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Advanced Machine Learning for Brain Tumor and Alzheimer’s Disease Detection: A Comprehensive Review of Neuroimaging-based Classification Techniques

Cilt: 4 Sayı: 2 30 Aralık 2024
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Advanced Machine Learning for Brain Tumor and Alzheimer’s Disease Detection: A Comprehensive Review of Neuroimaging-based Classification Techniques

Öz

Alzheimer's disease with progressive neurodegeneration and brain tumors notably characterized by rapid, not limited cell proliferation poses significant health risks unless timely diagnosed and treated. Tumors have a diverse feature and characteristics, added to subtle changes in the brain whose hallmark is Alzheimer's, making accurate segmentation and classification quite challenging. Indeed, while there have been research in the last decade or so that have proven promising results, challenges still linger on. The present work discusses various approaches for image classification and staging of Alzheimer's disease and brain tumors by exploiting techniques in statistical image processing and computational intelligence. This paper includes discussion on morphology of brain tumors along with neuroimaging changes caused by Alzheimer's disease, existing datasets, data augmentation techniques, and methods for component extraction and classification within the DL, TL, and ML framework. Such specific systems have been given the metrics using the datasets; the descriptions of the implementations, however may vary with the case at hand.

Anahtar Kelimeler

Kaynakça

  1. Yadav, S. S., & Jadhav, S. M. (2019). Deep convolutional neural network based medical image classification for disease diagnosis. Journal of Big Data, 6(1), 1-18.
  2. Irmak, E. (2021). Multi-Classification of Brain Tumor MRI Images Using Deep Convolutional Neural Network with Fully Optimized Framework. Electronics, 10(2), 184.
  3. Wen, J., Thibeau-Sutre, E., Diaz-Melo, M., Samper-Gonzalez, J., Routier, A., Bottani, S., ... & Colliot, O. (2020). Convolutional neural networks for classification of Alzheimer's disease: Overview and reproducible evaluation. Medical Image Analysis, 63, 101694.
  4. Mehmood, A., Yang, S., Feng, Z., Wang, M., Ahmad, A. S., Khan, R., ... & Yaqub, M. (2021). A transfer learning approach for early diagnosis of Alzheimer's disease on MRI images. Neuroscience, 460, 43-52.
  5. Xie, X. (2021). Deep learning-based image classification of MRI brain image. College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China.
  6. Singh, J., Singh, A., Singh, K. K., Lal, B., William, R. A., Turukmane, A. V., & Kumar, A. (2021). Identification of Brain Diseases using Image Classification: A Deep Learning Approach.
  7. Woźniak, M., Siłka, J., & Wieczorek, M. (2021). Deep neural network correlation learning mechanism for CT brain tumor detection. Neural Computing and Applications, 33(4), 1143-1155.
  8. Noreen, N., Palaniappan, S., Qayyum, A., Ahmad, I., Imran, M., & Shoaib, M. (2020). A deep learning model based on a concatenation approach for the diagnosis of brain tumor. IEEE Access, 8, 55135-55144.

Ayrıntılar

Birincil Dil

İngilizce

Konular

Görüntü İşleme

Bölüm

İnceleme Makalesi

Yayımlanma Tarihi

30 Aralık 2024

Gönderilme Tarihi

9 Kasım 2024

Kabul Tarihi

28 Aralık 2024

Yayımlandığı Sayı

Yıl 2024 Cilt: 4 Sayı: 2

Kaynak Göster

APA
Kumar, N., Narawade, V., Chheda, K., Patkar, H., & Mishra, A. (2024). Advanced Machine Learning for Brain Tumor and Alzheimer’s Disease Detection: A Comprehensive Review of Neuroimaging-based Classification Techniques. Advances in Artificial Intelligence Research, 4(2), 62-68. https://doi.org/10.54569/aair.1582085
AMA
1.Kumar N, Narawade V, Chheda K, Patkar H, Mishra A. Advanced Machine Learning for Brain Tumor and Alzheimer’s Disease Detection: A Comprehensive Review of Neuroimaging-based Classification Techniques. Adv. Artif. Intell. Res. 2024;4(2):62-68. doi:10.54569/aair.1582085
Chicago
Kumar, Naman, Vaibhav Narawade, Kanish Chheda, Harisha Patkar, ve Aniket Mishra. 2024. “Advanced Machine Learning for Brain Tumor and Alzheimer’s Disease Detection: A Comprehensive Review of Neuroimaging-based Classification Techniques”. Advances in Artificial Intelligence Research 4 (2): 62-68. https://doi.org/10.54569/aair.1582085.
EndNote
Kumar N, Narawade V, Chheda K, Patkar H, Mishra A (01 Aralık 2024) Advanced Machine Learning for Brain Tumor and Alzheimer’s Disease Detection: A Comprehensive Review of Neuroimaging-based Classification Techniques. Advances in Artificial Intelligence Research 4 2 62–68.
IEEE
[1]N. Kumar, V. Narawade, K. Chheda, H. Patkar, ve A. Mishra, “Advanced Machine Learning for Brain Tumor and Alzheimer’s Disease Detection: A Comprehensive Review of Neuroimaging-based Classification Techniques”, Adv. Artif. Intell. Res., c. 4, sy 2, ss. 62–68, Ara. 2024, doi: 10.54569/aair.1582085.
ISNAD
Kumar, Naman - Narawade, Vaibhav - Chheda, Kanish - Patkar, Harisha - Mishra, Aniket. “Advanced Machine Learning for Brain Tumor and Alzheimer’s Disease Detection: A Comprehensive Review of Neuroimaging-based Classification Techniques”. Advances in Artificial Intelligence Research 4/2 (01 Aralık 2024): 62-68. https://doi.org/10.54569/aair.1582085.
JAMA
1.Kumar N, Narawade V, Chheda K, Patkar H, Mishra A. Advanced Machine Learning for Brain Tumor and Alzheimer’s Disease Detection: A Comprehensive Review of Neuroimaging-based Classification Techniques. Adv. Artif. Intell. Res. 2024;4:62–68.
MLA
Kumar, Naman, vd. “Advanced Machine Learning for Brain Tumor and Alzheimer’s Disease Detection: A Comprehensive Review of Neuroimaging-based Classification Techniques”. Advances in Artificial Intelligence Research, c. 4, sy 2, Aralık 2024, ss. 62-68, doi:10.54569/aair.1582085.
Vancouver
1.Naman Kumar, Vaibhav Narawade, Kanish Chheda, Harisha Patkar, Aniket Mishra. Advanced Machine Learning for Brain Tumor and Alzheimer’s Disease Detection: A Comprehensive Review of Neuroimaging-based Classification Techniques. Adv. Artif. Intell. Res. 01 Aralık 2024;4(2):62-8. doi:10.54569/aair.1582085

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