Computational Pathology -- A Machine Learning Approach

Computational Pathology is a novel field comprising aspects of machine learning, Computational Pathology computer vision, clinical statistics and general pathology. The principal focus of this thesis is to define this new field, develop and investigate statistical methods which can be combined within an unified framework to answer scientific and clinical questions in pathology. The histological assessment of human tissue has emerged as the key challenge for detection and treatment of cancer. A plethora of different data sources ranging from tissue microarray data to gene expression, proteomics or me-tabolomics data provide a detailed overview of the health status of a patient. Medical doctors need to assess these information sources and they rely on data driven automatic analysis tools. Methods for classification, grouping and seg-mentation of heterogeneous data sources as well as regression of noisy depen-dencies and estimation of survival probabilities enter the processing workflow of a pathology diagnosis system at various stages