122 citations · 175 across the 16 of their papers we have counts for
20 papers
Point Tracking in Surgery--The 2025 Surgical Tattoos in Infrared Challenge (STIRC2025)
Adam Schmidt, Mert Asim Karaoglu, Zijian Wu +32
Point tracking in surgery is crucial to enable applications in downstream tasks such as segmentation, 3D reconstruction, virtual tissue landmarking, autonomous probe-based scanning…
Automated Estimation of Anatomical Risk Metrics for Endoscopic Sinus Surgery Using Deep Learning
Konrad Reuter, Lennart Thaysen, Bilkay Doruk +7
Endoscopic sinus surgery requires careful preoperative assessment of the skull base anatomy to minimize risks such as cerebrospinal fluid leakage. Anatomical risk scores like the K…
Deep Learning for High Speed Optical Coherence Elastography with a Fiber Scanning Endoscope
Maximilian Neidhardt, Sarah Latus, Tim Eixmann +2
Tissue stiffness is related to soft tissue pathologies and can be assessed through palpation or via clinical imaging systems, e.g., ultrasound or magnetic resonance imaging. Typica…
Tracking Any Point Methods for Markerless 3D Tissue Tracking in Endoscopic Stereo Images
Konrad Reuter, Suresh Guttikonda, Sarah Latus +4
Minimally invasive surgery presents challenges such as dynamic tissue motion and a limited field of view. Accurate tissue tracking has the potential to support surgical guidance, i…
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 Mobile Robotic Approach to Autonomous Surface Scanning in Legal Medicine
Sarah Grube, Sarah Latus, Martin Fischer +4
Purpose: Comprehensive legal medicine documentation includes both an internal but also an external examination of the corpse. Typically, this documentation is conducted manually du…
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…
Collaborative Robotic Biopsy with Trajectory Guidance and Needle Tip Force Feedback
Robin Mieling, Maximilian Neidhardt, Sarah Latus +6
The diagnostic value of biopsies is highly dependent on the placement of needles. Robotic trajectory guidance has been shown to improve needle positioning, but feedback for real-ti…
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…
In-Vitro MPI-Guided IVOCT Catheter Tracking in Real Time for Motion Artifact Compensation
Florian Griese, Sarah Latus, Matthias Schlüter +4
Purpose: Using 4D magnetic particle imaging (MPI), intravascular optical coherence tomography (IVOCT) catheters are tracked in real time in order to compensate for image artifacts…
Bimodal intravascular volumetric imaging combining OCT and MPI
Sarah Latus, Florian Griese, Matthias Schlüter +6
Intravascular optical coherence tomography (IVOCT) is a catheter based image modality allowing for high resolution imaging of vessels. It is based on a fast sequential acquisition…
Towards Automatic Lesion Classification in the Upper Aerodigestive Tract Using OCT and Deep Transfer Learning Methods
Nils Gessert, Matthias Schlüter, Sarah Latus +3
Early detection of cancer is crucial for treatment and overall patient survival. In the upper aerodigestive tract (UADT) the gold standard for identification of malignant tissue is…
Endoscopic vs. volumetric OCT imaging of mastoid bone structure for pose estimation in minimally invasive cochlear implant surgery
Max-Heinrich Laves, Sarah Latus, Jan Bergmeier +3
Purpose: The facial recess is a delicate structure that must be protected in minimally invasive cochlear implant surgery. Current research estimates the drill trajectory by using e…
Bioresorbable Scaffold Visualization in IVOCT Images Using CNNs and Weakly Supervised Localization
Nils Gessert, Sarah Latus, Youssef S. Abdelwahed +3
Bioresorbable scaffolds have become a popular choice for treatment of coronary heart disease, replacing traditional metal stents. Often, intravascular optical coherence tomography…
Automatic Plaque Detection in IVOCT Pullbacks Using Convolutional Neural Networks
Nils Gessert, Matthias Lutz, Markus Heyder +4
Coronary heart disease is a common cause of death despite being preventable. To treat the underlying plaque deposits in the arterial walls, intravascular optical coherence tomograp…
Adversarial Training for Patient-Independent Feature Learning with IVOCT Data for Plaque Classification
Nils Gessert, Markus Heyder, Sarah Latus +4
Deep learning methods have shown impressive results for a variety of medical problems over the last few years. However, datasets tend to be small due to time-consuming annotation.…
Plaque Classification in Coronary Arteries from IVOCT Images Using Convolutional Neural Networks and Transfer Learning
Nils Gessert, Markus Heyder, Sarah Latus +2
Advanced atherosclerosis in the coronary arteries is one of the leading causes of deaths worldwide while being preventable and treatable. In order to image atherosclerotic lesions…