PT Unknown
AU S.Grau
   Ana Puig
   Sergio Escalera
   Maria Salamo
TI Intelligent Interactive Volume Classification
BT Pacific Graphics
PY 2013
BP 23
EP 28
VL 32
IS 7
DI 10.2312/PE.PG.PG2013short.023-028
AB This paper defines an intelligent and interactive framework to classify multiple regions of interest from the original data on demand, without requiring any preprocessing or previous segmentation. The proposed intelligent and interactive approach is divided in three stages: visualize, training and testing. First, users visualize and label some samples directly on slices of the volume. Training and testing are based on a framework of Error Correcting Output Codes and Adaboost classifiers that learn to classify each region the user has painted. Later, at the testing stage, each classifier is directly applied on the rest of samples and combined to perform multi-class labeling, being used in the final rendering. We also parallelized the training stage using a GPU-based implementation forobtaining a rapid interaction and classification.
ER