Near-infrared Charge-coupled Device Research Articles

Infrared Sensor Detection and Actuator Treatment Applied during Hemodialysis.

Infrared thermography can be applied in different medical systems, for example it can be used to catch the images of living blood vessels. Far infrared rays can be used in a heating machine, which can be applied in the clinical hemodialysis patients. Infrared electronically sensitized images, which are generated by near-infrared Charge-coupled Device (CCD), are used to detect blood vessels, and used as a long-wavelength external stimulating therapeutic tissue repair system. When an infrared sensor detection and actuator treatment is applied during hemodialysis, a missing needle can be detected, and far infrared rays have a therapeutic effect on blood vessels. Because a far-infrared actuated light source can improve blood circulation, it is currently used to prevent fistula embolism in hemodialysis (HD) patients and reduce vascular occlusion after hemodialysis. Sensors used for sudden changes in heart rate variability (HRV) are used as predictive and evaluation indicators for our new method. Far-infrared actuated radiation can increase sympathetic nerve activity and regulation of parasympathetic and sympathetic nerves. We performed baseline measurements of the low-frequency/high-frequency ratio of autonomic nerve activity before hemodialysis (low frequency (LF), high frequency (HF), LF/HF, before HD) and after hemodialysis (LF/HF, after-HD). Based on data from the HRV continuity tracking report, 35 patients with autonomic nerve activation were treated and evaluated. We have demonstrated that the resulting near-infrared (NIR) sensor imaging and far-infrared actuator illumination can be used for the detection and treatment of hemodialysis patients.

Improved Arterial Preservation Achieved by Combined Use of Indocyanine Green Angiography and Doppler Detector During Microsurgical Subinguinal Varicocelectomy

Objectives: The microsurgical approach is considered the most reliable procedure in varicocelectomy. However, as there are difficulties in identifying the spermatic artery at the peripheral level, we had introduced intraoperative indocyanine green angiography (ICGA) for identification of arteries. In this study, we further investigated the usefulness of intraoperative ICGA in combination with an ordinary Doppler detector in microsurgical subinguinal varicocelectomy. Methods: A total of 140 men who underwent microsurgical subinguinal varicocelectomy at Gunma University Hospital were included. An operating microscope equipped with a near-infrared charge-coupled device was used for intraoperative ICGA. After exposing the vessels, arteries were identified using endoscopic vision only or with assistance of Doppler detector or ICGA, or of both. The number of preserved arteries was compared among the groups. Results: ICGA clearly visualized the internal spermatic arteries in all cases, allowing the surgeon to perform real-time identification and isolation of the spermatic artery intraoperatively. The use of ICGA or Doppler detector significantly increased the number of preserved arteries compared to the microscope-only operation from 1.11 to 1.75 (p < 0.05) and 1.57 (p < 0.05), respectively. The additional use of ICGA with Doppler detector further increased the number of preserved arteries to 2.41 (p < 0.05). Conclusions: Intraoperative ICGA facilitated safe and quick microsurgical subinguinal varicocelectomy by enabling visualization of thin spermatic cord blood vessels. Improved preservation of thin arteries, which is essential for patients with infertility, can be achieved with the combined use of ICGA and ordinary Doppler detector.

Dorsal hand vein recognition based on 2D Gabor filters

Hand vein patterns are among the biometric traits being investigated today for identification purposes, attracting interest from both the research community and industry. A reliable and robust personal verification approach using dorsal hand vein patterns is presented in this paper. This approach needs less computational and memory requirements and has a higher recognition accuracy than similar methods. In our work, a near-infrared charge-coupled device camera is adopted as an input device for capturing dorsal hand vein images, due to its advantages of the low-cost and non-contact imaging. In the proposed approach, two finger-peaks are automatically selected to define the region of interest in the dorsal hand vein images. In order to obtain effective pattern of dorsal hand vein vascular, we proposed an innovative and robust adaptive Gabor filter method to extract the dorsal hand vein patterns and encode the vein features in bit string representation. The bit string representation, called VeinCode, offers speedy template matching and enables more effective template storage and retrieval. The similarity of two VeinCodes is measured by normalised Hamming distance. A total of 6160 dorsal hand vein images were collected from 308 persons to verify the validity of the proposed dorsal hand vein recognition approach. High accuracies (>99%) have been obtained by the proposed method, and the speed of the method (responding time <0·8 s) is rapid enough for real-time recognition. Experimental results demonstrate that our proposed approach is feasible and effective for dorsal hand vein recognition.

Palm vein recognition based on a modified $$\text{(2D)}^{2}\text{ LDA}$$

Biometric computing offers an effective approach to personal identification based on unique, stable physical or behavioral characteristics. A reliable and robust personal verification approach using palm vein patterns is presented in this paper. This approach has lower computational and memory requirements and a higher recognition accuracy than similar methods. In my work, a near-infrared charge-coupled device camera is adopted as an input device for capturing palm vein images, since it can provide low-cost, non-contact imaging. In the proposed approach, two finger-webs are automatically selected to define the region of interest (ROI) in the palm vein images. Modified two-directional two-dimensional linear discriminant analysis (\(\text{(2D)}^{2}\text{ LDA}\)), which performs an alternate two-dimensional LDA (2DLDA) in the column direction of images in the 2DLDA subspace, is proposed to exploit the correlation between rows and columns of palm vein features inside the ROI. The major advantage of the method is that it requires fewer coefficients for efficient palm vein image representation and recognition. A total of 4,140 palm vein images were collected from 207 persons to verify the validity of the proposed palm vein recognition approach. High accuracies (\(>\)99 %) have been obtained by the proposed method, and the speed of the method (response time \(<\)0.75 s) is rapid enough for real-time recognition. Experimental results demonstrate that the proposed approach is feasible and effective for palm vein recognition.

Personal authentication through dorsal hand vein patterns

Biometric identification is an emerging technology that can solve security problems in our networked society. A reliable and robust personal verification approach using dorsal hand vein patterns is proposed in this paper. The characteristic of the approach needs less computational and memory requirements and has a higher recognition accuracy. In our work, the near-infrared charge-coupled device (CCD) camera is adopted as an input device for capturing dorsal hand vein images, it has the advantages of the low-cost and noncontact imaging. In the proposed approach, two finger-peaks are automatically selected as the datum points to define the region of interest (ROI) in the dorsal hand vein images. The modified two-directional two-dimensional principal component analysis, which performs an alternate two-dimensional PCA (2DPCA) in the column direction of images in the 2DPCA subspace, is proposed to exploit the correlation of vein features inside the ROI between images. The major advantage of the proposed method is that it requires fewer coefficients for efficient dorsal hand vein image representation and recognition. The experimental results on our large dorsal hand vein database show that the presented schema achieves promising performance (false reject rate: 0.97% and false acceptance rate: 0.05%) and is feasible for dorsal hand vein recognition.

Colors of Objects in the Field of the Double Quasi-Stellar Object 1146+111B,C

Color images of faint objects were used to test two hypotheses for the quasi-stellar object (QSO) pair 1146+ 111B,C: gravitational lens or massive string. Blue, red, and near-infrared CCD (charge-coupled device) images of the field of this QSO pair were examined for gravitational lens multiple-image candidates for all four QSO's in the field (B, C, D, and E). No third image of 1146+111B,C was found, down to 4 magnitudes fainter than BC. This result implies a compact lens mass distribution, if B and C are images of the same QSO. C appears to be redder than B in the wavelength region from 700 to 1100 nanometers. This raises the question of whether B and C are images of the same QSO. Three blue stellar objects of unusual color were found at plausible locations for multiple images of the other two QSO's in the field. A very red object was found at a plausible lens position. Under the hypothesis that B and C are lensed images, these color data severely restrict the possible lens models and imaged QSO multiplicities. One possibility is a compact lens mass of 4 x 10(15) solar masses at a redshift of 0.8. Another is an S-shaped massive string. If the spectrum of any of the three anomalous blue objects were available, it would be possible to distinguish between these two models. However, it is difficult to fit the color and intensity data reported here to either simple string or black hole models. Overall, the simplest model consistent with all the data is the no-lens, no-string hypothesis: B and C probably are separate QSO's, but with some spectral similarities.