122 citations · 175 across the 16 of their papers we have counts for
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Do We Need Pre-Processing for Deep Learning Based Ultrasound Shear Wave Elastography?
Sarah Grube, Sören Grünhagen, Sarah Latus +2
Estimating the elasticity of soft tissue can provide useful information for various diagnostic applications. Ultrasound shear wave elastography offers a non-invasive approach. Howe…
A Modified da Vinci Surgical Instrument for OCE based Elasticity Estimation with Deep Learning
Maximilian Neidhardt, Robin Mieling, Sarah Latus +3
Robot-assisted surgery has advantages compared to conventional laparoscopic procedures, e.g., precise movement of the surgical instruments, improved dexterity, and high-resolution…
Tissue Classification During Needle Insertion Using Self-Supervised Contrastive Learning and Optical Coherence Tomography
Debayan Bhattacharya, Sarah Latus, Finn Behrendt +4
Needle positioning is essential for various medical applications such as epidural anaesthesia. Physicians rely on their instincts while navigating the needle in epidural spaces. Th…
Ultrasound Shear Wave Elasticity Imaging with Spatio-Temporal Deep Learning
Maximilian Neidhardt, Marcel Bengs, Sarah Latus +4
Ultrasound shear wave elasticity imaging is a valuable tool for quantifying the elastic properties of tissue. Typically, the shear wave velocity is derived and mapped to an elastic…
A novel optical needle probe for deep learning-based tissue elasticity characterization
Robin Mieling, Johanna Sprenger, Sarah Latus +2
The distinction between malignant and benign tumors is essential to the treatment of cancer. The tissue's elasticity can be used as an indicator for the required tissue characteriz…
Deep Learning for High Speed Optical Coherence Elastography
Maximilian Neidhardt, Marcel Bengs, Sarah Latus +3
Mechanical properties of tissue provide valuable information for identifying lesions. One approach to obtain quantitative estimates of elastic properties is shear wave elastography…