output
20182024
most citedIterative annotation to ease neural network training: Specialized machine learning in medical image analysis

154 citations

6 papers

eess.IV2024★ 4 cited

Deep Harmonic Finesse: Signal Separation in Wearable Systems with Limited Data

Mahya Saffarpour, Kourosh Vali, Weitai Qian +3

We present a method, referred to as Deep Harmonic Finesse (DHF), for separation of non-stationary quasi-periodic signals when limited data is available. The problem frequently aris…

physics.med-ph2020★ 8 cited

Multiparametric Cardiac 18F-FDG PET: Pilot Comparison of FDG Delivery Rate with 82Rb Myocardial Blood Flow

Yang Zuo, Javier E. Lopez, Thomas W. Smith +4

Myocardial blood flow (MBF) and flow reserve are usually quantified in the clinic with positron emission tomography (PET) using a perfusion-specific radiotracer (e.g. 82Rbchloride)…

physics.med-ph2020★ 13 cited

Modified Kernel MLAA Using Autoencoder for PET-enabled Dual-Energy CT

Siqi Li, Guobao Wang

Combined use of PET and dual-energy CT provides complementary information for multi-parametric imaging. PETenabled dual-energy CT combines a low-energy x-ray CT image with a high-e…

physics.med-ph2020★ 21 cited

Multiparametric Cardiac 18F-FDG PET in Humans: Kinetic Model Selection and Identifiability Analysis

Yang Zuo, Ramsey D. Badawi, Cameron C. Foster +3

Cardiac 18F-FDG PET has been used in clinics to assess myocardial glucose metabolism. Its ability for imaging myocardial glucose transport, however, has rarely been exploited in cl…

cs.LG2019★ 4 cited

Improving Mechanical Ventilator Clinical Decision Support Systems with A Machine Learning Classifier for Determining Ventilator Mode

Gregory B. Rehm, Brooks T. Kuhn, Jimmy Nguyen +3

Clinical decision support systems (CDSS) will play an in-creasing role in improving the quality of medical care for critically ill patients. However, due to limitations in current…

eess.IV2018★ 154 cited

Iterative annotation to ease neural network training: Specialized machine learning in medical image analysis

Brendon Lutnick, Brandon Ginley, Darshana Govind +7

Neural networks promise to bring robust, quantitative analysis to medical fields, but adoption is limited by the technicalities of training these networks. To address this translat…