References
- Abiwinanda N, Hanif M, Hesaputra ST, Handayani A, Mengko TR (2019) Brain tumor classification using convolutional neuralnetwork. IFMBE Proc 68(1):183-189. https://doi.org/10.1007/978-981-10-9035-6_33
- Ayadi W, Elhamzi W, Charfi I, Atri M (2021) Deep CNN for brain tumor classification. Neural Process Lett 53(1):671-700. https://doi.org/10.1007/s11063-020-10398-2
- Badza MM, Barjaktarovic MC (2020) Classification of brain tumors from MRI images using a convolutional neural network. Appl Sci 10(6):1-13. https://doi.org/10.3390/app10061999
- Barboriak D (2015) Data from RIDER_NEURO_MRI. Cancer Imag Arch. https://doi.org/10.7937/K9/TCIA.2015.VOSN3HN1
- Cheng J, Huang W, Cao S, Yang R, Yang W, Yun Z, Wang Z, Feng Q (2015) Enhanced performance of brain tumor classification via tumor region augmentation and partition. PLoS ONE 10(10):1-13. https://doi.org/10.1371/journal.pone.0140381
- Cinar A, Yildirim M (2020) Detection of tumors on brain MRI images using the hybrid convolutional neural network architecture. Med Hypotheses 139:109684. https://doi.org/10.1016/j.mehy.2020.109684.
- Clark K, Vendt B, Smith K, Freymann J, Kirb J, Koppel P, Moore S,Phillips S, Maffitt D, Pringle M (2013) The cancer imaging archive (TCIA): Maintaining and operating a public information repository. J Digit Imag 26(6):1045-1057. https://doi.org/10.1007/s10278-013-9622-7
- Deepak S, Ameer P (2019) Brain tumor classification using deep CNN features via transfer learning. Comput Biol Med111:103345. https://doi.org/10.1016/j.compbiomed.2019.103345
- Dogantekin A, Ozyurt F, Avci E, Koc, M (2019) A novel approach for liver image classification PH-C-ELM. Measurement137:332-338. https://doi.org/10.1016/j.measurement.2019.01.060
- El-Dahshan ESA, Hosny T, Salem ABM (2010) Hybrid intelligent techniques for MRI brain images classification. Digital Signal Process 20(2):433-441. https://doi.org/10.1016/j.dsp.2009.07.002
- Ertosun MG, Rubin DL (2015) Automated grading of gliomas using deep learning in digital pathology images: a modular approach with ensemble of convolutional neural networks. Annu Symp Proc AMIA Symp 2015:1899-1908
- Kabir Anaraki A, Ayati M, Kazemi F (2019) Magnetic Resonance imaging-based brain tumor grades classification and grading via convolutional neural networks and genetic algorithms. Biocybern Biomed Eng39(1):63-74.https://doi.org/10.1016/j.bbe.2018.10.004
- Khan HA, Jue W, Mushtaq M, Mushtaq MU (2020) Brain tumor classification in MRI image using convolutional neural network Math Biosci Eng 17(5):6203-6216. https://doi.org/10.3934/MBE.2020328
- Khawaldeh S, Pervaiz U, Rafiq A, Alkhawaldeh RS (2017) Noninvasivegrading of glioma tumor using magnetic resonanceimaging with convolutional neural networks. ApplSci8(1):1-17. https://doi.org/10.3390/app8010027
- Kleihues P, Burger PC, Scheithauer BW (2012) Histological typing oftumours of the central nervous system, 2nd edn. Springer, Berlin
- Lisa S, Flanders Adam E, Mikkelsen JR, Tom Andrews DW (2015)Data From REMBRANDT. Cancer Imag Arch. https://doi.org/10.7937/K9/TCIA.2015.588OZUZB
- Litjens G, Kooi T, Bejnordi BE, Setio AAA, Ciompi F, Ghafoorian M, Vander Laak JAWM, Van Ginneken B, Sa'nchez CI (2017) Asurvey on deep learning in medical image analysis. Med Image Anal 42:60-88. https://doi.org/10.1016/j.media.2017.07.005
- Lotan E, Jain R, Razavian N, Fatterpekar GM, Lui YW (2019) Stateof the art: Machine learning applications in glioma imaging. Am J Roentgenol 212(1):26-37 https://doi.org/10.2214/ajr.18.20218
- Mehmood A, Maqsood M, Bashir M, Shuyuan Y (2020) A deepsiamese convolution neural network for multi-class classificationof alzheimer disease. Brain Sci 10(2):1-15. https://doi.org/10.3390/brainsci10020084
- Mehmood A, Yang S, Feng Z, Wang M, Ahmad ALS, Khan R, Maqsood M, Yaqub M (2021) A transfer learning approach forearly diagnosis of alzheimer's disease on MRI images. Neuroscience15(460):43-52. https://doi.org/10.1016/j.neuroscience.2021.01.002
- Mehrotra R, Ansari MA, Agrawal R, Anand RS (2020) A Transferlearning approach for AI-based classification of brain tumors.Mach Learn Appl 2(9):1-12. https://doi.org/10.1016/j.mlwa.2020.100003
- Mohsen H, El-Dahshan ESA, El-Horbaty ESM, Salem ABM (2018)Classification using deep learning neural networks for braintumors. Future Comput Informat J 3(1):68-71. https://doi.org/10.1016/j.fcij.2017.12.001
- Muhammad K, Khan S, Ser JD, Albuquerque VHC (2021) Deeplearning for multigrade brain tumor classification in smarthealthcare systems: a prospective survey. IEEE Trans Neural Netw Learn Syst 32(2):507-522. https://doi.org/10.1109/TNNLS.2020.2995800
- Mzoughi H, Njeh I, Wali A, Slima M, Ben Ben Hamida A, Mhiri C, Mahfoudhe K (2020) Deep Multi-Scale 3D convolutional neuralnetwork (CNN) for MRI gliomas brain tumor classification. J Digit Imag 33(4):903-915. https://doi.org/10.1007/s10278-020-00347-9
- Ozyurt F, Sert E, Avci E, Dogantekin E (2019) Brain tumor detectionbased on Convolutional Neural Network with neutrosophicexpert maximum fuzzy sure entropy. Measurement147(106803):1-7. https://doi.org/10.1016/j.measurement.2019.07.058
- Papageorgiou EI, Spyridonos PP, Glotsos DT, Stylios CD, Ravazoula P, Nikiforidis GN, Groumpos PP (2008) Brain tumor characterizationusing the soft computing technique of fuzzy cognitivemaps. Appl Soft Comput J 8(1):820-828. https://doi.org/10.1016/j.asoc.2007.06.006
- Pedano N, Flanders AE, Scarpace L, Mikkelsen T, Eschbacher JM, Hermes B, Ostrom Q (2016) Radiology data from the cancergenome atlas low grade glioma [TCGA-LGG] collection. CancerImag Arch. https://doi.org/10.7937/K9/TCIA.2016.L4LTD3TK
- Pereira S, Meier R, Alves V, Reyes M, Silva CA (2018) Automaticbrain tumor grading from MRI data using convolutional neuralnetworks and quality assessment. Understanding and interpretingmachine learning in medical image computing applications.Springer, Cham, pp 106-114
- Rehman A, Naz S, Razzak MI, Akram F, Imran M (2020) A Deep Learning-based framework for automatic brain tumors classification using transfer learning. Circuits, Syst, Signal Process 39(2):757-775. https://doi.org/10.1007/s00034-019-01246-3
- Sajjad M, Khan S, Muhammad K, Wu W, Ullah A, Baik SW (2019) Multi-grade brain tumor classification using deep CNN with extensive data augmentation. J Comput Sci 30:174-182. https://doi.org/10.1016/j.jocs.2018.12.003
- Seetha J, Raja SS (2018) Brain tumor classification using convolutional neural networks. Biomed Pharmacol J 11(3):1457-1461 https://doi.org/10.13005/bpj/1511
- Shaver MM, Kohanteb PA, Chiou C, Bardis MD, Chantaduly C, Bota D, Filippi CG, Weinberg B, Grinband J, Chow DS, Chang PD (2019) Optimizing neuro-oncology imaging: a review of deep learning approaches for glioma imaging. Cancers 11(6):1-14. https://doi.org/10.3390/cancers11060829
- Shirazi AZ, Fornaciari E, McDonnell MD, Yaghoobi M, Cevallos Y, Tello-Oquendo L, Inca D, Gomez GA (2020) The application of deep convolutional neural networks to brain cancer images: A survey. J Personal Med 10(4):1-27. https://doi.org/10.3390/jpm10040224
- Sultan HH, Salem NM, Al-Atabany W (2019) Multi-classification of brain tumor images using deep neural network. IEEE Access 7:69215-69225. https://doi.org/10.1109/ACCESS.2019.2919122
- Talo M, Baloglu UB, Yildirim O, Rajendra Acharya U (2019) Application of deep transfer learning for automated brainabnormality classification using MR images. Cogn Syst Res 54(12):176-188. https://doi.org/10.1016/j.cogsys.2018.12.007
- Tandel GS, Biswas M, Kakde OG, Tiwari A, Suri HS, Turk M, Laird JR, Asare CK, Ankrah AA, Khanna NN, Madhusudhan BK, Saba L, Suri JS (2019) A review on a deep learning perspective in brain cancer classification. Cancers 11(1):1-32. https://doi.org/10.3390/cancers11010111
- Tiwari A, Srivastava S, Pant M (2020) Brain tumor segmentation and classification from magnetic resonance images: review ofselected methods from 2014 to 2019. Pattern Recogn Lett 131:244-260. https://doi.org/10.1016/j.patrec.2019.11.020
- Yaqub M, Jinchao F, Zia MS, Arshid K, Jia K, Rehman ZU, Mehmood A (2020) State-of-the-art CNN optimizer for braintumor segmentation in magnetic resonance images. Brain Sci 10(7):1-19. https://doi.org/10.3390/brainsci10070427
- Yang Y, Yan LF, Zhang X, Han Y, Nan HY, Hu YC, Hu B, Yan SL, Zhang J, Cheng DL, Ge XW (2018) Glioma grading onconventional MR images: a deep learning study with transferlearning. Front Neurosci 12:804. https://doi.org/10.3389/fnins.2018.00804