Incremental learning for an evolving stream of medical ultrasound images via counterfactual thinking

Evaluation of Pulmonary Edema Using Ultrasound Imaging in COVID-19 Patients Using a Non-Local Channel Attention ResNet

(2022) Qinghua Huang et al.   ULTRASOUND IN MEDICINE AND BIOLOGY

Classification for thyroid nodule using ViT with contrastive learning in ultrasound images

(2022) Jiawei Sun et al.   COMPUTERS IN BIOLOGY AND MEDICINE

Tumor Classification in Automated Breast Ultrasound (ABUS) based on a modified extracting feature network

(2021) Zhemin Zhuang et al.   COMPUTERIZED MEDICAL IMAGING AND GRAPHICS

Knowledge Distillation: A Survey

(2021) Jianping Gou et al.   INTERNATIONAL JOURNAL OF COMPUTER VISION

Prospective assessment of breast cancer risk from multimodal multiview ultrasound images via clinically applicable deep learning

(2021) Xuejun Qian et al.   Nature Biomedical Engineering

Clinical value of radiomics and machine learning in breast ultrasound: a multicenter study for differential diagnosis of benign and malignant lesions

(2021) Valeria Romeo et al.   EUROPEAN RADIOLOGY

Unseen Artificial Intelligence—Deep Learning Paradigm for Segmentation of Low Atherosclerotic Plaque in Carotid Ultrasound: A Multicenter Cardiovascular Study

(2021) Pankaj K. Jain et al.   Diagnostics

Knowledge Distillation and Student-Teacher Learning for Visual Intelligence: A Review and New Outlooks

(2021) Lin Wang et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Improving B-mode ultrasound diagnostic performance for focal liver lesions using deep learning: A multicentre study

(2020) Qi Yang et al.   EBioMedicine

Classification of malignant tumors in breast ultrasound using a pretrained deep residual network model and support vector machine

(2020) Wei-Chung Shia et al.   COMPUTERIZED MEDICAL IMAGING AND GRAPHICS

Deep learning with convolutional neural network in the assessment of breast cancer molecular subtypes based on US images: a multicenter retrospective study

(2020) Meng Jiang et al.   EUROPEAN RADIOLOGY

Embracing Change: Continual Learning in Deep Neural Networks

(2020) Raia Hadsell et al.   TRENDS IN COGNITIVE SCIENCES

A comprehensive study of class incremental learning algorithms for visual tasks

(2020) Eden Belouadah et al.   NEURAL NETWORKS

Wider or Deeper: Revisiting the ResNet Model for Visual Recognition

(2019) Zifeng Wu et al.   PATTERN RECOGNITION

Deep Learning in Medical Ultrasound Analysis: A Review

(2019) Shengfeng Liu et al.   Engineering

Continual lifelong learning with neural networks: A review

(2019) German I. Parisi et al.   NEURAL NETWORKS

Deep learning Radiomics of shear wave elastography significantly improved diagnostic performance for assessing liver fibrosis in chronic hepatitis B: a prospective multicentre study

(2018) Kun Wang et al.   GUT

Machine learning for medical ultrasound: status, methods, and future opportunities

(2018) Laura J. Brattain et al.   Abdominal Radiology

Privacy in the age of medical big data

(2018) W. Nicholson Price et al.   NATURE MEDICINE

Overcoming catastrophic forgetting in neural networks

(2017) James Kirkpatrick et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

A Bio-Inspired Incremental Learning Architecture for Applied Perceptual Problems

(2016) Alexander Gepperth et al.   Cognitive Computation

Deep learning

(2015) Yann LeCun et al.   NATURE

Rising Use Of Diagnostic Medical Imaging In A Large Integrated Health System

(2008) Rebecca Smith-Bindman et al.   HEALTH AFFAIRS