This article is part of the supplement: New trends in digital pathology: Proceedings of the 9th European Congress on Telepathology and 3rd International Congress on Virtual Microscopy
Automated region of interest retrieval and classification using spectral analysis
1 TRIBVN, 39 rue Louveau, 92320 Châtillon, France
2 EPF Ecole d'ingénieurs, 3 bis rue Lakanal, 92330 Sceaux, France
3 Histo-imagerie quantitative, GRECAN (EA 1772, IFR 146 ICORE University of Caen Basse-Normandie), F. Baclesse Cancer Centre, Bd Général Harris, F 14076 Caen, France
4 Service d'Anatomie pathologique, F. Baclesse Cancer Centre, Bd Général Harris, F 14076 Caen, France
5 GREYC, UMR 6072, University of Caen Basse-Normandie, 6 Boulevard du Maréchal Juin, 14050 Caen Cedex, France
Diagnostic Pathology 2008, 3(Suppl 1):S17 doi:10.1186/1746-1596-3-S1-S17Published: 15 July 2008
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.