114 related articles for article (PubMed ID: 37222527)
41. Computed Tomography-Based Radiomics Model to Predict Central Cervical Lymph Node Metastases in Papillary Thyroid Carcinoma: A Multicenter Study.
Li J; Wu X; Mao N; Zheng G; Zhang H; Mou Y; Jia C; Mi J; Song X
Front Endocrinol (Lausanne); 2021; 12():741698. PubMed ID: 34745008
[TBL] [Abstract][Full Text] [Related]
42. Glioma grading prediction using multiparametric magnetic resonance imaging-based radiomics combined with proton magnetic resonance spectroscopy and diffusion tensor imaging.
Lin K; Cidan W; Qi Y; Wang X
Med Phys; 2022 Jul; 49(7):4419-4429. PubMed ID: 35366379
[TBL] [Abstract][Full Text] [Related]
43. Hematolymphoid neoplasms are common in bone marrow biopsies performed for non-specific, diffuse marrow signal alterations on magnetic resonance imaging.
Jones TE; Wyse AJ; Gibson SE
Ann Diagn Pathol; 2019 Jun; 40():7-12. PubMed ID: 30825791
[TBL] [Abstract][Full Text] [Related]
44. Identification of the most significant magnetic resonance imaging (MRI) radiomic features in oncological patients with vertebral bone marrow metastatic disease: a feasibility study.
Filograna L; Lenkowicz J; Cellini F; Dinapoli N; Manfrida S; Magarelli N; Leone A; Colosimo C; Valentini V
Radiol Med; 2019 Jan; 124(1):50-57. PubMed ID: 30191445
[TBL] [Abstract][Full Text] [Related]
45. Fully automated prediction of liver fibrosis using deep learning analysis of gadoxetic acid-enhanced MRI.
Hectors SJ; Kennedy P; Huang KH; Stocker D; Carbonell G; Greenspan H; Friedman S; Taouli B
Eur Radiol; 2021 Jun; 31(6):3805-3814. PubMed ID: 33201285
[TBL] [Abstract][Full Text] [Related]
46. Classification of Cancer at Prostate MRI: Deep Learning versus Clinical PI-RADS Assessment.
Schelb P; Kohl S; Radtke JP; Wiesenfarth M; Kickingereder P; Bickelhaupt S; Kuder TA; Stenzinger A; Hohenfellner M; Schlemmer HP; Maier-Hein KH; Bonekamp D
Radiology; 2019 Dec; 293(3):607-617. PubMed ID: 31592731
[TBL] [Abstract][Full Text] [Related]
47. Magnetic resonance imaging radiomics predicts preoperative axillary lymph node metastasis to support surgical decisions and is associated with tumor microenvironment in invasive breast cancer: A machine learning, multicenter study.
Yu Y; He Z; Ouyang J; Tan Y; Chen Y; Gu Y; Mao L; Ren W; Wang J; Lin L; Wu Z; Liu J; Ou Q; Hu Q; Li A; Chen K; Li C; Lu N; Li X; Su F; Liu Q; Xie C; Yao H
EBioMedicine; 2021 Jul; 69():103460. PubMed ID: 34233259
[TBL] [Abstract][Full Text] [Related]
48. Machine learning-based radiomics model to predict benign and malignant PI-RADS v2.1 category 3 lesions: a retrospective multi-center study.
Jin P; Shen J; Yang L; Zhang J; Shen A; Bao J; Wang X
BMC Med Imaging; 2023 Mar; 23(1):47. PubMed ID: 36991347
[TBL] [Abstract][Full Text] [Related]
49. Mammography-based radiomics for predicting the risk of breast cancer recurrence: a multicenter study.
Mao N; Yin P; Zhang H; Zhang K; Song X; Xing D; Chu T
Br J Radiol; 2021 Nov; 94(1127):20210348. PubMed ID: 34520235
[TBL] [Abstract][Full Text] [Related]
50. Development and Evaluation of Deep Learning-based Automated Segmentation of Pituitary Adenoma in Clinical Task.
Wang H; Zhang W; Li S; Fan Y; Feng M; Wang R
J Clin Endocrinol Metab; 2021 Aug; 106(9):2535-2546. PubMed ID: 34060609
[TBL] [Abstract][Full Text] [Related]
51. More advantages in detecting bone and soft tissue metastases from prostate cancer using
Pianou NK; Stavrou PZ; Vlontzou E; Rondogianni P; Exarhos DN; Datseris IE
Hell J Nucl Med; 2019; 22(1):6-9. PubMed ID: 30843003
[TBL] [Abstract][Full Text] [Related]
52. Evaluation of Diffuse Bone Marrow Infiltration Pattern in Monoclonal Plasma Cell Diseases by Quantitative Whole-body Magnetic Resonance Imaging.
Sun M; Cheng J; Ren C; Zhang Y; Li Y; Wang L; Zhang S; Lin L
Acad Radiol; 2022 Apr; 29(4):490-500. PubMed ID: 34362664
[TBL] [Abstract][Full Text] [Related]
53. MRI-based texture analysis of the primary tumor for pre-treatment prediction of bone metastases in prostate cancer.
Wang Y; Yu B; Zhong F; Guo Q; Li K; Hou Y; Lin N
Magn Reson Imaging; 2019 Jul; 60():76-84. PubMed ID: 30917943
[TBL] [Abstract][Full Text] [Related]
54. Radiomics Models Based on Apparent Diffusion Coefficient Maps for the Prediction of High-Grade Prostate Cancer at Radical Prostatectomy: Comparison With Preoperative Biopsy.
Han C; Ma S; Liu X; Liu Y; Li C; Zhang Y; Zhang X; Wang X
J Magn Reson Imaging; 2021 Dec; 54(6):1892-1901. PubMed ID: 33682286
[TBL] [Abstract][Full Text] [Related]
55. Deep Learning Improves Speed and Accuracy of Prostate Gland Segmentations on Magnetic Resonance Imaging for Targeted Biopsy.
Soerensen SJC; Fan RE; Seetharaman A; Chen L; Shao W; Bhattacharya I; Kim YH; Sood R; Borre M; Chung BI; To'o KJ; Rusu M; Sonn GA
J Urol; 2021 Sep; 206(3):604-612. PubMed ID: 33878887
[TBL] [Abstract][Full Text] [Related]
56. CT-based deep learning segmentation of ovarian cancer and the stability of the extracted radiomics features.
Wang Y; Wang M; Cao P; Wong EMF; Ho G; Lam TPW; Han L; Lee EYP
Quant Imaging Med Surg; 2023 Aug; 13(8):5218-5229. PubMed ID: 37581064
[TBL] [Abstract][Full Text] [Related]
57. Osteolytic lesions, cytogenetic features and bone marrow levels of cytokines and chemokines in multiple myeloma patients: Role of chemokine (C-C motif) ligand 20.
Palma BD; Guasco D; Pedrazzoni M; Bolzoni M; Accardi F; Costa F; Sammarelli G; Craviotto L; De Filippo M; Ruffini L; Omedè P; Ria R; Aversa F; Giuliani N
Leukemia; 2016 Feb; 30(2):409-16. PubMed ID: 26419509
[TBL] [Abstract][Full Text] [Related]
58. A deep learning masked segmentation alternative to manual segmentation in biparametric MRI prostate cancer radiomics.
Bleker J; Kwee TC; Rouw D; Roest C; Borstlap J; de Jong IJ; Dierckx RAJO; Huisman H; Yakar D
Eur Radiol; 2022 Sep; 32(9):6526-6535. PubMed ID: 35420303
[TBL] [Abstract][Full Text] [Related]
59. Preoperative prediction of sentinel lymph node metastasis in breast cancer by radiomic signatures from dynamic contrast-enhanced MRI.
Liu C; Ding J; Spuhler K; Gao Y; Serrano Sosa M; Moriarty M; Hussain S; He X; Liang C; Huang C
J Magn Reson Imaging; 2019 Jan; 49(1):131-140. PubMed ID: 30171822
[TBL] [Abstract][Full Text] [Related]
60. Automated deep learning method for whole-breast segmentation in diffusion-weighted breast MRI.
Zhang L; Mohamed AA; Chai R; Guo Y; Zheng B; Wu S
J Magn Reson Imaging; 2020 Feb; 51(2):635-643. PubMed ID: 31301201
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]