||Analysis of dermatological images for teledermatology and diagnostic applications|
We are researching and developing image processing algorithms for dermatological applications in diagnostic and decision making systems as well as for education. This includes the creation of a personalized surface model from a set of color and depth camera images, detection and classification of dermatological findings, such as psoriasis lesions and plaques, as well as longitudinal analysis of changes.
||Elastic Registration of 3D Objects|
Correspondance-less alignment of 3D non-rigid objects using parametric nonlinear deformation models. Our algorithms are able to estimate the parameters of the deformation without an established set of correspondences, thus providing a fully automatic and computationally efficient registration framework for 3D objects.
||Elastic Registration of Multimodal Prostate Images|
A novel method for non-rigid registration of transrectal
ultrasound and magnetic resonance prostate images based on a non-linear
||Estimation of Linear Shape Deformations and its Medical Applications|
We consider the problem of planar shape registration on binary images. Our primary goal is to investigate novel methodologies which work without feature point extraction and established correspondences; avoid the solution of complex optimization problems; and provide an exact solution regardless of the strength of the distortion. The newly developed techniques are validated on medical images.
A novel solution for reassembling a broken object from its parts without established correspondences, where each part is subject to a linear deformation.
||Recovering Diffeomorfic Shape Deformations without Correspondences|
We consider the problem of estimation the parameters of transformations aligning two binary images. The advantage of our algorithm is that it is easy to implement, less sensitive to the strength of the deformation, and robust against segmentation errors.
||Transforming CT studies of the pelvic region to a common reference frame|
Our automatic registration method was tailored to the needs of a model-based segmentation framework of the pelvic area in CT studies in collaboration with GE Medical Systems. Registration was used as a preprocesing task. The goal of it was the acceptable alignment of the pubic bone area (where the two organs of interest, the prostate and bladder are located) of studies from different patients.
||Voxel similarity based automatic image registration|
An automatic registration method utilizing mutual information and its various medical and neutron tomography applications.
||Robotically assisted, image guided planning and execution of percutaneous therapies|
We developed a unified framework for percutaneous therapies utilizing localization frames and implemented an application using CT imaging and a robot.
||Point-based registration and its error analysis|
We investigated registration methods based on interactively identified point pairs used in medical image registration. We proposed an affine search method and gave a sufficient existence condition for the unique solution. The properties of rigid-body and affine methods were examined via numerical simulations.