1 citations · 1 across the 4 of their papers we have counts for
4 papers
A Workflow to Efficiently Generate Dense Tissue Ground Truth Masks for Digital Breast Tomosynthesis
Tamerlan Mustafaev, Oleg Kruglov, Margarita Zuley +6
Digital breast tomosynthesis (DBT) is now the standard of care for breast cancer screening in the USA. Accurate segmentation of fibroglandular tissue in DBT images is essential for…
Toward explainable AI approaches for breast imaging: adapting foundation models to diverse populations
Guilherme J. Cavalcante, José Gabriel A. Moreira, Gabriel A. B. do Nascimento +10
Foundation models hold promise for specialized medical imaging tasks, though their effectiveness in breast imaging remains underexplored. This study leverages BiomedCLIP as a found…
Toward a robust lesion detection model in breast DCE-MRI: adapting foundation models to high-risk women
Gabriel A. B. do Nascimento, Vincent Dong, Guilherme J. Cavalcante +9
Accurate breast MRI lesion detection is critical for early cancer diagnosis, especially in high-risk populations. We present a classification pipeline that adapts a pretrained foun…
Convolutional Neural Network Model Observers Discount Signal-like Anatomical Structures During Search in Virtual Digital Breast Tomosynthesis Phantoms
Aditya Jonnalagadda, Bruno B. Barufaldi, Andrew D. A. Maidment +3
Model observers are computational tools to evaluate and optimize task-based medical image quality. Linear model observers, such as the Channelized Hotelling Observer (CHO), predict…