Results 51 to 60 of about 1,160,554 (311)
Anatomically Constrained Implicit Face Models [PDF]
arXiv, 2023 Coordinate based implicit neural representations have gained rapid popularity in recent years as they have been successfully used in image, geometry and scene modeling tasks. In this work, we present a novel use case for such implicit representations in the context of learning anatomically constrained face models.
arxiv
Function-based Intersubject Alignment of Human Cortical Anatomy [PDF]
, 2009 Making conclusions about the functional neuroanatomical organization of the human brain requires methods for relating the functional anatomy of an individual's brain to population variability.
Benjamin D. Singer +6 more
core +2 more sources
Statistical process control to monitor use of a web‐based autoplanning tool
Journal of Applied Clinical Medical Physics, Volume 23, Issue 12, December 2022., 2022 Abstract Purpose To investigate the use of statistical process control (SPC) for quality assurance of an integrated web‐based autoplanning tool, Radiation Planning Assistant (RPA). Methods Automatically generated plans were downloaded and imported into two treatment planning systems (TPSs), RayStation and Eclipse, in which they were recalculated using ...
Hunter Mehrens +5 more
wiley +1 more source
Hybrid graph convolutional neural networks for landmark-based anatomical segmentation [PDF]
, 2021 In this work we address the problem of landmark-based segmentation for anatomical structures. We propose HybridGNet, an encoder-decoder neural architecture which combines standard convolutions for image feature encoding, with graph convolutional neural networks to decode plausible representations of anatomical structures.
arxiv +1 more source
The accuracy of three-dimensional prediction of soft tissue changes following the surgical correction of facial asymmetry: an innovative concept [PDF]
, 2017 The accuracy of three-dimensional (3D) predictions of soft tissue changes in the surgical correction of facial asymmetry was evaluated in this study. Preoperative (T1) and 6–12-month postoperative (T2) cone beam computed tomography scans of 13 patients ...
Almukhtar, A. +3 more
core +1 more source
Anatomically motivated modeling of cortical laminae
NeuroImage, 2014 Improvements in the spatial resolution of structural and functional MRI are beginning to enable analysis of intracortical structures such as heavily myelinated layers in 3D, a prerequisite for in-vivo parcellation of individual human brains. This parcellation can only be performed precisely if the profiles used in cortical analysis are anatomically ...
M.D. Waehnert +7 more
openaire +3 more sources
Impact of flexible noise control (FNC) image processing parameters on portable chest radiography
Journal of Applied Clinical Medical Physics, Volume 23, Issue 12, December 2022., 2022 Abstract There is a lack of understanding in the performance of flexible noise control (FNC) processing, which is used in digital radiography on a scanner vendor and has four parameters each involving multiple options. The aim of this study was to investigate the impact of FNC on portable chest imaging. An anthropomorphic chest phantom was imaged using
Krystal M. Kirby +6 more
wiley +1 more source
Emerging technologies to create inducible and genetically defined porcine cancer models
Frontiers in Genetics, 2016 There is an emerging need for new animal models that address unmet translational cancer research requirements. Transgenic porcine models provide an exceptional opportunity due to their genetic, anatomic and physiological similarities with humans.
Lawrence B Schook +6 more
doaj +1 more source
3D printing and urology: Review of the clinical applications
Український Журнал Нефрології та Діалізу, 2020 Three-dimensional (3D) printing is a process that translates a 3D virtual model into its physical 3D replica. In medicine, Neurosurgery, Orthopedics and Maxillo-facial surgery were the first specialties to successfully incorporate this technology in ...
K. Wendo, R. Olszewski
doaj +1 more source
AnaXNet: Anatomy Aware Multi-label Finding Classification in Chest X-ray [PDF]
arXiv, 2021 Radiologists usually observe anatomical regions of chest X-ray images as well as the overall image before making a decision. However, most existing deep learning models only look at the entire X-ray image for classification, failing to utilize important anatomical information.
arxiv