Recently, there are many traffic accidents in turning right at an intersection. They are mainly caused by a driver's oversight of pedestrians and motorcycles that are occluded by oncoming cars. Therefore a system is necessary to detect moving objects such as oncoming cars and pedestrians at an intersection, and warn a vehicle driver. This paper describes a technique for detecting moving objects in turning right at an intersection when vehicle is stopping. Moving objects are detected by Mixture of Gaussians (MoG). In addition, we distinguish cars from pedestrians using the difference of the area size and the aspect ratio of detected objects. The object which is classified as a pedestrian is tracked using Lucas-Kanade Tracker. If the detected cars and pedestrians overlap or a car completely obscures pedestrians, we perform the estimation of pedestrian's location by using the information on past frames. By doing this, it is possible to detect pedestrians that drivers are actually difficult to see. The performance of the proposed technique was examined employing car videos and satisfactory results were obtained.
Automatic extraction/segmentation and the recognition of moving objects on a road environment is often problematic. This is especially the case when cameras are mounted on a moving vehicle (for vehicular vision), yet this remains a critical task in vision based safety transportation. The essential problem is twofold: extracting the foreground from the movingbackground, and separating and recognizing pedestrians from other moving objects such as cars that appear in the foreground.The challenge of our proposed technique is to use a single mobile camera for separating the foreground from the background, and to recognize pedestrians and other objects from vehicular vision in order to achieve a low cost and intelligent driver assistance system. In this paper, the normal distribution is employed for modelling pixel gray values. The proposed technique separates the foreground from the background by comparing the pixel gray values of an input image with the normal distribution model of the pixel. The model is renewed after the separation to give a new background model for the next image. The renewal strategy changes depending on if the concerned pixel is in the background or on the foreground. Performance of the present technique was examined by real world vehicle videos captured at a junction when a car turns left or right and satisfactory results were obtained.
Green nail syndrome is an infectious nail disorder caused most commonly by Pseudomonas aeruginosa. We report a rare case of peritoneal dialysis (PD) exit site infection (ESI) accompanied by P. aeruginosa-associated green nail syndrome. The patient was treated with oral and topical antibiotics without the need for PD catheter removal. We aim to emphasise the importance of nail assessment for ESI in patients undergoing PD.
Significance: Polyp size is important for selecting the surveillance interval or treatment policy. Nevertheless, it is challenging to accurately estimate the polyp size during endoscopy. An easy and cost-effective function to assist in polyp size estimation is required. Aim: To propose a virtual scale function for endoscopy and evaluate its performance and expected accuracy. Approach: An adaptive virtual scale behavior was demonstrated. The measurement error of the virtual scale along the distance between the tip of the endoscope and the object plane was evaluated using graph paper. The accuracy of polyp size estimation by an expert endoscopist was compared with the accuracy of the biopsy forceps method using phantom images. Results: The measurement errors of the virtual scale were ≤ 0.7 mm when the distance to the graph paper, which faced the tip of the endoscope, varied from 4 to 30 mm. The accuracy with the virtual scale was significantly higher than that obtained with biopsy forceps (5.3 ± 5.5 % versus 11.9 ± 9.4 % , P < 0.001). Conclusions: The virtual scale function, which operates in real-time without any additional device, can be used to estimate polyp sizes easily and accurately with endoscopy.
Chemosensitivity to cisplatin derivatives varies among individual patients with intractable malignancies including ovarian cancer, while how to unlock the resistance remain unknown. Ovarian cancer tissues were collected the debulking surgery in discovery- (n = 135) and validation- (n = 47) cohorts, to be analyzed with high-throughput automated immunohistochemistry which identified cystathionine γ-lyase (CSE) as an independent marker distinguishing non-responders from responders to post-operative platinum-based chemotherapy. We aimed to identify CSE-derived metabolites responsible for chemoresistant mechanisms: gold-nanoparticle (AuN)-based surface-enhanced Raman spectroscopy (SERS) was used to enhance electromagnetic fields which enabled to visualize multiple sulfur-containing metabolites through detecting scattering light from Au–S vibration two-dimensionally. Clear cell carcinoma (CCC) who turned out less sensitive to cisplatin than serous adenocarcinoma was classified into two groups by the intensities of SERS intensities at 480 cm−1; patients with greater intensities displayed the shorter overall survival after the debulking surgery. The SERS signals were eliminated by topically applied monobromobimane that breaks sulfane-sulfur bonds of polysulfides to result in formation of sulfodibimane which was detected at 580 cm−1, manifesting the presence of polysulfides in cancer tissues. CCC-derived cancer cell lines in culture were resistant against cisplatin, but treatment with ambroxol, an expectorant degrading polysulfides, renders the cells CDDP-susceptible. Co-administration of ambroxol with cisplatin significantly suppressed growth of cancer xenografts in nude mice. Furthermore, polysulfides, but neither glutathione nor hypotaurine, attenuated cisplatin-induced disturbance of DNA supercoiling. Polysulfide detection by on-tissue SERS thus enables to predict prognosis of cisplatin-based chemotherapy. The current findings suggest polysulfide degradation as a stratagem unlocking cisplatin chemoresistance.
