137 related articles for article (PubMed ID: 36797331)
21. Development and Validation of a Deep Learning-Based Model to Distinguish Glioblastoma from Solitary Brain Metastasis Using Conventional MR Images.
Shin I; Kim H; Ahn SS; Sohn B; Bae S; Park JE; Kim HS; Lee SK
AJNR Am J Neuroradiol; 2021 May; 42(5):838-844. PubMed ID: 33737268
[TBL] [Abstract][Full Text] [Related]
22. Deep learning for fully automated tumor segmentation and extraction of magnetic resonance radiomics features in cervical cancer.
Lin YC; Lin CH; Lu HY; Chiang HJ; Wang HK; Huang YT; Ng SH; Hong JH; Yen TC; Lai CH; Lin G
Eur Radiol; 2020 Mar; 30(3):1297-1305. PubMed ID: 31712961
[TBL] [Abstract][Full Text] [Related]
23. Detection and Segmentation of Pelvic Bones Metastases in MRI Images for Patients With Prostate Cancer Based on Deep Learning.
Liu X; Han C; Cui Y; Xie T; Zhang X; Wang X
Front Oncol; 2021; 11():773299. PubMed ID: 34912716
[TBL] [Abstract][Full Text] [Related]
24. Deep learning-based high-accuracy detection for lumbar and cervical degenerative disease on T2-weighted MR images.
Yi W; Zhao J; Tang W; Yin H; Yu L; Wang Y; Tian W
Eur Spine J; 2023 Nov; 32(11):3807-3814. PubMed ID: 36943484
[TBL] [Abstract][Full Text] [Related]
25. Quantitative dynamic contrast-enhanced MR imaging for differentiating benign, borderline, and malignant ovarian tumors.
Li HM; Feng F; Qiang JW; Zhang GF; Zhao SH; Ma FH; Li YA; Gu WY
Abdom Radiol (NY); 2018 Nov; 43(11):3132-3141. PubMed ID: 29556691
[TBL] [Abstract][Full Text] [Related]
26. A computerized diagnostic model for automatically evaluating placenta accrete spectrum disorders based on the combined MR radiomics-clinical signatures.
Zhu H; Yin X; Wang H; Wang Y; Liu X; Wang C; Li X; Lu Y; Yang G; Zhang H
Sci Rep; 2022 Jun; 12(1):10130. PubMed ID: 35710881
[TBL] [Abstract][Full Text] [Related]
27. Borderline ovarian tumors: Guidelines from the French national college of obstetricians and gynecologists (CNGOF).
Bourdel N; Huchon C; Abdel Wahab C; Azaïs H; Bendifallah S; Bolze PA; Brun JL; Canlorbe G; Chauvet P; Chereau E; Courbiere B; De La Motte Rouge T; Devouassoux-Shisheboran M; Eymerit-Morin C; Fauvet R; Gauroy E; Gauthier T; Grynberg M; Koskas M; Larouzee E; Lecointre L; Levêque J; Margueritte F; Mathieu D'argent E; Nyangoh-Timoh K; Ouldamer L; Raad J; Raimond E; Ramanah R; Rolland L; Rousset P; Rousset-Jablonski C; Thomassin-Naggara I; Uzan C; Zilliox M; Daraï E
Eur J Obstet Gynecol Reprod Biol; 2021 Jan; 256():492-501. PubMed ID: 33262005
[TBL] [Abstract][Full Text] [Related]
28. 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]
29. Automatic segmentation of magnetic resonance images for high-dose-rate cervical cancer brachytherapy using deep learning.
Yoganathan SA; Paul SN; Paloor S; Torfeh T; Chandramouli SH; Hammoud R; Al-Hammadi N
Med Phys; 2022 Mar; 49(3):1571-1584. PubMed ID: 35094405
[TBL] [Abstract][Full Text] [Related]
30. Differentiation of borderline tumors from type I ovarian epithelial cancers on CT and MR imaging.
Yang S; Tang H; Xiao F; Zhu J; Hua T; Tang G
Abdom Radiol (NY); 2020 Oct; 45(10):3230-3238. PubMed ID: 32162020
[TBL] [Abstract][Full Text] [Related]
31. The enhanced T
Han X; Sun M; Wang M; Fan R; Chen D; Xie L; Liu A
Eur J Radiol; 2019 Sep; 118():187-193. PubMed ID: 31439240
[TBL] [Abstract][Full Text] [Related]
32. Automatic segmentation of rectal tumor on diffusion-weighted images by deep learning with U-Net.
Zhu HT; Zhang XY; Shi YJ; Li XT; Sun YS
J Appl Clin Med Phys; 2021 Sep; 22(9):324-331. PubMed ID: 34343402
[TBL] [Abstract][Full Text] [Related]
33. [Borderline Ovarian Tumours: CNGOF Guidelines for Clinical Practice - Imaging].
Abdel Wahab C; Rousset P; Bolze PA; Thomassin-Naggara I
Gynecol Obstet Fertil Senol; 2020 Mar; 48(3):260-276. PubMed ID: 32004779
[TBL] [Abstract][Full Text] [Related]
34. MR imaging of epithelial ovarian cancer: a combined model to predict histologic subtypes.
Qian L; Ren J; Liu A; Gao Y; Hao F; Zhao L; Wu H; Niu G
Eur Radiol; 2020 Nov; 30(11):5815-5825. PubMed ID: 32535738
[TBL] [Abstract][Full Text] [Related]
35. Differentiation of Seromucinous Borderline Tumor from Serous Borderline Tumor on MR Imaging.
Kurata Y; Kido A; Moribata Y; Kameyama K; Minamiguchi S; Konishi I; Togashi K
Magn Reson Med Sci; 2018 Jul; 17(3):211-217. PubMed ID: 28993546
[TBL] [Abstract][Full Text] [Related]
36. AI-Based Automated Lipomatous Tumor Segmentation in MR Images: Ensemble Solution to Heterogeneous Data.
Liu CC; Abdelhafez YG; Yap SP; Acquafredda F; Schirò S; Wong AL; Sarohia D; Bateni C; Darrow MA; Guindani M; Lee S; Zhang M; Moawad AW; Ng QK; Shere L; Elsayes KM; Maroldi R; Link TM; Nardo L; Qi J
J Digit Imaging; 2023 Jun; 36(3):1049-1059. PubMed ID: 36854923
[TBL] [Abstract][Full Text] [Related]
37. Magnetic Resonance Imaging Features on Deep Learning Algorithm for the Diagnosis of Nasopharyngeal Carcinoma.
Huang R; Zhou Z; Wang X; Cao X
Contrast Media Mol Imaging; 2022; 2022():3790269. PubMed ID: 35677026
[TBL] [Abstract][Full Text] [Related]
38. Ultrasonographic markers and preoperative CA-125 to distinguish between borderline ovarian tumors and stage I ovarian cancer.
Zacharakis D; Thomakos N; Biliatis I; Rodolakis A; Simou M; Daskalakis G; Bamias A; Antsaklis A
Acta Obstet Gynecol Scand; 2013 Mar; 92(3):285-92. PubMed ID: 23193945
[TBL] [Abstract][Full Text] [Related]
39. Deep learning-based automatic segmentation of meningioma from multiparametric MRI for preoperative meningioma differentiation using radiomic features: a multicentre study.
Chen H; Li S; Zhang Y; Liu L; Lv X; Yi Y; Ruan G; Ke C; Feng Y
Eur Radiol; 2022 Oct; 32(10):7248-7259. PubMed ID: 35420299
[TBL] [Abstract][Full Text] [Related]
40. Diagnostic performance of MR imaging findings and quantitative values in the differentiation of seromucinous borderline tumour from endometriosis-related malignant ovarian tumour.
Kurata Y; Kido A; Moribata Y; Kameyama K; Himoto Y; Minamiguchi S; Konishi I; Togashi K
Eur Radiol; 2017 Apr; 27(4):1695-1703. PubMed ID: 27553934
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
