Lend us your thermal images!

Please consider taking part of an open repository initiative of thermal images hosted at the following website: https://trench-ir.azurewebsites.net/. If you are acquiring thermal images of plants, animals, or their environment using FLIR cameras, we would like you to share your images as part of this initiative. We welcome images from research grade cameras or from hand-held mobile phone provided the images are radiometric jpgs.

Infrared imagery offers a unique opportunity to see biophysical properties in real time. We can watch organisms heat up, cool down, and generally transfer heat back and forth throughout their environment. In the TrEnCh-IR Project, we use infrared imagery to help people see the world from a thermal perspective because we believe it’s an intuitive first step to understanding microclimate and the impacts of warming.

The TrEnCh-IR project is part of a larger initiative interested in Translating Environmental Change into organismal responses. Our goal is to build case studies of how animals are impacted by climate change to improve our approach to climate change biology education, policy, and research.

Mission

FLIR cameras are extensively used, increasingly so with the availability of FLIR thermal cameras that attach to phones. However, the cameras produce images in a non-standard format (radiometric jpgs) and analyzing the images requires purchasing expensive FLIR software. Project collaborator Tattersall has produced an open source R package (ThermImage, https://github.com/gtatters/Thermimage) that converts the images into standard formats and extracts additional data to allow analysis in commonly used and open source software such as ImageJ. Our web service makes these tools more accessible. We aim to empower more people to view the world from a thermal perspective.

Our thermal image repository will allow researchers to analyze the surface temperatures of disparate organisms in diverse environments. Education and outreach resources promote understanding how organisms experience their environment. We aim to maintain the repository long term, but can not guarantee longevity at this point. An ongoing aim is to use initial AI algorithms, potentially combined with crowd sourced landmarking, to distinguish organisms, particular body parts, and backgrounds. Our interface will allow users to explore the images to understand how organisms interact with their environments.

Motivation

Currently most analyses of the impacts of climate change on organisms are based on air temperatures, but body temperatures of ectotherms can differ from air temperatures by tens of degrees. Additionally, the characteristics and behaviours of organisms can result in their experiencing different body temperatures even in the same environment with repercussions for species interactions. Moving beyond air temperatures to consider body and surface temperatures may thus be essential to accurately forecasting climate change impacts. Thermal images provide compelling visual examples of why we need to move beyond air temperatures in examining climate change impacts as well as data that can inform approaches for modelling how organisms interact with their environment.

Team

Dr. Lauren Buckley, University of Washington, Professor

Abigail Meyer, Lead Developer & University of Washington Research Scientist

Dr. Glenn Tattersall, Brock University Professor & Thermal Biologist

Site development based with University of Washington, in the Department of Biology.

We are funded by AI for Earth, a Microsoft initiative.

Forced Hibernation on the CBC

My former MSc student and colleague, Anne Yagi’s research is featured on this CBC – Radio Canada link!

https://ici.radio-canada.ca/tele/la-semaine-verte/site/segments/reportage/211434/serpent-massasauga-espece-voie-disparition

This speaks to ~8 years of winter efforts to test this technique out in the lab and in the field! Hopefully we will publish soon. I’m not used to the CBC scooping us, but they don’t have to write the manuscripts and do the stats, so maybe I can excuse them.

These efforts are all related to a head starting project initiated by Anne Yagi on the Massasauga, taking physiological and behavioural data performed in careful lab experiments, testing these for 1-2 winters, then expanding to larger sample sizes in subsequent years to lead to the 9 minute videos above.

Many thanks to 8Trees Inc, Anne Yagi, Dr. Katharine Yagi and all of the animal care and field assistants that make Anne’s work possible (Theresa Bukovics, Tom Eles, Shawn Bukovac, Matt Jung, and many others).

Fish get the “rotten egg gas” chills.

At long last, resulting from herculean efforts of a number of former students, our paper is published. Out today in Royal Society Open Science, our paper entitled: “Hydrogen sulfide exposure reduces thermal set point in zebrafish” represents the efforts of two honours students (JC Shaw and CD Dobell) and the writing and analytical skills of a great PDF and colleague (DA Skandalis).

Here is a link to the study and full citation:

Skandalis DA, Dobell CD, Shaw JC, Tattersall GJ. 2020 Hydrogen sulfide exposure reduces thermal set point in zebrafish. R. Soc. Open Sci. 7: 200416.

https://royalsocietypublishing.org/doi/10.1098/rsos.200416

We tested whether dissolved H2S in the water will alter thermal preference. Previously, work in mice has suggested that mice could be induced to adopt a “hibernation-like” state, although there was some doubt (in the literature) as to whether H2S signalled a change in thermoregulatory state or simply acted as a metabolic inhibitor. By testing this in zebrafish, we could test formally whether they prefer cooler temperatures with H2S exposure, and they did. Not only did they choose to cool down, but they continued to make thermoregulatory decisions, swimming back and forth between cool and warmer water, suggesting they are still making thermoregulatory decisions and not simply caught in the cold water. So…yeah, complicated. H2S might induce a behavioural anapyrexia (a lowered thermal set-point). We discuss the potential environmental and neurophysiological context in the paper for those interested. The rotten egg reference is to the smell of H2S gas.

To conduct this study, we used a system built by Brock University’s Technical Services and employed in our research lab that allows us to track fish in a two chamber thermal shuttle box:

Schematic of the Shuttle Box System (see Figure S1 in the paper).

This setup allows us to heat and cool a tank and track the fish’s choices over time. Here is a thermal image depicting an earlier version of the shuttle box (correcting the spill over of warm-water in the centre can be corrected using baffles and a circular chamber system, but I haven’t taken a new picture with the thermal camera during the pandemic lockdown):

There was some considerable interest in developing H2S as a therapeutic to put mammals and/or tissues/organs into a suspended state. It is intriguing that animals like zebrafish that can behaviourally regulate body temperature continue to do so under this exposure. Anaprexic stategies are commonly seen in ectotherms and perhaps by hijacking an innate signalling system, H2S evokes this response.

World Cassowary Day

It’s World Cassowary Day (26 September).

https://www.worldcassowaryday.org/

In honour of this day, here is a thermal image collage of a baby cassowary surrounded by thermal images of its siblings in egg shells.

Congratulations to Dr. Todd Green (@CassowaryKid) for completing his PhD on Cassowary casque development (see below).

Many thanks to Todd Green and Paul Gignac for hosting me on our Cassowary adventure a few years back. It’s nice to see Todd’s work coming out in press!

Do surface temperatures measure core temperature? No.

Working from home during the COVID19 pandemic has proven a challenge for many of us. Our students are not allowed to pursue their research, and yet most of us are working as hard from home as we would be on campus.

Anyhow, at the beginning of the lockdown, I gathered what equipment I could from the lab and set up to research at home. Hardly a serious pursuit, but I was designing some training material for an overseas student and needed the equipment at home anyway.

What kind of research can you do on yourself on lockdown you might ask? A little bit of thermal imaging!

Since COVID19 is/was on everyone’s mind, I knew it was only a matter of time before the fever scanning would start up again (remembering SARS 2003 and all the thermal cameras in airports).

But thermoregulatory physiologists know that surface temperature rarely, if ever, is equal to core temperature so then, how do we reconcile this with the return to use of superficial fever scanning?

Maybe it is because imaging is appealing to people and it is compelling that a region of the face or head close to the eye always appears warm, so naturally people assume it might represent or correlate to core measurements of body temperature. Indeed, even in animal thermal biology, this is one of more common questions people ask me: “Can eye temperature be an estimate of core temperature?”. To which I quip, “No”, with caveats.

I am not aware of systematic studies demonstrating that these warm eye/head surface temperatures are really good at estimating core temperature, but we previously measured core and surface temperatures in a previous study of ours in ducklings across different times of day and during a period of fasting:

Duckling thermal images – captures at two air temperatures and under different conditions.

Core temperature rises and falls quite substantially (ranging from ~39 to ~42C) across these different states and time periods:

Core (crop) temperature in ducklings measured over a course of 12 days, including a fasting period between days 5-8.

But the correlation between core temperature and the maximum eye region temperature is not that great. Indeed, you would expect the values to fall along or at least be parallel to the dotted line of equality below, but in the case of low air temperatures, the relationship is quite poor and the surface temperatures are much cooler than core.

Maximum eye region temperature correlates with core temperature, but not very strongly and is quite heavily dependent on surrounding air temperature.

So, it is easy to conclude that max eye temperature is not always a reliable indicator of core temperature in these ducks. Maybe we could derive an empirical calibration curve, taking into account air temperature, but the point is that this requires accurate temperature data and stable environmental conditions rarely present in the field.

So, what about the lockdown research mentioned earlier?

Having plenty of time to myself, I set up a thermal camera to capture a thermal image of my face at various times throughout the day to capture the natural variation in body temperature (no fever, per se, but my daily oral temperature measurements range from 35.6 to 36.9C). Here is a sample image, outlining the typical regions of skin surface measured:

Red arrow (inner canthus of the eye, typical hottest part of the face, ~35.2C here). Blue arrow (tongue, equivalent to measurement with oral thermomemeter, ~36.7C here). Green question mark (forehead, location of scanners seen on a lot of websites, ~32.4C here).

It got too scary the longer I was in lockdown as my hair grew too long and disheveled, so I ceased the experiment after only a short period.

But the results (next 3 graphs) below show how poorly forehead assesses normal oral temperature, and even how maximum eye temperature is ~1C cooler than oral temperature and influenced by nearby ambient conditions (my garage was cold back in April so I set up there for a few measurements).

Conclusions: Ignoring the N=1 subject (due to the pandemic this seems justified), forehead is a poor measure of oral temperature (3.85C too low), maximum eye temperature a bit better (but still 1C too low and affected by air temperature), while simply pointing the camera in your mouth and getting maximum temperature yields a temperature ~0.5C higher than an oral thermometer.

So, why if you look at any images of companies and airports doing fever scanning they point devices at people’s foreheads or relying on a single pixel value from possibly the eye region?

The simple answer is that it is easy to do, but from a target accuracy perspective, it is terrible, especially if low accuracy devices are being employed inappropriately. In the one image above, the device is pointing at someone’s hair, which shields the skin and thus produces a cooler value. Cooler values will not trigger a fever detection even if it is there!

So, wherefore is the future of fever scanning? Intuitively, it seems it should work, but are we measuring the wrong thing? Why don’t we measure inside the mouth where normal oral thermometers do? At least this is better than crappy forehead measurements. Is this a privacy issue? Is it feasible to do in rapid scanning processes? Will it be feasible if we are all wearing masks?

I am not the first to write on this. This blog project was mostly a distraction in the early days of lockdown to keep my mind off the situation. I attach a few key articles and opinion pieces on the subject below that have commented more clearly on the connection (or lack) between fever and infection and why fever screening is not a panacea.

Links to further reading:

Scientific studies demonstrating reasonable predictive power for fever scanning:

Other articles discussing why using fever scanning does not equate to infection and misses asymptomatic cases of COVID19:

WHO Recommendations on temperature screening:

Idea for a Review Paper Anyone?

I think this situation really needs another look by the physiology community. My anecdote here is simply based on self reflection/measurement but also based on years of experience with thermal imaging.

The first rule of thermal imaging in biological systems: “Surface Temperature is not equal to Core Temperature.” We can’t forget that. If you want to use surface temperature, you have to do a lot of calibration checks or have very good control over your subject.

In case a grad student locked down at home wants a writing project, here are a few key points that I know should impact the predictive power of max surface temperature measurements in the context of rapid fever scanning in public places:

  • Air temperature near skin
  • Air flow (convective heat exchange) over skin
  • Blood flow relationship with the skin surface
  • Camera user skills and training
  • Quality and accuracy of the thermal scanner (some scanners I see people using have accuracies of +-2 to 4C).
  • Pre-symptomatic people lack fever
  • Masking of fever with antipyretic drugs undetected by scanning
  • What is the precise correspondence of eye canthus temperature with core temperature measurement?

Video based quantification of activity

Although not an inspiring or catchy title, our study has just been published, demonstrating that fixed-frame video capture can provide a quantitative assessment of energetics (citation below).

Summary of the study

Infrared thermal imaging is a passive imaging technique that captures the emitted radiation from an object to estimate surface temperature, often for inference of heat transfer.

Infrared thermal imaging offers the potential to detect movement without the challenges of glare, shadows, or changes in lighting associated with visual digital imaging or active infrared imaging.

In this paper, we employ a frame subtraction algorithm for extracting the pixel-by-pixel relative change in signal from a fixed focus video file, tailored for use with thermal imaging videos.  

A greyscale video of a metronome. Inanimate objects are still visible to the thermal camera due to slight differences in thermal equilibration, emissivity, and reflectivity across the different surfaces.
Same video as above, but as an “absolute difference image”, where each frame is subtracted from the previous frame and positized (i.e. the absolute value taken for each pixel difference). During zero motion, the image space is black with low variability based on sensor noise (sd number in upper left). After motion starts (~0:11), you clearly see the moving metronome as each frame difference depicts how pixels in a fixed frame differ.

By then cumulatively summing the sd for each frame across an entire video, we are able to assign quantitative activity assessments to thermal imaging data for comparison with simultaneous recordings of metabolic rates. We tested the accuracy and limits of this approach by analyzing movement of a metronome (see above) and provide an example of the approach to a study of Darwin’s finches.

Fixed frame Different Image Thermography video of a bird filmed over a long period of time within a viewing chamber. The cumulative difference image provides a slope value that corresponds to an indication of movement. Scale is relative to the degree of motion.

Simultaneous measurements of oxygen consumption (dark black lines) match up well with smoothed estimates (blue lines) of the activity score (grey lines) derived from the difference image thermography videos. Resolving fast respirometry data is difficult and best left to the experts at Sable Systems, but the average trends are informative for energy expenditure.
Correlations between 5 minute average oxygen consumption measurements and the activity values line up well at the individual level.

In principle, this “Difference Imaging Thermography” (DIT) would allow for activity data to be standardized to energetic measurements and could be applied to any radiometric imaging system.

Caveats

Fixed frame is required. Changing the reference frame or using a camera without a tripod would not work unless you do a lot of motion correction. Also, we used infrared thermal imaging because we were collecting data for a different purpose (still writing those up!), but we think that any sort of imaging should work, provided it produces a simple, ratiometric or radiometric image. Usually monochrome cameras or near infrared cameras produce a signal that is a simple greyscale image. Reflected light might interfere with the approach, so this is why we argued this might be an addition use of thermal imaging videos.

Behind the scenes

This paper took a long time to put together, but was the beginning of my lab’s journey into R, ImageJ, and open source coding. A lot has changed since I started the data analysis. Combing through 500 Gb of video files, extracting, processing, converting them into something manageable took the better part of 2 weeks on a supercomputer, until I realised that there were more efficient routes!

We have since created routines in ImageJ that help facilitate the conversions and have placed those routines in a github repository, where we will write them up as a methods paper in the future. The principles outlined in the paper are not themselves novel. Sliding average and frame subtraction routines are common in video processing software. Assessing whether the motion captured is correlated with meaningful biological information is what we hoped to capture with the study.

Citation

Tattersall, GJ, Danner, RM, Chaves, JA, and Levesque, DL. 2020. Activity analysis of thermal imaging videos using a difference imaging approach. Journal of Thermal Biology.  91 102611 https://doi.org/10.1016/j.jtherbio.2020.102611

Link to the full text here (first 50 clicks can access the paper).

Congratulations, Nick Sakich, MSc!

In a first for the lab, we just held a completely online MSc defence. Valiantly, Nick defended his MSc with grace, precision, insight, humour, and interesting anecdotes.

His thesis is entitled: “The Physiological and Behavioural Consequences of Reduced Scalation in Captive-bred Phenotypes of the Bearded Dragon (Pogona vitticeps Ahl 1926)“.

Here he is giving his presentation (sorry for the screen cap, Nick)

speaking about one of our favourite study animals:

The 3 phenotypes of captive-bred Pogona vitticeps studied in Nick’s thesis. a) wildtype, b) leatherback, and c) silkback.

Many thanks to the examining committee:

External Examiner, Dr. Chris Oufiero, Towson University
Chair, Dr. Cheryl McCormick
Committee Member, Dr. Jeff Stuart
Committee Member, Dr. Robert Carlone
Supervisor, Dr. Glenn Tattersall

Virtual congratulations to Nick are insufficient expression of gratitude for his hard work and devotion to his research. When and if we can safely congregate in small groups, we will celebrate appropriately! I really owe Nick my thanks for joining my lab. He has helped educate me through his efforts. It cannot be fun wrapping up one’s MSc during a pandemic, and Nick did a brilliant job.

A few highlights from Nick’s presentation below.

Thanks as well to A&A Dragons for their support over the years.

Avian Thermal Biology Visitor

The lab will be hosting a PhD student from Spain for the next 3 months.

Núria Playà Montmany from the University of Extremadura has just arrived (I’m a few days late, she arrived in late January!). I met Núria last summer defending her poster at the SEB meeting in Sevilla. She will be becoming a thermal imaging expert while she is here!

With overlapping interests in avian physiology and the lab’s interests in thermal biology and studying animal responses to climate change, we hope to have a productive visit. Here is a link to Núria’s blog:

https://birdsfacingclimatechange.wordpress.com/author/nuriaplaya/

Welcome to the lab, Núria! Let’s hope you have a good few months working with us.