In this paper, based on the SαS distributions, we design SαS filters and use the filters as a new feature extraction method for non-rigid medical image registration. In brain MR images, the energy distributions of different frequency bands often exhibit heavy-tailed behavior. Such non-Gaussian behavior is essential for non-rigid image registration but cannot be satisfactorily modeled by the con...

Anecdotally, surgeons sometimes observe large errors when using image guidance in endonasal surgery. We hypothesize that one contributing factor is the possibility that operating room personnel might accidentally bump the optically tracked rigid body attached to the patient after registration has been performed. In this paper we explore the registration error at the skull base that can be induc...

Medical imaging applications of rigid and non-rigid elastic deformable image registration are undergoing wide scale development. Our approach determines image deformation maps through a hierarchical process, from global to local scales. Vemuri (2000) reported a registration method, based on levelset evolution theory, to morph an image along the motion gradient until it deforms to the reference ...

This paper describes the design, implementation and results of a unified non-rigid feature registration method for the purposes of anatomical MRI brain registration. An important characteristic of the method is its ability to fuse different types of anatomical features into a single point-set representation. We demonstrate the application of the method using two different types of features: the...

Background: Surgery and accurate removal of the brain tumor in the operating room and after opening the scalp is one of the major challenges for neurosurgeons due to the removal of skull pressure and displacement and deformation of the brain tissue. This displacement of the brain changes the location of the tumor relative to the MR image taken preoperatively. Methods: This study, which is done...

We present a Parallel Adaptive Physics-Based Non-Rigid Registration framework for aligning preoperative to intra-operative brain Magnetic Resonance Images (MRI) of patients who have undergone a tumor resection. This framework extends our earlier work on the Physics-Based methods by using an adaptive, multi-material, parallel Finite Element (FE) biomechanical model to describe the physical defor...

PURPOSE In oxygen-enhanced magnetic resonance imaging of the lung (O2-MRI), motion artifacts related to breathing hamper the quality of the parametric O2-maps. In this study, fully automatic non-rigid image registration was assessed as a post-processing method to improve the quality of O2-MRI. MATERIALS AND METHODS Twenty healthy volunteers were investigated on a 1.5 T MR system. O2-MRI was o...

Non-rigid image registration techniques are commonly used to estimate complex tissue deformations in medical imaging. A range of non-rigid registration algorithms have been proposed, but they typically have high computational complexity. To reduce this complexity, combinations of multiple less complex deformations have been proposed such as hierarchical techniques which successively split the n...

Mutual information (MI) based registration methods are susceptible to the variation of the intensity of the image. We present a multi-modality MRI-CT non-rigid registration method by combining Kmeans clustering technique with mutual information. This method makes use of K-means clustering to determine variant bin sizes in CT image. The resulting clustered (labeled) CT image is non-rigidly regis...

Wing disc pouches of fruit flies are a powerful genetic model for studying physiological intercellular calcium (Ca) signals for dynamic analysis of cell signaling in organ development and disease studies. A key to analyzing spatial-temporal patterns of Ca signal waves is to accurately align the pouches across image sequences. However, pouches in different image frames may exhibit extensive inte...