Related references
Note: Only part of the references are listed.Artificial intelligence for breast cancer detection in mammography and digital breast tomosynthesis: State of the art
Ioannis Sechopoulos et al.
SEMINARS IN CANCER BIOLOGY (2021)
Artificial Intelligence Applied to Breast MRI for Improved Diagnosis
Yulei Jiang et al.
RADIOLOGY (2021)
Robust breast cancer detection in mammography and digital breast tomosynthesis using an annotation-efficient deep learning approach
William Lotter et al.
NATURE MEDICINE (2021)
Applications of Artificial Intelligence in Breast Imaging
Matthew B. Morgan et al.
RADIOLOGIC CLINICS OF NORTH AMERICA (2021)
Artificial intelligence in breast ultrasonography
Jaeil Kim et al.
ULTRASONOGRAPHY (2021)
Artificial intelligence in the interpretation of breast cancer on MRI
Deepa Sheth et al.
JOURNAL OF MAGNETIC RESONANCE IMAGING (2020)
Overview of radiomics in breast cancer diagnosis and prognostication
Alberto Stefano Tagliafico et al.
BREAST (2020)
CAD and AI for breast cancer-recent development and challenges
Heang-Ping Chan et al.
BRITISH JOURNAL OF RADIOLOGY (2020)
Lymph Node Metastasis Prediction from Primary Breast Cancer US Images Using Deep Learning
Li-Qiang Zhou et al.
RADIOLOGY (2020)
Deep learning radiomics can predict axillary lymph node status in early-stage breast cancer
Xueyi Zheng et al.
NATURE COMMUNICATIONS (2020)
Detection and Diagnosis of Breast Cancer Using Artificial Intelligence Based Assessment of Maximum Intensity Projection Dynamic Contrast-Enhanced Magnetic Resonance Images
Mio Adachi et al.
DIAGNOSTICS (2020)
Current Status and Future Perspectives of Artificial Intelligence in Magnetic Resonance Breast Imaging
Anke Meyer-Base et al.
CONTRAST MEDIA & MOLECULAR IMAGING (2020)
Comparison of breast density assessment between human eye and automated software on digital and synthetic mammography: Impact on breast cancer risk
M. Le Boulc'h et al.
DIAGNOSTIC AND INTERVENTIONAL IMAGING (2020)
Application of MRI Radiomics-Based Machine Learning Model to Improve Contralateral BI-RADS 4 Lesion Assessment
Wen Hao et al.
FRONTIERS IN ONCOLOGY (2020)
Artificial intelligence in breast imaging
E. P. Le et al.
CLINICAL RADIOLOGY (2019)
Breast Microcalcification Diagnosis Using Deep Convolutional Neural Network from Digital Mammograms
Hongmin Cai et al.
COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE (2019)
Automatic classification of ultrasound breast lesions using a deep convolutional neural network mimicking human decision-making
Alexander Ciritsis et al.
EUROPEAN RADIOLOGY (2019)
Impact of Machine Learning With Multiparametric Magnetic Resonance Imaging of the Breast for Early Prediction of Response to Neoadjuvant Chemotherapy and Survival Outcomes in Breast Cancer Patients
Amirhessam Tahmassebi et al.
INVESTIGATIVE RADIOLOGY (2019)
Artificial Intelligence-Based Classification of Breast Lesions Imaged With a Multiparametric Breast MRI Protocol With Ultrafast DCE-MRI, T2, and DWI
Mehmet U. Dalmis et al.
INVESTIGATIVE RADIOLOGY (2019)
Automated diagnosis of breast ultrasonography images using deep neural networks
Xiaofeng Qi et al.
MEDICAL IMAGE ANALYSIS (2019)
Detection of potential microcalcification clusters using multivendor for-presentation digital mammograms for short-term breast cancer risk estimation
Maya Alsheh Ali et al.
MEDICAL PHYSICS (2019)
Computer-aided detection of mass in digital breast tomosynthesis using a faster region-based convolutional neural network
Ming Fan et al.
METHODS (2019)
Radiomic versus Convolutional Neural Networks Analysis for Classification of Contrast-enhancing Lesions at Multiparametric Breast MRI
Daniel Truhn et al.
RADIOLOGY (2019)
Artificial intelligence in medical imaging of the liver
Li-Qiang Zhou et al.
WORLD JOURNAL OF GASTROENTEROLOGY (2019)
Detection and characterization of MRI breast lesions using deep learning
P. Herent et al.
DIAGNOSTIC AND INTERVENTIONAL IMAGING (2019)
Can we reduce the workload of mammographic screening by automatic identification of normal exams with artificial intelligence? A feasibility study
Alejandro Rodriguez-Ruiz et al.
EUROPEAN RADIOLOGY (2019)
A Deep Learning Mammography-based Model for Improved Breast Cancer Risk Prediction
Adam Yala et al.
RADIOLOGY (2019)
Digital Mammography versus Digital Mammography Plus Tomosynthesis in Breast Cancer Screening: The Oslo Tomosynthesis Screening Trial
Per Skaane et al.
RADIOLOGY (2019)
Early breast cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up
F. Cardoso et al.
ANNALS OF ONCOLOGY (2019)
Deep convolutional neural networks for mammography: advances, challenges and applications
Dina Abdelhafiz et al.
BMC BIOINFORMATICS (2019)
Application of deep learning (3-dimensional convolutional neural network) for the prediction of pathological invasiveness in lung adenocarcinoma A preliminary study
Masahiro Yanagawa et al.
MEDICINE (2019)
Artificial Intelligence: Applications in orthognathic surgery
P. Bouletreau et al.
JOURNAL OF STOMATOLOGY ORAL AND MAXILLOFACIAL SURGERY (2019)
Machine Learning in Neurooncology Imaging: From Study Request to Diagnosis and Treatment
Javier E. Villanueva-Meyer et al.
AMERICAN JOURNAL OF ROENTGENOLOGY (2019)
Dual-mode artificially-intelligent diagnosis of breast tumours in shear-wave elastography and B-mode ultrasound using deep polynomial networks
Qi Zhang et al.
MEDICAL ENGINEERING & PHYSICS (2019)
A graph-based lesion characterization and deep embedding approach for improved computer-aided diagnosis of nonmass breast MRI lesions
Cristina Gallego-Ortiz et al.
MEDICAL IMAGE ANALYSIS (2019)
Automatic tumor segmentation in breast ultrasound images using a dilated fully convolutional network combined with an active contour model
Yuzhou Hu et al.
MEDICAL PHYSICS (2019)
Technical challenges in generalizing calibration techniques for breast density measurements
Erin E. E. Fowler et al.
MEDICAL PHYSICS (2019)
A computer-aided diagnosis system using artificial intelligence for the diagnosis and characterization of breast masses on ultrasound Added value for the inexperienced breast radiologist
Hee Jeong Park et al.
MEDICINE (2019)
Mammographic Breast Density Assessment Using Deep Learning: Clinical Implementation
Constance D. Lehman et al.
RADIOLOGY (2019)
Breast tumor classification using different features of quantitative ultrasound parametric images
Soa-Min Hsu et al.
INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY (2019)
Artificial Intelligence in Breast Imaging: Potentials and Limitations
Ellen B. Mendelson
AMERICAN JOURNAL OF ROENTGENOLOGY (2019)
A Review of the Role of Augmented Intelligence in Breast Imaging: From Automated Breast Density Assessment to Risk Stratification
Andrea Arieno et al.
AMERICAN JOURNAL OF ROENTGENOLOGY (2019)
Artificial intelligence in breast ultrasound
Ge-Ge Wu et al.
WORLD JOURNAL OF RADIOLOGY (2019)
Understanding Clinical Mammographic Breast Density Assessment: a Deep Learning Perspective
Aly A. Mohamed et al.
JOURNAL OF DIGITAL IMAGING (2018)
Support vector machine for breast cancer classification using diffusion-weighted MRI histogram features: Preliminary study
Igor Vidic et al.
JOURNAL OF MAGNETIC RESONANCE IMAGING (2018)
A deep learning method for classifying mammographic breast density categories
Aly A. Mohamed et al.
MEDICAL PHYSICS (2018)
Interpretation Time Using a Concurrent-Read Computer-Aided Detection System for Automated Breast Ultrasound in Breast Cancer Screening of Women With Dense Breast Tissue
Yulei Jiang et al.
AMERICAN JOURNAL OF ROENTGENOLOGY (2018)
Mammographic mass segmentation using fuzzy contours
Marwa Hmida et al.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2018)
A fully integrated computer-aided diagnosis system for digital X-ray mammograms via deep learning detection, segmentation, and classification
Mugahed A. Al-antari et al.
INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS (2018)
Classification of micro-calcification in mammograms using scalable linear Fisher discriminant analysis
Zobia Suhail et al.
MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING (2018)
Automated and real-time segmentation of suspicious breast masses using convolutional neural network
Viksit Kumar et al.
PLOS ONE (2018)
Computer-aided detection in chest radiography based on artificial intelligence: a survey
Chunli Qin et al.
BIOMEDICAL ENGINEERING ONLINE (2018)
Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries
Freddie Bray et al.
CA-A CANCER JOURNAL FOR CLINICIANS (2018)
Automated Detection and Segmentation of Nonmass-Enhancing Breast Tumors with Dynamic Contrast-Enhanced Magnetic Resonance Imaging
Ignacio Alvarez Illan et al.
CONTRAST MEDIA & MOLECULAR IMAGING (2018)
Analysis of the Cluster Prominence Feature for Detecting Calcifications in Mammograms
Alejandra Cruz-Bernal et al.
JOURNAL OF HEALTHCARE ENGINEERING (2018)
Use of clinical MRI maximum intensity projections for improved breast lesion classification with deep convolutional neural networks
Natalia Antropova et al.
JOURNAL OF MEDICAL IMAGING (2018)
Classification of breast cancer in ultrasound imaging using a generic deep learning analysis software: a pilot study
Anton S. Becker et al.
BRITISH JOURNAL OF RADIOLOGY (2018)
Artificial intelligence in radiology
Ahmed Hosny et al.
NATURE REVIEWS CANCER (2018)
Adjusting for BMI in analyses of volumetric mammographic density and breast cancer risk
Sue Hudson et al.
BREAST CANCER RESEARCH (2018)
Application of computer-aided diagnosis in breast ultrasound interpretation: improvements in diagnostic performance according to reader experience
Ji-Hye Choi et al.
ULTRASONOGRAPHY (2018)
Risk Factors and Preventions of Breast Cancer
Yi-Sheng Sun et al.
INTERNATIONAL JOURNAL OF BIOLOGICAL SCIENCES (2017)
Malignancy Detection on Mammography Using Dual Deep Convolutional Neural Networks and Genetically Discovered False Color Input Enhancement
Philip Teare et al.
JOURNAL OF DIGITAL IMAGING (2017)
Large scale deep learning for computer aided detection of mammographic lesions
Thijs Kooi et al.
MEDICAL IMAGE ANALYSIS (2017)
An adaptive Fuzzy C-means method utilizing neighboring information for breast tumor segmentation in ultrasound images
Yuan Feng et al.
MEDICAL PHYSICS (2017)
Globally supported radial basis function based collocation method for evolution of level set in mass segmentation using mammograms
Kanchan Lata Kashyap et al.
COMPUTERS IN BIOLOGY AND MEDICINE (2017)
Breast Cancer Screening, Mammography, and Other Modalities
James V. Fiorica
CLINICAL OBSTETRICS AND GYNECOLOGY (2016)
A new method of detecting micro-calcification clusters in mammograms using contourlet transform and non-linking simplified PCNN
Ya'nan Guo et al.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2016)
Multiple-Instance Learning for Anomaly Detection in Digital Mammography
Gwenole Quellec et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING (2016)
Predicting the Future - Big Data, Machine Learning, and Clinical Medicine
Ziad Obermeyer et al.
NEW ENGLAND JOURNAL OF MEDICINE (2016)
Breast-Cancer Tumor Size, Overdiagnosis, and Mammography Screening Effectiveness
H. Gilbert Welch et al.
NEW ENGLAND JOURNAL OF MEDICINE (2016)
Deep learning based classification of breast tumors with shear-wave elastography
Qi Zhang et al.
ULTRASONICS (2016)
Effectiveness of Digital Breast Tomosynthesis Compared With Digital Mammography Outcomes Analysis From 3 Years of Breast Cancer Screening
Elizabeth S. McDonald et al.
JAMA ONCOLOGY (2016)
Computer-aided detection (CAD) system for breast MRI in assessment of local tumor extent, nodal status, and multifocality of invasive breast cancers: preliminary study
Sung Eun Song et al.
CANCER IMAGING (2015)
Big Data, Big Knowledge: Big Data for Personalized Healthcare
Marco Viceconti et al.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (2015)
Computer-aided Detection of Masses at Mammography: Interactive Decision Support versus Prompts
Rianne Hupse et al.
RADIOLOGY (2013)
Computer-aided diagnosis of breast microcalcifications based on dual-tree complex wavelet transform
Wushuai Jian et al.
BIOMEDICAL ENGINEERING ONLINE (2012)
Breast Mass Segmentation in Mammography Using Plane Fitting and Dynamic Programming
Enmin Song et al.
ACADEMIC RADIOLOGY (2009)