21.9.7.3 Brain, Cortex, MRI Segmentation

Gerig, G.[Guido], Martin, J.[John], Kikinis, R.[Ron], Kubler, O.[Olaf], Shenton, M.[Martha], Jolesz, F.A.[Ferenc A.],
Unsupervised tissue type segmentation of 3D dual-echo MR head data,
IVC(10), No. 6, July-August 1992, pp. 349-360.
Elsevier DOI 0401
BibRef

Joliot, M., and Mazoyer, B.M.,
Three-Dimensional Segmentation and Interpolation of Magnetic Resonance Brain Images,
MedImg(12), No. 2, June 1993, pp. 269-277.
IEEE Top Reference. BibRef 9306

Worth, A.J., Kennedy, D.N.,
Segmentation of Magnetic-Resonance Brain Images Using Analog Constraint Satisfaction Neural Networks,
IVC(12), No. 6, July-August 1994, pp. 345-354.
Elsevier DOI BibRef 9407

Tsai, C., Manjunath, B.S., Jagadeesan, R.,
Automated Segmentation of Brain MR-Images,
PR(28), No. 12, December 1995, pp. 1825-1837.
Elsevier DOI BibRef 9512

Li, X.H.[Xiao-Hong], Bhide, S., Kabuka, M.R.,
Labeling of MR brain images using Boolean neural network,
MedImg(15), No. 5, October 1996, pp. 628-638.
IEEE Top Reference. 0203
BibRef

Wells, III, W.M., Grimson, W.E.L., Kikinis, R., Jolesz, F.A.,
Adaptive segmentation of MRI data,
MedImg(15), No. 4, August 1996, pp. 429-442.
IEEE Top Reference.
PDF File. 0203
BibRef
Earlier: CVRMed95(XX-YY) Segmentation.
See also Automatic Registration Method for Frameless Stereotaxy, Image Guided Surgery and Enhanced Reality Visualization, An. BibRef

Kapur, T.[Tina], Grimson, W.E.L., Kikinis, R.,
Segmentation of Brain Tissue from MR Images,
MIA(1), No. 2, 1996, pp. 109-127.
PDF File. BibRef 9600 CVRMed95(XX-YY) BibRef
Earlier: A1 Only: MIT AI-TR-1566, January 1995.
WWW Link. BibRef

Rajapakse, J.C., Giedd, J.N., Rapoport, J.L.,
Statistical approach to segmentation of single-channel cerebral MR images,
MedImg(16), No. 2, April 1997, pp. 176-186.
IEEE Top Reference. 0205
BibRef

Rajapakse, J.C., Kruggel, F.,
Segmentation of MR-Images With Intensity Inhomogeneities,
IVC(16), No. 3, March 16 1998, pp. 165-180.
Elsevier DOI 9804
BibRef

Held, K., Kops, E.R., Krause, B.J., Wells, W.M., Kikinis, R., Müller-Gartner, H.W.,
Markov Random-Field Segmentation of Brain MR-Images,
MedImg(16), No. 6, December 1997, pp. 878-886.
IEEE Top Reference. 9803
BibRef

Soltanian-Zadeh, H.[Hamid], and Windham, J.P.[Joe P.],
A multiresolution approach for contour extraction from brain images,
MedPhys(24), No. 12, December 1997, pp. 1844-1853. BibRef 9712
And:
Computerized Analysis of Magnetic Resonance Images,
SCIA97(xx-yy)
HTML Version. 9705
BibRef

Atkins, M.S., Mackiewich, B.T.,
Fully-Automatic Segmentation of the Brain in MRI,
MedImg(17), No. 1, February 1998, pp. 98-107.
IEEE Top Reference. 9806
BibRef

Worth, A.J., Makris, N., Patti, M.R., Goodman, J.M., Hoge, E.A., Caviness, V.S., Kennedy, D.N.,
Precise Segmentation of the Lateral Ventricles and Caudate-Nucleus in MR Brain Images Using Anatomically Driven Histograms,
MedImg(17), No. 2, April 1998, pp. 303-310.
IEEE Top Reference. 9808
BibRef

Wang, Y., Adali, T., Kung, S.Y., Szabo, Z.,
Quantification and Segmentation of Brain Tissues from MR-Images: A Probabilistic Neural Network Approach,
IP(7), No. 8, August 1998, pp. 1165-1181.
IEEE DOI 9808
BibRef

Xuan, J.H.[Jian-Hua], Adali, T., Wang, Y.[Yue],
Segmentation of magnetic resonance brain image: Integrating region growing and edge detection,
ICIP95(III: 544-547).
IEEE DOI 9510
BibRef

Niessen, W.J., Vincken, K.L., Weickert, J.A., ter Haar Romeny, B.M., Viergever, M.A.,
Multiscale Segmentation of Three-Dimensional MR Brain Images,
IJCV(31), No. 2/3, April 1999, pp. 185-202.
DOI Link BibRef 9904

van der Lijn, F., de Bruijne, M., Klein, S., den Heijer, T., Hoogendam, Y.Y., van der Lugt, A., Breteler, M.M.B., Niessen, W.J.,
Automated Brain Structure Segmentation Based on Atlas Registration and Appearance Models,
MedImg(31), No. 2, February 2012, pp. 276-286.
IEEE DOI 1202
BibRef

Niessen, W.J.[Wiro J.], Vincken, K.L.[Koen L.], Weickert, J.A.[Joachim A.], and Viergever, M.A.[Max A.],
Three Dimensional MR Brain Segmentation,
ICCV98(53-58).
IEEE DOI BibRef 9800

Schultz, T.[Thomas], Burgeth, B.[Bernhard], Weickert, J.A.[Joachim A.],
Flexible Segmentation and Smoothing of DT-MRI Fields Through a Customizable Structure Tensor,
ISVC06(I: 455-464).
Springer DOI 0611
BibRef

Simmons, A.[Andrew], Jones, D.K.[Derek K.], Horsfield, M.A.[Mark A.], Williams, S.C.R.[Steven C.R.],
Application of diffusion tensor MRI to neurological segmentation,
IJIST(10), No. 3, 1999, pp. 273-286. BibRef 9900

Zeng, X.L.[Xiao-Lan], Staib, L.H.[Lawrence H.], Schultz, R.T.[Robert T.], and Duncan, J.S.[James S.],
Segmentation and Measurement of the Cortex from 3-D MR Images Using Coupled-Surfaces Propagation,
MedImg(18), No. 10, October 1999, pp. 927-937.
IEEE Top Reference. BibRef 9910
Earlier:
Volumetric Layer Segmentation Using Coupled Surfaces Propagation,
CVPR98(708-715).
IEEE DOI From CT Slices. Couple the surfaces to prevent going too far -- extracting the cortex layer from images. BibRef

Hata, Y., Kobashi, S., Hirano, S., Kitagaki, H., Mori, E.,
Automated Segmentation of Human Brain MR Images Aided by Fuzzy Information Granulation and Fuzzy Inference,
SMC-C(30), No. 3, August 2000, pp. 381.
IEEE Top Reference. 0011
BibRef

Hirano, S., Kamiura, N., Hata, Y., and Ishikawa, M.,
MAGNET: An Active Ditch Extraction Model,
ICIP97(II: 124-127).
IEEE DOI BibRef 9700

Xue, J.H.[Jing-Hao], Ruan, S.[Su], Moretti, B.[Bruno], Revenu, M.[Marinette], Bloyet, D.[Daniel],
Knowledge-based segmentation and labeling of brain structures from MRI images,
PRL(22), No. 3-4, March 2001, pp. 395-405.
Elsevier DOI 0105
BibRef

Dou, W.[Weibei], Ruan, S.[Su], Chen, Y.P.[Yan-Ping], Bloyet, D.[Daniel], Constans, J.M.[Jean-Marc],
A framework of fuzzy information fusion for the segmentation of brain tumor tissues on MR images,
IVC(25), No. 2, February 2007, pp. 164-171.
Elsevier DOI 0701
Fuzzy; Information fusion; Segmentation; Brain tumor; MRI BibRef

Ruan, S., Jaggi, C., Xue, J., Fadili, J., Bloyet, D.,
Brain tissue classification of magnetic resonance images using partial volume modeling,
MedImg(19), No. 12, December 2000, pp. 1179-1187.
IEEE Top Reference. 0110
BibRef

Ruan, S.[Su], Moretti, B.[Bruno], Fadili, J.[Jalal], Bloyet, D.[Daniel],
Fuzzy Markovian Segmentation in Application of Magnetic Resonance Images,
CVIU(85), No. 1, January 2002, pp. 54-69.
DOI Link 0210
BibRef
Earlier:
Segmentation of Magnetic Resonance Images Using Fuzzy Markov Random Fields,
ICIP01(III: 1051-1054).
IEEE DOI 0108
BibRef

Bailleul, J., Ruan, S.[Su], Bloyet, D., Romaniuk, B.,
Segmentation of anatomical structures from 3D brain MRI using automatically-built statistical shape models,
ICIP04(IV: 2741-2744).
IEEE DOI 0505
BibRef

Ruan, S., Jaggi, C., Constans, J.M., Bloyet, D.,
Detection of Brain Activation from MRI Data by Likelihood-Ratio Test,
CVRMed95(XX-YY) BibRef 9500

van Leemput, K., Maes, F.[Frederik], Vandermeulen, D.[Dirk], Suetens, P.[Paul],
Automated model-based bias field correction of MR images of the brain,
MedImg(18), No. 10, October 1999, pp. 885-896.
IEEE Top Reference. 0110
BibRef

van Leemput, K., Maes, F.[Frederik], Vandermeulen, D.[Dirk], Suetens, P.[Paul],
A unifying framework for partial volume segmentation of brain MR images,
MedImg(22), No. 1, January 2003, pp. 105-119.
IEEE Top Reference. 0304
BibRef

van Leemput, K., Maes, F.[Frederik], Vandermeulen, D.[Dirk], Suetens, P.[Paul],
Automated model-based tissue classification of MR images of the brain,
MedImg(18), No. 10, October 1999, pp. 897-908.
IEEE Top Reference. 0110
BibRef

Moon, N., Bullitt, E., van Leemput, K., Gerig, G.,
Model-based brain and tumor segmentation,
ICPR02(I: 528-531).
IEEE DOI 0211
BibRef

Ribbens, A.[Annemie], Maes, F.[Frederik], Vandermeulen, D.[Dirk], Suetens, P.[Paul],
Semisupervised Probabilistic Clustering of Brain MR Images Including Prior Clinical Information,
MCV10(184-194).
Springer DOI 1009
BibRef

van Leemput, K.,
Encoding Probabilistic Brain Atlases Using Bayesian Inference,
MedImg(28), No. 6, June 2009, pp. 822-837.
IEEE DOI 0906
BibRef

Dawant, B.M., Hartmann, S.L., Thirion, J.P., Maes, F., Vandermeulen, D., Demaerel, P.,
Automatic 3-D segmentation of internal structures of the head in MR images using a combination of similarity and free-form transformations. I. Methodology and validation on normal subjects,
MedImg(18), No. 10, October 1999, pp. 909-916.
IEEE Top Reference. 0110
BibRef

Hartmann, S.L., Parks, M.H., Martin, P.R., Dawant, B.M.,
Automatic 3-D segmentation of internal structures of the head in MR images using a combination of similarity and free-form transformations. II. Validation on severely atrophied brains,
MedImg(18), No. 10, October 1999, pp. 917-926.
IEEE Top Reference. 0110
BibRef

Zhang, Y., Brady, J.M., Smith, S.M.,
Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm,
MedImg(20), No. 1, January 2001, pp. 45-57.
IEEE Top Reference. 0110
BibRef

Barra, V., Boire, J.Y.,
Automatic segmentation of subcortical brain structures in MR images using information fusion,
MedImg(20), No. 7, July 2001, pp. 549-558.
IEEE Top Reference. 0110
BibRef

Marroquin, J.L., Vemuri, B.C., Botello, S., Calderon, F., Fernandez-Bouzas, A.,
An Accurate and Efficient Bayesian Method for Automatic Segmentation of Brain MRI,
MedImg(21), No. 8, August 2002, pp. 934-945.
IEEE Top Reference. 0301
BibRef
Earlier: A1, A2, A3, A4 only: ECCV02(IV: 560 ff.).
Springer DOI 0205
BibRef

Pitiot, A.[Alain], Toga, A.W., Thompson, P.M.[Paul M.],
Adaptive elastic segmentation of brain MRI via shape-model-guided evolutionary programming,
MedImg(21), No. 8, August 2002, pp. 910-923.
IEEE Top Reference. 0301

See also Learning Shape Correspondence for n-D curves. BibRef

Shi, Y.G.[Yong-Gang], Li, J.N.[Jun-Ning], Toga, A.W.[Arthur W.],
Persistent Reeb Graph Matching for Fast Brain Search,
MLMI14(306-313).
Springer DOI 1410
BibRef

Lai, R.J.[Rong-Jie], Shi, Y.G.[Yong-Gang], Sicotte, N.[Nancy], Toga, A.W.[Arthur W.],
Automated corpus callosum extraction via Laplace-Beltrami nodal parcellation and intrinsic geodesic curvature flows on surfaces,
ICCV11(2034-2040).
IEEE DOI 1201
BibRef

Pitiot, A.[Alain], Bardinet, É.[Éric], Thompson, P.M.[Paul M.], Malandain, G.[Grégoire],
Automated Piecewise Affine Registration of Biological Images,
INRIARR-4866, 2003.
HTML Version. BibRef 0300

Xu, M., Thompson, P.M., Toga, A.W.,
An Adaptive Level Set Segmentation on a Triangulated Mesh,
MedImg(23), No. 2, February 2004, pp. 191-201.
IEEE Abstract. 0403
Boundaries of complex structures. BibRef

Xu, M., Thompson, P.M., Toga, A.W.,
Adaptive Reproducing Kernel Particle Method for Extraction of the Cortical Surface,
MedImg(25), No. 6, June 2006, pp. 755-767.
IEEE DOI 0606
BibRef

Kwon, M.J., Han, Y.J., Shin, I.H., Park, H.W.,
Hierarchical fuzzy segmentation of brain MR images,
IJIST(13), No. 2, 2003, pp. 115-125.
WWW Link. 0308
BibRef

Xue, J.H.[Jing-Hao], Pizurica, A.[Aleksandra], Philips, W.[Wilfried], Kerre, E.[Etienne], van de Walle, R.[Rik], Lemahieu, I.[Ignace],
An integrated method of adaptive enhancement for unsupervised segmentation of MRI brain images,
PRL(24), No. 15, November 2003, pp. 2549-2560.
Elsevier DOI 0308
BibRef

Dokládal, P.[Petr], Bloch, I.[Isabelle], Couprie, M.[Michel], Ruijters, D.[Daniel], Urtasun, R.[Raquel], Garnero, L.[Line],
Topologically controlled segmentation of 3D magnetic resonance images of the head by using morphological operators,
PR(36No. 10, October 2003, pp. 2463-2478.
Elsevier DOI 0308
BibRef

Moussaoui, A.[Abdelouahab], Benmahammed, K.[Khier], Ferahta, N.[Nabila], Chen, V.,
A New MR Brain Image Segmentation Using an Optimal Semi-supervised Fuzzy C-means and pdf Estimation,
ELCVIA(5), No. 4, 2005, pp. 1-11.
WWW Link. 0601
BibRef

Siyal, M.Y., Yu, L.[Lin],
An intelligent modified fuzzy c-means based algorithm for bias estimation and segmentation of brain MRI,
PRL(26), No. 13, 1 October 2005, pp. 2052-2062.
Elsevier DOI 0509
BibRef

Jimenez-Alaniz, J.R., Medina-Banuelos, V., Yanez-Suarez, O.,
Data-Driven Brain MRI Segmentation Supported on Edge Confidence and A Priori Tissue Information,
MedImg(25), No. 1, January 2006, pp. 74-83.
IEEE DOI 0601
BibRef

Ramirez-Manzanares, A.[Alonso], Rivera, M.[Mariano],
Basis Tensor Decomposition for Restoring Intra-Voxel Structure and Stochastic Walks for Inferring Brain Connectivity in DT-MRI,
IJCV(69), No. 1, August 2006, pp. 77-92.
Springer DOI 0606
Diffusion Tensor Magnetic Resonance Imaging BibRef

Kobashi, S., Fujiki, Y., Matsui, M., Inoue, N., Kondo, K., Hata, Y., Sawada, T.,
Interactive Segmentation of the Cerebral Lobes With Fuzzy Inference in 3T MR Images,
SMC-B(36), No. 1, February 2006, pp. 74-86.
IEEE DOI 0602
BibRef

Lenglet, C.[Christophe], Rousson, M.[Mikaël], Deriche, R.[Rachid],
DTI Segmentation by Statistical Surface Evolution,
MedImg(25), No. 6, June 2006, pp. 685-700.
IEEE DOI 0606
BibRef
Earlier: INRIARR-5843, 2006.
HTML Version. BibRef

Descoteaux, M.[Maxime], Deriche, R.[Rachid],
High Angular Resolution Diffusion MRI Segmentation Using Region-Based Statistical Surface Evolution,
JMIV(33), No. 2, February 2009, pp. xx-yy.
Springer DOI 0903
BibRef

Descoteaux, M.[Maxime], Angelino, E.[Elaine], Fitzgibbons, S.[Shaun], Deriche, R.[Rachid],
Apparent Diffusion Coefficients from High Angular Resolution Diffusion Images: Estimation and Applications,
INRIARR-5681, 2005.
HTML Version. MRI white matter analysis. BibRef 0500

Lenglet, C.[Christophe], Rousson, M.[Mikaël], Deriche, R.[Rachid], Faugeras, O.D.[Olivier D.],
Statistics on the Manifold of Multivariate Normal Distributions: Theory and Application to Diffusion Tensor MRI Processing,
JMIV(25), No. 3, October 2006, pp. 423-444.
Springer DOI 0611
BibRef
Earlier:
Toward Segmentation of 3D Probability Density Fields by Surface Evolution: Application to Diffusion MRI,
INRIARR-5243, 2004.
HTML Version. BibRef
And:
Statistics on Multivariate Normal Distributions: A Geometric Approach and its Application to Diffusion Tensor MRI,
INRIARR-5242, 2004.
HTML Version. BibRef

Lenglet, C.[Christophe], Deriche, R.[Rachid], Faugeras, O.D.[Olivier D.],
Inferring White Matter Geometry from Diffusion Tensor MRI: Application to Connectivity Mapping,
ECCV04(Vol IV: 127-140).
Springer DOI 0405
BibRef

Greenspan, H., Ruf, A., Goldberger, J.,
Constrained Gaussian mixture model framework for automatic segmentation of MR brain images,
MedImg(25), No. 9, September 2006, pp. 1233-1245.
IEEE DOI 0609
BibRef

Ibrahim, M., John, N., Kabuka, M.R., Younis, A.A.,
Hidden Markov models-based 3D MRI brain segmentation,
IVC(24), No. 10, 1 October 2006, pp. 1065-1079.
Elsevier DOI 0609
Hidden Markov Models; Image segmentation; Medical imaging BibRef

Han, X.[Xiao], Fischl, B.[Bruce],
Atlas Renormalization for Improved Brain MR Image Segmentation Across Scanner Platforms,
MedImg(26), No. 4, April 2007, pp. 479-486.
IEEE DOI 0704
BibRef

Bazin, P.L.[Pierre-Louis], Pham, D.L.[Dzung L.],
Topology-Preserving Tissue Classification of Magnetic Resonance Brain Images,
MedImg(26), No. 4, April 2007, pp. 487-496.
IEEE DOI 0704
BibRef

Roy, S., Carass, A.[Aaron], Prince, J.L.[Jerry L.],
Magnetic Resonance Image Example-Based Contrast Synthesis,
MedImg(32), No. 12, 2013, pp. 2348-2363.
IEEE DOI 1312
Algorithm design and analysis BibRef

Liu, X.Y.[Xin-Yang], Bazin, P.L.[Pierre-Louis], Carass, A.[Aaron], Prince, J.L.[Jerry L.],
Topology Preserving Brain Tissue Segmentation Using Graph Cuts,
MMBIA12(185-190).
IEEE DOI 1203

See also Topology Correction in Brain Cortex Segmentation Using a Multiscale, Graph-Based Algorithm. BibRef

Xia, Y.[Yan], Bettinger, K.[Keith], Shen, L.[Lin], Reiss, A.L.[Allan L.],
Automatic Segmentation of the Caudate Nucleus From Human Brain MR Images,
MedImg(26), No. 4, April 2007, pp. 509-517.
IEEE DOI 0704
BibRef

Jiang, S., Xue, H., Glover, A., Rutherford, M.A., Rueckert, D., Hajnal, J.V.,
MRI of Moving Subjects Using Multislice Snapshot Images With Volume Reconstruction (SVR): Application to Fetal, Neonatal, and Adult Brain Studies,
MedImg(26), No. 7, July 2007, pp. 967-980.
IEEE DOI 0707
BibRef

Zhao, L.[Lu], Tohka, J.[Jussi], Ruotsalainen, U.[Ulla],
Accurate 3D Left-Right Brain Hemisphere Segmentation in MR Images Based on Shape Bottlenecks and Partial Volume Estimation,
SCIA07(581-590).
Springer DOI 0706
BibRef

Richard, N.[Nathalie], Dojat, M.[Michel], Garbay, C.[Catherine],
Distributed Markovian segmentation: Application to MR brain scans,
PR(40), No. 12, December 2007, pp. 3467-3480.
Elsevier DOI 0709
Hidden Markov field; Medical imaging; Neuroimaging; Multi-agent BibRef

Scherrer, B., Forbes, F., Garbay, C., Dojat, M.,
Distributed Local MRF Models for Tissue and Structure Brain Segmentation,
MedImg(28), No. 8, August 2009, pp. 1278-1295.
IEEE DOI 0909
BibRef

Barmpoutis, A.[Angelos], Vemuri, B.C.[Baba C.], Shepherd, T.M., Forder, J.R.,
Tensor Splines for Interpolation and Approximation of DT-MRI With Applications to Segmentation of Isolated Rat Hippocampi,
MedImg(26), No. 11, November 2007, pp. 1537-1546.
IEEE DOI 0709
BibRef

Liao, L.[Liang], Lin, T.S.[Tu-Sheng], Li, B.[Bi],
MRI brain image segmentation and bias field correction based on fast spatially constrained kernel clustering approach,
PRL(29), No. 10, 15 July 2008, pp. 1580-1588.
Elsevier DOI 0711
Image segmentation; Kernel-based clustering; Intensity inhomogeneities; Magnetic resonance imaging BibRef

Mayer, A., Greenspan, H.,
An Adaptive Mean-Shift Framework for MRI Brain Segmentation,
MedImg(28), No. 8, August 2009, pp. 1238-1250.
IEEE DOI 0909
BibRef

Mechouche, A., Morandi, X., Golbreich, C., Gibaud, B.,
A Hybrid System Using Symbolic and Numeric Knowledge for the Semantic Annotation of Sulco-Gyral Anatomy in Brain MRI Images,
MedImg(28), No. 8, August 2009, pp. 1165-1178.
IEEE DOI 0909
BibRef

Ronen, I.[Itamar],
Studying brain cytoarchitecture with MRI - Present, future and promises of high field,
IJIST(20), No. 1, March 2010, pp. 57-61.
DOI Link 1003
BibRef

Wu, J.[Jie], Chen, J.[Jiabi], Zhang, X.L.[Xue-Long], Chen, J.H.[Jing-Hai],
The Segmentation of Brain MR Images Using Reformative Expectation-maximization Algorithm,
IJIG(10), No. 2, April 2010, pp. 289-297.
DOI Link 1003
BibRef

Li, W., Ogunbona, P., Desilva, C., Attikiouzel, Y.,
Semi-supervised maximum a posteriori probability segmentation of brain tissues from dual-echo magnetic resonance scans using incomplete training data,
IET-IPR(5), No. 3, June 2011, pp. 222-232.
DOI Link 1105
BibRef

Jeon, S.[Seun], Yoon, U.[Uicheul], Park, J.S.[Jun-Sung], Seo, S.W.[Sang Won], Kim, J.H.[Jung-Hyun], Kim, S.T.[Sung Tae], Kim, S.I.[Sun I.], Na, D.L.[Duk L.], Lee, J.M.[Jong-Min],
Fully automated pipeline for quantification and localization of white matter hyperintensity in brain magnetic resonance image,
IJIST(21), No. 2, June 2011, pp. 193-200.
DOI Link 1101
BibRef

Caldairou, B.[Benoît], Passat, N.[Nicolas], Habas, P.A.[Piotr A.], Studholme, C.[Colin], Rousseau, F.[François],
A Non-Local Fuzzy Segmentation Method: Application to Brain MRI,
PR(44), No. 9, September 2011, pp. 1916-1927.
Elsevier DOI 1106
BibRef
Earlier: A1, A5, A2, A3, A4, Plus: Add A6: Heinrich, C.[Christian], CAIP09(606-613).
Springer DOI 0909
Fuzzy clustering; Regularisation; Non-local processing; Brain segmentation; MRI BibRef

Rousseau, F.[Francois], Habas, P.A.[Piotr A.], Studholme, C.[Colin],
Human brain labeling using image similarities,
CVPR11(1081-1088).
IEEE DOI 1106
BibRef

Chou, N., Wu, J., Bai Bingren, J., Qiu, A., Chuang, K.H.,
Robust Automatic Rodent Brain Extraction Using 3-D Pulse-Coupled Neural Networks (PCNN),
IP(20), No. 9, September 2011, pp. 2554-2564.
IEEE DOI 1109
BibRef

Ji, Z.X.[Ze-Xuan], Sun, Q.S.[Quan-Sen], Xia, D.S.[De-Shen],
Retraction notice: A framework with modified fast FCM for brain MR images segmentation,
PR(116), No. 1, August 2021, pp.
Elsevier DOI 2106
BibRef
Earlier: PR(47), No. 12, 2014, pp. 3979-.
Elsevier DOI 1410
BibRef
And: Retracted article: PR(44), No. 5, May 2011, pp. 999-1013.
Elsevier DOI 1101
BibRef

Cappabianco, F.A.M.[Fábio A.M.], Falcão, A.X.[Alexandre X.], Yasuda, C.L.[Clarissa L.], Udupa, J.K.[Jayaram K.],
Brain tissue MR-image segmentation via optimum-path forest clustering,
CVIU(116), No. 10, October 2012, pp. 1047-1059.
Elsevier DOI 1209
Brain tissue segmentation; Field inhomogeneity/bias correction; Magnetic resonance images; Graph-based methods; Medical image analysis; Segmentation evaluation; Image clustering BibRef

Cappabianco, F.A.M.[Fabio A.M.], Ide, J.S.[Jaime S.], Falcao, A.X.[Alexandre X.], Li, C.S.R.[Chiang-Shan R.],
Automatic subcortical tissue segmentation of MR images using optimum-path forest clustering,
ICIP11(2653-2656).
IEEE DOI 1201
BibRef

Chen, Y., Zhang, J., Wang, S., Zheng, Y.,
Brain magnetic resonance image segmentation based on an adapted non-local fuzzy c-means method,
IET-CV(6), No. 6, 2012, pp. 610-625.
DOI Link 1301
BibRef

Rittner, L.[Leticia], Campbell, J.S.W.[Jennifer S. W.], Freitas, P.F.[Pedro F.], Appenzeller, S.[Simone], Pike, G.B.[G. Bruce], Lotufo, R.A.[Roberto A.],
Analysis of Scalar Maps for the Segmentation of the Corpus Callosum in Diffusion Tensor Fields,
JMIV(45), No. 3, March 2013, pp. 214-226.
WWW Link. 1301
BibRef

Liu, T.M.[Tian-Ming], Hu, X.T.[Xin-Tao], Li, X.J.[Xiao-Jin], Chen, M.[Mo], Han, J.W.[Jun-Wei], Guo, L.[Lei],
Merging Neuroimaging and Multimedia: Methods, Opportunities, and Challenges,
HMS(44), No. 2, April 2014, pp. 270-280.
IEEE DOI 1404
biomedical MRI BibRef

Ji, Z.X.[Ze-Xuan], Liu, J.Y.[Jin-Yao], Cao, G.[Guo], Sun, Q.S.[Quan-Sen], Chen, Q.A.[Qi-Ang],
Robust spatially constrained fuzzy c-means algorithm for brain MR image segmentation,
PR(47), No. 7, 2014, pp. 2454-2466.
Elsevier DOI 1404
Image segmentation BibRef

Zhang, J.D.[Jing-Dan], Jiang, W.[Wuhan],
Segmentation for brain magnetic resonance images using dual-tree complex wavelet transform and spatial constrained self-organizing tree map,
IJIST(24), No. 3, 2014, pp. 208-214.
DOI Link 1408
medical image segmentation BibRef

Gupta, N.[Nidhi], Khanna, P.[Pritee],
A fast and efficient computer aided diagnostic system to detect tumor from brain magnetic resonance imaging,
IJIST(25), No. 2, 2015, pp. 123-130.
DOI Link 1506
brain tumor BibRef

Gupta, N.[Nidhi], Khanna, P.[Pritee],
A non-invasive and adaptive CAD system to detect brain tumor from T2-weighted MRIs using customized Otsu's thresholding with prominent features and supervised learning,
SP:IC(59), No. 1, 2017, pp. 18-26.
Elsevier DOI 1711
Magnetic, resonance, imaging BibRef

Adhikari, S.K.[Sudip Kumar], Sing, J.K.[Jamuna Kanta], Basu, D.K.[Dipak Kumar], Nasipuri, M.[Mita], Saha, P.K.[Punam Kumar],
A nonparametric method for intensity inhomogeneity correction in MRI brain images by fusion of Gaussian surfaces,
SIViP(9), No. 8, November 2015, pp. 1945-1954.
Springer DOI 1511
BibRef

Prabu, C., Bavithiraja, S.V.M.G., Narayanamoorthy, S.,
A novel brain image segmentation using intuitionistic fuzzy C means algorithm,
IJIST(26), No. 1, 2016, pp. 24-28.
DOI Link 1604
image segmentation BibRef

Kalavathi, P., Prasath, V.B.S.[V. B. Surya],
Automatic segmentation of cerebral hemispheres in MR human head scans,
IJIST(26), No. 1, 2016, pp. 15-23.
DOI Link 1604
cerebral hemisphere segmentation BibRef

Moeskops, P.[Pim], Viergever, M.A.[Max A.], Mendrik, A.M.[Adriënne M.], de Vries, L.S.[Linda S.], Benders, M.J.N.L.[Manon J.N.L.], Išgum, I.[Ivana],
Automatic Segmentation of MR Brain Images With a Convolutional Neural Network,
MedImg(35), No. 5, May 2016, pp. 1252-1261.
IEEE DOI 1605
Aging BibRef

Feng, C.[Chaolu], Zhao, D.[Dazhe], Huang, M.[Min],
Segmentation of longitudinal brain MR images using bias correction embedded fuzzy c-means with non-locally spatio-temporal regularization,
JVCIR(38), No. 1, 2016, pp. 517-529.
Elsevier DOI 1605
Longitudinal segmentation BibRef

Prakash, R.M.[R. Meena], Kumari, R.S.S.[R. Shantha Selva],
Fuzzy C means integrated with spatial information and contrast enhancement for segmentation of MR brain images,
IJIST(26), No. 2, 2016, pp. 116-123.
DOI Link 1606
MR brain image segmentation, fuzzy C means, spatial information BibRef

Hemanth, D.J.[D. Jude], Anitha, J., Balas, V.E.[Valentina Emilia],
Fast and accurate fuzzy C-means algorithm for MR brain image segmentation,
IJIST(26), No. 3, 2016, pp. 188-195.
DOI Link 1609
fuzzy C-means BibRef

Kwon, G.R.[Goo-Rak], Basukala, D.[Dibash], Lee, S.W.[Sang-Woong], Lee, K.H.[Kun Ho], Kang, M.[Moonsoo],
Brain image segmentation using a combination of expectation-maximization algorithm and watershed transform,
IJIST(26), No. 3, 2016, pp. 225-232.
DOI Link 1609
image segmentation BibRef

Ramasamy, U., Arulprakash, G.,
Mid-sagittal plane detection in brain magnetic resonance image based on multifractal techniques,
IET-IPR(10), No. 10, 2016, pp. 751-762.
DOI Link 1610
biomedical MRI BibRef

Wang, B.[Bo], Prastawa, M.[Marcel], Irimia, A.[Andrei], Saha, A.[Avishek], Liu, W.[Wei], Goh, S.Y.M.[S.Y. Matthew], Vespa, P.M.[Paul M.], van Horn, J.D.[John D.], Gerig, G.[Guido],
Modeling 4D pathological changes by leveraging normative models,
CVIU(151), No. 1, 2016, pp. 3-13.
Elsevier DOI 1610
Image segmentation BibRef

Prastawa, M.[Marcel], Awate, S.P.[Suyash P.], Gerig, G.[Guido],
Building spatiotemporal anatomical models using joint 4-D segmentation, registration, and subject-specific atlas estimation,
MMBIA12(49-56).
IEEE DOI 1203
BibRef

Prastawa, M.[Marcel], Gerig, G.[Guido],
Brain Lesion Segmentation through Physical Model Estimation,
ISVC08(I: 562-571).
Springer DOI 0812
BibRef

Belgrana, F.Z.[Fatima Zohra], Benamrane, N.[Nacéra],
A Fast and Robust Segmentation of Magnetic Resonance Brain Images Using a Combination of the Pyramidal Approach and Level Set Method,
IJIST(27), No. 2, 2017, pp. 182-182.
DOI Link 1706
BibRef
Earlier: IJIST(26), No. 4, 2016, pp. 243-253.
DOI Link 1701
segmentation, brain MRI, level set method, Gaussian pyramid BibRef

Saritha, S.[Saladi], Prabha, N.A.[N. Amutha],
A comprehensive review: Segmentation of MRI images: brain tumor,
IJIST(26), No. 4, 2016, pp. 295-304.
DOI Link 1701
magnetic resonance imaging, segmentation, brain tumor BibRef

Chang, H., Huang, W., Wu, C., Huang, S., Guan, C., Sekar, S., Bhakoo, K.K., Duan, Y.,
A New Variational Method for Bias Correction and Its Applications to Rodent Brain Extraction,
MedImg(36), No. 3, March 2017, pp. 721-733.
IEEE DOI 1703
Brain modeling BibRef

Rabeh, A.B.[Amira Ben], Benzarti, F.[Faouzi], Amiri, H.[Hamid],
Segmentation of brain MRI using active contour model,
IJIST(27), No. 1, 2017, pp. 3-11.
DOI Link 1704
Alzheimer disease BibRef

Yan, M.[Meng], Liu, H.[Hong], Xu, X.Y.[Xiang-Yang], Song, E.[Enmin], Qian, Y.J.[Yue-Jing], Pan, N.[Ning], Jin, R.C.[Ren-Chao], Jin, L.H.[Liang-Hai], Cheng, S.R.[Shao-Rong], Hung, C.C.[Chih-Cheng],
An improved label fusion approach with sparse patch-based representation for MRI brain image segmentation,
IJIST(27), No. 1, 2017, pp. 23-32.
DOI Link 1704
brain image segmentation BibRef

Liu, H.[Hong], Yan, M.[Meng], Song, E.[Enmin], Qian, Y.J.[Yue-Jing], Xu, X.Y.[Xiang-Yang], Jin, R.C.[Ren-Chao], Jin, L.H.[Liang-Hai], Hung, C.C.[Chih-Cheng],
Label fusion method based on sparse patch representation for the brain MRI image segmentation,
IET-IPR(11), No. 7, July 2017, pp. 502-511.
DOI Link 1707
BibRef

Yan, M.[Meng], Liu, H.[Hong], Song, E.[Enmin], Qian, Y.J.[Yue-Jing], Jin, L.H.[Liang-Hai], Hung, C.C.[Chih-Cheng],
Sparse patch-based representation with combined information of atlas for multi-atlas label fusion,
IET-IPR(12), No. 8, August 2018, pp. 1345-1353.
DOI Link 1808
BibRef

Ahmadvand, A.[Ali], Yousefi, S.[Sahar], Shalmani, M.T.M.[M. T. Manzuri],
A novel Markov random field model based on region adjacency graph for T1 magnetic resonance imaging brain segmentation,
IJIST(27), No. 1, 2017, pp. 78-88.
DOI Link 1704
brain segmentation BibRef

Baghdadi, M.[Mohamed], Benamrane, N.[Nacéra], Sais, L.[Lakhdar],
Fuzzy generalized fast marching method for 3D segmentation of brain structures,
IJIST(27), No. 3, 2017, pp. 281-306.
DOI Link 1708
brain imaging, deformable models, fuzzy c-means method (FCM), generalized fast marching method (GFMM), MRI, , segmentation BibRef

Milletari, F.[Fausto], Ahmadi, S.A.[Seyed-Ahmad], Kroll, C.[Christine], Plate, A.[Annika], Rozanski, V.[Verena], Maiostre, J.[Juliana], Levin, J.[Johannes], Dietrich, O.[Olaf], Ertl-Wagner, B.[Birgit], Bötzel, K.[Kai], Navab, N.[Nassir],
Hough-CNN: Deep learning for segmentation of deep brain regions in MRI and ultrasound,
CVIU(164), No. 1, 2017, pp. 92-102.
Elsevier DOI 1801
Convolutional neural networks BibRef

Zhang, M.L.[Ming-Li], Desrosiers, C.[Christian], Zhang, C.M.[Cai-Ming],
Atlas-based reconstruction of high performance brain MR data,
PR(76), No. 1, 2018, pp. 549-559.
Elsevier DOI 1801
Multi-subject MRI BibRef

Ghosh, P.[Partha], Mali, K.[Kalyani], Das, S.K.[Sitansu Kumar],
Chaotic firefly algorithm-based fuzzy C-means algorithm for segmentation of brain tissues in magnetic resonance images,
JVCIR(54), 2018, pp. 63-79.
Elsevier DOI 1806
FCM, FAFCM, En-FAOFCM, Bias field, Spatial information, Total variation, PVE, Tanimoto coefficient and dice similarity BibRef

Tavakoli, F.[Fattane], Ghasemi, J.[Jamal],
Brain MRI segmentation by combining different MRI modalities using Dempster-Shafer theory,
IET-IPR(12), No. 8, August 2018, pp. 1322-1330.
DOI Link 1808
BibRef

Saladi, S.[Saritha], Prabha, N.A.[N. Amutha],
MRI brain segmentation in combination of clustering methods with Markov random field,
IJIST(28), No. 3, September 2018, pp. 207-216.
WWW Link. 1808
BibRef

Subramani, B.[Bharath], Veluchamy, M.[Magudeeswaran],
MRI brain image enhancement using brightness preserving adaptive fuzzy histogram equalization,
IJIST(28), No. 3, September 2018, pp. 217-222.
WWW Link. 1808
BibRef

Veluchamy, M.[Magudeeswaran], Mayathevar, K.[Krishnamurthy], Subramani, B.[Bharath],
Brightness preserving optimized weighted bi-histogram equalization algorithm and its application to MR brain image segmentation,
IJIST(29), No. 3, September 2019, pp. 339-352.
DOI Link 1908
BibRef

Tuan, T.A.[Tran Anh], Kim, J.Y.[Jin Young], Bao, P.T.[Pham The],
3D brain magnetic resonance imaging segmentation by using bitplane and adaptive fast marching,
IJIST(28), No. 3, September 2018, pp. 223-230.
WWW Link. 1808
BibRef

Nie, D.[Dong], Wang, L.[Li], Adeli, E.[Ehsan], Lao, C.J.[Cui-Jin], Lin, W.L.[Wei-Li], Shen, D.G.[Ding-Gang],
3-D Fully Convolutional Networks for Multimodal Isointense Infant Brain Image Segmentation,
Cyber(49), No. 3, March 2019, pp. 1123-1136.
IEEE DOI 1902
Image segmentation, Brain, Magnetic resonance imaging, Convolution, Solid modeling, Biomedical imaging, tissue segmentation BibRef

Wang, X.C.[Xu-Chu], Wang, L.[Li], Suk, H.I.[Heung-Il], Shen, D.G.[Ding-Gang],
Online Discriminative Multi-atlas Learning for Isointense Infant Brain Segmentation,
MLMI14(297-305).
Springer DOI 1410
BibRef

Wu, G.R.[Guo-Rong], Wang, L.[Li], Gilmore, J.H.[John H.], Lin, W.[Weili], Shen, D.G.[Ding-Gang],
Joint Segmentation and Registration for Infant Brain Images,
MCV14(13-21).
Springer DOI 1501
BibRef

Wang, L.[Li], Gao, Y.Z.[Yao-Zong], Li, G.[Gang], Shi, F.[Feng], Lin, W.[Weili], Shen, D.G.[Ding-Gang],
LATEST: Local AdapTivE and Sequential Training for Tissue Segmentation of Isointense Infant Brain MR Images,
MCV16(26-34).
Springer DOI 1711
BibRef

Wang, L.[Li], Gao, Y.Z.[Yao-Zong], Shi, F.[Feng], Li, G.[Gang], Gilmore, J.H.[John H.], Lin, W.L.[Wei-Li], Shen, D.G.[Ding-Gang],
LINKS: Learning-Based Multi-source IntegratioN FrameworK for Segmentation of Infant Brain Images,
MCV14(22-33).
Springer DOI 1501
BibRef

Wang, Q.[Qian], Wu, G.R.[Guo-Rong], Wang, L.[Li], Shi, P.F.[Peng-Fei], Lin, W.[Weili], Shen, D.G.[Ding-Gang],
Sparsity-Learning-Based Longitudinal MR Image Registration for Early Brain Development,
MLMI14(1-8).
Springer DOI 1410
BibRef

Dolz, J., Gopinath, K., Yuan, J., Lombaert, H., Desrosiers, C., Ben Ayed, I.,
HyperDense-Net: A Hyper-Densely Connected CNN for Multi-Modal Image Segmentation,
MedImg(38), No. 5, May 2019, pp. 1116-1126.
IEEE DOI 1905
Image segmentation, Brain, Training, Magnetic resonance imaging, Task analysis, Deep learning, multi-modal imaging BibRef

Somasundaram, K., Kalaividya, P.A., Kalaiselvi, T., Krishnamoorthy, R., Praveenkumar, S.,
Edge detection using Chebyshev's orthogonal polynomial and brain extraction from magnetic resonance images of human head,
IJIST(29), No. 2, June 2019, pp. 110-120.
WWW Link. 1906
BibRef

Xu, L.J.[Li-Jun], Liu, H.[Hong], Song, E.[Enmin], Jin, R.C.[Ren-Chao], Hung, C.C.[Chih-Cheng],
Automatic brain tissue segmentation in MR images using hybrid atlas forest based on confidence-weighted probability matrix,
IJIST(29), No. 2, June 2019, pp. 97-109.
WWW Link. 1906
BibRef

Minaee, S., Wang, Y., Aygar, A., Chung, S., Wang, X., Lui, Y.W., Fieremans, E., Flanagan, S., Rath, J.,
MTBI Identification From Diffusion MR Images Using Bag of Adversarial Visual Features,
MedImg(38), No. 11, November 2019, pp. 2545-2555.
IEEE DOI 1911
Feature extraction, Magnetic resonance imaging, White matter, Machine learning, Measurement, Visualization, MTBI identification, machine learning BibRef

Kuijf, H.J., Biesbroek, J.M., de Bresser, J., Heinen, R., Andermatt, S., Bento, M., Berseth, M., Belyaev, M., Cardoso, M.J., Casamitjana, A., Collins, D.L., Dadar, M., Georgiou, A., Ghafoorian, M., Jin, D., Khademi, A., Knight, J., Li, H., Lladó, X., Luna, M., Mahmood, Q., McKinley, R., Mehrtash, A., Ourselin, S., Park, B., Park, H., Park, S.H., Pezold, S., Puybareau, E., Rittner, L., Sudre, C.H., Valverde, S., Vilaplana, V., Wiest, R., Xu, Y., Xu, Z., Zeng, G., Zhang, J., Zheng, G., Chen, C., van der Flier, W., Barkhof, F., Viergever, M.A., Biessels, G.J.,
Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities and Results of the WMH Segmentation Challenge,
MedImg(38), No. 11, November 2019, pp. 2556-2568.
IEEE DOI 1911
Image segmentation, Manuals, White matter, Biomedical imaging, Radiology, segmentation BibRef

Chen, Y.J.[Yun-Jie], Wu, M.L.[Meng-Lin],
A level set method for brain MR image segmentation under asymmetric distributions,
SIViP(13), No. 7, October 2019, pp. 1421-1429.
WWW Link. 1911
BibRef

Kim, D.C.[Dong-Chan], Chae, J.H.[Jong-Hee], Han, Y.[Yeji],
Pediatric brain extraction from T2-weighted MR images using 3D dual frame U-net and human connectome database,
IJIST(29), No. 4, 2019, pp. 476-482.
DOI Link 1911
dual frame 3D U-net, HCP database, pediatric brain extraction BibRef

Sun, L., Shao, W., Wang, M., Zhang, D., Liu, M.,
High-Order Feature Learning for Multi-Atlas Based Label Fusion: Application to Brain Segmentation With MRI,
IP(29), 2020, pp. 2702-2713.
IEEE DOI 2001
High-order features, multi-atlas, ROI segmentation BibRef

Chen, X., Lian, C.F., Wang, L., Deng, H., Fung, S.H., Nie, D., Thung, K., Yap, P., Gateno, J., Xia, J.J., Shen, D.G.,
One-Shot Generative Adversarial Learning for MRI Segmentation of Craniomaxillofacial Bony Structures,
MedImg(39), No. 3, March 2020, pp. 787-796.
IEEE DOI 2004
Craniomaxillofacial bone segmentation, MRI, generative adversarial learning, one-shot learning BibRef

Tripathi, P.C.[Prasun Chandra], Bag, S.[Soumen],
Segmentation of brain magnetic resonance images using a novel fuzzy clustering based method,
IET-IPR(14), No. 15, 15 December 2020, pp. 3705-3717.
DOI Link 2103
BibRef

Chatterjee, P.[Pubali], Sharma, K.D.[Kaushik Das], Chakrabarti, A.[Amlan],
A stochastic approach for automated brain MRI segmentation,
IET-IPR(15), No. 3, 2021, pp. 735-745.
DOI Link 2106
BibRef

Yan, M.[Meng], Jin, H.Z.[Hua-Zhong], Zhao, Z.Q.[Zhi-Qiang], Xia, D.[Dahai], Pan, N.[Ning],
Double-weighted patch-based label fusion for MR brain image segmentation,
IET-IPR(15), No. 1, 2021, pp. 218-227.
DOI Link 2106
BibRef

Mishro, P.K.[Pranaba K.], Agrawal, S.[Sanjay], Panda, R.[Rutuparna], Abraham, A.[Ajith],
A Novel Type-2 Fuzzy C-Means Clustering for Brain MR Image Segmentation,
Cyber(51), No. 8, August 2021, pp. 3901-3912.
IEEE DOI 2108
Image segmentation, Clustering algorithms, Uncertainty, Standards, Brain modeling, Cybernetics, MRI BibRef

Kradda, A.O.[Ali Ould], Ghomari, A.[Abdelghani], Ben Hmed, A.[Abdennacer], Binczak, S.[Stephane],
Anatomical multiatlas segmentation using local texture statistical properties for matching descriptor with machine learning,
IJIST(31), No. 3, 2021, pp. 1437-1454.
DOI Link 2108
anatomical multiatlas, cerebral MRI, local texture descriptor, machine learning, matching, registration BibRef

Lai, J., Zhu, H.,
A Fusion Algorithm: Fully Convolutional Networks and Student's T Mixture Model for Brain Magnetic Resonance Imaging Segmentation,
ICIP18(1598-1602)
IEEE DOI 1809
Image segmentation, Mixture models, Magnetic resonance imaging, Training, Image recognition, Biomedical imaging, fusion algorithm BibRef

Hamu Goldberg, H.B., Mushkin, J., Raviv, T.R., Sochen, N.,
Sampling Technique for Defining Segmentation Error Margins with Application to Structural Brain MRI,
ICIP18(734-738)
IEEE DOI 1809
Image segmentation, Markov processes, Biomedical imaging, Uncertainty, Magnetic resonance imaging, Monte Carlo methods, Markov Chain Monte Carlo BibRef

Kaushik, S.[Sumit], Slovak, J.[Jan],
DTI Segmentation Using Anisotropy Preserving Quaternion Based Distance Measure,
ICIAR18(81-89).
Springer DOI 1807
BibRef

Wang, L., Huang, J., Lav, B., Pan, C.,
MR images segmentation and bias correction via LIC model,
ICIP17(4412-4416)
IEEE DOI 1803
Additives, Brain modeling, Estimation, Gaussian noise, Image segmentation, Nonhomogeneous media, Optimization, Linear Intrinsic Component BibRef

Xu, Y., Géraud, T., Bloch, I.,
From neonatal to adult brain MR image segmentation in a few seconds using 3D-like fully convolutional network and transfer learning,
ICIP17(4417-4421)
IEEE DOI 1803
biological tissues, biomedical MRI, brain, diseases, image classification, image segmentation, Neonatal/Adult brain segmentation BibRef

Guo, D., Zheng, K., Wang, S.,
Lesion detection using T1-weighted MRI: A new approach based on functional cortical ROIs,
ICIP17(4427-4431)
IEEE DOI 1803
biomedical MRI, brain, image segmentation, medical image processing, neurophysiology, T1-weighted MR images, T1-weighted MRI BibRef

Cappabianco, F.A.M., de Miranda, P.A.V., Udupa, J.K.,
A critical analysis of the methods of evaluating MRI brain segmentation algorithms,
ICIP17(3894-3898)
IEEE DOI 1803
biological tissues, biomedical MRI, brain, image classification, image segmentation, medical image processing, Partial Volume Effect BibRef

Kapás, Z.[Zoltán], Lefkovits, L.[László], Iclanzan, D.[David], Gyorfi, Á.[Ágnes], Iantovics, B.L.[Barna László], Lefkovits, S.[Szidónia], Szilágyi, M.[Miklós], Szilágyi, L.[László],
Automatic Brain Tumor Segmentation in Multispectral MRI Volumes Using a Random Forest Approach,
PSIVT17(137-149).
Springer DOI 1802
BibRef

Singh, A., Hazarika, D., Bhattacharya, A.,
Texture and Structure Incorporated ScatterNet Hybrid Deep Learning Network (TS-SHDL) for Brain Matter Segmentation,
CEFR-LCV17(1181-1188)
IEEE DOI 1802
Encoding, Feature extraction, Image segmentation, Machine learning, Personal area networks, Unsupervised learning BibRef

Cappabianco, F.A.M.[Fábio A. M.], Lellis, L.S.[Lucas Santana], Miranda, P.[Paulo], Ide, J.S.[Jaime S.], Mujica-Parodi, L.R.[Lilianne R.],
Edge Detection Robust to Intensity Inhomogeneity: A 7T MRI Case Study,
CIARP16(459-466).
Springer DOI 1703
BibRef

Chou, Y.[Yao], Lee, D.J.[Dah Jye], Zhang, D.[Dong],
Edge Detection Using Convolutional Neural Networks for Nematode Development and Adaptation Analysis,
CVS17(228-238).
Springer DOI 1711
BibRef
Earlier:
Semantic-Based Brain MRI Image Segmentation Using Convolutional Neural Network,
ISVC16(I: 628-638).
Springer DOI 1701
BibRef

Yu, R.[Renping], Deng, M.H.[Ming-Hui], Yap, P.T.[Pew-Thian], Wei, Z.H.[Zhi-Hui], Wang, L.[Li], Shen, D.G.[Ding-Gang],
Learning-Based 3T Brain MRI Segmentation with Guidance from 7T MRI Labeling,
MLMI16(213-220).
Springer DOI 1611
BibRef

Wu, Z.W.[Zheng-Wang], Park, S.H.[Sang Hyun], Guo, Y.R.[Yan-Rong], Gao, Y.Z.[Yao-Zong], Shen, D.G.[Ding-Gang],
Regression Guided Deformable Models for Segmentation of Multiple Brain ROIs,
MLMI16(237-245).
Springer DOI 1611
BibRef

Wu, Z.W.[Zheng-Wang], Gao, Y.Z.[Yao-Zong], Shi, F.[Feng], Jewells, V.[Valerie], Shen, D.G.[Ding-Gang],
Automatic Hippocampal Subfield Segmentation from 3T Multi-modality Images,
MLMI16(229-236).
Springer DOI 1611
BibRef

Liu, Y.[Yuan], Çetingül, H.E.[Hasan E.], Odry, B.L.[Benjamin L.], Nadar, M.S.[Mariappan S.],
Learning Global and Cluster-Specific Classifiers for Robust Brain Extraction in MR Data,
MLMI16(130-138).
Springer DOI 1611
BibRef

Bao, S.Q.[Si-Qi], Chung, A.C.S.[Albert C. S.],
Label inference encoded with local and global patch priors,
ICIP16(3374-3378)
IEEE DOI 1610
Biomedical imaging BibRef

Shao, Y.Q.[Ye-Qin], Guo, Y.R.[Yan-Rong], Gao, Y.Z.[Yao-Zong], Yang, X.[Xin], Shen, D.G.[Ding-Gang],
Hippocampus Segmentation from MR Infant Brain Images via Boundary Regression,
MCV15(146-154).
Springer DOI 1608
BibRef

López-Lopera, A.F.[Andrés F.], Álvarez, M.A.[Mauricio A.], Orozco, Á.Á.[Álvaro Á.],
Improving Diffusion Tensor Estimation Using Adaptive and Optimized Filtering Based on Local Similarity,
IbPRIA15(612-620).
Springer DOI 1506
BibRef

Jimenez, D.A.[David A.], García, H.F.[Hernán F.], Álvarez, A.M.[Andres M.], Orozco, Á.A.[Álvaro A.], Holguín, G.,
A Kernelized Morphable Model for 3D Brain Tumor Analysis,
ICIAR18(529-537).
Springer DOI 1807
BibRef
Earlier: A1, A2, A3, A4, Only:
3D Probabilistic Morphable Models for Brain Tumor Segmentation,
CIARP17(314-322).
Springer DOI 1802
BibRef

García, H.F.[Hernán F.], Álvarez, M.A.[Mauricio A.], Orozco, Á.Á.[Álvaro Á.],
Bayesian Optimization for Fitting 3D Morphable Models of Brain Structures,
CIARP16(291-299).
Springer DOI 1703
BibRef
Earlier:
Groupwise Shape Correspondences on 3D Brain Structures Using Probabilistic Latent Variable Models,
ISVC15(I: 491-500).
Springer DOI 1601
BibRef
Earlier:
Bayesian Shape Models with Shape Priors for MRI Brain Segmentation,
ISVC14(II: 851-860).
Springer DOI 1501
BibRef

Cardona, H.D.V.[Hernán Darío Vargas], Orozco, Á.A.[Álvaro A.], Álvarez, M.A.[Mauricio A.],
Analysis of the Geometry and Electric Properties of Brain Tissue in Simulation Models for Deep Brain Stimulation,
CIARP16(493-501).
Springer DOI 1703
BibRef

Koch, L.M.[Lisa M.], Wright, R.[Robert], Vatansever, D.[Deniz], Kyriakopoulou, V.[Vanessa], Malamateniou, C.[Christina], Patkee, P.A.[Prachi A.], Rutherford, M.[Mary], Hajnal, J.V.[Joseph V.], Aljabar, P.[Paul], Rueckert, D.[Daniel],
Graph-Based Label Propagation in Fetal Brain MR Images,
MLMI14(9-16).
Springer DOI 1410
BibRef

Miyapuram, K.P., Schultz, W., Tobler, P.N.,
Predicting the imagined contents using brain activation,
NCVPRIPG13(1-3)
IEEE DOI 1408
biomedical MRI BibRef

Anami, B.S., Unki, P.H.,
A combined fuzzy and level sets' based approach for brain MRI image segmentation,
NCVPRIPG13(1-4)
IEEE DOI 1408
biological tissues BibRef

Murphy, S.[Sean], Mohr, B.[Brian], Fushimi, Y.[Yasutaka], Yamagata, H.[Hitoshi], Poole, I.[Ian],
Fast, Simple, Accurate Multi-Atlas Segmentation of the Brain,
WBIR14(1-10).
Springer DOI 1407
BibRef

Wang, Y.P.[Ya-Ping], Jia, H.J.[Hong-Jun], Yap, P.T.[Pew-Thian], Cheng, B.[Bo], Wee, C.Y.[Chong-Yaw], Guo, L.[Lei], Shen, D.G.[Ding-Gang],
Groupwise Segmentation Improves Neuroimaging Classification Accuracy,
MBIA12(185-193).
Springer DOI 1210
BibRef

Desrosiers, C.[Christian],
Unsupervised segmentation using dynamic superpixel random walks,
ICIP15(1772-1776)
IEEE DOI 1512
Image segmentation; random walks; un-supervised segmentation BibRef

Morin, J.P.[Jean-Philippe], Desrosiers, C.[Christian], Duong, L.[Luc],
A random walk approach for multiatlas-based segmentation,
ICPR12(3636-3639).
WWW Link. 1302
BibRef
And:
Atlas-based segmentation of brain magnetic resonance imaging using random walks,
MCV12(44-49).
IEEE DOI 1207
BibRef

Xu, R.[Rong], Ohya, J.,
An improved Kernel-based Fuzzy C-means Algorithm with spatial information for brain MR image segmentation,
IVCNZ10(1-7).
IEEE DOI 1203
BibRef

Liu, C.Y.[Cheng-Yi], Iglesias, J.E.[Juan Eugenio], Tu, Z.W.[Zhuo-Wen],
Pictorial multi-atlas segmentation of brain MRI,
MMBIA12(65-70).
IEEE DOI 1203
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Péporté, M.[Michèle], Ghita, D.E.I.[Dana E. Ilea], Twomey, E.[Eilish], Whelan, P.F.[Paul F.],
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CISP09(1-5).
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Guan, Y.H.[Yi-Hong], Lv, L.[Liang], Duan, R.[Rui], Ji, Y.H.[Yun-Hai],
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CISP09(1-5).
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Zhang, S.T.[Shao-Ting], Zhou, J.H.[Jing-Hao], Wang, X.X.[Xiao-Xu], Chang, S.[Sukmoon], Metaxas, D.N.[Dimitris N.], Pappas, G.[George], Delis, F.[Foteini], Volkow, N.D.[Nora D.], Wang, G.J.[Gene-Jack], Thanos, P.K.[Panayotis K.], Kambhamettu, C.[Chandra],
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MMBIA09(141-148).
IEEE DOI 0906
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ISVC08(I: 552-561).
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ICIAR08(xx-yy).
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MMBIA07(1-8).
IEEE DOI 0710
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Veloz, A.[Alejandro], Chabert, S.[Steren], Salas, R.[Rodrigo], Orellana, A.[Antonio], Vielma, J.[Juan],
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CIARP07(861-870).
Springer DOI 0711
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Liu, J.D.[Jun-Dong], Chelberg, D., Smith, C.[Charles], Chebrolu, H.[Hima],
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Liu, J.D.[Jun-Dong], Smith, C.[Charles], Chebrolu, H.[Hima],
A Local Probabilistic Prior-Based Active Contour Model for Brain MR Image Segmentation,
ACCV07(I: 956-964).
Springer DOI 0711
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Szilágyi, L.[László], Szilágyi, S.M.[Sándor M.], Benyó, Z.[Zoltán],
A Thorough Analysis of the Suppressed Fuzzy C-Means Algorithm,
CIARP08(203-210).
Springer DOI 0809
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Earlier:
A Modified Fuzzy C-Means Algorithm for MR Brain Image Segmentation,
ICIAR07(866-877).
Springer DOI 0708
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And:
Efficient Feature Extraction for Fast Segmentation of MR Brain Images,
SCIA07(611-620).
Springer DOI 0706

See also Echocardiographic Image Sequence Compression Based on Spatial Active Appearance Model.
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CVAMIA06(132-142).
Springer DOI 0605
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Probabilistic Brain Lesion Segmentation in DT-MRI,
ICIP06(89-92).
IEEE DOI 0610
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Yu, G.[Gang], Wang, C.G.[Chang-Guo], Zhang, H.M.[Hong-Mei], Yang, Y.X.[Yu-Xiang], Bian, Z.Z.[Zheng-Zhong],
A Novel Fuzzy Segmentation Approach for Brain MRI,
ACIVS06(887-896).
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He, H.G.[Hui-Guang], Lv, B.[Bin], Lu, K.[Ke],
Robust Partial Volume Segmentation with Bias Field Correction in Brain MRI,
ICPR06(II: 175-178).
IEEE DOI 0609
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Fan, X.[Xian], Yang, J.[Jie], Zheng, Y.J.[Yuan-Jie], Cheng, L.S.[Li-Shui], Zhu, Y.[Yun],
A Novel Unsupervised Segmentation Method for MR Brain Images Based on Fuzzy Methods,
CVBIA05(160-169).
Springer DOI 0601
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Peng, Z.G.[Zhi-Gang], Cai, X.[Xiang], Wee, W.[William], Lee, J.H.[Jing-Huei],
3D Method of Using Spatial-Varying Gaussian Mixture and Local Information to Segment MR Brain Volumes,
ICIAR06(II: 660-671).
Springer DOI 0610
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Peng, Z.G.[Zhi-Gang], Wee, W.[William], Lee, J.H.[Jing-Huei],
Automatic Segmentation of MR Brain Images Using Spatial-Varying Gaussian Mixture and Markov Random Field Approach,
MMBIA06(80).
IEEE DOI 0609
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Earlier:
MR Brain Imaging Segmentation Based On Spatial Gaussian Mixture Model And Markov Random Field,
ICIP05(I: 313-316).
IEEE DOI 0512
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Li, W.Q.[Wan-Qing], de Silver, C., Attikiouzel, Y.,
Simultaneous Map Estimation of Inhomogeneity and Segmentation of Brain Tissues from MR Images,
ICIP05(II: 1234-1237).
IEEE DOI 0512
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Li, W.Q.[Wan-Qing], Morrison, M.W., Attikiouzel, Y.,
Unsupervised segmentation of dual-echo MR images by a sequentially learned Gaussian mixture model,
ICIP95(III: 576-579).
IEEE DOI 9510
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Hu, Q.M.[Qing-Mao], Qian, G.Y.[Guo-Yu], Nowinski, W.L.[Wieslaw L.],
Fast and Robust Segmentation of Head in T1-weighted Magnetic Resonance Volumes,
ICARCV06(1-4).
IEEE DOI 0612
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Parimal, A.S., Ivanou, N., Nowinski, W.L.,
Transformation Of Images By Radial Basis Functions With Varying Centre Point,
ICARCV06(1-5).
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Warping images with a variety of landmarks. BibRef

Zuo, W.[Wei], Hu, Q.M.[Qing-Mao], Aziz, A., Loe, K.[Kiatock], Nowinski, W.L.,
Knowledge-driven segmentation of the central sulcus from human brain MR images,
ICIP04(IV: 2443-2446).
IEEE DOI 0505
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Legal-Ayala, H.A., Facon, J.,
Automatic segmentation of brain MRI through learning by example,
ICIP04(II: 917-920).
IEEE DOI 0505
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Hult, R.[Roger],
Segmentation of T1-MRI of the Human Cortex Using a 3D Grey-level Morphology Approach,
SCIA03(462-469).
Springer DOI 0310
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Earlier:
Grey-level morphology based segmentation of MRI of the human cortex,
CIAP01(578-583).
IEEE DOI 0210
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Hult, R., Bengtsson, E., Thurfjell, L.,
Segmentation of the Brain in MRI Using Grey Level Morphology and Propagation of Information,
SCIA99(Biological Applications I). BibRef 9900

Undeman, C.[Carl], Lindeberg, T.[Tony],
Fully Automatic Segmentation of MRI Brain Images Using Probabilistic Anisotropic Diffusion and Multi-scale Watersheds,
ScaleSpace03(641-656).
Springer DOI 0310
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Menegaz, G., Grewe, L.,
3D/2D object-based coding of head MRI data,
ICIP02(I: 181-184).
IEEE DOI 0210
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Biancardi, A.[Alberto], Segovia-Martínez, M.[Manuel],
Adaptive Segmentation of MR Axial Brain Images Using Connected Components,
VF01(295 ff.).
Springer DOI 0209
BibRef

Dokladal, P., Urtasun, R., Bloch, I., Garnero, L.,
Segmentation of 3D Head MR Images Using Morphological Reconstruction Under Constraints and Automatic Selection of Markers,
ICIP01(III: 1075-1078).
IEEE DOI 0108
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Lundervold, A.[Arvid], Duta, N.[Nicolae], Taxt, T.[Torfinn], Jain, A.K.[Anil K.],
Model-guided Segmentation of Corpus Callosum in MR Images,
CVPR99(I: 231-237).
IEEE DOI BibRef 9900

Vinitski, S.[Simon], Iwanaga, T.[Tad], Gonzalez, C.[Carlos], Andrews, D.[David], Knobler, R.[Robert], Mack, J.[John],
Fast tissue segmentation based on a 4D feature map: Preliminary results,
CIAP97(II: 445-452).
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Vinitski, S.[Simon], Gonzalez, C.[Carlos], Burnett, C.[Claudio], Mohamed, F.[Feroze], Iwanaga, T.[Tad], Ortega, H.[Hector], Faro, S.[Scott],
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CIAP95(265-270).
Springer DOI 9509
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Klemencic, J.[Jan], Valencic, V.[Vojko], Pecaric, N.[Nuska],
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CAIP01(298 ff.).
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Sammouda, R., Niki, N., Nishitani, H.,
Hopfield neural network with prespecified time convergence for the segmentation of brain MR images,
ICPR96(IV: 462-471).
IEEE DOI 0509
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Ghanei, A., Soltanian-Zadeh, H., Windham, J.P.,
Automatic segmentation of hippocampus from brain MRI using deformable contours,
ICIP96(II: 245-248).
IEEE DOI 9610
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Soltanian-Zadeh, H., Windham, J.P.,
Linear filter design for CNR enhancement of MR images with multiple interfering features,
ICIP96(II: 241-244).
IEEE DOI 9610
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Kosugi, Y., Suganaimi, Y., Uemoto, N., Kameyama, K., Sase, M., Momose, T., Nishikawa, J.,
CCE-based index selection for neuro assisted MR-image segmentation,
ICIP96(II: 249-252).
IEEE DOI 9610
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Batista, J.[João], Kitney, R.I.[Richard I.],
Extraction of tumours from MR images of the brain by texture and clustering,
CIAP95(235-240).
Springer DOI 9509
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Bello, F.[Fernando], Kitney, R.I.[Richard I.],
Automatic identification of brain contours in magnetic resonance images of the head,
CIAP95(241-246).
Springer DOI 9509
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Parvin, B., Johnston, W., and Roselli, D.,
Pinta: A System for Visualizing the Anatomical Structures of the Brain from MR Imaging,
CVPR93(615-616).
IEEE DOI BibRef 9300

Zijdenbos, A.P., Dawant, B.M., Margolin, R.A.,
Automatic extraction of the intracranial cavity on transverse MR brain images,
ICPR92(III:430-433).
IEEE DOI 9208
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Kapouleas, I.,
Segmentation and feature extraction for magnetic resonance brain image analysis,
ICPR90(I: 583-590).
IEEE DOI 9006
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Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Brain, Cortex, Registration, Alignment, MRI, Other .