LARNet-STC: Spatio-temporal orthogonal region selection network for laryngeal closure detection in endoscopy videos
The vocal folds (VFs) are a pair of muscles in the larynx that play a critical role in breathing,
swallowing, and speaking. VF function can be adversely affected by various medical …
swallowing, and speaking. VF function can be adversely affected by various medical …
Real-Time Motion Analysis with 4D Deep Learning for Ultrasound-Guided Radiotherapy
Motion compensation in radiation therapy is a challenging scenario that requires estimating
and forecasting motion of tissue structures to deliver the target dose. Ultrasound offers direct …
and forecasting motion of tissue structures to deliver the target dose. Ultrasound offers direct …
High-resolution in vivo 4D-OCT fish-eye imaging using 3D-UNet with multi-level residue decoder
Optical coherence tomography (OCT) allows high-resolution volumetric imaging of
biological tissues in vivo. However, 3D-image acquisition often suffers from motion artifacts …
biological tissues in vivo. However, 3D-image acquisition often suffers from motion artifacts …
4D spatio-temporal convolutional networks for object position estimation in OCT volumes
Tracking and localizing objects is a central problem in computer-assisted surgery. Optical
coherence tomography (OCT) can be employed as an optical tracking system, due to its high …
coherence tomography (OCT) can be employed as an optical tracking system, due to its high …
Motion correction in retinal optical coherence tomography imaging using deep learning registration
K Ntatsis, LS Brea, DA De Jesus… - Medical Imaging …, 2022 - spiedigitallibrary.org
Optical coherence tomography (OCT) retinal volumes are prone to motion artifacts due to the
movement of the eye during acquisition. Current retrospective motion correction algorithms …
movement of the eye during acquisition. Current retrospective motion correction algorithms …
Deep learning with multi-dimensional medical image data
NT Gessert - 2020 - tore.tuhh.de
In this work, we explore deep learning model design and application in the context of multi-
dimensional data in medical image analysis. A lot of medical image analysis problems come …
dimensional data in medical image analysis. A lot of medical image analysis problems come …
[PDF][PDF] Analysis of ultrasound and optical coherence tomography for markerless volumetric image guidance in robotic radiosurgery
M Schlüter - 2021 - tore.tuhh.de
This thesis analyzes different aspects of image guidance in robotic radiosurgery considering
the modalities ultrasound imaging and optical coherence tomography (OCT). Robotic …
the modalities ultrasound imaging and optical coherence tomography (OCT). Robotic …
Spatio-temporal deep learning for medical image sequences
M Bengs - 2023 - tore.tuhh.de
In this work, we study and present spatio-temporal deep learning methods for analyzing
medical image sequences. We focus on two application scenarios, motion analysis and …
medical image sequences. We focus on two application scenarios, motion analysis and …
Multi-Modal and Multi-Dimensional Biomedical Image Data Analysis Using Deep Learning
Y Wang - 2023 - search.proquest.com
There is a growing need for the development of computational methods and tools for
automated, objective, and quantitative analysis of biomedical signal and image data to …
automated, objective, and quantitative analysis of biomedical signal and image data to …
[引用][C] Spatio-Temporal Deep Learning for Estimating and Forecasting Tissue Motion in 4D Ultrasound
M Bengs, J Sprenger, S Gerlach, M Neidhardt… - 2021