Detalhe da pesquisa
1.
Convolutional Neural Network Using a Breast MRI Tumor Dataset Can Predict Oncotype Dx Recurrence Score.
J Magn Reson Imaging
; 49(2): 518-524, 2019 02.
Artigo
em Inglês
| MEDLINE | ID: mdl-30129697
2.
Accuracy of Distinguishing Atypical Ductal Hyperplasia From Ductal Carcinoma In Situ With Convolutional Neural Network-Based Machine Learning Approach Using Mammographic Image Data.
AJR Am J Roentgenol
; 212(5): 1166-1171, 2019 May.
Artigo
em Inglês
| MEDLINE | ID: mdl-30860901
3.
Fully Automated Convolutional Neural Network Method for Quantification of Breast MRI Fibroglandular Tissue and Background Parenchymal Enhancement.
J Digit Imaging
; 32(1): 141-147, 2019 02.
Artigo
em Inglês
| MEDLINE | ID: mdl-30076489
4.
Predicting Breast Cancer Molecular Subtype with MRI Dataset Utilizing Convolutional Neural Network Algorithm.
J Digit Imaging
; 32(2): 276-282, 2019 04.
Artigo
em Inglês
| MEDLINE | ID: mdl-30706213
5.
Prior to Initiation of Chemotherapy, Can We Predict Breast Tumor Response? Deep Learning Convolutional Neural Networks Approach Using a Breast MRI Tumor Dataset.
J Digit Imaging
; 32(5): 693-701, 2019 10.
Artigo
em Inglês
| MEDLINE | ID: mdl-30361936
6.
Predicting Post Neoadjuvant Axillary Response Using a Novel Convolutional Neural Network Algorithm.
Ann Surg Oncol
; 25(10): 3037-3043, 2018 Oct.
Artigo
em Inglês
| MEDLINE | ID: mdl-29978368
7.
Insulin Hexamer-Caged Gadolinium Ion as MRI Contrast-o-phore.
Chemistry
; 24(42): 10646-10652, 2018 Jul 25.
Artigo
em Inglês
| MEDLINE | ID: mdl-29873848
8.
Axillary Lymph Node Evaluation Utilizing Convolutional Neural Networks Using MRI Dataset.
J Digit Imaging
; 31(6): 851-856, 2018 12.
Artigo
em Inglês
| MEDLINE | ID: mdl-29696472
9.
Evaluation of neonatal brain myelination using the T1- and T2-weighted MRI ratio.
J Magn Reson Imaging
; 46(3): 690-696, 2017 09.
Artigo
em Inglês
| MEDLINE | ID: mdl-28019046
10.
Can diffusion-weighted imaging serve as a biomarker of fibrosis in pancreatic adenocarcinoma?
J Magn Reson Imaging
; 46(2): 393-402, 2017 08.
Artigo
em Inglês
| MEDLINE | ID: mdl-28152252
11.
Weakly Supervised Deep Learning Approach to Breast MRI Assessment.
Acad Radiol
; 29 Suppl 1: S166-S172, 2022 01.
Artigo
em Inglês
| MEDLINE | ID: mdl-34108114
12.
Deep learning prediction of axillary lymph node status using ultrasound images.
Comput Biol Med
; 143: 105250, 2022 Apr.
Artigo
em Inglês
| MEDLINE | ID: mdl-35114444
13.
How Many Radiographs Does It Take to Screen for Femoral Cam Morphology?: A Noninferiority Study.
Curr Probl Diagn Radiol
; 50(1): 48-53, 2021.
Artigo
em Inglês
| MEDLINE | ID: mdl-31351696
14.
Multi-site, multi-platform comparison of MRI T1 measurement using the system phantom.
PLoS One
; 16(6): e0252966, 2021.
Artigo
em Inglês
| MEDLINE | ID: mdl-34191819
15.
A novel CNN algorithm for pathological complete response prediction using an I-SPY TRIAL breast MRI database.
Magn Reson Imaging
; 73: 148-151, 2020 11.
Artigo
em Inglês
| MEDLINE | ID: mdl-32889091
16.
Convolutional Neural Network Detection of Axillary Lymph Node Metastasis Using Standard Clinical Breast MRI.
Clin Breast Cancer
; 20(3): e301-e308, 2020 06.
Artigo
em Inglês
| MEDLINE | ID: mdl-32139272
17.
Advanced MR Imaging of the Temporal Bone.
Neuroimaging Clin N Am
; 29(1): 197-202, 2019 Feb.
Artigo
em Inglês
| MEDLINE | ID: mdl-30466642
18.
Convolutional Neural Network Based Breast Cancer Risk Stratification Using a Mammographic Dataset.
Acad Radiol
; 26(4): 544-549, 2019 04.
Artigo
em Inglês
| MEDLINE | ID: mdl-30072292
19.
Multicenter Repeatability Study of a Novel Quantitative Diffusion Kurtosis Imaging Phantom.
Tomography
; 5(1): 36-43, 2019 03.
Artigo
em Inglês
| MEDLINE | ID: mdl-30854440
20.
Repeatability of Quantitative Diffusion-Weighted Imaging Metrics in Phantoms, Head-and-Neck and Thyroid Cancers: Preliminary Findings.
Tomography
; 5(1): 15-25, 2019 03.
Artigo
em Inglês
| MEDLINE | ID: mdl-30854438