A major factor affecting the clarity of graphical displays that include text labels is the degree to which labels obscure display features (including other labels) as a result of spatial overlap. Point-feature label placement (PFLP) is the problem of placing text labels adjacent to point features on a map or diagram so as to maximize legibility. This problem occurs frequently in the production of many types of informational graphics, though it arises most often in automated cartography. In this paper we present a comprehensive treatment of the PFLP problem, viewed as a type of combinatorial optimization problem. Complexity analysis reveals that the basic PFLP problem and most interesting variants of it are NP-hard. These negative results help inform a survey of previously reported algorithms for PFLP; not surprisingly, all such algorithms either have exponential time complexity or are incomplete. To solve the PFLP problem in practice, then, we must rely on good heuristic methods. We propose two new methods, one based on a discrete form of gradient descent, the other on simulated annealing, and report on a series of empirical tests comparing these and the other known algorithms for the problem. Based on this study, the first to be conducted, we identify the best approaches as a function of available computation time.
Significant improvement in DSS was seen in patients with clear margins, early stage grouping and clinical (pretreatment) tumor stage, and negative nodes. Significant decrease in DSS was seen in patients with close or involved margins, advanced stage grouping and clinical (pretreatment) tumor staging, positive clinical (pretreatment) node staging, and tumor recurrence. Obtaining clear margins of resection is crucial because it significantly affects survival. A minimum of 5 years of close monitoring is recommended because of the high incidence of second primary cancers.
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