Background and objectives: Dynamic thermal imaging in medicine has several advantages in comparison to static thermal image analysis and has potential as a novel patient assessment method e.g. in the area of vascular surgery. Since dynamic thermal imaging has become in the scope of research only during the last decade, the computational available analysis methods are often lacking or not existing. Most of the published software is not available to the research community or are behind a paywall. IRlab provides an easy-to-use dynamic thermal video processing and analysis platform, freely accessible to researchers. Methods: IRlab is programmed in Matlab R2020b. Computational tools for dynamic analysis are divided into spatio-temporal and spectral methods, where spatio-temporal methods consist of region of interest delineation tools, thermal modulation analysis, standard thermal measures such as median, maximum, minimum and deviation values, and subtraction and gamma maps. Spectral methods include spectral band power, spectral flow, and wavelet analysis tools. Preliminary data of a single healthy subject was analyzed with the program as a sample run. Results: IRlab provides a platform for lower limb thermal image and video analysis with a clear workflow and variety of processing and analysis tools for time and frequency space analysis. The whole source code for IRlab is freely available for the research community under the General public license. Conclusions: IRlab is a versatile tool for dynamic thermal image and video processing. Freeware and open-source programs for medical thermal imaging are severely lacking, thus as a completely open-source project IRlab offers a unique platform for researchers within the field of medical thermal imaging.
|Julkaisu||Informatics in Medicine Unlocked|
|DOI - pysyväislinkit|
|Tila||Julkaistu - 2022|
|OKM-julkaisutyyppi||A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä|
- Jufo-taso 1
!!ASJC Scopus subject areas
- Health Informatics