125 related articles for article (PubMed ID: 38508797)
1. Benign and malignant classification of breast tumor ultrasound images using conventional radiomics and transfer learning features: A multicenter retrospective study.
Tian R; Lu G; Tang S; Sang L; Ma H; Qian W; Yang W
Med Eng Phys; 2024 Mar; 125():104117. PubMed ID: 38508797
[TBL] [Abstract][Full Text] [Related]
2. A multi-stage fusion framework to classify breast lesions using deep learning and radiomics features computed from four-view mammograms.
Jones MA; Sadeghipour N; Chen X; Islam W; Zheng B
Med Phys; 2023 Dec; 50(12):7670-7683. PubMed ID: 37083190
[TBL] [Abstract][Full Text] [Related]
3. Differentiation of benign and malignant parotid gland tumors based on the fusion of radiomics and deep learning features on ultrasound images.
Wang Y; Gao J; Yin Z; Wen Y; Sun M; Han R
Front Oncol; 2024; 14():1384105. PubMed ID: 38803533
[TBL] [Abstract][Full Text] [Related]
4. Constructing the Optimal Classification Model for Benign and Malignant Breast Tumors Based on Multifeature Analysis from Multimodal Images.
Tian R; Lu G; Zhao N; Qian W; Ma H; Yang W
J Imaging Inform Med; 2024 Feb; ():. PubMed ID: 38381383
[TBL] [Abstract][Full Text] [Related]
5. Effective diagnostic model construction based on discriminative breast ultrasound image regions using deep feature extraction.
Yu H; Sun H; Li J; Shi L; Bao N; Li H; Qian W; Zhou S
Med Phys; 2021 Jun; 48(6):2920-2928. PubMed ID: 33690962
[TBL] [Abstract][Full Text] [Related]
6. Predicting the risk stratification of gastrointestinal stromal tumors using machine learning-based ultrasound radiomics.
Zhuo M; Tang Y; Guo J; Qian Q; Xue E; Chen Z
J Med Ultrason (2001); 2024 Jan; 51(1):71-82. PubMed ID: 37798591
[TBL] [Abstract][Full Text] [Related]
7. A multi-instance tumor subtype classification method for small PET datasets using RA-DL attention module guided deep feature extraction with radiomics features.
Diao Z; Jiang H
Comput Biol Med; 2024 May; 174():108461. PubMed ID: 38626509
[TBL] [Abstract][Full Text] [Related]
8. Fus2Net: a novel Convolutional Neural Network for classification of benign and malignant breast tumor in ultrasound images.
Ma H; Tian R; Li H; Sun H; Lu G; Liu R; Wang Z
Biomed Eng Online; 2021 Nov; 20(1):112. PubMed ID: 34794443
[TBL] [Abstract][Full Text] [Related]
9. Application of MRI Radiomics-Based Machine Learning Model to Improve Contralateral BI-RADS 4 Lesion Assessment.
Hao W; Gong J; Wang S; Zhu H; Zhao B; Peng W
Front Oncol; 2020; 10():531476. PubMed ID: 33194589
[TBL] [Abstract][Full Text] [Related]
10. Classification of pulmonary lesion based on multiparametric MRI: utility of radiomics and comparison of machine learning methods.
Wang X; Wan Q; Chen H; Li Y; Li X
Eur Radiol; 2020 Aug; 30(8):4595-4605. PubMed ID: 32222795
[TBL] [Abstract][Full Text] [Related]
11. Classification of MR-Detected Additional Lesions in Patients With Breast Cancer Using a Combination of Radiomics Analysis and Machine Learning.
Lee HJ; Nguyen AT; Ki SY; Lee JE; Do LN; Park MH; Lee JS; Kim HJ; Park I; Lim HS
Front Oncol; 2021; 11():744460. PubMed ID: 34926256
[TBL] [Abstract][Full Text] [Related]
12. Clinical value of radiomics and machine learning in breast ultrasound: a multicenter study for differential diagnosis of benign and malignant lesions.
Romeo V; Cuocolo R; Apolito R; Stanzione A; Ventimiglia A; Vitale A; Verde F; Accurso A; Amitrano M; Insabato L; Gencarelli A; Buonocore R; Argenzio MR; Cascone AM; Imbriaco M; Maurea S; Brunetti A
Eur Radiol; 2021 Dec; 31(12):9511-9519. PubMed ID: 34018057
[TBL] [Abstract][Full Text] [Related]
13. Exploring the efficacy of multi-flavored feature extraction with radiomics and deep features for prostate cancer grading on mpMRI.
Khanfari H; Mehranfar S; Cheki M; Mohammadi Sadr M; Moniri S; Heydarheydari S; Rezaeijo SM
BMC Med Imaging; 2023 Nov; 23(1):195. PubMed ID: 37993801
[TBL] [Abstract][Full Text] [Related]
14. Ultrasound-based deep learning radiomics model for differentiating benign, borderline, and malignant ovarian tumours: a multi-class classification exploratory study.
Du Y; Guo W; Xiao Y; Chen H; Yao J; Wu J
BMC Med Imaging; 2024 Apr; 24(1):89. PubMed ID: 38622546
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. A Comparison of Computer-Aided Diagnosis Schemes Optimized Using Radiomics and Deep Transfer Learning Methods.
Danala G; Maryada SK; Islam W; Faiz R; Jones M; Qiu Y; Zheng B
Bioengineering (Basel); 2022 Jun; 9(6):. PubMed ID: 35735499
[TBL] [Abstract][Full Text] [Related]
17. Breast ultrasound tumor image classification using image decomposition and fusion based on adaptive multi-model spatial feature fusion.
Zhuang Z; Yang Z; Raj ANJ; Wei C; Jin P; Zhuang S
Comput Methods Programs Biomed; 2021 Sep; 208():106221. PubMed ID: 34144251
[TBL] [Abstract][Full Text] [Related]
18. Pretreatment ultrasound-based deep learning radiomics model for the early prediction of pathologic response to neoadjuvant chemotherapy in breast cancer.
Yu FH; Miao SM; Li CY; Hang J; Deng J; Ye XH; Liu Y
Eur Radiol; 2023 Aug; 33(8):5634-5644. PubMed ID: 36976336
[TBL] [Abstract][Full Text] [Related]
19. Diagnostic Performance of 2D and 3D T2WI-Based Radiomics Features With Machine Learning Algorithms to Distinguish Solid Solitary Pulmonary Lesion.
Wan Q; Zhou J; Xia X; Hu J; Wang P; Peng Y; Zhang T; Sun J; Song Y; Yang G; Li X
Front Oncol; 2021; 11():683587. PubMed ID: 34868905
[TBL] [Abstract][Full Text] [Related]
20. Parameter tuning in machine learning based on radiomics biomarkers of lung cancer.
Luo Y; Li Y; Zhang Y; Zhang J; Liang M; Jiang L; Guo L
J Xray Sci Technol; 2022; 30(3):477-490. PubMed ID: 35342074
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]