20.9.1 Brain Tumors, Cortex, Cancer

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

Anitha, R., Raja, D.S.S.[D. Siva Sundhara],
Segmentation of glioma tumors using convolutional neural networks,
IJIST(27), No. 4, 2017, pp. 354-360.
DOI Link 1712
brain tumors, classifier, features, glioma, image fusion BibRef

Rundo, L.[Leonardo], Militello, C.[Carmelo], Tangherloni, A.[Andrea], Russo, G.[Giorgio], Vitabile, S.[Salvatore], Gilardi, M.C.[Maria Carla], Mauri, G.[Giancarlo],
NeXt for neuro-radiosurgery: A fully automatic approach for necrosis extraction in brain tumor MRI using an unsupervised machine learning technique,
IJIST(28), No. 1, 2018, pp. 21-37.
DOI Link 1802
brain tumors, magnetic resonance imaging, necrosis extraction, neuro-radiosurgery treatments, unsupervised Fuzzy C-Means clustering BibRef

Ding, Y.[Yi], Dong, R.F.[Rong-Feng], Lan, T.[Tian], Li, X.R.[Xue-Rui], Shen, G.Y.[Guang-Yu], Chen, H.[Hao], Qin, Z.[Zhiguang],
Multi-modal brain tumor image segmentation based on SDAE,
IJIST(28), No. 1, 2018, pp. 38-47.
DOI Link 1802
brain tumor segmentation, BRATS 2015, stacked de-noising auto-encoder BibRef

Anitha, R., Raja, D.S.S.[D. Siva Sundhara],
Development of computer-aided approach for brain tumor detection using random forest classifier,
IJIST(28), No. 1, 2018, pp. 48-53.
DOI Link 1802
abnormal patterns, brain tumors, classification, diagnose, segmentation BibRef

Sasikanth, S., Kumar, S.S.[S. Suresh],
Glioma tumor detection in brain MRI image using ANFIS-based normalized graph cut approach,
IJIST(28), No. 1, 2018, pp. 64-71.
DOI Link 1802
classifier, glioma tumor, graph cut approach, orientation analysis, validation BibRef

Wu, G.Q.[Guo-Qing], Chen, Y.S.[Yin-Sheng], Wang, Y.Y.[Yuan-Yuan], Yu, J.H.[Jin-Hua], Lv, X.F.[Xiao-Fei], Ju, X.[Xue], Shi, Z.F.[Zhi-Feng], Chen, L.[Liang], Chen, Z.P.[Zhong-Ping],
Sparse Representation-Based Radiomics for the Diagnosis of Brain Tumors,
MedImg(37), No. 4, April 2018, pp. 893-905.
IEEE DOI 1804
Cancer, Dictionaries, Estimation, Feature extraction, Medical diagnostic imaging, Tumors, Brain tumors, tumor differentiation BibRef

Anantha, N.H.[N. Herald], Selvathi, R.D.[Rufus D.],
Performance analysis of brain tissues and tumor detection and grading system using ANFIS classifier,
IJIST(28), No. 2, 2018, pp. 77-85.
WWW Link. 1806
BibRef

Pinto, A.[Adriano], Pereira, S.[Sérgio], Rasteiro, D.[Deolinda], Silva, C.A.[Carlos A.],
Hierarchical brain tumour segmentation using extremely randomized trees,
PR(82), 2018, pp. 105-117.
Elsevier DOI 1806
Brain tumour, Magnetic resonance imaging, Image segmentation, Hierarchy of classifiers, Extremely randomized trees, Machine learning BibRef

Izadyyazdanabadi, M.[Mohammadhassan], Belykh, E.[Evgenii], Mooney, M.[Michael], Martirosyan, N.[Nikolay], Eschbacher, J.[Jennifer], Nakaji, P.[Peter], Preul, M.C.[Mark C.], Yang, Y.Z.[Ye-Zhou],
Convolutional neural networks: Ensemble modeling, fine-tuning and unsupervised semantic localization for neurosurgical CLE images,
JVCIR(54), 2018, pp. 10-20.
Elsevier DOI 1806
Neural network, Unsupervised localization, Ensemble modeling, Brain tumor, Confocal laser endomicroscopy, Surgical vision BibRef

Arnaud, A., Forbes, F., Coquery, N., Collomb, N., Lemasson, B., Barbier, E.L.,
Fully Automatic Lesion Localization and Characterization: Application to Brain Tumors Using Multiparametric Quantitative MRI Data,
MedImg(37), No. 7, July 2018, pp. 1678-1689.
IEEE DOI 1808
biomedical MRI, brain, cancer, feature extraction, Gaussian distribution, image segmentation, fingerprint model BibRef

Ma, C., Luo, G., Wang, K.,
Concatenated and Connected Random Forests With Multiscale Patch Driven Active Contour Model for Automated Brain Tumor Segmentation of MR Images,
MedImg(37), No. 8, August 2018, pp. 1943-1954.
IEEE DOI 1808
Image segmentation, Tumors, Brain modeling, Magnetic resonance imaging, Active contours, Radio frequency, multiscale patch BibRef

Tang, Z., Ahmad, S., Yap, P., Shen, D.,
Multi-Atlas Segmentation of MR Tumor Brain Images Using Low-Rank Based Image Recovery,
MedImg(37), No. 10, October 2018, pp. 2224-2235.
IEEE DOI 1810
Brain, Tumors, Image segmentation, Pathology, Convergence, Radiology, Low-rank, multi-atlas segmentation BibRef

Kermi, A.[Adel], Andjouh, K.[Khaled], Zidane, F.[Ferhat],
Fully automated brain tumour segmentation system in 3D-MRI using symmetry analysis of brain and level sets,
IET-IPR(12), No. 11, November 2018, pp. 1964-1971.
DOI Link 1810
BibRef

Angulakshmi, M., Lakshmi Priya, G.G.,
Walsh Hadamard kernel-based texture feature for multimodal MRI brain tumour segmentation,
IJIST(28), No. 4, December 2018, pp. 254-266.
WWW Link. 1811
BibRef

Selvapandian, A., Manivannan, K.,
Performance analysis of meningioma brain tumor classifications based on gradient boosting classifier,
IJIST(28), No. 4, December 2018, pp. 295-301.
WWW Link. 1811
BibRef

Lian, C., Ruan, S., Denœux, T., Li, H., Vera, P.,
Joint Tumor Segmentation in PET-CT Images Using Co-Clustering and Fusion Based on Belief Functions,
IP(28), No. 2, February 2019, pp. 755-766.
IEEE DOI 1811
cancer, computerised tomography, image fusion, image segmentation, iterative methods, lung, medical image processing, PET-CT BibRef

Chen, S.C.[Sheng-Cong], Ding, C.X.[Chang-Xing], Liu, M.F.[Min-Feng],
Dual-force convolutional neural networks for accurate brain tumor segmentation,
PR(88), 2019, pp. 90-100.
Elsevier DOI 1901
Brain tumor segmentation, Dual-force network, Convolutional neural network, Label distribution, Post-processing BibRef

Chang, J.[Jie], Zhang, L.[Luming], Gu, N.[Naijie], Zhang, X.[Xiaoci], Ye, M.[Minquan], Yin, R.[Rongzhang], Meng, Q.[Qianqian],
A mix-pooling CNN architecture with FCRF for brain tumor segmentation,
JVCIR(58), 2019, pp. 316-322.
Elsevier DOI 1901
MR image segmentation, Convolutional Neural Network, Fully CRF BibRef

Saman, S.[Sangeetha], Narayanan, S.J.[Swathi Jamjala],
Survey on brain tumor segmentation and feature extraction of MR images,
MultInfoRetr(8), No. 2, June 2019, pp. 79-99.
Springer DOI 1906
Survey, Brain Tumors. BibRef

Rezaei, K.[Kimia], Agahi, H.[Hamed], Mahmoodzadeh, A.[Azar],
Multi-objective differential evolution-based ensemble method for brain tumour diagnosis,
IET-IPR(13), No. 9, 18 July 2019, pp. 1421-1430.
DOI Link 1907
BibRef

Lipková, J., Angelikopoulos, P., Wu, S., Alberts, E., Wiestler, B., Diehl, C., Preibisch, C., Pyka, T., Combs, S.E., Hadjidoukas, P., Van Leemput, K., Koumoutsakos, P., Lowengrub, J., Menze, B.,
Personalized Radiotherapy Design for Glioblastoma: Integrating Mathematical Tumor Models, Multimodal Scans, and Bayesian Inference,
MedImg(38), No. 8, August 2019, pp. 1875-1884.
IEEE DOI 1908
Tumors, Mathematical model, Bayes methods, Biomedical imaging, Magnetic resonance imaging, Predictive models, Glioblastoma, multimodal medical scans BibRef

Rajagopal, R.,
Glioma brain tumor detection and segmentation using weighting random forest classifier with optimized ant colony features,
IJIST(29), No. 3, September 2019, pp. 353-359.
DOI Link 1908
BibRef

Kale, V.V.[Vandana V.], Hamde, S.T.[Satish T.], Holambe, R.S.[Raghunath S.],
Brain disease diagnosis using local binary pattern and steerable pyramid,
MultInfoRetr(8), No. 3, September 2019, pp. 155-165.
Springer DOI 1908
BibRef

Gtifa, W.[Wafa], Hamdaoui, F.[Fayçal], Sakly, A.[Anis],
3D brain tumor segmentation in MRI images based on a modified PSO technique,
IJIST(29), No. 4, 2019, pp. 501-509.
DOI Link 1911
2D images, 3D brain tumor segmentation, modified particle swarm optimization BibRef

Nagarathinam, E.[Ezhilmathi], Ponnuchamy, T.[Thirumurugan],
Image registration-based brain tumor detection and segmentation using ANFIS classification approach,
IJIST(29), No. 4, 2019, pp. 510-517.
DOI Link 1911
abnormal cells, classifications, detection, segmentation, tumor BibRef

Johnpeter, J.H.[Jasmine Hephzipah], Ponnuchamy, T.[Thirumurugan],
Computer aided automated detection and classification of brain tumors using CANFIS classification method,
IJIST(29), No. 4, 2019, pp. 431-438.
DOI Link 1911
abnormal, brain, classification, statistical features, tumors BibRef

Gilanie, G.[Ghulam], Bajwa, U.I.[Usama Ijaz], Waraich, M.M.[Mustansar Mahmood], Habib, Z.[Zulfiqar],
Automated and reliable brain radiology with texture analysis of magnetic resonance imaging and cross datasets validation,
IJIST(29), No. 4, 2019, pp. 531-538.
DOI Link 1911
brain tumor diagnosis, cross dataset validation, MRI texture analysis, neoplastic and non-neoplastic tissues, primary and secondary brain tumor BibRef

Tamilmani, G., Sivakumari, S.,
Early detection of brain cancer using association allotment hierarchical clustering,
IJIST(29), No. 4, 2019, pp. 617-632.
DOI Link 1911
association allotment hierarchical clustering, gray wolf optimization, mutual piece-wise linear transformation filtering BibRef

Nalepa, J., Mrukwa, G., Piechaczek, S., Lorenzo, P.R., Marcinkiewicz, M., Bobek-Billewicz, B., Wawrzyniak, P., Ulrych, P., Szymanek, J., Cwiek, M., Dudzik, W., Kawulok, M., Hayball, M.P.,
Data Augmentation via Image Registration,
ICIP19(4250-4254)
IEEE DOI 1910
Deep learning, data augmentation, image registration, brain-tumor segmentation BibRef

Sun, Y., Zhou, C., Fu, Y., Xue, X.,
Parasitic GAN for Semi-Supervised Brain Tumor Segmentation,
ICIP19(1535-1539)
IEEE DOI 1910
Generative adversarial networks, medical image processing, volume segmentation BibRef