14th International Workshop on Breast Imaging (IWBI 2018)
8-11 July 2018
Atlanta, Georgia, United States
Front Matter: Volume 10718
Proc. SPIE 10718, Front Matter: Volume 10718, 1071801 (6 July 2018); doi: 10.1117/12.2502754
Screening & Clinical Interpretation
Proc. SPIE 10718, Breast compression parameters among women imaged with full field digital mammography and breast tomosynthesis in BreastScreen Norway , 1071802 (6 July 2018); doi: 10.1117/12.2317918
Proc. SPIE 10718, Can radiologists improve their breast cancer detection in mammography when using a deep learning based computer system as decision support?, 1071803 (6 July 2018); doi: 10.1117/12.2317937
Proc. SPIE 10718, Detection of the abnormal gist in the prior mammograms even with no overt sign of breast cancer , 1071804 (6 July 2018); doi: 10.1117/12.2318321
Deep Learning: Lesion Detection & Classification
Proc. SPIE 10718, Automated lesion detection and segmentation in digital mammography using a u-net deep learning network, 1071805 (6 July 2018); doi: 10.1117/12.2318326
Proc. SPIE 10718, Deep learning in computer-aided diagnosis incorporating mammographic characteristics of both tumor and parenchyma stroma, 1071806 (6 July 2018); doi: 10.1117/12.2318282
Proc. SPIE 10718, Comparing the performance of various deep networks for binary classification of breast tumours, 1071807 (6 July 2018); doi: 10.1117/12.2318084
Proc. SPIE 10718, Improving the automated detection of calcifications by combining deep cascades and deep convolutional nets, 1071808 (6 July 2018); doi: 10.1117/12.2318016
Proc. SPIE 10718, Retrieval of reference images of breast masses on mammograms by similarity space modeling, 1071809 (6 July 2018); doi: 10.1117/12.2318717
Breast Density
Proc. SPIE 10718, Volumetric breast density measurement for personalized screening: accuracy, reproducibility, and agreement with visual assessment, 107180A (6 July 2018); doi: 10.1117/12.2315069
Proc. SPIE 10718, Mammogram breast density classification using mean-elliptical local binary patterns, 107180B (6 July 2018); doi: 10.1117/12.2318057
Proc. SPIE 10718, Mammographic breast density over time among women who have participated in BreastScreen Norway, 107180C (6 July 2018); doi: 10.1117/12.2317927
Proc. SPIE 10718, Using a convolutional neural network to predict readers' estimates of mammographic density for breast cancer risk assessment, 107180D (6 July 2018); doi: 10.1117/12.2318464
Proc. SPIE 10718, Masking risk predictors in screening mammography, 107180E (6 July 2018); doi: 10.1117/12.2318074
Intersection of Clinical Imaging Sources
Proc. SPIE 10718, Simulation of sequential pathology images for the virtual clinical trials with rad-path correlation, 107180F (6 July 2018); doi: 10.1117/12.2318492
Proc. SPIE 10718, Developing imaging biomarkers for mammographically-occult cancer in dense breasts using a radiologist's progress rating on cancer development: a preliminary analysis, 107180G (6 July 2018); doi: 10.1117/12.2318324
Proc. SPIE 10718, Effect of biopsy on the MRI radiomics classification of benign lesions and luminal A cancers , 107180H (6 July 2018); doi: 10.1117/12.2318387
Image Quality: Dose & Motion
Proc. SPIE 10718, Diagnostic radiation dose after the implementation of digital breast tomosynthesis screening, 107180I (6 July 2018); doi: 10.1117/12.2318140
Proc. SPIE 10718, Dose reduction in breast CT by spectrum switching, 107180J (6 July 2018); doi: 10.1117/12.2318425
Proc. SPIE 10718, Development of an automated detection algorithm for patient motion blur in digital mammograms, 107180K (6 July 2018); doi: 10.1117/12.2318225
Proc. SPIE 10718, Measuring breast motion at multiple DBT compression levels using ultrasound speckle-tracking techniques, 107180L (6 July 2018); doi: 10.1117/12.2318394
Novel Imaging Technology
Proc. SPIE 10718, The PET/X dedicated breast-PET scanner for optimizing cancer therapy, 107180M (6 July 2018); doi: 10.1117/12.2318419
Proc. SPIE 10718, Acquisition parameters for dual-energy contrast-enhanced digital mammography using a micelle-based all-in-one nanoparticle (AION) contrast agent: a phantom study, 107180N (6 July 2018); doi: 10.1117/12.2318093
Proc. SPIE 10718, Multisource x-ray system for artifact reduction in dedicated breast CT, 107180O (6 July 2018); doi: 10.1117/12.2317846
Imaging Phantoms
Proc. SPIE 10718, Breast phantom validation of a mammographic image modification method, 107180P (6 July 2018); doi: 10.1117/12.2318367
Proc. SPIE 10718, Method for task-based evaluation of clinical FFDM and DBT systems using an anthropomorphic breast phantom, 107180Q (6 July 2018); doi: 10.1117/12.2318523
Proc. SPIE 10718, Validation of the textural realism of a 3D anthropomorphic phantom for digital breast tomosynthesis, 107180R (6 July 2018); doi: 10.1117/12.2318029
Proc. SPIE 10718, Development of a physical anthropomorphic breast phantom for objective task-based assessment of dedicated breast CT systems, 107180S (6 July 2018); doi: 10.1117/12.2318524
Image Analysis & Computer-Aided Techniques
Proc. SPIE 10718, Orientation dependent detectability of fiber-like signals in linear iterative image reconstruction for breast tomosynthesis, 107180T (6 July 2018); doi: 10.1117/12.2318463
Proc. SPIE 10718, A framework for distinguishing benign from malignant breast histopathological images using deep residual networks, 107180U (6 July 2018); doi: 10.1117/12.2318320
Proc. SPIE 10718, Superpixel pattern graphs for identifying breast mass ROIs in dense background: a preliminary study, 107180V (6 July 2018); doi: 10.1117/12.2317589
Proc. SPIE 10718, Mammogram denoising to improve the calcification detection performance of convolutional nets, 107180W (6 July 2018); doi: 10.1117/12.2318069
Proc. SPIE 10718, Breast cancer detection using synthetic mammograms from generative adversarial networks in convolutional neural networks, 107180X (6 July 2018); doi: 10.1117/12.2318100
Simulation & Virtual Clinical Trials
Proc. SPIE 10718, Performance evaluation of a 3D structured phantom with simulated lesions on breast imaging systems, 107180Y (6 July 2018); doi: 10.1117/12.2318472
Proc. SPIE 10718, A hybrid approach for virtual clinical trials for mammographic imaging, 107180Z (6 July 2018); doi: 10.1117/12.2318452
Proc. SPIE 10718, Phantom-based comparison of microcalcification visibility between digital and synthetic mammography using humans and a deep neural network as observers , 1071810 (6 July 2018); doi: 10.1117/12.2318458
Interactive Poster Session
Proc. SPIE 10718, A deep learning framework for micro-calcification detection in 2D mammography and C-view, 1071811 (6 July 2018); doi: 10.1117/12.2318023
Proc. SPIE 10718, Multi-scale morphological feature extraction for the classification of micro-calcifications, 1071812 (6 July 2018); doi: 10.1117/12.2317726
Proc. SPIE 10718, Transfer deep learning mammography diagnostic model from public datasets to clinical practice: a comparison of model performance and mammography datasets, 1071813 (6 July 2018); doi: 10.1117/12.2317411
Proc. SPIE 10718, Radiation dose reduction in digital breast tomosynthesis (DBT) by means of neural network convolution (NNC) deep learning , 1071814 (6 July 2018); doi: 10.1117/12.2317789
Proc. SPIE 10718, Metastatic breast cancer: characterization of axillary sentinel lymph node (SLN) on the preoperative spectral CT, 1071815 (6 July 2018); doi: 10.1117/12.2318323
Proc. SPIE 10718, Automatic classification of clustered microcalcifications in digitized mammogram using ensemble learning, 1071816 (6 July 2018); doi: 10.1117/12.2315375
Proc. SPIE 10718, Creation of new artificial calcification shadows for breast cancer and verification of effectiveness of CAD development technique that uses no actual cases, 1071817 (6 July 2018); doi: 10.1117/12.2315790
Proc. SPIE 10718, Fully automated pectoral muscle identification on MLO-view mammograms with deep convolutional neural network , 1071818 (6 July 2018); doi: 10.1117/12.2318124
Proc. SPIE 10718, First results with a deep learning (feed-forward CNN) approach for daily quality control in digital breast tomosynthesis, 1071819 (6 July 2018); doi: 10.1117/12.2318451
Proc. SPIE 10718, Bag of visual words based approach for the classification of benign and malignant masses in mammograms using voting-based feature encoding, 107181A (6 July 2018); doi: 10.1117/12.2316307
Proc. SPIE 10718, Classification of mammographic microcalcification clusters with machine learning confidence levels, 107181B (6 July 2018); doi: 10.1117/12.2318058
Proc. SPIE 10718, A novel nipple detection algorithm on Digital Mammography (DM), 107181C (6 July 2018); doi: 10.1117/12.2318042
Proc. SPIE 10718, Deep learning methods aid in predicting risk of interval cancer, 107181D (6 July 2018); doi: 10.1117/12.2318471
Proc. SPIE 10718, Deep learning and color variability in breast cancer histopathological images: a preliminary study, 107181E (6 July 2018); doi: 10.1117/12.2316613
Proc. SPIE 10718, Mass detection in mammograms using pre-trained deep learning models, 107181F (6 July 2018); doi: 10.1117/12.2317681
Proc. SPIE 10718, Automatic estimation of glandular tissue loss due to limited reconstruction voxel size in tomographic images of the breast, 107181G (6 July 2018); doi: 10.1117/12.2317938