120 related articles for article (PubMed ID: 36039494)
1. Differentiation of benign and malignant spinal schwannoma using guided attention inference networks on multi-source MRI: comparison with radiomics method and radiologist-based clinical assessment.
Cao J; Wang X; Qiao Y; Chen S; Wang P; Sun H; Zhang L; Liu T; Liu S
Acta Radiol; 2023 Mar; 64(3):1184-1193. PubMed ID: 36039494
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. Differentiating Benign from Malignant Renal Tumors Using T2- and Diffusion-Weighted Images: A Comparison of Deep Learning and Radiomics Models Versus Assessment from Radiologists.
Xu Q; Zhu Q; Liu H; Chang L; Duan S; Dou W; Li S; Ye J
J Magn Reson Imaging; 2022 Apr; 55(4):1251-1259. PubMed ID: 34462986
[TBL] [Abstract][Full Text] [Related]
4. Differentiation between spinal multiple myeloma and metastases originated from lung using multi-view attention-guided network.
Chen K; Cao J; Zhang X; Wang X; Zhao X; Li Q; Chen S; Wang P; Liu T; Du J; Liu S; Zhang L
Front Oncol; 2022; 12():981769. PubMed ID: 36158659
[TBL] [Abstract][Full Text] [Related]
5. Bi-parametric magnetic resonance imaging based radiomics for the identification of benign and malignant prostate lesions: cross-vendor validation.
Ji X; Zhang J; Shi W; He D; Bao J; Wei X; Huang Y; Liu Y; Chen JC; Gao X; Tang Y; Xia W
Phys Eng Sci Med; 2021 Sep; 44(3):745-754. PubMed ID: 34075559
[TBL] [Abstract][Full Text] [Related]
6. Value of MRI-based radiomics analysis for differentiation of benign and malignant epithelial neoplasms in the lacrimal gland: a retrospective study.
Guo J; Li Z; Qu X; Xian J
Acta Radiol; 2021 Jun; 62(6):743-751. PubMed ID: 32660315
[TBL] [Abstract][Full Text] [Related]
7. MR-Based Radiomics for Differential Diagnosis between Cystic Pituitary Adenoma and Rathke Cleft Cyst.
Wang Y; Chen S; Shi F; Cheng X; Xu Q; Li J; Luo S; Jiang P; Wei Y; Zhou C; Zheng L; Xia K; Lu G; Zhang Z
Comput Math Methods Med; 2021; 2021():6438861. PubMed ID: 34422095
[TBL] [Abstract][Full Text] [Related]
8. Deep Learning for Automatic Differential Diagnosis of Primary Central Nervous System Lymphoma and Glioblastoma: Multi-Parametric Magnetic Resonance Imaging Based Convolutional Neural Network Model.
Xia W; Hu B; Li H; Shi W; Tang Y; Yu Y; Geng C; Wu Q; Yang L; Yu Z; Geng D; Li Y
J Magn Reson Imaging; 2021 Sep; 54(3):880-887. PubMed ID: 33694250
[TBL] [Abstract][Full Text] [Related]
9. Radiomics Based on Multimodal MRI for the Differential Diagnosis of Benign and Malignant Breast Lesions.
Zhang Q; Peng Y; Liu W; Bai J; Zheng J; Yang X; Zhou L
J Magn Reson Imaging; 2020 Aug; 52(2):596-607. PubMed ID: 32061014
[TBL] [Abstract][Full Text] [Related]
10. Convolutional neural network for discriminating nasopharyngeal carcinoma and benign hyperplasia on MRI.
Wong LM; King AD; Ai QYH; Lam WKJ; Poon DMC; Ma BBY; Chan KCA; Mo FKF
Eur Radiol; 2021 Jun; 31(6):3856-3863. PubMed ID: 33241522
[TBL] [Abstract][Full Text] [Related]
11. Utilization of radiomics to predict long-term outcome of magnetic resonance-guided focused ultrasound ablation therapy in adenomyosis.
Li Z; Zhang J; Song Y; Yin X; Chen A; Tang N; Prince MR; Yang G; Wang H
Eur Radiol; 2021 Jan; 31(1):392-402. PubMed ID: 32725335
[TBL] [Abstract][Full Text] [Related]
12. Differentiation of benign from malignant solid renal lesions with MRI-based radiomics and machine learning.
Massa'a RN; Stoeckl EM; Lubner MG; Smith D; Mao L; Shapiro DD; Abel EJ; Wentland AL
Abdom Radiol (NY); 2022 Aug; 47(8):2896-2904. PubMed ID: 35723716
[TBL] [Abstract][Full Text] [Related]
13. Radiomic versus Convolutional Neural Networks Analysis for Classification of Contrast-enhancing Lesions at Multiparametric Breast MRI.
Truhn D; Schrading S; Haarburger C; Schneider H; Merhof D; Kuhl C
Radiology; 2019 Feb; 290(2):290-297. PubMed ID: 30422086
[TBL] [Abstract][Full Text] [Related]
14. Task-based assessment of a convolutional neural network for segmenting breast lesions for radiomic analysis.
Spuhler KD; Ding J; Liu C; Sun J; Serrano-Sosa M; Moriarty M; Huang C
Magn Reson Med; 2019 Aug; 82(2):786-795. PubMed ID: 30957936
[TBL] [Abstract][Full Text] [Related]
15. Primary central nervous system lymphoma and atypical glioblastoma: Differentiation using radiomics approach.
Suh HB; Choi YS; Bae S; Ahn SS; Chang JH; Kang SG; Kim EH; Kim SH; Lee SK
Eur Radiol; 2018 Sep; 28(9):3832-3839. PubMed ID: 29626238
[TBL] [Abstract][Full Text] [Related]
16. Deep-learning approach with convolutional neural network for classification of maximum intensity projections of dynamic contrast-enhanced breast magnetic resonance imaging.
Fujioka T; Yashima Y; Oyama J; Mori M; Kubota K; Katsuta L; Kimura K; Yamaga E; Oda G; Nakagawa T; Kitazume Y; Tateishi U
Magn Reson Imaging; 2021 Jan; 75():1-8. PubMed ID: 33045323
[TBL] [Abstract][Full Text] [Related]
17. Attention feature fusion methodology with additional constraint for ovarian lesion diagnosis on magnetic resonance images.
Wang S; Xu X; Du H; Chen Y; Mei W
Med Phys; 2023 Jan; 50(1):297-310. PubMed ID: 35975618
[TBL] [Abstract][Full Text] [Related]
18. Ultrasound-based radiomics analysis for differentiating benign and malignant breast lesions: From static images to CEUS video analysis.
Zhu JY; He HL; Lin ZM; Zhao JQ; Jiang XC; Liang ZH; Huang XP; Bao HW; Huang PT; Chen F
Front Oncol; 2022; 12():951973. PubMed ID: 36185229
[TBL] [Abstract][Full Text] [Related]
19. Distinction between benign and malignant breast masses at breast ultrasound using deep learning method with convolutional neural network.
Fujioka T; Kubota K; Mori M; Kikuchi Y; Katsuta L; Kasahara M; Oda G; Ishiba T; Nakagawa T; Tateishi U
Jpn J Radiol; 2019 Jun; 37(6):466-472. PubMed ID: 30888570
[TBL] [Abstract][Full Text] [Related]
20. Computer-aided diagnosis of ground glass pulmonary nodule by fusing deep learning and radiomics features.
Hu X; Gong J; Zhou W; Li H; Wang S; Wei M; Peng W; Gu Y
Phys Med Biol; 2021 Mar; 66(6):065015. PubMed ID: 33596552
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]