2/14/21: Research by Jean-Emmanuel Bibault and Lei Xing on using deep learning to predict cancer prevalence from satellite images was highlighted by the popular newspaper Le Figaro in a beautifully-titled article, "When Man’s Health is Assessed from Space." Read it here (in French)!
11/10/20: Xing Lab research was recently featured in Stanford's Bio-X News! Notably, our broadly applicable data-driven algorithm for dimensionality reduction was published in Nature Biomedical Engineering.
11/1/20: The 2020 ASTRO Program Committee has selected our abstract titled "Dual-energy CT Imaging Using a Single-energy CT Data via Deep Learning: A Contrast-enhanced CT Study" for Best of ASTRO. Congratulations to Wei Zhao, Tianling Lv, Yang Chen and Lei Xing!
10/1/20: Our work on using AI to guide colorectal cancer care decision has been featured in Stanford Medicine and Bio-X news!
9/17/20: A new book edited by Lei Xing, Maryellen L. Giger, and James K. Min titled Artificial Intelligence in Medicine: Technical Basis and Clinical Applications has been published and is now available for purchase on Amazon.
9/14/20: Our manuscript titled "A data-driven dimensionality-reduction algorithm for the exploration of patterns in biomedical data," written by Md Tauhidul Islam and Lei Xing, has been accepted for publication in Nature Biomedical Engineering. Stay tuned!
9/3/20: Our research on using a machine learning strategy to predict survival in colorectal cancer has been published in Gut, the premier journal of gastroenterology. The model not only accurately predicts survival 10 years after a diagnosis of colorectal cancer, but also affords the reasons that explain the prediction. The model has been deployed online at https://colorectalcancersurvival.stanford.edu/.
7/12/20: Two of our abstracts were accepted to the AAPM Science Council Session at the 2020 AAPM Annual Meeting:
- SU-CD-TRACK 2-6: Deep-Learning Assisted Automatic Segmentation of Interstitial Needles in 3D Ultrasound Based High Dose-Rate Brachytherapy of Prostate Cancer. Contributors: B Han, F Wang, L Xing, H Bagshaw, M Buyyounouski.
- SU-CD-TRACK 2-10: Deriving Ventilation Imaging From Free Breathing Proton MRI Via Deep Convolutional Neural Network. Contributors: D Capaldi, F Guo, L Xing, G Parraga.
5/5/20: Our research on using AI for real-time bladder tumor detection won Best Video at AUA2020, the 2020 Annual Meeting of the American Urological Association.
12/31/19: An AI paper published in Medical Physics by Ming Ma, Nataliya Kovalchuk, Mark Buyyounouski, Lei Xing, and Yong Yang titled "Dosimetric Features-Driven Machine Learning Model for DVHs Prediction in VMAT Treatment Planning" has been listed as the Top Download of the Year!
10/28/19: Our research on using deep learning for CT image reconstruction when given only a single projection view has been published in Nature Biomedical Engineering.
6/28/19: A new book co-edited by Ruijiang Li, Lei Xing, Sandy Napel, and Daniel Rubin titled Radiomics and Radiogenomics: Technical Basis and Clinical Applications has been published as part of the Imaging in Medical Diagnosis and Therapy book series and is now available for purchase on Amazon.
3/20/19: Congratulations to Dr. Xianjin Dai who has received an Early Investigator Research Award (FY18) from the Prostate Cancer Research Program sponsored by the US Department of Defense.
3/16/19: Congratulations to Varun Vasudevan, PhD candidate from Stanford ICME, for receiving a 2019 Seed Grant Award from the Stanford Institute for Human-Centered Artificial Intelligence (HAI). His project is titled "Robust Deep Neural Network Optimization with Second Order Method for Biomedical Applications."
3/15/19: Dr. Lei Xing has been selected to receive a Google Faculty Research Award!
3/8/19: Congratulations to Dr. Wei Zhao, who has been selected as the runner-up to the Image-Guided Procedures, Robotic Interventions, and Modeling Young Scientist Award for his paper, “Automatic marker-free target positioning and tracking for image-guided radiotherapy and interventions” (10951-10) at the 2019 SPIE Medical Imaging Conference in San Diego.
3/7/19: A new book co-edited by Jun Deng and Lei Xing titled Big Data in Radiation Oncology has been published as part of the Imaging in Medical Diagnosis and Therapy book series and is now available for purchase on Amazon.
2/22/19: Dr. Lei Xing was invited to give a talk on “Augmented Human Intelligence: Imaging in Treatment Planning” at the American Association of Medical Dosimetrists (AAMD) 2019 annual meeting in Anaheim, CA, which will be held June 16-20.
12/31/18: Dr. Lei Xing is organizing an NCI Workshop on Artificial Intelligence (AI) in Radiation Oncology and Medical Physics with Dr. Issam Al Naqa from the University of Michigan. The workshop will be held on an NIH campus, April 4-5, 2019, and attendance will be by invitation.
12/1/18: We are pleased to receive an NIH R01 Award for the development of dual modality CT and molecular imaging from the National Cancer Institute (NCI). Thanks for the support!
11/28/18: Dr. Lei Xing was invited to and served as a panelist for a session titled “Medical Imaging Analytics & AI: Technologies and Solutions for Better Healthcare Today and in the Future” at the Radiological Society of North America (RSNA) 2018 annual meeting in Chicago, IL, held November 25-30.
11/16/18: Dr. Lei Xing has been invited as an advisor to the first Radiomics, Radiogenomics, and AI working group for Japan, Korea, and Taiwan (JKT).
10/31/18: Dr. Hyunseok Seo placed first in the Liver Tumor Segmentation (LiTS) Challenge. His novel deep learning network emphasizes the high-frequency component during liver segmentation and prevents the duplication of the low-frequency component, mitigating a drawback of the conventional U-Net. Congratulations on this great achievement!
9/24/18: Dr. Lei Xing has been invited to present work from the lab on AI in Medicine and Deep Learning for Medical Imaging at the upcoming Computer Vision and Pattern Recognition (CVPR) 2019 annual conference in Long Beach, CA, which will be held June 19-25.
8/4/18: Dr. Lei Xing served as the Director of Scientific Program (Therapy Track) at the American Association of Physicists in Medicine (AAPM) 2018 annual meeting in Nashville, TN, held July 29th through August 4th.
8/2/18: Dr. Lei Xing moderated and participated as a panelist in a debate session about the role of artificial intelligence (AI) in medical physics and precision medicine at the American Association of Physicists in Medicine (AAPM) 2018 annual meeting in Nashville, TN.
7/1/18: Congratulations to Dr. Xianjin Dai who has been selected to receive the 2018 AAPM Research Seed Funding Grant for his proposal titled “Quantitative X-ray-induced shortwave infrared luminescence computed tomography in a single snapshot.” As the recipient of this award, he receives a grant of $25,000 from the AAPM Education and Research Fund.
6/1/18: We are excited to receive an NIH R01 Award for the development of novel radioluminescence dosimetry solutions for precision radiation therapy from the National Cancer Institute (NCI). Thanks for the support!
4/27/18: Congratulations to Wei Zhao, Bin Han, Yong Yang, Mark Buyyounouski, Steven Hancock, Hilary Bagshaw, and Lei Xing for winning the Basic/Translational Science Abstract Award for an abstract and oral presentation on using deep learning for prostate IGRT at the American Society for Radiation Oncology (ASTRO) 2018 annual meeting in San Antonio, TX, which will be held October 21-24.
1/24/18: Dr. Lei Xing was invited to and delivered a talk on the recent progress of AI in medicine at the Precision Medicine World Conference (PMWC) 2018.
12/1/17: Dr. Lei Xing served as a Scientific Program Committee Member at the Radiological Society of North America (RSNA) 2017 annual meeting in Chicago, IL, held November 25th through December 1st.
11/12/17: Dr. Lei Xing delivered a keynote talk on AI in radiation oncology at the Chinese Society of Therapeutic Radiation Oncology (CSTRO) 2017 annual meeting.