Computational pathology in oncology


Abstract : Evaluation of histomorphological features and molecular biomarkers on tissue slides is a routine procedure in clinical pathology for cancer diagnosis and prognosis as well as for guiding therapeutic decisions. However, this evaluation generally uses partial visual examination and semi-quantification scoring. In addition to intra- and inter-observer variability, this evaluation suffers from difficulties to identify morphological features with potential prognostic and/or therapeutic values in the complex and heterogeneous microenvironment of tumor cells. Whole slide imaging and image analysis may overcome such limitations in current pathological setting by providing quantitative evaluation of established and new histopathological features. In the present project, we propose to apply this strategy for colorectal cancer and tumor budding, because optimal quantification of budding may improve patient prognostic estimation and therapeutic decision making.
Promoteur/Supervisor : Prof. Decaestecker Christine
Email : cdecaes@ulb.ac.be
Site Web/Web site :
Centre de recherche/Research center : LISA - DIAPath (CMMI)
Faculté/Faculty : Brussels School of Engineering (Faculty of Applied Sciences)/Faculté des Sciences appliquées - école polytechnique
Ecole doctorale/Graduate Colleges : Engineering/Sciences de l'ingénieur
Ecole doctorale thématique/Graduate School (French Only):



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