Titlebook: Image Analysis and Recognition; International Confer Aurélio Campilho,Mohamed Kamel Conference proceedings 2004 Springer-Verlag Berlin Heid

用手捏

弯曲道理

Ordeal

条约

Keratin

Fuzzy-Snake Segmentation of Anatomical Structures Applied to CT Imagesan adapted PDM by fuzzy c-means classification, which also uses the fuzzy decision to evolve PDM into the final contour. Furthermore, the fuzzy reasoning exploits .. statistical information from several knowledge sources based on histogram analysis and the intensity values of the structures under co

Adherent

拥护者

Region of Interest Based Prostate Tissue Characterization Using Least Square Support Vector Machine chnique is designed to automatically identify the Regions of Interest (ROI) in the segmented prostate image. These ROIs are the high probable cancerous regions in the gland. Furthermore, statistical texture analysis for these regions is carried out by employing Grey Level Difference Matrix (GLDM), w

知识分子

Ribcage Boundary Delineation in Chest X-ray Images image landmarks: the center of the ribcage and, using polar transformation from this point, two initial points belonging to the ribcage. A bank of Gabor filters (in analogy with the simple cells present in the human visual cortex) is used to obtain an . enhanced image. In this enhanced image, an ed

braggadocio

A Level-Set Based Volumetric CT Segmentation Technique: A Case Study with Pulmonary Air Bubblesl pulmonary regions on volumetric data, using a model deforming towards the objects of interest, is presented. We propose a variant to the well known level-set method that keeps the level-set function moving along desired directions, with an improved stopping function that proved to be successful, e

灰心丧气

Robust Fitting of a Point Distribution Model of the Prostate Using Genetic Algorithmsasound images. We developed a new, two stage, method: first the PDM is fitted, using a multi-population genetic algorithm, to a binary image produced from Bayesian pixel classification. This contour is then used during the second stage to seed the initial population of a simple genetic algorithm, wh