446 citations · 2.3k across the 135 of their papers we have counts for
17 papers · 1 filter
Real-time guidewire tracking and segmentation in intraoperative x-ray
Baochang Zhang, Mai Bui, Cheng Wang +3
During endovascular interventions, physicians have to perform accurate and immediate operations based on the available real-time information, such as the shape and position of guid…
AiAReSeg: Catheter Detection and Segmentation in Interventional Ultrasound using Transformers
Alex Ranne, Yordanka Velikova, Nassir Navab +1
To date, endovascular surgeries are performed using the golden standard of Fluoroscopy, which uses ionising radiation to visualise catheters and vasculature. Prolonged Fluoroscopic…
Ultra-NeRF: Neural Radiance Fields for Ultrasound Imaging
Magdalena Wysocki, Mohammad Farid Azampour, Christine Eilers +3
We present a physics-enhanced implicit neural representation (INR) for ultrasound (US) imaging that learns tissue properties from overlapping US sweeps. Our proposed method leverag…
CACTUSS: Common Anatomical CT-US Space for US examinations
Yordanka Velikova, Walter Simson, Mehrdad Salehi +3
Abdominal aortic aneurysm (AAA) is a vascular disease in which a section of the aorta enlarges, weakening its walls and potentially rupturing the vessel. Abdominal ultrasound has b…
Speckle2Speckle: Unsupervised Learning of Ultrasound Speckle Filtering Without Clean Data
Rüdiger Göbl, Christoph Hennersperger, Nassir Navab
In ultrasound imaging the appearance of homogeneous regions of tissue is subject to speckle, which for certain applications can make the detection of tissue irregularities difficul…
Spotlight on nerves: Portable multispectral optoacoustic imaging of peripheral nerve vascularization and morphology
Dominik Jüstel, Hedwig Irl, Florian Hinterwimmer +5
Various morphological and functional parameters of peripheral nerves and their vascular supply are indicative of pathological changes due to injury or disease. Based on recent impr…
Shape-Aware Masking for Inpainting in Medical Imaging
Yousef Yeganeh, Azade Farshad, Nassir Navab
Inpainting has recently been proposed as a successful deep learning technique for unsupervised medical image model discovery. The masks used for inpainting are generally independen…
Weakly-supervised Biomechanically-constrained CT/MRI Registration of the Spine
Bailiang Jian, Mohammad Farid Azampour, Francesca De Benetti +9
CT and MRI are two of the most informative modalities in spinal diagnostics and treatment planning. CT is useful when analysing bony structures, while MRI gives information about t…
Y-Net: A Spatiospectral Dual-Encoder Networkfor Medical Image Segmentation
Azade Farshad, Yousef Yeganeh, Peter Gehlbach +1
Automated segmentation of retinal optical coherence tomography (OCT) images has become an important recent direction in machine learning for medical applications. We hypothesize th…
Interactive Segmentation for COVID-19 Infection Quantification on Longitudinal CT scans
Michelle Xiao-Lin Foo, Seong Tae Kim, Magdalini Paschali +6
Consistent segmentation of COVID-19 patient's CT scans across multiple time points is essential to assess disease progression and response to therapy accurately. Existing automatic…
MetaMedSeg: Volumetric Meta-learning for Few-Shot Organ Segmentation
Anastasia Makarevich, Azade Farshad, Vasileios Belagiannis +1
The lack of sufficient annotated image data is a common issue in medical image segmentation. For some organs and densities, the annotation may be scarce, leading to poor model trai…
Sickle Cell Disease Severity Prediction from Percoll Gradient Images using Graph Convolutional Networks
Ario Sadafi, Asya Makhro, Leonid Livshits +4
Sickle cell disease (SCD) is a severe genetic hemoglobin disorder that results in premature destruction of red blood cells. Assessment of the severity of the disease is a challengi…
Deformation-Aware Robotic 3D Ultrasound
Zhongliang Jiang, Yue Zhou, Yuan Bi +3
Tissue deformation in ultrasound (US) imaging leads to geometrical errors when measuring tissues due to the pressure exerted by probes. Such deformation has an even larger effect o…
`Project & Excite' Modules for Segmentation of Volumetric Medical Scans
Anne-Marie Rickmann, Abhijit Guha Roy, Ignacio Sarasua +2
Fully Convolutional Neural Networks (F-CNNs) achieve state-of-the-art performance for image segmentation in medical imaging. Recently, squeeze and excitation (SE) modules and varia…
Image to Images Translation for Multi-Task Organ Segmentation and Bone Suppression in Chest X-Ray Radiography
Mohammad Eslami, Solale Tabarestani, Shadi Albarqouni +3
Chest X-ray radiography is one of the earliest medical imaging technologies and remains one of the most widely-used for diagnosis, screening, and treatment follow up of diseases re…
Multi-scale Microaneurysms Segmentation Using Embedding Triplet Loss
Mhd Hasan Sarhan, Shadi Albarqouni, Mehmet Yigitsoy +2
Deep learning techniques are recently being used in fundus image analysis and diabetic retinopathy detection. Microaneurysms are an important indicator of diabetic retinopathy prog…
Initialize globally before acting locally: Enabling Landmark-free 3D US to MRI Registration
Julia Rackerseder, Maximilian Baust, Rüdiger Göbl +2
Registration of partial-view 3D US volumes with MRI data is influenced by initialization. The standard of practice is using extrinsic or intrinsic landmarks, which can be very tedi…