Literature DB >> 33572091

An Anatomical Thermal 3D Model in Preclinical Research: Combining CT and Thermal Images.

Franziska Schollemann1, Carina Barbosa Pereira1, Stefanie Rosenhain2, Andreas Follmann1, Felix Gremse2, Fabian Kiessling2, Michael Czaplik1, Mauren Abreu de Souza3.   

Abstract

Even though animal trials are a controversial topic, they provide knowledge about diseases and the course of infections in a medical context. To refine the detection of abnormalities that can cause pain and stress to the animal as early as possible, new processes must be developed. Due to its noninvasive nature, thermal imaging is increasingly used for severity assessment in animal-based research. Within a multimodal approach, thermal images combined with anatomical information could be used to simulate the inner temperature profile, thereby allowing the detection of deep-seated infections. This paper presents the generation of anatomical thermal 3D models, forming the underlying multimodal model in this simulation. These models combine anatomical 3D information based on computed tomography (CT) data with a registered thermal shell measured with infrared thermography. The process of generating these models consists of data acquisition (both thermal images and CT), camera calibration, image processing methods, and structure from motion (SfM), among others. Anatomical thermal 3D models were successfully generated using three anesthetized mice. Due to the image processing improvement, the process was also realized for areas with few features, which increases the transferability of the process. The result of this multimodal registration in 3D space can be viewed and analyzed within a visualization tool. Individual CT slices can be analyzed axially, sagittally, and coronally with the corresponding superficial skin temperature distribution. This is an important and successfully implemented milestone on the way to simulating the internal temperature profile. Using this temperature profile, deep-seated infections and inflammation can be detected in order to reduce animal suffering.

Entities:  

Keywords:  3D THERMO-SCAN; 3D model; CT; SfM; VisualSFM; camera calibration; image processing; multimodality; registration; thermal imaging

Year:  2021        PMID: 33572091      PMCID: PMC7915503          DOI: 10.3390/s21041200

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  19 in total

1.  3D thermal medical image visualization tool: Integration between MRI and thermographic images.

Authors:  Mauren Abreu de Souza; André Augusto Chagas Paz; Ionildo Jóse Sanches; Percy Nohama; Humberto Remigio Gamba
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2014

2.  Generation of 3D thermal models for dentistry applications.

Authors:  Mauren Abreu de Souza; Andriy Guilherme Krefer; Gustavo Benvenutti Borba; Gustavo J Vizinoni E Silva; Ana Paula G O Franco; Humberto Remigio Gamba
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2016-08

3.  Convolutional Neural Network With Shape Prior Applied to Cardiac MRI Segmentation.

Authors:  Clement Zotti; Zhiming Luo; Alain Lalande; Pierre-Marc Jodoin
Journal:  IEEE J Biomed Health Inform       Date:  2018-08-14       Impact factor: 5.772

4.  Non-invasive thermal imaging of cardiac remodeling in mice.

Authors:  Rafael Y Brzezinski; Zehava Ovadia-Blechman; Nir Lewis; Neta Rabin; Yair Zimmer; Lapaz Levin-Kotler; Olga Tepper-Shaihov; Nili Naftali-Shani; Olga Tsoref; Ehud Grossman; Jonathan Leor; Oshrit Hoffer
Journal:  Biomed Opt Express       Date:  2019-11-08       Impact factor: 3.732

Review 5.  Infrared skin temperature measurements for monitoring health in pigs: a review.

Authors:  Dennis Dam Soerensen; Lene Juul Pedersen
Journal:  Acta Vet Scand       Date:  2015-02-03       Impact factor: 1.695

6.  A preclinical micro-computed tomography database including 3D whole body organ segmentations.

Authors:  Stefanie Rosenhain; Zuzanna A Magnuska; Grace G Yamoah; Wa'el Al Rawashdeh; Fabian Kiessling; Felix Gremse
Journal:  Sci Data       Date:  2018-12-18       Impact factor: 6.444

7.  Infrared 3D Thermography for Inflammation Detection in Diabetic Foot Disease: A Proof of Concept.

Authors:  Rob F M van Doremalen; Jaap J van Netten; Jeff G van Baal; Miriam M R Vollenbroek-Hutten; Ferdinand van der Heijden
Journal:  J Diabetes Sci Technol       Date:  2019-06-14

8.  Perspective review of optical imaging in welfare assessment in animal-based research.

Authors:  Carina Pereira; Janosch Kunczik; André Bleich; Christine Haeger; Fabian Kiessling; Thomas Thum; René Tolba; Ute Lindauer; Stefan Treue; Michael Czaplik
Journal:  J Biomed Opt       Date:  2019-07       Impact factor: 3.170

9.  Refinement and validation of infrared thermal imaging (IRT): a non-invasive technique to measure disease activity in a mouse model of rheumatoid arthritis.

Authors:  Zeynab Nosrati; Marta Bergamo; Cristina Rodríguez-Rodríguez; Katayoun Saatchi; Urs O Häfeli
Journal:  Arthritis Res Ther       Date:  2020-11-30       Impact factor: 5.156

10.  Automated thermal imaging for the detection of fatty liver disease.

Authors:  Rafael Y Brzezinski; Lapaz Levin-Kotler; Neta Rabin; Zehava Ovadia-Blechman; Yair Zimmer; Adi Sternfeld; Joanna Molad Finchelman; Razan Unis; Nir Lewis; Olga Tepper-Shaihov; Nili Naftali-Shani; Nora Balint-Lahat; Michal Safran; Ziv Ben-Ari; Ehud Grossman; Jonathan Leor; Oshrit Hoffer
Journal:  Sci Rep       Date:  2020-09-23       Impact factor: 4.379

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  1 in total

1.  Tomographic reconstruction from planar thermal imaging using convolutional neural network.

Authors:  Daniel Ledwon; Agata Sage; Jan Juszczyk; Marcin Rudzki; Pawel Badura
Journal:  Sci Rep       Date:  2022-02-11       Impact factor: 4.379

  1 in total

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