Motivation and Context
Plankton play a vital role in marine ecosystems. From a climate perspective, these organisms are a huge factor within the global carbon budget impacting the amount of carbon pulled from the atmosphere. Increasingly, oceanographers rely on in-situ (submerged) imaging systems to study populations in their natural environment. While typical in-situ imaging captures 2D images, many processes relate to the 3D structure fundamental to the absorption/diffusion of nutrients and waste.
Motivated by this, we asked the following question: can we reveal the 3D structure of organisms within a flow? The recovered structure in this case does not come from a specific organism, rather, it represents an average structure among organisms. As organisms flow through an imaging chamber they are captured at a random orientation. Drawing the analogy to computational and mathematical aspects of CryoEM tomography, we developed an approach for 3D in-situ plankton imaging.
While motivated by plankton, revealing the 3D structure of elements in a flow could be used in a wide variety of environmental applications (e.g. imaging sediments, aerosols, ice crystals, etc). In this proof-of-concept, we established the concept and showed initial results on data from Woods Hole Oceanographic Institution (WHOI). In a self-calibrated way, we estimated the orientation and scale of each plankton, resulting in size distribution (right panel below), together with the mean 3D volume (middle panel).
Our work has opened the door to novel computational solutions; continuing this line of inquiry, a follow-up work by Roi Ronen has received the 2021 Optical Society of America Best Paper stating: "Since climate change is acknowledged as a global problem for scientists to address, the development of enhanced tools for large-scale investigation of plankton populations is timely and highly significant"
Aviad Levis, Yoav Schechner, Ronen Talmon, “Statistical Tomography of Microscopic Life”, Proc. IEEE CVPR, 2018, and Invited talk in CVPR Workshop on Automated Analysis of Marine Video for Environmental Monitoring (2018).