409 related articles for article (PubMed ID: 36650498)
1. Biparametric magnetic resonance imaging-based radiomics features for prediction of lymphovascular invasion in rectal cancer.
Tong P; Sun D; Chen G; Ni J; Li Y
BMC Cancer; 2023 Jan; 23(1):61. PubMed ID: 36650498
[TBL] [Abstract][Full Text] [Related]
2. Preoperative detection of lymphovascular invasion in rectal cancer using intravoxel incoherent motion imaging based on radiomics.
Wong C; Liu T; Zhang C; Li M; Zhang H; Wang Q; Fu Y
Med Phys; 2024 Jan; 51(1):179-191. PubMed ID: 37929807
[TBL] [Abstract][Full Text] [Related]
3. Preoperative prediction of lymphovascular invasion in invasive breast cancer with dynamic contrast-enhanced-MRI-based radiomics.
Liu Z; Feng B; Li C; Chen Y; Chen Q; Li X; Guan J; Chen X; Cui E; Li R; Li Z; Long W
J Magn Reson Imaging; 2019 Sep; 50(3):847-857. PubMed ID: 30773770
[TBL] [Abstract][Full Text] [Related]
4. Preoperative prediction of perineural invasion of rectal cancer based on a magnetic resonance imaging radiomics model: A dual-center study.
Liu Y; Sun BJ; Zhang C; Li B; Yu XX; Du Y
World J Gastroenterol; 2024 Apr; 30(16):2233-2248. PubMed ID: 38690027
[TBL] [Abstract][Full Text] [Related]
5. Assessment of Lymphovascular Invasion in Breast Cancer Using a Combined MRI Morphological Features, Radiomics, and Deep Learning Approach Based on Dynamic Contrast-Enhanced MRI.
Yang X; Fan X; Lin S; Zhou Y; Liu H; Wang X; Zuo Z; Zeng Y
J Magn Reson Imaging; 2024 Jun; 59(6):2238-2249. PubMed ID: 37855421
[TBL] [Abstract][Full Text] [Related]
6. [Application of MRI-based Radiomics Models in the Assessment of Hepatic Metastasis of Rectal Cancer].
Hu SX; Yang K; Wang XR; Wen DG; Xia CC; Li X; Li ZL
Sichuan Da Xue Xue Bao Yi Xue Ban; 2021 Mar; 52(2):311-318. PubMed ID: 33829708
[TBL] [Abstract][Full Text] [Related]
7. A Nomogram of Combining IVIM-DWI and MRI Radiomics From the Primary Lesion of Rectal Adenocarcinoma to Assess Nonenlarged Lymph Node Metastasis Preoperatively.
Jia H; Jiang X; Zhang K; Shang J; Zhang Y; Fang X; Gao F; Li N; Dong J
J Magn Reson Imaging; 2022 Sep; 56(3):658-667. PubMed ID: 35090079
[TBL] [Abstract][Full Text] [Related]
8. Development and external validation of a multiparametric MRI-based radiomics model for preoperative prediction of microsatellite instability status in rectal cancer: a retrospective multicenter study.
Li Z; Zhang J; Zhong Q; Feng Z; Shi Y; Xu L; Zhang R; Yu F; Lv B; Yang T; Huang C; Cui F; Chen F
Eur Radiol; 2023 Mar; 33(3):1835-1843. PubMed ID: 36282309
[TBL] [Abstract][Full Text] [Related]
9. Radiomics based on T2-weighted and diffusion-weighted MR imaging for preoperative prediction of tumor deposits in rectal cancer.
Sun Z; Xia F; Lv W; Li J; Zou Y; Wu J
Am J Surg; 2024 Jun; 232():59-67. PubMed ID: 38272767
[TBL] [Abstract][Full Text] [Related]
10. [Radiomics-based prediction of microsatellite instability in stage Ⅱ and Ⅲ rectal cancer patients based on T2WI MRI and diffusion-weighted imaging].
Xiang S; Zheng LB; Zhu L; Gao Y; Wang DS; Liu SL; Zhang S; Wang TY; Lu Y
Zhonghua Wai Ke Za Zhi; 2023 Sep; 61(9):782-787. PubMed ID: 37491171
[No Abstract] [Full Text] [Related]
11. Intra- and Peritumoral Based Radiomics for Assessment of Lymphovascular Invasion in Invasive Breast Cancer.
Jiang W; Meng R; Cheng Y; Wang H; Han T; Qu N; Yu T; Hou Y; Xu S
J Magn Reson Imaging; 2024 Feb; 59(2):613-625. PubMed ID: 37199241
[TBL] [Abstract][Full Text] [Related]
12. A clinical-radiomics model incorporating T2-weighted and diffusion-weighted magnetic resonance images predicts the existence of lymphovascular invasion / perineural invasion in patients with colorectal cancer.
Zhang K; Ren Y; Xu S; Lu W; Xie S; Qu J; Wang X; Shen B; Pang P; Cai X; Sun J
Med Phys; 2021 Sep; 48(9):4872-4882. PubMed ID: 34042185
[TBL] [Abstract][Full Text] [Related]
13. Development of a joint prediction model based on both the radiomics and clinical factors for preoperative prediction of circumferential resection margin in middle-low rectal cancer using T2WI images.
Ju Y; Zheng L; Qi W; Tian G; Lu Y
Med Phys; 2024 Apr; 51(4):2563-2577. PubMed ID: 37987563
[TBL] [Abstract][Full Text] [Related]
14. A combinatorial MRI sequence-based radiomics model for preoperative prediction of microsatellite instability status in rectal cancer.
Xing X; Li D; Peng J; Shu Z; Zhang Y; Song Q
Sci Rep; 2024 May; 14(1):11760. PubMed ID: 38783014
[TBL] [Abstract][Full Text] [Related]
15. [Application of Automated Machine Learning Based on Radiomics Features of T2WI and RS-EPI DWI to Predict Preoperative T Staging of Rectal Cancer].
Wen DG; Hu SX; Li ZL; Deng XB; Tian C; Li X; Wang XR; Leng Q; Xia CC
Sichuan Da Xue Xue Bao Yi Xue Ban; 2021 Jul; 52(4):698-705. PubMed ID: 34323052
[TBL] [Abstract][Full Text] [Related]
16. Multiparametric MRI-based machine learning models for preoperatively predicting rectal adenoma with canceration.
Li P; Song G; Wu R; Li H; Zhang R; Zuo P; Li A
MAGMA; 2021 Oct; 34(5):707-716. PubMed ID: 33646452
[TBL] [Abstract][Full Text] [Related]
17. [A prediction model of pathological complete response in patients with locally advanced rectal cancer after PD-1 antibody combined with total neoadjuvant chemoradiotherapy based on MRI radiomics].
Zhang XY; Zhu HT; Li XT; Li YJ; Li ZW; Wang WH; Wu AW; Sun YS; Zhang L
Zhonghua Wei Chang Wai Ke Za Zhi; 2022 Mar; 25(3):228-234. PubMed ID: 35340172
[No Abstract] [Full Text] [Related]
18. MRI-based radiomics feature combined with tumor markers to predict TN staging of rectal cancer.
Liu Z; Zhang J; Wang H; Chen X; Song J; Xu D; Li J; Zheng M
J Robot Surg; 2024 May; 18(1):229. PubMed ID: 38809383
[TBL] [Abstract][Full Text] [Related]
19. An endorectal ultrasound-based radiomics signature for preoperative prediction of lymphovascular invasion of rectal cancer.
Wu YQ; Gao RZ; Lin P; Wen R; Li HY; Mou MY; Chen FH; Huang F; Zhou WJ; Yang H; He Y; Wu J
BMC Med Imaging; 2022 May; 22(1):84. PubMed ID: 35538520
[TBL] [Abstract][Full Text] [Related]
20. Multi-Parametric Magnetic Resonance Imaging-Based Radiomics Analysis of Cervical Cancer for Preoperative Prediction of Lymphovascular Space Invasion.
Huang G; Cui Y; Wang P; Ren J; Wang L; Ma Y; Jia Y; Ma X; Zhao L
Front Oncol; 2021; 11():663370. PubMed ID: 35096556
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
