705 related articles for article (PubMed ID: 36691030)
1. MRI-based brain tumor detection using convolutional deep learning methods and chosen machine learning techniques.
Saeedi S; Rezayi S; Keshavarz H; R Niakan Kalhori S
BMC Med Inform Decis Mak; 2023 Jan; 23(1):16. PubMed ID: 36691030
[TBL] [Abstract][Full Text] [Related]
2. A dual autoencoder and singular value decomposition based feature optimization for the segmentation of brain tumor from MRI images.
Aswani K; Menaka D
BMC Med Imaging; 2021 May; 21(1):82. PubMed ID: 33985449
[TBL] [Abstract][Full Text] [Related]
3. Tumor Diagnosis against Other Brain Diseases Using T2 MRI Brain Images and CNN Binary Classifier and DWT.
Papadomanolakis TN; Sergaki ES; Polydorou AA; Krasoudakis AG; Makris-Tsalikis GN; Polydorou AA; Afentakis NM; Athanasiou SA; Vardiambasis IO; Zervakis ME
Brain Sci; 2023 Feb; 13(2):. PubMed ID: 36831891
[TBL] [Abstract][Full Text] [Related]
4. A Hybrid Approach Based on Deep CNN and Machine Learning Classifiers for the Tumor Segmentation and Classification in Brain MRI.
Haq EU; Jianjun H; Huarong X; Li K; Weng L
Comput Math Methods Med; 2022; 2022():6446680. PubMed ID: 36035291
[TBL] [Abstract][Full Text] [Related]
5. Automated glioma grading on conventional MRI images using deep convolutional neural networks.
Zhuge Y; Ning H; Mathen P; Cheng JY; Krauze AV; Camphausen K; Miller RW
Med Phys; 2020 Jul; 47(7):3044-3053. PubMed ID: 32277478
[TBL] [Abstract][Full Text] [Related]
6. An Efficient Multi-Scale Convolutional Neural Network Based Multi-Class Brain MRI Classification for SaMD.
Yazdan SA; Ahmad R; Iqbal N; Rizwan A; Khan AN; Kim DH
Tomography; 2022 Jul; 8(4):1905-1927. PubMed ID: 35894026
[TBL] [Abstract][Full Text] [Related]
7. A Novel Method for Classifying Liver and Brain Tumors Using Convolutional Neural Networks, Discrete Wavelet Transform and Long Short-Term Memory Networks.
Kutlu H; Avcı E
Sensors (Basel); 2019 Apr; 19(9):. PubMed ID: 31035406
[TBL] [Abstract][Full Text] [Related]
8. A New Deep Hybrid Boosted and Ensemble Learning-Based Brain Tumor Analysis Using MRI.
Zahoor MM; Qureshi SA; Bibi S; Khan SH; Khan A; Ghafoor U; Bhutta MR
Sensors (Basel); 2022 Apr; 22(7):. PubMed ID: 35408340
[TBL] [Abstract][Full Text] [Related]
9. Brain Tumor/Mass Classification Framework Using Magnetic-Resonance-Imaging-Based Isolated and Developed Transfer Deep-Learning Model.
Alanazi MF; Ali MU; Hussain SJ; Zafar A; Mohatram M; Irfan M; AlRuwaili R; Alruwaili M; Ali NH; Albarrak AM
Sensors (Basel); 2022 Jan; 22(1):. PubMed ID: 35009911
[TBL] [Abstract][Full Text] [Related]
10. Timely Diagnosis of Acute Lymphoblastic Leukemia Using Artificial Intelligence-Oriented Deep Learning Methods.
Rezayi S; Mohammadzadeh N; Bouraghi H; Saeedi S; Mohammadpour A
Comput Intell Neurosci; 2021; 2021():5478157. PubMed ID: 34804144
[TBL] [Abstract][Full Text] [Related]
11. Brain tumor classification for MRI images using dual-discriminator conditional generative adversarial network.
Selvi T K; Sumaiya Begum A; Poonkuzhali P; Aarthi R
Electromagn Biol Med; 2024 Apr; 43(1-2):81-94. PubMed ID: 38461438
[TBL] [Abstract][Full Text] [Related]
12. An enhanced deep learning approach for brain cancer MRI images classification using residual networks.
Abdelaziz Ismael SA; Mohammed A; Hefny H
Artif Intell Med; 2020 Jan; 102():101779. PubMed ID: 31980109
[TBL] [Abstract][Full Text] [Related]
13. A Deep Convolutional Neural Network With Performance Comparable to Radiologists for Differentiating Between Spinal Schwannoma and Meningioma.
Maki S; Furuya T; Horikoshi T; Yokota H; Mori Y; Ota J; Kawasaki Y; Miyamoto T; Norimoto M; Okimatsu S; Shiga Y; Inage K; Orita S; Takahashi H; Suyari H; Uno T; Ohtori S
Spine (Phila Pa 1976); 2020 May; 45(10):694-700. PubMed ID: 31809468
[TBL] [Abstract][Full Text] [Related]
14. A methodological approach for deep learning to distinguish between meningiomas and gliomas on canine MR-images.
Banzato T; Bernardini M; Cherubini GB; Zotti A
BMC Vet Res; 2018 Oct; 14(1):317. PubMed ID: 30348148
[TBL] [Abstract][Full Text] [Related]
15. Brain tumor detection from images and comparison with transfer learning methods and 3-layer CNN.
Khaliki MZ; Başarslan MS
Sci Rep; 2024 Feb; 14(1):2664. PubMed ID: 38302604
[TBL] [Abstract][Full Text] [Related]
16. Refining neural network algorithms for accurate brain tumor classification in MRI imagery.
Alshuhail A; Thakur A; Chandramma R; Mahesh TR; Almusharraf A; Vinoth Kumar V; Khan SB
BMC Med Imaging; 2024 May; 24(1):118. PubMed ID: 38773391
[TBL] [Abstract][Full Text] [Related]
17. A hybrid deep CNN model for brain tumor image multi-classification.
Srinivasan S; Francis D; Mathivanan SK; Rajadurai H; Shivahare BD; Shah MA
BMC Med Imaging; 2024 Jan; 24(1):21. PubMed ID: 38243215
[TBL] [Abstract][Full Text] [Related]
18. Chaotic Harris Hawks Optimization with Quasi-Reflection-Based Learning: An Application to Enhance CNN Design.
Basha J; Bacanin N; Vukobrat N; Zivkovic M; Venkatachalam K; Hubálovský S; Trojovský P
Sensors (Basel); 2021 Oct; 21(19):. PubMed ID: 34640973
[TBL] [Abstract][Full Text] [Related]
19. Deep learning approaches using 2D and 3D convolutional neural networks for generating male pelvic synthetic computed tomography from magnetic resonance imaging.
Fu J; Yang Y; Singhrao K; Ruan D; Chu FI; Low DA; Lewis JH
Med Phys; 2019 Sep; 46(9):3788-3798. PubMed ID: 31220353
[TBL] [Abstract][Full Text] [Related]
20. Self-attention-based generative adversarial network optimized with color harmony algorithm for brain tumor classification.
S SP; A S; T K; S D
Electromagn Biol Med; 2024 Apr; 43(1-2):31-45. PubMed ID: 38369844
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]