In the clinical research, three-dimensional/volumetric anatomical structure of the human
body is very significant for diagnosis, computer-aided surgery, surgical planning, patient …

Registration of pre-and intra-interventional data is one of the key technologies for image-
guided radiation therapy, radiosurgery, minimally invasive surgery, endoscopy, and …

Computed tomography (CT) can provide a 3D view of the patient's internal organs,
facilitating disease diagnosis, but it incurs more radiation dose to a patient and a CT scanner …

We present an end-to-end Convolutional Neural Network (CNN) approach for 3D
reconstruction of knee bones directly from two bi-planar X-ray images. Clinically, capturing …

In our chapter we are describing how to reconstruct three-dimensional anatomy from
medical image data and how to build Statistical 3D Shape Models out of many such …

As many different 3D volumes could produce the same 2D x‐ray image, inverting this
process is challenging. We show that recent deep learning‐based convolutional neural …

Three-dimensional patient specific bone models are required in a range of medical
applications, such as pre-operative surgery planning and improved guidance during …

Constructing a 3D bone surface model from a limited number of calibrated 2D X-ray images
(eg 2) and a 3D point distribution model is a challenging task, especially, when we would …

This paper introduces a deep neural network based method, ie, DeepOrganNet, to generate
and visualize fully high-fidelity 3D/4D organ geometric models from single-view medical …