Laura Heacock

According to our database, Laura Heacock authored at least 15 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

An Efficient Deep Neural Network to Classify Large 3D Images With Small Objects.

Jungkyu Park, Jakub Chledowski, Stanislaw Jastrzebski, 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

IEEE Trans. Medical Imaging, January, 2024

A training regime to learn unified representations from complementary breast imaging modalities.

Umang Sharma, Jungkyu Park, Laura Heacock, Sumit Chopra, Krzysztof J. Geras

CoRR, 2024

fastMRI Breast: A publicly available radial k-space dataset of breast dynamic contrast-enhanced MRI.

Eddy Solomon, Patricia M. Johnson, Zhengguo Tan, Radhika Tibrewala, Yvonne W. Lui, Florian Knoll, Linda Moy, Sungheon Gene Kim, Laura Heacock

CoRR, 2024

Understanding differences in applying DETR to natural and medical images.

Yanqi Xu, Yiqiu Shen, Carlos Fernandez-Granda, Laura Heacock, Krzysztof J. Geras

CoRR, 2024

2023

Leveraging Transformers to Improve Breast Cancer Classification and Risk Assessment with Multi-modal and Longitudinal Data.

Yiqiu Shen, Jungkyu Park, Frank Yeung, Eliana Goldberg, Laura Heacock, Farah Shamout, Krzysztof J. Geras

CoRR, 2023

BenchMD: A Benchmark for Modality-Agnostic Learning on Medical Images and Sensors.

Kathryn Wantlin, Chenwei Wu, Shih-Cheng Huang, Oishi Banerjee, Farah Dadabhoy, Veeral Vipin Mehta, Ryan Wonhee Han, Fang Cao, Raja R. Narayan, Errol Colak, Adewole S. Adamson, Laura Heacock, Geoffrey H. Tison, Alex Tamkin, Pranav Rajpurkar

CoRR, 2023

2022

3D-GMIC: an efficient deep neural network to find small objects in large 3D images.

Jungkyu Park, Jakub Chledowski, Stanislaw Jastrzebski, 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

CoRR, 2022

2021

Lessons from the first DBTex Challenge.

Jungkyu Park, Yoel Shoshan, Robert Martí, Pablo Gómez del Campo, Vadim Ratner, Daniel Khapun, Aviad Zlotnick, Ella Barkan, Flora Gilboa-Solomon, Jakub Chledowski, Jan Witowski, Alexandra Millet, Eric Kim, Alana Lewin, Kristine Pysarenko, Sardius Chen, Julia Goldberg, Shalin Patel, Anastasia Plaunova, Melanie Wegener, Stacey Wolfson, Jiyon Lee, Sana Hava, Sindhoora Murthy, Linda Du, Sushma Gaddam, Ujas Parikh, Laura Heacock, Linda Moy, Beatriu Reig, Michal Rosen-Zvi, Krzysztof J. Geras

Nat. Mach. Intell., 2021

An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization.

Yiqiu Shen, Nan Wu, Jason Phang, Jungkyu Park, Kangning Liu, Sudarshini Tyagi, Laura Heacock, Sungheon Gene Kim, Linda Moy, Kyunghyun Cho, Krzysztof J. Geras

Medical Image Anal., 2021

Reducing False-Positive Biopsies using Deep Neural Networks that Utilize both Local and Global Image Context of Screening Mammograms.

Nan Wu, Zhe Huang, Yiqiu Shen, Jungkyu Park, Jason Phang, Taro Makino, Sungheon Gene Kim, Kyunghyun Cho, Laura Heacock, Linda Moy, Krzysztof J. Geras

J. Digit. Imaging, 2021

A Simulation Pipeline to Generate Realistic Breast Images for Learning DCE-MRI Reconstruction.

Zhengnan Huang, Jonghyun Bae, Patricia M. Johnson, Terlika Sood, Laura Heacock, Justin Fogarty, Linda Moy, Sungheon Gene Kim, Florian Knoll

Proceedings of the Machine Learning for Medical Image Reconstruction, 2021

2020

Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening.

Nan Wu, Jason Phang, Jungkyu Park, Yiqiu Shen, Zhe Huang, Masha Zorin, Stanislaw Jastrzebski, Thibault Févry, Joe Katsnelson, Eric Kim, Stacey Wolfson, Ujas Parikh, Sushma Gaddam, Leng Leng Young Lin, Kara Ho, Joshua D. Weinstein, Beatriu Reig, Yiming Gao, Hildegard Toth, Kristine Pysarenko, Alana Lewin, Jiyon Lee, Krystal Airola, Eralda Mema, Stephanie Chung, Esther Hwang, Naziya Samreen, Sungheon Gene Kim, Laura Heacock, Linda Moy, Kyunghyun Cho, Krzysztof J. Geras

IEEE Trans. Medical Imaging, 2020

Differences between human and machine perception in medical diagnosis.

Taro Makino, Stanislaw Jastrzebski, Witold Oleszkiewicz, Celin Chacko, Robin Ehrenpreis, Naziya Samreen, Chloe Chhor, Eric Kim, Jiyon Lee, Kristine Pysarenko, Beatriu Reig, Hildegard Toth, Divya Awal, Linda Du, Alice Kim, James Park, Daniel K. Sodickson, Laura Heacock, Linda Moy, Kyunghyun Cho, Krzysztof J. Geras

CoRR, 2020

Reducing false-positive biopsies with deep neural networks that utilize local and global information in screening mammograms.

Nan Wu, Zhe Huang, Yiqiu Shen, Jungkyu Park, Jason Phang, Taro Makino, Sungheon Gene Kim, Kyunghyun Cho, Laura Heacock, Linda Moy, Krzysztof J. Geras

CoRR, 2020

Understanding the robustness of deep neural network classifiers for breast cancer screening.

Witold Oleszkiewicz, Taro Makino, Stanislaw Jastrzebski, Tomasz Trzcinski, Linda Moy, Kyunghyun Cho, Laura Heacock, Krzysztof J. Geras

CoRR, 2020