An anatomical thermal 3d model in preclinical research: Combining ct and thermal images

Franziska Schollemann*, Carina Barbosa Pereira, Stefanie Rosenhain, Andreas Follmann, Felix Gremse, Fabian Kiessling, Michael Czaplik, Mauren Abreu de Souza

*Corresponding author for this work
5 Citations (Scopus)

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.

Original languageEnglish
Article number1200
JournalSensors (Switzerland)
Volume21
Issue number4
Pages (from-to)1-16
Number of pages16
ISSN1424-8220
DOIs
Publication statusPublished - 02.02.2021

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