Related references
Note: Only part of the references are listed.nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation
Fabian Isensee et al.
NATURE METHODS (2021)
Transfer Learning of a Deep Learning Model for Exploring Tourists' Urban Image Using Geotagged Photos
Youngok Kang et al.
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION (2021)
Automatic Breast Tumor Diagnosis in MRI Based on a Hybrid CNN and Feature-Based Method Using Improved Deer Hunting Optimization Algorithm
Weitao Ha et al.
COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE (2021)
Breast tumor movements analysis using MRI scans in prone and supine positions
Chuan-Bing Wang et al.
SCIENTIFIC REPORTS (2020)
Automated fibroglandular tissue segmentation in breast MRI using generative adversarial networks
Xiangyuan Ma et al.
PHYSICS IN MEDICINE AND BIOLOGY (2020)
Not-so-supervised: A survey of semi-supervised, multi-instance, and transfer learning in medical image analysis
Veronika Cheplygina et al.
MEDICAL IMAGE ANALYSIS (2019)
Automated deep learning method for whole-breast segmentation in diffusion-weighted breast MRI
Lei Zhang et al.
JOURNAL OF MAGNETIC RESONANCE IMAGING (2019)
Breast cancer statistics, 2019
Carol E. DeSantis et al.
CA-A CANCER JOURNAL FOR CLINICIANS (2019)
Contrast-enhanced MRI for breast cancer screening
Ritse M. Mann et al.
JOURNAL OF MAGNETIC RESONANCE IMAGING (2019)
Evaluation of the correlation between prostatic displacement and rectal deformation using the Dice similarity coefficient of the rectum
Yoshinori Tanabe et al.
Medical Dosimetry (2019)
U-Net: deep learning for cell counting, detection, and morphometry
Thorsten Falk et al.
NATURE METHODS (2019)
Automatic Breast and Fibroglandular Tissue Segmentation in Breast MRI Using Deep Learning by a Fully-Convolutional Residual Neural Network U-Net
Yang Zhang et al.
ACADEMIC RADIOLOGY (2019)
Quantitative Volumetric K-Means Cluster Segmentation of Fibroglandular Tissue and Skin in Breast Mill
Anton Niukkanen et al.
JOURNAL OF DIGITAL IMAGING (2018)
Deep Learning Based Transfer Learning for Possible Facial Psychological Expression Recognition
Mi Li et al.
JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS (2018)
Breast MRI segmentation for density estimation: Do different methods give the same results and how much do differences matter?
Simon J. Doran et al.
MEDICAL PHYSICS (2017)
Using deep learning to segment breast and fibroglandular tissue in MRI volumes
Mehmet Ufuk Dalmis et al.
MEDICAL PHYSICS (2017)
A review of biomechanically informed breast image registration
John H. Hipwell et al.
PHYSICS IN MEDICINE AND BIOLOGY (2016)
Symmetric Biomechanically Guided Prone-to-Supine Breast Image Registration
Bjoern Eiben et al.
ANNALS OF BIOMEDICAL ENGINEERING (2016)
Automated breast-region segmentation in the axial breast MR images
Jana Milenkovic et al.
COMPUTERS IN BIOLOGY AND MEDICINE (2015)
Transfer Learning for Visual Categorization: A Survey
Ling Shao et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2015)
Transfer learning for activity recognition: a survey
Diane Cook et al.
KNOWLEDGE AND INFORMATION SYSTEMS (2013)
Template-based automatic breast segmentation on MRI by excluding the chest region
Muqing Lin et al.
MEDICAL PHYSICS (2013)
Automated chest wall line detection for whole-breast segmentation in sagittal breast MR images
Shandong Wu et al.
MEDICAL PHYSICS (2013)
The descriptive epidemiology of female breast cancer: An international comparison of screening, incidence, survival and mortality
Danny R. Youlden et al.
CANCER EPIDEMIOLOGY (2012)
A new bias field correction method combining N3 and FCM for improved segmentation of breast density on MRI
Muqing Lin et al.
MEDICAL PHYSICS (2011)
Quantitative Analysis of Lesion Morphology and Texture Features for Diagnostic Prediction in Breast MRI
Ke Nie et al.
ACADEMIC RADIOLOGY (2008)
Development of a quantitative method for analysis of breast density based on three-dimensional breast MRI
Ke Nie et al.
MEDICAL PHYSICS (2008)
Mammographic density and the risk and detection of breast cancer
Norman F. Boyd et al.
NEW ENGLAND JOURNAL OF MEDICINE (2007)
The use of MRI scanning for investigating soft-tissue abnormalities in the elbow
P Melloni et al.
EUROPEAN JOURNAL OF RADIOLOGY (2005)
Share Paper
