452 citations · 495 across the 13 of their papers we have counts for
9 papers · 1 filter
A multi-reconstruction study of breast density estimation using Deep Learning
Vikash Gupta, Mutlu Demirer, Robert W. Maxwell +2
Breast density estimation is one of the key tasks in recognizing individuals predisposed to breast cancer. It is often challenging because of low contrast and fluctuations in mammo…
Cascading Neural Network Methodology for Artificial Intelligence-Assisted Radiographic Detection and Classification of Lead-Less Implanted Electronic Devices within the Chest
Mutlu Demirer, Richard D. White, Vikash Gupta +2
Background & Purpose: Chest X-Ray (CXR) use in pre-MRI safety screening for Lead-Less Implanted Electronic Devices (LLIEDs), easily overlooked or misidentified on a frontal view (o…
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…
Democratizing Artificial Intelligence in Healthcare: A Study of Model Development Across Two Institutions Incorporating Transfer Learning
Vikash Gupta1, Holger Roth, Varun Buch3 +9
The training of deep learning models typically requires extensive data, which are not readily available as large well-curated medical-image datasets for development of artificial i…
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…
Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI
Engin Dikici, John L. Ryu, Mutlu Demirer +5
Brain Metastases (BM) complicate 20-40% of cancer cases. BM lesions can present as punctate (1 mm) foci, requiring high-precision Magnetic Resonance Imaging (MRI) in order to preve…