Structural Brain Network: What is the Effect of LiFE Optimization of Whole Brain Tractography?

Structural brain networks constructed based on diffusion-weighted MRI (dMRI) have provided a systems perspective to explore the organization of the human brain. Some redundant and nonexistent fibers, however, are inevitably generated in whole brain tractography. We propose to add one critical step while constructing the networks to remove these fibers using the linear fascicle evaluation (LiFE) method, and study the differences between the networks with and without LiFE optimization.

A Comprehensive Study of Osteogenic Calcium Phosphate Silicate Cement: Material Characterization and In Vitro/In Vivo Testing.

Vertebral compression fractures can be successfully restored by injectable bone cements. Here the as-yet unexplored in vitro cytotoxicity, in vivo biodegradation, and osteoconductivity of a new calcium phosphate silicate cements (CPSC) are studied, where monocalcium phosphate (MCP; 5, 10, and 15 wt%) is added to calcium silicate cement (CSC). Setting rate and compressive strength of CPSC decrease with the addition of MCP.

Reconstruction Method for Optical Tomography Based on the Linearized Bregman Iteration with Sparse Regularization.

Optical molecular imaging is a promising technique and has been widely used in physiology, and pathology at cellular and molecular levels, which includes different modalities such as bioluminescence tomography, fluorescence molecular tomography and Cerenkov luminescence tomography. The inverse problem is ill-posed for the above modalities, which cause a nonunique solution. In this paper, we propose an effective reconstruction method based on the linearized Bregman iterative algorithm with sparse regularization (LBSR) for reconstruction.

Fast axial and lateral displacement estimation in myocardial elastography based on RF signals with predictions.

Myocardial elastography (ME) is a strain imaging technique used to diagnose myocardial diseases. Axial and lateral displacement calculations are pre-conditions of strain image acquisition in ME. W.

Robust boundary detection of left ventricles on ultrasound images using ASM-level set method.

Level set method has been widely used in medical image analysis, but it has difficulties when being used in the segmentation of left ventricular (LV) boundaries on echocardiography images because the boundaries are not very distinguish, and the signal-to-noise ratio of echocardiography images is not very high. In this paper, we introduce the Active Shape Model (ASM) into the traditional level set method to enforce shape constraints. It improves the accuracy of boundary detection and makes the evolution more efficient.

Iterative reconstruction with segmentation penalty for PET.

Segmentation technique is widely accepted to reduce noise propagation from transmission scanning for positron emission tomography. The conventional routine is to sequentially perform reconstruction and segmentation. A smoothness penalty is also usually used to reduce noise, which can be imposed to both the ML and WLS estimators.

The influence of construction methodology on structural brain network measures: A review.

Structural brain networks based on diffusion MRI and tractography show robust attributes such as small-worldness, hierarchical modularity, and rich-club organization. However, there are large discrepancies in the reports about specific network measures. It is hypothesized that these discrepancies result from the influence of construction methodology.

Using multiscale texture and density features for near-term breast cancer risk analysis.

Purpose: To help improve efficacy of screening mammography by eventually establishing a new optimal personalized screening paradigm, the authors investigated the potential of using the quantitative multiscale texture and density feature analysis of digital mammograms to predict near-term breast cancer risk.

Methods: The authors' dataset includes digital mammograms acquired from 340 women. Among them, 141 were positive and 199 were negative/benign cases.

Optic disc segmentation by balloon snake with texture from color fundus image.

A well-established method for diagnosis of glaucoma is the examination of the optic nerve head based on fundus image as glaucomatous patients tend to have larger cup-to-disc ratios. The difficulty of optic segmentation is due to the fuzzy boundaries and peripapillary atrophy (PPA). In this paper a novel method for optic nerve head segmentation is proposed.

FPGA-based design and implementation of arterial pulse wave generator using piecewise Gaussian-cosine fitting.

Because arterial pulse waves contain vital information related to the condition of the cardiovascular system, considerable attention has been devoted to the study of pulse waves in recent years. Accurate acquisition is essential to investigate arterial pulse waves. However, at the stage of developing equipment for acquiring and analyzing arterial pulse waves, specific pulse signals may be unavailable for debugging and evaluating the system under development.

Mutation analysis and prenatal diagnosis for three families affected by isolated methylmalonic aciduria.

Isolated methylmalonic acidemia (MMA) is a genetically heterogeneous disorder caused mainly by deficiency of methylmalonyl-CoA mutase. In the present study, we analyzed MUT gene mutations in 3 Chinese couples with a birth history of isolated MMA. We also provided prenatal diagnoses for the detected mutation.

3D bone subtraction CT angiography for the evaluation of intracranial aneurysms: a comparison study with 2D bone subtraction CT angiography and conventional non-subtracted CT angiography.

Background: Bone subtraction computed tomography angiography (BSCTA) is better able to facilitate the detection of intracranial aneurysms adjacent to bone structures compared to conventional non-subtracted CTA (CNSCTA). However, the comparison of the diagnostic accuracy of three-dimensional (3D) and two-dimensional (2D) BSCTA and conventional CTA in evaluating intracranial aneurysms remains unclear.

Purpose: To evaluate whether 3D BSCTA has a superior diagnostic accuracy to those of 2D BSCTA and CNSCTA in a single center with the same instrument.

Morphology variability of radial pulse wave during exercise.

Pulse wave contains much information on a cardiovascular system. Pulse wave variability during exercise is of great significance as it reflects more information combining with pulse wave under stationary state. This paper studied the morphology variability of radial pulse wave during exercise.

Fiducial markers configuration optimization in image-guided surgery.

The rigid registration is a key step of Image Guided Surgery (IGS), and the point-pair method is the main way used for registration. However the configuration of fiducial points has a great influence on the registration accuracy at the target point. Now almost all the optimization method of fiducial points configuration relies on the empirical simulation-based Fitzpatrick's target registration error (TRE).

Accurate airway centerline extraction based on topological thinning using graph-theoretic analysis.

The quantitative analysis of the airway tree is of critical importance in the CT-based diagnosis and treatment of popular pulmonary diseases. The extraction of airway centerline is a precursor to identify airway hierarchical structure, measure geometrical parameters, and guide visualized detection. Traditional methods suffer from extra branches and circles due to incomplete segmentation results, which induce false analysis in applications.

Automatic segmentation of juxta-pleural tumors from CT images based on morphological feature analysis.

Extraction of lung tumors is a fundamental step for further quantitative analysis of the tumor, but is challenging for juxta-pleural tumors due to the adhesion to the pleurae. An automatic algorithm for segmentation of juxta-pleural tumors based on the analysis of the geometric and morphological features was proposed. Initially, the lung is extracted by means of thresholding using 2D Otsu's method.

Robust boundary detection and tracking of left ventricles on ultrasound images using active shape model and ant colony optimization.

Information regarding the motion, strain and synchronization are important for cardiac diagnosis and therapy. Extraction of such information from ultrasound images remains an open problem till today. In this paper, a novel method is proposed to extract the boundaries of left ventricles and track these boundaries in ultrasound image sequences.

Computational fluid dynamics simulation of airflow in the trachea and main bronchi for the subjects with left pulmonary artery sling.

Background: Left pulmonary artery sling (LPAS) is a rare but severe congenital anomaly, in which the stenoses are formed in the trachea and/or main bronchi. Multi-detector computed tomography (MDCT) provides useful anatomical images, but does not offer functional information. The objective of the present study is to quantitatively analyze the airflow in the trachea and main bronchi of LPAS subjects through computational fluid dynamics (CFD) simulation.

Automatic pulmonary fissure detection and lobe segmentation in CT chest images.

Background: Multi-detector Computed Tomography has become an invaluable tool for the diagnosis of chronic respiratory diseases. Based on CT images, the automatic algorithm to detect the fissures and divide the lung into five lobes will help regionally quantify, amongst others, the lung density, texture, airway and, blood vessel structures, ventilation and perfusion.

Methods: Sagittal adaptive fissure scanning based on the sparseness of the vessels and bronchi is employed to localize the potential fissure region.

Increased Tbx1 expression may play a role via TGFβ-Smad2/3 signaling pathway in acute kidney injury induced by gentamicin.

T-box 1 (Tbx1) gene is closely involved in embryonic kidney development. To explore the role of Tbx1 in acute kidney injury (AKI) and the underlying mechanism, we detected the expression of Tbx1 and components of transforming growth factor-beta (TGF-β) signaling pathways including TGF-β, phosphorylated Smad2/3 (p-Smad2/3) and phosphorylated Smad1/5/8 (p-Smad1/5/8) in kidney tissues derived from a rat model for AKI induced by gentamicin (GM). Apoptosis of renal cells was assessed by terminal deoxynucleotidyl transferase-mediated dUTP nick end-labeling (TUNEL), along with the expression of two essential genes involved in apoptosis, caspase-3 and Bcl-2.

A novel bioinformatics method for efficient knowledge discovery by BLSOM from big genomic sequence data.

With remarkable increase of genomic sequence data of a wide range of species, novel tools are needed for comprehensive analyses of the big sequence data. Self-Organizing Map (SOM) is an effective tool for clustering and visualizing high-dimensional data such as oligonucleotide composition on one map. By modifying the conventional SOM, we have previously developed Batch-Learning SOM (BLSOM), which allows classification of sequence fragments according to species, solely depending on the oligonucleotide composition.

Automated detection of the arterial input function using normalized cut clustering to determine cerebral perfusion by dynamic susceptibility contrast-magnetic resonance imaging.

Purpose: To propose a new clustering method for the automatic detection of arterial input function (AIF) with high accuracy in dynamic susceptibility contrast-magnetic resonance imaging (DSC-MRI).

Materials And Methods: A novel method for automatically determining the AIF was proposed to facilitate the analysis of MR perfusion, which relied on normalized cut (Ncut) clustering. Its performance was compared with those of two other previously reported clustering methods: k-means and fuzzy c-means (FCM) techniques, in terms of the detection accuracy and computational time.

Prediction of near-term risk of developing breast cancer using computerized features from bilateral mammograms.

Asymmetry of bilateral mammographic tissue density and patterns is a potentially strong indicator of having or developing breast abnormalities or early cancers. The purpose of this study is to design and test the global asymmetry features from bilateral mammograms to predict the near-term risk of women developing detectable high risk breast lesions or cancer in the next sequential screening mammography examination. The image dataset includes mammograms acquired from 90 women who underwent routine screening examinations, all interpreted as negative and not recalled by the radiologists during the original screening procedures.

Fast and robust reconstruction for fluorescence molecular tomography via a sparsity adaptive subspace pursuit method.

Fluorescence molecular tomography (FMT), as a promising imaging modality, can three-dimensionally locate the specific tumor position in small animals. However, it remains challenging for effective and robust reconstruction of fluorescent probe distribution in animals. In this paper, we present a novel method based on sparsity adaptive subspace pursuit (SASP) for FMT reconstruction.

Comparison of K-means and fuzzy c-means algorithm performance for automated determination of the arterial input function.

The arterial input function (AIF) plays a crucial role in the quantification of cerebral perfusion parameters. The traditional method for AIF detection is based on manual operation, which is time-consuming and subjective. Two automatic methods have been reported that are based on two frequently used clustering algorithms: fuzzy c-means (FCM) and K-means.