scholarly journals Special Features on Intelligent Imaging and Analysis

2019 ◽  
Vol 9 (22) ◽  
pp. 4804 ◽  
Author(s):  
Dosik Hwang ◽  
DaeEun Kim
Keyword(s):  
Computer Vision ◽  
Medical Imaging ◽  
Biomedical Applications ◽  
Visual Inspection ◽  
Research Fields ◽  
Robot Systems

Intelligent imaging and analysis have been studied in various research fields, including medical imaging, biomedical applications, computer vision, visual inspection and robot systems [...]

scholarly journals Utilizing UAV and 3D Computer Vision for Visual Inspection of a Large Gravity Dam

2018 ◽  
Vol 4 ◽  
Author(s):  
Ali Khaloo ◽  
David Lattanzi ◽  
Adam Jachimowicz ◽  
Charles Devaney
Keyword(s):  
Computer Vision ◽  
Visual Inspection ◽  
Gravity Dam ◽  
3D Computer Vision

scholarly journals Deep learning-enabled medical computer vision

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Andre Esteva ◽  
Katherine Chou ◽  
Serena Yeung ◽  
Nikhil Naik ◽  
Ali Madani ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Computer Vision ◽  
Deep Learning ◽  
Medical Imaging ◽  
Real World ◽  
Recent Progress ◽  
Medical Applications ◽  
Modern Computer ◽  
Medical Computer

AbstractA decade of unprecedented progress in artificial intelligence (AI) has demonstrated the potential for many fields—including medicine—to benefit from the insights that AI techniques can extract from data. Here we survey recent progress in the development of modern computer vision techniques—powered by deep learning—for medical applications, focusing on medical imaging, medical video, and clinical deployment. We start by briefly summarizing a decade of progress in convolutional neural networks, including the vision tasks they enable, in the context of healthcare. Next, we discuss several example medical imaging applications that stand to benefit—including cardiology, pathology, dermatology, ophthalmology–and propose new avenues for continued work. We then expand into general medical video, highlighting ways in which clinical workflows can integrate computer vision to enhance care. Finally, we discuss the challenges and hurdles required for real-world clinical deployment of these technologies.

scholarly journals Modular Interoperability in Surgical Robotics Software

2015 ◽  
Vol 137 (09) ◽  
pp. S19-S22
Author(s):  
Peter Kazanzides ◽  
Anton Deguet ◽  
Balazs Vagvolgyi ◽  
Zihan Chen ◽  
Russell H. Taylor
Keyword(s):  
Medical Imaging ◽  
Rate Control ◽  
Da Vinci ◽  
Integrated Systems ◽  
Ultrasound Images ◽  
Image Guided ◽  
Modular Software ◽  
Image Guided Intervention ◽  
Robot Systems ◽  
Software Modules

This article reviews on modular interoperability of the software that is used for these types of systems. One key point is that while hierarchical multi-rate control may be suitable for the master and slave robots, there is also a requirement to handle the video and ultrasound images. This article presented an overview of surgical robot systems, with the recognition that these systems are not just robots, but integrated systems that include robots, databases, and real-time sensors such as video and other medical imaging devices. Common research platforms, such as the da Vinci Research Kit and Raven II, have recently become available. This has underscored the need for modular software interoperability, so that researchers can share software modules and more easily integrate other robots and devices. Standardization and interoperability are most applicable at the higher software layers, and can benefit from the availability of widely-adopted middleware such as ROS. Other interface protocols, such as OpenIGTLink, can be useful due to their wide support within the medical imaging and image-guided intervention domains.

A Comparison of Orthogonal Transforms in Engineering Computer Vision

1990 ◽  
Vol 204 (5) ◽  
pp. 321-327 ◽  
Author(s):  
G A H Al-Kindi ◽  
R M Baul ◽  
K F Gill
Keyword(s):  
Computer Vision ◽  
Machine Vision ◽  
Visual Inspection ◽  
Computational Time ◽  
Transform Coefficients ◽  
Orthogonal Transforms ◽  
The Impact

A comparison of a number of commonly used orthogonal transforms, when applied to the recognition and visual inspection of engineering components, has been made. The impact on the performance and computational time for the machine vision process due to varying numbers of transform coefficients is assessed.

Nanogold-based materials in medicine: from their origins to their future

Nanomedicine ◽  
2021 ◽  
Author(s):  
Tânia Ferreira-Gonçalves ◽  
David Ferreira ◽  
Hugo A Ferreira ◽  
Catarina P Reis
Keyword(s):  
Gold Nanoparticles ◽  
Optical Properties ◽  
Potential Application ◽  
Biomedical Applications ◽  
Production Method ◽  
Therapeutic Approaches ◽  
Production Methods ◽  
Research Fields

The properties of gold-based materials have been explored for centuries in several research fields, including medicine. Multiple published production methods for gold nanoparticles (AuNPs) have shown that the physicochemical and optical properties of AuNPs depend on the production method used. These different AuNP properties have allowed exploration of their usefulness in countless distinct biomedical applications over the last few years. Here we present an extensive overview of the most commonly used AuNP production methods, the resulting distinct properties of the AuNPs and the potential application of these AuNPs in diagnostic and therapeutic approaches in biomedicine.

Wavelet Transform-Based Soft Computational Techniques and Applications in Medical Imaging

2016 ◽  
pp. 339-363
Author(s):  
Shabana Urooj ◽  
Satya P. Singh
Keyword(s):  
Neural Networks ◽  
Wavelet Transform ◽  
Medical Imaging ◽  
Biomedical Applications ◽  
Imaging Techniques ◽  
Emission Tomography ◽  
Computational Techniques ◽  
Biomedical Image ◽  
Positron Emission ◽  
Neuro Imaging

The aim of this chapter is to highlight the biomedical applications of wavelet transform based soft computational techniques i.e. wavenet and corresponding research efforts in imaging techniques. A brief introduction of wavelet transform, its properties that are vital for biomedical applications touched by various researchers and basics of neural networks has been discussed. The concept of wavelon and wavenet is also discussed in detail. Recent survey of wavelet based neural networks in medical imaging is another facet of this script, which includes biomedical image denoising, image enhancement and functional neuro-imaging, including positron emission tomography and functional MRI.

scholarly journals An overview of research on plant based natural dyes in Nepal: scope and challenges

2020 ◽  
Vol 3 (2) ◽  
pp. 45-66
Author(s):  
Netra Lal Bhandari ◽  
Basant Pokhrel ◽  
Upashana Bhandari ◽  
Sulakshana Bhattarai ◽  
Anil Devkota ◽  
...  
Keyword(s):  
Research Laboratory ◽  
Biomedical Applications ◽  
Public Awareness ◽  
Natural Dyes ◽  
Synthetic Dyes ◽  
Fastness Properties ◽  
Research Fields ◽  
Dyeing Process ◽  
Wide Range ◽  
Dye Extraction

The worldwide demand of natural dyes is of great interest due to the increased public awareness about the atmospheric and environmental pollution caused by the commercially available synthetic dyes. Nepal being wealthy in flora, would be fine research laboratory land for the plant based natural dyes. Among most of the natural dyes, plant-based dyes/pigments have wide range of applications in fabric, food, drug coloring, therapeutic values and also in solar cells in presence of different mordants. The use of mordant is inevitable during natural dyeing process in order to improve the fastness properties on fabrics, foods and drugs by forming a co-ordination complex with dye. In this article, a short overview of plant based natural dyes extraction applications and their scope and limitations will be discussed with special reference to Nepal. In the present review, the green methods of dye extraction, and dyeing technologies will be discussed, and the research fields based on natural dyes will be explored. Some of the natural dyes has also shown the antimicrobial, antioxidant, antifungal properties and hence are also discussed with biomedical applications.  

scholarly journals Classification of Metro Facilities with Deep Neural Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Deqiang He ◽  
Zhou Jiang ◽  
Jiyong Chen ◽  
Jianren Liu ◽  
Jian Miao ◽  
...  
Keyword(s):  
Neural Networks ◽  
Computer Vision ◽  
Learning Technology ◽  
Deep Convolutional Neural Networks ◽  
Research Fields ◽  
Human Labor ◽  
Train Operation ◽  
The Common ◽  
Automatic Train Operation ◽  
Computational Resources

Metro barrier-detection has been one of the most popular research fields. How to detect obstacles quickly and accurately during metro operation is the key issue in the study of automatic train operation. Intelligent monitoring systems based on computer vision not only complete safeguarding tasks efficiently but also save a great deal of human labor. Deep convolutional neural networks (DCNNs) are the most state-of-the-art technology in computer vision tasks. In this paper, we evaluated the effectiveness in classifying the common facility images in metro tunnels based on Google’s Inception V3 DCNN. The model requires fewer computational resources. The number of parameters and the computational complexity are much smaller than similar DCNNs. We changed its architecture (the last softmax layer and the auxiliary classifier) and used transfer learning technology to retrain the common facility images in the metro tunnel. We use mean average precision (mAP) as the metric for performance evaluation. The results indicate that our recognition model achieved 90.81% mAP. Compared with the existing method, this method is a considerable improvement.

Indexing of diffraction patterns for determination of crystal orientations

2020 ◽  
Vol 76 (6) ◽  
pp. 719-734
Author(s):  
Adam Morawiec
Keyword(s):  
Computer Vision ◽  
Computer Science ◽  
Reciprocal Lattice ◽  
General Description ◽  
Indexing Methods ◽  
Research Fields ◽  
Underlying Principle ◽  
Star Identification ◽  
Diffraction Patterns

The task of determining the orientations of crystals is usually performed by indexing reflections detected on diffraction patterns. The well known underlying principle of indexing methods is universal: they are based on matching experimental scattering vectors to some vectors of the reciprocal lattice. Despite this, the standard attitude has been to devise algorithms applicable to patterns of a particular type. This paper provides a broader perspective. A general approach to indexing of diffraction patterns of various types is presented. References are made to formally similar problems in other research fields, e.g. in computational geometry, computer science, computer vision or star identification. Besides a general description of available methods, concrete algorithms are presented in detail and their applicability to patterns of various types is demonstrated; a program based on these algorithms is shown to index Kikuchi patterns, Kossel patterns and Laue patterns, among others.

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