5 papers
Lesion Detection in CT with Frozen Self-Distilled Features: SALT, a Spatially Adaptive Label-Guided Temperature
Mahmut S. Gokmen, Evan W. Damron, Mitchell A. Klusty +3
Self-supervised pretraining objectives are spatially uniform: the teacher temperature and the per-patch loss weight are identical everywhere in the image, so a lesion a few patches…
DALE-CT: Depth-Aware Foundation Models for Computed Tomography
Evan W. Damron, Mahmut S. Gokmen, Mitchell A. Klusty +3
Recent breakthroughs in self-supervised learning (SSL), such as the Latent-Euclidean Joint-Embedding Predictive Architecture (LeJEPA), alongside successes in integrating visual enc…
Curriculum-Driven 3D CT Report Generation via Language-Free Visual Grafting and Zone-Constrained Compression
V. K. Cody Bumgardner, Mitchell A. Klusty, Mahmut S. Gokmen +1
Automated radiology report generation from 3D computed tomography (CT) volumes is challenging due to extreme sequence lengths, severe class imbalance, and the tendency of large lan…
Leveraging LLMs for Structured Data Extraction from Unstructured Patient Records
Mitchell A. Klusty, Elizabeth C. Solie, Caroline N. Leach +8
Manual chart review remains an extremely time-consuming and resource-intensive component of clinical research, requiring experts to extract often complex information from unstructu…
SmartState: An Automated Research Protocol Adherence System
Samuel E. Armstrong, Mitchell A. Klusty, Aaron D. Mullen +2
Developing and enforcing study protocols is crucial in medical research, especially as interactions with participants become more intricate. Traditional rules-based systems struggl…