Computational Enhancement of Molecularly Targeted Contrast-Enhanced Ultrasound: Application to Human Breast Tumor Imaging

no code implementations • 22 Jun 2020 • Andrew A. Berlin, Mon Young, Ahmed El Kaffas, Sam Gambhir, Amelie Lutz, Maria Luigia Storto, Juergen Willmann

Molecularly targeted contrast enhanced ultrasound (mCEUS) is a clinically promising approach for early cancer detection through targeted imaging of VEGFR2 (KDR) receptors.

A 3D Probabilistic Deep Learning System for Detection and Diagnosis of Lung Cancer Using Low-Dose CT Scans

no code implementations • 8 Feb 2019 • Onur Ozdemir, Rebecca L. Russell, Andrew A. Berlin

We introduce a new computer aided detection and diagnosis system for lung cancer screening with low-dose CT scans that produces meaningful probability assessments.

Decision Making General Classification +2

Propagating Uncertainty in Multi-Stage Bayesian Convolutional Neural Networks with Application to Pulmonary Nodule Detection

no code implementations • 1 Dec 2017 • Onur Ozdemir, Benjamin Woodward, Andrew A. Berlin

Motivated by the problem of computer-aided detection (CAD) of pulmonary nodules, we introduce methods to propagate and fuse uncertainty information in a multi-stage Bayesian convolutional neural network (CNN) architecture.