Oncohema Key

(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…

Fig. 5.1 With each step along the process, more information is created and collected which is associated with the patient The imaging data, accompanied by identifiers, is then transferred to…

Fig. 12.1 Cast the gating problem (a) into a binary classification problem (b) (Reprint from Cui et al. [2]) One major issue with learning from images is the large dimensionality…

Fig. 15.1 (a) The average chart for the clinical case. Subgroup size of four is used to verify the constancy of the flatness and symmetry. (b) The range chart of…

Fig. 1.1 Categories of machine learning algorithms according to training data nature From a concept learning perspective, machine learning can be categorized into transductive and inductive learning [27]. Transductive learning…