Qingli Li

Finger vein recognition with manifold learning

Finger vein is a promising biometric pattern for personal identification in terms of its security and convenience. However, so residual information, such as shade produced by various thicknesses of the finger muscles, bones, and tissue networks surrounding the vein, are also captured in the infrared images of finger vein. Meanwhile, the pose variation of the finger may also cause failure to recognition. In this paper, for the first time, we address this problem by unifying manifold learning and point manifold distance concept. The experiments based on the TED-FV database demonstrate that the proposed algorithmic framework is robust and effective.

Review of spectral imaging technology in biomedical engineering: achievements and challenges

Abstract. Spectral imaging is a technology that integrates conventional imaging and spectroscopy to get both spatial and spectral information from an object. Although this technology was originally developed for remote sensing, it has been extended to the biomedical engineering field as a powerful analytical tool for biological and biomedical research. This review introduces the basics of spectral imaging, imaging methods, current equipment, and recent advances in biomedical applications. The performance and analytical capabilities of spectral imaging systems for biological and biomedical imaging are discussed. In particular, the current achievements and limitations of this technology in biomedical engineering are presented. The benefits and development trends of biomedical spectral imaging are highlighted to provide the reader with an insight into the current technological advances and its potential for biomedical research.

Classification of hyperspectral medical tongue images for tongue diagnosis

Human tongue is one of the important organs of the body, which carries abound of information of the health status. The images of the human tongue that are used in computerized tongue diagnosis of traditional Chinese medicine (TCM) are all RGB color images captured with color CCD cameras currently. However, this conversional method impedes the accurate analysis on the subjects of tongue surface because of the influence of illumination and tongue pose. To address this problem, this paper presents a novel approach to analyze the tongue surface information based on hyperspectral medical tongue images with support vector machines. The experimental results based on chronic Cholecystitis patients and healthy volunteers illustrate its effectiveness.

Automated tongue segmentation in hyperspectral images for medicine

Automatic tongue area segmentation is crucial for computer aided tongue diagnosis, but traditional intensity-based segmentation methods that make use of monochromatic images cannot provide accurate and robust results. We propose a novel tongue segmentation method that uses hyperspectral images and the support vector machine. This method combines spatial and spectral information to analyze the medical tongue image and can provide much better tongue segmentation results. The promising experimental results and quantitative evaluations demonstrate that our method can provide much better performance than the traditional method.

Tongue tumor detection in medical hyperspectral images.

A hyperspectral imaging system to measure and analyze the reflectance spectra of the human tongue with high spatial resolution is proposed for tongue tumor detection. To achieve fast and accurate performance for detecting tongue tumors, reflectance data were collected using spectral acousto-optic tunable filters and a spectral adapter, and sparse representation was used for the data analysis algorithm. Based on the tumor image database, a recognition rate of 96.5% was achieved. The experimental results show that hyperspectral imaging for tongue tumor diagnosis, together with the spectroscopic classification method provide a new approach for the noninvasive computer-aided diagnosis of tongue tumors.

Tongue color analysis and discrimination based on hyperspectral images.

Human tongue is one of the important organs of the body, which carries abound of information of the health status. Among the various information on tongue, color is the most important factor. Most existing methods carry out pixel-wise or RGB color space classification in a tongue image captured with color CCD cameras. However, these conversional methods impede the accurate analysis on the subjects of tongue surface because of the less information of this kind of images. To address problems in RGB images, a pushbroom hyperspectral tongue imager is developed and its spectral response calibration method is discussed. A new approach to analyze tongue color based on spectra with spectral angle mapper is presented. In addition, 200 hyperspectral tongue images from the tongue image database were selected on which the color recognition is performed with the new method. The results of experiment show that the proposed method has good performance in terms of the rates of correctness for color recognition of tongue coatings and substances. The overall rate of correctness for each color category was 85% of tongue substances and 88% of tongue coatings with the new method. In addition, this algorithm can trace out the color distribution on the tongue surface which is very helpful for tongue disease diagnosis. The spectrum of organism can be used to retrieve organism colors more accurately. This new color analysis approach is superior to the traditional method especially in achieving meaningful areas of substances and coatings of tongue.

A novel hyperspectral medical sensor for tongue diagnosis

Purpose – Tongue diagnosis is a standard expert technique of traditional Chinese medicine (TCM). Computerized tongue diagnosis promises to automate the process of tongue diagnosis yet the tongue images segmentation upon which it depends is made difficult by the fact that the tongue is non‐rigid and varies greatly in size, shape, color, and texture. This paper presents a novel medical sensor system for TCM tongue diagnosis, which makes use of hyperspectral imaging technology.Design/methodology/approach – The tongue image capturing sensor device for Chinese medical is based on the theory of the pushbroom hyperspectral imager. The paper illustrates its advantages by detecting the tongue contour in the hyperspectral images.Findings – The experiments from 1,522 clinical tongue images show the validity of the system.Practical implications – In this paper, the authors propose to use hyperspectral technology for tongue diagnosis for the first time in the literature and obtain promising results.Originality/value –...

AOTF based molecular hyperspectral imaging system and its applications on nerve morphometry

The neuroanatomical morphology of nerve fibers is an important description for understanding the pathological aspects of nerves. Different from the traditional automatic nerve morphometry methods, a molecular hyperspectral imaging system based on an acousto-optic tunable filter (AOTF) was developed and used to identify unstained nerve histological sections. The hardware, software, and system performance of the imaging system are presented and discussed. The gray correction coefficient was used to calibrate the systems spectral response and to remove the effects of noises and artifacts. A spatial-spectral kernel-based approach through the support vector machine formulation was proposed to identify nerve fibers. This algorithm can jointly use both the spatial and spectral information of molecular hyperspectral images for segmentation. Then, the morphological parameters such as fiber diameter, axon diameter, myelin sheath thickness, fiber area, and g-ratio were calculated and evaluated. Experimental results show that the hyperspectral-based method has the potential to recognize and measure the nerve fiber more accurately than traditional methods.

Tongue fissure extraction and classification using hyperspectral imaging technology

Tongue fissures, an important feature on the tongue surface, may be pathologically related to some diseases. Most existing tongue fissure extraction methods use tongue images captured by traditional charge coupled device cameras. However, these conventional methods cannot be used for an accurate analysis of the tongue surface due to limited information from the images. To solve this, a hyperspectral tongue imager is used to capture tongue images instead of a digital camera. New algorithms for automatic tongue fissure extraction and classification, based on hyperspectral images, are presented. Both spectral and spatial information of the tongue surface is used to segment the tongue body and extract tongue fissures. Then a classification algorithm based on a hidden Markov model is used to classify tongue fissures into 12 typical categories. Results of the experiment show that the new method has good performance in terms of the classification rates of correctness.

New microscopic pushbroom hyperspectral imaging system for application in diabetic retinopathy research

To aid ophthalmologists in determining the pathogenesis of diabetic retinopathy and in evaluating the effects of medication, a microscopic pushbroom hyperspectral imaging system is developed. 40 healthy Wistar rats of half gender are selected in this study. They are divided into three groups (six rats failed to be models). 10 normal rats as the normal control group, 12 diabetic rats without any treatment as the model control group, and another 12 diabetic rats treated with LCVS1001 as the LCVS1001 group. The microscopic hyperspectral image of each retina section is collected and processed. Some typical spectrum curves between 400 and 800 nm of the outer nuclear layer are extracted, and images at various wavelengths are analyzed. The results show that a small trough appears near 522.2 nm in the typical spectrum curve of the model control group, and the transmittance of it is higher than that of the normal control group. In addition, the spectrum of the LCVS1001 group changes gradually to the normal spectrum after treatment with LCVS1001. Our findings indicate that LCVS1001 has some therapeutic effect on the diabetic retinopathy of rats, and the microscopic pushbroom hyperspectral imaging system can be used to study the pathogenesis of diabetic retinopathy.