From post

Fuzzy Multi-class Statistical Modeling for Efficient Total Lesion Metabolic Activity Estimation from Realistic PET Images.

, , , , , , , и . MICCAI (1), том 7510 из Lecture Notes in Computer Science, стр. 107-114. Springer, (2012)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed.

 

Другие публикации лиц с тем же именем

Quantitative comparison of automated PET volume delineation methodologies using simulated tumor lesions., , , , , , и . ISBI, стр. 653-656. IEEE, (2011)Fuzzy Statistical Unsupervised Learning Based Total Lesion Metabolic Activity Estimation in Positron Emission Tomography Images., , , , , , и . MLMI, том 7009 из Lecture Notes in Computer Science, стр. 233-240. Springer, (2011)Revised guidelines for the clinical management of Lynch syndrome (HNPCC): recommendations by a group of European experts, , , , , , , , , и 26 other автор(ы). Gut, 62 (6): 812–823 (2013)SLAC: Statistical total lesion metabolic activity computation by fuzzy unsupervised learning of PET images., , , , , , , и . Mach. Vis. Appl., 24 (7): 1341-1358 (2013)Fuzzy Multi-class Statistical Modeling for Efficient Total Lesion Metabolic Activity Estimation from Realistic PET Images., , , , , , , и . MICCAI (1), том 7510 из Lecture Notes in Computer Science, стр. 107-114. Springer, (2012)A textural feature based tumor therapy response prediction model for longitudinal evaluation with PET imaging., , , , , , , и . ISBI, стр. 1048-1051. IEEE, (2012)