296 related articles for article (PubMed ID: 36333180)
1. A novel multimodal deep learning model for preoperative prediction of microvascular invasion and outcome in hepatocellular carcinoma.
Wang F; Chen Q; Chen Y; Zhu Y; Zhang Y; Cao D; Zhou W; Liang X; Yang Y; Lin L; Hu H
Eur J Surg Oncol; 2023 Jan; 49(1):156-164. PubMed ID: 36333180
[TBL] [Abstract][Full Text] [Related]
2. Deep learning radiomics based on contrast enhanced computed tomography predicts microvascular invasion and survival outcome in early stage hepatocellular carcinoma.
Yang Y; Zhou Y; Zhou C; Ma X
Eur J Surg Oncol; 2022 May; 48(5):1068-1077. PubMed ID: 34862094
[TBL] [Abstract][Full Text] [Related]
3. Deep-learning-based analysis of preoperative MRI predicts microvascular invasion and outcome in hepatocellular carcinoma.
Sun BY; Gu PY; Guan RY; Zhou C; Lu JW; Yang ZF; Pan C; Zhou PY; Zhu YP; Li JR; Wang ZT; Gao SS; Gan W; Yi Y; Luo Y; Qiu SJ
World J Surg Oncol; 2022 Jun; 20(1):189. PubMed ID: 35676669
[TBL] [Abstract][Full Text] [Related]
4. Using deep learning to predict microvascular invasion in hepatocellular carcinoma based on dynamic contrast-enhanced MRI combined with clinical parameters.
Song D; Wang Y; Wang W; Wang Y; Cai J; Zhu K; Lv M; Gao Q; Zhou J; Fan J; Rao S; Wang M; Wang X
J Cancer Res Clin Oncol; 2021 Dec; 147(12):3757-3767. PubMed ID: 33839938
[TBL] [Abstract][Full Text] [Related]
5. Deep learning nomogram based on Gd-EOB-DTPA MRI for predicting early recurrence in hepatocellular carcinoma after hepatectomy.
Yan M; Zhang X; Zhang B; Geng Z; Xie C; Yang W; Zhang S; Qi Z; Lin T; Ke Q; Li X; Wang S; Quan X
Eur Radiol; 2023 Jul; 33(7):4949-4961. PubMed ID: 36786905
[TBL] [Abstract][Full Text] [Related]
6. Comparison of MRI and CT for the Prediction of Microvascular Invasion in Solitary Hepatocellular Carcinoma Based on a Non-Radiomics and Radiomics Method: Which Imaging Modality Is Better?
Meng XP; Wang YC; Zhou JY; Yu Q; Lu CQ; Xia C; Tang TY; Xu J; Sun K; Xiao W; Ju S
J Magn Reson Imaging; 2021 Aug; 54(2):526-536. PubMed ID: 33622022
[TBL] [Abstract][Full Text] [Related]
7. Radiomics and nomogram of magnetic resonance imaging for preoperative prediction of microvascular invasion in small hepatocellular carcinoma.
Chen YD; Zhang L; Zhou ZP; Lin B; Jiang ZJ; Tang C; Dang YW; Xia YW; Song B; Long LL
World J Gastroenterol; 2022 Aug; 28(31):4399-4416. PubMed ID: 36159011
[TBL] [Abstract][Full Text] [Related]
8. Preoperative Evaluation of Gd-EOB-DTPA-Enhanced MRI Radiomics-Based Nomogram in Small Solitary Hepatocellular Carcinoma (≤3 cm) With Microvascular Invasion: A Two-Center Study.
Tian Y; Hua H; Peng Q; Zhang Z; Wang X; Han J; Ma W; Chen J
J Magn Reson Imaging; 2022 Nov; 56(5):1459-1472. PubMed ID: 35298849
[TBL] [Abstract][Full Text] [Related]
9. Radiomic analysis based on multi-phase magnetic resonance imaging to predict preoperatively microvascular invasion in hepatocellular carcinoma.
Li YM; Zhu YM; Gao LM; Han ZW; Chen XJ; Yan C; Ye RP; Cao DR
World J Gastroenterol; 2022 Jun; 28(24):2733-2747. PubMed ID: 35979164
[TBL] [Abstract][Full Text] [Related]
10. Radiomic analysis of contrast-enhanced CT predicts microvascular invasion and outcome in hepatocellular carcinoma.
Xu X; Zhang HL; Liu QP; Sun SW; Zhang J; Zhu FP; Yang G; Yan X; Zhang YD; Liu XS
J Hepatol; 2019 Jun; 70(6):1133-1144. PubMed ID: 30876945
[TBL] [Abstract][Full Text] [Related]
11. Predicting microvascular invasion in hepatocellular carcinoma: a deep learning model validated across hospitals.
Liu SC; Lai J; Huang JY; Cho CF; Lee PH; Lu MH; Yeh CC; Yu J; Lin WC
Cancer Imaging; 2021 Oct; 21(1):56. PubMed ID: 34627393
[TBL] [Abstract][Full Text] [Related]
12. Development of a deep learning-based auto-segmentation algorithm for hepatocellular carcinoma (HCC) and application to predict microvascular invasion of HCC using CT texture analysis: preliminary results.
Park S; Kim JH; Kim J; Joseph W; Lee D; Park SJ
Acta Radiol; 2023 Mar; 64(3):907-917. PubMed ID: 35570797
[TBL] [Abstract][Full Text] [Related]
13. Hepatobiliary MR contrast agent uptake as a predictive biomarker of aggressive features on pathology and reduced recurrence-free survival in resectable hepatocellular carcinoma: comparison with dual-tracer 18F-FDG and 18F-FCH PET/CT.
Mulé S; Chalaye J; Legou F; Tenenhaus A; Calderaro J; Galletto Pregliasco A; Laurent A; Kharrat R; Amaddeo G; Regnault H; Tacher V; Kobeiter H; Itti E; Luciani A
Eur Radiol; 2020 Oct; 30(10):5348-5357. PubMed ID: 32405753
[TBL] [Abstract][Full Text] [Related]
14. Prediction of Microvascular Invasion in Hepatocellular Carcinoma via Deep Learning: A Multi-Center and Prospective Validation Study.
Wei J; Jiang H; Zeng M; Wang M; Niu M; Gu D; Chong H; Zhang Y; Fu F; Zhou M; Chen J; Lyv F; Wei H; Bashir MR; Song B; Li H; Tian J
Cancers (Basel); 2021 May; 13(10):. PubMed ID: 34068972
[TBL] [Abstract][Full Text] [Related]
15. [Value of the application of enhanced CT radiomics and machine learning in preoperative prediction of microvascular invasion in hepatocellular carcinoma].
Yu YX; Hu CH; Wang XM; Fan YF; Hu MJ; Shi C; Hu S; Zhu M; Zhang Y
Zhonghua Yi Xue Za Zhi; 2021 May; 101(17):1239-1245. PubMed ID: 34865392
[No Abstract] [Full Text] [Related]
16. Prediction of Microvascular Invasion of Hepatocellular Carcinoma Based on Preoperative Diffusion-Weighted MR Using Deep Learning.
Wang G; Jian W; Cen X; Zhang L; Guo H; Liu Z; Liang C; Zhou W
Acad Radiol; 2021 Nov; 28 Suppl 1():S118-S127. PubMed ID: 33303346
[TBL] [Abstract][Full Text] [Related]
17. Preoperative radiomics nomogram for microvascular invasion prediction in hepatocellular carcinoma using contrast-enhanced CT.
Ma X; Wei J; Gu D; Zhu Y; Feng B; Liang M; Wang S; Zhao X; Tian J
Eur Radiol; 2019 Jul; 29(7):3595-3605. PubMed ID: 30770969
[TBL] [Abstract][Full Text] [Related]
18. Contrast-enhanced CT findings-based model to predict MVI in patients with hepatocellular carcinoma.
Yue Q; Zhou Z; Zhang X; Xu X; Liu Y; Wang K; Liu Q; Wang J; Zhao Y; Yin Y
BMC Gastroenterol; 2022 Dec; 22(1):544. PubMed ID: 36577952
[TBL] [Abstract][Full Text] [Related]
19. Preoperative identification of microvascular invasion in hepatocellular carcinoma by XGBoost and deep learning.
Jiang YQ; Cao SE; Cao S; Chen JN; Wang GY; Shi WQ; Deng YN; Cheng N; Ma K; Zeng KN; Yan XJ; Yang HZ; Huan WJ; Tang WM; Zheng Y; Shao CK; Wang J; Yang Y; Chen GH
J Cancer Res Clin Oncol; 2021 Mar; 147(3):821-833. PubMed ID: 32852634
[TBL] [Abstract][Full Text] [Related]
20. Application of a Convolutional Neural Network for Multitask Learning to Simultaneously Predict Microvascular Invasion and Vessels that Encapsulate Tumor Clusters in Hepatocellular Carcinoma.
Chu T; Zhao C; Zhang J; Duan K; Li M; Zhang T; Lv S; Liu H; Wei F
Ann Surg Oncol; 2022 Oct; 29(11):6774-6783. PubMed ID: 35754067
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
