136 related articles for article (PubMed ID: 38780895)
1. The diagnostic value of multimodal imaging based on MR combined with ultrasound in benign and malignant breast diseases.
Bai D; Zhou N; Liu X; Liang Y; Lu X; Wang J; Liang L; Wang Z
Clin Exp Med; 2024 May; 24(1):110. PubMed ID: 38780895
[TBL] [Abstract][Full Text] [Related]
2. Radiomics Based on Multimodal MRI for the Differential Diagnosis of Benign and Malignant Breast Lesions.
Zhang Q; Peng Y; Liu W; Bai J; Zheng J; Yang X; Zhou L
J Magn Reson Imaging; 2020 Aug; 52(2):596-607. PubMed ID: 32061014
[TBL] [Abstract][Full Text] [Related]
3. Diagnostic efficacy of contrast-enhanced ultrasound for breast lesions of different sizes: a comparative study with magnetic resonance imaging.
Li C; Yao M; Shao S; Li X; Li G; Wu R
Br J Radiol; 2020 Jun; 93(1110):20190932. PubMed ID: 32216631
[TBL] [Abstract][Full Text] [Related]
4. Additive value of texture analysis based on breast MRI for distinguishing between benign and malignant non-mass enhancement in premenopausal women.
Tan Y; Mai H; Huang Z; Zhang L; Li C; Wu S; Huang H; Tang W; Liu Y; Jiang K
BMC Med Imaging; 2021 Mar; 21(1):48. PubMed ID: 33706695
[TBL] [Abstract][Full Text] [Related]
5. [Preoperative prediction of HER-2 expression status in breast cancer based on MRI radiomics model].
Zhang Y; Huang H; Yin L; Wang ZX; Lu SY; Wang XX; Xiang LL; Zhang Q; Zhang JL; Shan XH
Zhonghua Zhong Liu Za Zhi; 2024 May; 46(5):428-437. PubMed ID: 38742356
[No Abstract] [Full Text] [Related]
6. Study on the differential diagnosis of benign and malignant breast lesions using a deep learning model based on multimodal images.
Du Y; Wang D; Liu M; Zhang X; Ren W; Sun J; Yin C; Yang S; Zhang L
J Cancer Res Ther; 2024 Apr; 20(2):625-632. PubMed ID: 38687933
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. Noninvasive Assessment of Tumor Histological Grade in Invasive Breast Carcinoma Based on Ultrasound Radiomics and Clinical Characteristics: A Multicenter Study.
Ge L; Wu J; Jin Y; Xu D; Wang Z
Technol Cancer Res Treat; 2024; 23():15330338241257424. PubMed ID: 38780506
[No Abstract] [Full Text] [Related]
9. [Value of radiomics models based on MRI diffusion weighted imaging and apparent diffusion coefficient in differentiating benign and malignant thyroid nodules].
Xu HJ; Yang Q; He P; Luo HH; Deng WM; Liu Z; Luo DH
Zhonghua Yi Xue Za Zhi; 2023 Nov; 103(41):3279-3286. PubMed ID: 37926572
[No Abstract] [Full Text] [Related]
10. Multi-region radiomics for artificially intelligent diagnosis of breast cancer using multimodal ultrasound.
Xu Z; Wang Y; Chen M; Zhang Q
Comput Biol Med; 2022 Oct; 149():105920. PubMed ID: 35986969
[TBL] [Abstract][Full Text] [Related]
11. Radiomics Analysis Based on Automatic Image Segmentation of DCE-MRI for Predicting Triple-Negative and Nontriple-Negative Breast Cancer.
Ma M; Gan L; Jiang Y; Qin N; Li C; Zhang Y; Wang X
Comput Math Methods Med; 2021; 2021():2140465. PubMed ID: 34422088
[TBL] [Abstract][Full Text] [Related]
12. Combination of Breast Ultrasound With Magnetic Resonance Imaging in the Diagnosis of Non-mass-like Breast Lesions Detected on Ultrasound: A New Integrated Strategy to Improve Diagnostic Performance.
Niu RL; Li JK; Wang B; Jiang Y; Li SY; Fu NQ; Liu G; Wang ZL
Ultrasound Med Biol; 2024 Jan; 50(1):105-111. PubMed ID: 37833192
[TBL] [Abstract][Full Text] [Related]
13. A New Application of Multimodality Radiomics Improves Diagnostic Accuracy of Nonpalpable Breast Lesions in Patients with Microcalcifications-Only in Mammography.
Chen S; Guan X; Shu Z; Li Y; Cao W; Dong F; Zhang M; Shao G; Shao F
Med Sci Monit; 2019 Dec; 25():9786-9793. PubMed ID: 31860635
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. Radiomics With Attribute Bagging for Breast Tumor Classification Using Multimodal Ultrasound Images.
Li Y; Liu Y; Zhang M; Zhang G; Wang Z; Luo J
J Ultrasound Med; 2020 Feb; 39(2):361-371. PubMed ID: 31432552
[TBL] [Abstract][Full Text] [Related]
16. [Prediction of platinum-based chemotherapy sensitivity for epithelial ovarian cancer by multi-sequence MRI-based radiomic nomogram].
Mao MM; Li HM; Shi J; Qiu QS; Feng F
Zhonghua Yi Xue Za Zhi; 2022 Jan; 102(3):201-208. PubMed ID: 35042289
[No Abstract] [Full Text] [Related]
17. Value of multimodal imaging in the diagnosis of breast sclerosing adenosis associated with malignant lesions.
Chen H; Bao L; Yu L; Sun H; Tan Y; Wei P; Zheng Z
J Clin Ultrasound; 2023 Mar; 51(3):485-493. PubMed ID: 36250329
[TBL] [Abstract][Full Text] [Related]
18. Radiomics analysis of ultrasound images to discriminate between benign and malignant adnexal masses with solid ultrasound morphology.
Moro F; Vagni M; Tran HE; Bernardini F; Mascilini F; Ciccarone F; Nero C; Giannarelli D; Boldrini L; Fagotti A; Scambia G; Valentin L; Testa AC
Ultrasound Obstet Gynecol; 2024 May; ():. PubMed ID: 38748935
[TBL] [Abstract][Full Text] [Related]
19. A radiomics method based on MR FS-T2WI sequence for diagnosing of autosomal dominant polycystic kidney disease progression.
Cong L; Hua QQ; Huang ZQ; Ma QL; Wang XM; Huang CC; Xu JX; Ma T
Eur Rev Med Pharmacol Sci; 2021 Sep; 25(18):5769-5780. PubMed ID: 34604968
[TBL] [Abstract][Full Text] [Related]
20. Applying machine-learning models to differentiate benign and malignant thyroid nodules classified as C-TIRADS 4 based on 2D-ultrasound combined with five contrast-enhanced ultrasound key frames.
Chen JH; Zhang YQ; Zhu TT; Zhang Q; Zhao AX; Huang Y
Front Endocrinol (Lausanne); 2024; 15():1299686. PubMed ID: 38633756
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
