title: A cognitive virtual microscopic framework for knowledge-based exploration of large microscopic images in breast cancer histopathology.
abstract: Histopathological examination is a powerful method for prognosis of major diseases such as breast cancer. Analysis of medical images largely remains the work of human experts. Current virtual microscope systems are mainly an emulation of real microscopes with annotation and some image analysis capabilities. However, the lack of effective knowledge management prevents such systems from being computer-aided prognosis platforms. The cognitive virtual microscopic framework, through an extended modeling and use of medical knowledge, has the capacity to analyse histopathological images and to perform grading of breast cancer, providing pathologists with a robust and traceable second opinion.
authors: Image & Pervasive Access Lab, UMI CNRS, University Joseph Fourier, Grenoble, France. vislr@i2r.a-star.edu.sg
authors: Ludovic
authors: L
authors: Roux
authors: Adina
authors: A
authors: Tutac
authors: Nicolas
authors: N
authors: Lomenie
authors: Didier
authors: D
authors: Balensi
authors: Daniel
authors: D
authors: Racoceanu
authors: Antoine
authors: A
authors: Veillard
authors: Wee-Kheng
authors: WK
authors: Leow
authors: Jacques
authors: J
authors: Klossa
authors: Thomas C
authors: TC
authors: Putti
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000473:pathology; D003071:Cognition; D003196:Computer Graphics; D003201:Computers; D003952:Diagnostic Imaging / Q000379:methods; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D051188:Knowledge Bases; D008495:Medical Oncology / Q000379:methods; D008853:Microscopy / Q000379:methods*; D011379:Prognosis; D012984:Software; D014584:User-Computer Interface