30 citations · 34 across the 4 of their papers we have counts for
4 papers
Vision-Language Modeling in PET/CT for Visual Grounding of Positive Findings
Zachary Huemann, Samuel Church, Joshua D. Warner +7
Vision-language models can connect the text description of an object to its specific location in an image through visual grounding. This has potential applications in enhanced radi…
Automatic Quantification of Serial PET/CT Images for Pediatric Hodgkin Lymphoma Patients Using a Longitudinally-Aware Segmentation Network
Xin Tie, Muheon Shin, Changhee Lee +10
: Automatic quantification of longitudinal changes in PET scans for lymphoma patients has proven challenging, as residual disease in interim-therapy scans is ofte…
Automatic Personalized Impression Generation for PET Reports Using Large Language Models
Xin Tie, Muheon Shin, Ali Pirasteh +8
In this study, we aimed to determine if fine-tuned large language models (LLMs) can generate accurate, personalized impressions for whole-body PET reports. Twelve language models w…
ConTEXTual Net: A Multimodal Vision-Language Model for Segmentation of Pneumothorax
Zachary Huemann, Xin Tie, Junjie Hu +1
Radiology narrative reports often describe characteristics of a patient's disease, including its location, size, and shape. Motivated by the recent success of multimodal learning,…