1 citations · 3 across the 7 of their papers we have counts for
7 papers
CodeCytos: AI-assisted spatial molecular imaging analysis via code-augmented agent action space
Hung Q. Vo, Huy Q. Vo, Son T. Ly +6
Conventional tissue image analysis software provides foundational capabilities for cellular analysis, including segmentation, basic morphological feature extraction, and spatial or…
Self-Auditing Parameter-Efficient Fine-Tuning for Few-Shot 3D Medical Image Segmentation
Son Thai Ly, Hien V. Nguyen
Adapting foundation models to new clinical sites remains challenging in practice. Domain shift and scarce annotations must be handled by experts, yet many clinical groups do not ha…
Efficient Multi-scale Masked Autoencoders with Hybrid-Attention Mechanism for Breast Lesion Classification
Hung Q. Vo, Pengyu Yuan, Zheng Yin +5
Self-supervised learning (SSL) with Vision Transformers (ViT) has shown immense potential in medical image analysis. However, the quadratic complexity () of stand…
Revisiting Invariant Learning for Out-of-Domain Generalization on Multi-Site Mammogram Datasets
Hung Q. Vo, Samira Zare, Son T. Ly +6
Achieving health equity in Artificial Intelligence (AI) requires diagnostic models that maintain reliability across diverse populations. However, breast cancer screening systems fr…
Enhancing Parameter-Efficient Fine-Tuning of Vision Transformers through Frequency-Based Adaptation
Son Thai Ly, Hien V. Nguyen
Adapting vision transformer foundation models through parameter-efficient fine-tuning (PEFT) methods has become increasingly popular. These methods optimize a limited subset of par…
Anomaly Detection in Satellite Videos using Diffusion Models
Akash Awasthi, Son Ly, Jaer Nizam +7
The definition of anomaly detection is the identification of an unexpected event. Real-time detection of extreme events such as wildfires, cyclones, or floods using satellite data…
Multiplexed Immunofluorescence Brain Image Analysis Using Self-Supervised Dual-Loss Adaptive Masked Autoencoder
Son T. Ly, Bai Lin, Hung Q. Vo +3
Reliable large-scale cell detection and segmentation is the fundamental first step to understanding biological processes in the brain. The ability to phenotype cells at scale can a…