Deep reinforcement learning in medical imaging: A literature review
Deep reinforcement learning (DRL) augments the reinforcement learning framework, which
learns a sequence of actions that maximizes the expected reward, with the representative …
learns a sequence of actions that maximizes the expected reward, with the representative …
A review on deep-learning algorithms for fetal ultrasound-image analysis
Deep-learning (DL) algorithms are becoming the standard for processing ultrasound (US)
fetal images. A number of survey papers in the field is today available, but most of them are …
fetal images. A number of survey papers in the field is today available, but most of them are …
Recent advances in artificial intelligence-assisted ultrasound scanning
R Tenajas, D Miraut, CI Illana, R Alonso-Gonzalez… - Applied Sciences, 2023 - mdpi.com
Ultrasound (US) is a flexible imaging modality used globally as a first-line medical exam
procedure in many different clinical cases. It benefits from the continued evolution of …
procedure in many different clinical cases. It benefits from the continued evolution of …
Autonomous navigation of an ultrasound probe towards standard scan planes with deep reinforcement learning
Autonomous ultrasound (US) acquisition is an important yet challenging task, as it involves
interpretation of the highly complex and variable images and their spatial relationships. In …
interpretation of the highly complex and variable images and their spatial relationships. In …
Extracting keyframes of breast ultrasound video using deep reinforcement learning
Ultrasound (US) plays a vital role in breast cancer screening, especially for women with
dense breasts. Common practice requires a sonographer to recognize key diagnostic …
dense breasts. Common practice requires a sonographer to recognize key diagnostic …
Image-guided navigation of a robotic ultrasound probe for autonomous spinal sonography using a shadow-aware dual-agent framework
Ultrasound (US) imaging is commonly used to assist in the diagnosis and interventions of
spine diseases, while the standardized US acquisitions performed by manually operating …
spine diseases, while the standardized US acquisitions performed by manually operating …
Learning to map 2D ultrasound images into 3D space with minimal human annotation
PH Yeung, M Aliasi, AT Papageorghiou, M Haak… - Medical Image …, 2021 - Elsevier
In fetal neurosonography, aligning two-dimensional (2D) ultrasound scans to their
corresponding plane in the three-dimensional (3D) space remains a challenging task. In this …
corresponding plane in the three-dimensional (3D) space remains a challenging task. In this …
Searching collaborative agents for multi-plane localization in 3D ultrasound
Abstract 3D ultrasound (US) has become prevalent due to its rich spatial and diagnostic
information not contained in 2D US. Moreover, 3D US can contain multiple standard planes …
information not contained in 2D US. Moreover, 3D US can contain multiple standard planes …
Agent with warm start and adaptive dynamic termination for plane localization in 3D ultrasound
Accurate standard plane (SP) localization is the fundamental step for prenatal ultrasound
(US) diagnosis. Typically, dozens of US SPs are collected to determine the clinical …
(US) diagnosis. Typically, dozens of US SPs are collected to determine the clinical …
Deep reinforcement learning framework for thoracic diseases classification via prior knowledge guidance
The chest X-ray is commonly employed in the diagnosis of thoracic diseases. Over the
years, numerous approaches have been proposed to address the issue of automatic …
years, numerous approaches have been proposed to address the issue of automatic …