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Hierarchical Conditional Random Fields for Detection of Gad-Enhancing Lesions in Multiple Sclerosis.

Z. Karimaghaloo, D. Arnold, D. Collins, and T. Arbel. MICCAI (2), volume 7511 of Lecture Notes in Computer Science, page 379-386. Springer, (2012)

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L. Ahlgrimm

Prof. Dr. Ulli Arnold University of Stuttgart

Dr. -Ing. Eckhard Arnold University of Stuttgart

Seraphine Arnold University of Stuttgart

Univ. -Prof. Dr. -Ing. Arnold Kistner University of Stuttgart

Other publications of authors with the same name

Improved Precision in the Measurement of Longitudinal Global and Regional Volumetric Changes via a Novel MRI Gradient Distortion Characterization and Correction Technique.V. Fonov, A. Janke, Z. Caramanos, D. Arnold, S. Narayanan, G. Pike, and D. Collins. MIAR, volume 6326 of Lecture Notes in Computer Science, page 324-333. Springer, (2010)Prediction of Disease Progression in Multiple Sclerosis Patients using Deep Learning Analysis of MRI Data.A. Tousignant, P. Lemaître, D. Precup, D. Arnold, and T. Arbel. MIDL, volume 102 of Proceedings of Machine Learning Research, page 483-492. PMLR, (2019)Optimal Gaussian Mixture Models of Tissue Intensities in Brain MRI of Patients with Multiple-Sclerosis.Y. Xiao, M. Shah, S. Francis, D. Arnold, T. Arbel, and D. Collins. MLMI, volume 6357 of Lecture Notes in Computer Science, page 165-173. Springer, (2010)Cortical Surface Analysis of Multi-contrast MR Data to Improve Detection of Cortical Pathology in Multiple Sclerosis.M. Archambault-Wallenburg, D. Arnold, S. Narayanan, G. Pike, and D. Collins. MBIA, volume 8159 of Lecture Notes in Computer Science, page 138-149. Springer, (2013)IMaGe: Iterative Multilevel Probabilistic Graphical Model for Detection and Segmentation of Multiple Sclerosis Lesions in Brain MRI.N. Subbanna, D. Precup, D. Arnold, and T. Arbel. IPMI, volume 9123 of Lecture Notes in Computer Science, page 514-526. Springer, (2015)A Generative Model for Automatic Detection of Resolving Multiple Sclerosis Lesions.C. Elliott, D. Arnold, D. Collins, and T. Arbel. BAMBI, volume 8677 of Lecture Notes in Computer Science, page 118-129. Springer, (2014)Automatic Detection of Gadolinium-Enhancing Multiple Sclerosis Lesions in Brain MRI Using Conditional Random Fields.Z. Karimaghaloo, M. Shah, S. Francis, D. Arnold, D. Collins, and T. Arbel. IEEE Trans. Med. Imaging, 31 (6): 1181-1194 (2012)Estimating and accounting for the effect of MRI scanner changes on longitudinal whole-brain volume change measurements.H. Lee, K. Nakamura, S. Narayanan, R. Brown, and D. Arnold. NeuroImage, (2019)Corrigendum to "Gradient distortions in MRI: Characterizing and correcting for their effects on SIENA-generated measures of brain volume change" NeuroImage 49 (2010) 1601-1611.Z. Caramanos, V. Fonov, S. Francis, S. Narayanan, G. Pike, D. Collins, and D. Arnold. NeuroImage, 49 (4): 3498 (2010)No-reference quality measure in brain MRI images using binary operations, texture and set analysis.M. Osadebey, M. Pedersen, D. Arnold, and K. Wendel-Mitoraj. IET Image Processing, 11 (9): 672-684 (2017)