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In this paper, we present a new fully automatic approach for noise parameter estimation in the context of fluorescence imaging systems. In particular, we address the problem of Poisson-Gaussian noise modeling in the nonstationary case. In microscopy practice, the nonstationarity is due to the photobleaching effect. The proposed method consists of an adequate moment based initialization followed by...
This paper addresses the denoising problem associated with diffusion MR imaging. Building on previous approaches to this problem, this paper presents a new method for joint denoising of a sequence of diffusion-weighted (DW) magnitude images. The proposed method uses a maximum a posteriori (MAP) estimation formulation to incorporate a Rician likelihood (for modeling the noisy magnitude data), a low...
We investigate saddle points in 3D cardiac images. We do so by improving a critical point detection algorithm, the 3D winding number, or Poincaré index. We consider two different applications. We estimate cardiac motion from 3D tagged MRI data, based on tracking of saddle points. We also employ our method for saddle point extraction in blood flow data, acquired by phase contrast MRI.
By modeling major degrading factors in SPECT imaging along with motion-compensated temporal denoising, 4D reconstruction is demonstrated to significantly improve the quality of reconstructed images in cardiac gated SPECT (GSPECT) at the standard dose level. The utility of 4D reconstruction for radiation dose reduction in GSPECT has not been studied despite increased concern in population based risk...
This paper describes a realistic cardiac MR perfusion simulator; both the kinematic model of the perfusion process as well as breathing effects are described and a novel model for the AIF is proposed. Additionally the most common degradation factors involved in the MR image formation, such as those derived from parallel acquisition protocols, the presence of thermal noise and its correlation, the...
This paper investigates the validity of the analytical framework for bias and variance in kinetic parameter estimations. Analytical computation of bias and variance is compared against Monte Carlo simulations for two different compartment models at different noise levels. Difference between the estimated and measured variance increases with the level of noise and complexity of the compartment model...
The presence of noise in High Angular Resolution Diffusion Imaging (HARDI) data of the brain can limit the accuracy with which fiber pathways of the brain can be extracted. In this work, we present a variational model to denoise HARDI data corrupted by Rician noise. Numerical experiments are performed on three types of data: 2D synthetic data, 3D diffusion-weighted Magnetic Resonance Imaging (DW-MRI)...
Fiber tracking techniques are essential for representing and visualizing the cardiac fiber architecture information encoded in diffusion-tensor imaging (DTI) data. We propose a neighborhood-based probabilistic fiber tracking method for cardiac DTI which accounts for spatial correlation and data uncertainty. The method consists in tracking fiber paths by sampling step directions from a normalized weighted...
The differential phase contrast CT (DPC-CT) implemented with x-ray tube and grating is emerging as a new technology to improve the contrast sensitivity of the conventional CT. Via system modeling, analysis and computer simulation, we investigate the DPC-CT's characteristics of signal and noise and compare them with the conventional CT. The preliminary data show that the DPC-CT possesses a modulation...
The Richardson-Lucy algorithm is one of the most important algorithms in the image deconvolution area. However, one of its drawbacks is slow convergence. A very significant acceleration is obtained by the technique proposed by Biggs and Andrews (BA), which is implemented in the deconvlucy function of the Image Processing MATLAB toolbox. The BA method was developed heuristically with no proof of convergence...
In phosphorescence lifetime imaging methods oxygen tension in retinal vessels has traditionally been indirectly determined from the estimates of intermediate variables whose noise-contaminated linear combinations are observed as phosphorescence intensity images. The classical least squares (LS) and regularized least squares (RLS) methods were used to obtain estimates of the intermediate variables...
Ultrasound image resolution enhancement is an ongoing challenge to date. Though many works have been performed using device-based approach, there exists few works dealing with post-processing methods. This paper investigates a technique based on the Alternating Direction Method of Multipliers for the resolution enhancement in ultrasound imaging, which includes the deblurring and denoising tasks. We...
We present a fast and robust approach to tracking whole fluorescent cells in time-lapse series. The proposed tracking scheme involves two steps. First, coherence-enhancing diffusion filtering is applied on each frame to reduce the amount of noise and enhance flow-like structures. Second, the enhanced cell boundaries are detected by minimizing the Chan-Vese model in a fast level set-like framework...
In this article, we are interested in restoring images from 3D fluorescence microscopy. In fact, these images are affected by a depth-variant blur due to light refraction phenomenon. We present and compare two different restoration strategies for that problem. The first one is based on multiple deconvolutions with depth-invariant blur functions and the second one consists in using a depth-variant...
We present a new automatic method for segmentation of Multiple Sclerosis (MS) lesions in Magnetic Resonance Images. The algorithm performs tissue classification combining a within subject global tissue intensity model and a local tissue intensity model derived from an aligned set of healthy reference subjects. MS lesions are detected as outliers towards the proposed coupled global/local intensity...
The understanding of the embryogenesis in living systems requires reliable quantitative analysis of the cell migration throughout all the stages of development. This is a major challenge of the ”in-toto” reconstruction based on different modalities of ”in-vivo” imaging techniques-spatio-temporal resolution and image artifacts and noise. Several methods for cell tracking are available, but expensive...
Over decades, segmentation has remained a salient task in most medical imaging applications confronting multi-faced challenges including limited image quality. In this paper, we present a new anisotropic region growing segmentation approach for vascular or other elongated structures. A fundamental challenge during tracing vascular structures is broken continuity of structures by noise and other imaging...
Accurate inter-subject registration of magnetic resonance (MR) images of the human brain is required to allow meaningful comparisons across groups of subjects. Some anatomical structures can be very difficult to match and this can result in intensity based registration approaches inferring complex and implausible mappings in some regions. In this work, we propose a generic probabilistic framework...
Functional imaging serves as an important supplement to anatomical imaging modalities such as MR and CT in modern health care. In perfusion CT (CTP), hemodynamic parameters are derived from the tracking of the first-pass of the contrast bolus entering a tissue region of interest. In practice, however, the post-processed parametric maps tend to be noisy, especially in low-dose CTP, in part due to the...
In this work, we present an automatic branch and stenoses detection method that is capable of detecting all types of plaques in Computed Tomography Angiography (CTA) modality. Our method is based on the vessel extraction algorithm we proposed in [1], and detects branches and stenoses in a very fast way. We demonstrate the performance of our branch detection method on 3 complex tubular structured synthetic...
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