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A Novel Stochastic Combination of 3D Texture Features for Automated Segmentation of Prostatic Adenocarcinoma from High Resolution MRI
[chapter]
2003
Lecture Notes in Computer Science
In this work, we present a new methodology for fully automated segmentation of prostatic adenocarcinoma from high resolution MR by using a novel feature ensemble of 3D texture features. This work represents the first attempt to solve this difficult problem using high resolution MR. The difficulty of the problem stems from lack of shape and structure in the adenocarcinoma. Hence, in our methodology we compute statistical, gradient and Gabor filter features at multiple scales and orientations in
doi:10.1007/978-3-540-39899-8_72
fatcat:p75dikufkfaglixbuywsmxfwyy