A 3D Scan Model and Thermal Image Data Fusion Algorithms for 3D Thermography in Medicine

Objectives. At present, medical thermal imaging is still considered a mere qualitative tool enabling us to distinguish between but lacking the ability to quantify the physiological and nonphysiological states of the body. Such a capability would, however, facilitate solving the problem of medical quantification, whose presence currently manifests itself within the entire healthcare system. Methods. A generally applicable method to enhance captured 3D spatial data carrying temperature-related information is presented; in this context, all equations required for other data fusions are derived. The method can be utilized for high-density point clouds or detailed meshes at a high resolution but is conveniently usable in large objects with sparse points. Results. The benefits of the approach are experimentally demonstrated on 3D thermal scans of injured subjects. We obtained diagnostic information inaccessible via traditional methods. Conclusion. Using a 3D model and thermal image data fusion allows the quantification of inflammation, facilitating more precise injury and illness diagnostics or monitoring. The technique offers a wide application potential in medicine and multiple technological domains, including electrical and mechanical engineering.

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Detecting abnormality in medical images with thermal and RGB images

10.46532/978-81-950008-1-4_082 ◽

2020 ◽

pp. 373-379

Author(s):

Sreelatha P ◽

Jothin R ◽

Bharath V ◽

Rajeshwari R ◽

Sudarvilizhi D ◽

...

Keyword(s):

Thermal Imaging ◽

Infrared Imaging ◽

Region Of Interest ◽

Thermal Image ◽

The Body ◽

Temperature Variations ◽

Thermal Cameras ◽

Assessment And Treatment ◽

Rgb Images ◽

Processing Techniques

Medical abnormalities in human body are often reflected by raise in temperature at various areas in the body. With the requirement of reliable non-invasive on the increase Infrared Thermal Image is an effective aiding in monitoring and diagnosing medical abnormalities. Existing research has applied Infrared Thermal Image effectively for various medical conditions like breast cancer screening, diabetes and peripheral vascular disorder, Risk Assessment and Treatment Monitoring. Thermal Image cameras are capable of capturing the body temperature variations, these temperature variations can lead to significant diagnosis in several areas ranging from simple flu caused by influenza virus to several conditions like diabetes, eye syndrome and thyroid to name a few. Heat distribution captured from Infrared Thermal Image by thermal cameras like Forward Looking Infrared Imaging (FLIR) with a sensitivity range of 0.10C and wide temperature ranging from - 100C to +1000C can produce good thermal images. This research suggests a non-expensive and non-obtrusive diagnostic procedure which utilizes thermal imaging for unexplored areas of applying thermal imaging and the possibility of extracting thermal variations with RGB images. To achieve the objective various image processing techniques like image preprocessing, selecting the Region of Interest (ROI), extraction by region segmentation, selective feature extraction and finally suitable classification of the relevant application selection are adopted. Results of the proposed method for detecting abnormality have been validated based on the temperature map histogram comparison from thermal image.

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WebGL Visualisation of 3D Environmental Models Based on Finnish Open Geospatial Data Sets

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xl-3-163-2014 ◽

2014 ◽

Vol XL-3 ◽

pp. 163-169 ◽

Cited By ~ 3

Author(s):

A. Krooks ◽

J. Kahkonen ◽

L. Lehto ◽

P. Latvala ◽

M. Karjalainen ◽

...

Keyword(s):

Spatial Data ◽

Laser Scanning ◽

National Level ◽

Image Data ◽

Point Clouds ◽

Open Pit ◽

Data Sets ◽

Environmental Models ◽

3D City Model ◽

Recent Developments

Recent developments in spatial data infrastructures have enabled real time GIS analysis and visualization using open input data sources and service interfaces. In this study we present a new concept where metric point clouds derived from national open airborne laser scanning (ALS) and photogrammetric image data are processed, analyzed, finally visualised a through open service interfaces to produce user-driven analysis products from targeted areas. The concept is demonstrated in three environmental applications: assessment of forest storm damages, assessment of volumetric changes in open pit mine and 3D city model visualization. One of the main objectives was to study the usability and requirements of national level photogrammetric imagery in these applications. The results demonstrated that user driven 3D geospatial analyses were possible with the proposed approach and current technology, for instance, the landowner could assess the amount of fallen trees within his property borders after a storm easily using any web browser. On the other hand, our study indicated that there are still many uncertainties especially due to the insufficient standardization of photogrammetric products and processes and their quality indicators.

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Integration of Image and Laser Scanning Data Based on Selected Example

Image Processing & Communications ◽

10.1515/ipc-2015-0008 ◽

2014 ◽

Vol 19 (2-3) ◽

pp. 37-44 ◽

Cited By ~ 5

Author(s):

Sławomir Mikrut ◽

Agnieszka Moskal ◽

Urszula Marmol

Keyword(s):

Point Cloud ◽

Laser Scanning ◽

3D Model ◽

Image Data ◽

Point Clouds ◽

Model Reconstruction ◽

Railway Line ◽

3D Model Reconstruction ◽

Conducting Research ◽

The Village

Abstract The paper aims at presentation of results of research on integration of image and laser data based on selected example. Since a few years the authors have been conducting research on processing image data, and those obtained from laser scanning in the form of the so-called point cloud. In experiments data from terrestrial and mobile laser scanning gained for two different objects were compared: a parish house from Goźlice located in the open-air ethnographic museum at the village of Tokarnia, Poland, and part of the Cracow-Warsaw railway line. The results of those experiments proved that data in the form of point cloud were not always sufficient for a precise 3D model reconstruction. Supplementing point clouds with photogrammetric images seems to be the best solution.

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Design of a Thermal Imaging System to Detect Possible Cases of COVID-19 Patients

International Journal of Emerging Technology and Advanced Engineering ◽

10.46338/ijetae0921_08 ◽

2021 ◽

Vol 11 (9) ◽

pp. 66-72

Author(s):

Luis Nuñez Tapia ◽

◽

Brian Meneses Claudio ◽

Witman Alvarado Díaz

Keyword(s):

Body Temperature ◽

Thermal Imaging ◽

Imaging System ◽

National Level ◽

Processing System ◽

Thermal Image ◽

The Body ◽

Thermal Camera ◽

The Government ◽

Thermal Imaging System

Abstract— The problem that the world is currently facing and that has claimed more than 3.2 million lives worldwide is COVID-19. Being a highly contagious disease, the WHO recommended limiting the movement of people out of their residence. Given this, Peru took the necessary measures to control the spread of this virus, therefore, the government decreed a general quarantine in the country, which from March 6th to May 9th, 2020, had reported the death of 1814 people in the country, because the health system at the national level was not prepared for such magnitude, in addition to that the number of infections continued to grow since they do not respect social distancing. In view of this problem, this article will design a thermal image processing system to detect possible cases of patients with COVID-19, in such a way that it allows companies or institutions to know the body temperature of each person, and thus know they are possibly COVID-19 patients. Through the design of this system, it will be possible to measure body temperature with the drone and the thermal camera at 50 cm from the person, in such a way that if the person has a body temperature higher than 38°C it could be infected with COVID-19. Therefore, the implementation of this system will help reduce the number of infections within an institution or workplace. Keywords-- Thermal camera, COVID-19, Drone, MATLAB, Image.

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Applications of 4D GIS Model in Construction Management

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.i8632.078919 ◽

2019 ◽

Vol 8 (9) ◽

pp. 2597-2608

Keyword(s):

Spatial Data ◽

Construction Management ◽

3D Model ◽

Project Planning ◽

Building Construction ◽

Construction Site ◽

Gis Model ◽

Related Information ◽

Logical Errors ◽

Information Database

Construction project involves participation of various stakeholders, contractors, and agencies for timely and effective completion. Each activity and resources of contractors are preplanned to avoid delay of project. Planning, designing and scheduling of structure are done with the help of available software’s. But this software’s still lack feature of providing related construction information in 3D model and also there isn’t any system available which can handle all project related information and documents on single platform. 4D Geographic information system (GIS) model is created by inter-linking schedule of activities and computer aided designs (CAD) drawings on GIS platform for G+4 building located in Navi Mumbai, India. The developed model can handle all project related database on single platform. Proposed methodology helps in determining incompleteness and logical errors in scheduling or designing and helps us to determine feasible route for manpower and material movement from different locations to construction site. 4D GIS model maintains spatial data such as different 3D components of structure in separate layers which is geo-referenced spatially and necessary nonspatial information such as dimensions, materials required, schedule, related documents, persons responsible, safety and quality control recommendations, site expenditure and material inventory are stored in attribute tables. This research concludes that GIS model can create real time building construction information database

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Registration and Fusion of UAV LiDAR System Sequence Images and Laser Point Clouds

Journal of Imaging Science and Technology ◽

10.2352/j.imagingsci.technol.2021.65.1.01050110.2352/j.imagingsci.technol.2021.65.1.010501 ◽

2020 ◽

Author(s):

Jiayong Yu ◽

Longchen Ma ◽

Maoyi Tian, ◽

Xiushan Lu

Keyword(s):

Point Cloud ◽

Image Data ◽

Point Clouds ◽

Optical Image ◽

Point Cloud Data ◽

Feature Points ◽

Lidar System ◽

Registration Accuracy ◽

Cloud Data ◽

Intensity Image

The unmanned aerial vehicle (UAV)-mounted mobile LiDAR system (ULS) is widely used for geomatics owing to its efficient data acquisition and convenient operation. However, due to limited carrying capacity of a UAV, sensors integrated in the ULS should be small and lightweight, which results in decrease in the density of the collected scanning points. This affects registration between image data and point cloud data. To address this issue, the authors propose a method for registering and fusing ULS sequence images and laser point clouds, wherein they convert the problem of registering point cloud data and image data into a problem of matching feature points between the two images. First, a point cloud is selected to produce an intensity image. Subsequently, the corresponding feature points of the intensity image and the optical image are matched, and exterior orientation parameters are solved using a collinear equation based on image position and orientation. Finally, the sequence images are fused with the laser point cloud, based on the Global Navigation Satellite System (GNSS) time index of the optical image, to generate a true color point cloud. The experimental results show the higher registration accuracy and fusion speed of the proposed method, thereby demonstrating its accuracy and effectiveness.

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The core academic and scientific disciplines underlying data-driven smart sustainable urbanism: an interdisciplinary and transdisciplinary framework

Computational Urban Science ◽

10.1007/s43762-021-00001-2 ◽

2021 ◽

Vol 1 (1) ◽

Author(s):

Simon Elias Bibri

Keyword(s):

The Body ◽

Data Driven ◽

New Era ◽

The Core ◽

Sustainable Urbanism ◽

Scientific Disciplines ◽

Specific Direction ◽

Research Problems ◽

Urban Planning And Development ◽

Application Potential

AbstractA new era is presently unfolding wherein both smart urbanism and sustainable urbanism processes and practices are becoming highly responsive to a form of data-driven urbanism under what has to be identified as data-driven smart sustainable urbanism. This flourishing field of research is profoundly interdisciplinary and transdisciplinary in nature. It operates out of the understanding that advances in knowledge necessitate pursuing multifaceted questions that can only be resolved from the vantage point of interdisciplinarity and transdisciplinarity. This implies that the research problems within the field of data-driven smart sustainable urbanism are inherently too complex and dynamic to be addressed by single disciplines. As this field is not a specific direction of research, it does not have a unitary disciplinary framework in terms of a uniform set of the academic and scientific disciplines from which the underlying theories can be drawn. These theories constitute a unified foundation for the practice of data-driven smart sustainable urbanism. Therefore, it is of significant importance to develop an interdisciplinary and transdisciplinary framework. With that in regard, this paper identifies, describes, discusses, evaluates, and thematically organizes the core academic and scientific disciplines underlying the field of data-driven smart sustainable urbanism. This work provides an important lens through which to understand the set of established and emerging disciplines that have high integration, fusion, and application potential for informing the processes and practices of data-driven smart sustainable urbanism. As such, it provides fertile insights into the core foundational principles of data-driven smart sustainable urbanism as an applied domain in terms of its scientific, technological, and computational strands. The novelty of the proposed framework lies in its original contribution to the body of foundational knowledge of an emerging field of urban planning and development.

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