Information Technology Reference
In-Depth Information
4. Axer, H., Jantzen, J., von Keyserlingk, D.G., Berks, G.: The Application of Fuzzy-based
Methods to Central Nerve Fiber Imaging. Artificial Intelligence in Medicine 29(3), 225-
239 (2003)
5. Ayala, G., Leon, T., Zapater, V.: Different Averages of a Fuzzy Set with an Application
to Vessel Segmentation. IEEE Transactions on Fuzzy Systems 13(3), 384-393 (2005)
6. Belhassen, S., Zaidi, H.: A Novel Fuzzy C-means Algorithm for Unsupervised Hetero-
geneous Tumor Quantification in PET. Medical Physics 37(3), 1309-1324 (2010)
7. Bougioukos, P., Glotsos, D., Kostopoulos, S., Daskalakis, A., Kalatzis, I., Dimitropou-
los, N., Nikiforidis, G., Cavouras, D.: Fuzzy C-means-driven FHCE Contextual Seg-
mentation Method for Mammographic Microcalcification Detection. Imaging Science
Journal 58(3), 146-154 (2010)
8. Bustince, H., Barrenechea, E., Pagola, M.: Image Thresholding using Restricted Equiv-
alence Functions and Maximizing the Measures of Similarity. Fuzzy Sets and Sys-
tems 158(5), 496-516 (2007)
9. Bustince, H., Pagola, M., Barrenechea, E., Fernandez, J., Melo-Pinto, P., Couto, P.,
Tizhoosh, H.R., Montero, J.: Ignorance Functions. An application to the Calculation of
the Threshold in Prostate Ultrasound Images. Fuzzy Sets and Systems 161(1), 20-36
(2010)
10. Chaira, T.: Intuitionistic Fuzzy Segmentation of Medical Images. IEEE Transactions on
Biomedical Engineering 57(6), 1430-1436 (2010)
11. Costin, H., Rotariu, C.: Medical Image Analysis and Representation Using a Fuzzy and
Rule-based Hybrid Approach. International Journal of Computers, Communications &
Control 1(suppl. S), 156-162 (2006)
12. Couto, P., Filipe, V., Melo-Pinto, P., Bustince, H., Barrenechea, E.: A A-IFSs Based Im-
age Segmentation Methodology for Gait Analysis. In: 2009 9th International Conference
on Intelligent Systems, Design, and Applications, pp. 1318-1323. Machine Intelligence
Res Lab., IEEE Syst. Man & Cybernetics Soc., Int Fuzzy Syst Assoc., European Neural
Network Soc., European Soc. Fuzzy Log. & Technol., World Fed. Soft. Comp,
13. Di Zenzo, S., Cinque, L., Levialdi, S.: Image Thresholding using Fuzzy Entropies.
IEEE Transactions on Systems, Man, and Cybernetics PART B-Cybernetics 28(1), 15-
23 (1998)
14. Forkert, N.D., Schmidt-Richberg, A., Fiehler, J., Illies, T., Moeller, D., Handels, H.,
Saering, D.: Fuzzy-based Vascular Structure Enhancement in Time-of-Flight MRA Im-
ages for Improved Segmentation. Methods of Information in Medicine 50(1), 74-83
(2011)
15. Guliato, D., Rangayyan, R.M., Carnielli, W.A., Zuffo, J.A., Leo Desautels, J.E.: Seg-
mentation of Breast Tumors in Mammograms Using Fuzzy Sets. Journal of Electronic
Imaging 12(3), 369-378 (2003)
16. Hasanzadeh, M., Kasaei, S.: Fuzzy Image Segmentation Using Membership Connected-
ness. Eurasip Journal on Advances in Signal Processing (November 2008)
17. He, L., Greenshields, I.R.: An MRF Spatial Fuzzy Clustering Method for fMRI SPMs.
Biomedical Signal Processing and Control 3(4), 327-333 (2008)
18. Kannan, S., Ramathilagam, S., Devi, R., Sathya, A.: Robust Kernel FCM in Segmen-
tation of Breast Medical Images. Expert Systems with Applications 38(4), 4382-4389
(2011)
19. Kannan, S., Ramathilagam, S., Sathya, A., Devi, R.: Effective Fuzzy c-means Based Ker-
nel Function in Segmenting Medical Images. Computers in Biology and Medicine 40(6),
572-579 (2010)
Search WWH ::




Custom Search