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An adaptive fuzzy C-means algorithm for image segmentation in the presence of intensity inhomogeneities.

D. Pham, und J. Prince. Pattern Recognition Letters, 20 (1): 57-68 (1999)

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L. Ahlgrimm

Lambert Theisen University of Stuttgart

Annika Liebgott

Automated reference-free assessment of MR image quality using an active learning approach: Comparison of Support Vector Machine versus Deep Neural Network classificationS. Gatidis, A. Liebgott, M. Schwartz, P. Martirosian, F. Schick, K. Nikolaou, B. Yang, und T. Küstner. Proceedings of the International Society for Magnetic Resonance in Medicine (ISMRM), Honolulu, Hawaii, USA, (April 2017)

Automated reference-free assessment of MR image quality using an active learning approach: Comparison of Support Vector Machine versus Deep Neural Network classificationS. Gatidis, A. Liebgott, M. Schwartz, P. Martirosian, F. Schick, K. Nikolaou, B. Yang, und T. Küstner. Proceedings of the International Society for Magnetic Resonance in Medicine (ISMRM), Honolulu, Hawaii, USA, (April 2017)An easy-to-use image labeling platform for automatic Magnetic Resonance Image Quality AssessmentT. Küstner, P. Wolf, M. Schwartz, A. Liebgott, F. Schick, S. Gatidis, und B. Yang. Proceedings of the IEEE International Symposium on Biomedical Imaging (ISBI), Melbourne, Australia, (April 2017)Automated image quality assessment in whole-body MRIS. Gatidis, A. Liebgott, H. Schmidt, N. Schwenzer, P. Martirosian, K. Nikolaou, F. Schick, B. Yang, und T. Küstner. Proceedings of the Radiological Society of North America (RSNA), Chicago, USA, (November 2016)

Univ. -Prof. Dr. Remco Ingmar Leine University of Stuttgart

Christian León University of Stuttgart

Weitere Publikationen von Autoren mit dem selben Namen

Automatic segmentation of white matter lesions in T1-weighted brain MR images.S. Yu, D. Pham, D. Shen, E. Herskovits, S. Resnick, und C. Davatzikos. ISBI, Seite 253-256. IEEE, (2002)Statistical and Topological Atlas Based Brain Image Segmentation.P. Bazin, und D. Pham. MICCAI (1), Volume 4791 von Lecture Notes in Computer Science, Seite 94-101. Springer, (2007)A Deep Learning Based Anti-aliasing Self Super-Resolution Algorithm for MRI.C. Zhao, A. Carass, B. Dewey, J. Woo, J. Oh, P. Calabresi, D. Reich, P. Sati, D. Pham, und J. Prince. MICCAI (1), Volume 11070 von Lecture Notes in Computer Science, Seite 100-108. Springer, (2018)Dice Overlap Measures for Objects of Unknown Number: Application to Lesion Segmentation.I. Oguz, A. Carass, D. Pham, S. Roy, N. Subbana, P. Calabresi, P. Yushkevich, R. Shinohara, und J. Prince. BrainLes@MICCAI, Volume 10670 von Lecture Notes in Computer Science, Seite 3-14. Springer, (2017)Topology-Preserving Tissue Classification of Magnetic Resonance Brain Images.P. Bazin, und D. Pham. IEEE Trans. Med. Imaging, 26 (4): 487-496 (2007)Topology correction of segmented medical images using a fast marching algorithm.P. Bazin, und D. Pham. Computer Methods and Programs in Biomedicine, 88 (2): 182-190 (2007)Adaptive fuzzy c-means algorithm for image segmentation in the presence of intensity inhomogeneities.D. Pham, und J. Prince. Medical Imaging: Image Processing, Volume 3338 von SPIE Proceedings, SPIE, (1998)Robust Fuzzy Segmentation of Magnetic Resonance Images.D. Pham. CBMS, Seite 127-131. IEEE Computer Society, (2001)Robust skull stripping using multiple MR image contrasts insensitive to pathology.S. Roy, J. Butman, und D. Pham. NeuroImage, (2017)Edge-Adaptive Clustering for Unsupervised Image Segmentation.D. Pham. ICIP, Seite 816-819. (2000)