171 related articles for article (PubMed ID: 36326937)
1. Grading of gliomas using transfer learning on MRI images.
Fasihi Shirehjini O; Babapour Mofrad F; Shahmohammadi M; Karami F
MAGMA; 2023 Feb; 36(1):43-53. PubMed ID: 36326937
[TBL] [Abstract][Full Text] [Related]
2. 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]
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. Radiomics strategy for glioma grading using texture features from multiparametric MRI.
Tian Q; Yan LF; Zhang X; Zhang X; Hu YC; Han Y; Liu ZC; Nan HY; Sun Q; Sun YZ; Yang Y; Yu Y; Zhang J; Hu B; Xiao G; Chen P; Tian S; Xu J; Wang W; Cui GB
J Magn Reson Imaging; 2018 Dec; 48(6):1518-1528. PubMed ID: 29573085
[TBL] [Abstract][Full Text] [Related]
5. Voxel-based clustered imaging by multiparameter diffusion tensor images for glioma grading.
Inano R; Oishi N; Kunieda T; Arakawa Y; Yamao Y; Shibata S; Kikuchi T; Fukuyama H; Miyamoto S
Neuroimage Clin; 2014; 5():396-407. PubMed ID: 25180159
[TBL] [Abstract][Full Text] [Related]
6. Glioma grading using a machine-learning framework based on optimized features obtained from T
Sengupta A; Ramaniharan AK; Gupta RK; Agarwal S; Singh A
J Magn Reson Imaging; 2019 Oct; 50(4):1295-1306. PubMed ID: 30895704
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. Brain tumor segmentation and grading of lower-grade glioma using deep learning in MRI images.
Naser MA; Deen MJ
Comput Biol Med; 2020 Jun; 121():103758. PubMed ID: 32568668
[TBL] [Abstract][Full Text] [Related]
9. On differentiation between vasogenic edema and non-enhancing tumor in high-grade glioma patients using a support vector machine classifier based upon pre and post-surgery MRI images.
Sengupta A; Agarwal S; Gupta PK; Ahlawat S; Patir R; Gupta RK; Singh A
Eur J Radiol; 2018 Sep; 106():199-208. PubMed ID: 30150045
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. Radiomics-Based Machine Learning Classification for Glioma Grading Using Diffusion- and Perfusion-Weighted Magnetic Resonance Imaging.
Hashido T; Saito S; Ishida T
J Comput Assist Tomogr; 2021 Jul-Aug 01; 45(4):606-613. PubMed ID: 34270479
[TBL] [Abstract][Full Text] [Related]
12. Multi-Classification of Brain Tumors on Magnetic Resonance Images Using an Ensemble of Pre-Trained Convolutional Neural Networks.
Wu M; Liu Q; Yan C; Sen G
Curr Med Imaging; 2022; 19(1):65-76. PubMed ID: 35430973
[TBL] [Abstract][Full Text] [Related]
13. Optimizing a machine learning based glioma grading system using multi-parametric MRI histogram and texture features.
Zhang X; Yan LF; Hu YC; Li G; Yang Y; Han Y; Sun YZ; Liu ZC; Tian Q; Han ZY; Liu LD; Hu BQ; Qiu ZY; Wang W; Cui GB
Oncotarget; 2017 Jul; 8(29):47816-47830. PubMed ID: 28599282
[TBL] [Abstract][Full Text] [Related]
14. Machine-learning in grading of gliomas based on multi-parametric magnetic resonance imaging at 3T.
Citak-Er F; Firat Z; Kovanlikaya I; Ture U; Ozturk-Isik E
Comput Biol Med; 2018 Aug; 99():154-160. PubMed ID: 29933126
[TBL] [Abstract][Full Text] [Related]
15. Imaging biomarker analysis of advanced multiparametric MRI for glioma grading.
Vamvakas A; Williams SC; Theodorou K; Kapsalaki E; Fountas K; Kappas C; Vassiou K; Tsougos I
Phys Med; 2019 Apr; 60():188-198. PubMed ID: 30910431
[TBL] [Abstract][Full Text] [Related]
16. Prediction of malignant glioma grades using contrast-enhanced T1-weighted and T2-weighted magnetic resonance images based on a radiomic analysis.
Nakamoto T; Takahashi W; Haga A; Takahashi S; Kiryu S; Nawa K; Ohta T; Ozaki S; Nozawa Y; Tanaka S; Mukasa A; Nakagawa K
Sci Rep; 2019 Dec; 9(1):19411. PubMed ID: 31857632
[TBL] [Abstract][Full Text] [Related]
17. Noninvasive Isocitrate Dehydrogenase 1 Status Prediction in Grade II/III Glioma Based on Magnetic Resonance Images: A Transfer Learning Strategy.
Zhang J; Wang Y; Yang Y; Han Y; Yu Y; Hu Y; Liang S; Sun Q; Shang D; Bi J; Cui G; Yan L
J Comput Assist Tomogr; 2024 May-Jun 01; 48(3):449-458. PubMed ID: 38271541
[TBL] [Abstract][Full Text] [Related]
18. Automated machine learning to predict the co-occurrence of isocitrate dehydrogenase mutations and O
Zhang S; Sun H; Su X; Yang X; Wang W; Wan X; Tan Q; Chen N; Yue Q; Gong Q
J Magn Reson Imaging; 2021 Jul; 54(1):197-205. PubMed ID: 33393131
[TBL] [Abstract][Full Text] [Related]
19. Optimizing Texture Retrieving Model for Multimodal MR Image-Based Support Vector Machine for Classifying Glioma.
Yang Y; Yan LF; Zhang X; Nan HY; Hu YC; Han Y; Zhang J; Liu ZC; Sun YZ; Tian Q; Yu Y; Sun Q; Wang SY; Zhang X; Wang W; Cui GB
J Magn Reson Imaging; 2019 May; 49(5):1263-1274. PubMed ID: 30623514
[TBL] [Abstract][Full Text] [Related]
20. Postoperative glioma segmentation in CT image using deep feature fusion model guided by multi-sequence MRIs.
Tang F; Liang S; Zhong T; Huang X; Deng X; Zhang Y; Zhou L
Eur Radiol; 2020 Feb; 30(2):823-832. PubMed ID: 31650265
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]