SPIE, the international society for optics and photonics

Another year has come to an end, but Don't Stop Us Now: #PhotonicsWest is traveling at the speed of light, just weeks away. While we are Under Pressure to bring you the best event yet, we wanted to take time to re-introduce you to the four rockstars who make up the 2025 SPIE presidential chain: President Peter de Groot, President-Elect Julie Bentley, Vice President Cather Simpson, and Immediate Past President Jennifer Barton. 🎸 Be sure to say hello to these Cool Cats if you see them around the Moscone Center in San Francisco! 👋

What a Wednesday at #SPIEMedicalImaging! 💯 From keynotes on image-guided surgery using ultrasound and the role of computational pathology in tomorrow's medicine to an exciting evening of poster competition, it was an insightful and productive day. Congratulations to the winners of the second 3-minute poster competition, sponsored by #SPIE_JMI! In first place was Clara Duquette Evans; in second place was Adam Saunders; and in third place was Marco Wende. 👏 Browse this photo gallery, and be sure to tag your friends if you see them in the photos! 📸

Last night's #SPIEMedicalImaging poster session covered a range of topics, from image processing and computer-aided diagnosis to ultrasound and computational pathology. Meet three of the researchers who presented! Vivek Yadav, PhD student at the Icahn School of Medicine at Mount Sinai, is working to improve how doctors find liver cancer, or hepatocellular carcinoma (HCC), in patients using imaging techniques. His team investigated the application of deep learning techniques to automate HCC tumor detection and segmentation within dynamic contrast-enhanced protocols. They also introduced a new approach to improve the AI’s ability to identify tumors more accurately. ✅ Walia Farzana, graduate student at Old Dominion University, shared results from a new study on understanding obesity as a brain-related problem, where the brain's control over hunger and eating isn't working correctly. With a new Conformal Deep Learning model, her team achieved a 5-fold cross-validated average precision of 77.65% and an F1-score of 75.42%, effectively classifying a patient as obese or healthy with an uncertainty score from structural MRI. 🏷️ Milla Nielsen, undergraduate student at UCLA, presented work she did while studying abroad at the University of Copenhagen (Københavns Universitet). Her study aimed to detect significant indicators of early Alzheimer’s disease by extracting and integrating various imaging biomarkers. The team analyzed structural MRI scans utilizing comprehensive image analysis and machine learning techniques, showing that combining multiple biomarkers significantly improves detection accuracy. 💯 We are excited for next year's #SPIE Medical Imaging poster sessions in Vancouver, BC! 👋

"Miniaturized and high-accuracy diamond vector magnetometers will unlock better, faster mineral surveys at scale, with drone fleets flying close to ore bodies and exploiting diamond vector measurements to reveal deep and complex mineral structures currently blurred by the lack of rich and accurate magnetic data at a certain depth." Read more about this technology in the January/February issue of #PhotonicsFocus: https://lnkd.in/gfMaN2nc

Next week, Tatiana Novikova joins the #SPIEOnline Henri Poincare webinar series to discuss multi-wavelength, wide-field imaging Mueller polarimetry as a diagnostic tool for the optical biopsy of tissue. Hear about this promising new approach: https://lnkd.in/gZSiA_Ju #optics #imaging #SPIE

Just a snapshot of the energy and excitement at #SPIEMedicalImaging on Tuesday! 📸🎈

SPIE Medical Imaging 🤝 Best Paper Awards This week at #SPIEMedicalImaging, we are celebrating exceptional work with conference Best Paper Awards. Congratulations to these recipients and thank you to the sponsors! Physics of Medical Imaging Student Paper Award, sponsored by United Imaging Healthcare 🏆 Winner: Zitong Yu, Washington University in St. Louis (Accepted by Abhinav Kumar Jha on behalf of the recipient) ✨ Runner-up: Yuanming Hu, University of North Carolina at Chapel Hill  Imaging Informatics Best Paper Award 🏆 Winners: Lance Long, University of Pittsburgh and Ying Zhang, Polytechnique Montréal Image Processing Student Paper Award, sponsored by Philips 🏆 Winner: Jongyeon Yoon, Vanderbilt University ✨ Runner-up: Xuan Loc Pham, Radboudumc

We're back with another #WiOWednesday! This week, we have the pleasure of highlighting Mariana Amorim Fraga, Assistant Professor and Lead of Sensors and #Photovoltaic Devices Research Group at Universidade Presbiteriana Mackenzie. Since childhood, her curiosity about science and her good performance in physics, chemistry, and mathematics inspired her to pursue a career in engineering. Now, she teaches electronic circuits to engineering students, helping them understand how the systems work. She also guides doctoral students in microelectronics, semiconductor material synthesis, and device fabrication processes. Her advice to young girls or women considering a career in STEM is to, "Embrace challenges as opportunities for growth, seek out mentors and supportive networks, and don’t be afraid to ask questions or seek help when needed." Read her story in the 2025 #SPIE #WomenInOptics notebook here: https://lnkd.in/gW6M6F7E

Image this 📸😎 Monday at #SPIEMedicalImaging was buzzing with excitement! Thomas Grist, Abhinav Kumar Jha, and Karandeep Singh kicked off the day with keynotes on fostering innovation, AI in clinical imaging, and the AI health paradox. Throughout the morning and afternoon, attendees enjoyed discussing their latest work over coffee ☕, sharing results via hundreds of technical presentations 📊, and posing for group photos in front of our photo wall 😀. Monday evening brought the first of two poster sessions and the first-ever 3-minute poster competition at SPIE Medical Imaging, sponsored by #SPIE_JMI! Congratulations to our winners: first place, Jessica Im; second place, Grace Minesinger; third place, Coleman Farvolden. We’re looking forward to the rest of the week. Share your Monday highlights with us in the comments below! 💬

Last night’s poster session at #SPIEMedicalImaging was a great opportunity to connect, share, and learn about the latest work in image processing, informatics, modeling, image perception, and more. Let’s take a look at some of the innovative work that was presented! ✨ Grace Burton, undergraduate physics student at Yale University, presented work she did while studying abroad in Sweden. At KTH Royal Institute of Technology, she investigated the feasibility of developing a tabletop photon-counting micro-computed tomography device to perform intraoperative virtual histopathology on tumor specimens. The simulation, using the SpekPy Python package, shows promise for distinguishing features as small as 33 microns in soft tissue, making it capable of effectively assessing tumor margins during surgery.   ✨ Michelle Bryarly, undergraduate biomedical engineering student at The University of Texas at Dallas, is working to address the lack of precision in retinal imaging models and the variable and ethical concerns with using live animals. Bryarly and her team designed a 3D-printed mouse phantom retina to simulate eye conditions and produced a gelatin phantom with deoxygenated blood to simulate veins and arteries. Their results showed that the phantom had rich spatial and spectral details and produced reliable blood oxygenation rates. ✨ Kaitlyn Sims, master’s student at Toronto Metropolitan University, presented research on scatter levels in triple-energy photon-counting X-ray imaging. This technology could allow for real-time removal of background scatter in interventional radiography. By analyzing scatter at various energy levels, Sims’ work aims to improve image clarity, which is particularly useful for medical procedures like angiograms. ✨ Syed Anwar is a principal investigator at Children's National Hospital and associate professor at The George Washington University School of Medicine and Health Sciences. His work showcases promising results from testing a machine learning algorithm to predict the outcomes of an alveolar molding plate treatment, which is used to near-normalize the oral cleft deformity of neonates with unilateral cleft lip and palate before their first cleft repair surgery.