AIMC Topic: Respiration

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Few-shot learning for deformable image registration in 4DCT images.

The British journal of radiology
OBJECTIVES: To develop a rapid and accurate 4D deformable image registration (DIR) approach for online adaptive radiotherapy.

Development of a tracking error prediction system for the CyberKnife Synchrony Respiratory Tracking System with use of support vector regression.

Medical & biological engineering & computing
PURPOSE: The accuracy of the CyberKnife Synchrony Respiratory Tracking System is dependent on the breathing pattern of a patient. Therefore, the tracking error in each patient must be determined. Support vector regression (SVR) can be used to easily ...

Scalable quorum-based deep neural networks with adversarial learning for automated lung lobe segmentation in fast helical free-breathing CTs.

International journal of computer assisted radiology and surgery
PURPOSE: Fast helical free-breathing CT (FHFBCT) scans are widely used for 5DCT and 5D Cone Beam imaging protocols. For quantitative analysis of lung physiology and function, it is important to segment the lung lobes in these scans. Since the 5DCT pr...

Free-breathing Accelerated Cardiac MRI Using Deep Learning: Validation in Children and Young Adults.

Radiology
Background Obtaining ventricular volumetry and mass is key to most cardiac MRI but challenged by long multibreath-hold acquisitions. Purpose To assess the image quality and performance of a highly accelerated, free-breathing, two-dimensional cine car...

Predictive online 3D target tracking with population-based generative networks for image-guided radiotherapy.

International journal of computer assisted radiology and surgery
PURPOSE: Respiratory motion of thoracic organs poses a severe challenge for the administration of image-guided radiotherapy treatments. Providing online and up-to-date volumetric information during free breathing can improve target tracking, ultimate...

Non-Contact Respiration Measurement Method Based on RGB Camera Using 1D Convolutional Neural Networks.

Sensors (Basel, Switzerland)
Conventional respiration measurement requires a separate device and/or can cause discomfort, so it is difficult to perform routinely, even for patients with respiratory diseases. The development of contactless respiration measurement technology would...

Deep learning-based segmentation of the lung in MR-images acquired by a stack-of-spirals trajectory at ultra-short echo-times.

BMC medical imaging
BACKGROUND: Functional lung MRI techniques are usually associated with time-consuming post-processing, where manual lung segmentation represents the most cumbersome part. The aim of this study was to investigate whether deep learning-based segmentati...

Deep learning architectures for estimating breathing signal and respiratory parameters from speech recordings.

Neural networks : the official journal of the International Neural Network Society
Respiration is an essential and primary mechanism for speech production. We first inhale and then produce speech while exhaling. When we run out of breath, we stop speaking and inhale. Though this process is involuntary, speech production involves a ...

Highly accelerated free-breathing real-time phase contrast cardiovascular MRI via complex-difference deep learning.

Magnetic resonance in medicine
PURPOSE: To develop and evaluate a real-time phase contrast (PC) MRI protocol via complex-difference deep learning (DL) framework.

GroupRegNet: a groupwise one-shot deep learning-based 4D image registration method.

Physics in medicine and biology
Accurate deformable four-dimensional (4D) (three-dimensional in space and time) medical images registration is essential in a variety of medical applications. Deep learning-based methods have recently gained popularity in this area for the significan...