__________________
We recently released a multi-center gastrointestinal tract dataset with 8K images from 27 classes. We hope that it opens new possibilities in GI endoscopy & colonoscopy research.
Dataset link: https://osf.io/84e7f/
paper link: https://arxiv.org/pdf/2307.08140.pdf
The annual Research Day at Northwestern is a campuswide event to promote faculty and trainee development by sharing exciting research and conversations with colleagues. This year we have 11 posters to present:
Congrats!
At the International Symposium on Current Advances in Medical Imaging Techniques, Prof. Bagci highlighted our recent findings from several high-risk, high-gain projects, funded by NIH.
Two papers got accepted by Winter Conference on Applications of Computer Vision (WACV2024).
WACV is a premier venue for computer vision and machine learning research. Read more details at:
Our lab MHIL was recently featured in Northwestern Medicine’s newsletter, highlighting progress in AI for Pancreatic Diseases. Read more details at:
Congrats to Sanaz Karimijafarbigloo and Reza Azad for this great work!
Paper #1: A Privacy-Preserving Walk in the Latent Space of Generative Models for Medical Applications.
First author: Matteo Pennisi
Paper #2: Laplacian-Former: Overcoming the Limitations of Vision Transformers in Local Texture Detection. (link to be published)
First author: Reza Azad.
arXiv:2309.00108 (2023).
Paper #3: Radiomics boosts deep learning in Pancreas IPMN Classification. (link to be published)
First author: Lanhong Yao
http://arxiv.org/abs/2309.05857
We’re proud to announce that Dr. Bagci represented our lab as a panelist in the ML4MHD (Machine Learning for Multimodal Healthcare Data) session at ICML 2023. Chaired by Dr. Pallavi Tiwari, the panel also featured esteemed experts like Dr. Daniel Rueckert and Dr. Xiaoxiao Li.
GastroVision: A Multi-class Endoscopy Image Dataset for Computer Aided Gastrointestinal Disease Detection.
by Debesh J. et al.
We were honored to host Dr. Bo Zhou, a distinguished final-year Ph.D. Candidate from the Department of Biomedical Engineering at Yale University, for a captivating seminar on AI applications in Multi-modal Nuclear Medicine (NM) Imaging. Dr. Zhou’s extensive research addresses the critical challenges of high radiation doses, image quality degradation, and prolonged acquisition times in imaging modalities like PET-CT and PET-MRI. His innovative deep-learning strategies aim to enhance the safety, efficiency, and quality of these imaging techniques, potentially elevating their clinical utility. Dr. Zhou, with a commendable academic and research background marked by awards and over 50 publications, shared insights that promise to redefine the boundaries of medical imaging. Explore more about Dr. Zhou’s work on his homepage.
Congratulations to our visiting student, Harmony, on her stellar presentation at Northwestern University! Her insightful study on “Pancreatic Cancer: Decoding Risks with Duct Diameter, Cyst Size, and Abdominal Circumference” showcased an in-depth analysis and a fresh perspective, further contributing to the evolving discourse on pancreatic cancer research. We’re proud of her achievements and commend her dedication to this vital field of study.
On July 21st, our lab resonated with inspiration and forward-thinking, thanks to our remarkable women scientists at the forefront of medical imaging research. Their tales of dedication, challenges, and groundbreaking discoveries were the highlight of this special gathering.
Read More >>
We are honored to welcome Dr. Mubarak Shah, a renowned professor from the University of Central Florida (UCF), to our lab. During his visit, we will share our latest research findings and engage in fruitful discussions to explore potential collaborations and future directions in our respective fields.
We are excited to announce the acceptance of our MIDL 2023 paper for publication! Stay tuned for more details on the study.
The new book co-edited by Prof. Bagci, “AI in Clinical Medicine: A Practical Guide for Healthcare Professionals,” is now available for purchase in both physical and electronic formats from Wiley. Get your copy at :
Prof. Bagci will be sharing expertise at the MICCAI 2023 workshop focusing on medical image learning with limited and noisy data.
A highly-anticipated keynote speech is set to be given at the upcoming IEEE ICECCME 2023 conference. It will focus on the failures of deep learning / AI algorithms and propose several approaches to increase robustness of AI powered medical imaging systems.
On March 16, 2023, an insightful talk was delivered at the University of Pennsylvania’s Radiology department, delving into the diagnosis and risk stratification of pancreatic cysts using explainable AI techniques.
On February 15, 2023, an invited talk was given at the University of Wisconsin Madison’s BME department, highlighting the significance of trustworthy AI in imaging-based diagnosis.
An improved method of performing object segmentation and classification that reduces the memory required to perform these tasks, while increasing predictive accuracy.
Bagci lab received a grant funded by RSNA Emerging Issues – Long-Term COVID Effects EILTC2208, entitled “PASC Pulmonary Fibrosis Prediction with Deep Learning and Multimodal Data.”
Bagci Lab 2023, Department of Radiology, Feinberg School of Medicine, Northwestern University.
