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20162026
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61 citations · 334 across the 42 of their papers we have counts for

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Showing 2019Show all

8 papers · 1 filter

cs.CV2019

Active Learning for Segmentation Based on Bayesian Sample Queries

Firat Ozdemir, Zixuan Peng, Philipp Fuernstahl +2

Segmentation of anatomical structures is a fundamental image analysis task for many applications in the medical field. Deep learning methods have been shown to perform well, but fo…

physics.med-ph2019★ 46 cited

Speed-of-Sound Imaging using Diverging Waves

Richard Rau, Dieter Schweizer, Valery Vishnevskiy +1

Recent ultrasound imaging modalities based on ultrasound computed tomography indicate a huge potential to detect pathologies is tissue due to altered biomechanical properties. Espe…

eess.IV2019★ 48 cited

Ultrasound Aberration Correction based on Local Speed-of-Sound Map Estimation

Richard Rau, Dieter Schweizer, Valery Vishnevskiy +1

For beamforming ultrasound (US) signals, typically a spatially constant speed-of-sound (SoS) is assumed to calculate delays. As SoS in tissue may vary relatively largely, this appr…

eess.SP2019★ 11 cited

Attenuation Imaging with Pulse-Echo Ultrasound based on an Acoustic Reflector

Richard Rau, Ozan Unal, Dieter Schweizer +2

Ultrasound attenuation is caused by absorption and scattering in tissue and is thus a function of tissue composition, hence its imaging offers great potential for screening and dif…

eess.IV2019

Deep Variational Networks with Exponential Weighting for Learning Computed Tomography

Valery Vishnevskiy, Richard Rau, Orcun Goksel

Tomographic image reconstruction is relevant for many medical imaging modalities including X-ray, ultrasound (US) computed tomography (CT) and photoacoustics, for which the access…

cs.CV2019★ 61 cited

Weighted Mean Curvature

Yuanhao Gong, Orcun Goksel

In image processing tasks, spatial priors are essential for robust computations, regularization, algorithmic design and Bayesian inference. In this paper, we introduce weighted mea…

eess.IV2019

SCATGAN for Reconstruction of Ultrasound Scatterers Using Generative Adversarial Networks

Andrawes Al Bahou, Christine Tanner, Orcun Goksel

Computational simulation of ultrasound (US) echography is essential for training sonographers. Realistic simulation of US interaction with microscopic tissue structures is often mo…

cs.CV2019

Siamese Networks with Location Prior for Landmark Tracking in Liver Ultrasound Sequences

Alvaro Gomariz, Weiye Li, Ece Ozkan +2

Image-guided radiation therapy can benefit from accurate motion tracking by ultrasound imaging, in order to minimize treatment margins and radiate moving anatomical targets, e.g.,…