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Rosen, David P

0000-0001-5082-3409

Mayo Clinic

Mayo Clinic

Citations 5

BWS-Net: An Optimal Deep Learning Architecture for the Anterior Bladder Wall Segmentation Using Ultrasound Imaging
Saini, Manali , Jiang, Yifei, Gangopadhyay, Tuhinangshu , Rosen, David , Fatemi, Mostafa , Fatemi, Mostafa , Rosen, David P , Alizad, Azra

IEEE Journal of Biomedical and Health Informatics | March 19, 2026 | Volume: 30 | Issue: 10 | Pages: 8774-8786

10.1109/jbhi.2026.3675965 Get It

Pulsed Vibro-Acoustic Analysis Technique for Monitoring Bone Health in Preterm Infants: A Pilot Study
Chaudhary, Pradeep Kumar , Rosen, David , Larson, Nicholas B. , Brumbaugh, Jane E. , Fatemi, Mostafa , Gu, Juanjuan, Rosen, David P , Fatemi, Mostafa , Larson, Nicholas B , Brumbaugh, Jane E , Gu, Juanjuan , Alizad, Azra

IEEE Access | August 2, 2024 | Volume: 12 | Issue: No issue available | Pages: 106707-106719

10.1109/access.2024.3437375 Get It

A Force-Matched Approach to Large-Strain Nonlinearity in Elasticity Imaging for Breast Lesion Characterization
Rosen, David , Nayak, Rohit , Wang, Yuqi , Gendin, Daniel , Larson, Nicholas B. , Fazzio, Robert T. , Oberai, Assad A. , Hall, Timothy J. , Barbone, Paul E. , Hall, Timothy J , Rosen, David P , Larson, Nicholas B , Alizad, Azra , Fatemi, Mostafa

IEEE Transactions on Biomedical Engineering | August 17, 2023 | Volume: 71 | Issue: 1 | Pages: 367-374

10.1109/tbme.2023.3305986 Get It

Non-Invasive Measurement of the Internal Pressure of a Pressurized Biological Compartment Using Lamb Waves
Rosen, David , Larson, Nicholas B. , Fatemi, Mostafa , Fatemi, Mostafa , Rosen, David P , Larson, Nicholas B , Alizad, Azra

IEEE Transactions on Biomedical Engineering | November 22, 2021 | Volume: 69 | Issue: 6 | Pages: 1860-1869

10.1109/tbme.2021.3129652 Get It

Detrusor overactivity assessment using ultrasound bladder vibrometry
Rosen, David , Husmann, Douglas A. , Mynderse, Lance A. , Kelly, Troy F, Fatemi, Mostafa , Rosen, David P , Alizad, Azra , Fatemi, Mostafa , Alizad, Azra

Physiological Measurement | October 1, 2021 | Volume: 42 | Issue: 10 | Pages: 105012

10.1088/1361-6579/ac2c5c Get It

Abstract Objective . Detrusor overactivity (DO) is a urodynamic observation characterized by fluctuations in detrusor pressure ( P det ) of the bladder. Although detecting DO is important for the management of bladder symptoms, the invasive nature of urodynamic studies (UDS) makes it a source of discomfort and morbidity for patients. Ultrasound bladder vibrometry (UBV) could provide a direct and noninvasive means of detecting DO, due to its sensitivity to changes in elasticity and load in the bladder wall. In this study, we investigated the feasibility and applying UBV toward detecting DO. Approach . UBV and urodynamic study (UDS) measurements were collected in 76 neurogenic bladder patients (23 with DO). Timestamped group velocity squared ( c g 2 ) data series were collected from UBV measurements. Concurrent P det data series were identically analyzed for comparison and validation. A processing approach is developed to separate transient fluctuations in the data series from the larger trend of the data and a DO index is proposed for characterizing the transient peaks observed in the data. Main Results. Applying the DO index as a classifier for DO produced sensitivities and specificities of 0.70 and 0.75 for c g 2 data series and 0.70 and 0.83 for P det data series respectively. Significance . It was found that DO can be feasibly detected from data series of timestamped UBV measurements. Collectively, these initial results are promising, and further refinement to the UBV measurement process is likely to improve and clarify its capabilities for noninvasive detection of DO.