Fetching the paper…
Reading the bibliography…
Multi-atlas segmentation is a widely used tool in medical image analysis, providing robust and accurate results by learning from annotated atlas datasets.
S. Li, “Markov random field models in computer vision,” in ECCV , 1994, pp. 361–70
1994
Earlier work this paper cites.
D. Rueckert, L. I. Sonoda, C. Hayes, D. L. G. Hill, M. O. Leach, and D. J. Hawkes, “Nonrigid registration using free-form deformations: application to breast MR images,” IEEE Trans Med Imag , vol. 18, no. 8, pp. 712–21, 1999
1999
Earlier work this paper cites.
L. G. Nyúl and J. K. Udupa, “On standardizing the MR image intensity scale.” Magn Reson Med , vol. 42, no. 6, pp. 1072–81, 1999
1999
Earlier work this paper cites.
Y. Boykov and M. Jolly, “Interactive organ segmentation using graph cuts,” in MICCAI , 2000, pp. 276–86
2000
Earlier work this paper cites.
Y. Boykov, O. Veksler, and R. Zabih, “Fast approximate energy minimization via graph cuts,” IEEE Trans PAMI , vol. 23, no. 11, pp. 1222–39, 2001
2001
Earlier work this paper cites.
T. Rohlfing, R. Brandt, R. Menzel, and C. R. Maurer, “Evaluation of atlas selection strategies for atlas-based image segmentation with application to confocal microscopy images of bee brains.” NeuroImage , vol. 21, no. 4, pp. 1428–42, 2004
2004
Earlier work this paper cites.
S. K. Warfield, K. H. Zou, and W. M. Wells, “Simultaneous truth and performance level estimation (STAPLE): an algorithm for the validation of image segmentation.” IEEE Trans Med Imag , vol. 23, no. 7, pp. 903–21, 2004
2004
Earlier work this paper cites.
C. Rother, V. Kolmogorov, and A. Blake, “Grabcut: Interactive foreground extraction using iterated graph cuts,” ACM T Graphic , vol. 23, no. 3, pp. 309–14, 2004
2004
Earlier work this paper cites.
V. Kolmogorov and R. Zabin, “What energy functions can be minimized via graph cuts?” IEEE Trans PAMI , vol. 26, no. 2, pp. 147–59, 2004
2004
Earlier work this paper cites.
A. Chambolle, “An algorithm for total variation minimization and applications,” J Math Imaging Vis , vol. 20, no. 2, pp. 89–97, 2004
2004
Earlier work this paper cites.
A. Klein, B. Mensh, S. Ghosh, J. Tourville, and J. Hirsch, “Mindboggle: automated brain labeling with multiple atlases.” BMC medical imaging , vol. 5, p. 7, 2005
2005
Earlier work this paper cites.
R. A. Heckemann, J. V. Hajnal, P. Aljabar, D. Rueckert, and A. Hammers, “Automatic anatomical brain MRI segmentation combining label propagation and decision fusion,” NeuroImage , vol. 33, no. 1, pp. 115–26, 2006
2006
Earlier work this paper cites.
P. A. Yushkevich, J. Piven, H. C. Hazlett, R. G. Smith, S. Ho, J. C. Gee, and G. Gerig, “User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability,” NeuroImage , vol. 31, no. 3, pp. 1116–28, 2006
2006
Earlier work this paper cites.
C. R. Jack, M. Bernstein, N. C. Fox, P. Thompson, G. Alexander, D. Harvey, B. Borowski, P. Britson, J. Whitwell, C. Ward, A. Dale, J. Felmlee, J. Gunter, D. Hill, R. Killiany, N. Schuff, S. Fox-Bosetti, C. Lin, C. Studholme, C. DeCarli, G. Krueger, H. Ward, G. Metzger, K. Scott, R. Mallozzi, D. Blezek, J. Levy, J. Debbins, A. Fleisher, M. Albert, R. Green, G. Bartzokis, G. Glover, J. Mugler, and M. Weiner, “The Alzheimer’s Disease Neuroimaging Initiative (ADNI): MRI methods,” Magn Reson Im , vol. 27, no. 4, pp. 685–91, 2008
2008
Earlier work this paper cites.
F. van der Lijn, T. den Heijer, M. Breteler, and W. J. Niessen, “Hippocampus segmentation in MR images using atlas registration, voxel classification, and graph cuts.” NeuroImage , vol. 43, no. 4, pp. 708–20, 2008
2008
Earlier work this paper cites.
X. Artaechevarria, A. Munoz-Barrutia, and C. Ortiz-de Solórzano, “Combination strategies in multi-atlas image segmentation: Application to brain MR data,” IEEE Trans Med Imag , vol. 28, no. 8, pp. 1266–77, 2009
2009
Cited alongside, same era.
P. Aljabar, R. A. Heckemann, A. Hammers, J. V. Hajnal, and D. Rueckert, “Multi-atlas based segmentation of brain images: atlas selection and its effect on accuracy.” NeuroImage , vol. 46, no. 3, pp. 726–38, 2009
2009
Cited alongside, same era.
R. Wolz, P. Aljabar, J. V. Hajnal, A. Hammers, and D. Rueckert, “LEAP: learning embeddings for atlas propagation.” NeuroImage , vol. 49, no. 2, pp. 1316–25, 2010
2010
Cited alongside, same era.
M. R. Sabuncu, B. T. T. Yeo, K. Van Leemput, B. Fischl, and P. Golland, “A generative model for image segmentation based on label fusion,” IEEE Trans Med Imag , vol. 29, no. 10, pp. 1714–29, 2010
2010
Cited alongside, same era.
W. Bai, W. Shi, D. P. O’Regan, T. Tong, H. Wang, S. Jamil-Copley, N. S. Peters, and D. Rueckert, “A probabilistic patch-based label fusion model for multi-atlas segmentation with registration refinement: application to cardiac MR images.” IEEE Trans Med Imag , vol. 32, no. 7, pp. 1302–15, 2013
2013
Later among the works it cites.
R. Wolz, C. Chu, and K. Misawa, “Automated abdominal multi-organ segmentation with subject-specific atlas generation,” IEEE Trans Med Imag , vol. 32, no. 9, pp. 1723–1730, 2013
2013
Later among the works it cites.
A. Makropoulos, I. S. Gousias, C. Ledig, P. Aljabar, A. Serag, J. V. Hajnal, D. Edwards, S. J. Counsell, and D. Rueckert, “Automatic whole brain MRI segmentation of the developing neonatal brain.” IEEE Trans Med Imag , vol. 33, no. 9, pp. 1818–31, 2014
2014
Later among the works it cites.
L. M. Koch, R. Wright, D. Vatansever, V. Kyriakopoulou, C. Malamateniou, P. A. Patkee, M. A. Rutherford, J. V. Hajnal, P. Aljabar, and D. Rueckert, “Graph-Based Label Propagation in Fetal Brain MR Images,” in MLMI . Springer, 2014, pp. 9–16
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
J. M. Lötjönen, R. Wolz, J. R. Koikkalainen, L. Thurfjell, G. Waldemar, H. Soininen, and D. Rueckert, “Fast and robust multi-atlas segmentation of brain magnetic resonance images.” NeuroImage , vol. 49, no. 3, pp. 2352–65, 2010
2010
Cited alongside, same era.
J. Yuan, E. Bae, and X. Tai, “A study on continuous max-flow and min-cut approaches,” in CVPR , 2010, pp. 2217–24
2010
Cited alongside, same era.
J. Yuan, E. Bae, X. Tai, and Y. Boykov, “A continuous max-flow approach to potts model,” in ECCV , 2010, pp. 379–92
2010
Cited alongside, same era.
P. Coupé, J. V. Manjón, V. Fonov, J. Pruessner, M. Robles, and D. L. Collins, “Patch-based segmentation using expert priors: application to hippocampus and ventricle segmentation.” NeuroImage , vol. 54, no. 2, pp. 940–54, 2011
2011
Cited alongside, same era.
F. Rousseau, “A supervised patch-based approach for human brain labeling,” IEEE Trans Med Imag , vol. 30, no. 10, pp. 1852–62, 2011
2011
Cited alongside, same era.
D. Han, J. Bayouth, Q. Song, and A. Taurani, “Globally optimal tumor segmentation in PET-CT images: A graph-based co-segmentation method,” in IPMI , 2011, pp. 245–56
2011
Cited alongside, same era.
H. Wang, J. Suh, S. Das, J. Pluta, C. Craige, and P. Yushkevich, “Multi-Atlas Segmentation with Joint Label Fusion.” IEEE Trans PAMI , vol. 35, no. 3, pp. 611–23, 2012
2012
Cited alongside, same era.
D. Kuettel, M. Guillaumin, and V. Ferrari, “Segmentation propagation in ImageNet,” in ECCV , ser. LNCS, vol. 7578. Springer, 2012, pp. 459–73
2012
Cited alongside, same era.
2014
Later among the works it cites.
L.-C. Chen, S. Fidler, A. L. Yuille, and R. Urtasun, “Beat the MTurkers: Automatic Image Labeling from Weak 3D Supervision,” in CVPR . IEEE, 2014, pp. 3198–3205
2014
Later among the works it cites.
J. Xu, A. G. Schwing, and R. Urtasun, “Tell Me What You See and I will Show You Where It Is,” in CVPR . IEEE, 2014, pp. 3190–97
2014
Later among the works it cites.
W. Qiu, J. Yuan, E. Ukwatta, Y. Sun, M. Rajchl, and A. Fenster, “Prostate Segmentation: An Efficient Convex Optimization Approach with Axial Symmetry Using 3D TRUS and MR Images,” IEEE Trans Med Imag , vol. 33, no. 4, pp. 947–60, 2014
2014
Later among the works it cites.
Z. Wang, K. K. Bhatia, B. Glocker, A. Marvao, T. Dawes, K. Misawa, K. Mori, and D. Rueckert, “Geodesic patch-based segmentation,” in MICCAI , vol. 8673, 2014, pp. 666–673
2014
Later among the works it cites.
J. E. Iglesias and M. R. Sabuncu, “Multi-Atlas Segmentation of Biomedical Images: A Survey,” Med Image Anal , vol. 24, no. 1, pp. 205–219, 2015
2015
Later among the works it cites.
J. E. Iglesias, M. R. Sabuncu, I. Aganj, P. Bhatt, C. Casillas, D. Salat, A. Boxer, B. Fischl, and K. Van Leemput, “An algorithm for optimal fusion of atlases with different labeling protocols,” NeuroImage , vol. 106, pp. 451–63, 2015
2015
Later among the works it cites.
C. Ledig, R. a. Heckemann, A. Hammers, J. C. Lopez, V. F. J. Newcombe, A. Makropoulos, J. Lötjönen, D. K. Menon, and D. Rueckert, “Robust whole-brain segmentation: application to traumatic brain injury.” Med Image Anal , vol. 21, no. 1, pp. 40–58, 2015
2015
Later among the works it cites.
M. J. Cardoso, M. Modat, R. Wolz, A. Melbourne, D. Cash, D. Rueckert, and S. Ourselin, “Geodesic Information Flows: Spatially-Variant Graphs and Their Application to Segmentation and Fusion,” IEEE Trans Med Imag , pp. 1976–88, 2015
2015
Later among the works it cites.
J. Xu, A. G. Schwing, and R. Urtasun, “Learning to Segment Under Various Forms of Weak Supervision,” in CVPR . IEEE, 2015, pp. 3781–90
2015
Later among the works it cites.
L. M. Koch, M. Rajchl, T. Tong, J. Passerat-palmbach, P. Aljabar, and D. Rueckert, “Multi-atlas Segmentation as a Graph Labelling Problem: Application to Partially Annotated Atlas Data,” in IPMI , vol. 9123, 2015, pp. 221–232
2015
Later among the works it cites.