Search Results for author: Yanqi Xu

Found 2 papers, 1 papers with code

Understanding differences in applying DETR to natural and medical images

no code implementations • 27 May 2024 • Yanqi Xu, Yiqiu Shen, Carlos Fernandez-Granda, Laura Heacock, Krzysztof J. Geras

This study evaluates the applicability of these transformer-based design choices when applied to a screening mammography dataset that represents these distinct medical imaging data characteristics.

Medical Diagnosis object-detection +1

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An efficient deep neural network to find small objects in large 3D images

1 code implementation • 16 Oct 2022 • Jungkyu Park, Jakub Chłędowski, Stanisław Jastrzębski, Jan Witowski, Yanqi Xu, Linda Du, Sushma Gaddam, Eric Kim, Alana Lewin, Ujas Parikh, Anastasia Plaunova, Sardius Chen, Alexandra Millet, James Park, Kristine Pysarenko, Shalin Patel, Julia Goldberg, Melanie Wegener, Linda Moy, Laura Heacock, Beatriu Reig, Krzysztof J. Geras

On a dataset collected at NYU Langone Health, including 85, 526 patients with full-field 2D mammography (FFDM), synthetic 2D mammography, and 3D mammography, 3D-GMIC achieves an AUC of 0. 831 (95% CI: 0. 769-0. 887) in classifying breasts with malignant findings using 3D mammography.

Anatomy

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