Deformable image registration poses a highly non-convex optimisation problem. Conventionally, medical image registration techniques rely on continuous optimisation, which is prone to local minima. Recent advances in the mathematics and new programming methods enable these disadvantages to be overcome using discrete optimisation. In this paper, we present a new technique deeds, which employs a d...

Peptide receptor radionuclide therapy (PRRT) is an effective MRT (molecular radiotherapy) treatment, which consists of multiple administrations of a radiopharmaceutical labelled with 177Lu or 90Y. Through sequential functional imaging a patient specific 3D dosimetry can be derived. Multiple scans should be previously co-registered to allow accurate absorbed dose calculations. The purpose of thi...

PURPOSE For asymmetric organ shrinkage caused by heterogeneity dose distribution, tissue elasticity based deformable organ registration cannot be directly applied to the treatment image to construct the treatment dose. A novel approach is proposed to include radiation dose inducible organ shrinkage/deformation in the consideration of treatment dose assessment. METHODS A model and algorithm we...

Introduction An essential step in radiation therapy is accurate three-dimensional segmentation of the target and organs at risk. Traditionally, this has been done by manual contouring on a slice-by-slice basis, but modern adaptive radiation therapy (ART) protocols can require segmentation of multiple daily images for each patient [1], increasing the pressure to develop automated methods for seg...

PURPOSE Radiotherapy (RT) that selectively avoids irradiating highly functional lung regions may reduce pulmonary toxicity, which is substantial in lung cancer RT. Single-energy computed tomography (CT) pulmonary perfusion imaging has several advantages (e.g., higher resolution) over other modalities and has great potential for widespread clinical implementation, particularly in RT. The purpose...

The purpose of this study was to develop an approach to generate artificial computed tomography (CT) images with known deformation by learning the anatomy changes in a patient population for voxel-level validation of deformable image registration. Using a dataset of CT images representing anatomy changes during the course of radiation therapy, we selected a reference image and registered the re...

The ability to perform fast, accurate, deformable registration with intraoperative images featuring surgical excisions was investigated for use in cone-beam CT (CBCT) guided head and neck surgery. Existing deformable registration methods generally fail to account for tissue excised between image acquisitions and typically simply “move” voxels within the images with no ability to account for tis...

Deformable medical image registration requires the optimisation of a function with a large number of degrees of freedom. Commonly-used approaches to reduce the computational complexity, such as uniform B-splines and Gaussian image pyramids, introduce translation-invariant homogeneous smoothing, and may lead to less accurate registration in particular for motion fields with discontinuities. This...