20.9.1 Brain Tumors, Cortex, Cancer

Chapter Contents (Back)
Brain. Brain Tumor. Tumor.

brain lesion segmentation,
Online
WWW Link. 1605
Code, Brain Lesion Segmentation. multi-scale 3D Deep Convolutional Neural Network coupled with a 3D fully connected Conditional Random Field. BibRef

Kyriacou, S.K., Davatzikos, C., Zinreich, S.J., Bryan, R.N.,
Nonlinear elastic registration of brain images with tumor pathology using a biomechanical model [MRI],
MedImg(18), No. 7, July 1999, pp. 580-592.
IEEE Top Reference. 0110
BibRef

Iftekharuddin, K.M.[Khan M.], Jia, W.[Wei], Marsh, R.[Ronald],
Fractal analysis of tumor in brain MR images,
MVA(13), No. 5-6, 2003, pp. 352-362.
WWW Link. 0304
See also FractalNet: A biologically inspired neural network approach to fractal geometry. BibRef

Corso, J.J., Sharon, E., Dube, S., El-Saden, S., Sinha, U., Yuille, A.L.,
Efficient Multilevel Brain Tumor Segmentation With Integrated Bayesian Model Classification,
MedImg(27), No. 5, May 2008, pp. 629-640.
IEEE DOI 0711
BibRef

Al-Kadi, O.S.[Omar S.],
Texture measures combination for improved meningioma classification of histopathological images,
PR(43), No. 6, June 2010, pp. 2043-2053.
Elsevier DOI 1003
BibRef
Earlier:
A fractal dimension based optimal wavelet packet analysis technique for classification of meningioma brain tumours,
ICIP09(4177-4180).
IEEE DOI 0911
Coloured texture analysis; Feature extraction; Histopathological images; Meningioma; Naive Bayesian classifier; Bhattacharyya distance BibRef

Zhang, N.[Nan], Ruan, S.[Su], Lebonvallet, S.[Stephane], Liao, Q.M.[Qing-Min], Zhu, Y.M.[Yue-Min],
Kernel feature selection to fuse multi-spectral MRI images for brain tumor segmentation,
CVIU(115), No. 2, February 2011, pp. 256-269.
Elsevier DOI 1102
BibRef
Earlier:
Multi-kernel SVM based classification for brain tumor segmentation of MRI multi-sequence,
ICIP09(3373-3376).
IEEE DOI 0911
SVM; Segmentation; Feature selection; Fusion; Follow-up system; Brain tumor; MRI BibRef

Boughattas, N.[Naouel], Berar, M.[Maxime], Hamrouni, K.[Kamel], Ruan, S.[Su],
Brain tumor segmentation from multiple MRI sequences using multiple kernel learning,
ICIP14(1887-1891)
IEEE DOI 1502
Feature extraction BibRef

Hamamci, A., Kucuk, N., Karaman, K., Engin, K., Unal, G.,
Tumor-Cut: Segmentation of Brain Tumors on Contrast Enhanced MR Images for Radiosurgery Applications,
MedImg(31), No. 3, March 2012, pp. 790-804.
IEEE DOI 1203
BibRef

Jayachandran, A., Dhanasekaran, R.,
Automatic detection of brain tumor in magnetic resonance images using multi-texton histogram and support vector machine,
IJIST(23), No. 2, 2013, pp. 97-103.
DOI Link 1307
support vector machine, radial basis function, binarized image BibRef

Jayachandran, A., Dhanasekaran, R.,
Brain tumor severity analysis using modified multi-texton histogram and hybrid kernel SVM,
IJIST(24), No. 1, 2014, pp. 72-82.
DOI Link 1403
tumor BibRef

El-Melegy, M.[Moumen], Mokhtar, H.[Hashim],
Tumor segmentation in brain MRI using a fuzzy approach with class center priors,
JIVP(2014), No. 1, 2014, pp. 21.
DOI Link 1404
BibRef
Earlier:
Incorporating prior information in the fuzzy C-mean algorithm with application to brain tissues segmentation in MRI,
ICIP09(3393-3396).
IEEE DOI 0911
BibRef

Chih-Feng, C.[Chen], Ling-Wei, H.[Hsu], Chun-Chung, L.[Lui], Chen-Chang, L.[Lee], Hsu-Huei, W.[Weng], Yuan-Hsiung, T.[Tsai], Ho-Ling, L.[Liu],
In vivo correlation between semi-quantitative hemodynamic parameters and Ktrans derived from DCE-MRI of brain tumors,
IJIST(22), No. 2, June 2012, pp. 132-136.
DOI Link 1202
BibRef

Angoth, V.[Vivek], Dwith, C.Y.N., Singh, A.[Amarjot],
A Novel Wavelet Based Image Fusion for Brain Tumor Detection,
IJCVSP(2), No. 1, 2013, pp. xx-yy.
WWW Link. 1303
BibRef

Bauer, S.[Stefan], Lu, H.X.[Huan-Xiang], May, C.P.[Christian P.], Nolte, L.P.[Lutz P.], Büchler, P.[Philippe], Reyes, M.[Mauricio],
Integrated segmentation of brain tumor images for radiotherapy and neurosurgery,
IJIST(23), No. 1, March 2013, pp. 59-63.
DOI Link 1303
BibRef

Dhanalakshmi, K., Rajamani, V.,
An intelligent mining system for diagnosing medical images using combined texture-histogram features,
IJIST(23), No. 2, 2013, pp. 194-203.
DOI Link brain tumor, image processing, association rule mining, associative classifier 1307
BibRef

Arakeri, M.P.[Megha P.], Reddy, G.R.M.[G. Ram Mohana],
An intelligent content-based image retrieval system for clinical decision support in brain tumor diagnosis,
MultInfoRetr(2), No. 3, September 2013, pp. 175-188.
WWW Link. 1307
BibRef

Arakeri, M.P.[Megha P.], Reddy, G.R.M.[G. Ram Mohana],
Computer-aided diagnosis system for tissue characterization of brain tumor on magnetic resonance images,
SIViP(9), No. 2, February 2015, pp. 409-425.
WWW Link. 1503
BibRef

Vilamala, A.[Albert], Lisboa, P.J.G.[Paulo J.G.], Ortega-Martorell, S.[Sandra], Vellido, A.[Alfredo],
Discriminant Convex Non-negative Matrix Factorization for the classification of human brain tumours,
PRL(34), No. 14, 2013, pp. 1734-1747.
Elsevier DOI 1308
Discriminant Convex Non-negative Matrix Factorization BibRef

Beno, M.M.[M. Marsaline], Valarmathi, I.R., Swamy, S.M., Rajakumar, B.R.,
Threshold prediction for segmenting tumour from brain MRI scans,
IJIST(24), No. 2, 2014, pp. 129-137.
DOI Link 1405
bilateral filter BibRef

Kwon, D.J.[Dong-Jin], Niethammer, M., Akbari, H., Bilello, M., Davatzikos, C., Pohl, K.M.,
PORTR: Pre-Operative and Post-Recurrence Brain Tumor Registration,
MedImg(33), No. 3, March 2014, pp. 651-667.
IEEE DOI 1404
biomedical MRI BibRef

Govindaraj, V.[Vishnuvarthanan], Murugan, P.R.[Pallikonda Rajasekaran],
A complete automated algorithm for segmentation of tissues and identification of tumor region in T1, T2, and FLAIR brain images using optimization and clustering techniques,
IJIST(24), No. 4, 2014, pp. 313-325.
DOI Link 1411
image segmentation BibRef

Balasubramani, P.[Perumal], Murugan, P.R.[Pallikonda Rajasekaran],
Efficient image compression techniques for compressing multimodal medical images using neural network radial basis function approach,
IJIST(25), No. 2, 2015, pp. 115-122.
DOI Link 1506
MRI images BibRef

Militello, C.[Carmelo], Rundo, L.[Leonardo], Vitabile, S.[Salvatore], Russo, G.[Giorgio], Pisciotta, P.[Pietro], Marletta, F.[Francesco], Ippolito, M.[Massimo], D'Arrigo, C.[Corrado], Midiri, M.[Massimo], Gilardi, M.C.[Maria Carla],
Gamma Knife treatment planning: MR brain tumor segmentation and volume measurement based on unsupervised Fuzzy C-Means clustering,
IJIST(25), No. 3, 2015, pp. 213-225.
DOI Link 1509
semi-automatic segmentation BibRef

Stefano, A.[Alessandro], Vitabile, S.[Salvatore], Russo, G.[Giorgio], Ippolito, M.[Massimo], Marletta, F.[Franco], D'Arrigo, C.[Corrado], D'Urso, D.[Davide], Sabini, M.G.[Maria Gabriella], Gambino, O.[Orazio], Pirrone, R.[Roberto], Ardizzone, E.[Edoardo], Gilardi, M.C.[Maria Carla],
An Automatic Method for Metabolic Evaluation of Gamma Knife Treatments,
CIAP15(I:579-589).
Springer DOI 1511
BibRef

Menze, B.H., Jakab, A., Bauer, S., Kalpathy-Cramer, J., Farahani, K., Kirby, J., Burren, Y., Porz, N., Slotboom, J., Wiest, R., Lanczi, L., Gerstner, E., Weber, M.A., Arbel, T., Avants, B.B., Ayache, N., Buendia, P., Collins, D.L., Cordier, N., Corso, J.J., Criminisi, A., Das, T., Delingette, H., Demiralp, C., Durst, C.R., Dojat, M., Doyle, S., Festa, J., Forbes, F., Geremia, E., Glocker, B., Golland, P., Guo, X.[Xiaotao], Hamamci, A., Iftekharuddin, K.M., Jena, R., John, N.M., Konukoglu, E., Lashkari, D., Mariz, J.A., Meier, R., Pereira, S., Precup, D., Price, S.J., Raviv, T.R.[T. Riklin], Reza, S.M.S., Ryan, M., Sarikaya, D., Schwartz, L., Shin, H.C.[Hoo-Chang], Shotton, J., Silva, C.A., Sousa, N., Subbanna, N.K., Szekely, G., Taylor, T.J., Thomas, O.M., Tustison, N.J., Unal, G., Vasseur, F., Wintermark, M., Ye, D.H.[Dong Hye], Zhao, L.[Liang], Zhao, B.[Binsheng], Zikic, D., Prastawa, M., Reyes, M., Van Leemput, K.,
The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS),
MedImg(34), No. 10, October 2015, pp. 1993-2024.
IEEE DOI 1511
benchmark testing BibRef

Shanthakumar, P., Kumar, P.G.[P. Ganesh],
Computer aided brain tumor detection system using watershed segmentation techniques,
IJIST(25), No. 4, 2015, pp. 297-301.
DOI Link 1512
enhancement BibRef

Ai, Y.[Ye], Miao, F.[Feng], Hu, Q.M.[Qing-Mao], Li, W.F.[Wei-Feng],
Multi-Feature Guided Brain Tumor Segmentation Based on Magnetic Resonance Images,
IEICE(E98-D), No. 12, December 2015, pp. 2250-2256.
WWW Link. 1601
BibRef

Anitha, V., Murugavalli, S.,
Brain tumour classification using two-tier classifier with adaptive segmentation technique,
IET-CV(10), No. 1, 2016, pp. 9-17.
DOI Link 1601
biomedical MRI BibRef

Jui, S.L., Zhang, S., Xiong, W., Yu, F., Fu, M., Wang, D., Hassanien, A.E.[Aboul Ella], Xiao, K.[Kai],
Brain MRI Tumor Segmentation with 3D Intracranial Structure Deformation Features,
IEEE_Int_Sys(31), No. 2, March 2016, pp. 66-76.
IEEE DOI 1604
Biomedical image processing BibRef

Xiao, K.[Kai], Hassanien, A.E.[Aboul Ella], Sun, Y.[Yan], Ng, E.K.K.[Edwin Kit Keong],
Brain MR Image Tumor Segmentation with Ventricular Deformation,
ICIG11(297-302).
IEEE DOI 1109
BibRef

Stefano, A.[Alessandro], Vitabile, S.[Salvatore], Russo, G.[Giorgio], Ippolito, M.[Massimo], Marletta, F.[Franco], d'Arrigo, C.[Corrado], d'Urso, D.[Davide], Gambino, O.[Orazio], Pirrone, R.[Roberto], Ardizzone, E.[Edoardo], Gilardi, M.C.[Maria Carla],
A fully automatic method for biological target volume segmentation of brain metastases,
IJIST(26), No. 1, 2016, pp. 29-37.
DOI Link 1604
random walk BibRef

Pereira, S., Pinto, A., Alves, V., Silva, C.A.,
Brain Tumor Segmentation Using Convolutional Neural Networks in MRI Images,
MedImg(35), No. 5, May 2016, pp. 1240-1251.
IEEE DOI 1605
Brain modeling BibRef

Thirumurugan, P., Ramkumar, D., Batri, K., Raja, D.S.[D. Sundhara],
Automated detection of glioblastoma tumor in brain magnetic imaging using ANFIS classifier,
IJIST(26), No. 2, 2016, pp. 151-156.
DOI Link 1606
contourlet transform BibRef

Kathirvel, R., Batri, K.,
A computer-aided approach for meningioma brain tumor detection using CANFIS classifier,
IJIST(27), No. 3, 2017, pp. 193-200.
DOI Link 1708
accuracy, brain tumor, classifier, contourlet transform, , features BibRef

Kathirvel, R., Batri, K.,
Detection and diagnosis of meningioma brain tumor using ANFIS classifier,
IJIST(27), No. 3, 2017, pp. 187-192.
DOI Link 1708
brain tumors, detection, diagnosis, features, , tissues BibRef

Thirumurugan, P., Shanthakumar, P.,
Brain tumor detection and diagnosis using ANFIS classifier,
IJIST(26), No. 2, 2016, pp. 157-162.
DOI Link 1606
gray matter, white matter, CSF, brain tumor, brain tissue BibRef

Kumarganesh, S., Suganthi, M.,
An efficient approach for brain image (tissue) compression based on the position of the brain tumor,
IJIST(26), No. 4, 2016, pp. 237-242.
DOI Link 1701
brain tumor BibRef

Thiruvenkadam, K.[Kalaiselvi], Perumal, N.[Nagaraja],
Fully automatic method for segmentation of brain tumor from multimodal magnetic resonance images using wavelet transformation and clustering technique,
IJIST(26), No. 4, 2016, pp. 305-314.
DOI Link 1701
clustering, fuzzy c-means, segmentation, tumor, wavelet BibRef

Vishnuvarthanan, G., Rajasekaran, M.P.[M. Pallikonda], Vishnuvarthanan, N.A.[N. Anitha], Prasath, T.A.[T. Arun], Kannan, M.,
Tumor detection in T1, T2, FLAIR and MPR brain images using a combination of optimization and fuzzy clustering improved by seed-based region growing algorithm,
IJIST(27), No. 1, 2017, pp. 33-45.
DOI Link 1704
MPSO-based FCM BibRef

Angulakshmi, M., Priya, G.G.L.[G.G. Lakshmi],
Automated brain tumour segmentation techniques: A review,
IJIST(27), No. 1, 2017, pp. 66-77.
DOI Link 1704
review BibRef

Sivakumar, P., Ganeshkumar, P.,
CANFIS based glioma brain tumor classification and retrieval system for tumor diagnosis,
IJIST(27), No. 2, 2017, pp. 109-117.
DOI Link 1706
brain tumor, CANFIS, classification, retrieval, segmentation BibRef

Farhi, L.[Lubna], Yusuf, A.[Adeel], Raza, R.H.[Rana Hammad],
Adaptive stochastic segmentation via energy-convergence for brain tumor in MR images,
JVCIR(46), No. 1, 2017, pp. 303-311.
Elsevier DOI 1706
Active, contours BibRef

Kaur, T.[Taranjit], Saini, B.S.[Barjinder Singh], Gupta, S.[Savita],
Quantitative metric for MR brain tumour grade classification using sample space density measure of analytic intrinsic mode function representation,
IET-IPR(11), No. 8, August 2017, pp. 620-632.
DOI Link 1708
BibRef

Ramakrishnan, T., Sankaragomathi, B.,
A professional estimate on the computed tomography brain tumor images using SVM-SMO for classification and MRG-GWO for segmentation,
PRL(94), No. 1, 2017, pp. 163-171.
Elsevier DOI 1708
Feature, extraction BibRef

Rajinikanth, V., Satapathy, S.C.[Suresh Chandra], Fernandes, S.L.[Steven Lawrence], Nachiappan, S.,
Entropy based segmentation of tumor from brain MR images: A study with teaching learning based optimization,
PRL(94), No. 1, 2017, pp. 87-95.
Elsevier DOI 1708
BibRef

Arunachalam, M.[Murugan], Savarimuthu, S.R.[Sabeenian Royappan],
An efficient and automatic glioblastoma brain tumor detection using shift-invariant shearlet transform and neural networks,
IJIST(27), No. 3, 2017, pp. 216-226.
DOI Link 1708
brain image, NSCT multiresolution, SIST enhancement, texture features, , classification BibRef

Rufus, N.H.A.[N. Herald Anantha], Selvathi, D.,
Performance analysis of computer aided brain tumor detection system using ANFIS classifier,
IJIST(27), No. 3, 2017, pp. 273-280.
DOI Link 1708
brain image, classifier, features, GLCM, , tumor BibRef

Gupta, M.[Manu], Rajagopalan, V.[Venkateswaran], Pioro, E.P.[Erik P.], Prabhakar Rao, B.V.V.S.N.,
Volumetric analysis of MR images for glioma classification and their effect on brain tissues,
SIViP(11), No. 7, October 2017, pp. 1337-1345.
Springer DOI 1708
BibRef

Ravì, D., Fabelo, H., Callic, G.M., Yang, G.Z.,
Manifold Embedding and Semantic Segmentation for Intraoperative Guidance With Hyperspectral Brain Imaging,
MedImg(36), No. 9, September 2017, pp. 1845-1857.
IEEE DOI 1709
biological tissues, brain, cancer, hyperspectral imaging, image classification, image segmentation, medical image processing, semantic networks, stochastic processes, T-distributed stochastic neighbor approach, brain surgery, dimensionality reduction scheme, hyperspectral brain imaging, semantic segmentation technique, semantic texton forest, tissue classification, tumor classification map, Brain, Cancer, Hyperspectral imaging, Image segmentation, Manifolds, Semantics, Tumors, Manifold embedding, brain cancer detection, hyperspectral imaging, semantic, segmentation BibRef


Murthy, V., Hou, L., Samaras, D., Kurc, T.M., Saltz, J.H.,
Center-Focusing Multi-task CNN with Injected Features for Classification of Glioma Nuclear Images,
WACV17(834-841)
IEEE DOI 1609
Computer vision, Conferences, Decision support systems, Handheld, computers BibRef

Urien, H.[Hélène], Buvat, I.[Irène], Rougon, N.[Nicolas], Soussan, M.[Michaël], Bloch, I.[Isabelle],
Brain Lesion Detection in 3D PET Images Using Max-Trees and a New Spatial Context Criterion,
ISMM17(455-466).
Springer DOI 1706
BibRef

Bento, M.[Mariana], Sym, Y.[Yan], Frayne, R.[Richard], Lotufo, R.[Roberto], Rittner, L.[Letícia],
Probabilistic Segmentation of Brain White Matter Lesions Using Texture-Based Classification,
ICIAR17(71-78).
Springer DOI 1706
BibRef

Salvador, R., Fabelo, H., Lazcano, R., Ortega, S., Madroñal, D., Callicó, G.M., Juárez, E., Sanz, C.,
Demo: HELICoiD tool demonstrator for real-time brain cancer detection,
DASIP16(237-238)
IEEE DOI 1704
biological tissues BibRef

Mukherjee, S.[Sabyasachi], Bandyopadhyay, O.[Oishila], Biswas, A.[Arindam],
Automated Brain Tumor Diagnosis and Severity Analysis from Brain MRI,
CompIMAGE16(194-207).
Springer DOI 1704
BibRef

Réjichi, S., Chaabane, F.,
Brain tumor extraction using graph based classification of MRI time series for diagnostic assistance,
ISIVC16(320-324)
IEEE DOI 1704
Feature extraction BibRef

Jaroudi, R.[Rym], Baravdish, G.[George], Åström, F.[Freddie], Johansson, B.T.[B. Tomas],
Source Localization of Reaction-Diffusion Models for Brain Tumors,
GCPR16(414-425).
Springer DOI 1611
BibRef

Dvorák, P.[Pavel], Menze, B.[Bjoern],
Local Structure Prediction with Convolutional Neural Networks for Multimodal Brain Tumor Segmentation,
MCV15(59-71).
Springer DOI 1608
BibRef

Swiderska, Z.[Zaneta], Markiewicz, T.[Tomasz], Grala, B.[Bartlomiej], Kozlowski, W.[Wojciech],
Texture and Mathematical Morphology for Hot-Spot Detection in Whole Slide Images of Meningiomas and Oligodendrogliomas,
CAIP15(II:1-12).
Springer DOI 1511
BibRef

De Marsico, M.[Maria], Nappi, M.[Michele], Riccio, D.[Daniel],
Entropy-Based Automatic Segmentation and Extraction of Tumors from Brain MRI Images,
CAIP15(II:195-206).
Springer DOI 1511
BibRef

Pedoia, V.[Valentina], Balbi, S.[Sergio], Binaghi, E.[Elisabetta],
Fully Automatic Brain Tumor Segmentation by Using Competitive EM and Graph Cut,
CIAP15(I:568-578).
Springer DOI 1511
BibRef

Roy, S.[Shaswati], Maji, P.[Pradipta],
A New Post-processing Method to Detect Brain Tumor Using Rough-Fuzzy Clustering,
PReMI15(407-417).
Springer DOI 1511
BibRef

Oh, K.H.[Kang Han], Kim, S.H.[Soo Hyung], Lee, M.[Myungeun],
Tumor detection on brain MR images using regional features: Method and preliminary results,
FCV15(1-4)
IEEE DOI 1506
biomedical MRI BibRef

Martinez-Cortes, T.[Tomas], Fernandez-Torres, M.A.[Miguel Angel], Jimenez-Moreno, A.[Amaya], Gonzalez-Diaz, I.[Ivan], Diaz-de-Maria, F.[Fernando], Guzman-De-Villoria, J.A.[Juan Adan], Fernandez, P.[Pilar],
A Bayesian model for brain tumor classification using clinical-based features,
ICIP14(2779-2783)
IEEE DOI 1502
Bayes methods BibRef

Al-Shaikhli, S.D.S.[Saif Dawood Salman], Yang, M.Y.[Michael Ying], Rosenhahn, B.[Bodo],
Brain tumor classification using sparse coding and dictionary learning,
ICIP14(2774-2778)
IEEE DOI 1502
Brain BibRef
And:
Coupled Dictionary Learning for Automatic Multi-Label Brain Tumor Segmentation in Flair MRI images,
ISVC14(I: 489-500).
Springer DOI 1501
BibRef

Havaei, M.[Mohammad], Jodoin, P.M.[Pierre-Marc], Larochelle, H.[Hugo],
Efficient Interactive Brain Tumor Segmentation as Within-Brain kNN Classification,
ICPR14(556-561)
IEEE DOI 1412
Brain BibRef

Zhou, M.[Mu], Hall, L.O.[Lawrence O.], Goldgof, D.B.[Dmitry B.],
Exploring Brain Tumor Heterogeneity for Survival Time Prediction,
ICPR14(580-585)
IEEE DOI 1412
Accuracy BibRef

Subbanna, N.[Nagesh], Precup, D.[Doina], Arbel, T.[Tal],
Iterative Multilevel MRF Leveraging Context and Voxel Information for Brain Tumour Segmentation in MRI,
CVPR14(400-405)
IEEE DOI 1409
BibRef

Drakopoulos, F.[Fotis], Chrisochoides, N.P.[Nikos P.],
A Parallel Adaptive Physics-Based Non-rigid Registration Framework for Brain Tumor Resection,
CompIMAGE14(57-68).
Springer DOI 1407
BibRef

Nasir, M.[Muhammad], Baig, A.[Asim], Khanum, A.[Aasia],
Brain Tumor Classification in MRI Scans Using Sparse Representation,
ICISP14(629-637).
Springer DOI 1406
BibRef

Kvet, M.[Michal], Kvet, M.[Marek], Matiasko, K.[Karol],
Application for brain tumour imaging,
WSSIP14(47-50) 1406
Atmospheric measurements BibRef

Parisot, S.[Sarah], Wells, W.[William], Chemouny, S.[Stephane], Duffau, H.[Hugues], Paragios, N.[Nikos],
Uncertainty-Driven Efficiently-Sampled Sparse Graphical Models for Concurrent Tumor Segmentation and Atlas Registration,
ICCV13(641-648)
IEEE DOI 1403
BibRef

Parisot, S.[Sarah], Duffau, H.[Hugues], Chemouny, S.[Stephane], Paragios, N.[Nikos],
Graph-based detection, segmentation and characterization of brain tumors,
CVPR12(988-995).
IEEE DOI 1208
BibRef

Salah, M.B.[Mohamed Ben], Diaz, I.[Idanis], Greiner, R.[Russell], Boulanger, P.[Pierre], Hoehn, B.[Bret],
Fully Automated Brain Tumor Segmentation Using Two MRI Modalities,
ISVC13(I:30-39).
Springer DOI 1310
BibRef

Bauer, S.[Stefan], Tessier, J.[Jean], Krieter, O.[Oliver], Nolte, L.P.[Lutz P.], Reyes, M.[Mauricio],
Integrated Spatio-Temporal Segmentation of Longitudinal Brain Tumor Imaging Studies,
MCV13(74-83).
Springer DOI 1405
BibRef

Sridhar, D., Krishna, I.M.[IV. Murali],
Brain Tumor Classification using Discrete Cosine Transform and Probabilistic Neural Network,
ICSIPR13(92-96).
IEEE DOI 1304
BibRef

Geremia, E.[Ezequiel], Menze, B.H.[Bjoern H.], Prastawa, M.[Marcel], Weber, M.A., Criminisi, A.[Antonio],
Brain Tumor Cell Density Estimation from Multi-modal MR Images Based on a Synthetic Tumor Growth Model,
MCVM12(273-282).
Springer DOI 1305
BibRef

Wei, Z.W.[Zhen-Wen], Zhang, C.M.[Cai-Ming], Yang, X.Q.[Xing-Qiang], Zhang, X.F.[Xiao-Feng],
Segmentation of Brain Tumors in CT Images Using Level Sets,
ISVC12(I: 22-31).
Springer DOI 1209
BibRef

Gasmi, K.[Karim], Kharrat, A.[Ahmed], Messaoud, M.B.[Mohamed Ben], Abid, M.[Mohamed],
Automated Segmentation of Brain Tumor Using Optimal Texture Features and Support Vector Machine Classifier,
ICIAR12(II: 230-239).
Springer DOI 1206
BibRef

Fazlollahi, A., Dowson, N., Meriaudeau, F., Rose, S., Fay, M., Thomas, P., Taylor, Z., Gal, Y., Coultard, A., Winter, C., MacFarlane, D., Salvado, O., Crozier, S., Bourgeat, P.,
Automatic Brain Tumour Segmentation in 18F-FDOPA PET Using PET/MRI Fusion,
DICTA11(325-329).
IEEE DOI 1205
BibRef

Tran, L.[Loc], Banerjee, D.[Deb], Sun, X.Y.[Xiao-Yan], Wang, J.H.[Ji-Hong], Kumar, A.J.[Ashok J.], Vinning, D.[David], McKenzie, F.D.[Frederic D.], Li, Y.H.[Yao-Hang], Li, J.[Jiang],
A Large-Scale Manifold Learning Approach for Brain Tumor Progression Prediction,
MLMI11(265-272).
Springer DOI 1109
BibRef

Zoghbi, J.M., Mamede, M.H., Jackowski, M.P.,
Computer-assisted segmentation of brain tumor lesions from multi-sequence Magnetic Resonance Imaging using the Mumford-Shah model,
IVCNZ10(1-6).
IEEE DOI 1203
BibRef

Li, H.M.[Hong-Ming], Song, M.[Ming], Fan, Y.[Yong],
Segmentation of Brain Tumors in Multi-parametric MR Images via Robust Statistic Information Propagation,
ACCV10(IV: 606-617).
Springer DOI 1011
BibRef

Wang, T.[Tao], Cheng, I.[Irene], Basu, A.[Anup],
Fully automatic brain tumor segmentation using a normalized Gaussian Bayesian Classifier and 3D Fluid Vector Flow,
ICIP10(2553-2556).
IEEE DOI 1009
BibRef

Cho, W.[Wanhyun], Park, J.[Jonghyun], Park, S.[Soonyoung], Kim, S.Y.[Sooh-Yung], Kim, S.[Sunworl], Ahn, G.[Gukdong], Lee, M.[Myungeun], Lee, G.S.[Guee-Sang],
Level-Set Segmentation of Brain Tumors Using a New Hybrid Speed Function,
ICPR10(1545-1548).
IEEE DOI 1008
BibRef

Gooya, A.[Ali], Biros, G.[George], Davatzikos, C.[Christos],
An EM algorithm for brain tumor image registration: A tumor growth modeling based approach,
MMBIA10(39-46).
IEEE DOI 1006
BibRef

Chen, V.[Victor], Ruan, S.[Su],
Graph cut segmentation technique for MRI brain tumor extraction,
IPTA10(284-287).
IEEE DOI 1007
BibRef

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Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Brain, Cortex, Alzheimer's Disease, Dementia .


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