Biomedical subjects

Chenyang Xu

Publications and source records attributed to Chenyang Xu.

8 recordsLinked to original sources

PubMed2005

Comparative performance analysis of time-frequency distributions for spectroscopic optical coherence tomography.

The analysis of spectroscopic optical coherence tomography (SOCT) signals suffers the trade-off between time resolution and frequency resolution. Various joint time-frequency distributions (TFDs) can optimize this trade-off. Synthesized signals were generated and experimentally acquired data were obtained to compare and validate several different TFDs under different SOCT imaging schemes. Specific criteria were designed to quantify the TFD performance. We found that different SOCT imaging schemes require different optimal TFDs. Cohen's class TFDs generate the most compact time-frequency (TF) analysis, while linear TFDs offer the most reliable TF analysis. In both cases, if some prior information is known, model-based TF analysis can improve the performance.

Algorithms↗

PubMed2005

Learning based non-rigid multi-modal image registration using Kullback-Leibler divergence.

The need for non-rigid multi-modal registration is becoming increasingly common for many clinical applications. To date, however, existing proposed techniques remain as largely academic research effort with very few methods being validated for clinical product use. It has been suggested by Crum et al. that the context-free nature of these methods is one of the main limitations and that moving towards context-specific methods by incorporating prior knowledge of the underlying registration problem is necessary to achieve registration results that are accurate and robust enough for clinical applications. In this paper, we propose a novel non-rigid multi-modal registration method using a variational formulation that incorporates a prior learned joint intensity distribution. The registration is achieved by simultaneously minimizing the Kullback-Leibler divergence between an observed and a learned joint intensity distribution and maximizing the mutual information between reference and alignment images. We have applied our proposed method on both synthetic and real images with encouraging results.

Algorithms↗

PubMed2004

Near-infrared dyes as contrast-enhancing agents for spectroscopic optical coherence tomography.

Optical coherence tomography (OCT) images of biological tissues often have low contrast. Spectroscopic optical coherence tomography (SOCT) methods have been developed to enhance contrast but remain limited because most tissues are not spectrally active in the frequency bands of laser sources commonly used in OCT. Near-infrared (NIR) dyes with absorption spectra features within the OCT source spectrum can be used for enhancing contrast in this situation. We introduce and demonstrate the use of NIR dyes as contrast agents for SOCT. Contrast-enhanced images are compared with fluorescence microscopy, demonstrating a link between SOCT and fluorescence imaging.

Apium↗

PubMed2004

CRUISE: cortical reconstruction using implicit surface evolution.

Segmentation and representation of the human cerebral cortex from magnetic resonance (MR) images play an important role in neuroscience and medicine. A successful segmentation method must be robust to various imaging artifacts and produce anatomically meaningful and consistent cortical representations. A method for the automatic reconstruction of the inner, central, and outer surfaces of the cerebral cortex from T1-weighted MR brain images is presented. The method combines a fuzzy tissue classification method, an efficient topology correction algorithm, and a topology-preserving geometric deformable surface model (TGDM). The algorithm is fast and numerically stable, and yields accurate brain surface reconstructions that are guaranteed to be topologically correct and free from self-intersections. Validation results on real MR data are presented to demonstrate the performance of the method.

Algorithms↗

PubMed2004

Cortical surface segmentation and mapping.

Segmentation and mapping of the human cerebral cortex from magnetic resonance (MR) images plays an important role in neuroscience and medicine. This paper describes a comprehensive approach for cortical reconstruction, flattening, and sulcal segmentation. Robustness to imaging artifacts and anatomical consistency are key achievements in an overall approach that is nearly fully automatic and computationally fast. Results demonstrating the application of this approach to a study of cortical thickness changes in aging are presented.

Aging↗

PubMed2002

Automated sulcal segmentation using watersheds on the cortical surface.

The human cortical surface is a highly complex, folded structure. Sulci, the spaces between the folds, define location on the cortex and provide a parcellation into anatomically distinct areas. A topic that has recently received increased attention is the segmentation of these sulci from magnetic resonance images, with most work focusing on extracting either the sulcal spaces between the folds or curve representations of sulci. Unlike these methods, we propose a technique that extracts actual regions of the cortical surface that surround sulci, which we call "sulcal regions." The method is based on a watershed algorithm applied to a geodesic depth measure on the cortical surface. A well-known problem with the watershed algorithm is a tendency toward oversegmentation, meaning that a single region is segmented as several pieces. To address this problem, we propose a postprocessing algorithm that merges appropriate segments from the watershed algorithm. The sulcal regions are then manually labeled by simply selecting the appropriate regions with a mouse click and a preliminary study of sulcal depth is reported. Finally, a scheme is presented for computing a complete parcellation of the cortical surface.

Automation↗

PubMed2002

Topology correction in brain cortex segmentation using a multiscale, graph-based algorithm.

Reconstructing an accurate and topologically correct representation of the cortical surface of the brain is an important objective in various neuroscience applications. Most cortical surface reconstruction methods either ignore topology or correct it using manual editing or methods that lead to inaccurate reconstructions. Shattuck and Leahy recently reported a fully automatic method that yields a topologically correct representation with little distortion of the underlying segmentation. We provide an alternate approach that has several advantages over their approach, including the use of arbitrary digital connectivities, a flexible morphology-based multiscale approach, and the option of foreground-only or background-only correction. A detailed analysis of the method's performance on 15 magnetic resonance brain images is provided.

Algorithms↗

PubMedDate not supplied

Optical probes and techniques for molecular contrast enhancement in coherence imaging.

Optics has played a key role in the rapidly developing field of molecular imaging. The spectroscopic nature and high-resolution imaging capabilities of light provide a means for probing biological morphology and function at the cellular and molecular levels. While the use of bioluminescent and fluorescent probes has become a mainstay in optical molecular imaging, a large number of other optical imaging modalities exist that can be included in this emerging field. In vivo imaging technologies such as optical coherence tomography and reflectance confocal microscopy have had limited use of molecular probes. In the last few years, novel nonfluorescent and nonbioluminescent molecular imaging probes have been developed that will initiate new directions in coherent optical molecular imaging. Classes of probes reviewed in this work include those that alter the local optical scattering or absorption properties of the tissue, those that modulate these local optical properties in a predictable manner, and those that are detected utilizing spectroscopic optical coherence tomography (OCT) principles. In addition to spectroscopic OCT, novel nonlinear interferometric imaging techniques have recently been developed to detect endogenous molecules. Probes and techniques designed for coherent molecular imaging are likely to improve the detection and diagnostic capabilities of OCT.

Animals↗