Matthew T. Bigelow

Orcid: 0000-0002-4733-5911

According to our database1, Matthew T. Bigelow authored at least 11 papers between 2019 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2023
Detecting and Characterizing Inferior Vena Cava Filters on Abdominal Computed Tomography with Data-Driven Computational Frameworks.
J. Digit. Imaging, December, 2023

2022
Augmented networks for faster brain metastases detection in T1-weighted contrast-enhanced 3D MRI.
Comput. Medical Imaging Graph., 2022

2021
Artificial Intelligence to Assist in Exclusion of Coronary Atherosclerosis During CCTA Evaluation of Chest Pain in the Emergency Department: Preparing an Application for Real-world Use.
J. Digit. Imaging, 2021

Advancing Brain Metastases Detection in T1-Weighted Contrast-Enhanced 3D MRI using Noisy Student-based Training.
CoRR, 2021

2020
Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI.
IEEE J. Biomed. Health Informatics, 2020

Performance of a Deep Neural Network Algorithm Based on a Small Medical Image Dataset: Incremental Impact of 3D-to-2D Reformation Combined with Novel Data Augmentation, Photometric Conversion, or Transfer Learning.
J. Digit. Imaging, 2020

Predicting Rate of Cognitive Decline at Baseline Using a Deep Neural Network with Multidata Analysis.
CoRR, 2020

Automated coronary artery atherosclerosis detection and weakly supervised localization on coronary CT angiography with a deep 3-dimensional convolutional neural network.
Comput. Medical Imaging Graph., 2020

Using Transfer Learning and Class Activation Maps Supporting Detection and Localization of Femoral Fractures on Anteroposterior Radiographs.
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

2019
Coronary Artery Classification and Weakly Supervised Abnormality Localization on Coronary CT Angiography with 3-Dimensional Convolutional Neural Networks.
CoRR, 2019

Are Quantitative Features of Lung Nodules Reproducible at Different CT Acquisition and Reconstruction Parameters?
CoRR, 2019


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