4 papers
From Heads to Neurons: Causal Attribution and Steering in Multi-Task Vision-Language Models
Qidong Wang, Junjie Hu, Ming Jiang
Recent work has increasingly explored neuron-level interpretation in vision-language models (VLMs) to identify neurons critical to final predictions. However, existing neuron analy…
Opportunistic Promptable Segmentation: Leveraging Routine Radiological Annotations to Guide 3D CT Lesion Segmentation
Samuel Church, Joshua D. Warner, Danyal Maqbool +4
The development of machine learning models for CT imaging depends on the availability of large, high-quality, and diverse annotated datasets. Although large volumes of CT images an…
PETAR: Localized Findings Generation with Mask-Aware Vision-Language Modeling for PET Automated Reporting
Danyal Maqbool, Changhee Lee, Zachary Huemann +11
Generating automated reports for 3D positron emission tomography (PET) is an important and challenging task in medical imaging. PET plays a vital role in oncology, but automating r…
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…