Texture Analysis of Native T1 Images as a Novel Method for Noninvasive Assessment of Uremic Cardiomyopathy.

Background: Noncontrast cardiac T times are increased in dialysis patients which might indicate fibrotic alterations in uremic cardiomyopathy.

Purpose: To explore the application of the texture analysis (TA) of T images in the assessment of myocardial alterations in dialysis patients.

Study Type: Case-control study.

The capability of detecting small vessels beyond the conventional MRI sensitivity using iron-based contrast agent enhanced susceptibility weighted imaging.

Imaging brain microvasculature is important in cerebrovascular diseases. However, there is still a lack of non-invasive, non-radiation, and whole-body imaging techniques to investigate them. The aim of this study is to develop an ultra-small superparamagnetic iron oxide (USPIO) enhanced susceptibility weighted imaging (SWI) method for imaging micro-vasculature in both animal (~10 μm in rat) and human brain.

Correction to: Non-contrast MRI for breast screening: preliminary study on detectability of benign and malignant lesions in women with dense breasts.

In the original version of the article, the image of Figure 2 was erroneously duplicated as Figure 4. The correct version of Figure 4 is given below. The original article has been corrected.

Non-contrast MRI for breast screening: preliminary study on detectability of benign and malignant lesions in women with dense breasts.

Purpose: The importance of breast cancer screening has long been known. Unfortunately, there is no imaging modality for screening women with dense breasts that is both sensitive and without concerns regarding potential side effects. The purpose of this study is to explore the possibility of combined diffusion-weighted imaging and turbo inversion recovery magnitude MRI (DWI + TIRM) to overcome the difficulty of detection sensitivity and safety.

CDCA5 overexpression is an Indicator of poor prognosis in patients with hepatocellular carcinoma (HCC).

Background: Accurate and early prognosis of disease is essential to clinical decision making, particularly in diseases, such as HCC, that are typically diagnosed at a late stage in the course of disease and therefore carry a poor prognosis. CDCA5 is a cell cycle regulatory protein that has shown prognostic value in several cancers.

Methods: We retrospectively evaluated 178 patients with HCC treated with curative liver resection between September 2009 and September 2012 at Nanchong Central Hospital in Nanchong, Sichuan Province, China.

Discrimination between malignant and benign mass-like lesions from breast dynamic contrast enhanced MRI: semi-automatic vs. manual analysis of the signal time-intensity curves.

To investigate the performance of a new semi-automatic method for analyzing the signal time-intensity curve (TIC) obtained by breast dynamic contrast enhancement (DCE)-MRI. In the conventional method, a circular region of interest was drawn manually onto the map reflecting the maximum slope of increase (MSI) to delineate the suspicious lesions. The mean TIC was determined subjectively as one of three different wash-out patterns.

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.

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.

Limited-view photoacoustic imaging based on an iterative adaptive weighted filtered backprojection approach.

An iterative adaptive weighted filtered backprojection (FBP) approach was applied to our photoacoustic imaging (PAI) of the optical absorption in biological tissues from limited-view data. By using an image-based adaptive weighted PAI reconstruction, we can modify the defect of the artifacts degrading the quality of the image. Results of numerical simulations demonstrated that the proposed algorithm was superior to FBP in terms of both accuracy and robustness to noise.

[Optimization of the ray-casting algorithm based on streaming single instruction multiple datum extension].

At present, ray-casting algorithm is the most widely used algorithm in the field of medical image visualization, and it can achieve the best image quality. Due to large amounts of computation like sampling, gradient, lighting and blending calculation, the cost of ray-casting algorithm is very large. The characteristic of Streaming single instruction multiple datum extensions (SSE) instruction--supporting vector computation--can satisfy the property of ray-casting algorithm well.

The CUBLAS and CULA based GPU acceleration of adaptive finite element framework for bioluminescence tomography.

In molecular imaging (MI), especially the optical molecular imaging, bioluminescence tomography (BLT) emerges as an effective imaging modality for small animal imaging. The finite element methods (FEMs), especially the adaptive finite element (AFE) framework, play an important role in BLT. The processing speed of the FEMs and the AFE framework still needs to be improved, although the multi-thread CPU technology and the multi CPU technology have already been applied.

A trust region method in adaptive finite element framework for bioluminescence tomography.

Bioluminescence tomography (BLT) is an effective molecular imaging (MI) modality. Because of the ill-posedness, the inverse problem of BLT is still open. We present a trust region method (TRM) for BLT source reconstruction.