Artificial intelligence in breast ultrasonography

Deep learning radiomics can predict axillary lymph node status in early-stage breast cancer

(2020) Xueyi Zheng et al.   Nature Communications

Prediction of Cancer Incidence and Mortality in Korea, 2020

(2020) Kyu-Won Jung et al.   Cancer Research and Treatment

Computer-aided tumor detection in automated breast ultrasound using a 3-D convolutional neural network

(2020) Woo Kyung Moon et al.   COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE

Axillary Nodal Evaluation in Breast Cancer: State of the Art

(2020) Jung Min Chang et al.   RADIOLOGY

Minimum information about clinical artificial intelligence modeling: the MI-CLAIM checklist

(2020) Beau Norgeot et al.   NATURE MEDICINE

One Algorithm May Not Fit All: How Selection Bias Affects Machine Learning Performance

(2020) Alice C. Yu et al.   RADIOGRAPHICS

A computer-aided diagnosis system using artificial intelligence for the diagnosis and characterization of breast masses on ultrasound

(2019) Hee Jeong Park et al.   MEDICINE

Not-so-supervised: a survey of semi-supervised, multi-instance, and transfer learning in medical image analysis

(2019) Veronika Cheplygina et al.   MEDICAL IMAGE ANALYSIS

Automatic classification of ultrasound breast lesions using a deep convolutional neural network mimicking human decision-making

(2019) Alexander Ciritsis et al.   EUROPEAN RADIOLOGY

Distinction between benign and malignant breast masses at breast ultrasound using deep learning method with convolutional neural network

(2019) Tomoyuki Fujioka et al.   JAPANESE JOURNAL OF RADIOLOGY

Performance and Reading Time of Automated Breast US with or without Computer-aided Detection

(2019) Shanling Yang et al.   RADIOLOGY

An experimental study on breast lesion detection and classification from ultrasound images using deep learning architectures

(2019) Zhantao Cao et al.   BMC MEDICAL IMAGING

Performance of a Deep Neural Network Algorithm Based on a Small Medical Image Dataset: Incremental Impact of 3D-to-2D Reformation Combined with Novel Data Augmentation, Photometric Conversion, or Transfer Learning

(2019) Vikash Gupta et al.   JOURNAL OF DIGITAL IMAGING

Lymph Node Metastasis Prediction from Primary Breast Cancer US Images Using Deep Learning

(2019) Li-Qiang Zhou et al.   RADIOLOGY

Predicting Post Neoadjuvant Axillary Response Using a Novel Convolutional Neural Network Algorithm

(2018) Richard Ha et al.   ANNALS OF SURGICAL ONCOLOGY

Automated and real-time segmentation of suspicious breast masses using convolutional neural network

(2018) Viksit Kumar et al.   PLoS One

Methodologic Guide for Evaluating Clinical Performance and Effect of Artificial Intelligence Technology for Medical Diagnosis and Prediction

(2018) Seong Ho Park et al.   RADIOLOGY

Projection of Breast Cancer Burden due to Reproductive/Lifestyle Changes in Korean Women (2013-2030) Using an Age-Period-Cohort Model

(2018) Joo Eun Lee et al.   Cancer Research and Treatment

Automated Breast Ultrasound Lesions Detection Using Convolutional Neural Networks

(2018) Moi Hoon Yap et al.   IEEE Journal of Biomedical and Health Informatics

Breast density implications and supplemental screening

(2018) Athina Vourtsis et al.   EUROPEAN RADIOLOGY

Tumor Detection in Automated Breast Ultrasound Using 3-D CNN and Prioritized Candidate Aggregation

(2018) Tsung-Chen Chiang et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Joint Weakly and Semi-Supervised Deep Learning for Localization and Classification of Masses in Breast Ultrasound Images

(2018) Seung Yeon Shin et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Prior to Initiation of Chemotherapy, Can We Predict Breast Tumor Response? Deep Learning Convolutional Neural Networks Approach Using a Breast MRI Tumor Dataset

(2018) Richard Ha et al.   JOURNAL OF DIGITAL IMAGING

Breast mass classification in sonography with transfer learning using a deep convolutional neural network and color conversion

(2018) Michal Byra et al.   MEDICAL PHYSICS

An explainable deep-learning algorithm for the detection of acute intracranial haemorrhage from small datasets

(2018) Hyunkwang Lee et al.   Nature Biomedical Engineering

National Performance Benchmarks for Modern Screening Digital Mammography: Update from the Breast Cancer Surveillance Consortium

(2017) Constance D. Lehman et al.   RADIOLOGY

Screening Breast Ultrasound: Past, Present, and Future

(2015) Rachel F. Brem et al.   AMERICAN JOURNAL OF ROENTGENOLOGY

Awareness of Breast Density and Its Impact on Breast Cancer Detection and Risk

(2015) Deborah J. Rhodes et al.   JOURNAL OF CLINICAL ONCOLOGY

Tumor detection in automated breast ultrasound images using quantitative tissue clustering

(2014) Woo Kyung Moon et al.   MEDICAL PHYSICS

The California Breast Density Information Group: A Collaborative Response to the Issues of Breast Density, Breast Cancer Risk, and Breast Density Notification Legislation

(2013) Elissa R. Price et al.   RADIOLOGY

Computer-Aided Tumor Detection Based on Multi-Scale Blob Detection Algorithm in Automated Breast Ultrasound Images

(2012) Woo Kyung Moon et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Rapid image stitching and computer-aided detection for multipass automated breast ultrasound

(2010) Ruey-Feng Chang et al.   MEDICAL PHYSICS

Breast Imaging Reporting and Data System Lexicon for US: Interobserver Agreement for Assessment of Breast Masses

(2009) Nouf Abdullah et al.   RADIOLOGY

Weakly Supervised Learning of a Classifier for Unusual Event Detection

(2008) M. Jager et al.   IEEE TRANSACTIONS ON IMAGE PROCESSING