Oncohema Key

(8.1) where f(u, v) is a function determined using a machine learning approach, which we choose to be support vector machine (SVM) learning [26], and ζ is the modeling error. The…

Fig. 7.1 Flowchart for a generic CADe scheme for the detection of lesions in diagnostic images. Boxes with solid lines indicate four core steps in the CADe scheme, and those…

Fig. 17.1 As the dose delivered to a tumour increases, so does the probability of tumour control (TCP). However, the resultant increase in dose to surrounding healthy tissues increases the…

Fig. 4.1 The main steps of evaluation Comparison of a new algorithm to other (may be generic or application-specific) classifiers on a specific domain (e.g., when proposing a novel learning…

(14.1) where C j is the j -th cluster, μ j is the center of the j -th cluster, and D stands for the distance between the two points. Each…

(18.1) where d is the fraction size, D is the total delivered dose, t is the difference between the total treatment time (T) and the lag period before accelerated clonogen…

Fig. 2.1 Computational modeling vs. statistical analysis (Adapted from [5]) Machine learning is a branch of computational modeling that inherited many of its properties and utilizes statistical modeling techniques as…

(13.1) subject to: (13.2)where w and ρ are hyperplane parameters, Φ is the map from input space to feature space, v is the asymptotic fraction of outliers (errors) allowed, l…

Fig. 16.1 Radiotherapy treatment involves complex interaction of physical, biological, and clinical factors. The successful informatics approach should be able to resolve this interaction “puzzle” in the observed treatment outcome…

Fig. 10.1 Summary of a typical treatment planning process (The image is courtesy M. Lewis from imPACT) More recently, there has been interest in using prior treatment planning information, referred…