scholarly journals Computational and mathematical methods in brain atlasing

2017 ◽  
Vol 30 (6) ◽  
pp. 520-534 ◽  
Author(s):  
Wieslaw L Nowinski
Keyword(s):  
Virtual Reality ◽  
Image Segmentation ◽  
Computational Methods ◽  
Physical Modelling ◽  
Clinical Applications ◽  
Brain Atlas ◽  
Mathematical Methods ◽  
Wide Range ◽  
Scan Registration ◽  
Brain Atlases

Brain atlases have a wide range of use from education to research to clinical applications. Mathematical methods as well as computational methods and tools play a major role in the process of brain atlas building and developing atlas-based applications. Computational methods and tools cover three areas: dedicated editors for brain model creation, brain navigators supporting multiple platforms, and atlas-assisted specific applications. Mathematical methods in atlas building and developing atlas-aided applications deal with problems in image segmentation, geometric body modelling, physical modelling, atlas-to-scan registration, visualisation, interaction and virtual reality. Here I overview computational and mathematical methods in atlas building and developing atlas-assisted applications, and share my contribution to and experience in this field.

scholarly journals Towards an Architecture of a Multi-purpose, User-Extendable Reference Human Brain Atlas

2021 ◽  
Author(s):  
Wieslaw L. Nowinski
Keyword(s):  
Human Brain ◽  
Clinical Applications ◽  
Brain Atlas ◽  
Communication Research ◽  
Functional Roles ◽  
Knowledge Database ◽  
Knowledge Presentation ◽  
Database Research ◽  
Wide Range ◽  
Definition Of

AbstractHuman brain atlas development is predominantly research-oriented and the use of atlases in clinical practice is limited. Here I introduce a new definition of a reference human brain atlas that serves education, research and clinical applications, and is extendable by its user. Subsequently, an architecture of a multi-purpose, user-extendable reference human brain atlas is proposed and its implementation discussed. The human brain atlas is defined as a vehicle to gather, present, use, share, and discover knowledge about the human brain with highly organized content, tools enabling a wide range of its applications, massive and heterogeneous knowledge database, and means for content and knowledge growing by its users. The proposed architecture determines major components of the atlas, their mutual relationships, and functional roles. It contains four functional units, core cerebral models, knowledge database, research and clinical data input and conversion, and toolkit (supporting processing, content extension, atlas individualization, navigation, exploration, and display), all united by a user interface. Each unit is described in terms of its function, component modules and sub-modules, data handling, and implementation aspects. This novel architecture supports brain knowledge gathering, presentation, use, sharing, and discovery and is broadly applicable and useful in student- and educator-oriented neuroeducation for knowledge presentation and communication, research for knowledge acquisition, aggregation and discovery, and clinical applications in decision making support for prevention, diagnosis, treatment, monitoring, and prediction. It establishes a backbone for designing and developing new, multi-purpose and user-extendable brain atlas platforms, serving as a potential standard across labs, hospitals, and medical schools.

scholarly journals Human Brain Atlases in Stroke Management

2020 ◽  
Vol 18 (4) ◽  
pp. 549-567 ◽  
Author(s):  
Wieslaw L. Nowinski
Keyword(s):  
Pulse Sequences ◽  
Brain Atlas ◽  
Stroke Management ◽  
Permanent Disability ◽  
Wide Range ◽  
Mri Scans ◽  
One Year ◽  
Rapid Processing ◽  
Brain Atlases

Abstract Stroke is a leading cause of death and a major cause of permanent disability. Its management is demanding because of variety of protocols, imaging modalities, pulse sequences, hemodynamic maps, criteria for treatment, and time constraints to promptly evaluate and treat. To cope with some of these issues, we propose novel, patented solutions in stroke management by employing multiple brain atlases for diagnosis, treatment, and prediction. Numerous and diverse CT and MRI scans are used: ARIC cohort, ischemic and hemorrhagic stroke CT cases, MRI cases with multiple pulse sequences, and 128 stroke CT patients, each with 170 variables and one year follow-up. The method employs brain atlases of anatomy, blood supply territories, and probabilistic stroke atlas. It rapidly maps an atlas to scan and provides atlas-assisted scan processing. Atlas-to-scan mapping is application-dependent and handles three types of regions of interest (ROIs): atlas-defined ROIs, atlas-quantified ROIs, and ROIs creating an atlas. An ROI is defined by atlas-guided anatomy or scan-derived pathology. The atlas defines ROI or quantifies it. A brain atlas potential has been illustrated in four atlas-assisted applications for stroke occurrence prediction and screening, rapid and automatic stroke diagnosis in emergency room, quantitative decision support in thrombolysis in ischemic stroke, and stroke outcome prediction and treatment assessment. The use of brain atlases in stroke has many potential advantages, including rapid processing, automated and robust handling, wide range of applications, and quantitative assessment. Further work is needed to enhance the developed prototypes, clinically validate proposed solutions, and introduce them to clinical practice.

Recent Advances in Computational Methods for Identifying Anticancer Peptides

2019 ◽  
Vol 20 (5) ◽  
pp. 481-487 ◽  
Author(s):  
Pengmian Feng ◽  
Zhenyi Wang
Keyword(s):  
Computational Methods ◽  
Clinical Applications ◽  
Future Perspectives ◽  
Small Peptides ◽  
Accurate Identification ◽  
Normal Cells ◽  
Anticancer Peptide ◽  
Anticancer Peptides ◽  
Computational Identification ◽  
Reliable Methods

Anticancer peptide (ACP) is a kind of small peptides that can kill cancer cells without damaging normal cells. In recent years, ACP has been pre-clinically used for cancer treatment. Therefore, accurate identification of ACPs will promote their clinical applications. In contrast to labor-intensive experimental techniques, a series of computational methods have been proposed for identifying ACPs. In this review, we briefly summarized the current progress in computational identification of ACPs. The challenges and future perspectives in developing reliable methods for identification of ACPs were also discussed. We anticipate that this review could provide novel insights into future researches on anticancer peptides.

scholarly journals A Self-Spatial Adaptive Weighting Based U-Net for Image Segmentation

Electronics ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 348
Author(s):  
Choongsang Cho ◽  
Young Han Lee ◽  
Jongyoul Park ◽  
Sangkeun Lee
Keyword(s):  
Image Segmentation ◽  
Medical Image ◽  
Medical Image Segmentation ◽  
Feature Maps ◽  
Data Set ◽  
Feature Map ◽  
Adaptive Weighting ◽  
Spatially Adaptive ◽  
Wide Range ◽  
Decoder Architecture

Semantic image segmentation has a wide range of applications. When it comes to medical image segmentation, its accuracy is even more important than those of other areas because the performance gives useful information directly applicable to disease diagnosis, surgical planning, and history monitoring. The state-of-the-art models in medical image segmentation are variants of encoder-decoder architecture, which is called U-Net. To effectively reflect the spatial features in feature maps in encoder-decoder architecture, we propose a spatially adaptive weighting scheme for medical image segmentation. Specifically, the spatial feature is estimated from the feature maps, and the learned weighting parameters are obtained from the computed map, since segmentation results are predicted from the feature map through a convolutional layer. Especially in the proposed networks, the convolutional block for extracting the feature map is replaced with the widely used convolutional frameworks: VGG, ResNet, and Bottleneck Resent structures. In addition, a bilinear up-sampling method replaces the up-convolutional layer to increase the resolution of the feature map. For the performance evaluation of the proposed architecture, we used three data sets covering different medical imaging modalities. Experimental results show that the network with the proposed self-spatial adaptive weighting block based on the ResNet framework gave the highest IoU and DICE scores in the three tasks compared to other methods. In particular, the segmentation network combining the proposed self-spatially adaptive block and ResNet framework recorded the highest 3.01% and 2.89% improvements in IoU and DICE scores, respectively, in the Nerve data set. Therefore, we believe that the proposed scheme can be a useful tool for image segmentation tasks based on the encoder-decoder architecture.

scholarly journals Controlling Teleportation-Based Locomotion in Virtual Reality with Hand Gestures: A Comparative Evaluation of Two-Handed and One-Handed Techniques

Electronics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 715
Author(s):  
Alexander Schäfer ◽  
Gerd Reis ◽  
Didier Stricker
Keyword(s):  
Virtual Reality ◽  
Virtual Worlds ◽  
User Preferences ◽  
Interaction Techniques ◽  
Hand Gestures ◽  
Wide Range ◽  
Effectiveness And Efficiency ◽  
High Degree ◽  
Additional Hardware ◽  
Comprehensive Study

Virtual Reality (VR) technology offers users the possibility to immerse and freely navigate through virtual worlds. An important component for achieving a high degree of immersion in VR is locomotion. Often discussed in the literature, a natural and effective way of controlling locomotion is still a general problem which needs to be solved. Recently, VR headset manufacturers have been integrating more sensors, allowing hand or eye tracking without any additional required equipment. This enables a wide range of application scenarios with natural freehand interaction techniques where no additional hardware is required. This paper focuses on techniques to control teleportation-based locomotion with hand gestures, where users are able to move around in VR using their hands only. With the help of a comprehensive study involving 21 participants, four different techniques are evaluated. The effectiveness and efficiency as well as user preferences of the presented techniques are determined. Two two-handed and two one-handed techniques are evaluated, revealing that it is possible to move comfortable and effectively through virtual worlds with a single hand only.

scholarly journals The effect of water immersion on vection in virtual reality

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Géraldine Fauville ◽  
Anna C. M. Queiroz ◽  
Erika S. Woolsey ◽  
Jonathan W. Kelly ◽  
Jeremy N. Bailenson
Keyword(s):  
Virtual Reality ◽  
Motion Sickness ◽  
Water Immersion ◽  
Sensory Information ◽  
Future Research ◽  
Visually Induced Motion Sickness ◽  
Wide Range ◽  
Induced Motion ◽  
Ground Condition ◽  
The Impact

AbstractResearch about vection (illusory self-motion) has investigated a wide range of sensory cues and employed various methods and equipment, including use of virtual reality (VR). However, there is currently no research in the field of vection on the impact of floating in water while experiencing VR. Aquatic immersion presents a new and interesting method to potentially enhance vection by reducing conflicting sensory information that is usually experienced when standing or sitting on a stable surface. This study compares vection, visually induced motion sickness, and presence among participants experiencing VR while standing on the ground or floating in water. Results show that vection was significantly enhanced for the participants in the Water condition, whose judgments of self-displacement were larger than those of participants in the Ground condition. No differences in visually induced motion sickness or presence were found between conditions. We discuss the implication of this new type of VR experience for the fields of VR and vection while also discussing future research questions that emerge from our findings.

scholarly journals Image Segmentation and Object-Based Image Analysis for Environmental Monitoring: Recent Areas of Interest, Researchers’ Views on the Future Priorities

2020 ◽  
Vol 12 (11) ◽  
pp. 1772
Author(s):  
Brian Alan Johnson ◽  
Lei Ma
Keyword(s):  
Remote Sensing ◽  
Image Analysis ◽  
Image Segmentation ◽  
Online Survey ◽  
Accuracy Assessment ◽  
Learning Approaches ◽  
Special Issue ◽  
Object Based Image Analysis ◽  
Object Based ◽  
Wide Range

Image segmentation and geographic object-based image analysis (GEOBIA) were proposed around the turn of the century as a means to analyze high-spatial-resolution remote sensing images. Since then, object-based approaches have been used to analyze a wide range of images for numerous applications. In this Editorial, we present some highlights of image segmentation and GEOBIA research from the last two years (2018–2019), including a Special Issue published in the journal Remote Sensing. As a final contribution of this special issue, we have shared the views of 45 other researchers (corresponding authors of published papers on GEOBIA in 2018–2019) on the current state and future priorities of this field, gathered through an online survey. Most researchers surveyed acknowledged that image segmentation/GEOBIA approaches have achieved a high level of maturity, although the need for more free user-friendly software and tools, further automation, better integration with new machine-learning approaches (including deep learning), and more suitable accuracy assessment methods was frequently pointed out.

Virtual Reality (VR) in Pediatrics: Innovative Perspectives With Special Reference To Clinical Applications and Pediatric Rehabilitation

2021 ◽  
Author(s):  
Stefan Bittmann
Keyword(s):  
Virtual Reality ◽  
Virtual Environment ◽  
Virtual Worlds ◽  
Virtual World ◽  
Mixed Reality ◽  
Clinical Applications ◽  
Virtual Space ◽  
Data Glove ◽  
Input Devices ◽  
Head Mounted Displays

Virtual reality (VR) is the term used to describe representation and perception in a computer-generated, virtual environment. The term was coined by author Damien Broderick in his 1982 novel “The Judas Mandala". The term "Mixed Reality" describes the mixing of virtual reality with pure reality. The term "hyper-reality" is also used. Immersion plays a major role here. Immersion describes the embedding of the user in the virtual world. A virtual world is considered plausible if the interaction is logical in itself. This interactivity creates the illusion that what seems to be happening is actually happening. A common problem with VR is "motion sickness." To create a sense of immersion, special output devices are needed to display virtual worlds. Here, "head-mounted displays", CAVE and shutter glasses are mainly used. Input devices are needed for interaction: 3D mouse, data glove, flystick as well as the omnidirectional treadmill, with which walking in virtual space is controlled by real walking movements, play a role here.

Treatment of Arrhythmias by Radiofrequency Ablation

2013 ◽  
Author(s):  
M. Erol Ulucakli ◽  
Evan P. Sheehan
Keyword(s):  
Radiofrequency Ablation ◽  
Cardiac Tissue ◽  
Clinical Applications ◽  
Bioheat Transfer ◽  
Temperature Profiles ◽  
Cellular Injury ◽  
Rf Ablation ◽  
Transcatheter Therapy ◽  
Wide Range ◽  
Primary Modality

Radiofrequency ablation may be described as a thermal strategy to destroy tissue by increasing its temperature and causing irreversible cellular injury. Radiofrequency ablation is a relatively new modality which has found use in a wide range of medical applications and gained acceptance. RF ablation has been used to destroy tumors in the liver, prostate, breasts, lungs, kidneys, bones, and eyes. One of the early clinical applications was its use in treating supraventricular arrhythmias by selectively destroying cardiac tissue. Radiofrequency ablation has become established as the primary modality of transcatheter therapy for the treatment of symptomatic arrhythmias. Radiofrequency catheter ablation of cardiac arrhythmias was investigated using a finite-element based solution of the bioheat transfer equation. Spatial and temporal temperature profiles in the cardiac tissue were visualized.

scholarly journals Sustained inhibition of the native language in bilingual language production: A virtual reality approach

2017 ◽  
Vol 21 (5) ◽  
pp. 1035-1061 ◽  
Author(s):  
DAVID PEETERS ◽  
TON DIJKSTRA
Keyword(s):  
Virtual Reality ◽  
Language Production ◽  
Ecological Validity ◽  
Event Related Potentials ◽  
Control Mechanisms ◽  
Language Background ◽  
Wide Range ◽  
Related Potentials ◽  
Mixing Costs ◽  
Sustained Inhibition

Bilinguals often switch languages as a function of the language background of their addressee. The control mechanisms supporting bilinguals' ability to select the contextually appropriate language are heavily debated. Here we present four experiments in which unbalanced bilinguals named pictures in their first language Dutch and their second language English in mixed and blocked contexts. Immersive virtual reality technology was used to increase the ecological validity of the cued language-switching paradigm. Behaviorally, we consistently observed symmetrical switch costs, reversed language dominance, and asymmetrical mixing costs. These findings indicate that unbalanced bilinguals apply sustained inhibition to their dominant L1 in mixed language settings. Consequent enhanced processing costs for the L1 in a mixed versus a blocked context were reflected by a sustained positive component in event-related potentials. Methodologically, the use of virtual reality opens up a wide range of possibilities to study language and communication in bilingual and other communicative settings.

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