142 related articles for article (PubMed ID: 34076829)
1. Clinicopathologic breast cancer characteristics: predictions using global textural features of the ipsilateral breast mammogram.
Kanbayti IH; Rae WID; McEntee MF; Gandomkar Z; Ekpo EU
Radiol Phys Technol; 2021 Sep; 14(3):248-261. PubMed ID: 34076829
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. 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]
4. Parenchymal texture analysis in digital mammography: A fully automated pipeline for breast cancer risk assessment.
Zheng Y; Keller BM; Ray S; Wang Y; Conant EF; Gee JC; Kontos D
Med Phys; 2015 Jul; 42(7):4149-60. PubMed ID: 26133615
[TBL] [Abstract][Full Text] [Related]
5. Computer-extracted global radiomic features can predict the radiologists' first impression about the abnormality of a screening mammogram.
Siviengphanom S; Lewis SJ; Brennan PC; Gandomkar Z
Br J Radiol; 2024 Jan; 97(1153):168-179. PubMed ID: 38263826
[TBL] [Abstract][Full Text] [Related]
6. Value of [
Li K; Sun H; Lu Z; Xin J; Zhang L; Guo Y; Guo Q
Eur J Radiol; 2018 Sep; 106():160-166. PubMed ID: 30150039
[TBL] [Abstract][Full Text] [Related]
7. Statistical harmonization can improve the development of a multicenter CT-based radiomic model predictive of nonresponse to induction chemotherapy in laryngeal cancers.
Masson I; Da-Ano R; Lucia F; Doré M; Castelli J; Goislard de Monsabert C; Ramée JF; Sellami S; Visvikis D; Hatt M; Schick U
Med Phys; 2021 Jul; 48(7):4099-4109. PubMed ID: 34008178
[TBL] [Abstract][Full Text] [Related]
8. Ability of
Ou X; Wang J; Zhou R; Zhu S; Pang F; Zhou Y; Tian R; Ma X
Contrast Media Mol Imaging; 2019; 2019():4507694. PubMed ID: 30930700
[No Abstract] [Full Text] [Related]
9. Development and Validation of a Preoperative Magnetic Resonance Imaging Radiomics-Based Signature to Predict Axillary Lymph Node Metastasis and Disease-Free Survival in Patients With Early-Stage Breast Cancer.
Yu Y; Tan Y; Xie C; Hu Q; Ouyang J; Chen Y; Gu Y; Li A; Lu N; He Z; Yang Y; Chen K; Ma J; Li C; Ma M; Li X; Zhang R; Zhong H; Ou Q; Zhang Y; He Y; Li G; Wu Z; Su F; Song E; Yao H
JAMA Netw Open; 2020 Dec; 3(12):e2028086. PubMed ID: 33289845
[TBL] [Abstract][Full Text] [Related]
10. Predicting cell invasion in breast tumor microenvironment from radiological imaging phenotypes.
Arefan D; Hausler RM; Sumkin JH; Sun M; Wu S
BMC Cancer; 2021 Apr; 21(1):370. PubMed ID: 33827490
[TBL] [Abstract][Full Text] [Related]
11. Breast Cancer Molecular Subtype Prediction by Mammographic Radiomic Features.
Ma W; Zhao Y; Ji Y; Guo X; Jian X; Liu P; Wu S
Acad Radiol; 2019 Feb; 26(2):196-201. PubMed ID: 29526548
[TBL] [Abstract][Full Text] [Related]
12. Prediction of malignancy by a radiomic signature from contrast agent-free diffusion MRI in suspicious breast lesions found on screening mammography.
Bickelhaupt S; Paech D; Kickingereder P; Steudle F; Lederer W; Daniel H; Götz M; Gählert N; Tichy D; Wiesenfarth M; Laun FB; Maier-Hein KH; Schlemmer HP; Bonekamp D
J Magn Reson Imaging; 2017 Aug; 46(2):604-616. PubMed ID: 28152264
[TBL] [Abstract][Full Text] [Related]
13. Radiomic analysis of HTR-DCE MR sequences improves diagnostic performance compared to BI-RADS analysis of breast MR lesions.
Perre SV; Duron L; Milon A; Bekhouche A; Balvay D; Cornelis FH; Fournier L; Thomassin-Naggara I
Eur Radiol; 2021 Jul; 31(7):4848-4859. PubMed ID: 33404696
[TBL] [Abstract][Full Text] [Related]
14. Using Convolutional Neural Networks for Enhanced Capture of Breast Parenchymal Complexity Patterns Associated with Breast Cancer Risk.
Gastounioti A; Oustimov A; Hsieh MK; Pantalone L; Conant EF; Kontos D
Acad Radiol; 2018 Aug; 25(8):977-984. PubMed ID: 29395798
[TBL] [Abstract][Full Text] [Related]
15. Prediction of pathological nodal involvement by CT-based Radiomic features of the primary tumor in patients with clinically node-negative peripheral lung adenocarcinomas.
Liu Y; Kim J; Balagurunathan Y; Hawkins S; Stringfield O; Schabath MB; Li Q; Qu F; Liu S; Garcia AL; Ye Z; Gillies RJ
Med Phys; 2018 Jun; 45(6):2518-2526. PubMed ID: 29624702
[TBL] [Abstract][Full Text] [Related]
16. Radiomic features of axillary lymph nodes based on pharmacokinetic modeling DCE-MRI allow preoperative diagnosis of their metastatic status in breast cancer.
Luo HB; Liu YY; Wang CH; Qing HM; Wang M; Zhang X; Chen XY; Xu GH; Zhou P; Ren J
PLoS One; 2021; 16(3):e0247074. PubMed ID: 33647031
[TBL] [Abstract][Full Text] [Related]
17. The MR radiomic signature can predict preoperative lymph node metastasis in patients with esophageal cancer.
Qu J; Shen C; Qin J; Wang Z; Liu Z; Guo J; Zhang H; Gao P; Bei T; Wang Y; Liu H; Kamel IR; Tian J; Li H
Eur Radiol; 2019 Feb; 29(2):906-914. PubMed ID: 30039220
[TBL] [Abstract][Full Text] [Related]
18. Mammography-based radiomic analysis for predicting benign BI-RADS category 4 calcifications.
Lei C; Wei W; Liu Z; Xiong Q; Yang C; Yang M; Zhang L; Zhu T; Zhuang X; Liu C; Liu Z; Tian J; Wang K
Eur J Radiol; 2019 Dec; 121():108711. PubMed ID: 31677544
[TBL] [Abstract][Full Text] [Related]
19. Integrating tumor and nodal radiomics to predict lymph node metastasis in gastric cancer.
Yang J; Wu Q; Xu L; Wang Z; Su K; Liu R; Yen EA; Liu S; Qin J; Rong Y; Lu Y; Niu T
Radiother Oncol; 2020 Sep; 150():89-96. PubMed ID: 32531334
[TBL] [Abstract][Full Text] [Related]
20.
Li P; Wang X; Xu C; Liu C; Zheng C; Fulham MJ; Feng D; Wang L; Song S; Huang G
Eur J Nucl Med Mol Imaging; 2020 May; 47(5):1116-1126. PubMed ID: 31982990
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
