An efficient brain tumor classification using MRI images with hybrid deep intelligence model

References

• Saranya C, Priya JG, Jayalakshmi P, et al. Brain tumor identification using deep learning. Mater Today Proc. 2021 Jan 3;1279:1–7.
   Google Scholar
• Shahvaran Z, Kazemi K, Fouladivanda M, et al. Morphological active contour model for automatic brain tumor extraction from multimodal magnetic resonance images. J Neurosci Methods. 2021;362:109296.
   PubMed Web of Science ®Google Scholar
• Ghahfarrokhi SS, Khodadadi H. Human brain tumor diagnosis using the combination of the complexity measures and texture features through magnetic resonance image. Biomed Signal Process Control. 2020;61:102025.
   Web of Science ®Google Scholar
• Al-Saffar ZA, Yildirim T. A hybrid approach based on multiple eigenvalues selection (MES) for the automated grading of a brain tumor using MRI. Comput Methods Programs Biomed. 2021;201:105945.
   PubMed Web of Science ®Google Scholar
• Ramkumar G, Prabu RT, Singh NP, et al. Experimental analysis of brain tumor detection system using machine learning approach. Mater Today Proc. 2021 Feb 25.
   Google Scholar
• Badshah N, Rabbani H, Atta H. On local active contour model for automatic detection of tumor in MRI and mammogram images. Biomed Signal Process Control. 2020;60:101993.
   Web of Science ®Google Scholar
• Alsattar HA, Zaidan AA, Zaidan BB. Novel meta-heuristic bald eagle search optimisation algorithm. Artif Intell Rev. 2020;53(3):2237–2264.
   Web of Science ®Google Scholar
• Rai HM, Chatterjee K, Dashkevich S. Automatic and accurate abnormality detection from brain MR images using a novel hybrid UnetResNext-50 deep CNN model. Biomed Signal Process Control. 2021;66:102477.
   Web of Science ®Google Scholar
• Essadike A, Ouabida E, Bouzid A. Optical scanning holography for tumor extraction from brain magnetic resonance images. Opt Laser Technol. 2020;127:106158.
   Web of Science ®Google Scholar
• Barzegar Z, Jamzad M. WLFS: weighted label fusion learning framework for glioma tumor segmentation in brain MRI. Biomed Signal Process Control. 2021;68:102617.
   Web of Science ®Google Scholar
• Naser MA, Deen MJ. Brain tumor segmentation and grading of lower-grade glioma using deep learning in MRI images. Comput Biol Med. 2020;121:103758.
   PubMed Web of Science ®Google Scholar
• Mahmood M, Al-Khateeb B. The blue monkey: a new nature inspired metaheuristic optimization algorithm. Periodicals Eng Nat Sci (PEN). 2019;7(3):1054–1066.
   Google Scholar
• Hashemzehi R, Mahdavi SJ, Kheirabadi M, et al. Detection of brain tumors from MRI images base on deep learning using hybrid model CNN and NADE. Biocybernetics Biomed Eng. 2020;40(3):1225–1232.
   Web of Science ®Google Scholar
• Aghalari M, Aghagolzadeh A, Ezoji M. Brain tumor image segmentation via asymmetric/symmetric UNet based on two-pathway-residual blocks. Biomed Signal Process Control. 2021;69:102841.
   Web of Science ®Google Scholar
• Rammurthy D, Mahesh PK. Whale Harris hawks optimization based deep learning classifier for brain tumor detection using MRI images. J King Saud Univ-Comput Inf Sci. 2020 Aug 15;34:3259–3272.
   Web of Science ®Google Scholar
• Harish P, Baskar S. MRI based detection and classification of brain tumor using enhanced faster R-CNN and Alex net model. Mater Today Proc. 2020 Dec 30.
   Google Scholar
• Çinar A, Yildirim M. Detection of tumors on brain MRI images using the hybrid convolutional neural network architecture. Med Hypotheses. 2020;139:109684.
   PubMed Web of Science ®Google Scholar
• Sabitha V, Nayak J, Reddy PR. MRI brain tumor detection and classification using KPCA and KSVM. Mater Today Proc. 2021 Mar 4.
   Google Scholar
• Sivakumar V, Janakiraman N. A novel method for segmenting brain tumor using modified watershed algorithm in MRI image with FPGA. Biosystems. 2020;198:104226.
   PubMed Web of Science ®Google Scholar
• Islam MK, Ali MS, Miah MS, et al. Brain tumor detection in MR image using superpixels, principal component analysis and template based K-means clustering algorithm. Mach Learn Appl. 2021;5:100044.
   Google Scholar
• Khairandish MO, Sharma M, Jain V, et al. A hybrid CNN-SVM threshold segmentation approach for tumor detection and classification of MRI brain images. IRBM. 2021 Jun 11;43:290–299.
   Web of Science ®Google Scholar
• Kesav N, Jibukumar MG. Efficient and low complex architecture for detection and classification of brain tumor using RCNN with two channel CNN. Journal King Saud Univ-Comput Inf Sci. 2021;34:6229–6242.
   Web of Science ®Google Scholar
• Aamir M, Rahman Z, Dayo ZA, et al. A deep learning approach for brain tumor classification using MRI images. Comput Electr Eng. 2022;101:108105.
   Web of Science ®Google Scholar
• Mehnatkesh H, Jalali SM, Khosravi A, et al. An intelligent driven deep residual learning framework for brain tumor classification using MRI images. Expert Syst Appl. 2023;213:119087.
   Web of Science ®Google Scholar
• https://paperswithcode.com/method/u-net.
   Google Scholar
• Hafiane A, Palaniappan K, Seetharaman G. Joint adaptive median binary patterns for texture classification. Pattern Recognit. 2015;48(8):2609–2620.
   Web of Science ®Google Scholar
• Ishraque SZ, Banna AH, Chae O. Local Gabor directional pattern for facial expression recognition). 2012 15th international conference on computer and information technology (ICCIT); 2012 (pp. 164-167); IEEE.
   Google Scholar
• Shabat AM, Tapamo JR. Angled local directional pattern for texture analysis with an application to facial expression recognition. IET Comput Vision. 2018;12(5):603–608.
   Web of Science ®Google Scholar
• Zheng X, Chen W. An attention-based Bi-LSTM method for visual object classification via EEG. Biomed Signal Process Control. 2021;63:102174.
   Web of Science ®Google Scholar
• https://medium.datadriveninvestor.com/deep-learning-deep-belief-network-dbn-ab715b5b8afc.
   Google Scholar
• https://paperswithcode.com/dataset/brats-2015-1.
   Google Scholar
• Abualigah L, Diabat A, Mirjalili S, et al. The arithmetic optimization algorithm. Comput Methods Appl Mech Eng. 2021;376:113609.
   Web of Science ®Google Scholar
• Chengtian O, Yujia L, Donglin Z. An adaptive chaotic sparrow search optimization algorithm). 2021 IEEE 2nd international conference on Big data, artificial intelligence and internet of things engineering (ICBAIE); 2021 Mar 26 (pp. 76-82); IEEE.
   Google Scholar