Radiology

Weakly-supervised localization and classification of proximal femur fractures

Semi-supervised deep learning for fully convolutional networks

Deep learning usually requires large amounts of labeled training data, but annotating data is costly and tedious. The framework of semi-supervised learning provides the means to use both labeled data and arbitrary amounts of unlabeled data for …

X-ray in-depth decomposition: Revealing the latent structures

X-ray is the most readily available imaging modality and has a broad range of applications that spans from diagnosis to intra-operative guidance in cardiac, orthopedics, and trauma procedures. Proper interpretation of the hidden and obscured anatomy …

X-Ray PoseNet: 6 DoF pose estimation for mobile X-Ray devices

Precise reconstruction of 3D volumes from X-ray projections requires precisely pre-calibrated systems where accurate knowledge of the systems geometric parameters is known ahead. However, when dealing with mobile X-ray devices such calibration …

ROAM

Implemntation of our recent paper on Whole Brain Segmentation and COVID-19 CT Lung Segmentation using RandOm lAyer Mixup in Semi-Supervised Learning

Cathnets: detection and single-view depth prediction of catheter electrodes

Single-view X-ray depth recovery: toward a novel concept for image-guided interventions