89 citations · 97 across the 6 of their papers we have counts for
7 papers · 1 filter
Augmented Networks for Faster Brain Metastases Detection in T1-Weighted Contrast-Enhanced 3D MRI
Engin Dikici, Xuan V. Nguyen, Matthew Bigelow +1
Early detection of brain metastases (BM) is one of the determining factors for the successful treatment of patients with cancer; however, the accurate detection of small BM lesions…
Deep Learning-Based Automatic Detection of Poorly Positioned Mammograms to Minimize Patient Return Visits for Repeat Imaging: A Real-World Application
Vikash Gupta, Clayton Taylor, Sarah Bonnet +5
Screening mammograms are a routine imaging exam performed to detect breast cancer in its early stages to reduce morbidity and mortality attributed to this disease. In order to maxi…
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
Richard D. White, Barbaros S. Erdal, Mutlu Demirer +9
Coronary Computed Tomography Angiography (CCTA) evaluation of chest-pain patients in an Emergency Department (ED) is considered appropriate. While a negative CCTA interpretation su…
Constrained Generative Adversarial Network Ensembles for Sharable Synthetic Data Generation
Engin Dikici, Luciano M. Prevedello, Matthew Bigelow +2
The sharing of medical imaging datasets between institutions, and even inside the same institution, is limited by various regulations/legal barriers. Although these limitations are…
Integrating AI into Radiology workflow: Levels of research, production, and feedback maturity
Engin Dikici, Matthew Bigelow, Luciano M. Prevedello +2
This report represents a roadmap for integrating Artificial Intelligence (AI)-based image analysis algorithms into existing Radiology workflows such that: (1) radiologists can sign…
Are Quantitative Features of Lung Nodules Reproducible at Different CT Acquisition and Reconstruction Parameters?
Barbaros S. Erdal, Mutlu Demirer, Chiemezie C. Amadi +9
Consistency and duplicability in Computed Tomography (CT) output is essential to quantitative imaging for lung cancer detection and monitoring. This study of CT-detected lung nodul…