Natasha Antropova
Natasha Antropova
DeepMind
Zweryfikowany adres z google.com
Tytuł
Cytowane przez
Cytowane przez
Rok
International evaluation of an AI system for breast cancer screening
SM McKinney, M Sieniek, V Godbole, J Godwin, N Antropova, H Ashrafian, ...
Nature 577 (7788), 89-94, 2020
7162020
A deep feature fusion methodology for breast cancer diagnosis demonstrated on three imaging modality datasets
N Antropova, BQ Huynh, ML Giger
Medical physics 44 (10), 5162-5171, 2017
1952017
Deep learning in breast cancer risk assessment: evaluation of convolutional neural networks on a clinical dataset of full-field digital mammograms
H Li, ML Giger, BQ Huynh, NO Antropova
Journal of medical imaging 4 (4), 041304, 2017
492017
Use of clinical MRI maximum intensity projections for improved breast lesion classification with deep convolutional neural networks
NO Antropova, H Abe, ML Giger
Journal of Medical Imaging 5 (1), 014503, 2018
432018
Most-enhancing tumor volume by MRI radiomics predicts recurrence-free survival “early on” in neoadjuvant treatment of breast cancer
K Drukker, H Li, N Antropova, A Edwards, J Papaioannou, ML Giger
Cancer imaging 18 (1), 1-9, 2018
352018
SU‐D‐207B‐06: predicting breast cancer malignancy on DCE‐MRI data using pre‐trained convolutional neural networks
N Antropova, B Huynh, M Giger
Medical physics 43 (6Part4), 3349-3350, 2016
292016
Comparison of breast DCE-MRI contrast time points for predicting response to neoadjuvant chemotherapy using deep convolutional neural network features with transfer learning
BQ Huynh, N Antropova, ML Giger
Medical imaging 2017: computer-aided diagnosis 10134, 101340U, 2017
192017
Breast lesion classification based on dynamic contrast-enhanced magnetic resonance images sequences with long short-term memory networks
N Antropova, B Huynh, H Li, ML Giger
Journal of Medical Imaging 6 (1), 011002, 2018
122018
Performance comparison of deep learning and segmentation-based radiomic methods in the task of distinguishing benign and malignant breast lesions on DCE-MRI
N Antropova, B Huynh, M Giger
Medical imaging 2017: Computer-aided diagnosis 10134, 101341G, 2017
112017
Recurrent neural networks for breast lesion classification based on DCE-MRIs
N Antropova, B Huynh, M Giger
Medical imaging 2018: Computer-aided diagnosis 10575, 105752M, 2018
92018
Efficient iterative image reconstruction algorithm for dedicated breast CT
N Antropova, A Sanchez, IS Reiser, EY Sidky, J Boone, X Pan
Medical Imaging 2016: Physics of Medical Imaging 9783, 97834K, 2016
62016
Model-based quantitative optical biopsy in multilayer in vitro soft tissue models for whole field assessment of nonmelanoma skin cancer
BN Kanakaraj, SN Unni
Journal of Medical Imaging 5 (1), 014506, 2018
52018
Addendum: International evaluation of an AI system for breast cancer screening
SM McKinney, M Sieniek, V Godbole, J Godwin, N Antropova, H Ashrafian, ...
Nature 586 (7829), E19-E19, 2020
42020
Deep Learning and Radiomics of Breast Cancer on DCE-MRI in Assessment of Malignancy and Response to Therapy
N Antropova
The University of Chicago, 2018
12018
TU‐AB‐BRA‐07: Radiomics of Breast Cancer: A Robustness Study
N Antropova, M Giger, H Li, K Drukker, L Lan
Medical Physics 42 (6Part31), 3588-3588, 2015
12015
International evaluation of an AI system for breast cancer screening (vol 577, pg 89, 2020)
SM McKinney, M Sieniek, V Godbole, J Godwin, N Antropova, H Ashrafian, ...
NATURE 586 (7829), E19-E19, 2020
2020
Use of Deep Learning in the Classification of Benign Lesions, Lumina! A Cancers, and Other Molecular Cancer Subtypes in Breast Magnetic Resonance Imaging
H Whitney, N Antropova, M Giger
MEDICAL PHYSICS 45 (6), E175-E175, 2018
2018
MRI-Based Prediction of Recurrence-Free Survival in Breast Cancer Patients Early On in Neoadjuvant Chemotherapy: SU-F-605-07
K Drukker, H Li, N Antropova, A Edwards, J Papaioannou, M Giger
Medical Physics 44 (6), 2017
2017
Multi-task Learning in the Computerized Diagnosis of Breast Cancer on DCE-MRIs
N Antropova, B Huynh, M Giger
arXiv preprint arXiv:1701.03882, 2017
2017
Radiomics of Breast Cancer: A Robustness Study: TU-AB-BRA-07
N Antropova, M Giger, H Li, K Drukker, L Lan
Medical Physics 42 (6), 2015
2015
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