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AIME
2009
Springer

Causal Probabilistic Modelling for Two-View Mammographic Analysis

10 years 9 days ago
Causal Probabilistic Modelling for Two-View Mammographic Analysis
Abstract. Mammographic analysis is a difficult task due to the complexity of image interpretation. This results in diagnostic uncertainty, thus provoking the need for assistance by computer decision-making tools. Probabilistic modelling based on Bayesian networks is among the suitable tools, as it allows for the formalization of the uncertainty about parameters, models, and predictions in a statistical manner, yet such that available background knowledge about characteristics of the domain can be taken into account. In this paper, we investigate a specific class of Bayesian networks—causal independence models—for exploring the dependencies between two breast image views. The proposed method is based on a multi-stage scheme incorporating domain knowledge and information obtained from two computer-aided detection systems. The experiments with actual mammographic data demonstrate the potential of the proposed two-view probabilistic system for supporting radiologists in detecting brea...
Marina Velikova, Maurice Samulski, Peter J. F. Luc
Added 25 May 2010
Updated 25 May 2010
Type Conference
Year 2009
Where AIME
Authors Marina Velikova, Maurice Samulski, Peter J. F. Lucas, Nico Karssemeijer
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