Visual search in three-dimensional non-medical images: visual-motor performance of radiologists

2019 ◽  
Author(s):  
Tatjana Pladere ◽  
Mara Velina ◽  
Viktorija Andriksone ◽  
Reinis Pitura ◽  
Karola Panke ◽  
...  
Keyword(s):  
Visual Search ◽  
Motor Performance ◽  
Medical Images ◽  
Three Dimensional ◽  
Visual Motor

Automatic recognition of anatomical regions in three-dimensional medical images

2016 ◽  
Vol 76 ◽  
pp. 120-133
Author(s):  
Márton Tóth ◽  
László Ruskó ◽  
Balázs Csébfalvi
Keyword(s):  
Medical Images ◽  
Three Dimensional ◽  
Automatic Recognition

scholarly journals 3D-StyleGAN: A Style-Based Generative Adversarial Network for Generative Modeling of Three-Dimensional Medical Images

2021 ◽  
pp. 24-34
Author(s):  
Sungmin Hong ◽  
Razvan Marinescu ◽  
Adrian V. Dalca ◽  
Anna K. Bonkhoff ◽  
Martin Bretzner ◽  
...  
Keyword(s):  
Medical Images ◽  
Three Dimensional ◽  
Generative Adversarial Network ◽  
Adversarial Network ◽  
Generative Modeling

Evaluation of Spherical Parameterization Methods for Three-Dimensional Reconstruction of Medical Images

2013 ◽  
Vol 365-366 ◽  
pp. 1342-1349
Author(s):  
Xing Hui Wu ◽  
Zhi Xiu Hao
Keyword(s):  
Medical Images ◽  
Three Dimensional ◽  
3D Models ◽  
Mapping Method ◽  
Geometric Error ◽  
Patient Specific ◽  
Shape Modelling ◽  
Dimensional Reconstruction ◽  
Statistical Shape ◽  
Spherical Parameterization

The spherical parameterization is important for the correspondence problem that is a major part of statistical shape modelling for the reconstruction of patient-specific 3D models from medical images. In this paper, we present comparative studies of five common spherical mapping methods applied to the femur and tibia models: the Issenburg et al. method, the Alexa method, the Saba et al. method, the Praun et al. method and the Shen et al. method. These methods are evaluated using three sets of measures: distortion property, geometric error and distance to standard landmarks. Results show that the Praun et al. method performs better than other methods while the Shen et al. method can be regarded as the most reliable one for providing an acceptable correspondence result. We suggest that the area preserving property can be used as a sufficient condition while the angle preserving property is not important when choosing a spherical mapping method for correspondence application.

scholarly journals Computational assessment of visual search strategies in volumetric medical images

2016 ◽  
Vol 3 (1) ◽  
pp. 015501 ◽  
Author(s):  
Gezheng Wen ◽  
Avigael Aizenman ◽  
Trafton Drew ◽  
Jeremy M. Wolfe ◽  
Tamara Miner Haygood ◽  
...  
Keyword(s):  
Visual Search ◽  
Medical Images ◽  
Search Strategies ◽  
Volumetric Medical Images

Open Source Applications for Image Visualization and Processing in Neuroimaging Training

2015 ◽  
pp. 1319-1332
Author(s):  
Juan A. Juanes ◽  
Pablo Ruisoto ◽  
Alberto Prats-Galino ◽  
Andrés Framiñán
Keyword(s):  
Magnetic Resonance ◽  
Medical Imaging ◽  
Open Source ◽  
Medical Images ◽  
Three Dimensional ◽  
Mr Images ◽  
Image Visualization ◽  
3D Slicer ◽  
Volumetric Reconstruction ◽  
Key Features

The aim of this paper is to demonstrate the major role and potential of three of the most powerful open source computerized tools for the advanced processing of medical images, in the study of neuroanatomy. DICOM images were acquired with radiodiagnostic equipment using 1.5 Tesla Magnetic Resonance (MR) images. Images were further processed using the following applications: first, OsiriXTM version 4.0 32 bits for OS; Second, 3D Slicer version 4.3; and finally, MRIcron, version 6. Advanced neuroimaging processing requires two key features: segmentation and three-dimensional or volumetric reconstruction. Examples of identification and reconstruction of some of the most complex neuroimaging elements such vascular ones and tractographies are included in this paper. The three selected applications represent some of the most versatile technologies within the field of medical imaging.

Medical images segmentation based on improved three-dimensional pulse coupled neural network

2017 ◽  
Vol 13 (1) ◽  
pp. 72 ◽  
Author(s):  
Maxin Wang ◽  
Xinzheng Xu ◽  
Guanying Wang ◽  
Shifei Ding ◽  
Tongfeng Sun
Keyword(s):  
Neural Network ◽  
Medical Images ◽  
Three Dimensional ◽  
Pulse Coupled Neural Network

scholarly journals Spatial Auditory Cueing for a Dynamic Three-Dimensional Virtual Reality Visual Search Task

2019 ◽  
Vol 63 (1) ◽  
pp. 1766-1770
Author(s):  
Rachel J. Cunio ◽  
David Dommett ◽  
Joseph Houpt
Keyword(s):  
Virtual Reality ◽  
Visual Search ◽  
Visual System ◽  
Spatial Information ◽  
Visual Awareness ◽  
Three Dimensional ◽  
Search Time ◽  
Primary Concern ◽  
Search Performance ◽  
Auditory Cues

Maintaining spatial awareness is a primary concern for operators, but relying only on visual displays can cause visual system overload and lead to performance decrements. Our study examined the benefits of providing spatialized auditory cues for maintaining visual awareness as a method of combating visual system overload. We examined visual search performance of seven participants in an immersive, dynamic (moving), three-dimensional, virtual reality environment both with no cues, non-masked, spatialized auditory cues, and masked, spatialized auditory cues. Results indicated a significant reduction in visual search time from the no-cue condition when either auditory cue type was presented, with the masked auditory condition slower. The results of this study can inform attempts to improve visual search performance in operational environments, such as determining appropriate display types for providing spatial information.

Sign in / Sign up

Export Citation Format

Share Document