Brain Tumor Segmentation Based on Random Forest
Journal Title: Memoirs of the Scientific Sections - Year 2016, Vol 0, Issue
Abstract
In this article we present a discriminative model for tumor detection from multimodal MR images. The main part of the model is built around the random forest (RF) classifier. We created an optimization algorithm able to select the important features for reducing the dimensionality of data. This method is also used to find out the training parameters used in the learning phase. The algorithm is based on random feature properties for evaluating the importance of the variable, the evolution of learning errors and the proximities between instances. The detection performances obtained have been compared with the most recent systems, offering similar results.
Authors and Affiliations
László Lefkovits, Szidónia Lefkovits, Mircea-Florin Vaida
In Memoriam LOTFI A. ZADEH
The paper entitled In Memoriam Lofti A. Zadeh synthesizes the main scientific achievements of a great man-of-science – system theorist, computer scientist, physicist and engineer - the author of several key notions, such...
Selection of Relevant Parameters for Human Locomotion Unsupervised Classification
A method for the automatic selection of the most relevant parameters for human locomotion classification is proposed. A set of 36 statistical parameters extracted from video sequences showing three basic movement types i...
Study on Poly(Vinyl Alcohol) CopolymersBiodegradation
In the study the biodegradability of some poly(vinyl alcohol)-g-aspartic acid copolymers was investigated, using Trichotecium roseum fungus. The biodegraded samples were examined after established days of inoculation (3–...
Image-Based Visual Servoing for Manipulation Via Predictive Control – A Survey of Some Results
In this paper, a review of predictive control algorithms developed by the authors for visual servoing of robots in manipulation applications is presented. Using these algorithms, a control predictive framework was create...
Optic Disc Localization Based on Feature Sorting
Localization of the optic disc (OD) is a necessary step in automatic diagnosis of ocular diseases in retinal images: diabetic retinopathy, glaucoma and so on. In this paper, we combine different features and classificati...