Deformable image registration is a fundamental step for medical image analysis. Recently
transformers have been used for registration and outperformed Convolutional Neural …

Establishing dense anatomical correspondence across distinct imaging modalities is a
foundational yet challenging procedure for numerous medical image analysis studies and …

International benchmarking competitions have become fundamental for the comparative
performance assessment of image analysis methods. However, little attention has been …

The field of surgical computer vision has undergone considerable breakthroughs in recent
years with the rising popularity of deep neural network-based methods. However, standard …

Cine magnetic resonance imaging (MRI) is the current gold standard for the assessment of
cardiac anatomy and function. However, it typically only acquires a set of two-dimensional …

By focusing on metabolic and morphological tissue properties respectively,
FluoroDeoxyGlucose (FDG)-Positron Emission Tomography (PET) and Computed …

Reconstructing the 3D articulated shape of an animal from a single in-the-wild image is a
challenging task. We propose LEPARD, a learning-based framework that discovers …

The ability to automatically detect and track surgical instruments in endoscopic videos can
enable transformational interventions. Assessing surgical performance and efficiency …

Survival prediction is crucial for cancer patients as it provides early prognostic information
for treatment planning. Recently, deep survival models based on deep learning and medical …

Recent advancements in surgical computer vision have been driven by vision-only models,
which lack language semantics, relying on manually annotated videos to predict fixed object …