Related references
Note: Only part of the references are listed.Segmentation of Fetal Left Ventricle in Echocardiographic Sequences Based on Dynamic Convolutional Neural Networks
Li Yu et al.
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING (2017)
Fully Convolutional Networks for Semantic Segmentation
Evan Shelhamer et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2017)
A survey on deep learning in medical image analysis
Geert Litjens et al.
MEDICAL IMAGE ANALYSIS (2017)
Reproducibility of quantitative high-throughput BI-RADS features extracted from ultrasound images of breast cancer
Yuzhou Hu et al.
MEDICAL PHYSICS (2017)
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
Hoo-Chang Shin et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING (2016)
NEW FULLY AUTOMATED METHOD FOR SEGMENTATION OF BREAST LESIONS ON ULTRASOUND BASED ON TEXTURE ANALYSIS
Wilfrido Gomez-Flores et al.
ULTRASOUND IN MEDICINE AND BIOLOGY (2016)
COMPUTER-AIDED DIAGNOSIS FOR BREAST ULTRASOUND USING COMPUTERIZED BI-RADS FEATURES AND MACHINE LEARNING METHODS
Juan Shan et al.
ULTRASOUND IN MEDICINE AND BIOLOGY (2016)
Computer-aided detection system for masses in automated whole breast ultrasonography: development and evaluation of the effectiveness
Jeoung Hyun Kim et al.
ULTRASONOGRAPHY (2014)
Computer-aided detection/diagnosis of breast cancer in mammography and ultrasound: a review
Afsaneh Jalalian et al.
CLINICAL IMAGING (2013)
Combining support vector machine with genetic algorithm to classify ultrasound breast tumor images
Wen-Jie Wu et al.
COMPUTERIZED MEDICAL IMAGING AND GRAPHICS (2012)
Detection of Breast Cancer With Addition of Annual Screening Ultrasound or a Single Screening MRI to Mammography in Women With Elevated Breast Cancer Risk
Wendie A. Berg et al.
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION (2012)
COMPLETELY AUTOMATED SEGMENTATION APPROACH FOR BREAST ULTRASOUND IMAGES USING MULTIPLE-DOMAIN FEATURES
Juan Shan et al.
ULTRASOUND IN MEDICINE AND BIOLOGY (2012)
Intraobserver interpretation of breast ultrasonography following the BI-RADS classification
M. J. G. Calas et al.
EUROPEAN JOURNAL OF RADIOLOGY (2010)
Processed images in human perception: A case study in ultrasound breast imaging
Moi Hoon Yap et al.
EUROPEAN JOURNAL OF RADIOLOGY (2010)
Fully automatic and segmentation-robust classification of breast tumors based on local texture analysis of ultrasound images
Bo Liu et al.
PATTERN RECOGNITION (2010)
Automated breast cancer detection and classification using ultrasound images: A survey
H. D. Cheng et al.
PATTERN RECOGNITION (2010)
AUTOMATED SEGMENTATION OF ULTRASONIC BREAST LESIONS USING STATISTICAL TEXTURE CLASSIFICATION AND ACTIVE CONTOUR BASED ON PROBABILITY DISTANCE
Bo Liu et al.
ULTRASOUND IN MEDICINE AND BIOLOGY (2009)
Computer-aided Diagnosis Using Neural Networks and Support Vector Machines for Breast Ultrasonography
Yu-Len Huang
JOURNAL OF MEDICAL ULTRASOUND (2009)
The Bayesian Lasso
Trevor Park et al.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION (2008)
Ultrasound image segmentation: A survey
J. Alison Noble et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING (2006)
Diagnostic accuracy of mammography, clinical examination, US, and MR imaging in preoperative assessment of breast cancer
WA Berg et al.
RADIOLOGY (2004)
Improvement in breast tumor discrimination by support vector machines and speckle-emphasis texture analysis
RF Chang et al.
ULTRASOUND IN MEDICINE AND BIOLOGY (2003)
Combining low-, high-level and empirical domain knowledge for automated segmentation of ultrasonic breast lesions
A Madabhushi et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING (2003)
Segmentation of ultrasound B-mode images with intensity inhomogeneity correction
GF Xiao et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING (2002)
Share Paper
