Hua-Chieh Shao won ASTRO Annual Meeting Travel Award
Hua-Chieh Shao, senior research associate, won the ASTRO Annual Meeting Travel Award in the physics category for his abstract title: "Deep Learning-Driven Real-Time Liver Tumor Localization via Optical Surface Imaging and Biomechanical Modeling."
Dr. Jiang, Visiting Professor at UCLA Health
Dr. Jiang participated in UCLA's Visiting Professor Series on August 26. His topic covered the clinical deployment of AI.
Dr. Jiang spoke at the Symposium at the University of Maryland
Dr. Jiang, along with Dr. Palta, a radiation oncologist at Duke, spoke at the University of Maryland School of Medicine's Symposium on Practical AI in Radiation Oncology on July 15.
Symposium at AAPM 2022
Dr. Jiang organized a symposium at AAPM 2022 in D.C. The topic was AI Clinical Translation: Opportunities and Pitfalls.
Anthony Wang, student intern, won the Inspire Award
Anthony Wang, student intern in the MAIA Lab, and his robotics team won the Inspire Award at the 2021-2022 FIRST World Championship. They were selected to represent Team USA at the 2022 FIRST Global Challenge in Geneva!
Dr. Jiang spoke at Mayo Clinic's first Proton Therapy Research Workshop
Dr. Jiang spoke at Mayo Clinic's first Proton Therapy Research Workshop about how deep learning can help meet the key requirements of dose calculations for proton therapy. His presentation and research were captured in "Physics World."Read the article
Drs. Wang and Sher awarded five-year NIH R01 grant
Jing Wang, Ph.D., and David Sher, M.D., MPH, MAIA faculty, were awarded a five-year NIH RO1 grant titled "A Multifaceted Radiomics Model to Predict Cervical Lymph Node Metastasis for Involved Nodal Radiation Therapy." The goal of their project is to develop, optimize, and test a multifaceted predictive model with both high sensitivity and specificity for lymph node metastasis to both maximize the efficacy and minimize the toxicity of involved nodal radiation therapy for head and neck cancer patients.
Dr. Ma successfully defended thesis
Biomedical Engineering graduate student, Lin Ma, defended his Ph.D. thesis “Efficient and intelligent radiotherapy planning and adaptation,” on April 13, 2022. He was mentored by Drs. Weiguo Lu and Xuejun Gu.
Drs. Jiang, Nguyen, and Zhang receive NIH-NCI R01 Grant
Dr. Steve Jiang, Vice Chair and Professor; Dr. Dan Nguyen, Assistant Professor; and Dr. You Zhang, Assistant Professor, received a five-year R01 grant totaling $2.98M to develop artificial intelligence-based quality assurance for online adaptive radiotherapy with MR linacs.
Steve Jiang, Ph.D., elected to AIMBE College of Fellows
Steve Jiang, Ph.D., was elected to the American Institute for Medical and Biological Engineering (AIMBE) College of Fellows Class of 2022. AIMBE Fellows, which are comprised of academia, industry, education, clinical practice, and government, represent only the top 2% of the most accomplished medical and biological engineers.Read the press release
Drs. Jiang, Jia and Nguyen receive NIH/NCI award
Dr. Steve Jiang, Vice Chair and Professor; Dr. Xun Jia, Professor; and Dr. Dan Nguyen, Assistant Professor, in collaboration with Varian Medical Systems Inc., received a $2.9M NIH Academic-Industrial Partnerships R01 grant to develop human-like AI agents for better and faster radiotherapy treatment planning. This is the second R01 grant received by three multiple principal investigators to develop AI tools for improving cancer radiotherapy.
MAIA Lab has two AI papers that are among the top 10 most cited publications
The MAIA Lab has two AI papers that are among the top 10 most cited publications of Physics in Medicine & Biology in 2020:
“3D radiotherapy dose prediction on head and neck cancer patients with a hierarchically densely connected U-net deep learning architecture,” by Drs. Dan Nguyen, Xun Jia, David Sher, Mu-Han Lin, Zohaib Iqbal, Hui Liu, and Steve Jiang
“An introduction to deep learning in medical physics: advantages, potential, and challenges,” by Drs. Chenyang Shen, Dan Nguyen, Zhiguo Zhou, Steve B Jiang, Bin Dong, and Xun Jia.
Dr. Xun Jia received $250,000 grant
Dr. Xun Jia, Professor of Radiation Oncology, in collaboration with Dr. Anke Henning, Professor of Radiology and Director of the Advanced Imaging Research Center, received a $250,000 grant to develop a new MRI scanner that will help keep radiation focus on tumors in radiotherapy. Instead of using MRI imaging conducted days or weeks ago, the MRI Dr. Jia is developing will attach to radiotherapy equipment and show MRI images immediately before or during radiation treatment. This will help see the tumor and target the radiation. The current state-of-the-art radiotherapy uses cone-beam computed tomography attached to radiotherapy equipment to guide radiation delivery. The new MRI scanner will enable better tumor visualizations without the concern of X-ray exposure in computed tomography.Read the full article
Roberts' Prize for best published paper in 2019
Xiao Liang, Liyuan Chen, Dan Nguyen, Zhiguo Zhou, Xuejun Gu, Ming Yang, Jing Wang, and Steve Jiang were just awarded the Roberts’ Prize for best paper published in the journal of Physics in Medicine and Biology for 2019. Their paper is entitled “Generating synthesized computed tomography (CT) from cone-beam computed tomography (CBCT) using CycleGAN for adaptive radiation therapy.”
The Roberts’ Prize, awarded annually, is named in honor of the first editor of Physics in Medicine and Biology—John Roberts.
Dr. Xun Jia invited to talk at the Department of Radiation Oncology at the University of Pennsylvania
Dr. Xun Jia gave a talk on "Medical Physics in the Deep-Learning Ear" at the Department of Radiation Oncology at the University of Pennsylvania on February 18, 2020.
Dr. Steve Jiang invited to talk at the Biomedical Engineering Department of UT Austin
Dr. Steve Jiang gave a talk on “Artificial Intelligence in Cancer Research” at the Biomedical Engineering Department of UT Austin on January 23-24, 2020.
Dr. Dan Nguyen invited to talk at Radiation Oncology of UTHSC San Antonio
Dr. Dan Nguyen gave a talk on “Artificial Intelligence in Radiation Therapy” at Radiation Oncology at UTHSC San Antonio on Thursday, January 16, 2020.
American Heart Association Grant
American Heart Association Grant: 19AMTG35120501
Award Type: American Heart Association and Amazon Web Services 4.0 Data Grant Portfolio: Artificial Intelligence and Machine Learning Training Grants
Title of Project: Title: Developing An Artificial Intelligence Based Radiotherapy Cardiotoxicity Analysis Platform
Total Cost: $100k
Date: 12/01/2019 - 11/30/2021
Principal Investigator: Erlei Zhang
Mentor: Xuejun Gu / Weiguo Lu
Dr. Xuejun Gu invited to talk at the Department of Radiation Oncology at Stanford University
Dr. Xuejun Gu gave a talk on “Advanced Radiotherapy From Automation to Intelligence” at the Department of Radiation Oncology at Stanford University on December 17, 2019.
UT Southwestern ranks eighth in NIH funding nationwide
According to an analysis at Emory, UT Southwestern ranks eighth in NIH funding nationwide among all radiation oncology departments. We further analyzed data for medical physics R01s or equivalent and we rank #1 with eight active R01s.
"Radiomics and Artificial Intelligence in Radiation Therapy" at the 2019 RRS Meeting
Xun Jia, Ph.D., Associate Professor and Jing Wang, Ph.D., Associate Professor present their work, "Radiomics and Artificial Intelligence in Radiation Therapy," at the 2019 Radiation Research Society Meeting!Check out more on Twitter
MICCAI-AIRT Workshop Call For Papers
MICCAI Workshop on Artificial Intelligence in Radiation Therapy 2019Read the full announcement
Congrats to Chenyang Shen on the ASTRO 2019 Annual Meeting Abstract Award!
Congrats to Chenyang Shen on receiving the ASTRO 2019 Annual Meeting Abstract Award for the abstract entitled "Automatic Treatment Planning in a Human-like manner: Operating Treatment Planning Systems by a Deep Reinforcement Learning based Virtual Treatment Planner."
Anjali Balagopal passed qualifier exam
Congratulations to Anjali for passing her qualifier examination! Anjali is a graduate student and valued member of MAIA Lab. Since starting her graduate studies with the Division of Medical Physics & Engineering in 2017, she has made great strides and contributions to radiation therapy with deep learning applications to image segmentation problems. We are so proud of her achievements and are elated to continue having her as a key team member.
UTSW x UTD Joint Workshop on Artificial Intelligence in MedicineSee the poster for the workshop
David A. Pistenmaa, M.D., Ph.D. Distinguished Lectureship in Radiation Oncology
We are honored to have Nigam Shah, MBBS, Ph.D., come from Stanford University to give a David A. Pistenmaa, M.D., Ph.D. Distinguished Lecture entitled "Personalizing Care via Machine Learning."Learn more about the Shah Lab
"Time Magazine" Article on AI in Medicine
"Time Magazine" released an article about the use of artificial intelligence in medicine. Steve Jiang, the Director of MAIA Laboratory, was one of the AI experts interviewed by TIME for the production of this article!Read the full article
Geoffrey Hinton, Yann LeCun, and Yoshua Bengio win the Turing Award
Turing Award by the Association for Computing Machinery (ACM) "for conceptual and engineering breakthroughs that have made deep neural networks a critical component of computing." The Turing Award is often referred to as the "Nobel Prize of Computing." Select technical accomplishments are, but not limited to, the following:
Geoffrey Hinton: Backpropagation, Boltzmann machines, and improvements to convolutional neural networks
Yann LeCun: Convolutional neural networks, improving backpropagation algorithms, and broadening the vision of neural networks
Yoshua Bengio: Probabilistic models of sequences, high-dimensional word embeddings and attention, and generative deep learning
Using Machine Learning for Smartphone-Based Health Sensing
Lecture by Dr. Eric Larson
March 7, 2019, 4 p.m.
NC8.212 Conference Room
The Impact of Artificial Intelligence on Radiation Therapy
A discussion with Steve Jiang, Ph.D., at AAPM 2018 about how AI will change treatment planning, radiation oncology and medical imaging.Watch the full video