This paper describes the development of a signal and image processing system for the hyperspectral biomedical imager (HBI). The HBI forms hyperspectral images of human tissue with high spatial and spectral resolution. The final goal of the research project is to develop a fully functional HBI image formation/processing system based on Texas Instrument's TMS320C6X floating-point digital signal processing (DSP) chip. This would permit fast and efficient data processing, enhancing the utility of the HBI.
An optical imaging device of retina function (OID-RF) has been developed to measure changes in blood oxygen saturation due to neural activity resulting from visual stimulation of the photoreceptors in the human retina. The video data that are collected represent a mixture of the functional signal in response to the retinal activation and other signals from undetermined physiological activity. Measured changes in reflectance in response to the visual stimulus are on the order of 0.1% to 1.0% of the total reflected intensity level which makes the functional signal difficult to detect by standard methods since it is masked by the other signals that are present. In this paper, we apply principal component analysis (PCA), blind source separation (BSS), using Extended Spatial Decorrelation (ESD) and independent component analysis (ICA) using the Fast-ICA algorithm to extract the functional signal from the retinal videos. The results revealed that the functional signal in a stimulated retina can be detected through the application of some of these techniques.
This paper demonstrates the utility of spectral imaging for improvement in visualization of pathologic lesions and normal anatomical tissue. Traditional color images produced by current film and digital cameras are limited in the information that is provided to the physician for detecting and subsequently diagnosing retinal disorders. A high-resolution spectral fundus imaging system was developed and tested on human subjects. Spectral images were found to provide new insight into the lesions usually classified by ophthalmologists in terms of color and morphology. Analysis of spectral data had strong correlation to the qualitative classification of drusen; however, there appeared to be subclasses of the same drusen. This finding may lead to a redefinition of drusen classes that could improve correlation of drusen to the risk assessment in epidemiological studies.
An optical imaging device of retina function (OID-RF) has been constructed to record changes in reflected 700-nm light from the fundus caused by retinal activation in response to a visual 535-nm stimulus. The resulting images reveal areas of the retina activated by visual stimulation. This device is a modified fundus camera designed to provide a patterned, moving visual stimulus over a 45-degree field of view to the subject in the green wavelength portion of the visual spectrum while simultaneously imaging the fundus in another, longer wavelength range. Data was collected from 3 normal subjects and recorded for 13 seconds at 4 Hz; 3 seconds were recorded during pre-stimulus baseline, 5 seconds during the stimulus, and 5 seconds post-stimulus. This procedure was repeated several times and, after image registration, the images were averaged to improve signal to noise. The change in reflected intensity from the retina due to the stimulus was then calculated by comparison to the pre-stimulus state. Reflected intensity from areas of stimulated retina began to increase steadily within 1 second after stimulus onset and decayed after stimulus offset. These results indicated that a functional optical signal can be recorded from the human eye.
Coronary arteriography is a technique used for evaluating the state of coronary arteries and assessing the need for bypass surgery and angioplasty. The present clinical application of this technology is based on the use of a contrast medium for manual radiographic visualization. This method is inaccurate due to varying interpretation of the visual results. Coronary arteriography based quantitations are impractical in a clinical setting without the use of automatic techniques applied to the 3-D reconstruction of the arterial tree. Such a system will provide an easily reproducible method for following the temporal changes in coronary morphology. The labeling of the arteries and establishing of the correspondence between multiple views is necessary for all subsequent processing required for 3-D reconstruction. This work represents a rule based expert system utilized for automatic labeling and segmentation of the arterial branches across multiple views. X-ray data of two and three views of human subjects and a pig arterial cast have been used for this research.
Visual and photographic examination of the back of the eye, or fundus, is a critical tool in diagnosing and monitoring both ocular and systemic diseases. Current techniques are not optimized for visualization of fundus tissue classes. High-resolution spectral imaging, which measures the spectral properties at spatially resolved points across the scene, has been applied to the examination of the ocular fundus. Spectral features resulting from this data provide good and consistent separation of the fundus tissue classes corresponding to normal anatomy.
