5 papers
Dataset-Specific Encoding of Image Content Underlies Cross-Dataset Failure in Brain MRI Foundation Models
Minh Sao Khue Luu, Bair N. Tuchinov
Frozen features of brain MRI foundation models lose accuracy on new datasets, a failure usually blamed on the features encoding where each scan came from. We show that the failure…
Component-Adaptive and Lesion-Level Supervision for Improved Small Structure Segmentation in Brain MRI
Minh Sao Khue Luu, Evgeniy N. Pavlovskiy, Bair N. Tuchinov
Small lesions in brain MRI are hard to segment because they occupy a tiny fraction of the volume and are dominated by background and larger lesions during voxel-wise optimization,…
A Foundation Model for Brain MRI with Dynamic Modality Integration
Minh Sao Khue Luu, Bair N. Tuchinov
We present a foundation model for brain MRI that can work with different combinations of imaging sequences. The model uses one encoder with learnable modality embeddings, condition…
A Structured Review and Quantitative Profiling of Public Brain MRI Datasets for Foundation Model Development
Minh Sao Khue Luu, Margaret V. Benedichuk, Ekaterina I. Roppert +2
The development of foundation models for brain MRI depends critically on the scale, diversity, and consistency of available data, yet systematic assessments of these factors remain…
ToolBrain: A Flexible Reinforcement Learning Framework for Agentic Tools
Quy Minh Le, Minh Sao Khue Luu, Khanh-Tung Tran +5
Effective tool use is essential for agentic AI, yet training agents to utilize tools remains challenging due to manually designed rewards, limited training data, and poor multi-too…