Biomedical subjects

Jiangli Lin

Publications and source records attributed to Jiangli Lin.

9 recordsLinked to original sources

PubMed2006

[A method based on image processing and analyzing technology for estimating the activity of mesenchymal stem cells].

Cell culture is one of the usual methods for studying living cell and tissue, the method presented in this paper is based on image processing and analyzing technology for activity estimation of mesenchymal stem cells (MSCs). The existing activity estimation methods are costly, complex and invasive. In this method, thresholding is used to preprocess image and to separate out the growth hallow. Then the area is calculated by counting the pixels of the growth hallow. The changes of the activity estimated by this method are similar to those by corresponding cellular experiments. Compared with the existing methods in biology, medicine or medical cellular science, this method is easier, faster, cost-effective and non-invasive. The proposed method has been proved to be efficient by primary experiments of MSCs.

Animals↗

PubMed2006

[Computer-aided diagnosis of fatty liver based on ultrasonic images].

This study aims to provide a computer-aided method for the diagnosis of fatty liver by B-scan ultrasonic imaging. Fatty liver is referred to the infiltration of triglycerides and other fats of the liver cells, which affected the texture of liver tissue. In this paper, some features including mean intensity ratio, as well as angular second moment, entropy and inverse differential moment of gray level co-occurrence matrix were extracted from B-scan ultrasonic liver images. Feature vectors which indicated two classes of images were created with the four features. Then we used kappa-means clustering algorithm, self-organized feature mapping (SOFM) artificial neural network and back-propagation (BP) artificial neural network to classify these vectors. The accuracy rate of kappa-means clustering algorithm was 100% for normal liver and 63.6% for fatty liver. The results of SOFM neural network showed that the accuracy rate was 84.8% for normal liver and 90.9% for fatty liver. The accuracy rate of neural network was 100% both for normal liver and fatty liver. This technology could detect the characteristics of B-scan images of normal liver and fatty liver more accurately. It could greatly improve the accuracy of the diagnosis of fatty liver.

Diagnosis, Differential↗

PubMed2006

[Review of nonlinear filters for medical ultrasonic images].

Ultrasound medical imaging has been widely applied in clinic diagnoses because of its real-time, non-invasiveness and convenience. However, it suffers from severe speckle noises. Until now, a lot of filtering algorithms have been proposed, but none of them is satisfactory. In this paper, four nonlinear filter methods, based on median filter, wavelet decomposition and anisotropic diffusion, are systematically reviewed. Finally, the prospect of the nonlinear filtering method is discussed.

Algorithms↗

PubMed2006

[The recognition of breast tumor based on ultrasonic image contour features].

The purpose of this article is to evaluate the role of quantitative margin features in the computer-aided diagnosis of malignant and benign solid breast masses using sonographic imaging. The tumour was seperated by the expert. Three contour features circurity (C), area ratio (A) and length width ratio (LWR) was caculated from the tumour contour. Then back-propagation (BP) neural network with contour features was used to classify tumors into benign and malignant. Results from 119 ultrasonic images have been applied in this experiment. BP neural network yielded the following results: 89.7% and 73.5% respectively. The methods applied in this paper are helpful to raise the correctance of breast cancer diagnosis.

Breast Neoplasms↗

PubMed2005

[Estimation of fetal weight on the basis of neural network].

The ultrasonic estimation of fetal weight at delivery is of important prognostic significance in obstetrical practice. The convertional regression formulas used for estimating fetal weight have the disadvantage of less reliability. In this study, we used the back propagation neural network (BP) to estimate Fetal Weight. Some input variables were adopted in constructing the BP model: biparietal diameter (BPD), cerebellum transverse diameter (TCD), abdominal circumference (AC), liver length (LL), femur length (FL), fetal thigh soft tissue thickness (FSTT), and gestational age (GA). The fetal weights of 109 singleton fetuses were estimated. In the training group and validation group, coincidence rates were 89.77% and 76.19% respectively. The results show that the estimation based on neural network is more accurate than that by regression method. GA, its unit is not week but day in our formulas, is very valuable in combination with other ultrasonic parameters on estimation.

Anthropometry↗

PubMed2005

[Recommendations for mitral regurgtitation with Doppler echocardiography].

Mitral regurgitation is one of the most serious heart diseases. With the development of up-to-date medical techniques, the ratio of successful operations in valvular repair and valvular replacement has been largely improved. Examinations before operation become extremely crucial. Accurate method is required in assessing the degree of mitral regurgitation to set down the corresponding treatment method. This paper reviews the evaluation methods of mitral valvular regurgitation provided in these years and presents comments on the application areas as well as the merits and disadvantages of those methods. Finally, the prospect of the method based on three-dimensional Doppler ultrasonographic imaging on mitral regurgitation is discussed.

Echocardiography, Doppler, Color↗

PubMed2004

[Axis registration and image interpolation of rotary scanning echocardiogram].

The object of this study was to work at accurate axis registration and interpolation methods for multi-dimension reconstruction of rotary scanning ultrasonic medical images. At first, time-field curves of the images' axes were analyzed according to their characteristic points and the axial direction registration was realized. Similar matrix was used to find registration pixels line near the axes of two images. Auto-correlation function and Fourier spectrum were used to evaluate the effects of axes registration. Second, an interpolation method was studied for the special space distribution of rotary scanning images. Results of experiments indicate that the axes registration and interpolation methods were suitable to rotary scanning medical images. The quality of reconstruction can be greatly improved by registration-based interpolation methods.

Algorithms↗

PubMed2004

[Fast volume rendering of echocardiogram with shear-warp algorithm].

Shear-warp is a volume rendering technology based on object-order. It has the characteristics of high speed and high image quality by comparison with the conventional visualization technology. The authors introduced the principle of this algorithm and applied it to the visualization of 3-D data obtained by interpolating rotary scanning echocardiogram. The 3-D reconstruction of the echocardiogram was efficiently completed with high image quality. This algorithm has a prospective application in medical image visualization.

Adult↗

PubMed2003

[On the correlation between the texture of contrast agent ultrasonic image and the intracardiac pressure].

Based on the application of box-counting fractal model to the texture analysis of ultrasonic image after intravenous injection of Levovist acoustics contrast agent in a dog, this paper presents a method to calculate the fractal dimension(D) and assistant characteristic (C(L)) of the ultrasonic images of left ventricle. It was found that the D and C(L) changed regularly in the continued cardiac cycles, that is, the maximum value of D appears during diastasis, the minimum value appears during end-systole; as the ventricular systole begins, D changes from maximum to smallness, and as the diastole begins, D changes from smallness to maximum; the maximum value of C(L) appears around end-systole, the minimum value appears around diastasis; from the start of left ventricular systole to end-systole, C(l) shows a tendency to change from smallness to maximum, and from the start of diastole to diastasis, it shows a tendency to change from maximum to smallness. The changes of D and C(L) are very similar to the changes of left ventricular pressure. It is thus evident that there is correlation between the fractal texture characteristics of the contrast agent ultrasonic images and the changes of intracardiac pressure. The results demonstrate that it is possible to measure the intracardiac pressure noninvasively.

Algorithms↗