117 related articles for article (PubMed ID: 38711198)
1. Robustness and classification capabilities of MRI radiomic features in identifying carotid plaque vulnerability.
Meddings Z; Rundo L; Sadat U; Zhao X; Teng Z; Graves MJ
Br J Radiol; 2024 May; ():. PubMed ID: 38711198
[TBL] [Abstract][Full Text] [Related]
2. Cardiac SPECT radiomic features repeatability and reproducibility: A multi-scanner phantom study.
Edalat-Javid M; Shiri I; Hajianfar G; Abdollahi H; Arabi H; Oveisi N; Javadian M; Shamsaei Zafarghandi M; Malek H; Bitarafan-Rajabi A; Oveisi M; Zaidi H
J Nucl Cardiol; 2021 Dec; 28(6):2730-2744. PubMed ID: 32333282
[TBL] [Abstract][Full Text] [Related]
3. Magnetic resonance radiomic feature performance in pulmonary nodule classification and impact of segmentation variability on radiomics.
Koo CW; Kline TL; Yoon JH; Vercnocke AJ; Johnson MP; Suman G; Lu A; Larson NB
Br J Radiol; 2022 Dec; 95(1140):20220230. PubMed ID: 36367095
[TBL] [Abstract][Full Text] [Related]
4. Physics-Informed Discretization for Reproducible and Robust Radiomic Feature Extraction Using Quantitative MRI.
Zhao W; Hu Z; Kazerooni AF; Körzdörfer G; Nittka M; Davatzikos C; Viswanath SE; Wang X; Badve C; Ma D
Invest Radiol; 2024 May; 59(5):359-371. PubMed ID: 37812483
[TBL] [Abstract][Full Text] [Related]
5. Identification of high-risk plaque features in intracranial atherosclerosis: initial experience using a radiomic approach.
Shi Z; Zhu C; Degnan AJ; Tian X; Li J; Chen L; Zhang X; Peng W; Chen C; Lu J; Jiang T; Saloner D; Liu Q
Eur Radiol; 2018 Sep; 28(9):3912-3921. PubMed ID: 29633002
[TBL] [Abstract][Full Text] [Related]
6. Radiomics-Based Precision Phenotyping Identifies Unstable Coronary Plaques From Computed Tomography Angiography.
Lin A; Kolossváry M; Cadet S; McElhinney P; Goeller M; Han D; Yuvaraj J; Nerlekar N; Slomka PJ; Marwan M; Nicholls SJ; Achenbach S; Maurovich-Horvat P; Wong DTL; Dey D
JACC Cardiovasc Imaging; 2022 May; 15(5):859-871. PubMed ID: 35512957
[TBL] [Abstract][Full Text] [Related]
7. Computed tomography angiography-based radiomics model for predicting carotid atherosclerotic plaque vulnerability.
Shan D; Wang S; Wang J; Lu J; Ren J; Chen J; Wang D; Qi P
Front Neurol; 2023; 14():1151326. PubMed ID: 37396779
[TBL] [Abstract][Full Text] [Related]
8. Carotid vulnerable plaque coexisting with cerebral small vessel disease and acute ischemic stroke: a Chinese Atherosclerosis Risk Evaluation study.
Li J; Wu H; Hang H; Sun B; Zhao H; Chen Z; Zhou Y; Xu J; Chen J; Zhou D; Zhao X; Yuan C
Eur Radiol; 2022 Sep; 32(9):6080-6089. PubMed ID: 35364716
[TBL] [Abstract][Full Text] [Related]
9. Differentiation of invasive ductal and lobular carcinoma of the breast using MRI radiomic features: a pilot study.
Maiti S; Nayak S; Hebbar KD; Pendem S
F1000Res; 2024; 13():91. PubMed ID: 38571894
[TBL] [Abstract][Full Text] [Related]
10. Radiomics Signatures of Carotid Plaque on Computed Tomography Angiography : An Approach to Identify Symptomatic Plaques.
Shi J; Sun Y; Hou J; Li X; Fan J; Zhang L; Zhang R; You H; Wang Z; Zhang A; Zhang J; Jin Q; Zhao L; Yang B
Clin Neuroradiol; 2023 Dec; 33(4):931-941. PubMed ID: 37195452
[TBL] [Abstract][Full Text] [Related]
11. Optimal co-clinical radiomics: Sensitivity of radiomic features to tumour volume, image noise and resolution in co-clinical T1-weighted and T2-weighted magnetic resonance imaging.
Roy S; Whitehead TD; Quirk JD; Salter A; Ademuyiwa FO; Li S; An H; Shoghi KI
EBioMedicine; 2020 Sep; 59():102963. PubMed ID: 32891051
[TBL] [Abstract][Full Text] [Related]
12. Usefulness of MRI-based radiomic features for distinguishing Warthin tumor from pleomorphic adenoma: performance assessment using T2-weighted and post-contrast T1-weighted MR images.
Faggioni L; Gabelloni M; De Vietro F; Frey J; Mendola V; Cavallero D; Borgheresi R; Tumminello L; Shortrede J; Morganti R; Seccia V; Coppola F; Cioni D; Neri E
Eur J Radiol Open; 2022; 9():100429. PubMed ID: 35757232
[TBL] [Abstract][Full Text] [Related]
13. Multiparametric MR radiomics in brain glioma: models comparation to predict biomarker status.
He J; Ren J; Niu G; Liu A; Wu Q; Xie S; Ma X; Li B; Wang P; Shen J; Wu J; Gao Y
BMC Med Imaging; 2022 Aug; 22(1):137. PubMed ID: 35931979
[TBL] [Abstract][Full Text] [Related]
14. Treatment response prediction using MRI-based pre-, post-, and delta-radiomic features and machine learning algorithms in colorectal cancer.
Shayesteh S; Nazari M; Salahshour A; Sandoughdaran S; Hajianfar G; Khateri M; Yaghobi Joybari A; Jozian F; Fatehi Feyzabad SH; Arabi H; Shiri I; Zaidi H
Med Phys; 2021 Jul; 48(7):3691-3701. PubMed ID: 33894058
[TBL] [Abstract][Full Text] [Related]
15. Radiomics with 3-dimensional magnetic resonance fingerprinting: influence of dictionary design on repeatability and reproducibility of radiomic features.
Fujita S; Hagiwara A; Yasaka K; Akai H; Kunimatsu A; Kiryu S; Fukunaga I; Kato S; Akashi T; Kamagata K; Wada A; Abe O; Aoki S
Eur Radiol; 2022 Jul; 32(7):4791-4800. PubMed ID: 35304637
[TBL] [Abstract][Full Text] [Related]
16. Combination of Peri-Tumoral and Intra-Tumoral Radiomic Features on Bi-Parametric MRI Accurately Stratifies Prostate Cancer Risk: A Multi-Site Study.
Algohary A; Shiradkar R; Pahwa S; Purysko A; Verma S; Moses D; Shnier R; Haynes AM; Delprado W; Thompson J; Tirumani S; Mahran A; Rastinehad AR; Ponsky L; Stricker PD; Madabhushi A
Cancers (Basel); 2020 Aug; 12(8):. PubMed ID: 32781640
[No Abstract] [Full Text] [Related]
17. Reliability of tumor segmentation in glioblastoma: Impact on the robustness of MRI-radiomic features.
Tixier F; Um H; Young RJ; Veeraraghavan H
Med Phys; 2019 Aug; 46(8):3582-3591. PubMed ID: 31131906
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. Identifying vulnerable plaques: A 3D carotid plaque radiomics model based on HRMRI.
Zhang X; Hua Z; Chen R; Jiao Z; Shan J; Li C; Li Z
Front Neurol; 2023; 14():1050899. PubMed ID: 36779063
[TBL] [Abstract][Full Text] [Related]
20. Prognosis of ischemic stroke predicted by machine learning based on multi-modal MRI radiomics.
Yu H; Wang Z; Sun Y; Bo W; Duan K; Song C; Hu Y; Zhou J; Mu Z; Wu N
Front Psychiatry; 2022; 13():1105496. PubMed ID: 36699499
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]