Medical imaging modalities are now faster and more powerful than ever before,
capturing thousands of images of diseased and healthy tissue. These images represent
a vast resource for researchers and clinicians who track the progression
of viruses or other illnesses under a microscope. The images reveal cellular dynamics
that have developed within the patient, as well as similar changes in samples collected
at other laboratories or hospitals. This treasure trove of health care data also presents a
challenge: how to sort through thousands of pictures within a reasonable amount of time
to obtain a full understanding of a condition and offer an accurate diagnosis. AI is helping
to bridge this gap between stored information and surgical or therapeutic guidance.
Companies that provide the software enabling AI integration into the clinical workflow
have worked to fill this market need. According to Signify Research, the global
market for medical imaging AI applications will reach about $1.2 billion by 2025, with
a compound annual growth rate of 26%, a rise of over $800 million since 2020. While
a full range of clinical trials needs to be completed, many applications are centered on
diagnoses in radiology, pathology, ophthalmology, and dermatology.
Gulpreet Kaur and Christopher Higgins write in our cover story in this edition of
BioPhotonics that AI can also aid in the discovery of effective drug treatments, guiding
therapies to a more successful outcome more quickly. Advancements in mechanical, electrical,
and optical components — along with the incumbent increase in computing power
— have enabled sophisticated whole-slide scanning techniques, as well as software that
facilitates both the segmentation of samples and the automation of image analysis. Read
more about some of these breakthroughs here.
AI also plays a pivotal role in quantifying tissue perforation, especially when coupled
with advancements in the sensitivity of hyperspectral imaging and endoscopy. Learn
more from authors Tehzeeb Gunja and Axel Kulcke, whose feature begins here.
Elsewhere in this edition, Jiang He discusses tools used to establish spatial context for
observations at the molecular level, including the use of various advancements in fluorescent
in situ hybridization to inform spatial genomics. Follow this evolution here.
Taylor Stathopoulos and Jeremy Rowlette articulate what has been made possible
in the lab and clinic thanks to QCL-IR microscopy, where the brightness of quantum
cascade lasers is enabling video-rate imaging in the infrared regime, with applications in
metabolic imaging and cancer research. Find out more here.
Finally, in “Biopinion,” as a follow-up to last issue’s cover story on advancements
in optofluidics and microfluidics, Henne van Heeren of the Microfluidics Association
argues that, if the technology is going to see widespread use, all levels of the industry
must embrace uniform standards for the manufacture of these devices. Due to the unique
capabilities of the optics and photonics industry for testing and analysis, companies in
this space could play a crucial role in bringing the industry forward. Find out here how key players are empowering developers.
