system applied to low-resolution images representing the totality of histological breast tumour sections. The images can be digitized directly at low resolution or be obtained from sub-sampled high-resolution virtual slides. Spectral Analysis is used (1) for image segmentation (stroma, tumour epithelium), by determining a "distance" between all the images of the database, (2) for choosing representative images and characteristic patterns of each histological type in order to index them, and (3) for visualizing images or features similar to a sample provided by the pathologist. In cytohematology, we studied a blood smear virtual slide acquired through high resolution oil scanning and Spectral Analysis is used to sort selected nucleated blood cell classes so that the pathologist may easily focus on specific classes whose morphology could then be studied more carefully or which can be analyzed through complementary instruments, like Multispectral Imaging or Raman MicroSpectroscopy.
authors.affiliation: TRIBVN, 39 rue Louveau, Châtillon, France. m.oger@baclesse.fr
authors.forename: Myriam
authors.initials: M
authors.lastname: Oger
authors.forename: Philippe
authors.initials: P
authors.lastname: Belhomme
authors.forename: Jacques
authors.initials: J
authors.lastname: Klossa
authors.forename: Jean-Jacques
authors.initials: JJ
authors.lastname: Michels
authors.forename: Abderrahim
authors.initials: A
authors.lastname: Elmoataz