Semi-automatic assessment of skin capillary density: proof of principle and validation.

PubMed

Gronenschild, E H B M; Muris, D M J; Schram, M T; Karaca, U; Stehouwer, C D A; Houben, A J H M

2013-11-01

Skin capillary density and recruitment have been proven to be relevant measures of microvascular function. Unfortunately, the assessment of skin capillary density from movie files is very time-consuming, since this is done manually. This impedes the use of this technique in large-scale studies. We aimed to develop a (semi-) automated assessment of skin capillary density. CapiAna (Capillary Analysis) is a newly developed semi-automatic image analysis application. The technique involves four steps: 1) movement correction, 2) selection of the frame range and positioning of the region of interest (ROI), 3) automatic detection of capillaries, and 4) manual correction of detected capillaries. To gain insight into the performance of the technique, skin capillary density was measured in twenty participants (ten women; mean age 56.2 [42-72] years). To investigate the agreement between CapiAna and the classic manual counting procedure, we used weighted Deming regression and Bland-Altman analyses. In addition, intra- and inter-observer coefficients of variation (CVs), and differences in analysis time were assessed. We found a good agreement between CapiAna and the classic manual method, with a Pearson's correlation coefficient (r) of 0.95 (P<0.001) and a Deming regression coefficient of 1.01 (95%CI: 0.91; 1.10). In addition, we found no significant differences between the two methods, with an intercept of the Deming regression of 1.75 (-6.04; 9.54), while the Bland-Altman analysis showed a mean difference (bias) of 2.0 (-13.5; 18.4) capillaries/mm(2). The intra- and inter-observer CVs of CapiAna were 2.5% and 5.6% respectively, while for the classic manual counting procedure these were 3.2% and 7.2%, respectively. Finally, the analysis time for CapiAna ranged between 25 and 35min versus 80 and 95min for the manual counting procedure. We have developed a semi-automatic image analysis application (CapiAna) for the assessment of skin capillary density, which agrees well with the classic manual counting procedure, is time-saving, and has a better reproducibility as compared to the classic manual counting procedure. As a result, the use of skin capillaroscopy is feasible in large-scale studies, which importantly extends the possibilities to perform microcirculation research in humans. © 2013.

Generalized procrustean image deformation for subtraction of mammograms

NASA Astrophysics Data System (ADS)

Good, Walter F.; Zheng, Bin; Chang, Yuan-Hsiang; Wang, Xiao Hui; Maitz, Glenn S.

1999-05-01

This project is a preliminary evaluation of two simple fully automatic nonlinear transformations which can map any mammographic image onto a reference image while guaranteeing registration of specific features. The first method automatically identifies skin lines, after which each pixel is given coordinates in the range [0,1] X [0,1], where the actual value of a coordinate is the fractional distance of the pixel between tissue boundaries in either the horizontal or vertical direction. This insures that skin lines are put in registration. The second method, which is the method of primary interest, automatically detects pectoral muscles, skin lines and nipple locations. For each image, a polar coordinate system is established with its origin at the intersection of the nipple axes line (NAL) and a line indicating the pectoral muscle. Points within a mammogram are identified by the angle of their position vector, relative to the NAL, and by their fractional distance between the origin and the skin line. This deforms mammograms in such a way that their pectoral lines, NALs and skin lines are all in registration. After images are deformed, their grayscales are adjusted by applying linear regression to pixel value pairs for corresponding tissue pixels. In a comparison of these methods to a previously reported 'translation/rotation' technique, evaluation of difference images clearly indicates that the polar coordinates method results in the most accurate registration of the transformations considered.

Automatic Skin Lesion Segmentation Using Deep Fully Convolutional Networks With Jaccard Distance.

PubMed

Yuan, Yading; Chao, Ming; Lo, Yeh-Chi

2017-09-01

Automatic skin lesion segmentation in dermoscopic images is a challenging task due to the low contrast between lesion and the surrounding skin, the irregular and fuzzy lesion borders, the existence of various artifacts, and various imaging acquisition conditions. In this paper, we present a fully automatic method for skin lesion segmentation by leveraging 19-layer deep convolutional neural networks that is trained end-to-end and does not rely on prior knowledge of the data. We propose a set of strategies to ensure effective and efficient learning with limited training data. Furthermore, we design a novel loss function based on Jaccard distance to eliminate the need of sample re-weighting, a typical procedure when using cross entropy as the loss function for image segmentation due to the strong imbalance between the number of foreground and background pixels. We evaluated the effectiveness, efficiency, as well as the generalization capability of the proposed framework on two publicly available databases. One is from ISBI 2016 skin lesion analysis towards melanoma detection challenge, and the other is the PH2 database. Experimental results showed that the proposed method outperformed other state-of-the-art algorithms on these two databases. Our method is general enough and only needs minimum pre- and post-processing, which allows its adoption in a variety of medical image segmentation tasks.

Hair segmentation using adaptive threshold from edge and branch length measures.

PubMed

Lee, Ian; Du, Xian; Anthony, Brian

2017-10-01

Non-invasive imaging techniques allow the monitoring of skin structure and diagnosis of skin diseases in clinical applications. However, hair in skin images hampers the imaging and classification of the skin structure of interest. Although many hair segmentation methods have been proposed for digital hair removal, a major challenge in hair segmentation remains in detecting hairs that are thin, overlapping, of similar contrast or color to underlying skin, or overlaid on highly-textured skin structure. To solve the problem, we present an automatic hair segmentation method that uses edge density (ED) and mean branch length (MBL) to measure hair. First, hair is detected by the integration of top-hat transform and modified second-order Gaussian filter. Second, we employ a robust adaptive threshold of ED and MBL to generate a hair mask. Third, the hair mask is refined by k-NN classification of hair and skin pixels. The proposed algorithm was tested using two datasets of healthy skin images and lesion images respectively. These datasets were taken from different imaging platforms in various illumination levels and varying skin colors. We compared the hair detection and segmentation results from our algorithm and six other hair segmentation methods of state of the art. Our method exhibits high value of sensitivity: 75% and specificity: 95%, which indicates significantly higher accuracy and better balance between true positive and false positive detection than the other methods. Published by Elsevier Ltd.

Skin image illumination modeling and chromophore identification for melanoma diagnosis

NASA Astrophysics Data System (ADS)

Liu, Zhao; Zerubia, Josiane

2015-05-01

The presence of illumination variation in dermatological images has a negative impact on the automatic detection and analysis of cutaneous lesions. This paper proposes a new illumination modeling and chromophore identification method to correct lighting variation in skin lesion images, as well as to extract melanin and hemoglobin concentrations of human skin, based on an adaptive bilateral decomposition and a weighted polynomial curve fitting, with the knowledge of a multi-layered skin model. Different from state-of-the-art approaches based on the Lambert law, the proposed method, considering both specular reflection and diffuse reflection of the skin, enables us to address highlight and strong shading effects usually existing in skin color images captured in an uncontrolled environment. The derived melanin and hemoglobin indices, directly relating to the pathological tissue conditions, tend to be less influenced by external imaging factors and are more efficient in describing pigmentation distributions. Experiments show that the proposed method gave better visual results and superior lesion segmentation, when compared to two other illumination correction algorithms, both designed specifically for dermatological images. For computer-aided diagnosis of melanoma, sensitivity achieves 85.52% when using our chromophore descriptors, which is 8~20% higher than those derived from other color descriptors. This demonstrates the benefit of the proposed method for automatic skin disease analysis.

Comparison of computer systems and ranking criteria for automatic melanoma detection in dermoscopic images.

PubMed

Møllersen, Kajsa; Zortea, Maciel; Schopf, Thomas R; Kirchesch, Herbert; Godtliebsen, Fred

2017-01-01

Melanoma is the deadliest form of skin cancer, and early detection is crucial for patient survival. Computer systems can assist in melanoma detection, but are not widespread in clinical practice. In 2016, an open challenge in classification of dermoscopic images of skin lesions was announced. A training set of 900 images with corresponding class labels and semi-automatic/manual segmentation masks was released for the challenge. An independent test set of 379 images, of which 75 were of melanomas, was used to rank the participants. This article demonstrates the impact of ranking criteria, segmentation method and classifier, and highlights the clinical perspective. We compare five different measures for diagnostic accuracy by analysing the resulting ranking of the computer systems in the challenge. Choice of performance measure had great impact on the ranking. Systems that were ranked among the top three for one measure, dropped to the bottom half when changing performance measure. Nevus Doctor, a computer system previously developed by the authors, was used to participate in the challenge, and investigate the impact of segmentation and classifier. The diagnostic accuracy when using an automatic versus the semi-automatic/manual segmentation is investigated. The unexpected small impact of segmentation method suggests that improvements of the automatic segmentation method w.r.t. resemblance to semi-automatic/manual segmentation will not improve diagnostic accuracy substantially. A small set of similar classification algorithms are used to investigate the impact of classifier on the diagnostic accuracy. The variability in diagnostic accuracy for different classifier algorithms was larger than the variability for segmentation methods, and suggests a focus for future investigations. From a clinical perspective, the misclassification of a melanoma as benign has far greater cost than the misclassification of a benign lesion. For computer systems to have clinical impact, their performance should be ranked by a high-sensitivity measure.

Hyperspectral imaging for melanoma screening

NASA Astrophysics Data System (ADS)

Martin, Justin; Krueger, James; Gareau, Daniel

2014-03-01

The 5-year survival rate for patients diagnosed with Melanoma, a deadly form of skin cancer, in its latest stages is about 15%, compared to over 90% for early detection and treatment. We present an imaging system and algorithm that can be used to automatically generate a melanoma risk score to aid clinicians in the early identification of this form of skin cancer. Our system images the patient's skin at a series of different wavelengths and then analyzes several key dermoscopic features to generate this risk score. We have found that shorter wavelengths of light are sensitive to information in the superficial areas of the skin while longer wavelengths can be used to gather information at greater depths. This accompanying diagnostic computer algorithm has demonstrated much higher sensitivity and specificity than the currently commercialized system in preliminary trials and has the potential to improve the early detection of melanoma.

In vivo classification of human skin burns using machine learning and quantitative features captured by optical coherence tomography

NASA Astrophysics Data System (ADS)

Singla, Neeru; Srivastava, Vishal; Singh Mehta, Dalip

2018-02-01

We report the first fully automated detection of human skin burn injuries in vivo, with the goal of automatic surgical margin assessment based on optical coherence tomography (OCT) images. Our proposed automated procedure entails building a machine-learning-based classifier by extracting quantitative features from normal and burn tissue images recorded by OCT. In this study, 56 samples (28 normal, 28 burned) were imaged by OCT and eight features were extracted. A linear model classifier was trained using 34 samples and 22 samples were used to test the model. Sensitivity of 91.6% and specificity of 90% were obtained. Our results demonstrate the capability of a computer-aided technique for accurately and automatically identifying burn tissue resection margins during surgical treatment.

Automatic segmentation and centroid detection of skin sensors for lung interventions

NASA Astrophysics Data System (ADS)

Lu, Kongkuo; Xu, Sheng; Xue, Zhong; Wong, Stephen T.

2012-02-01

Electromagnetic (EM) tracking has been recognized as a valuable tool for locating the interventional devices in procedures such as lung and liver biopsy or ablation. The advantage of this technology is its real-time connection to the 3D volumetric roadmap, i.e. CT, of a patient's anatomy while the intervention is performed. EM-based guidance requires tracking of the tip of the interventional device, transforming the location of the device onto pre-operative CT images, and superimposing the device in the 3D images to assist physicians to complete the procedure more effectively. A key requirement of this data integration is to find automatically the mapping between EM and CT coordinate systems. Thus, skin fiducial sensors are attached to patients before acquiring the pre-operative CTs. Then, those sensors can be recognized in both CT and EM coordinate systems and used calculate the transformation matrix. In this paper, to enable the EM-based navigation workflow and reduce procedural preparation time, an automatic fiducial detection method is proposed to obtain the centroids of the sensors from the pre-operative CT. The approach has been applied to 13 rabbit datasets derived from an animal study and eight human images from an observation study. The numerical results show that it is a reliable and efficient method for use in EM-guided application.

Three-phase general border detection method for dermoscopy images using non-uniform illumination correction.

PubMed

Norton, Kerri-Ann; Iyatomi, Hitoshi; Celebi, M Emre; Ishizaki, Sumiko; Sawada, Mizuki; Suzaki, Reiko; Kobayashi, Ken; Tanaka, Masaru; Ogawa, Koichi

2012-08-01

Computer-aided diagnosis of dermoscopy images has shown great promise in developing a quantitative, objective way of classifying skin lesions. An important step in the classification process is lesion segmentation. Many studies have been successful in segmenting melanocytic skin lesions (MSLs), but few have focused on non-melanocytic skin lesions (NoMSLs), as the wide variety of lesions makes accurate segmentation difficult. We developed an automatic segmentation program for detecting borders of skin lesions in dermoscopy images. The method consists of a pre-processing phase, general lesion segmentation phase, including illumination correction, and bright region segmentation phase. We tested our method on a set of 107 NoMSLs and a set of 319 MSLs. Our method achieved precision/recall scores of 84.5% and 88.5% for NoMSLs, and 93.9% and 93.8% for MSLs, in comparison with manual extractions from four or five dermatologists. The accuracy of our method was competitive or better than five recently published methods. Our new method is the first method for detecting borders of both non-melanocytic and melanocytic skin lesions. © 2011 John Wiley & Sons A/S.

Skin Lesion Analysis towards Melanoma Detection Using Deep Learning Network.

PubMed

Li, Yuexiang; Shen, Linlin

2018-02-11

Skin lesions are a severe disease globally. Early detection of melanoma in dermoscopy images significantly increases the survival rate. However, the accurate recognition of melanoma is extremely challenging due to the following reasons: low contrast between lesions and skin, visual similarity between melanoma and non-melanoma lesions, etc. Hence, reliable automatic detection of skin tumors is very useful to increase the accuracy and efficiency of pathologists. In this paper, we proposed two deep learning methods to address three main tasks emerging in the area of skin lesion image processing, i.e., lesion segmentation (task 1), lesion dermoscopic feature extraction (task 2) and lesion classification (task 3). A deep learning framework consisting of two fully convolutional residual networks (FCRN) is proposed to simultaneously produce the segmentation result and the coarse classification result. A lesion index calculation unit (LICU) is developed to refine the coarse classification results by calculating the distance heat-map. A straight-forward CNN is proposed for the dermoscopic feature extraction task. The proposed deep learning frameworks were evaluated on the ISIC 2017 dataset. Experimental results show the promising accuracies of our frameworks, i.e., 0.753 for task 1, 0.848 for task 2 and 0.912 for task 3 were achieved.

Fabrication of subcutaneous veins phantom for vessel visualization system

NASA Astrophysics Data System (ADS)

Cheng, Kai; Narita, Kazuyuki; Morita, Yusuke; Nakamachi, Eiji; Honda, Norihiro; Awazu, Kunio

2013-09-01

The technique of subcutaneous veins imaging by using NIR (Near Infrared Radiation) is widely used in medical applications, such as the intravenous injection and the blood sampling. In the previous study, an automatic 3D blood vessel search and automatic blood sampling system was newly developed. In order to validate this NIR imaging system, we adopted the subcutaneous vein in the human arm and its artificial phantom, which imitate the human fat and blood vessel. The human skin and subcutaneous vein is characterized as the uncertainty object, which has the individual specificity, non-accurate depth information, non-steady state and hardly to be fixed in the examination apparatus. On the other hand, the conventional phantom was quite distinct from the human's characteristics, such as the non-multilayer structure, disagreement of optical property. In this study, we develop a multilayer phantom, which is quite similar with human skin, for improvement of NIR detection system evaluation. The phantom consists of three layers, such as the epidermis layer, the dermis layer and the subcutaneous fat layer. In subcutaneous fat layer, we built a blood vessel. We use the intralipid to imitate the optical scattering characteristics of human skin, and the hemoglobin and melanin for the optical absorption characteristics. In this study, we did two subjects. First, we decide the fabrication process of the phantom. Second, we compared newly developed phantoms with human skin by using our NIR detecting system, and confirm the availability of these phantoms.

An Automatic Diagnosis Method of Facial Acne Vulgaris Based on Convolutional Neural Network.

PubMed

Shen, Xiaolei; Zhang, Jiachi; Yan, Chenjun; Zhou, Hong

2018-04-11

In this paper, we present a new automatic diagnosis method for facial acne vulgaris which is based on convolutional neural networks (CNNs). To overcome the shortcomings of previous methods which were the inability to classify enough types of acne vulgaris. The core of our method is to extract features of images based on CNNs and achieve classification by classifier. A binary-classifier of skin-and-non-skin is used to detect skin area and a seven-classifier is used to achieve the classification task of facial acne vulgaris and healthy skin. In the experiments, we compare the effectiveness of our CNN and the VGG16 neural network which is pre-trained on the ImageNet data set. We use a ROC curve to evaluate the performance of binary-classifier and use a normalized confusion matrix to evaluate the performance of seven-classifier. The results of our experiments show that the pre-trained VGG16 neural network is effective in extracting features from facial acne vulgaris images. And the features are very useful for the follow-up classifiers. Finally, we try applying the classifiers both based on the pre-trained VGG16 neural network to assist doctors in facial acne vulgaris diagnosis.

Human skin surface evaluation by image processing

NASA Astrophysics Data System (ADS)

Zhu, Liangen; Zhan, Xuemin; Xie, Fengying

2003-12-01

Human skin gradually lose its tension and becomes very dry as time flies by. Use of cosmetics is effective to prevent skin aging. Recently, there are many choices of products of cosmetics. To show their effects, It is desirable to develop a way to evaluate quantificationally skin surface condition. In this paper, An automatic skin evaluating method is proposed. The skin surface has the pattern called grid-texture. This pattern is composed of the valleys that spread vertically, horizontally, and obliquely and the hills separated by them. Changes of the grid are closely linked to the skin surface condition. They can serve as a good indicator for the skin condition. By measuring the skin grid using digital image processing technologies, we can evaluate skin surface about its aging, health, and alimentary status. In this method, the skin grid is first detected to form a closed net. Then, some skin parameters such as Roughness, tension, scale and gloss can be calculated from the statistical measurements of the net. Through analyzing these parameters, the condition of the skin can be monitored.

Human facial skin detection in thermal video to effectively measure electrodermal activity (EDA)

NASA Astrophysics Data System (ADS)

Kaur, Balvinder; Hutchinson, J. Andrew; Leonard, Kevin R.; Nelson, Jill K.

2011-06-01

In the past, autonomic nervous system response has often been determined through measuring Electrodermal Activity (EDA), sometimes referred to as Skin Conductance (SC). Recent work has shown that high resolution thermal cameras can passively and remotely obtain an analog to EDA by assessing the activation of facial eccrine skin pores. This paper investigates a method to distinguish facial skin from non-skin portions on the face to generate a skin-only Dynamic Mask (DM), validates the DM results, and demonstrates DM performance by removing false pore counts. Moreover, this paper shows results from these techniques using data from 20+ subjects across two different experiments. In the first experiment, subjects were presented with primary screening questions for which some had jeopardy. In the second experiment, subjects experienced standard emotion-eliciting stimuli. The results from using this technique will be shown in relation to data and human perception (ground truth). This paper introduces an automatic end-to-end skin detection approach based on texture feature vectors. In doing so, the paper contributes not only a new capability of tracking facial skin in thermal imagery, but also enhances our capability to provide non-contact, remote, passive, and real-time methods for determining autonomic nervous system responses for medical and security applications.

Skin Lesion Analysis towards Melanoma Detection Using Deep Learning Network

PubMed Central

2018-01-01

Skin lesions are a severe disease globally. Early detection of melanoma in dermoscopy images significantly increases the survival rate. However, the accurate recognition of melanoma is extremely challenging due to the following reasons: low contrast between lesions and skin, visual similarity between melanoma and non-melanoma lesions, etc. Hence, reliable automatic detection of skin tumors is very useful to increase the accuracy and efficiency of pathologists. In this paper, we proposed two deep learning methods to address three main tasks emerging in the area of skin lesion image processing, i.e., lesion segmentation (task 1), lesion dermoscopic feature extraction (task 2) and lesion classification (task 3). A deep learning framework consisting of two fully convolutional residual networks (FCRN) is proposed to simultaneously produce the segmentation result and the coarse classification result. A lesion index calculation unit (LICU) is developed to refine the coarse classification results by calculating the distance heat-map. A straight-forward CNN is proposed for the dermoscopic feature extraction task. The proposed deep learning frameworks were evaluated on the ISIC 2017 dataset. Experimental results show the promising accuracies of our frameworks, i.e., 0.753 for task 1, 0.848 for task 2 and 0.912 for task 3 were achieved. PMID:29439500

Automatic measurement of skin textures of the dorsal hand in evaluating skin aging.

PubMed

Gao, Qian; Yu, Jiaming; Wang, Fang; Ge, Tiantian; Hu, Liwen; Liu, Yang

2013-05-01

Changes in skin textures have been used to evaluate skin aging in many studies. In our previous study, we built some skin texture parameters, which can be used to evaluate skin aging of human dorsal hand. However, it will take too much time and need to work arduously to get the information from digital skin image by manual work. So, we want to build a simple and effective method to automatically count some of those skin texture parameters by using digital image-processing technology. A total of 100 subjects aged 30 years and above were involved. Sun exposure history and demographic information were collected by using a questionnaire. The skin image of subjects' dorsal hand was obtained by using a portable skin detector. The number of grids, which is one of skin texture parameters built in our previous study, was measured manually and automatically. Automated image analysis program was developed by using Matlab 7.1 software. The number of grids counted automatically (NGA) was significantly correlated with the number of grids counted manually (NGM) (r = 0.9287, P < 0.0001). And in each age group, there were no significant differences between NGA and NGM. The NGA was negatively correlated with age and lifetime sun exposure, and decreased with increasing Beagley-Gibson score from 3 to 6. In addition, even after adjusting for NGA, the standard deviation of grid areas for each image was positively correlated with age, sun exposure, and Bealey-Gibson score. The method introduced in present study can be used to measure some skin aging parameters automatically and objectively. And it will save much time, reduce labor, and avoid measurement errors of deferent investigators when evaluating a great deal of skin images in a short time. © 2013 John Wiley & Sons A/S. Published by Blackwell Publishing Ltd.

A Study on the Development of a Robot-Assisted Automatic Laser Hair Removal System

PubMed Central

Lim, Hyoung-woo; Park, Sungwoo; Noh, Seungwoo; Lee, Dong-Hun; Yoon, Chiyul; Koh, Wooseok; Kim, Youdan; Chung, Jin Ho; Kim, Hee Chan

2014-01-01

Abstract Background and Objective: The robot-assisted automatic laser hair removal (LHR) system is developed to automatically detect any arbitrary shape of the desired LHR treatment area and to provide uniform laser irradiation to the designated skin area. Methods: For uniform delivery of laser energy, a unit of a commercial LHR device, a laser distance sensor, and a high-resolution webcam are attached at the six axis industrial robot's end-effector, which can be easily controlled using a graphical user interface (GUI). During the treatment, the system provides real-time treatment progress as well as the total number of “pick and place” automatically. Results: During the test, it was demonstrated that the arbitrary shapes were detected, and that the laser was delivered uniformly. The localization error test and the area-per-spot test produced satisfactory outcome averages of 1.04 mm error and 38.22 mm2/spot, respectively. Conclusions: Results showed that the system successfully demonstrated accuracy and effectiveness. The proposed system is expected to become a promising device in LHR treatment. PMID:25343281

A study on the development of a robot-assisted automatic laser hair removal system.

PubMed

Lim, Hyoung-Woo; Park, Sungwoo; Noh, Seungwoo; Lee, Dong-Hun; Yoon, Chiyul; Koh, Wooseok; Kim, Youdan; Chung, Jin Ho; Kim, Hee Chan; Kim, Sungwan

2014-11-01

Abstract Background and Objective: The robot-assisted automatic laser hair removal (LHR) system is developed to automatically detect any arbitrary shape of the desired LHR treatment area and to provide uniform laser irradiation to the designated skin area. For uniform delivery of laser energy, a unit of a commercial LHR device, a laser distance sensor, and a high-resolution webcam are attached at the six axis industrial robot's end-effector, which can be easily controlled using a graphical user interface (GUI). During the treatment, the system provides real-time treatment progress as well as the total number of "pick and place" automatically. During the test, it was demonstrated that the arbitrary shapes were detected, and that the laser was delivered uniformly. The localization error test and the area-per-spot test produced satisfactory outcome averages of 1.04 mm error and 38.22 mm(2)/spot, respectively. RESULTS showed that the system successfully demonstrated accuracy and effectiveness. The proposed system is expected to become a promising device in LHR treatment.

Computer Based Melanocytic and Nevus Image Enhancement and Segmentation.

PubMed

Jamil, Uzma; Akram, M Usman; Khalid, Shehzad; Abbas, Sarmad; Saleem, Kashif

2016-01-01

Digital dermoscopy aids dermatologists in monitoring potentially cancerous skin lesions. Melanoma is the 5th common form of skin cancer that is rare but the most dangerous. Melanoma is curable if it is detected at an early stage. Automated segmentation of cancerous lesion from normal skin is the most critical yet tricky part in computerized lesion detection and classification. The effectiveness and accuracy of lesion classification are critically dependent on the quality of lesion segmentation. In this paper, we have proposed a novel approach that can automatically preprocess the image and then segment the lesion. The system filters unwanted artifacts including hairs, gel, bubbles, and specular reflection. A novel approach is presented using the concept of wavelets for detection and inpainting the hairs present in the cancer images. The contrast of lesion with the skin is enhanced using adaptive sigmoidal function that takes care of the localized intensity distribution within a given lesion's images. We then present a segmentation approach to precisely segment the lesion from the background. The proposed approach is tested on the European database of dermoscopic images. Results are compared with the competitors to demonstrate the superiority of the suggested approach.

Fast hierarchical knowledge-based approach for human face detection in color images

NASA Astrophysics Data System (ADS)

Jiang, Jun; Gong, Jie; Zhang, Guilin; Hu, Ruolan

2001-09-01

This paper presents a fast hierarchical knowledge-based approach for automatically detecting multi-scale upright faces in still color images. The approach consists of three levels. At the highest level, skin-like regions are determinated by skin model, which is based on the color attributes hue and saturation in HSV color space, as well color attributes red and green in normalized color space. In level 2, a new eye model is devised to select human face candidates in segmented skin-like regions. An important feature of the eye model is that it is independent of the scale of human face. So it is possible for finding human faces in different scale with scanning image only once, and it leads to reduction the computation time of face detection greatly. In level 3, a human face mosaic image model, which is consistent with physical structure features of human face well, is applied to judge whether there are face detects in human face candidate regions. This model includes edge and gray rules. Experiment results show that the approach has high robustness and fast speed. It has wide application perspective at human-computer interactions and visual telephone etc.

Automatic enhancement of skin fluorescence localization due to refractive index matching

NASA Astrophysics Data System (ADS)

Churmakov, Dmitry Y.; Meglinski, Igor V.; Piletsky, Sergey A.; Greenhalgh, Douglas A.

2004-07-01

Fluorescence diagnostic techniques are notable amongst many other optical methods, as they offer high sensitivity and non-invasive measurements of tissue properties. However, a combination of multiple scattering and physical heterogeneity of biological tissues hampers the interpretation of the fluorescence measurements. The analyses of the spatial distribution of endogenous and exogenous fluorophores excitations within tissues and their contribution to the detected signal localization are essential for many applications. We have developed a novel Monte Carlo technique that gives a graphical perception of how the excitation and fluorescence detected signal are localized in tissues. Our model takes into account spatial distribution of fluorophores and their quantum yields. We demonstrate that matching of the refractive indices of ambient medium and topical skin layer improves spatial localization of the detected fluorescence signal within the tissue. This result is consistent with the recent conclusion that administering biocompatible agents results in higher image contrast.

Automatic detection of measurement points for non-contact vibrometer-based diagnosis of cardiac arrhythmias

NASA Astrophysics Data System (ADS)

Metzler, Jürgen; Kroschel, Kristian; Willersinn, Dieter

2017-03-01

Monitoring of the heart rhythm is the cornerstone of the diagnosis of cardiac arrhythmias. It is done by means of electrocardiography which relies on electrodes attached to the skin of the patient. We present a new system approach based on the so-called vibrocardiogram that allows an automatic non-contact registration of the heart rhythm. Because of the contactless principle, the technique offers potential application advantages in medical fields like emergency medicine (burn patient) or premature baby care where adhesive electrodes are not easily applicable. A laser-based, mobile, contactless vibrometer for on-site diagnostics that works with the principle of laser Doppler vibrometry allows the acquisition of vital functions in form of a vibrocardiogram. Preliminary clinical studies at the Klinikum Karlsruhe have shown that the region around the carotid artery and the chest region are appropriate therefore. However, the challenge is to find a suitable measurement point in these parts of the body that differs from person to person due to e. g. physiological properties of the skin. Therefore, we propose a new Microsoft Kinect-based approach. When a suitable measurement area on the appropriate parts of the body are detected by processing the Kinect data, the vibrometer is automatically aligned on an initial location within this area. Then, vibrocardiograms on different locations within this area are successively acquired until a sufficient measuring quality is achieved. This optimal location is found by exploiting the autocorrelation function.

Wavelet-based statistical classification of skin images acquired with reflectance confocal microscopy

PubMed Central

Halimi, Abdelghafour; Batatia, Hadj; Le Digabel, Jimmy; Josse, Gwendal; Tourneret, Jean Yves

2017-01-01

Detecting skin lentigo in reflectance confocal microscopy images is an important and challenging problem. This imaging modality has not yet been widely investigated for this problem and there are a few automatic processing techniques. They are mostly based on machine learning approaches and rely on numerous classical image features that lead to high computational costs given the very large resolution of these images. This paper presents a detection method with very low computational complexity that is able to identify the skin depth at which the lentigo can be detected. The proposed method performs multiresolution decomposition of the image obtained at each skin depth. The distribution of image pixels at a given depth can be approximated accurately by a generalized Gaussian distribution whose parameters depend on the decomposition scale, resulting in a very-low-dimension parameter space. SVM classifiers are then investigated to classify the scale parameter of this distribution allowing real-time detection of lentigo. The method is applied to 45 healthy and lentigo patients from a clinical study, where sensitivity of 81.4% and specificity of 83.3% are achieved. Our results show that lentigo is identifiable at depths between 50μm and 60μm, corresponding to the average location of the the dermoepidermal junction. This result is in agreement with the clinical practices that characterize the lentigo by assessing the disorganization of the dermoepidermal junction. PMID:29296480

Study of smartphone suitability for mapping of skin chromophores

NASA Astrophysics Data System (ADS)

Kuzmina, Ilona; Lacis, Matiss; Spigulis, Janis; Berzina, Anna; Valeine, Lauma

2015-09-01

RGB (red-green-blue) technique for mapping skin chromophores by smartphones is proposed and studied. Three smartphones of different manufacturers were tested on skin phantoms and in vivo on benign skin lesions using a specially designed light source for illumination. Hemoglobin and melanin indices obtained by these smartphones showed differences in both tests. In vitro tests showed an increment of hemoglobin and melanin indices with the concentration of chromophores in phantoms. In vivo tests indicated higher hemoglobin index in hemangiomas than in nevi and healthy skin, and nevi showed higher melanin index compared to the healthy skin. Smartphones that allow switching off the automatic camera settings provided useful data, while those with "embedded" automatic settings appear to be useless for distant skin chromophore mapping.

Study of smartphone suitability for mapping of skin chromophores.

PubMed

Kuzmina, Ilona; Lacis, Matiss; Spigulis, Janis; Berzina, Anna; Valeine, Lauma

2015-09-01

RGB (red-green-blue) technique for mapping skin chromophores by smartphones is proposed and studied. Three smartphones of different manufacturers were tested on skin phantoms and in vivo on benign skin lesions using a specially designed light source for illumination. Hemoglobin and melanin indices obtained by these smartphones showed differences in both tests. In vitro tests showed an increment of hemoglobin and melanin indices with the concentration of chromophores in phantoms. In vivo tests indicated higher hemoglobin index in hemangiomas than in nevi and healthy skin, and nevi showed higher melanin index compared to the healthy skin. Smartphones that allow switching off the automatic camera settings provided useful data, while those with “embedded” automatic settings appear to be useless for distant skin chromophore mapping.

Automated in vivo 3D high-definition optical coherence tomography skin analysis system.

PubMed

Ai Ping Yow; Jun Cheng; Annan Li; Srivastava, Ruchir; Jiang Liu; Wong, Damon Wing Kee; Hong Liang Tey

2016-08-01

The in vivo assessment and visualization of skin structures can be performed through the use of high resolution optical coherence tomography imaging, also known as HD-OCT. However, the manual assessment of such images can be exhaustive and time consuming. In this paper, we present an analysis system to automatically identify and quantify the skin characteristics such as the topography of the surface of the skin and thickness of the epidermis in HD-OCT images. Comparison of this system with manual clinical measurements demonstrated its potential for automatic objective skin analysis and diseases diagnosis. To our knowledge, this is the first report of an automated system to process and analyse HD-OCT skin images.

Automatic evaluation of skin histopathological images for melanocytic features

NASA Astrophysics Data System (ADS)

Koosha, Mohaddeseh; Hoseini Alinodehi, S. Pourya; Nicolescu, Mircea; Safaei Naraghi, Zahra

2017-03-01

Successfully detecting melanocyte cells in the skin epidermis has great significance in skin histopathology. Because of the existence of cells with similar appearance to melanocytes in hematoxylin and eosin (HE) images of the epidermis, detecting melanocytes becomes a challenging task. This paper proposes a novel technique for the detection of melanocytes in HE images of the epidermis, based on the melanocyte color features, in the HSI color domain. Initially, an effective soft morphological filter is applied to the HE images in the HSI color domain to remove noise. Then a novel threshold-based technique is applied to distinguish the candidate melanocytes' nuclei. Similarly, the method is applied to find the candidate surrounding halos of the melanocytes. The candidate nuclei are associated with their surrounding halos using the suggested logical and statistical inferences. Finally, a fuzzy inference system is proposed, based on the HSI color information of a typical melanocyte in the epidermis, to calculate the similarity ratio of each candidate cell to a melanocyte. As our review on the literature shows, this is the first method evaluating epidermis cells for melanocyte similarity ratio. Experimental results on various images with different zooming factors show that the proposed method improves the results of previous works.

Automatic 3D segmentation of multiphoton images: a key step for the quantification of human skin.

PubMed

Decencière, Etienne; Tancrède-Bohin, Emmanuelle; Dokládal, Petr; Koudoro, Serge; Pena, Ana-Maria; Baldeweck, Thérèse

2013-05-01

Multiphoton microscopy has emerged in the past decade as a useful noninvasive imaging technique for in vivo human skin characterization. However, it has not been used until now in evaluation clinical trials, mainly because of the lack of specific image processing tools that would allow the investigator to extract pertinent quantitative three-dimensional (3D) information from the different skin components. We propose a 3D automatic segmentation method of multiphoton images which is a key step for epidermis and dermis quantification. This method, based on the morphological watershed and graph cuts algorithms, takes into account the real shape of the skin surface and of the dermal-epidermal junction, and allows separating in 3D the epidermis and the superficial dermis. The automatic segmentation method and the associated quantitative measurements have been developed and validated on a clinical database designed for aging characterization. The segmentation achieves its goals for epidermis-dermis separation and allows quantitative measurements inside the different skin compartments with sufficient relevance. This study shows that multiphoton microscopy associated with specific image processing tools provides access to new quantitative measurements on the various skin components. The proposed 3D automatic segmentation method will contribute to build a powerful tool for characterizing human skin condition. To our knowledge, this is the first 3D approach to the segmentation and quantification of these original images. © 2013 John Wiley & Sons A/S. Published by Blackwell Publishing Ltd.

Real-time Raman spectroscopy for automatic in vivo skin cancer detection: an independent validation.

PubMed

Zhao, Jianhua; Lui, Harvey; Kalia, Sunil; Zeng, Haishan

2015-11-01

In a recent study, we have demonstrated that real-time Raman spectroscopy could be used for skin cancer diagnosis. As a translational study, the objective of this study is to validate previous findings through a completely independent clinical test. In total, 645 confirmed cases were included in the analysis, including a cohort of 518 cases from a previous study, and an independent cohort of 127 new cases. Multi-variant statistical data analyses including principal component with general discriminant analysis (PC-GDA) and partial least squares (PLS) were used separately for lesion classification, which generated similar results. When the previous cohort (n = 518) was used as training and the new cohort (n = 127) was used as testing, the area under the receiver operating characteristic curve (ROC AUC) was found to be 0.889 (95 % CI 0.834-0.944; PLS); when the two cohorts were combined, the ROC AUC was 0.894 (95 % CI 0.870-0.918; PLS) with the narrowest confidence intervals. Both analyses were comparable to the previous findings, where the ROC AUC was 0.896 (95 % CI 0.846-0.946; PLS). The independent study validates that real-time Raman spectroscopy could be used for automatic in vivo skin cancer diagnosis with good accuracy.

Automatic red eye correction and its quality metric

NASA Astrophysics Data System (ADS)

Safonov, Ilia V.; Rychagov, Michael N.; Kang, KiMin; Kim, Sang Ho

2008-01-01

The red eye artifacts are troublesome defect of amateur photos. Correction of red eyes during printing without user intervention and making photos more pleasant for an observer are important tasks. The novel efficient technique of automatic correction of red eyes aimed for photo printers is proposed. This algorithm is independent from face orientation and capable to detect paired red eyes as well as single red eyes. The approach is based on application of 3D tables with typicalness levels for red eyes and human skin tones and directional edge detection filters for processing of redness image. Machine learning is applied for feature selection. For classification of red eye regions a cascade of classifiers including Gentle AdaBoost committee from Classification and Regression Trees (CART) is applied. Retouching stage includes desaturation, darkening and blending with initial image. Several versions of approach implementation using trade-off between detection and correction quality, processing time, memory volume are possible. The numeric quality criterion of automatic red eye correction is proposed. This quality metric is constructed by applying Analytic Hierarchy Process (AHP) for consumer opinions about correction outcomes. Proposed numeric metric helped to choose algorithm parameters via optimization procedure. Experimental results demonstrate high accuracy and efficiency of the proposed algorithm in comparison with existing solutions.

Importance of a Patient Dosimetry and Clinical Follow-up Program in the Detection of Radiodermatitis After Long Percutaneous Coronary Interventions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vano, Eliseo, E-mail: eliseov@med.ucm.es; Escaned, Javier; Vano-Galvan, Sergio

Complex percutaneous interventions often require high radiation doses likely to produce skin radiation injuries. We assessed the methodology used to select patients with potential skin injuries in cardiac procedures and in need of clinical follow-up. We evaluated peak skin dose and clinical follow-up in a case of radiodermatitis produced during a total occlusion recanalization. This prospective study followed CIRSE and ACC/AHA/SCAI recommendations for patient radiation dose management in interventional procedures carried out in a university hospital with a workload of 4200 interventional cardiac procedures per year. Patient dose reports were automatically transferred to a central database. Patients exceeding trigger levelsmore » for air kerma area product (500 Gy cm{sup 2}) and cumulative skin dose (5 Gy) were counseled and underwent follow-up for early detection of skin injuries, with dermatologic support. The Ethical Committee and the Quality Assurance and Radiation Safety Committee approved the program. During 2010, a total of 13 patients (3.0/1,000 that year) received dose values exceeding trigger levels in the cardiovascular institute. Only one patient, who had undergone two consecutive procedures resulting in 970 Gy cm{sup 2} and 13.0 Gy as cumulative skin dose, showed signs of serious radiodermatitis that resolved in 3.7 months. The remaining patients did not manifest skin lesions during follow-up, and whenever patient examination was not feasible as part of the follow-up, neither patients nor families reported any skin injuries. Peak skin dose calculation and close clinical follow-up were feasible and appropriate, with a moderate additional workload for the staff and satisfaction for the patient.« less

[Assessment of skin aging grading based on computer vision].

PubMed

Li, Lingyu; Xue, Jinxia; He, Xiangqian; Zhang, Sheng; Fan, Chu

2017-06-01

Skin aging is the most intuitive and obvious sign of the human aging processes. Qualitative and quantitative determination of skin aging is of particular importance for the evaluation of human aging and anti-aging treatment effects. To solve the problem of subjectivity of conventional skin aging grading methods, the self-organizing map (SOM) network was used to explore an automatic method for skin aging grading. First, the ventral forearm skin images were obtained by a portable digital microscope and two texture parameters, i.e. , mean width of skin furrows and the number of intersections were extracted by image processing algorithm. Then, the values of texture parameters were taken as inputs of SOM network to train the network. The experimental results showed that the network achieved an overall accuracy of 80.8%, compared with the aging grading results by human graders. The designed method appeared to be rapid and objective, which can be used for quantitative analysis of skin images, and automatic assessment of skin aging grading.

Pigmented skin lesion detection using random forest and wavelet-based texture

NASA Astrophysics Data System (ADS)

Hu, Ping; Yang, Tie-jun

2016-10-01

The incidence of cutaneous malignant melanoma, a disease of worldwide distribution and is the deadliest form of skin cancer, has been rapidly increasing over the last few decades. Because advanced cutaneous melanoma is still incurable, early detection is an important step toward a reduction in mortality. Dermoscopy photographs are commonly used in melanoma diagnosis and can capture detailed features of a lesion. A great variability exists in the visual appearance of pigmented skin lesions. Therefore, in order to minimize the diagnostic errors that result from the difficulty and subjectivity of visual interpretation, an automatic detection approach is required. The objectives of this paper were to propose a hybrid method using random forest and Gabor wavelet transformation to accurately differentiate which part belong to lesion area and the other is not in a dermoscopy photographs and analyze segmentation accuracy. A random forest classifier consisting of a set of decision trees was used for classification. Gabor wavelets transformation are the mathematical model of visual cortical cells of mammalian brain and an image can be decomposed into multiple scales and multiple orientations by using it. The Gabor function has been recognized as a very useful tool in texture analysis, due to its optimal localization properties in both spatial and frequency domain. Texture features based on Gabor wavelets transformation are found by the Gabor filtered image. Experiment results indicate the following: (1) the proposed algorithm based on random forest outperformed the-state-of-the-art in pigmented skin lesions detection (2) and the inclusion of Gabor wavelet transformation based texture features improved segmentation accuracy significantly.

Development of an infection screening system for entry inspection at airport quarantine stations using ear temperature, heart and respiration rates.

PubMed

Sun, Guanghao; Abe, Nobujiro; Sugiyama, Youhei; Nguyen, Quang Vinh; Nozaki, Kohei; Nakayama, Yosuke; Takei, Osamu; Hakozaki, Yukiya; Abe, Shigeto; Matsui, Takemi

2013-01-01

After the outbreak of severe acute respiratory syndrome (SARS) in 2003, many international airport quarantine stations conducted fever-based screening to identify infected passengers using infrared thermography for preventing global pandemics. Due to environmental factors affecting measurement of facial skin temperature with thermography, some previous studies revealed the limits of authenticity in detecting infectious symptoms. In order to implement more strict entry screening in the epidemic seasons of emerging infectious diseases, we developed an infection screening system for airport quarantines using multi-parameter vital signs. This system can automatically detect infected individuals within several tens of seconds by a neural-network-based discriminant function using measured vital signs, i.e., heart rate obtained by a reflective photo sensor, respiration rate determined by a 10-GHz non-contact respiration radar, and the ear temperature monitored by a thermography. In this paper, to reduce the environmental effects on thermography measurement, we adopted the ear temperature as a new screening indicator instead of facial skin. We tested the system on 13 influenza patients and 33 normal subjects. The sensitivity of the infection screening system in detecting influenza were 92.3%, which was higher than the sensitivity reported in our previous paper (88.0%) with average facial skin temperature.

Intelligent Image Analysis for Image-Guided Laser Hair Removal and Skin Therapy

NASA Technical Reports Server (NTRS)

Walker, Brian; Lu, Thomas; Chao, Tien-Hsin

2012-01-01

We present the development of advanced automatic target recognition (ATR) algorithms for the hair follicles identification in digital skin images to accurately direct the laser beam to remove the hair. The ATR system first performs a wavelet filtering to enhance the contrast of the hair features in the image. The system then extracts the unique features of the targets and sends the features to an Adaboost based classifier for training and recognition operations. The ATR system automatically classifies the hair, moles, or other skin lesion and provides the accurate coordinates of the intended hair follicle locations. The coordinates can be used to guide a scanning laser to focus energy only on the hair follicles. The intended benefit would be to protect the skin from unwanted laser exposure and to provide more effective skin therapy.

A soft kinetic data structure for lesion border detection.

PubMed

Kockara, Sinan; Mete, Mutlu; Yip, Vincent; Lee, Brendan; Aydin, Kemal

2010-06-15

The medical imaging and image processing techniques, ranging from microscopic to macroscopic, has become one of the main components of diagnostic procedures to assist dermatologists in their medical decision-making processes. Computer-aided segmentation and border detection on dermoscopic images is one of the core components of diagnostic procedures and therapeutic interventions for skin cancer. Automated assessment tools for dermoscopic images have become an important research field mainly because of inter- and intra-observer variations in human interpretations. In this study, a novel approach-graph spanner-for automatic border detection in dermoscopic images is proposed. In this approach, a proximity graph representation of dermoscopic images in order to detect regions and borders in skin lesion is presented. Graph spanner approach is examined on a set of 100 dermoscopic images whose manually drawn borders by a dermatologist are used as the ground truth. Error rates, false positives and false negatives along with true positives and true negatives are quantified by digitally comparing results with manually determined borders from a dermatologist. The results show that the highest precision and recall rates obtained to determine lesion boundaries are 100%. However, accuracy of assessment averages out at 97.72% and borders errors' mean is 2.28% for whole dataset.

A Preliminary Analysis of the Phenomenology of Skin-Picking in Prader-Willi Syndrome

ERIC Educational Resources Information Center

Morgan, Jessica R.; Storch, Eric A.; Woods, Douglas W.; Bodzin, Danielle; Lewin, Adam B.; Murphy, Tanya K.

2010-01-01

To examine the nature and psychosocial correlates of skin-picking behavior in youth with Prader-Willi Syndrome (PWS). Parents of 67 youth (aged 5-19 years) with PWS were recruited to complete an internet-based survey that included measures of: skin-picking behaviors, the automatic and/or focused nature of skin-picking, severity of skin-picking…

Automated colour identification in melanocytic lesions.

PubMed

Sabbaghi, S; Aldeen, M; Garnavi, R; Varigos, G; Doliantis, C; Nicolopoulos, J

2015-08-01

Colour information plays an important role in classifying skin lesion. However, colour identification by dermatologists can be very subjective, leading to cases of misdiagnosis. Therefore, a computer-assisted system for quantitative colour identification is highly desirable for dermatologists to use. Although numerous colour detection systems have been developed, few studies have focused on imitating the human visual perception of colours in melanoma application. In this paper we propose a new methodology based on QuadTree decomposition technique for automatic colour identification in dermoscopy images. Our approach mimics the human perception of lesion colours. The proposed method is trained on a set of 47 images from NIH dataset and applied to a test set of 190 skin lesions obtained from PH2 dataset. The results of our proposed method are compared with a recently reported colour identification method using the same dataset. The effectiveness of our method in detecting colours in dermoscopy images is vindicated by obtaining approximately 93% accuracy when the CIELab1 colour space is used.

Hair and bare skin discrimination for laser-assisted hair removal systems.

PubMed

Cayir, Sercan; Yetik, Imam Samil

2017-07-01

Laser-assisted hair removal devices aim to remove body hair permanently. In most cases, these devices irradiate the whole area of the skin with a homogenous power density. Thus, a significant portion of the skin, where hair is not present, is burnt unnecessarily causing health risks. Therefore, methods that can distinguish hair regions automatically would be very helpful avoiding these unnecessary applications of laser. This study proposes a new system of algorithms to detect hair regions with the help of a digital camera. Unlike previous limited number of studies, our methods are very fast allowing for real-time application. Proposed methods are based on certain features derived from histograms of hair and skin regions. We compare our algorithm with competing methods in terms of localization performance and computation time and show that a much faster real-time accurate localization of hair regions is possible with the proposed method. Our results show that the algorithm we have developed is extremely fast (around 45 milliseconds) allowing for real-time application with high accuracy hair localization ( 96.48 %).

[Experimental study of PVPP/silicone composite automatic expanded material as implants].

PubMed

Yin, Wei-min; Gao, Jian-hua; Yang, Qing-fang; Lu, Feng; Ye, Jia-jia

2009-03-01

To study the feasibility of Polyvinylpolypyrrolidone (PVPP)/silicone composite automatic expanded material as implants. The PVPP hydrogel was mixed with silicone through the location at the high temperature. Implants with different ratio of PVPP to silicone were placed under the back and nose skin in 24 New Zealand rabbits. The surrounding tissue reaction, material and skin expansion were observed and compared with those with pure silicone implants. The study lasted for 200 days. Compared with pure silicone implants, the composite material could expand automatically and stop expanding at about 2 weeks after implantation. Histological study showed similar inflectional and foreign body reaction around the composite material and the pure silicone. Compared with pure silicone, the PVPP/silicone composite implant has the advantage of automatic expansion, so as to expand the soft tissue.

Automatic Approach for Lung Segmentation with Juxta-Pleural Nodules from Thoracic CT Based on Contour Tracing and Correction.

PubMed

Wang, Jinke; Guo, Haoyan

2016-01-01

This paper presents a fully automatic framework for lung segmentation, in which juxta-pleural nodule problem is brought into strong focus. The proposed scheme consists of three phases: skin boundary detection, rough segmentation of lung contour, and pulmonary parenchyma refinement. Firstly, chest skin boundary is extracted through image aligning, morphology operation, and connective region analysis. Secondly, diagonal-based border tracing is implemented for lung contour segmentation, with maximum cost path algorithm used for separating the left and right lungs. Finally, by arc-based border smoothing and concave-based border correction, the refined pulmonary parenchyma is obtained. The proposed scheme is evaluated on 45 volumes of chest scans, with volume difference (VD) 11.15 ± 69.63 cm 3 , volume overlap error (VOE) 3.5057 ± 1.3719%, average surface distance (ASD) 0.7917 ± 0.2741 mm, root mean square distance (RMSD) 1.6957 ± 0.6568 mm, maximum symmetric absolute surface distance (MSD) 21.3430 ± 8.1743 mm, and average time-cost 2 seconds per image. The preliminary results on accuracy and complexity prove that our scheme is a promising tool for lung segmentation with juxta-pleural nodules.

Automatic detection and segmentation of vascular structures in dermoscopy images using a novel vesselness measure based on pixel redness and tubularness

NASA Astrophysics Data System (ADS)

Kharazmi, Pegah; Lui, Harvey; Stoecker, William V.; Lee, Tim

2015-03-01

Vascular structures are one of the most important features in the diagnosis and assessment of skin disorders. The presence and clinical appearance of vascular structures in skin lesions is a discriminating factor among different skin diseases. In this paper, we address the problem of segmentation of vascular patterns in dermoscopy images. Our proposed method is composed of three parts. First, based on biological properties of human skin, we decompose the skin to melanin and hemoglobin component using independent component analysis of skin color images. The relative quantities and pure color densities of each component were then estimated. Subsequently, we obtain three reference vectors of the mean RGB values for normal skin, pigmented skin and blood vessels from the hemoglobin component by averaging over 100000 pixels of each group outlined by an expert. Based on the Euclidean distance thresholding, we generate a mask image that extracts the red regions of the skin. Finally, Frangi measure was applied to the extracted red areas to segment the tubular structures. Finally, Otsu's thresholding was applied to segment the vascular structures and get a binary vessel mask image. The algorithm was implemented on a set of 50 dermoscopy images. In order to evaluate the performance of our method, we have artificially extended some of the existing vessels in our dermoscopy data set and evaluated the performance of the algorithm to segment the newly added vessel pixels. A sensitivity of 95% and specificity of 87% were achieved.

CONCENTRIC DECILE SEGMENTATION OF WHITE AND HYPOPIGMENTED AREAS IN DERMOSCOPY IMAGES OF SKIN LESIONS ALLOWS DISCRIMINATION OF MALIGNANT MELANOMA

PubMed Central

Dalal, Ankur; Moss, Randy H.; Stanley, R. Joe; Stoecker, William V.; Gupta, Kapil; Calcara, David A.; Xu, Jin; Shrestha, Bijaya; Drugge, Rhett; Malters, Joseph M.; Perry, Lindall A.

2011-01-01

Dermoscopy, also known as dermatoscopy or epiluminescence microscopy (ELM), permits visualization of features of pigmented melanocytic neoplasms that are not discernable by examination with the naked eye. White areas, prominent in early malignant melanoma and melanoma in situ, contribute to early detection of these lesions. An adaptive detection method has been investigated to identify white and hypopigmented areas based on lesion histogram statistics. Using the Euclidean distance transform, the lesion is segmented in concentric deciles. Overlays of the white areas on the lesion deciles are determined. Calculated features of automatically detected white areas include lesion decile ratios, normalized number of white areas, absolute and relative size of largest white area, relative size of all white areas, and white area eccentricity, dispersion, and irregularity. Using a back-propagation neural network, the white area statistics yield over 95% diagnostic accuracy of melanomas from benign nevi. White and hypopigmented areas in melanomas tend to be central or paracentral. The four most powerful features on multivariate analysis are lesion decile ratios. Automatic detection of white and hypopigmented areas in melanoma can be accomplished using lesion statistics. A neural network can achieve good discrimination of melanomas from benign nevi using these areas. Lesion decile ratios are useful white area features. PMID:21074971

Psoriasis skin biopsy image segmentation using Deep Convolutional Neural Network.

PubMed

Pal, Anabik; Garain, Utpal; Chandra, Aditi; Chatterjee, Raghunath; Senapati, Swapan

2018-06-01

Development of machine assisted tools for automatic analysis of psoriasis skin biopsy image plays an important role in clinical assistance. Development of automatic approach for accurate segmentation of psoriasis skin biopsy image is the initial prerequisite for developing such system. However, the complex cellular structure, presence of imaging artifacts, uneven staining variation make the task challenging. This paper presents a pioneering attempt for automatic segmentation of psoriasis skin biopsy images. Several deep neural architectures are tried for segmenting psoriasis skin biopsy images. Deep models are used for classifying the super-pixels generated by Simple Linear Iterative Clustering (SLIC) and the segmentation performance of these architectures is compared with the traditional hand-crafted feature based classifiers built on popularly used classifiers like K-Nearest Neighbor (KNN), Support Vector Machine (SVM) and Random Forest (RF). A U-shaped Fully Convolutional Neural Network (FCN) is also used in an end to end learning fashion where input is the original color image and the output is the segmentation class map for the skin layers. An annotated real psoriasis skin biopsy image data set of ninety (90) images is developed and used for this research. The segmentation performance is evaluated with two metrics namely, Jaccard's Coefficient (JC) and the Ratio of Correct Pixel Classification (RCPC) accuracy. The experimental results show that the CNN based approaches outperform the traditional hand-crafted feature based classification approaches. The present research shows that practical system can be developed for machine assisted analysis of psoriasis disease. Copyright © 2018 Elsevier B.V. All rights reserved.

Automatic segmentation of relevant structures in DCE MR mammograms

NASA Astrophysics Data System (ADS)

Koenig, Matthias; Laue, Hendrik; Boehler, Tobias; Peitgen, Heinz-Otto

2007-03-01

The automatic segmentation of relevant structures such as skin edge, chest wall, or nipple in dynamic contrast enhanced MR imaging (DCE MRI) of the breast provides additional information for computer aided diagnosis (CAD) systems. Automatic reporting using BI-RADS criteria benefits of information about location of those structures. Lesion positions can be automatically described relatively to such reference structures for reporting purposes. Furthermore, this information can assist data reduction for computation expensive preprocessing such as registration, or for visualization of only the segments of current interest. In this paper, a novel automatic method for determining the air-breast boundary resp. skin edge, for approximation of the chest wall, and locating of the nipples is presented. The method consists of several steps which are built on top of each other. Automatic threshold computation leads to the air-breast boundary which is then analyzed to determine the location of the nipple. Finally, results of both steps are starting point for approximation of the chest wall. The proposed process was evaluated on a large data set of DCE MRI recorded by T1 sequences and yielded reasonable results in all cases.

The Relative Effects of Manual Versus Automatic Exposure Control on Radiation Dose to Vital Organs in Total Hip Arthroplasty.

PubMed

Harper, Katharine D; Li, Shidong; Jennings, Rachel; Amer, Kamil M; Haydel, Christopher; Ali, Sayed

2018-01-01

Technologic advances have reduced medical radiation exposure while maintaining image quality. The purpose of this study was to determine the effects of the presence of total hip arthroplasty implants, compared with native hips, on radiation exposure of the most radiosensitive organs when manual and automatic exposure control settings are used. Detection probes were placed at six locations (stomach, sigmoid colon, right pelvic wall, left pelvic wall, pubic symphysis, and anterior pubic skin) in a cadaver. Radiographs were obtained with the use of manual and automatic exposure control protocols, with exposures recorded. A total hip arthroplasty implant was placed in the cadaver, probe positioning was confirmed, and the radiographs were repeated, with exposure values recorded. The control probe placed at the stomach had values ranging from 0.00 mSv to 0.01 mSv in protocols with and without implants. With the manual protocol, exposures in the pelvis ranged from 0.36 mSv to 2.74 mSv in the native hip and from 0.33 mSv to 2.24 mSv after implant placement. The increases in exposure after implant placement, represented as relative risk, were as follows: stomach, 1.000; pubic symphysis, 0.818; left pelvic wall, 1.381; sigmoid colon, 1.550; right pelvic wall, 0.917; and anterior pubic skin, 1.015. With automatic exposure control, exposures in the pelvis ranged from 0.07 mSv to 0.89 mSv in the native hip and from 0.21 mSv to 1.15 mSv after implant placement. With automatic exposure control, the increases in exposure after implant placement, represented as relative risk, were as follows: stomach, 1.000; pubic symphysis, 1.292; left pelvic wall, 1.476; sigmoid colon, 2.182; right pelvic wall, 3.000; and anterior pubic skin, 1.378. The amount of radiation to which patients are exposed as a result of medical procedures or imaging, and whether exposure is associated with an increased risk of malignant transformation, are the subject of ongoing debate. We found that after insertion of a total hip arthroplasty implant, exposure values increased threefold at some anatomic locations and surpassed 1 mSv, the generally accepted threshold for concern. Radiation exposure to radiosensitive organs increased up to threefold after total hip implantation with automatic exposure control and up to approximately 1.5 times with the manual protocol. Doses were greater with manual exposures than with automatic exposure control (except at the control probe on the stomach, where exposure was negligible, as expected). However, after implant placement, doses increased more with automatic exposure control than with manual exposure. This difference can be attributed to increased scatter and the difficulty of dose modification because of the density of the implant. Current radiographic protocols should be reassessed to determine if the benefits of frequent radiographs outweigh the newly demonstrated risks.

Detection of Pigment Networks in Dermoscopy Images

NASA Astrophysics Data System (ADS)

Eltayef, Khalid; Li, Yongmin; Liu, Xiaohui

2017-02-01

One of the most important structures in dermoscopy images is the pigment network, which is also one of the most challenging and fundamental task for dermatologists in early detection of melanoma. This paper presents an automatic system to detect pigment network from dermoscopy images. The design of the proposed algorithm consists of four stages. First, a pre-processing algorithm is carried out in order to remove the noise and improve the quality of the image. Second, a bank of directional filters and morphological connected component analysis are applied to detect the pigment networks. Third, features are extracted from the detected image, which can be used in the subsequent stage. Fourth, the classification process is performed by applying feed-forward neural network, in order to classify the region as either normal or abnormal skin. The method was tested on a dataset of 200 dermoscopy images from Hospital Pedro Hispano (Matosinhos), and better results were produced compared to previous studies.

Computer-Aided Diagnosis of Micro-Malignant Melanoma Lesions Applying Support Vector Machines.

PubMed

Jaworek-Korjakowska, Joanna

2016-01-01

Background. One of the fatal disorders causing death is malignant melanoma, the deadliest form of skin cancer. The aim of the modern dermatology is the early detection of skin cancer, which usually results in reducing the mortality rate and less extensive treatment. This paper presents a study on classification of melanoma in the early stage of development using SVMs as a useful technique for data classification. Method. In this paper an automatic algorithm for the classification of melanomas in their early stage, with a diameter under 5 mm, has been presented. The system contains the following steps: image enhancement, lesion segmentation, feature calculation and selection, and classification stage using SVMs. Results. The algorithm has been tested on 200 images including 70 melanomas and 130 benign lesions. The SVM classifier achieved sensitivity of 90% and specificity of 96%. The results indicate that the proposed approach captured most of the malignant cases and could provide reliable information for effective skin mole examination. Conclusions. Micro-melanomas due to the small size and low advancement of development create enormous difficulties during the diagnosis even for experts. The use of advanced equipment and sophisticated computer systems can help in the early diagnosis of skin lesions.

Automated segmentations of skin, soft-tissue, and skeleton, from torso CT images

NASA Astrophysics Data System (ADS)

Zhou, Xiangrong; Hara, Takeshi; Fujita, Hiroshi; Yokoyama, Ryujiro; Kiryu, Takuji; Hoshi, Hiroaki

2004-05-01

We have been developing a computer-aided diagnosis (CAD) scheme for automatically recognizing human tissue and organ regions from high-resolution torso CT images. We show some initial results for extracting skin, soft-tissue and skeleton regions. 139 patient cases of torso CT images (male 92, female 47; age: 12-88) were used in this study. Each case was imaged with a common protocol (120kV/320mA) and covered the whole torso with isotopic spatial resolution of about 0.63 mm and density resolution of 12 bits. A gray-level thresholding based procedure was applied to separate the human body from background. The density and distance features to body surface were used to determine the skin, and separate soft-tissue from the others. A 3-D region growing based method was used to extract the skeleton. We applied this system to the 139 cases and found that the skin, soft-tissue and skeleton regions were recognized correctly for 93% of the patient cases. The accuracy of segmentation results was acceptable by evaluating the results slice by slice. This scheme will be included in CAD systems for detecting and diagnosing the abnormal lesions in multi-slice torso CT images.

In-vivo detectability index: development and validation of an automated methodology

NASA Astrophysics Data System (ADS)

Smith, Taylor Brunton; Solomon, Justin; Samei, Ehsan

2017-03-01

The purpose of this study was to develop and validate a method to estimate patient-specific detectability indices directly from patients' CT images (i.e., "in vivo"). The method works by automatically extracting noise (NPS) and resolution (MTF) properties from each patient's CT series based on previously validated techniques. Patient images are thresholded into skin-air interfaces to form edge-spread functions, which are further binned, differentiated, and Fourier transformed to form the MTF. The NPS is likewise estimated from uniform areas of the image. These are combined with assumed task functions (reference function: 10 mm disk lesion with contrast of -15 HU) to compute detectability indices for a non-prewhitening matched filter model observer predicting observer performance. The results were compared to those from a previous human detection study on 105 subtle, hypo-attenuating liver lesions, using a two-alternative-forcedchoice (2AFC) method, over 6 dose levels using 16 readers. The in vivo detectability indices estimated for all patient images were compared to binary 2AFC outcomes with a generalized linear mixed-effects statistical model (Probit link function, linear terms only, no interactions, random term for readers). The model showed that the in vivo detectability indices were strongly predictive of 2AFC outcomes (P < 0.05). A linear comparison between the human detection accuracy and model-predicted detection accuracy (for like conditions) resulted in Pearson and Spearman correlations coefficients of 0.86 and 0.87, respectively. These data provide evidence that the in vivo detectability index could potentially be used to automatically estimate and track image quality in a clinical operation.

Automatic Detection of Blue-White Veil and Related Structures in Dermoscopy Images

PubMed Central

Celebi, M. Emre; Iyatomi, Hitoshi; Stoecker, William V.; Moss, Randy H.; Rabinovitz, Harold S.; Argenziano, Giuseppe; Soyer, H. Peter

2011-01-01

Dermoscopy is a non-invasive skin imaging technique, which permits visualization of features of pigmented melanocytic neoplasms that are not discernable by examination with the naked eye. One of the most important features for the diagnosis of melanoma in dermoscopy images is the blue-white veil (irregular, structureless areas of confluent blue pigmentation with an overlying white “ground-glass” film). In this article, we present a machine learning approach to the detection of blue-white veil and related structures in dermoscopy images. The method involves contextual pixel classification using a decision tree classifier. The percentage of blue-white areas detected in a lesion combined with a simple shape descriptor yielded a sensitivity of 69.35% and a specificity of 89.97% on a set of 545 dermoscopy images. The sensitivity rises to 78.20% for detection of blue veil in those cases where it is a primary feature for melanoma recognition. PMID:18804955

Automatic finger joint synovitis localization in ultrasound images

NASA Astrophysics Data System (ADS)

Nurzynska, Karolina; Smolka, Bogdan

2016-04-01

A long-lasting inflammation of joints results between others in many arthritis diseases. When not cured, it may influence other organs and general patients' health. Therefore, early detection and running proper medical treatment are of big value. The patients' organs are scanned with high frequency acoustic waves, which enable visualization of interior body structures through an ultrasound sonography (USG) image. However, the procedure is standardized, different projections result in a variety of possible data, which should be analyzed in short period of time by a physician, who is using medical atlases as a guidance. This work introduces an efficient framework based on statistical approach to the finger joint USG image, which enables automatic localization of skin and bone regions, which are then used for localization of the finger joint synovitis area. The processing pipeline realizes the task in real-time and proves high accuracy when compared to annotation prepared by the expert.

Facial skin pores: a multiethnic study

PubMed Central

Flament, Frederic; Francois, Ghislain; Qiu, Huixia; Ye, Chengda; Hanaya, Tomoo; Batisse, Dominique; Cointereau-Chardon, Suzy; Seixas, Mirela Donato Gianeti; Dal Belo, Susi Elaine; Bazin, Roland

2015-01-01

Skin pores (SP), as they are called by laymen, are common and benign features mostly located on the face (nose, cheeks, etc) that generate many aesthetic concerns or complaints. Despite the prevalence of skin pores, related literature is scarce. With the aim of describing the prevalence of skin pores and anatomic features among ethnic groups, a dermatoscopic instrument, using polarized lighting, coupled to a digital camera recorded the major features of skin pores (size, density, coverage) on the cheeks of 2,585 women in different countries and continents. A detection threshold of 250 μm, correlated to clinical scorings by experts, was input into a specific software to further allow for automatic counting of the SP density (N/cm2) and determination of their respective sizes in mm2. Integrating both criteria also led to establishing the relative part of the skin surface (as a percentage) that is actually covered by SP on cheeks. The results showed that the values of respective sizes, densities, and skin coverage: 1) were recorded in all studied subjects; 2) varied greatly with ethnicity; 3) plateaued with age in most cases; and 4) globally refected self-assessment by subjects, in particular those who self-declare having “enlarged pores” like Brazilian women. Inversely, Chinese women were clearly distinct from other ethnicities in having very low density and sizes. Analyzing the present results suggests that facial skin pore’s morphology as perceived by human eye less result from functional criteria of associated appendages such as sebaceous glands. To what extent skin pores may be viewed as additional criteria of a photo-altered skin is an issue to be further addressed. PMID:25733918

Detection of the nipple in automated 3D breast ultrasound using coronal slab-average-projection and cumulative probability map

NASA Astrophysics Data System (ADS)

Kim, Hannah; Hong, Helen

2014-03-01

We propose an automatic method for nipple detection on 3D automated breast ultrasound (3D ABUS) images using coronal slab-average-projection and cumulative probability map. First, to identify coronal images that appeared remarkable distinction between nipple-areola region and skin, skewness of each coronal image is measured and the negatively skewed images are selected. Then, coronal slab-average-projection image is reformatted from selected images. Second, to localize nipple-areola region, elliptical ROI covering nipple-areola region is detected using Hough ellipse transform in coronal slab-average-projection image. Finally, to separate the nipple from areola region, 3D Otsu's thresholding is applied to the elliptical ROI and cumulative probability map in the elliptical ROI is generated by assigning high probability to low intensity region. False detected small components are eliminated using morphological opening and the center point of detected nipple region is calculated. Experimental results show that our method provides 94.4% nipple detection rate.

Experimental functional analysis of severe skin-picking behavior in Prader-Willi syndrome.

PubMed

Hall, Scott S; Hustyi, Kristin M; Chui, Clara; Hammond, Jennifer L

2014-10-01

Skin picking is an extremely distressing and treatment resistant behavior commonly shown by individuals with Prader-Willi syndrome (PWS). However, with the exception of a limited number of published single-case and survey studies, little is known about the environmental determinants of skin picking in this population. In this study, functional analyses were conducted with thirteen individuals with PWS, aged 6-23 years, who engaged in severe skin-picking behavior. In addition to the conditions typically employed in a functional analysis (i.e., alone, attention, play, demand), we included an ignore condition to examine potential effects of stimulus control by the presence of an adult. Twelve participants engaged in skin picking during the functional analysis, with the highest levels occurring in the alone and ignore conditions for eight participants, suggesting that skin picking in these participants was maintained by automatic reinforcement. For the remaining four participants, an undifferentiated pattern of low-rate skin picking was observed across conditions. These data confirm previous studies indicating that skin picking in PWS may be maintained most often by automatically produced sensory consequences. There were no associations between demographic characteristics of the participants (e.g., sex, age, IQ or BMI) and levels of skin picking observed in the functional analysis. Additional investigations are needed to identify the nature of the sensory consequences produced during episodes of skin picking in PWS. Behavioral interventions designed to extinguish or compete with the potential sensory consequences arising from skin picking in PWS are also warranted. Copyright © 2014 Elsevier Ltd. All rights reserved.

A new physical model with multilayer architecture for facial expression animation using dynamic adaptive mesh.

PubMed

Zhang, Yu; Prakash, Edmond C; Sung, Eric

2004-01-01

This paper presents a new physically-based 3D facial model based on anatomical knowledge which provides high fidelity for facial expression animation while optimizing the computation. Our facial model has a multilayer biomechanical structure, incorporating a physically-based approximation to facial skin tissue, a set of anatomically-motivated facial muscle actuators, and underlying skull structure. In contrast to existing mass-spring-damper (MSD) facial models, our dynamic skin model uses the nonlinear springs to directly simulate the nonlinear visco-elastic behavior of soft tissue and a new kind of edge repulsion spring is developed to prevent collapse of the skin model. Different types of muscle models have been developed to simulate distribution of the muscle force applied on the skin due to muscle contraction. The presence of the skull advantageously constrain the skin movements, resulting in more accurate facial deformation and also guides the interactive placement of facial muscles. The governing dynamics are computed using a local semi-implicit ODE solver. In the dynamic simulation, an adaptive refinement automatically adapts the local resolution at which potential inaccuracies are detected depending on local deformation. The method, in effect, ensures the required speedup by concentrating computational time only where needed while ensuring realistic behavior within a predefined error threshold. This mechanism allows more pleasing animation results to be produced at a reduced computational cost.

Validation of artificial skin equivalents as in vitro testing systems

NASA Astrophysics Data System (ADS)

Schmitt, Robert; Marx, Ulrich; Walles, Heike; Schober, Lena

2011-03-01

With the increasing complexity of the chemical composition of pharmaceuticals, cosmetics and everyday substances, the awareness of potential health issues and long term damages for humanoid organs is shifting into focus. Artificial in vitro testing systems play an important role in providing reliable test conditions and replacing precarious animal testing. Especially artificial skin equivalents ASEs are used for a broad spectrum of studies like penetration, irritation and corrosion of substances. One major challenge in tissue engineering is the qualification of each individual ASE as in vitro testing system. Due to biological fluctuations, the stratum corneum hornified layer of some ASEs may not fully develop or other defects might occur. For monitoring these effects we developed an fully automated Optical Coherence Tomography device. Here, we present different methods to characterize and evaluate the quality of the ASEs based on image and data processing of OCT B-scans. By analysing the surface structure, defects, like cuts or tears, are detectable. A further indicator for the quality of the ASE is the morphology of the tissue. This allows to determine if the skin model has reached the final growth state. We found, that OCT is a well suited technology for automatically characterizing artificial skin equivalents and validating the application as testing system.

High Performance Automatic Character Skinning Based on Projection Distance

NASA Astrophysics Data System (ADS)

Li, Jun; Lin, Feng; Liu, Xiuling; Wang, Hongrui

2018-03-01

Skeleton-driven-deformation methods have been commonly used in the character deformations. The process of painting skin weights for character deformation is a long-winded task requiring manual tweaking. We present a novel method to calculate skinning weights automatically from 3D human geometric model and corresponding skeleton. The method first, groups each mesh vertex of 3D human model to a skeleton bone by the minimum distance from a mesh vertex to each bone. Secondly, calculates each vertex's weights to the adjacent bones by the vertex's projection point distance to the bone joints. Our method's output can not only be applied to any kind of skeleton-driven deformation, but also to motion capture driven (mocap-driven) deformation. Experiments results show that our method not only has strong generality and robustness, but also has high performance.

Automatic measurement of epidermal thickness from optical coherence tomography images using a new algorithm.

PubMed

Josse, G; George, J; Black, D

2011-08-01

Optical coherence tomography (OCT) is an imaging system that enables in vivo epidermal thickness (ET) measurement. In order to use OCT in large-scale clinical studies, automatic algorithm detection of the dermo-epidermal junction (DEJ) is needed. This may be difficult due to image noise from optical speckle, which requires specific image treatment procedures to reduce this. In the present work, a description of the position of the DEJ is given, and an algorithm for boundary detection is presented. Twenty-nine images were taken from the skin of normal healthy subjects, from five different body sites. Seven expert assessors were asked to trace the DEJ for ET measurement on each of the images. The variability between experts was compared with a new image processing method. Between-expert variability was relatively low with a mean standard deviation of 3.4 μm. However, local positioning of the DEJ between experts was often different. The described algorithm performed adequately on all images. ET was automatically measured with a precision of < 5 μm compared with the experts on all sites studied except that of the back. Moreover, the local algorithm positioning was verified. The new image processing method for measuring ET from OCT images significantly reduces calculation time for this parameter, and avoids user intervention. The main advantages of this are that data can be analyzed more rapidly and reproducibly in clinical trials. © 2011 John Wiley & Sons A/S.

3D bioprinting of functional human skin: production and in vivo analysis.

PubMed

Cubo, Nieves; Garcia, Marta; Del Cañizo, Juan F; Velasco, Diego; Jorcano, Jose L

2016-12-05

Significant progress has been made over the past 25 years in the development of in vitro-engineered substitutes that mimic human skin, either to be used as grafts for the replacement of lost skin, or for the establishment of in vitro human skin models. In this sense, laboratory-grown skin substitutes containing dermal and epidermal components offer a promising approach to skin engineering. In particular, a human plasma-based bilayered skin generated by our group, has been applied successfully to treat burns as well as traumatic and surgical wounds in a large number of patients in Spain. There are some aspects requiring improvements in the production process of this skin; for example, the relatively long time (three weeks) needed to produce the surface required to cover an extensive burn or a large wound, and the necessity to automatize and standardize a process currently performed manually. 3D bioprinting has emerged as a flexible tool in regenerative medicine and it provides a platform to address these challenges. In the present study, we have used this technique to print a human bilayered skin using bioinks containing human plasma as well as primary human fibroblasts and keratinocytes that were obtained from skin biopsies. We were able to generate 100 cm 2 , a standard P100 tissue culture plate, of printed skin in less than 35 min (including the 30 min required for fibrin gelation). We have analysed the structure and function of the printed skin using histological and immunohistochemical methods, both in 3D in vitro cultures and after long-term transplantation to immunodeficient mice. In both cases, the generated skin was very similar to human skin and, furthermore, it was indistinguishable from bilayered dermo-epidermal equivalents, handmade in our laboratories. These results demonstrate that 3D bioprinting is a suitable technology to generate bioengineered skin for therapeutical and industrial applications in an automatized manner.

46 CFR 161.002-9 - Automatic fire detecting system, power supply.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 6 2011-10-01 2011-10-01 false Automatic fire detecting system, power supply. 161.002-9 Section 161.002-9 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) EQUIPMENT...-9 Automatic fire detecting system, power supply. The power supply for an automatic fire detecting...

46 CFR 161.002-9 - Automatic fire detecting system, power supply.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 6 2010-10-01 2010-10-01 false Automatic fire detecting system, power supply. 161.002-9 Section 161.002-9 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) EQUIPMENT...-9 Automatic fire detecting system, power supply. The power supply for an automatic fire detecting...

Automated skin segmentation in ultrasonic evaluation of skin toxicity in breast cancer radiotherapy.

PubMed

Gao, Yi; Tannenbaum, Allen; Chen, Hao; Torres, Mylin; Yoshida, Emi; Yang, Xiaofeng; Wang, Yuefeng; Curran, Walter; Liu, Tian

2013-11-01

Skin toxicity is the most common side effect of breast cancer radiotherapy and impairs the quality of life of many breast cancer survivors. We, along with other researchers, have recently found quantitative ultrasound to be effective as a skin toxicity assessment tool. Although more reliable than standard clinical evaluations (visual observation and palpation), the current procedure for ultrasound-based skin toxicity measurements requires manual delineation of the skin layers (i.e., epidermis-dermis and dermis-hypodermis interfaces) on each ultrasound B-mode image. Manual skin segmentation is time consuming and subjective. Moreover, radiation-induced skin injury may decrease image contrast between the dermis and hypodermis, which increases the difficulty of delineation. Therefore, we have developed an automatic skin segmentation tool (ASST) based on the active contour model with two significant modifications: (i) The proposed algorithm introduces a novel dual-curve scheme for the double skin layer extraction, as opposed to the original single active contour method. (ii) The proposed algorithm is based on a geometric contour framework as opposed to the previous parametric algorithm. This ASST algorithm was tested on a breast cancer image database of 730 ultrasound breast images (73 ultrasound studies of 23 patients). We compared skin segmentation results obtained with the ASST with manual contours performed by two physicians. The average percentage differences in skin thickness between the ASST measurement and that of each physician were less than 5% (4.8 ± 17.8% and -3.8 ± 21.1%, respectively). In summary, we have developed an automatic skin segmentation method that ensures objective assessment of radiation-induced changes in skin thickness. Our ultrasound technology offers a unique opportunity to quantify tissue injury in a more meaningful and reproducible manner than the subjective assessments currently employed in the clinic. Copyright © 2013 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Dermoscopic Image Segmentation via Multistage Fully Convolutional Networks.

PubMed

Bi, Lei; Kim, Jinman; Ahn, Euijoon; Kumar, Ashnil; Fulham, Michael; Feng, Dagan

2017-09-01

Segmentation of skin lesions is an important step in the automated computer aided diagnosis of melanoma. However, existing segmentation methods have a tendency to over- or under-segment the lesions and perform poorly when the lesions have fuzzy boundaries, low contrast with the background, inhomogeneous textures, or contain artifacts. Furthermore, the performance of these methods are heavily reliant on the appropriate tuning of a large number of parameters as well as the use of effective preprocessing techniques, such as illumination correction and hair removal. We propose to leverage fully convolutional networks (FCNs) to automatically segment the skin lesions. FCNs are a neural network architecture that achieves object detection by hierarchically combining low-level appearance information with high-level semantic information. We address the issue of FCN producing coarse segmentation boundaries for challenging skin lesions (e.g., those with fuzzy boundaries and/or low difference in the textures between the foreground and the background) through a multistage segmentation approach in which multiple FCNs learn complementary visual characteristics of different skin lesions; early stage FCNs learn coarse appearance and localization information while late-stage FCNs learn the subtle characteristics of the lesion boundaries. We also introduce a new parallel integration method to combine the complementary information derived from individual segmentation stages to achieve a final segmentation result that has accurate localization and well-defined lesion boundaries, even for the most challenging skin lesions. We achieved an average Dice coefficient of 91.18% on the ISBI 2016 Skin Lesion Challenge dataset and 90.66% on the PH2 dataset. Our extensive experimental results on two well-established public benchmark datasets demonstrate that our method is more effective than other state-of-the-art methods for skin lesion segmentation.

A new method for skin color enhancement

NASA Astrophysics Data System (ADS)

Zeng, Huanzhao; Luo, Ronnier

2012-01-01

Skin tone is the most important color category in memory colors. Reproducing it pleasingly is an important factor in photographic color reproduction. Moving skin colors toward their preferred skin color center improves the skin color preference on photographic color reproduction. Two key factors to successfully enhance skin colors are: a method to detect original skin colors effectively even if they are shifted far away from the regular skin color region, and a method to morph skin colors toward a preferred skin color region properly without introducing artifacts. A method for skin color enhancement presented by the authors in the same conference last year applies a static skin color model for skin color detection, which may miss to detect skin colors that are far away from regular skin tones. In this paper, a new method using the combination of face detection and statistical skin color modeling is proposed to effectively detect skin pixels and to enhance skin colors more effectively.

Thermal imaging to detect physiological indicators of stress in humans

NASA Astrophysics Data System (ADS)

Cross, Carl B.; Skipper, Julie A.; Petkie, Douglas T.

2013-05-01

Real-time, stand-off sensing of human subjects to detect emotional state would be valuable in many defense, security and medical scenarios. We are developing a multimodal sensor platform that incorporates high-resolution electro-optical and mid-wave infrared (MWIR) cameras and a millimeter-wave radar system to identify individuals who are psychologically stressed. Recent experiments have aimed to: 1) assess responses to physical versus psychological stressors; 2) examine the impact of topical skin products on thermal signatures; and 3) evaluate the fidelity of vital signs extracted from thermal imagery and radar signatures. Registered image and sensor data were collected as subjects (n=32) performed mental and physical tasks. In each image, the face was segmented into 29 non-overlapping segments based on fiducial points automatically output by our facial feature tracker. Image features were defined that facilitated discrimination between psychological and physical stress states. To test the ability to intentionally mask thermal responses indicative of anxiety or fear, subjects applied one of four topical skin products to one half of their face before performing tasks. Finally, we evaluated the performance of two non-contact techniques to detect respiration and heart rate: chest displacement extracted from the radar signal and temperature fluctuations at the nose tip and regions near superficial arteries to detect respiration and heart rates, respectively, extracted from the MWIR imagery. Our results are very satisfactory: classification of physical versus psychological stressors is repeatedly greater than 90%, thermal masking was almost always ineffective, and accurate heart and respiration rates are detectable in both thermal and radar signatures.

The diagnostic performance of expert dermoscopists vs a computer-vision system on small-diameter melanomas.

PubMed

Friedman, Robert J; Gutkowicz-Krusin, Dina; Farber, Michele J; Warycha, Melanie; Schneider-Kels, Lori; Papastathis, Nicole; Mihm, Martin C; Googe, Paul; King, Roy; Prieto, Victor G; Kopf, Alfred W; Polsky, David; Rabinovitz, Harold; Oliviero, Margaret; Cognetta, Armand; Rigel, Darrell S; Marghoob, Ashfaq; Rivers, Jason; Johr, Robert; Grant-Kels, Jane M; Tsao, Hensin

2008-04-01

To evaluate the performance of dermoscopists in diagnosing small pigmented skin lesions (diameter

46 CFR 78.47-13 - Fire detecting and manual alarm, automatic sprinkler, and smoke detecting alarm bells.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., and smoke detecting alarm bells. 78.47-13 Section 78.47-13 Shipping COAST GUARD, DEPARTMENT OF.... § 78.47-13 Fire detecting and manual alarm, automatic sprinkler, and smoke detecting alarm bells. (a) The fire detecting and manual alarm automatic sprinklers, and smoke detecting alarm bells in the...

46 CFR 78.47-13 - Fire detecting and manual alarm, automatic sprinkler, and smoke detecting alarm bells.

Code of Federal Regulations, 2012 CFR

2012-10-01

..., and smoke detecting alarm bells. 78.47-13 Section 78.47-13 Shipping COAST GUARD, DEPARTMENT OF.... § 78.47-13 Fire detecting and manual alarm, automatic sprinkler, and smoke detecting alarm bells. (a) The fire detecting and manual alarm automatic sprinklers, and smoke detecting alarm bells in the...

46 CFR 78.47-13 - Fire detecting and manual alarm, automatic sprinkler, and smoke detecting alarm bells.

Code of Federal Regulations, 2010 CFR

2010-10-01

..., and smoke detecting alarm bells. 78.47-13 Section 78.47-13 Shipping COAST GUARD, DEPARTMENT OF.... § 78.47-13 Fire detecting and manual alarm, automatic sprinkler, and smoke detecting alarm bells. (a) The fire detecting and manual alarm automatic sprinklers, and smoke detecting alarm bells in the...

46 CFR 78.47-13 - Fire detecting and manual alarm, automatic sprinkler, and smoke detecting alarm bells.

Code of Federal Regulations, 2014 CFR

2014-10-01

..., and smoke detecting alarm bells. 78.47-13 Section 78.47-13 Shipping COAST GUARD, DEPARTMENT OF.... § 78.47-13 Fire detecting and manual alarm, automatic sprinkler, and smoke detecting alarm bells. (a) The fire detecting and manual alarm automatic sprinklers, and smoke detecting alarm bells in the...

46 CFR 78.47-13 - Fire detecting and manual alarm, automatic sprinkler, and smoke detecting alarm bells.

Code of Federal Regulations, 2013 CFR

2013-10-01

..., and smoke detecting alarm bells. 78.47-13 Section 78.47-13 Shipping COAST GUARD, DEPARTMENT OF.... § 78.47-13 Fire detecting and manual alarm, automatic sprinkler, and smoke detecting alarm bells. (a) The fire detecting and manual alarm automatic sprinklers, and smoke detecting alarm bells in the...

Localised photoplethysmography imaging for heart rate estimation of pre-term infants in the clinic

NASA Astrophysics Data System (ADS)

Chaichulee, Sitthichok; Villarroel, Mauricio; Jorge, João.; Arteta, Carlos; Green, Gabrielle; McCormick, Kenny; Zisserman, Andrew; Tarassenko, Lionel

2018-02-01

Non-contact vital-sign estimation allows the monitoring of physiological parameters (such as heart rate, respiratory rate, and peripheral oxygen saturation) without contact electrodes or sensors. Our recent work has demonstrated that a convolutional neural network (CNN) can be used to detect the presence of a patient and segment the patient's skin area for vital-sign estimation, thus enabling the automatic continuous monitoring of vital signs in a hospital environment. In a study approved by the local Research Ethical Committee, we made video recordings of pre-term infants nursed in a Neonatal Intensive Care Unit (NICU) at the John Radcliffe Hospital in Oxford, UK. We extended the CNN model to detect the head, torso and diaper of the infants. We extracted multiple photoplethysmographic imaging (PPGi) signals from each body part, analysed their signal quality, and compared them with the PPGi signal derived from the entire skin area. Our results demonstrated the benefits of estimating heart rate combined from multiple regions of interest using data fusion. In the test dataset, we achieved a mean absolute error of 2.4 beats per minute for 80% (31.1 hours) from a total recording time of 38.5 hours for which both reference heart rate and video data were valid.

46 CFR 161.002-2 - Types of fire-protective systems.

Code of Federal Regulations, 2013 CFR

2013-10-01

..., but not be limited to, automatic fire and smoke detecting systems, manual fire alarm systems, sample extraction smoke detection systems, watchman's supervisory systems, and combinations of these systems. (b) Automatic fire detecting systems. For the purpose of this subpart, automatic fire and smoke detecting...

46 CFR 161.002-2 - Types of fire-protective systems.

Code of Federal Regulations, 2014 CFR

2014-10-01

..., but not be limited to, automatic fire and smoke detecting systems, manual fire alarm systems, sample extraction smoke detection systems, watchman's supervisory systems, and combinations of these systems. (b) Automatic fire detecting systems. For the purpose of this subpart, automatic fire and smoke detecting...

Over-exposure correction in knee cone-beam CT imaging with automatic exposure control using a partial low dose scan

NASA Astrophysics Data System (ADS)

Choi, Jang-Hwan; Muller, Kerstin; Hsieh, Scott; Maier, Andreas; Gold, Garry; Levenston, Marc; Fahrig, Rebecca

2016-03-01

C-arm-based cone-beam CT (CBCT) systems with flat-panel detectors are suitable for diagnostic knee imaging due to their potentially flexible selection of CT trajectories and wide volumetric beam coverage. In knee CT imaging, over-exposure artifacts can occur because of limitations in the dynamic range of the flat panel detectors present on most CBCT systems. We developed a straightforward but effective method for correction and detection of over-exposure for an Automatic Exposure Control (AEC)-enabled standard knee scan incorporating a prior low dose scan. The radiation dose associated with the low dose scan was negligible (0.0042mSv, 2.8% increase) which was enabled by partially sampling the projection images considering the geometry of the knees and lowering the dose further to be able to just see the skin-air interface. We combined the line integrals from the AEC and low dose scans after detecting over-exposed regions by comparing the line profiles of the two scans detector row-wise. The combined line integrals were reconstructed into a volumetric image using filtered back projection. We evaluated our method using in vivo human subject knee data. The proposed method effectively corrected and detected over-exposure, and thus recovered the visibility of exterior tissues (e.g., the shape and density of the patella, and the patellar tendon), incorporating a prior low dose scan with a negligible increase in radiation exposure.

980 nm diode laser with automatic power control mode for dermatological applications

NASA Astrophysics Data System (ADS)

Belikov, Andrey V.; Gelfond, Mark L.; Shatilova, Ksenia V.; Sosenkova, Svetlana A.; Lazareva, Anastasia A.

2015-07-01

Results of nevus, papilloma, dermatofibroma, and basal cell skin cancer removal by a 980+/-10 nm diode laser with "blackened" tip operating in continuous (CW) mode and automatic power control (APC) mode are compared. It was demonstrated that using APC mode decreases the width of collateral damage at removing of these nosological neoplasms of human skin. The mean width of collateral damage reached 0.846+/-0.139 mm for patient group with nevus removing by 980 nm diode laser operating in CW mode, papilloma - 0.443+/-0.312 mm, dermatofibroma - 0.923+/-0.271 mm, and basal cell skin cancer - 0.787+/-0.325 mm. The mean width of collateral damage reached 0.592+/-0.197 mm for patient group with nevus removing by 980 nm diode laser operating in APC mode, papilloma - 0.191+/-0.162 mm, dermatofibroma - 0.476+/-0.366 mm, and basal cell skin cancer - 0.517+/-0.374 mm. It was found that the percentage of laser wounds with collateral damage less than 300 μm of quantity of removed nosological neoplasms in APC mode is 50%, that significantly higher than the percentage of laser wounds obtained using CW mode (13.4%).

A Marked Poisson Process Driven Latent Shape Model for 3D Segmentation of Reflectance Confocal Microscopy Image Stacks of Human Skin.

PubMed

Ghanta, Sindhu; Jordan, Michael I; Kose, Kivanc; Brooks, Dana H; Rajadhyaksha, Milind; Dy, Jennifer G

2017-01-01

Segmenting objects of interest from 3D data sets is a common problem encountered in biological data. Small field of view and intrinsic biological variability combined with optically subtle changes of intensity, resolution, and low contrast in images make the task of segmentation difficult, especially for microscopy of unstained living or freshly excised thick tissues. Incorporating shape information in addition to the appearance of the object of interest can often help improve segmentation performance. However, the shapes of objects in tissue can be highly variable and design of a flexible shape model that encompasses these variations is challenging. To address such complex segmentation problems, we propose a unified probabilistic framework that can incorporate the uncertainty associated with complex shapes, variable appearance, and unknown locations. The driving application that inspired the development of this framework is a biologically important segmentation problem: the task of automatically detecting and segmenting the dermal-epidermal junction (DEJ) in 3D reflectance confocal microscopy (RCM) images of human skin. RCM imaging allows noninvasive observation of cellular, nuclear, and morphological detail. The DEJ is an important morphological feature as it is where disorder, disease, and cancer usually start. Detecting the DEJ is challenging, because it is a 2D surface in a 3D volume which has strong but highly variable number of irregularly spaced and variably shaped "peaks and valleys." In addition, RCM imaging resolution, contrast, and intensity vary with depth. Thus, a prior model needs to incorporate the intrinsic structure while allowing variability in essentially all its parameters. We propose a model which can incorporate objects of interest with complex shapes and variable appearance in an unsupervised setting by utilizing domain knowledge to build appropriate priors of the model. Our novel strategy to model this structure combines a spatial Poisson process with shape priors and performs inference using Gibbs sampling. Experimental results show that the proposed unsupervised model is able to automatically detect the DEJ with physiologically relevant accuracy in the range 10- 20 μm .

A Marked Poisson Process Driven Latent Shape Model for 3D Segmentation of Reflectance Confocal Microscopy Image Stacks of Human Skin

PubMed Central

Ghanta, Sindhu; Jordan, Michael I.; Kose, Kivanc; Brooks, Dana H.; Rajadhyaksha, Milind; Dy, Jennifer G.

2016-01-01

Segmenting objects of interest from 3D datasets is a common problem encountered in biological data. Small field of view and intrinsic biological variability combined with optically subtle changes of intensity, resolution and low contrast in images make the task of segmentation difficult, especially for microscopy of unstained living or freshly excised thick tissues. Incorporating shape information in addition to the appearance of the object of interest can often help improve segmentation performance. However, shapes of objects in tissue can be highly variable and design of a flexible shape model that encompasses these variations is challenging. To address such complex segmentation problems, we propose a unified probabilistic framework that can incorporate the uncertainty associated with complex shapes, variable appearance and unknown locations. The driving application which inspired the development of this framework is a biologically important segmentation problem: the task of automatically detecting and segmenting the dermal-epidermal junction (DEJ) in 3D reflectance confocal microscopy (RCM) images of human skin. RCM imaging allows noninvasive observation of cellular, nuclear and morphological detail. The DEJ is an important morphological feature as it is where disorder, disease and cancer usually start. Detecting the DEJ is challenging because it is a 2D surface in a 3D volume which has strong but highly variable number of irregularly spaced and variably shaped “peaks and valleys”. In addition, RCM imaging resolution, contrast and intensity vary with depth. Thus a prior model needs to incorporate the intrinsic structure while allowing variability in essentially all its parameters. We propose a model which can incorporate objects of interest with complex shapes and variable appearance in an unsupervised setting by utilizing domain knowledge to build appropriate priors of the model. Our novel strategy to model this structure combines a spatial Poisson process with shape priors and performs inference using Gibbs sampling. Experimental results show that the proposed unsupervised model is able to automatically detect the DEJ with physiologically relevant accuracy in the range 10 – 20µm. PMID:27723590

Monitoring Chewing and Eating in Free-Living Using Smart Eyeglasses.

PubMed

Zhang, Rui; Amft, Oliver

2018-01-01

We propose to 3-D-print personal fitted regular-look smart eyeglasses frames equipped with bilateral electromyography recording to monitor temporalis muscles' activity for automatic dietary monitoring. Personal fitting supported electrode-skin contacts are at temple ear bend and temple end positions. We evaluated the smart monitoring eyeglasses during in-lab and free-living studies of food chewing and eating event detection with ten participants. The in-lab study was designed to explore three natural food hardness levels and determine parameters of an energy-based chewing cycle detection. Our free-living study investigated whether chewing monitoring and eating event detection using smart eyeglasses is feasible in free-living. An eating event detection algorithm was developed to determine intake activities based on the estimated chewing rate. Results showed an average food hardness classification accuracy of 94% and chewing cycle detection precision and recall above 90% for the in-lab study and above 77% for the free-living study covering 122 hours of recordings. Eating detection revealed the 44 eating events with an average accuracy above 95%. We conclude that smart eyeglasses are suitable for monitoring chewing and eating events in free-living and even could provide further insights into the wearer's natural chewing patterns.

SparCLeS: dynamic l₁ sparse classifiers with level sets for robust beard/moustache detection and segmentation.

PubMed

Le, T Hoang Ngan; Luu, Khoa; Savvides, Marios

2013-08-01

Robust facial hair detection and segmentation is a highly valued soft biometric attribute for carrying out forensic facial analysis. In this paper, we propose a novel and fully automatic system, called SparCLeS, for beard/moustache detection and segmentation in challenging facial images. SparCLeS uses the multiscale self-quotient (MSQ) algorithm to preprocess facial images and deal with illumination variation. Histogram of oriented gradients (HOG) features are extracted from the preprocessed images and a dynamic sparse classifier is built using these features to classify a facial region as either containing skin or facial hair. A level set based approach, which makes use of the advantages of both global and local information, is then used to segment the regions of a face containing facial hair. Experimental results demonstrate the effectiveness of our proposed system in detecting and segmenting facial hair regions in images drawn from three databases, i.e., the NIST Multiple Biometric Grand Challenge (MBGC) still face database, the NIST Color Facial Recognition Technology FERET database, and the Labeled Faces in the Wild (LFW) database.

Computer systems for automatic earthquake detection

USGS Publications Warehouse

Stewart, S.W.

1974-01-01

U.S Geological Survey seismologists in Menlo park, California, are utilizing the speed, reliability, and efficiency of minicomputers to monitor seismograph stations and to automatically detect earthquakes. An earthquake detection computer system, believed to be the only one of its kind in operation, automatically reports about 90 percent of all local earthquakes recorded by a network of over 100 central California seismograph stations. The system also monitors the stations for signs of malfunction or abnormal operation. Before the automatic system was put in operation, all of the earthquakes recorded had to be detected by manually searching the records, a time-consuming process. With the automatic detection system, the stations are efficiently monitored continuously. 

Automatic Fastening Large Structures: a New Approach

NASA Technical Reports Server (NTRS)

Lumley, D. F.

1985-01-01

The external tank (ET) intertank structure for the space shuttle, a 27.5 ft diameter 22.5 ft long externally stiffened mechanically fastened skin-stringer-frame structure, was a labor intensitive manual structure built on a modified Saturn tooling position. A new approach was developed based on half-section subassemblies. The heart of this manufacturing approach will be 33 ft high vertical automatic riveting system with a 28 ft rotary positioner coming on-line in mid 1985. The Automatic Riveting System incorporates many of the latest automatic riveting technologies. Key features include: vertical columns with two sets of independently operating CNC drill-riveting heads; capability of drill, insert and upset any one piece fastener up to 3/8 inch diameter including slugs without displacing the workpiece offset bucking ram with programmable rotation and deep retraction; vision system for automatic parts program re-synchronization and part edge margin control; and an automatic rivet selection/handling system.

SU-E-T-362: Automatic Catheter Reconstruction of Flap Applicators in HDR Surface Brachytherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Buzurovic, I; Devlin, P; Hansen, J

2014-06-01

Purpose: Catheter reconstruction is crucial for the accurate delivery of radiation dose in HDR brachytherapy. The process becomes complicated and time-consuming for large superficial clinical targets with a complex topology. A novel method for the automatic catheter reconstruction of flap applicators is proposed in this study. Methods: We have developed a program package capable of image manipulation, using C++class libraries of The-Visualization-Toolkit(VTK) software system. The workflow for automatic catheter reconstruction is: a)an anchor point is placed in 3D or in the axial view of the first slice at the tip of the first, last and middle points for the curvedmore » surface; b)similar points are placed on the last slice of the image set; c)the surface detection algorithm automatically registers the points to the images and applies the surface reconstruction filter; d)then a structured grid surface is generated through the center of the treatment catheters placed at a distance of 5mm from the patient's skin. As a result, a mesh-style plane is generated with the reconstructed catheters placed 10mm apart. To demonstrate automatic catheter reconstruction, we used CT images of patients diagnosed with cutaneous T-cell-lymphoma and imaged with Freiburg-Flap-Applicators (Nucletron™-Elekta, Netherlands). The coordinates for each catheter were generated and compared to the control points selected during the manual reconstruction for 16catheters and 368control point Results: The variation of the catheter tip positions between the automatically and manually reconstructed catheters was 0.17mm(SD=0.23mm). The position difference between the manually selected catheter control points and the corresponding points obtained automatically was 0.17mm in the x-direction (SD=0.23mm), 0.13mm in the y-direction (SD=0.22mm), and 0.14mm in the z-direction (SD=0.24mm). Conclusion: This study shows the feasibility of the automatic catheter reconstruction of flap applicators with a high level of positioning accuracy. Implementation of this technique has potential to decrease the planning time and may improve overall quality in superficial brachytherapy.« less

Automatic detection of confusion in elderly users of a web-based health instruction video.

PubMed

Postma-Nilsenová, Marie; Postma, Eric; Tates, Kiek

2015-06-01

Because of cognitive limitations and lower health literacy, many elderly patients have difficulty understanding verbal medical instructions. Automatic detection of facial movements provides a nonintrusive basis for building technological tools supporting confusion detection in healthcare delivery applications on the Internet. Twenty-four elderly participants (70-90 years old) were recorded while watching Web-based health instruction videos involving easy and complex medical terminology. Relevant fragments of the participants' facial expressions were rated by 40 medical students for perceived level of confusion and analyzed with automatic software for facial movement recognition. A computer classification of the automatically detected facial features performed more accurately and with a higher sensitivity than the human observers (automatic detection and classification, 64% accuracy, 0.64 sensitivity; human observers, 41% accuracy, 0.43 sensitivity). A drill-down analysis of cues to confusion indicated the importance of the eye and eyebrow region. Confusion caused by misunderstanding of medical terminology is signaled by facial cues that can be automatically detected with currently available facial expression detection technology. The findings are relevant for the development of Web-based services for healthcare consumers.

Combinatorial Color Space Models for Skin Detection in Sub-continental Human Images

NASA Astrophysics Data System (ADS)

Khaled, Shah Mostafa; Saiful Islam, Md.; Rabbani, Md. Golam; Tabassum, Mirza Rehenuma; Gias, Alim Ul; Kamal, Md. Mostafa; Muctadir, Hossain Muhammad; Shakir, Asif Khan; Imran, Asif; Islam, Saiful

Among different color models HSV, HLS, YIQ, YCbCr, YUV, etc. have been most popular for skin detection. Most of the research done in the field of skin detection has been trained and tested on human images of African, Mongolian and Anglo-Saxon ethnic origins, skin colors of Indian sub-continentals have not been focused separately. Combinatorial algorithms, without affecting asymptotic complexity can be developed using the skin detection concepts of these color models for boosting detection performance. In this paper a comparative study of different combinatorial skin detection algorithms have been made. For training and testing 200 images (skin and non skin) containing pictures of sub-continental male and females have been used to measure the performance of the combinatorial approaches, and considerable development in success rate with True Positive of 99.5% and True Negative of 93.3% have been observed.

Automatic color preference correction for color reproduction

NASA Astrophysics Data System (ADS)

Tsukada, Masato; Funayama, Chisato; Tajima, Johji

2000-12-01

The reproduction of natural objects in color images has attracted a great deal of attention. Reproduction more pleasing colors of natural objects is one of the methods available to improve image quality. We developed an automatic color correction method to maintain preferred color reproduction for three significant categories: facial skin color, green grass and blue sky. In this method, a representative color in an object area to be corrected is automatically extracted from an input image, and a set of color correction parameters is selected depending on the representative color. The improvement in image quality for reproductions of natural image was more than 93 percent in subjective experiments. These results show the usefulness of our automatic color correction method for the reproduction of preferred colors.

Apparatus and method for skin packaging articles

NASA Technical Reports Server (NTRS)

Madsen, B.; Pozsony, E. R.; Collin, E. E. (Inventor)

1973-01-01

A system for skin packaging articles including a loading zone for positioning articles to be packaged upon a substrate, a thermoplastic film heating and vacuum operated skin packaging zone for covering the articles with film laminated to the substrate and a slitting zone for separating and trimming the individual skin packaged articles. The articles are passed to the successive zones. The loading zone may be adapted for conveyorized instead of hand loading. In some cases, where only transverse cutting of the film web is necessary, it may be desirable to eliminate the slitting zone and remove the skin packaged article or articles directly from the packaging zone. A conveniently located operating panel contains controls for effecting automatic, semiautomatic or manual operation of the entire system of any portions in any manner desired.

In vivo hyperspectral imaging and differentiation of skin cancer

NASA Astrophysics Data System (ADS)

Zherdeva, Larisa A.; Bratchenko, Ivan A.; Myakinin, Oleg O.; Moryatov, Alexander A.; Kozlov, Sergey V.; Zakharov, Valery P.

2016-10-01

Results of hyperspectral imaging analysis for in vivo visualization of skin neoplasms are presented. 16 melanomas, 19 basal cell carcinomas and 10 benign tumors with different stages of neoplasm growth were tested. The HSI system provide skin tissue images with 5 nm spectral resolution in the range of 450-750 nm with automatic stabilization of each frame compensating displacement of the scanning area due to spontaneous macro-movements of the patient. The integrated optical densities in 530-600 and 600-670 nm ranges are used for real-time hemoglobin and melanin distribution imaging in skin tissue. It was shown that the total accuracy of skin cancer identification exceeds 90% and 70% for differentiation of melanomas from BCC and begihn tumors. It was demonstrated the possibility for HSI classification of melanomas of different stages.

Differences between automatically detected and steady-state fractional flow reserve.

PubMed

Härle, Tobias; Meyer, Sven; Vahldiek, Felix; Elsässer, Albrecht

2016-02-01

Measurement of fractional flow reserve (FFR) has become a standard diagnostic tool in the catheterization laboratory. FFR evaluation studies were based on pressure recordings during steady-state maximum hyperemia. Commercially available computer systems detect the lowest Pd/Pa ratio automatically, which might not always be measured during steady-state hyperemia. We sought to compare the automatically detected FFR and true steady-state FFR. Pressure measurement traces of 105 coronary lesions from 77 patients with intermediate coronary lesions or multivessel disease were reviewed. In all patients, hyperemia had been achieved by intravenous adenosine administration using a dosage of 140 µg/kg/min. In 42 lesions (40%) automatically detected FFR was lower than true steady-state FFR. Mean bias was 0.009 (standard deviation 0.015, limits of agreement -0.02, 0.037). In 4 lesions (3.8%) both methods lead to different treatment recommendations, in all 4 cases instantaneous wave-free ratio confirmed steady-state FFR. Automatically detected FFR was slightly lower than steady-state FFR in more than one-third of cases. Consequently, interpretation of automatically detected FFR values closely below the cutoff value requires special attention.

Automated Estimation of Melanocytic Skin Tumor Thickness by Ultrasonic Radiofrequency Data.

PubMed

Andrekute, Kristina; Valiukeviciene, Skaidra; Raisutis, Renaldas; Linkeviciute, Gintare; Makstiene, Jurgita; Kliunkiene, Renata

2016-05-01

High-frequency (>20-MHz) ultrasound (US) is a noninvasive preoperative tool for assessment of melanocytic skin tumor thickness. Ultrasonic melanocytic skin tumor thickness estimation is not always easy and is related to the experience of the clinician. In this article, we present an automated thickness measurement method based on time-frequency analysis of US radiofrequency signals. The study was performed on 52 thin (≤1-mm) melanocytic skin tumors (46 melanocytic nevi and 6 melanomas). Radiofrequency signals were obtained with a single-element focused transducer (fundamental frequency, 22 MHz; bandwidth, 12-28 MHz). The radiofrequency data were analyzed in the time-frequency domain to make the tumor boundaries more noticeable. The thicknesses of the tumors were evaluated by 3 different metrics: histologically measured Breslow thickness, manually measured US thickness, and automatically measured US thickness. The results showed a higher correlation coefficient between the automatically measured US thickness and Breslow thickness (r= 0.83; P< .0001) than the manually measured US thickness (r = 0.68; P < .0001). The sensitivity of the automated tumor thickness measurement algorithm was 96.55%, and the specificity was 78.26% compared with histologic measurement. The sensitivity of the manually measured US thickness was 75.86%, and the specificity was 73.91%. The efficient automated tumor thickness measurement method developed could be used as a tool for preoperative assessment of melanocytic skin tumor thickness. © 2016 by the American Institute of Ultrasound in Medicine.

A Physical Model of Human Skin and Its Application for Search and Rescue

DTIC Science & Technology

2009-12-01

allow iv for the development of skin detection algorithms with a high probability of detection (PD) and a low probability of false alarm ( PFA ). The...various skin colors were collected. The skin detection algorithm developed in this work had a PD as high as 0.95 with a PFA of 0.006. Skin...threshold 0 < γ < 1. . . . . . . . . . . . . 103 63. Top: Detection Image with NDSI threshold γ = 0.314 with PD = 0.95 and corresponding PFA = 0.0156

Algorithm for Automatic Detection, Localization and Characterization of Magnetic Dipole Targets Using the Laser Scalar Gradiometer

DTIC Science & Technology

2016-06-01

TECHNICAL REPORT Algorithm for Automatic Detection, Localization and Characterization of Magnetic Dipole Targets Using the Laser Scalar...Automatic Detection, Localization and Characterization of Magnetic Dipole Targets Using the Laser Scalar Gradiometer Leon Vaizer, Jesse Angle, Neil...of Magnetic Dipole Targets Using LSG i June 2016 TABLE OF CONTENTS INTRODUCTION

Semi-automatic mapping of cultural heritage from airborne laser scanning using deep learning

NASA Astrophysics Data System (ADS)

Due Trier, Øivind; Salberg, Arnt-Børre; Holger Pilø, Lars; Tonning, Christer; Marius Johansen, Hans; Aarsten, Dagrun

2016-04-01

This paper proposes to use deep learning to improve semi-automatic mapping of cultural heritage from airborne laser scanning (ALS) data. Automatic detection methods, based on traditional pattern recognition, have been applied in a number of cultural heritage mapping projects in Norway for the past five years. Automatic detection of pits and heaps have been combined with visual interpretation of the ALS data for the mapping of deer hunting systems, iron production sites, grave mounds and charcoal kilns. However, the performance of the automatic detection methods varies substantially between ALS datasets. For the mapping of deer hunting systems on flat gravel and sand sediment deposits, the automatic detection results were almost perfect. However, some false detections appeared in the terrain outside of the sediment deposits. These could be explained by other pit-like landscape features, like parts of river courses, spaces between boulders, and modern terrain modifications. However, these were easy to spot during visual interpretation, and the number of missed individual pitfall traps was still low. For the mapping of grave mounds, the automatic method produced a large number of false detections, reducing the usefulness of the semi-automatic approach. The mound structure is a very common natural terrain feature, and the grave mounds are less distinct in shape than the pitfall traps. Still, applying automatic mound detection on an entire municipality did lead to a new discovery of an Iron Age grave field with more than 15 individual mounds. Automatic mound detection also proved to be useful for a detailed re-mapping of Norway's largest Iron Age grave yard, which contains almost 1000 individual graves. Combined pit and mound detection has been applied to the mapping of more than 1000 charcoal kilns that were used by an iron work 350-200 years ago. The majority of charcoal kilns were indirectly detected as either pits on the circumference, a central mound, or both. However, kilns with a flat interior and a shallow ditch along the circumference were often missed by the automatic detection method. The successfulness of automatic detection seems to depend on two factors: (1) the density of ALS ground hits on the cultural heritage structures being sought, and (2) to what extent these structures stand out from natural terrain structures. The first factor may, to some extent, be improved by using a higher number of ALS pulses per square meter. The second factor is difficult to change, and also highlights another challenge: how to make a general automatic method that is applicable in all types of terrain within a country. The mixed experience with traditional pattern recognition for semi-automatic mapping of cultural heritage led us to consider deep learning as an alternative approach. The main principle is that a general feature detector has been trained on a large image database. The feature detector is then tailored to a specific task by using a modest number of images of true and false examples of the features being sought. Results of using deep learning are compared with previous results using traditional pattern recognition.

A Hybrid Color Space for Skin Detection Using Genetic Algorithm Heuristic Search and Principal Component Analysis Technique

PubMed Central

2015-01-01

Color is one of the most prominent features of an image and used in many skin and face detection applications. Color space transformation is widely used by researchers to improve face and skin detection performance. Despite the substantial research efforts in this area, choosing a proper color space in terms of skin and face classification performance which can address issues like illumination variations, various camera characteristics and diversity in skin color tones has remained an open issue. This research proposes a new three-dimensional hybrid color space termed SKN by employing the Genetic Algorithm heuristic and Principal Component Analysis to find the optimal representation of human skin color in over seventeen existing color spaces. Genetic Algorithm heuristic is used to find the optimal color component combination setup in terms of skin detection accuracy while the Principal Component Analysis projects the optimal Genetic Algorithm solution to a less complex dimension. Pixel wise skin detection was used to evaluate the performance of the proposed color space. We have employed four classifiers including Random Forest, Naïve Bayes, Support Vector Machine and Multilayer Perceptron in order to generate the human skin color predictive model. The proposed color space was compared to some existing color spaces and shows superior results in terms of pixel-wise skin detection accuracy. Experimental results show that by using Random Forest classifier, the proposed SKN color space obtained an average F-score and True Positive Rate of 0.953 and False Positive Rate of 0.0482 which outperformed the existing color spaces in terms of pixel wise skin detection accuracy. The results also indicate that among the classifiers used in this study, Random Forest is the most suitable classifier for pixel wise skin detection applications. PMID:26267377

Image quality enhancement for skin cancer optical diagnostics

NASA Astrophysics Data System (ADS)

Bliznuks, Dmitrijs; Kuzmina, Ilona; Bolocko, Katrina; Lihachev, Alexey

2017-12-01

The research presents image quality analysis and enhancement proposals in biophotonic area. The sources of image problems are reviewed and analyzed. The problems with most impact in biophotonic area are analyzed in terms of specific biophotonic task - skin cancer diagnostics. The results point out that main problem for skin cancer analysis is the skin illumination problems. Since it is often not possible to prevent illumination problems, the paper proposes image post processing algorithm - low frequency filtering. Practical results show diagnostic results improvement after using proposed filter. Along that, filter do not reduces diagnostic results' quality for images without illumination defects. Current filtering algorithm requires empirical tuning of filter parameters. Further work needed to test the algorithm in other biophotonic applications and propose automatic filter parameter selection.

Automatic multimodal detection for long-term seizure documentation in epilepsy.

PubMed

Fürbass, F; Kampusch, S; Kaniusas, E; Koren, J; Pirker, S; Hopfengärtner, R; Stefan, H; Kluge, T; Baumgartner, C

2017-08-01

This study investigated sensitivity and false detection rate of a multimodal automatic seizure detection algorithm and the applicability to reduced electrode montages for long-term seizure documentation in epilepsy patients. An automatic seizure detection algorithm based on EEG, EMG, and ECG signals was developed. EEG/ECG recordings of 92 patients from two epilepsy monitoring units including 494 seizures were used to assess detection performance. EMG data were extracted by bandpass filtering of EEG signals. Sensitivity and false detection rate were evaluated for each signal modality and for reduced electrode montages. All focal seizures evolving to bilateral tonic-clonic (BTCS, n=50) and 89% of focal seizures (FS, n=139) were detected. Average sensitivity in temporal lobe epilepsy (TLE) patients was 94% and 74% in extratemporal lobe epilepsy (XTLE) patients. Overall detection sensitivity was 86%. Average false detection rate was 12.8 false detections in 24h (FD/24h) for TLE and 22 FD/24h in XTLE patients. Utilization of 8 frontal and temporal electrodes reduced average sensitivity from 86% to 81%. Our automatic multimodal seizure detection algorithm shows high sensitivity with full and reduced electrode montages. Evaluation of different signal modalities and electrode montages paces the way for semi-automatic seizure documentation systems. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Screening Test for Shed Skin Cells by Measuring the Ratio of Human DNA to Staphylococcus epidermidis DNA.

PubMed

Nakanishi, Hiroaki; Ohmori, Takeshi; Hara, Masaaki; Takahashi, Shirushi; Kurosu, Akira; Takada, Aya; Saito, Kazuyuki

2016-05-01

A novel screening method for shed skin cells by detecting Staphylococcus epidermidis (S. epidermidis), which is a resident bacterium on skin, was developed. Staphylococcus epidermidis was detected using real-time PCR. Staphylococcus epidermidis was detected in all 20 human skin surface samples. Although not present in blood and urine samples, S. epidermidis was detected in 6 of 20 saliva samples, and 5 of 18 semen samples. The ratio of human DNA to S. epidermidisDNA was significantly smaller in human skin surface samples than in saliva and semen samples in which S. epidermidis was detected. Therefore, although skin cells could not be identified by detecting only S. epidermidis, they could be distinguished by measuring the S. epidermidis to human DNA ratio. This method could be applied to casework touch samples, which suggests that it is useful for screening whether skin cells and human DNA are present on potential evidentiary touch samples. © 2016 American Academy of Forensic Sciences.

Skin Color Segmentation Using Coarse-to-Fine Region on Normalized RGB Chromaticity Diagram for Face Detection

NASA Astrophysics Data System (ADS)

Soetedjo, Aryuanto; Yamada, Koichi

This paper describes a new color segmentation based on a normalized RGB chromaticity diagram for face detection. Face skin is extracted from color images using a coarse skin region with fixed boundaries followed by a fine skin region with variable boundaries. Two newly developed histograms that have prominent peaks of skin color and non-skin colors are employed to adjust the boundaries of the skin region. The proposed approach does not need a skin color model, which depends on a specific camera parameter and is usually limited to a particular environment condition, and no sample images are required. The experimental results using color face images of various races under varying lighting conditions and complex backgrounds, obtained from four different resources on the Internet, show a high detection rate of 87%. The results of the detection rate and computation time are comparable to the well known real-time face detection method proposed by Viola-Jones [11], [12].

Automatic Residential/Commercial Classification of Parcels with Solar Panel Detections

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morton, April M; Omitaomu, Olufemi A; Kotikot, Susan

A computational method to automatically detect solar panels on rooftops to aid policy and financial assessment of solar distributed generation. The code automatically classifies parcels containing solar panels in the U.S. as residential or commercial. The code allows the user to specify an input dataset containing parcels and detected solar panels, and then uses information about the parcels and solar panels to automatically classify the rooftops as residential or commercial using machine learning techniques. The zip file containing the code includes sample input and output datasets for the Boston and DC areas.

Cupping artifact correction and automated classification for high-resolution dedicated breast CT images.

PubMed

Yang, Xiaofeng; Wu, Shengyong; Sechopoulos, Ioannis; Fei, Baowei

2012-10-01

To develop and test an automated algorithm to classify the different tissues present in dedicated breast CT images. The original CT images are first corrected to overcome cupping artifacts, and then a multiscale bilateral filter is used to reduce noise while keeping edge information on the images. As skin and glandular tissues have similar CT values on breast CT images, morphologic processing is used to identify the skin mask based on its position information. A modified fuzzy C-means (FCM) classification method is then used to classify breast tissue as fat and glandular tissue. By combining the results of the skin mask with the FCM, the breast tissue is classified as skin, fat, and glandular tissue. To evaluate the authors' classification method, the authors use Dice overlap ratios to compare the results of the automated classification to those obtained by manual segmentation on eight patient images. The correction method was able to correct the cupping artifacts and improve the quality of the breast CT images. For glandular tissue, the overlap ratios between the authors' automatic classification and manual segmentation were 91.6% ± 2.0%. A cupping artifact correction method and an automatic classification method were applied and evaluated for high-resolution dedicated breast CT images. Breast tissue classification can provide quantitative measurements regarding breast composition, density, and tissue distribution.

Cupping artifact correction and automated classification for high-resolution dedicated breast CT images

PubMed Central

Yang, Xiaofeng; Wu, Shengyong; Sechopoulos, Ioannis; Fei, Baowei

2012-01-01

Purpose: To develop and test an automated algorithm to classify the different tissues present in dedicated breast CT images. Methods: The original CT images are first corrected to overcome cupping artifacts, and then a multiscale bilateral filter is used to reduce noise while keeping edge information on the images. As skin and glandular tissues have similar CT values on breast CT images, morphologic processing is used to identify the skin mask based on its position information. A modified fuzzy C-means (FCM) classification method is then used to classify breast tissue as fat and glandular tissue. By combining the results of the skin mask with the FCM, the breast tissue is classified as skin, fat, and glandular tissue. To evaluate the authors’ classification method, the authors use Dice overlap ratios to compare the results of the automated classification to those obtained by manual segmentation on eight patient images. Results: The correction method was able to correct the cupping artifacts and improve the quality of the breast CT images. For glandular tissue, the overlap ratios between the authors’ automatic classification and manual segmentation were 91.6% ± 2.0%. Conclusions: A cupping artifact correction method and an automatic classification method were applied and evaluated for high-resolution dedicated breast CT images. Breast tissue classification can provide quantitative measurements regarding breast composition, density, and tissue distribution. PMID:23039675

Review of automatic detection of pig behaviours by using image analysis

NASA Astrophysics Data System (ADS)

Han, Shuqing; Zhang, Jianhua; Zhu, Mengshuai; Wu, Jianzhai; Kong, Fantao

2017-06-01

Automatic detection of lying, moving, feeding, drinking, and aggressive behaviours of pigs by means of image analysis can save observation input by staff. It would help staff make early detection of diseases or injuries of pigs during breeding and improve management efficiency of swine industry. This study describes the progress of pig behaviour detection based on image analysis and advancement in image segmentation of pig body, segmentation of pig adhesion and extraction of pig behaviour characteristic parameters. Challenges for achieving automatic detection of pig behaviours were summarized.

Automatic detection and quantification of pulmonary arterio-venous malformations in hereditary hemorrhagic telangiectasia

NASA Astrophysics Data System (ADS)

Fetita, Catalin; Fortemps de Loneux, Thierry; Kouvahe, Amélé Florence; El Hajjam, Mostafa

2017-03-01

Hereditary hemorrhagic telangiectasia (HHT) is an autosomic dominant disorder, which is characterized by the development of multiple arterio-venous malformations in the skin, mucous membranes, and/or visceral organs. Pulmonary Arterio-Venous Malformation (PAVM) is an abnormal connection where feeding arteries shunt directly into draining veins with no intervening capillary bed. This condition may lead to paradoxical embolism and hemorrhagic complications. PAVMs patients should systematically be screened as the spontaneous complication rate is high, reaching almost 50%. Chest enhanced contrast CT scanner is the reference screening and follow-up examination. When performed by experienced operators as the prime treatment, percutaneous embolization of PAVMs is a safe, efficient and sustained therapy. The accuracy of PAVM detection and quantification of its progression over time is the key of embolotherapy success. In this paper, we propose an automatic method for PAVM detection and quantification relying on a modeling of vessel deformation, i.e. local caliber increase, based on mathematical morphology. The pulmonary field and vessels are first segmented using geodesic operators. The vessel caliber is estimated by means of a granulometric measure and the local caliber increase is detected by using a geodesic operator, the h-maxdomes. The detection sensitivity can be tuned up according to the choice of the h value which models the irregularity of the vessel caliber along its axis and the PAVM selection is performed according to a clinical criterion of >3 mm diameter of the feeding artery of the PAVM. The developed method was tested on a 20 patient dataset. A sensitivity study allowed choosing the irregularity parameter to maximize the true positive ratio reaching 85.4% in average. A specific false positive reduction procedure targeting the vessel trunks of the arterio-venous tree near mediastinum allows a precision increase from 13% to 67% with an average number of 1.15 false positives per scan.

Supporting the Development and Adoption of Automatic Lameness Detection Systems in Dairy Cattle: Effect of System Cost and Performance on Potential Market Shares

PubMed Central

Van Weyenberg, Stephanie; Van Nuffel, Annelies; Lauwers, Ludwig; Vangeyte, Jürgen

2017-01-01

Simple Summary Most prototypes of systems to automatically detect lameness in dairy cattle are still not available on the market. Estimating their potential adoption rate could support developers in defining development goals towards commercially viable and well-adopted systems. We simulated the potential market shares of such prototypes to assess the effect of altering the system cost and detection performance on the potential adoption rate. We found that system cost and lameness detection performance indeed substantially influence the potential adoption rate. In order for farmers to prefer automatic detection over current visual detection, the usefulness that farmers attach to a system with specific characteristics should be higher than that of visual detection. As such, we concluded that low system costs and high detection performances are required before automatic lameness detection systems become applicable in practice. Abstract Most automatic lameness detection system prototypes have not yet been commercialized, and are hence not yet adopted in practice. Therefore, the objective of this study was to simulate the effect of detection performance (percentage missed lame cows and percentage false alarms) and system cost on the potential market share of three automatic lameness detection systems relative to visual detection: a system attached to the cow, a walkover system, and a camera system. Simulations were done using a utility model derived from survey responses obtained from dairy farmers in Flanders, Belgium. Overall, systems attached to the cow had the largest market potential, but were still not competitive with visual detection. Increasing the detection performance or lowering the system cost led to higher market shares for automatic systems at the expense of visual detection. The willingness to pay for extra performance was €2.57 per % less missed lame cows, €1.65 per % less false alerts, and €12.7 for lame leg indication, respectively. The presented results could be exploited by system designers to determine the effect of adjustments to the technology on a system’s potential adoption rate. PMID:28991188

Noninvasive detection of skin cancers by measuring optical properties of tissues

NASA Astrophysics Data System (ADS)

Wang, Lihong V.; Jacques, Steven L.

1995-05-01

Skin cancer is the most frequently occurring cancer of all cancers. Each yea rover 500,000 new cases of skin cancer will be detected. A high percentage of skin cancers are diseases in which fatalities can be all but eliminated and morbidity reduced if detected early and treated properly. These skin lesions are distinguished generally by subjective visual inspection and their definitive diagnosis requires time-consuming expensive histopathological evaluation of excisional or incisional biopsies. In vivo experimental evidence published in the literature has shown that cancerous skin lesions have different total diffuse reflectance spectra than non- cancerous lesions or normal skin. Therefore, cancerous skin lesions may be differentiated from non-cancerous skin lesions by comparing the optical properties of the skin lesions with those of the surrounding normal skin sites, where the optical properties of the normal skin sites are used to account for different types of skin or different areas of skin. We have demonstrated that the effect of melanin concentration on the diffuse reflectance may be removed by extrapolating the reflectance at different wavelengths to an apparent pivot point. Because the concentration of melanin does not indicate malignancy, the removal of its effect is important to avoid false detection. The total diffuse reflectance depends on the albedo and anisotropy of tissues. Therefore, the total diffuse reflectance will remain the same as long as the anisotropy and the ratio between the absorption coefficient and the reduced scattering coefficient remain the same. Separating the absorption and scattering effects should enhance the detection sensitivity of skin cancers.

Automatic segmentation of psoriasis lesions

NASA Astrophysics Data System (ADS)

Ning, Yang; Shi, Chenbo; Wang, Li; Shu, Chang

2014-10-01

The automatic segmentation of psoriatic lesions is widely researched these years. It is an important step in Computer-aid methods of calculating PASI for estimation of lesions. Currently those algorithms can only handle single erythema or only deal with scaling segmentation. In practice, scaling and erythema are often mixed together. In order to get the segmentation of lesions area - this paper proposes an algorithm based on Random forests with color and texture features. The algorithm has three steps. The first step, the polarized light is applied based on the skin's Tyndall-effect in the imaging to eliminate the reflection and Lab color space are used for fitting the human perception. The second step, sliding window and its sub windows are used to get textural feature and color feature. In this step, a feature of image roughness has been defined, so that scaling can be easily separated from normal skin. In the end, Random forests will be used to ensure the generalization ability of the algorithm. This algorithm can give reliable segmentation results even the image has different lighting conditions, skin types. In the data set offered by Union Hospital, more than 90% images can be segmented accurately.

Robust skin color-based moving object detection for video surveillance

NASA Astrophysics Data System (ADS)

Kaliraj, Kalirajan; Manimaran, Sudha

2016-07-01

Robust skin color-based moving object detection for video surveillance is proposed. The objective of the proposed algorithm is to detect and track the target under complex situations. The proposed framework comprises four stages, which include preprocessing, skin color-based feature detection, feature classification, and target localization and tracking. In the preprocessing stage, the input image frame is smoothed using averaging filter and transformed into YCrCb color space. In skin color detection, skin color regions are detected using Otsu's method of global thresholding. In the feature classification, histograms of both skin and nonskin regions are constructed and the features are classified into foregrounds and backgrounds based on Bayesian skin color classifier. The foreground skin regions are localized by a connected component labeling process. Finally, the localized foreground skin regions are confirmed as a target by verifying the region properties, and nontarget regions are rejected using the Euler method. At last, the target is tracked by enclosing the bounding box around the target region in all video frames. The experiment was conducted on various publicly available data sets and the performance was evaluated with baseline methods. It evidently shows that the proposed algorithm works well against slowly varying illumination, target rotations, scaling, fast, and abrupt motion changes.

Automatic histologically-closer classification of skin lesions.

PubMed

Rebouças Filho, Pedro Pedrosa; Peixoto, Solon Alves; Medeiros da Nóbrega, Raul Victor; Hemanth, D Jude; Medeiros, Aldisio Gonçalves; Sangaiah, Arun Kumar; de Albuquerque, Victor Hugo C

2018-06-04

According to the American Cancer Society, melanoma is one of the most common types of cancer in the world. In 2017, approximately 87,110 new cases of skin cancer were diagnosed in the United States alone. A dermatoscope is a tool that captures lesion images with high resolution and is one of the main clinical tools to diagnose, evaluate and monitor this disease. This paper presents a new approach to classify melanoma automatically using structural co-occurrence matrix (SCM) of main frequencies extracted from dermoscopy images. The main advantage of this approach consists in transform the SCM in an adaptive feature extractor improving his power of discrimination using only the image as parameter. The images were collected from the International Skin Imaging Collaboration (ISIC) 2016, 2017 and Pedro Hispano Hospital (PH2) datasets. Specificity (Spe), sensitivity (Sen), positive predictive value, F Score, Harmonic Mean, accuracy (Acc) and area under the curve (AUC) were used to verify the efficiency of the SCM. The results show that the SCM in the frequency domain work automatically, where it obtained better results in comparison with local binary patterns, gray-level co-occurrence matrix and invariant moments of Hu as well as compared with recent works with the same datasets. The results of the proposed approach were: Spe 95.23%, 92.15% and 99.4%, Sen 94.57%, 89.9% and 99.2%, Acc 94.5%, 89.93% and 99%, and AUC 92%, 90% and 99% in ISIC 2016, 2017 and PH2 datasets, respectively. Copyright © 2018 Elsevier Ltd. All rights reserved.

Clinical experience with a computer-aided diagnosis system for automatic detection of pulmonary nodules at spiral CT of the chest

NASA Astrophysics Data System (ADS)

Wormanns, Dag; Fiebich, Martin; Saidi, Mustafa; Diederich, Stefan; Heindel, Walter

2001-05-01

The purpose of the study was to evaluate a computer aided diagnosis (CAD) workstation with automatic detection of pulmonary nodules at low-dose spiral CT in a clinical setting for early detection of lung cancer. Two radiologists in consensus reported 88 consecutive spiral CT examinations. All examinations were reviewed using a UNIX-based CAD workstation with a self-developed algorithm for automatic detection of pulmonary nodules. The algorithm was designed to detect nodules with at least 5 mm diameter. The results of automatic nodule detection were compared to the consensus reporting of two radiologists as gold standard. Additional CAD findings were regarded as nodules initially missed by the radiologists or as false positive results. A total of 153 nodules were detected with all modalities (diameter: 85 nodules <5mm, 63 nodules 5-9 mm, 5 nodules >= 10 mm). Reasons for failure of automatic nodule detection were assessed. Sensitivity of radiologists for nodules >=5 mm was 85%, sensitivity of CAD was 38%. For nodules >=5 mm without pleural contact sensitivity was 84% for radiologists at 45% for CAD. CAD detected 15 (10%) nodules not mentioned in the radiologist's report but representing real nodules, among them 10 (15%) nodules with a diameter $GREW5 mm. Reasons for nodules missed by CAD include: exclusion because of morphological features during region analysis (33%), nodule density below the detection threshold (26%), pleural contact (33%), segmentation errors (5%) and other reasons (2%). CAD improves detection of pulmonary nodules at spiral CT significantly and is a valuable second opinion in a clinical setting for lung cancer screening. Optimization of region analysis and an appropriate density threshold have a potential for further improvement of automatic nodule detection.

Adaboost multi-view face detection based on YCgCr skin color model

NASA Astrophysics Data System (ADS)

Lan, Qi; Xu, Zhiyong

2016-09-01

Traditional Adaboost face detection algorithm uses Haar-like features training face classifiers, whose detection error rate is low in the face region. While under the complex background, the classifiers will make wrong detection easily to the background regions with the similar faces gray level distribution, which leads to the error detection rate of traditional Adaboost algorithm is high. As one of the most important features of a face, skin in YCgCr color space has good clustering. We can fast exclude the non-face areas through the skin color model. Therefore, combining with the advantages of the Adaboost algorithm and skin color detection algorithm, this paper proposes Adaboost face detection algorithm method that bases on YCgCr skin color model. Experiments show that, compared with traditional algorithm, the method we proposed has improved significantly in the detection accuracy and errors.

Automatic spatiotemporal matching of detected pleural thickenings

NASA Astrophysics Data System (ADS)

Chaisaowong, Kraisorn; Keller, Simon Kai; Kraus, Thomas

2014-01-01

Pleural thickenings can be found in asbestos exposed patient's lung. Non-invasive diagnosis including CT imaging can detect aggressive malignant pleural mesothelioma in its early stage. In order to create a quantitative documentation of automatic detected pleural thickenings over time, the differences in volume and thickness of the detected thickenings have to be calculated. Physicians usually estimate the change of each thickening via visual comparison which provides neither quantitative nor qualitative measures. In this work, automatic spatiotemporal matching techniques of the detected pleural thickenings at two points of time based on the semi-automatic registration have been developed, implemented, and tested so that the same thickening can be compared fully automatically. As result, the application of the mapping technique using the principal components analysis turns out to be advantageous than the feature-based mapping using centroid and mean Hounsfield Units of each thickening, since the resulting sensitivity was improved to 98.46% from 42.19%, while the accuracy of feature-based mapping is only slightly higher (84.38% to 76.19%).

Residue depletion of ivermectin in broiler poultry.

PubMed

Mestorino, Nora; Buldain, Daniel; Buchamer, Andrea; Gortari, Lihuel; Daniele, Martín; Marchetti, María Laura

2017-04-01

Helminth infections are widespread in the poultry industry. There is evidence of extra-label use of some drugs, such as ivermectin (IVM), in broiler poultry. Pharmacokinetic and residual studies of IVM in poultry, however, are rather scarce. Our aim was to determine time restrictions for broiler chickens fed with balanced feed mixed with IVM for 21 days, and thus achieve acceptable residual levels for consumption as established by the European Union. Sixty 1-day-old chicks were fed with food supplemented with IVM at 5 mg kg -1 feed for 21 days. Groups of six treated animals were sacrificed at 0, 1, 2, 4, 8, 10, 15, 20 and 28 days after treatment. Liver, skin/fat, kidney and muscle samples were obtained. IVM were determined by liquid chromatography with fluorescence detection after automatic solid-phase extraction with SPE C 18 cartridges. The highest concentrations were measured in the liver, which is logical given that IVM is a drug that undergoes extensive hepatic metabolism. The optimal withdrawal time for edible tissues of these animals to stay within the permitted residual levels were: 12 days for liver, 8 days for skin/fat, 0 days for muscle and 10 days for kidney.

Adaptive skin detection based on online training

NASA Astrophysics Data System (ADS)

Zhang, Ming; Tang, Liang; Zhou, Jie; Rong, Gang

2007-11-01

Skin is a widely used cue for porn image classification. Most conventional methods are off-line training schemes. They usually use a fixed boundary to segment skin regions in the images and are effective only in restricted conditions: e.g. good lightness and unique human race. This paper presents an adaptive online training scheme for skin detection which can handle these tough cases. In our approach, skin detection is considered as a classification problem on Gaussian mixture model. For each image, human face is detected and the face color is used to establish a primary estimation of skin color distribution. Then an adaptive online training algorithm is used to find the real boundary between skin color and background color in current image. Experimental results on 450 images showed that the proposed method is more robust in general situations than the conventional ones.

Detecting hidden exfoliation corrosion in aircraft wing skins using thermography

NASA Astrophysics Data System (ADS)

Prati, John

2000-03-01

A thermal wave (pulse) thermography inspection technique demonstrated the ability to detect hidden subsurface exfoliation corrosion adjacent to countersunk fasteners in aircraft wing skins. In the wing skin, exfoliation corrosion is the result of the interaction between the steel fastener and the aluminum skin material in the presence of moisture. This interaction results in corrosion cracks that tend to grow parallel to the skin surface. The inspection technique developed allows rapid detection and evaluation of hidden (not visible on the surface) corrosion, which extends beyond the head of fastener countersinks in the aluminum skins.

Echo's Legacy

NASA Technical Reports Server (NTRS)

1980-01-01

The Echo 1 Satellite is simply a very large balloon, the diameter of a 10 story building. Metallized Products, Inc. developed a special material for NASA used for the balloons's skin. For "bouncing signals," material had to be reflective, lightweight, and thin enough to be folded into a beach ball size canister for delivery into orbit, where it would automatically inflate. Material selected was mylar polyester, with a reflective layer of tiny aluminum particles so fine that Echo's skin had a thickness half that of cellophane on a cigarette package.

A novel image-based BRDF measurement system and its application to human skin

NASA Astrophysics Data System (ADS)

Bintz, Jeffrey R.; Mendenhall, Michael J.; Marciniak, Michael A.; Butler, Samuel D.; Lloyd, James Tommy

2016-09-01

Human skin detection is an important first step in search and rescue (SAR) scenarios. Previous research performed human skin detection through an application specific camera system that ex- ploits the spectral properties of human skin at two visible and two near-infrared (NIR) wavelengths. The current theory assumes human skin is diffuse; however, it is observed that human skin exhibits specular and diffuse reflectance properties. This paper presents a novel image-based bidirectional reflectance distribution function (BRDF) measurement system, and applies it to the collection of human skin BRDF. The system uses a grid projecting laser and a novel signal processing chain to extract the surface normal from each grid location. Human skin BRDF measurements are shown for a variety of melanin content and hair coverage at the four spectral channels needed for human skin detection. The NIR results represent a novel contribution to the existing body of human skin BRDF measurements.

Image-guided automatic triggering of a fractional CO2 laser in aesthetic procedures.

PubMed

Wilczyński, Sławomir; Koprowski, Robert; Wiernek, Barbara K; Błońska-Fajfrowska, Barbara

2016-09-01

Laser procedures in dermatology and aesthetic medicine are associated with the need for manual laser triggering. This leads to pulse overlapping and side effects. Automatic laser triggering based on image analysis can provide a secure fit to each successive doses of radiation. A fractional CO2 laser was used in the study. 500 images of the human skin of healthy subjects were acquired. Automatic triggering was initiated by an application together with a camera which tracks and analyses the skin in visible light. The tracking algorithm uses the methods of image analysis to overlap images. After locating the characteristic points in analysed adjacent areas, the correspondence of graphs is found. The point coordinates derived from the images are the vertices of graphs with respect to which isomorphism is sought. When the correspondence of graphs is found, it is possible to overlap the neighbouring parts of the image. The proposed method of laser triggering owing to the automatic image fitting method allows for 100% repeatability. To meet this requirement, there must be at least 13 graph vertices obtained from the image. For this number of vertices, the time of analysis of a single image is less than 0.5s. The proposed method, applied in practice, may help reduce the number of side effects during dermatological laser procedures resulting from laser pulse overlapping. In addition, it reduces treatment time and enables to propose new techniques of treatment through controlled, precise laser pulse overlapping. Copyright © 2016 Elsevier Ltd. All rights reserved.

The algorithm for automatic detection of the calibration object

NASA Astrophysics Data System (ADS)

Artem, Kruglov; Irina, Ugfeld

2017-06-01

The problem of the automatic image calibration is considered in this paper. The most challenging task of the automatic calibration is a proper detection of the calibration object. The solving of this problem required the appliance of the methods and algorithms of the digital image processing, such as morphology, filtering, edge detection, shape approximation. The step-by-step process of the development of the algorithm and its adopting to the specific conditions of the log cuts in the image's background is presented. Testing of the automatic calibration module was carrying out under the conditions of the production process of the logging enterprise. Through the tests the average possibility of the automatic isolating of the calibration object is 86.1% in the absence of the type 1 errors. The algorithm was implemented in the automatic calibration module within the mobile software for the log deck volume measurement.

Skin Rounds: A Quality Improvement Approach to Enhance Skin Care in the Neonatal Intensive Care Unit.

PubMed

Nist, Marliese Dion; Rodgers, Elizabeth A; Ruth, Brenda M; Bertoni, C Briana; Bartman, Thomas; Keller, Leah A; Dail, James W; Gardikes-Gingery, Renee; Shepherd, Edward G

2016-10-01

Skin injuries are common among neonatal intensive care unit (NICU) patients and may lead to significant complications. Standardized methods of preventing, detecting, and treating skin injuries are needed. The aim of this project was to standardize the assessment, documentation, and tracking of skin injuries among hospitalized neonatal patients and to determine the incidence of pressure ulcers in this patient population. (1) Creation of an interdisciplinary skin team to identify skin injuries through weekly skin rounds. (2) Assessment of all patients at least twice daily for the presence of skin injuries. Interventions were implemented upon identification of a skin injury. Pressure ulcers of Stage II or more were further assessed by wound/ostomy nurses. A total of 2299 NICU patients were hospitalized and assessed between July 2011 and December 2015. After the initiation of skin rounds, the baseline incidence of pressure ulcers increased from 0.49 per 1000 patient days to 4.6 per 1000 patient days, reflecting an improvement in detection and reporting. The most common skin injuries detected included erythema, skin tears, and ecchymosis; the most common cause of injuries was medical devices. A dedicated skin team can improve the detection and reporting of skin injuries among NICU patients. Determination of the incidence of pressure ulcers in this population is critical to develop targeted interventions. Further research is needed to determine the most effective interventions to prevent and treat skin injuries among hospitalized neonates.

An effective method on pornographic images realtime recognition

NASA Astrophysics Data System (ADS)

Wang, Baosong; Lv, Xueqiang; Wang, Tao; Wang, Chengrui

2013-03-01

In this paper, skin detection, texture filtering and face detection are used to extract feature on an image library, training them with the decision tree arithmetic to create some rules as a decision tree classifier to distinguish an unknown image. Experiment based on more than twenty thousand images, the precision rate can get 76.21% when testing on 13025 pornographic images and elapsed time is less than 0.2s. This experiment shows it has a good popularity. Among the steps mentioned above, proposing a new skin detection model which called irregular polygon region skin detection model based on YCbCr color space. This skin detection model can lower the false detection rate on skin detection. A new method called sequence region labeling on binary connected area can calculate features on connected area, it is faster and needs less memory than other recursive methods.

Electrophysiological Correlates of Automatic Visual Change Detection in School-Age Children

ERIC Educational Resources Information Center

Clery, Helen; Roux, Sylvie; Besle, Julien; Giard, Marie-Helene; Bruneau, Nicole; Gomot, Marie

2012-01-01

Automatic stimulus-change detection is usually investigated in the auditory modality by studying Mismatch Negativity (MMN). Although the change-detection process occurs in all sensory modalities, little is known about visual deviance detection, particularly regarding the development of this brain function throughout childhood. The aim of the…

Automatic event recognition and anomaly detection with attribute grammar by learning scene semantics

NASA Astrophysics Data System (ADS)

Qi, Lin; Yao, Zhenyu; Li, Li; Dong, Junyu

2007-11-01

In this paper we present a novel framework for automatic event recognition and abnormal behavior detection with attribute grammar by learning scene semantics. This framework combines learning scene semantics by trajectory analysis and constructing attribute grammar-based event representation. The scene and event information is learned automatically. Abnormal behaviors that disobey scene semantics or event grammars rules are detected. By this method, an approach to understanding video scenes is achieved. Further more, with this prior knowledge, the accuracy of abnormal event detection is increased.

Reflectance-based skin detection in the short wave infrared band and its application to video

NASA Astrophysics Data System (ADS)

Langston, Tye

2016-10-01

Robust reflectance-based skin detection is a potentially powerful tool for security and search and rescue applications, especially when applied to video. However, to be useful it must be able to account for the variations of human skin, as well as other items in the environment that could cause false detections. This effort focused on identifying a robust skin detection scheme that is appropriate for video application. Skin reflectance was modeled to identify unique skin features and compare them to potential false positive materials. Based on these comparisons, specific wavelength bands were selected and different combinations of two and three optical filters were used for actively identifying skin, as well as identifying and removing potential false positive materials. One wavelength combination (1072/1250 nm) was applied to video using both single- and dual-camera configurations based on its still image performance, as well as its appropriateness for video application. There are several important factors regarding the extension of still image skin detection to video, including light available for detection (solar irradiance and reflectance intensity), overall intensity differences between different optical filters, optical component light loss, frame rate, time lag when switching between filters, image coregistration, and camera auto gain behavior.

Application of image recognition-based automatic hyphae detection in fungal keratitis.

PubMed

Wu, Xuelian; Tao, Yuan; Qiu, Qingchen; Wu, Xinyi

2018-03-01

The purpose of this study is to evaluate the accuracy of two methods in diagnosis of fungal keratitis, whereby one method is automatic hyphae detection based on images recognition and the other method is corneal smear. We evaluate the sensitivity and specificity of the method in diagnosis of fungal keratitis, which is automatic hyphae detection based on image recognition. We analyze the consistency of clinical symptoms and the density of hyphae, and perform quantification using the method of automatic hyphae detection based on image recognition. In our study, 56 cases with fungal keratitis (just single eye) and 23 cases with bacterial keratitis were included. All cases underwent the routine inspection of slit lamp biomicroscopy, corneal smear examination, microorganism culture and the assessment of in vivo confocal microscopy images before starting medical treatment. Then, we recognize the hyphae images of in vivo confocal microscopy by using automatic hyphae detection based on image recognition to evaluate its sensitivity and specificity and compare with the method of corneal smear. The next step is to use the index of density to assess the severity of infection, and then find the correlation with the patients' clinical symptoms and evaluate consistency between them. The accuracy of this technology was superior to corneal smear examination (p < 0.05). The sensitivity of the technology of automatic hyphae detection of image recognition was 89.29%, and the specificity was 95.65%. The area under the ROC curve was 0.946. The correlation coefficient between the grading of the severity in the fungal keratitis by the automatic hyphae detection based on image recognition and the clinical grading is 0.87. The technology of automatic hyphae detection based on image recognition was with high sensitivity and specificity, able to identify fungal keratitis, which is better than the method of corneal smear examination. This technology has the advantages when compared with the conventional artificial identification of confocal microscope corneal images, of being accurate, stable and does not rely on human expertise. It was the most useful to the medical experts who are not familiar with fungal keratitis. The technology of automatic hyphae detection based on image recognition can quantify the hyphae density and grade this property. Being noninvasive, it can provide an evaluation criterion to fungal keratitis in a timely, accurate, objective and quantitative manner.

[Effects on blood cell numbers and cytokines of dermal application rocket kerosene in mice].

PubMed

Xu, Bingxin; Wang, Jianying; Liu, Zhiguo; Li, Chenglin; Yang, Heming; Lou, Xiaotong; Li, Jianzhong; Cui, Yan

2015-09-01

To detect the number of cells and the level of IL-2, IL-4, IL-6, IL-10, TNF-alpha, IFN-γ and IL-17 cytokines in the peripheral blood of mice exposed to rocket kerosene by skin. ICR mice were randomly divided into the normal control group and RK experimental group (400 µl×1 group). RK undiluted fuel were applied directly to the dorsal skin of the mice. In control groups were treated with sesame oil (SO). the number of blood cells were detected by automatic blood cell counter and the level of IL-2, IL-4, IL-6, IL-10, TNF-alpha, IFN-γ and IL-17 cytokines in serum were detected by using flow cytometry and BD CBA Flex set kit. Compared with the normal group, WBC and LYM had a decreasing tendency 2 h and decreased significantly 6 h, 12 h and 1 d after RK exposure (P<0.05). They increased significantly 7 d after RK exposure (P<0.05). Compared with the normal group, the level of IL-6 increased significantly 2 h, 6 h, 12 h,1 d and 3 d (P<0.05). The level of TNF-α increased significantly 2h, 3d, 5d and 7d (P<0.05). The level of IL-10 increased significantly 2 h, 6 h, 3 d, 5 d and 7 d (P<0.05). The level of IFN-γ increased significantly 6 h and 3 d (P< 0.05). The level of IL-17 significantly increased 3 d, 5 d and 7d (P<0.05). RK can change the number of immune cells, causing the immune cytokine changes in mice after RK cutaneous exposure.

Automatic polymerase chain reaction product detection system for food safety monitoring using zinc finger protein fused to luciferase.

PubMed

Yoshida, Wataru; Kezuka, Aki; Murakami, Yoshiyuki; Lee, Jinhee; Abe, Koichi; Motoki, Hiroaki; Matsuo, Takafumi; Shimura, Nobuaki; Noda, Mamoru; Igimi, Shizunobu; Ikebukuro, Kazunori

2013-11-01

An automatic polymerase chain reaction (PCR) product detection system for food safety monitoring using zinc finger (ZF) protein fused to luciferase was developed. ZF protein fused to luciferase specifically binds to target double stranded DNA sequence and has luciferase enzymatic activity. Therefore, PCR products that comprise ZF protein recognition sequence can be detected by measuring the luciferase activity of the fusion protein. We previously reported that PCR products from Legionella pneumophila and Escherichia coli (E. coli) O157 genomic DNA were detected by Zif268, a natural ZF protein, fused to luciferase. In this study, Zif268-luciferase was applied to detect the presence of Salmonella and coliforms. Moreover, an artificial zinc finger protein (B2) fused to luciferase was constructed for a Norovirus detection system. In the luciferase activity detection assay, several bound/free separation process is required. Therefore, an analyzer that automatically performed the bound/free separation process was developed to detect PCR products using the ZF-luciferase fusion protein. By means of the automatic analyzer with ZF-luciferase fusion protein, target pathogenic genomes were specifically detected in the presence of other pathogenic genomes. Moreover, we succeeded in the detection of 10 copies of E. coli BL21 without extraction of genomic DNA by the automatic analyzer and E. coli was detected with a logarithmic dependency in the range of 1.0×10 to 1.0×10(6) copies. Copyright © 2013 Elsevier B.V. All rights reserved.

[Application of automatic photography in Schistosoma japonicum miracidium hatching experiments].

PubMed

Ming-Li, Zhou; Ai-Ling, Cai; Xue-Feng, Wang

2016-05-20

To explore the value of automatic photography in the observation of results of Schistosoma japonicum miracidium hatching experiments. Some fresh S. japonicum eggs were added into cow feces, and the samples of feces were divided into a low infested experimental group and a high infested group (40 samples each group). In addition, there was a negative control group with 40 samples of cow feces without S. japonicum eggs. The conventional nylon bag S. japonicum miracidium hatching experiments were performed. The process was observed with the method of flashlight and magnifying glass combined with automatic video (automatic photography method), and, at the same time, with the naked eye observation method. The results were compared. In the low infested group, the miracidium positive detection rates were 57.5% and 85.0% by the naked eye observation method and automatic photography method, respectively ( χ 2 = 11.723, P < 0.05). In the high infested group, the positive detection rates were 97.5% and 100% by the naked eye observation method and automatic photography method, respectively ( χ 2 = 1.253, P > 0.05). In the two infested groups, the average positive detection rates were 77.5% and 92.5% by the naked eye observation method and automatic photography method, respectively ( χ 2 = 6.894, P < 0.05). The automatic photography can effectively improve the positive detection rate in the S. japonicum miracidium hatching experiments.

An unsupervised machine learning method for delineating stratum corneum in reflectance confocal microscopy stacks of human skin in vivo

NASA Astrophysics Data System (ADS)

Bozkurt, Alican; Kose, Kivanc; Fox, Christi A.; Dy, Jennifer; Brooks, Dana H.; Rajadhyaksha, Milind

2016-02-01

Study of the stratum corneum (SC) in human skin is important for research in barrier structure and function, drug delivery, and water permeability of skin. The optical sectioning and high resolution of reflectance confocal microscopy (RCM) allows visual examination of SC non-invasively. Here, we present an unsupervised segmentation algorithm that can automatically delineate thickness of the SC in RCM images of human skin in-vivo. We mimic clinicians visual process by applying complex wavelet transform over non-overlapping local regions of size 16 x 16 μm called tiles, and analyze the textural changes in between consecutive tiles in axial (depth) direction. We use dual-tree complex wavelet transform to represent textural structures in each tile. This transform is almost shift-invariant, and directionally selective, which makes it highly efficient in texture representation. Using DT-CWT, we decompose each tile into 6 directional sub-bands with orientations in +/-15, 45, and 75 degrees and a low-pass band, which is the decimated version of the input. We apply 3 scales of decomposition by recursively transforming the low-pass bands and obtain 18 bands of different directionality at different scales. We then calculate mean and variance of each band resulting in a feature vector of 36 entries. Feature vectors obtained for each stack of tiles in axial direction are then clustered using spectral clustering in order to detect the textural changes in depth direction. Testing on a set of 15 RCM stacks produced a mean error of 5.45+/-1.32 μm, compared to the "ground truth" segmentation provided by a clinical expert reader.

Improved murine glioma detection following modified diet and photobleaching of skin PpIX fluorescence

NASA Astrophysics Data System (ADS)

Gibbs, Summer L.; O'Hara, Julia A.; Hoopes, P. Jack; Pogue, Brian W.

2007-02-01

The Aminolevulinic Acid (ALA) - Protoporphyrin IX (PpIX) system is unique in the world of photosensitizers in that the prodrug ALA is enzymatically transformed via the tissue of interest into fluorescently detectable levels of PpIX. This system can be used to monitor cellular metabolism of tumor tissue for applications such as therapy monitoring. Detecting PpIX fluorescence noninvasively has proven difficult due to the high levels of PpIX produced in the skin compared to other tissue both with and without ALA administration. In the current study, methods to decrease skin PpIX autofluorescence and skin PpIX fluorescence following ALA administration have been examined. Use of a purified diet is found to decrease both skin PpIX autofluorescence and skin PpIX fluorescence following ALA administration, while addition of a broad spectrum antibiotic to the water shows little effect. Following ALA administration, improved brain tumor detection is seen when skin PpIX fluorescence is photobleached via blue light prior to transmission spectroscopic measurements of tumor bearing and control animals. Both of these methods to decrease skin PpIX autofluorescence and skin PpIX fluorescence following ALA administration are shown to have a large effect on the ability to detect tumor tissue PpIX fluorescence noninvasively in vivo.

Automatic thermographic image defect detection of composites

NASA Astrophysics Data System (ADS)

Luo, Bin; Liebenberg, Bjorn; Raymont, Jeff; Santospirito, SP

2011-05-01

Detecting defects, and especially reliably measuring defect sizes, are critical objectives in automatic NDT defect detection applications. In this work, the Sentence software is proposed for the analysis of pulsed thermography and near IR images of composite materials. Furthermore, the Sentence software delivers an end-to-end, user friendly platform for engineers to perform complete manual inspections, as well as tools that allow senior engineers to develop inspection templates and profiles, reducing the requisite thermographic skill level of the operating engineer. Finally, the Sentence software can also offer complete independence of operator decisions by the fully automated "Beep on Defect" detection functionality. The end-to-end automatic inspection system includes sub-systems for defining a panel profile, generating an inspection plan, controlling a robot-arm and capturing thermographic images to detect defects. A statistical model has been built to analyze the entire image, evaluate grey-scale ranges, import sentencing criteria and automatically detect impact damage defects. A full width half maximum algorithm has been used to quantify the flaw sizes. The identified defects are imported into the sentencing engine which then sentences (automatically compares analysis results against acceptance criteria) the inspection by comparing the most significant defect or group of defects against the inspection standards.

Simulation study of melanoma detection in human skin tissues by laser-generated surface acoustic waves

NASA Astrophysics Data System (ADS)

Chen, Kun; Fu, Xing; Dorantes-Gonzalez, Dante J.; Lu, Zimo; Li, Tingting; Li, Yanning; Wu, Sen; Hu, Xiaotang

2014-07-01

Air pollution has been correlated to an increasing number of cases of human skin diseases in recent years. However, the investigation of human skin tissues has received only limited attention, to the point that there are not yet satisfactory modern detection technologies to accurately, noninvasively, and rapidly diagnose human skin at epidermis and dermis levels. In order to detect and analyze severe skin diseases such as melanoma, a finite element method (FEM) simulation study of the application of the laser-generated surface acoustic wave (LSAW) technique is developed. A three-layer human skin model is built, where LSAW's are generated and propagated, and their effects in the skin medium with melanoma are analyzed. Frequency domain analysis is used as a main tool to investigate such issues as minimum detectable size of melanoma, filtering spectra from noise and from computational irregularities, as well as on how the FEM model meshing size and computational capabilities influence the accuracy of the results. Based on the aforementioned aspects, the analysis of the signals under the scrutiny of the phase velocity dispersion curve is verified to be a reliable, a sensitive, and a promising approach for detecting and characterizing melanoma in human skin.

Simulation study of melanoma detection in human skin tissues by laser-generated surface acoustic waves.

PubMed

Chen, Kun; Fu, Xing; Dorantes-Gonzalez, Dante J; Lu, Zimo; Li, Tingting; Li, Yanning; Wu, Sen; Hu, Xiaotang

2014-01-01

Air pollution has been correlated to an increasing number of cases of human skin diseases in recent years. However, the investigation of human skin tissues has received only limited attention, to the point that there are not yet satisfactory modern detection technologies to accurately, noninvasively, and rapidly diagnose human skin at epidermis and dermis levels. In order to detect and analyze severe skin diseases such as melanoma, a finite element method (FEM) simulation study of the application of the laser-generated surface acoustic wave (LSAW) technique is developed. A three-layer human skin model is built, where LSAW’s are generated and propagated, and their effects in the skin medium with melanoma are analyzed. Frequency domain analysis is used as a main tool to investigate such issues as minimum detectable size of melanoma, filtering spectra from noise and from computational irregularities, as well as on how the FEM model meshing size and computational capabilities influence the accuracy of the results. Based on the aforementioned aspects, the analysis of the signals under the scrutiny of the phase velocity dispersion curve is verified to be a reliable, a sensitive, and a promising approach for detecting and characterizing melanoma in human skin.

Segmentation of human face using gradient-based approach

NASA Astrophysics Data System (ADS)

Baskan, Selin; Bulut, M. Mete; Atalay, Volkan

2001-04-01

This paper describes a method for automatic segmentation of facial features such as eyebrows, eyes, nose, mouth and ears in color images. This work is an initial step for wide range of applications based on feature-based approaches, such as face recognition, lip-reading, gender estimation, facial expression analysis, etc. Human face can be characterized by its skin color and nearly elliptical shape. For this purpose, face detection is performed using color and shape information. Uniform illumination is assumed. No restrictions on glasses, make-up, beard, etc. are imposed. Facial features are extracted using the vertically and horizontally oriented gradient projections. The gradient of a minimum with respect to its neighbor maxima gives the boundaries of a facial feature. Each facial feature has a different horizontal characteristic. These characteristics are derived by extensive experimentation with many face images. Using fuzzy set theory, the similarity between the candidate and the feature characteristic under consideration is calculated. Gradient-based method is accompanied by the anthropometrical information, for robustness. Ear detection is performed using contour-based shape descriptors. This method detects the facial features and circumscribes each facial feature with the smallest rectangle possible. AR database is used for testing. The developed method is also suitable for real-time systems.

An automated skin segmentation of Breasts in Dynamic Contrast-Enhanced Magnetic Resonance Imaging.

PubMed

Lee, Chia-Yen; Chang, Tzu-Fang; Chang, Nai-Yun; Chang, Yeun-Chung

2018-04-18

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is used to diagnose breast disease. Obtaining anatomical information from DCE-MRI requires the skin be manually removed so that blood vessels and tumors can be clearly observed by physicians and radiologists; this requires considerable manpower and time. We develop an automated skin segmentation algorithm where the surface skin is removed rapidly and correctly. The rough skin area is segmented by the active contour model, and analyzed in segments according to the continuity of the skin thickness for accuracy. Blood vessels and mammary glands are retained, which remedies the defect of removing some blood vessels in active contours. After three-dimensional imaging, the DCE-MRIs without the skin can be used to see internal anatomical information for clinical applications. The research showed the Dice's coefficients of the 3D reconstructed images using the proposed algorithm and the active contour model for removing skins are 93.2% and 61.4%, respectively. The time performance of segmenting skins automatically is about 165 times faster than manually. The texture information of the tumors position with/without the skin is compared by the paired t-test yielded all p < 0.05, which suggested the proposed algorithm may enhance observability of tumors at the significance level of 0.05.

Automatic detection of typical dust devils from Mars landscape images

NASA Astrophysics Data System (ADS)

Ogohara, Kazunori; Watanabe, Takeru; Okumura, Susumu; Hatanaka, Yuji

2018-02-01

This paper presents an improved algorithm for automatic detection of Martian dust devils that successfully extracts tiny bright dust devils and obscured large dust devils from two subtracted landscape images. These dust devils are frequently observed using visible cameras onboard landers or rovers. Nevertheless, previous research on automated detection of dust devils has not focused on these common types of dust devils, but on dust devils that appear on images to be irregularly bright and large. In this study, we detect these common dust devils automatically using two kinds of parameter sets for thresholding when binarizing subtracted images. We automatically extract dust devils from 266 images taken by the Spirit rover to evaluate our algorithm. Taking dust devils detected by visual inspection to be ground truth, the precision, recall and F-measure values are 0.77, 0.86, and 0.81, respectively.

Automatic detection of articulation disorders in children with cleft lip and palate.

PubMed

Maier, Andreas; Hönig, Florian; Bocklet, Tobias; Nöth, Elmar; Stelzle, Florian; Nkenke, Emeka; Schuster, Maria

2009-11-01

Speech of children with cleft lip and palate (CLP) is sometimes still disordered even after adequate surgical and nonsurgical therapies. Such speech shows complex articulation disorders, which are usually assessed perceptually, consuming time and manpower. Hence, there is a need for an easy to apply and reliable automatic method. To create a reference for an automatic system, speech data of 58 children with CLP were assessed perceptually by experienced speech therapists for characteristic phonetic disorders at the phoneme level. The first part of the article aims to detect such characteristics by a semiautomatic procedure and the second to evaluate a fully automatic, thus simple, procedure. The methods are based on a combination of speech processing algorithms. The semiautomatic method achieves moderate to good agreement (kappa approximately 0.6) for the detection of all phonetic disorders. On a speaker level, significant correlations between the perceptual evaluation and the automatic system of 0.89 are obtained. The fully automatic system yields a correlation on the speaker level of 0.81 to the perceptual evaluation. This correlation is in the range of the inter-rater correlation of the listeners. The automatic speech evaluation is able to detect phonetic disorders at an experts'level without any additional human postprocessing.

Estimating the cost of skin cancer detection by dermatology providers in a large health care system.

PubMed

Matsumoto, Martha; Secrest, Aaron; Anderson, Alyce; Saul, Melissa I; Ho, Jonhan; Kirkwood, John M; Ferris, Laura K

2018-04-01

Data on the cost and efficiency of skin cancer detection through total body skin examination are scarce. To determine the number needed to screen (NNS) and biopsy (NNB) and cost per skin cancer diagnosed in a large dermatology practice in patients undergoing total body skin examination. This is a retrospective observational study. During 2011-2015, a total of 20,270 patients underwent 33,647 visits for total body skin examination; 9956 lesion biopsies were performed yielding 2763 skin cancers, including 155 melanomas. The NNS to detect 1 skin cancer was 12.2 (95% confidence interval [CI] 11.7-12.6) and 1 melanoma was 215 (95% CI 185-252). The NNB to detect 1 skin cancer was 3.0 (95% CI 2.9-3.1) and 1 melanoma was 27.8 (95% CI 23.3-33.3). In a multivariable model for NNS, age and personal history of melanoma were significant factors. Age switched from a protective factor to a risk factor at 51 years of age. The estimated cost per melanoma detected was $32,594 (95% CI $27,326-$37,475). Data are from a single health care system and based on physician coding. Melanoma detection through total body skin examination is most efficient in patients ≥50 years of age and those with a personal history of melanoma. Our findings will be helpful in modeling the cost effectiveness of melanoma screening by dermatologists. Copyright © 2017 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.

Effects of polypeptide from Chlamys farreri on amino acid content in guinea pig skin irradiated by chronic ultraviolet A and B

NASA Astrophysics Data System (ADS)

Yu, Guoying; Cao, Pengli; Guo, Kun; Wang, Yuejun; Sun, Mi; Wang, Chunbo

2004-12-01

We examined the effects of polypeptide from Chlamys farreri (PCF) on the amount of hydroxyproline in guinea pig skin irradiated by chronic ultraviolet A (UVA) and ultraviolet B (UVB) radiation. PCF was applied locally before repeated exposure of guinea pig to UVA and UVB. The contents of hydroxyproline and other amino acids in guinea pig skin were determined by automatic amino acid analyzer. Our results showed that: (1) long-time UVA and UVB radiation can reduce dramatically the amounts of hydroxyproline, aspartic acid, threonine, glycine, phenylalanine and lysine in guinea pig skin in comparison with the control group ( P<0.05); (2) Compared with model group, pre-treatment with 5% and 20% PCF prior to UVA and UVB radiation can inhibit the decline of amino acids content in guinea pig skin in a dose-dependent manner ( P<0.05). As the decrease of hydroxyproline, glycine and lysine contents in the skin directly reflexes type I collagen degeneration, our results indicated that the chronic application of PCF can protect skin type I collagen against UV radiation, and thus protect skin from photoaging.

Automatic identification of artifacts in electrodermal activity data.

PubMed

Taylor, Sara; Jaques, Natasha; Chen, Weixuan; Fedor, Szymon; Sano, Akane; Picard, Rosalind

2015-01-01

Recently, wearable devices have allowed for long term, ambulatory measurement of electrodermal activity (EDA). Despite the fact that ambulatory recording can be noisy, and recording artifacts can easily be mistaken for a physiological response during analysis, to date there is no automatic method for detecting artifacts. This paper describes the development of a machine learning algorithm for automatically detecting EDA artifacts, and provides an empirical evaluation of classification performance. We have encoded our results into a freely available web-based tool for artifact and peak detection.

WE-DE-201-11: Sensitivity and Specificity of Verification Methods Based On Total Reference Air Kerma (TRAK) Or On User Provided Dose Points for Graphically Planned Skin HDR Brachytherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Damato, A; Devlin, P; Bhagwat, M

Purpose: To investigate the sensitivity and specificity of a novel verification methodology for image-guided skin HDR brachytherapy plans using a TRAK-based reasonableness test, compared to a typical manual verification methodology. Methods: Two methodologies were used to flag treatment plans necessitating additional review due to a potential discrepancy of 3 mm between planned dose and clinical target in the skin. Manual verification was used to calculate the discrepancy between the average dose to points positioned at time of planning representative of the prescribed depth and the expected prescription dose. Automatic verification was used to calculate the discrepancy between TRAK of themore » clinical plan and its expected value, which was calculated using standard plans with varying curvatures, ranging from flat to cylindrically circumferential. A plan was flagged if a discrepancy >10% was observed. Sensitivity and specificity were calculated using as a criteria for true positive that >10% of plan dwells had a distance to prescription dose >1 mm different than prescription depth (3 mm + size of applicator). All HDR image-based skin brachytherapy plans treated at our institution in 2013 were analyzed. Results: 108 surface applicator plans to treat skin of the face, scalp, limbs, feet, hands or abdomen were analyzed. Median number of catheters was 19 (range, 4 to 71) and median number of dwells was 257 (range, 20 to 1100). Sensitivity/specificity were 57%/78% for manual and 70%/89% for automatic verification. Conclusion: A check based on expected TRAK value is feasible for irregularly shaped, image-guided skin HDR brachytherapy. This test yielded higher sensitivity and specificity than a test based on the identification of representative points, and can be implemented with a dedicated calculation code or with pre-calculated lookup tables of ideally shaped, uniform surface applicators.« less

Detectability of bovine TB using the tuberculin skin test does not vary significantly according to pathogen genotype within Northern Ireland.

PubMed

Wright, David M; Allen, Adrian R; Mallon, Thomas R; McDowell, Stanley W J; Bishop, Stephen C; Glass, Elizabeth J; Bermingham, Mairead L; Woolliams, John A; Skuce, Robin A

2013-10-01

Strains of many infectious diseases differ in parameters that influence epidemic spread, for example virulence, transmissibility, detectability and host specificity. Knowledge of inter-strain variation can be exploited to improve management and decrease disease incidence. Bovine tuberculosis (bTB) is increasingly prevalent among farmed cattle in the UK, exerting a heavy economic burden on the farming industry and government. We aimed to determine whether strains of Mycobacterium bovis (the causative agent of bTB) identified and classified using genetic markers (spoligotyping and multi-locus VNTR analysis) varied in response to the tuberculin skin test; this being the primary method of bTB detection used in the UK. Inter-strain variation in detectability of M. bovis could have important implications for disease control. The skin test is based on a differential delayed type hypersensitivity (DTH) response to intradermal injections of purified protein derivative (PPD) from M. bovis (PPD-B) and Mycobacterium avium (PPD-A). We searched for an association between skin test response (PPD-B skin rise minus PPD-A skin rise) and M. bovis genotype at the disclosing test in culture-confirmed cases using a field dataset consisting of 21,000 isolates belonging to 63 genotypes of M. bovis from cattle in Northern Ireland. We found no substantial variation among genotypes (estimated responses clustered tightly around the mean) controlling for animal sex, breed and test effects. We also estimated the ratio of skin test detected to undetected cases (i.e. cases only detected at abattoir). The skin test detection ratio varied among abattoirs with some detecting a greater proportion of cases than others but this variation was unrelated to the community composition of genotypes within each abattoir catchment. These two lines of evidence indicate that M. bovis genotypes in Northern Ireland have similar detectability using the skin test. Crown Copyright © 2013. Published by Elsevier B.V. All rights reserved.

Polarization speckle imaging as a potential technique for in vivo skin cancer detection.

PubMed

Tchvialeva, Lioudmila; Dhadwal, Gurbir; Lui, Harvey; Kalia, Sunil; Zeng, Haishan; McLean, David I; Lee, Tim K

2013-06-01

Skin cancer is the most common cancer in the Western world. In order to accurately detect the disease, especially malignant melanoma-the most fatal form of skin cancer-at an early stage when the prognosis is excellent, there is an urgent need to develop noninvasive early detection methods. We believe that polarization speckle patterns, defined as a spatial distribution of depolarization ratio of traditional speckle patterns, can be an important tool for skin cancer detection. To demonstrate our technique, we conduct a large in vivo clinical study of 214 skin lesions, and show that statistical moments of the polarization speckle pattern could differentiate different types of skin lesions, including three common types of skin cancers, malignant melanoma, squamous cell carcinoma, basal cell carcinoma, and two benign lesions, melanocytic nevus and seborrheic keratoses. In particular, the fourth order moment achieves better or similar sensitivity and specificity than many well-known and accepted optical techniques used to differentiate melanoma and seborrheic keratosis.

Polarization speckle imaging as a potential technique for in vivo skin cancer detection

NASA Astrophysics Data System (ADS)

Tchvialeva, Lioudmila; Dhadwal, Gurbir; Lui, Harvey; Kalia, Sunil; Zeng, Haishan; McLean, David I.; Lee, Tim K.

2013-06-01

Skin cancer is the most common cancer in the Western world. In order to accurately detect the disease, especially malignant melanoma-the most fatal form of skin cancer-at an early stage when the prognosis is excellent, there is an urgent need to develop noninvasive early detection methods. We believe that polarization speckle patterns, defined as a spatial distribution of depolarization ratio of traditional speckle patterns, can be an important tool for skin cancer detection. To demonstrate our technique, we conduct a large in vivo clinical study of 214 skin lesions, and show that statistical moments of the polarization speckle pattern could differentiate different types of skin lesions, including three common types of skin cancers, malignant melanoma, squamous cell carcinoma, basal cell carcinoma, and two benign lesions, melanocytic nevus and seborrheic keratoses. In particular, the fourth order moment achieves better or similar sensitivity and specificity than many well-known and accepted optical techniques used to differentiate melanoma and seborrheic keratosis.

Automatic phase aberration compensation for digital holographic microscopy based on deep learning background detection.

PubMed

Nguyen, Thanh; Bui, Vy; Lam, Van; Raub, Christopher B; Chang, Lin-Ching; Nehmetallah, George

2017-06-26

We propose a fully automatic technique to obtain aberration free quantitative phase imaging in digital holographic microscopy (DHM) based on deep learning. The traditional DHM solves the phase aberration compensation problem by manually detecting the background for quantitative measurement. This would be a drawback in real time implementation and for dynamic processes such as cell migration phenomena. A recent automatic aberration compensation approach using principle component analysis (PCA) in DHM avoids human intervention regardless of the cells' motion. However, it corrects spherical/elliptical aberration only and disregards the higher order aberrations. Traditional image segmentation techniques can be employed to spatially detect cell locations. Ideally, automatic image segmentation techniques make real time measurement possible. However, existing automatic unsupervised segmentation techniques have poor performance when applied to DHM phase images because of aberrations and speckle noise. In this paper, we propose a novel method that combines a supervised deep learning technique with convolutional neural network (CNN) and Zernike polynomial fitting (ZPF). The deep learning CNN is implemented to perform automatic background region detection that allows for ZPF to compute the self-conjugated phase to compensate for most aberrations.

Acousto-optical assessment of skin viscoelasticity

NASA Astrophysics Data System (ADS)

Kirkpatrick, Sean J.; Duncan, Donald D.

2003-07-01

A multiphysics approach, combining acoustics, optics, and mechanics can be used to detect regions of skin with distinct mechanical behavior that may indicate a pathology, such as a cancerous skin lesion. Herein, an acousto-optical approach to evaluating the viscoelastic behavior of superficial skin layers will be presented. The method relies upon inducing low frequency guided surface waves in the skin and detecting these waves by monitoring the shift in the backscattered laser speckle pattern created by illuminating a small region of the skin with coherent light. Artificial lesions in the form of chemical cross-linking and chemical softening were induced in superficial porcine skin layers and detected based upon variations in local mechanical behavior. The lesions affect not only the time-of-flight of the guided surface waves, but also change the relative phase of the acoustic waves as determined optically. The method may be applicable in the study and diagnosis of superficial skin lesions.

Optical assessment of tissue mechanics: acousto-optical elastography of skin

NASA Astrophysics Data System (ADS)

Kirkpatrick, Sean J.

2003-10-01

A multiphysics approach, combining acoustics, optics, and mechanics can be used to detect regions of skin with distinct mechanical behavior that may indicate a pathology, such as a cancerous skin lesion. Herein, an acousto - optical approach to evaluating the viscoelastic behavior of superficial skin layers will be presented. The method relies upon inducing low frequency guided surface waves in the skin and detecting these waves by monitoring the shift in the backscattered laser speckle pattern created by illuminating a small region of the skin with coherent light. Artificial lesions in the form of chemical cross-linking and chemical softening were induced in superficial porcine skin layers and detected based upon variations in local mechanical behavior. The lesions affect not only the time-of-flight of the guided surface waves, but also change the relative phase of the acoustic waves as determined optically. The method may be applicable in the study and diagnosis of superficial skin lesions.

Farm-specific economic value of automatic lameness detection systems in dairy cattle: From concepts to operational simulations.

PubMed

Van De Gucht, Tim; Saeys, Wouter; Van Meensel, Jef; Van Nuffel, Annelies; Vangeyte, Jurgen; Lauwers, Ludwig

2018-01-01

Although prototypes of automatic lameness detection systems for dairy cattle exist, information about their economic value is lacking. In this paper, a conceptual and operational framework for simulating the farm-specific economic value of automatic lameness detection systems was developed and tested on 4 system types: walkover pressure plates, walkover pressure mats, camera systems, and accelerometers. The conceptual framework maps essential factors that determine economic value (e.g., lameness prevalence, incidence and duration, lameness costs, detection performance, and their relationships). The operational simulation model links treatment costs and avoided losses with detection results and farm-specific information, such as herd size and lameness status. Results show that detection performance, herd size, discount rate, and system lifespan have a large influence on economic value. In addition, lameness prevalence influences the economic value, stressing the importance of an adequate prior estimation of the on-farm prevalence. The simulations provide first estimates for the upper limits for purchase prices of automatic detection systems. The framework allowed for identification of knowledge gaps obstructing more accurate economic value estimation. These include insights in cost reductions due to early detection and treatment, and links between specific lameness causes and their related losses. Because this model provides insight in the trade-offs between automatic detection systems' performance and investment price, it is a valuable tool to guide future research and developments. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Automatic Processing of Changes in Facial Emotions in Dysphoria: A Magnetoencephalography Study.

PubMed

Xu, Qianru; Ruohonen, Elisa M; Ye, Chaoxiong; Li, Xueqiao; Kreegipuu, Kairi; Stefanics, Gabor; Luo, Wenbo; Astikainen, Piia

2018-01-01

It is not known to what extent the automatic encoding and change detection of peripherally presented facial emotion is altered in dysphoria. The negative bias in automatic face processing in particular has rarely been studied. We used magnetoencephalography (MEG) to record automatic brain responses to happy and sad faces in dysphoric (Beck's Depression Inventory ≥ 13) and control participants. Stimuli were presented in a passive oddball condition, which allowed potential negative bias in dysphoria at different stages of face processing (M100, M170, and M300) and alterations of change detection (visual mismatch negativity, vMMN) to be investigated. The magnetic counterpart of the vMMN was elicited at all stages of face processing, indexing automatic deviance detection in facial emotions. The M170 amplitude was modulated by emotion, response amplitudes being larger for sad faces than happy faces. Group differences were found for the M300, and they were indexed by two different interaction effects. At the left occipital region of interest, the dysphoric group had larger amplitudes for sad than happy deviant faces, reflecting negative bias in deviance detection, which was not found in the control group. On the other hand, the dysphoric group showed no vMMN to changes in facial emotions, while the vMMN was observed in the control group at the right occipital region of interest. Our results indicate that there is a negative bias in automatic visual deviance detection, but also a general change detection deficit in dysphoria.

Skin subspace color modeling for daytime and nighttime group activity recognition in confined operational spaces

NASA Astrophysics Data System (ADS)

Shirkhodaie, Amir; Poshtyar, Azin; Chan, Alex; Hu, Shuowen

2016-05-01

In many military and homeland security persistent surveillance applications, accurate detection of different skin colors in varying observability and illumination conditions is a valuable capability for video analytics. One of those applications is In-Vehicle Group Activity (IVGA) recognition, in which significant changes in observability and illumination may occur during the course of a specific human group activity of interest. Most of the existing skin color detection algorithms, however, are unable to perform satisfactorily in confined operational spaces with partial observability and occultation, as well as under diverse and changing levels of illumination intensity, reflection, and diffraction. In this paper, we investigate the salient features of ten popular color spaces for skin subspace color modeling. More specifically, we examine the advantages and disadvantages of each of these color spaces, as well as the stability and suitability of their features in differentiating skin colors under various illumination conditions. The salient features of different color subspaces are methodically discussed and graphically presented. Furthermore, we present robust and adaptive algorithms for skin color detection based on this analysis. Through examples, we demonstrate the efficiency and effectiveness of these new color skin detection algorithms and discuss their applicability for skin detection in IVGA recognition applications.

Designing and Implementing a Retrospective Earthquake Detection Framework at the U.S. Geological Survey National Earthquake Information Center

NASA Astrophysics Data System (ADS)

Patton, J.; Yeck, W.; Benz, H.

2017-12-01

The U.S. Geological Survey National Earthquake Information Center (USGS NEIC) is implementing and integrating new signal detection methods such as subspace correlation, continuous beamforming, multi-band picking and automatic phase identification into near-real-time monitoring operations. Leveraging the additional information from these techniques help the NEIC utilize a large and varied network on local to global scales. The NEIC is developing an ordered, rapid, robust, and decentralized framework for distributing seismic detection data as well as a set of formalized formatting standards. These frameworks and standards enable the NEIC to implement a seismic event detection framework that supports basic tasks, including automatic arrival time picking, social media based event detections, and automatic association of different seismic detection data into seismic earthquake events. In addition, this framework enables retrospective detection processing such as automated S-wave arrival time picking given a detected event, discrimination and classification of detected events by type, back-azimuth and slowness calculations, and ensuring aftershock and induced sequence detection completeness. These processes and infrastructure improve the NEIC's capabilities, accuracy, and speed of response. In addition, this same infrastructure provides an improved and convenient structure to support access to automatic detection data for both research and algorithmic development.

Automatic patient respiration failure detection system with wireless transmission

NASA Technical Reports Server (NTRS)

Dimeff, J.; Pope, J. M.

1968-01-01

Automatic respiration failure detection system detects respiration failure in patients with a surgically implanted tracheostomy tube, and actuates an audible and/or visual alarm. The system incorporates a miniature radio transmitter so that the patient is unencumbered by wires yet can be monitored from a remote location.

[Micron]ADS-B Detect and Avoid Flight Tests on Phantom 4 Unmanned Aircraft System

NASA Technical Reports Server (NTRS)

Arteaga, Ricardo; Dandachy, Mike; Truong, Hong; Aruljothi, Arun; Vedantam, Mihir; Epperson, Kraettli; McCartney, Reed

2018-01-01

Researchers at the National Aeronautics and Space Administration Armstrong Flight Research Center in Edwards, California and Vigilant Aerospace Systems collaborated for the flight-test demonstration of an Automatic Dependent Surveillance-Broadcast based collision avoidance technology on a small unmanned aircraft system equipped with the uAvionix Automatic Dependent Surveillance-Broadcast transponder. The purpose of the testing was to demonstrate that National Aeronautics and Space Administration / Vigilant software and algorithms, commercialized as the FlightHorizon UAS"TM", are compatible with uAvionix hardware systems and the DJI Phantom 4 small unmanned aircraft system. The testing and demonstrations were necessary for both parties to further develop and certify the technology in three key areas: flights beyond visual line of sight, collision avoidance, and autonomous operations. The National Aeronautics and Space Administration and Vigilant Aerospace Systems have developed and successfully flight-tested an Automatic Dependent Surveillance-Broadcast Detect and Avoid system on the Phantom 4 small unmanned aircraft system. The Automatic Dependent Surveillance-Broadcast Detect and Avoid system architecture is especially suited for small unmanned aircraft systems because it integrates: 1) miniaturized Automatic Dependent Surveillance-Broadcast hardware; 2) radio data-link communications; 3) software algorithms for real-time Automatic Dependent Surveillance-Broadcast data integration, conflict detection, and alerting; and 4) a synthetic vision display using a fully-integrated National Aeronautics and Space Administration geobrowser for three dimensional graphical representations for ownship and air traffic situational awareness. The flight-test objectives were to evaluate the performance of Automatic Dependent Surveillance-Broadcast Detect and Avoid collision avoidance technology as installed on two small unmanned aircraft systems. In December 2016, four flight tests were conducted at Edwards Air Force Base. Researchers in the ground control station looking at displays were able to verify the Automatic Dependent Surveillance-Broadcast target detection and collision avoidance resolutions.

Convolution neural-network-based detection of lung structures

NASA Astrophysics Data System (ADS)

Hasegawa, Akira; Lo, Shih-Chung B.; Freedman, Matthew T.; Mun, Seong K.

1994-05-01

Chest radiography is one of the most primary and widely used techniques in diagnostic imaging. Nowadays with the advent of digital radiology, the digital medical image processing techniques for digital chest radiographs have attracted considerable attention, and several studies on the computer-aided diagnosis (CADx) as well as on the conventional image processing techniques for chest radiographs have been reported. In the automatic diagnostic process for chest radiographs, it is important to outline the areas of the lungs, the heart, and the diaphragm. This is because the original chest radiograph is composed of important anatomic structures and, without knowing exact positions of the organs, the automatic diagnosis may result in unexpected detections. The automatic extraction of an anatomical structure from digital chest radiographs can be a useful tool for (1) the evaluation of heart size, (2) automatic detection of interstitial lung diseases, (3) automatic detection of lung nodules, and (4) data compression, etc. Based on the clearly defined boundaries of heart area, rib spaces, rib positions, and rib cage extracted, one should be able to use this information to facilitate the tasks of the CADx on chest radiographs. In this paper, we present an automatic scheme for the detection of lung field from chest radiographs by using a shift-invariant convolution neural network. A novel algorithm for smoothing boundaries of lungs is also presented.

Automatic characterization and segmentation of human skin using three-dimensional optical coherence tomography

NASA Astrophysics Data System (ADS)

Hori, Yasuaki; Yasuno, Yoshiaki; Sakai, Shingo; Matsumoto, Masayuki; Sugawara, Tomoko; Madjarova, Violeta; Yamanari, Masahiro; Makita, Shuichi; Yasui, Takeshi; Araki, Tsutomu; Itoh, Masahide; Yatagai, Toyohiko

2006-03-01

A set of fully automated algorithms that is specialized for analyzing a three-dimensional optical coherence tomography (OCT) volume of human skin is reported. The algorithm set first determines the skin surface of the OCT volume, and a depth-oriented algorithm provides the mean epidermal thickness, distribution map of the epidermis, and a segmented volume of the epidermis. Subsequently, an en face shadowgram is produced by an algorithm to visualize the infundibula in the skin with high contrast. The population and occupation ratio of the infundibula are provided by a histogram-based thresholding algorithm and a distance mapping algorithm. En face OCT slices at constant depths from the sample surface are extracted, and the histogram-based thresholding algorithm is again applied to these slices, yielding a three-dimensional segmented volume of the infundibula. The dermal attenuation coefficient is also calculated from the OCT volume in order to evaluate the skin texture. The algorithm set examines swept-source OCT volumes of the skins of several volunteers, and the results show the high stability, portability and reproducibility of the algorithm.

Neural network model for automatic traffic incident detection : executive summary.

DOT National Transportation Integrated Search

2001-04-01

Automatic freeway incident detection is an important component of advanced transportation management systems (ATMS) that provides information for emergency relief and traffic control and management purposes. In this research, a multi-paradigm intelli...

SU-E-CAMPUS-I-04: Automatic Skin-Dose Mapping for An Angiographic System with a Region-Of-Interest, High-Resolution Detector

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vijayan, S; Rana, V; Setlur Nagesh, S

2014-06-15

Purpose: Our real-time skin dose tracking system (DTS) has been upgraded to monitor dose for the micro-angiographic fluoroscope (MAF), a high-resolution, small field-of-view x-ray detector. Methods: The MAF has been mounted on a changer on a clinical C-Arm gantry so it can be used interchangeably with the standard flat-panel detector (FPD) during neuro-interventional procedures when high resolution is needed in a region-of-interest. To monitor patient skin dose when using the MAF, our DTS has been modified to automatically account for the change in scatter for the very small MAF FOV and to provide separated dose distributions for each detector. Themore » DTS is able to provide a color-coded mapping of the cumulative skin dose on a 3D graphic model of the patient. To determine the correct entrance skin exposure to be applied by the DTS, a correction factor was determined by measuring the exposure at the entrance surface of a skull phantom with an ionization chamber as a function of entrance beam size for various beam filters and kVps. Entrance exposure measurements included primary radiation, patient backscatter and table forward scatter. To allow separation of the dose from each detector, a parameter log is kept that allows a replay of the procedure exposure events and recalculation of the dose components.The graphic display can then be constructed showing the dose distribution from the MAF and FPD separately or together. Results: The DTS is able to provide separate displays of dose for the MAF and FPD with field-size specific scatter corrections. These measured corrections change from about 49% down to 10% when changing from the FPD to the MAF. Conclusion: The upgraded DTS allows identification of the patient skin dose delivered when using each detector in order to achieve improved dose management as well as to facilitate peak skin-dose reduction through dose spreading. Research supported in part by Toshiba Medical Systems Corporation and NIH Grants R43FD0158401, R44FD0158402 and R01EB002873.« less

Supporting the Development and Adoption of Automatic Lameness Detection Systems in Dairy Cattle: Effect of System Cost and Performance on Potential Market Shares.

PubMed

Van De Gucht, Tim; Van Weyenberg, Stephanie; Van Nuffel, Annelies; Lauwers, Ludwig; Vangeyte, Jürgen; Saeys, Wouter

2017-10-08

Most automatic lameness detection system prototypes have not yet been commercialized, and are hence not yet adopted in practice. Therefore, the objective of this study was to simulate the effect of detection performance (percentage missed lame cows and percentage false alarms) and system cost on the potential market share of three automatic lameness detection systems relative to visual detection: a system attached to the cow, a walkover system, and a camera system. Simulations were done using a utility model derived from survey responses obtained from dairy farmers in Flanders, Belgium. Overall, systems attached to the cow had the largest market potential, but were still not competitive with visual detection. Increasing the detection performance or lowering the system cost led to higher market shares for automatic systems at the expense of visual detection. The willingness to pay for extra performance was €2.57 per % less missed lame cows, €1.65 per % less false alerts, and €12.7 for lame leg indication, respectively. The presented results could be exploited by system designers to determine the effect of adjustments to the technology on a system's potential adoption rate.

Automatic zebrafish heartbeat detection and analysis for zebrafish embryos.

PubMed

Pylatiuk, Christian; Sanchez, Daniela; Mikut, Ralf; Alshut, Rüdiger; Reischl, Markus; Hirth, Sofia; Rottbauer, Wolfgang; Just, Steffen

2014-08-01

A fully automatic detection and analysis method of heartbeats in videos of nonfixed and nonanesthetized zebrafish embryos is presented. This method reduces the manual workload and time needed for preparation and imaging of the zebrafish embryos, as well as for evaluating heartbeat parameters such as frequency, beat-to-beat intervals, and arrhythmicity. The method is validated by a comparison of the results from automatic and manual detection of the heart rates of wild-type zebrafish embryos 36-120 h postfertilization and of embryonic hearts with bradycardia and pauses in the cardiac contraction.

Automatic detection of larynx cancer from contrast-enhanced magnetic resonance images

NASA Astrophysics Data System (ADS)

Doshi, Trushali; Soraghan, John; Grose, Derek; MacKenzie, Kenneth; Petropoulakis, Lykourgos

2015-03-01

Detection of larynx cancer from medical imaging is important for the quantification and for the definition of target volumes in radiotherapy treatment planning (RTP). Magnetic resonance imaging (MRI) is being increasingly used in RTP due to its high resolution and excellent soft tissue contrast. Manually detecting larynx cancer from sequential MRI is time consuming and subjective. The large diversity of cancer in terms of geometry, non-distinct boundaries combined with the presence of normal anatomical regions close to the cancer regions necessitates the development of automatic and robust algorithms for this task. A new automatic algorithm for the detection of larynx cancer from 2D gadoliniumenhanced T1-weighted (T1+Gd) MRI to assist clinicians in RTP is presented. The algorithm employs edge detection using spatial neighborhood information of pixels and incorporates this information in a fuzzy c-means clustering process to robustly separate different tissues types. Furthermore, it utilizes the information of the expected cancerous location for cancer regions labeling. Comparison of this automatic detection system with manual clinical detection on real T1+Gd axial MRI slices of 2 patients (24 MRI slices) with visible larynx cancer yields an average dice similarity coefficient of 0.78+/-0.04 and average root mean square error of 1.82+/-0.28 mm. Preliminary results show that this fully automatic system can assist clinicians in RTP by obtaining quantifiable and non-subjective repeatable detection results in a particular time-efficient and unbiased fashion.

Individual Differences in Automatic Emotion Regulation Interact with Primed Emotion Regulation during an Anger Provocation.

PubMed

Zhang, Jing; Lipp, Ottmar V; Hu, Ping

2017-01-01

The current study investigated the interactive effects of individual differences in automatic emotion regulation (AER) and primed emotion regulation strategy on skin conductance level (SCL) and heart rate during provoked anger. The study was a 2 × 2 [AER tendency (expression vs. control) × priming (expression vs. control)] between subject design. Participants were assigned to two groups according to their performance on an emotion regulation-IAT (differentiating automatic emotion control tendency and automatic emotion expression tendency). Then participants of the two groups were randomly assigned to two emotion regulation priming conditions (emotion control priming or emotion expression priming). Anger was provoked by blaming participants for slow performance during a subsequent backward subtraction task. In anger provocation, SCL of individuals with automatic emotion control tendencies in the control priming condition was lower than of those with automatic emotion control tendencies in the expression priming condition. However, SCL of individuals with automatic emotion expression tendencies did no differ in the automatic emotion control priming or the automatic emotion expression priming condition. Heart rate during anger provocation was higher in individuals with automatic emotion expression tendencies than in individuals with automatic emotion control tendencies regardless of priming condition. This pattern indicates an interactive effect of individual differences in AER and emotion regulation priming on SCL, which is an index of emotional arousal. Heart rate was only sensitive to the individual differences in AER, and did not reflect this interaction. This finding has implications for clinical studies of the use of emotion regulation strategy training suggesting that different practices are optimal for individuals who differ in AER tendencies.

Automatically Detecting Likely Edits in Clinical Notes Created Using Automatic Speech Recognition

PubMed Central

Lybarger, Kevin; Ostendorf, Mari; Yetisgen, Meliha

2017-01-01

The use of automatic speech recognition (ASR) to create clinical notes has the potential to reduce costs associated with note creation for electronic medical records, but at current system accuracy levels, post-editing by practitioners is needed to ensure note quality. Aiming to reduce the time required to edit ASR transcripts, this paper investigates novel methods for automatic detection of edit regions within the transcripts, including both putative ASR errors but also regions that are targets for cleanup or rephrasing. We create detection models using logistic regression and conditional random field models, exploring a variety of text-based features that consider the structure of clinical notes and exploit the medical context. Different medical text resources are used to improve feature extraction. Experimental results on a large corpus of practitioner-edited clinical notes show that 67% of sentence-level edits and 45% of word-level edits can be detected with a false detection rate of 15%. PMID:29854187

Neural network model for automatic traffic incident detection : final report, August 2001.

DOT National Transportation Integrated Search

2001-08-01

Automatic freeway incident detection is an important component of advanced transportation management systems (ATMS) that provides information for emergency relief and traffic control and management purposes. In this research, a multi-paradigm intelli...

Detecting cheaters without thinking: testing the automaticity of the cheater detection module.

PubMed

Van Lier, Jens; Revlin, Russell; De Neys, Wim

2013-01-01

Evolutionary psychologists have suggested that our brain is composed of evolved mechanisms. One extensively studied mechanism is the cheater detection module. This module would make people very good at detecting cheaters in a social exchange. A vast amount of research has illustrated performance facilitation on social contract selection tasks. This facilitation is attributed to the alleged automatic and isolated operation of the module (i.e., independent of general cognitive capacity). This study, using the selection task, tested the critical automaticity assumption in three experiments. Experiments 1 and 2 established that performance on social contract versions did not depend on cognitive capacity or age. Experiment 3 showed that experimentally burdening cognitive resources with a secondary task had no impact on performance on the social contract version. However, in all experiments, performance on a non-social contract version did depend on available cognitive capacity. Overall, findings validate the automatic and effortless nature of social exchange reasoning.

Self-powering/self-cleaning electronic-skin basing on PVDF/TiO2 nanofibers for actively detecting body motion and degrading organic pollutants

NASA Astrophysics Data System (ADS)

Dong, Chuanyi; Fu, Yongming; Zang, Weili; He, Haoxuan; Xing, Lili; Xue, Xinyu

2017-09-01

A flexible self-powering/self-cleaning electronic-skin (e-skin) for actively detecting body motion and degrading organic pollutants has been fabricated from PVDF/TiO2 nanofibers. PVDF/TiO2 nanofibers are synthesized by high voltage electrospinning method. The e-skin can be driven by external mechanical vibration, and actively output piezoelectric impulse. The outputting piezoelectric voltage can be significantly influenced by different applied deformation, acting as both the body-motion-detecting signal and the electricity power for driving the device. The e-skin can detect various body motions, such as pressing, stretching, bending finger and clenching fist. The e-skin also has distinct self-cleaning characteristic through piezo-photocatalytic coupling process. The photocatalytic activity of TiO2 and the piezoelectric effect of PVDF are coupled in a single physical/chemical process, which can efficiently degrade organic pollutants on the e-skin. For example, methylene blue (MB) can be completely degraded within 40 min under UV/ultrasonic irradiation. The present results could provoke a possible new research direction for realizing self-powering multifunctional e-skin.

Automatic Detection of Student Mental Models during Prior Knowledge Activation in MetaTutor

ERIC Educational Resources Information Center

Rus, Vasile; Lintean, Mihai; Azevedo, Roger

2009-01-01

This paper presents several methods to automatically detecting students' mental models in MetaTutor, an intelligent tutoring system that teaches students self-regulatory processes during learning of complex science topics. In particular, we focus on detecting students' mental models based on student-generated paragraphs during prior knowledge…

Automatic control of liquid cooling garment by cutaneous and external auditory meatus temperatures

NASA Technical Reports Server (NTRS)

Fulcher, C. W. G. (Inventor)

1971-01-01

An automatic control apparatus for a liquid cooling garment is described that is responsive to actual physiological needs during work and rest periods of a man clothed in the liquid cooling garment. Four skin temperature readings and a reading taken at the external portion of the auditory meatus are added and used in the control signal for a temperature control valve regulating inlet water temperature for the liquid cooling garment. The control apparatus comprises electronic circuits to which the temperatures are applied as control signals and an electro-pneumatic transducer attached to the control valve.

[Youth Healthcare guideline 'Skin disorders'].

PubMed

Deurloo, Jacqueline A; van Gameren-Oosterom, Helma B M; Kamphuis, Mascha

2012-01-01

There is a high incidence of skin disorders; these are also frequently encountered within Youth Healthcare (YHC). Some skin disorders are caused by an underlying disease, syndrome or child abuse. Therefore, detection of these causes in an early stage is important. Skin disorders can have a huge psychosocial impact on both child and parents. This is one of the reasons why prevention, detection, diagnosis, treatment, referral, and uniform advice and guidance are of great importance. The YHC Guideline examines counselling and advice, criteria for referral to primary or secondary healthcare, and skincare in general. It also describes the disorders that should be actively detected. The Guideline also looks at specific aspects of dark skins and ethnic diversity, and the impact of skin disorders on general wellbeing. The accompanying web-based tool includes argumentation and opinions from experts on more than 75 skin disorders, including illustrations and decision trees, to aid the drawing up of a treatment plan.

Multi-functional angiographic OFDI using frequency-multiplexed dual-beam illumination

PubMed Central

Kim, SunHee; Park, Taejin; Jang, Sun-Joo; Nam, Ahhyun S.; Vakoc, Benjamin J.; Oh, Wang-Yuhl

2015-01-01

Detection of blood flow inside the tissue sample can be achieved by measuring the local change of complex signal over time in angiographic optical coherence tomography (OCT). In conventional angiographic OCT, the transverse displacement of the imaging beam during the time interval between a pair of OCT signal measurements must be significantly reduced to minimize the noise due to the beam scanning-induced phase decorrelation at the expense of the imaging speed. Recent introduction of dual-beam scan method either using polarization encoding or two identical imaging systems in spectral-domain (SD) OCT scheme shows potential for high-sensitivity vasculature imaging without suffering from spurious phase noise caused by the beam scanning-induced spatial decorrelation. In this paper, we present multi-functional angiographic optical frequency domain imaging (OFDI) using frequency-multiplexed dual-beam illumination. This frequency multiplexing scheme, utilizing unique features of OFDI, provides spatially separated dual imaging beams occupying distinct electrical frequency bands that can be demultiplexed in the frequency domain processing. We demonstrate the 3D multi-functional imaging of the normal mouse skin in the dorsal skin fold chamber visualizing distinct layer structures from the intensity imaging, information about mechanical integrity from the polarization-sensitive imaging, and depth-resolved microvasculature from the angiographic imaging that are simultaneously acquired and automatically co-registered. PMID:25968731

Hyperspectrally-Resolved Surface Emissivity Derived Under Optically Thin Clouds

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Larar, Allen M.; Liu, Xu; Smith, William L.; Strow, L. Larrabee; Yang, Ping

2010-01-01

Surface spectral emissivity derived from current and future satellites can and will reveal critical information about the Earth s ecosystem and land surface type properties, which can be utilized as a means of long-term monitoring of global environment and climate change. Hyperspectrally-resolved surface emissivities are derived with an algorithm utilizes a combined fast radiative transfer model (RTM) with a molecular RTM and a cloud RTM accounting for both atmospheric absorption and cloud absorption/scattering. Clouds are automatically detected and cloud microphysical parameters are retrieved; and emissivity is retrieved under clear and optically thin cloud conditions. This technique separates surface emissivity from skin temperature by representing the emissivity spectrum with eigenvectors derived from a laboratory measured emissivity database; in other words, using the constraint as a means for the emissivity to vary smoothly across atmospheric absorption lines. Here we present the emissivity derived under optically thin clouds in comparison with that under clear conditions.

An All-Silk-Derived Dual-Mode E-skin for Simultaneous Temperature-Pressure Detection.

PubMed

Wang, Chunya; Xia, Kailun; Zhang, Mingchao; Jian, Muqiang; Zhang, Yingying

2017-11-15

Flexible skin-mimicking electronics are highly desired for development of smart human-machine interfaces and wearable human-health monitors. Human skins are able to simultaneously detect different information, such as touch, friction, temperature, and humidity. However, due to the mutual interferences of sensors with different functions, it is still a big challenge to fabricate multifunctional electronic skins (E-skins). Herein, a combo temperature-pressure E-skin is reported through assembling a temperature sensor and a strain sensor in both of which flexible and transparent silk-nanofiber-derived carbon fiber membranes (SilkCFM) are used as the active material. The temperature sensor presents high temperature sensitivity of 0.81% per centigrade. The strain sensor shows an extremely high sensitivity with a gauge factor of ∼8350 at 50% strain, enabling the detection of subtle pressure stimuli that induce local strain. Importantly, the structure of the SilkCFM in each sensor is designed to be passive to other stimuli, enabling the integrated E-skin to precisely detect temperature and pressure at the same time. It is demonstrated that the E-skin can detect and distinguish exhaling, finger pressing, and spatial distribution of temperature and pressure, which cannot be realized using single mode sensors. The remarkable performance of the silk-based combo temperature-pressure sensor, together with its green and large-scalable fabrication process, promising its applications in human-machine interfaces and soft electronics.

DALMATIAN: An Algorithm for Automatic Cell Detection and Counting in 3D.

PubMed

Shuvaev, Sergey A; Lazutkin, Alexander A; Kedrov, Alexander V; Anokhin, Konstantin V; Enikolopov, Grigori N; Koulakov, Alexei A

2017-01-01

Current 3D imaging methods, including optical projection tomography, light-sheet microscopy, block-face imaging, and serial two photon tomography enable visualization of large samples of biological tissue. Large volumes of data obtained at high resolution require development of automatic image processing techniques, such as algorithms for automatic cell detection or, more generally, point-like object detection. Current approaches to automated cell detection suffer from difficulties originating from detection of particular cell types, cell populations of different brightness, non-uniformly stained, and overlapping cells. In this study, we present a set of algorithms for robust automatic cell detection in 3D. Our algorithms are suitable for, but not limited to, whole brain regions and individual brain sections. We used watershed procedure to split regional maxima representing overlapping cells. We developed a bootstrap Gaussian fit procedure to evaluate the statistical significance of detected cells. We compared cell detection quality of our algorithm and other software using 42 samples, representing 6 staining and imaging techniques. The results provided by our algorithm matched manual expert quantification with signal-to-noise dependent confidence, including samples with cells of different brightness, non-uniformly stained, and overlapping cells for whole brain regions and individual tissue sections. Our algorithm provided the best cell detection quality among tested free and commercial software.

OKCARS : Oklahoma Collision Analysis and Response System.

DOT National Transportation Integrated Search

2012-10-01

By continuously monitoring traffic intersections to automatically detect that a collision or nearcollision : has occurred, automatically call for assistance, and automatically forewarn oncoming traffic, : our OKCARS has the capability to effectively ...

Testing & Evaluation of Close-Range SAR for Monitoring & Automatically Detecting Pavement Conditions

DOT National Transportation Integrated Search

2012-01-01

This report summarizes activities in support of the DOT contract on Testing & Evaluating Close-Range SAR for Monitoring & Automatically Detecting Pavement Conditions & Improve Visual Inspection Procedures. The work of this project was performed by Dr...

Influence of enrichment and isolation media on the detection of Campylobacter spp. in naturally contaminated chicken samples.

PubMed

Repérant, E; Laisney, M J; Nagard, B; Quesne, S; Rouxel, S; Le Gall, F; Chemaly, M; Denis, M

2016-09-01

Investigating Campylobacter epidemiology requires adequate technique and media to ensure optimal culturing and accurate detection and isolation of Campylobacter strains. In the present study, we investigated the performances of three enrichment durations in Bolton broth (0, 24 and 48h) and compared four isolation media (mCCDA, Karmali, Butzler no. 2 and CampyFood agar (CFA)) for the detection of Campylobacter positive samples and the identification of Campylobacter species, from naturally contaminated broiler chicken samples (caeca, neck skin from carcasses, and skin from thighs). We compared our local results to those we obtained with samples from a European survey (caeca and neck skin) and a national survey (neck skin, thigh skin, and breast). Direct plating favored the detection of positive samples highly contaminated by Campylobacter (caeca and neck skin from carcasses) whatever the media. A longer enrichment reduced the rates of Campylobacter recovery except when using Butzler no. 2, more particularly for neck skin which background microflora was less important than in caeca. As a matter of fact, enrichment allowed a higher detection rate of positive samples with low Campylobacter contamination levels (breast, thigh skin), this detection being enhanced when using Butzler no. 2. When comparing the 3 other selective media, CFA was the 2nd most efficient media prior to mCCDA and Karmali. Interestingly, enrichment promoted the growth of Campylobacter coli but this promotion was least with Butzler no. 2 agar. Our study has confirmed the need to adapt the method to the types of samples for improving the detection of Campylobacter and that the method may affect the prevalence of the species. Copyright © 2016 Elsevier B.V. All rights reserved.

Comparison of acetate tape impression with squeezing versus skin scraping for the diagnosis of canine demodicosis.

PubMed

Pereira, A V; Pereira, S A; Gremião, I D F; Campos, M P; Ferreira, A M R

2012-11-01

This study compared the sensitivity of acetate tape impression and skin squeezing with that of deep skin scraping for the diagnosis of demodicosis in dogs. Demodex canis was detected in 100% of acetate tape impressions obtained after skin squeezing and in 90% of deep skin scrapings. There was a significant difference (P < 0.001) between the techniques in the total number of mites detected. Acetate tape impression with skin squeezing was found to be more sensitive than deep skin scraping and is an alternative diagnostic method for canine demodicosis. © 2012 The Authors. Australian Veterinary Journal © 2012 Australian Veterinary Association.

Automated Segmentation Methods of Drusen to Diagnose Age-Related Macular Degeneration Screening in Retinal Images.

PubMed

Kim, Young Jae; Kim, Kwang Gi

2018-01-01

Existing drusen measurement is difficult to use in clinic because it requires a lot of time and effort for visual inspection. In order to resolve this problem, we propose an automatic drusen detection method to help clinical diagnosis of age-related macular degeneration. First, we changed the fundus image to a green channel and extracted the ROI of the macular area based on the optic disk. Next, we detected the candidate group using the difference image of the median filter within the ROI. We also segmented vessels and removed them from the image. Finally, we detected the drusen through Renyi's entropy threshold algorithm. We performed comparisons and statistical analysis between the manual detection results and automatic detection results for 30 cases in order to verify validity. As a result, the average sensitivity was 93.37% (80.95%~100%) and the average DSC was 0.73 (0.3~0.98). In addition, the value of the ICC was 0.984 (CI: 0.967~0.993, p < 0.01), showing the high reliability of the proposed automatic method. We expect that the automatic drusen detection helps clinicians to improve the diagnostic performance in the detection of drusen on fundus image.

A fast automatic target detection method for detecting ships in infrared scenes

NASA Astrophysics Data System (ADS)

Özertem, Kemal Arda

2016-05-01

Automatic target detection in infrared scenes is a vital task for many application areas like defense, security and border surveillance. For anti-ship missiles, having a fast and robust ship detection algorithm is crucial for overall system performance. In this paper, a straight-forward yet effective ship detection method for infrared scenes is introduced. First, morphological grayscale reconstruction is applied to the input image, followed by an automatic thresholding onto the suppressed image. For the segmentation step, connected component analysis is employed to obtain target candidate regions. At this point, it can be realized that the detection is defenseless to outliers like small objects with relatively high intensity values or the clouds. To deal with this drawback, a post-processing stage is introduced. For the post-processing stage, two different methods are used. First, noisy detection results are rejected with respect to target size. Second, the waterline is detected by using Hough transform and the detection results that are located above the waterline with a small margin are rejected. After post-processing stage, there are still undesired holes remaining, which cause to detect one object as multi objects or not to detect an object as a whole. To improve the detection performance, another automatic thresholding is implemented only to target candidate regions. Finally, two detection results are fused and post-processing stage is repeated to obtain final detection result. The performance of overall methodology is tested with real world infrared test data.

Automatic Detection of Storm Damages Using High-Altitude Photogrammetric Imaging

NASA Astrophysics Data System (ADS)

Litkey, P.; Nurminen, K.; Honkavaara, E.

2013-05-01

The risks of storms that cause damage in forests are increasing due to climate change. Quickly detecting fallen trees, assessing the amount of fallen trees and efficiently collecting them are of great importance for economic and environmental reasons. Visually detecting and delineating storm damage is a laborious and error-prone process; thus, it is important to develop cost-efficient and highly automated methods. Objective of our research project is to investigate and develop a reliable and efficient method for automatic storm damage detection, which is based on airborne imagery that is collected after a storm. The requirements for the method are the before-storm and after-storm surface models. A difference surface is calculated using two DSMs and the locations where significant changes have appeared are automatically detected. In our previous research we used four-year old airborne laser scanning surface model as the before-storm surface. The after-storm DSM was provided from the photogrammetric images using the Next Generation Automatic Terrain Extraction (NGATE) algorithm of Socet Set software. We obtained 100% accuracy in detection of major storm damages. In this investigation we will further evaluate the sensitivity of the storm-damage detection process. We will investigate the potential of national airborne photography, that is collected at no-leaf season, to automatically produce a before-storm DSM using image matching. We will also compare impact of the terrain extraction algorithm to the results. Our results will also promote the potential of national open source data sets in the management of natural disasters.

Automatic video shot boundary detection using k-means clustering and improved adaptive dual threshold comparison

NASA Astrophysics Data System (ADS)

Sa, Qila; Wang, Zhihui

2018-03-01

At present, content-based video retrieval (CBVR) is the most mainstream video retrieval method, using the video features of its own to perform automatic identification and retrieval. This method involves a key technology, i.e. shot segmentation. In this paper, the method of automatic video shot boundary detection with K-means clustering and improved adaptive dual threshold comparison is proposed. First, extract the visual features of every frame and divide them into two categories using K-means clustering algorithm, namely, one with significant change and one with no significant change. Then, as to the classification results, utilize the improved adaptive dual threshold comparison method to determine the abrupt as well as gradual shot boundaries.Finally, achieve automatic video shot boundary detection system.

Obscenity detection using haar-like features and Gentle Adaboost classifier.

PubMed

Mustafa, Rashed; Min, Yang; Zhu, Dingju

2014-01-01

Large exposure of skin area of an image is considered obscene. This only fact may lead to many false images having skin-like objects and may not detect those images which have partially exposed skin area but have exposed erotogenic human body parts. This paper presents a novel method for detecting nipples from pornographic image contents. Nipple is considered as an erotogenic organ to identify pornographic contents from images. In this research Gentle Adaboost (GAB) haar-cascade classifier and haar-like features used for ensuring detection accuracy. Skin filter prior to detection made the system more robust. The experiment showed that, considering accuracy, haar-cascade classifier performs well, but in order to satisfy detection time, train-cascade classifier is suitable. To validate the results, we used 1198 positive samples containing nipple objects and 1995 negative images. The detection rates for haar-cascade and train-cascade classifiers are 0.9875 and 0.8429, respectively. The detection time for haar-cascade is 0.162 seconds and is 0.127 seconds for train-cascade classifier.

Bringing skin assessments to life using human patient simulation: an emphasis on cancer prevention and early detection.

PubMed

Kuhrik, Marilee; Seckman, Christy; Kuhrik, Nancy; Ahearn, Tina; Ercole, Patrick

2011-12-01

Skin cancer is the most common cancer in the United States, with about 1,000,000 people developing the disease each year. The incidence of melanoma has rapidly increased in young white women between the ages of 15-34 over the last three decades. While melanoma accounts for approximately 3% of skin cancers, it causes more than 75% of skin cancer deaths. Thorough skin assessments and awareness of new or changing appearance of skin lesions are critical to early detection and treatment of skin cancer, as well as teaching sun-protective behaviors. Educators created a novel approach to "bring to life" skin cancer assessment skills to promote awareness of prevention and early detection of skin cancer using moulage in a human patient simulation lab. Through the use of moulage-like lesions, simulated patients were evaluated and taught skin cancer prevention and early detection principles by baccalaureate nursing students. The average age of study participants (n = 104) was 26.50 years. The majority of responders were female. At the end of the lab, students' average responses to an evaluation based on program goals were very positive. Anecdotal comments affirmed positive student perceptions of their simulation experience. Data analyses indicated item means were consistently higher for upper-division students. The age and gender of students who participated in this study align with the NCI statistics on age and gender of the population with increased incidence of melanoma.

Health system costs of skin cancer and cost-effectiveness of skin cancer prevention and screening: a systematic review.

PubMed

Gordon, Louisa G; Rowell, David

2015-03-01

The objective of this study was to review the literature for malignant melanoma, basal and squamous cell carcinomas to understand: (a) national estimates of the direct health system costs of skin cancer and (b) the cost-effectiveness of interventions for skin cancer prevention or early detection. A systematic review was performed using Medline, Cochrane Library and the National Health Service Economic Evaluation Databases as well as a manual search of reference lists to identify relevant studies up to 31 August 2013. A narrative synthesis approach was used to summarize the data. National cost estimates were adjusted for country-specific inflation and presented in 2013 euros. The CHEERS statement was used to assess the quality of the economic evaluation studies. Sixteen studies reporting national estimates of skin cancer costs and 11 cost-effectiveness studies on skin cancer prevention or early detection were identified. Relative to the size of their respective populations, the annual direct health system costs for skin cancer were highest for Australia, New Zealand, Sweden and Denmark (2013 euros). Skin cancer prevention initiatives are highly cost-effective and may also be cost-saving. Melanoma early detection programmes aimed at high-risk individuals may also be cost-effective; however, updated analyses are needed. There is a significant cost burden of skin cancer for many countries and health expenditure for this disease will grow as incidence increases. Public investment in skin cancer prevention and early detection programmes show strong potential for health and economic benefits.

SU-E-J-15: Automatically Detect Patient Treatment Position and Orientation in KV Portal Images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Qiu, J; Yang, D

2015-06-15

Purpose: In the course of radiation therapy, the complex information processing workflow will Result in potential errors, such as incorrect or inaccurate patient setups. With automatic image check and patient identification, such errors could be effectively reduced. For this purpose, we developed a simple and rapid image processing method, to automatically detect the patient position and orientation in 2D portal images, so to allow automatic check of positions and orientations for patient daily RT treatments. Methods: Based on the principle of portal image formation, a set of whole body DRR images were reconstructed from multiple whole body CT volume datasets,more » and fused together to be used as the matching template. To identify the patient setup position and orientation shown in a 2D portal image, the 2D portal image was preprocessed (contrast enhancement, down-sampling and couch table detection), then matched to the template image so to identify the laterality (left or right), position, orientation and treatment site. Results: Five day’s clinical qualified portal images were gathered randomly, then were processed by the automatic detection and matching method without any additional information. The detection results were visually checked by physicists. 182 images were correct detection in a total of 200kV portal images. The correct rate was 91%. Conclusion: The proposed method can detect patient setup and orientation quickly and automatically. It only requires the image intensity information in KV portal images. This method can be useful in the framework of Electronic Chart Check (ECCK) to reduce the potential errors in workflow of radiation therapy and so to improve patient safety. In addition, the auto-detection results, as the patient treatment site position and patient orientation, could be useful to guide the sequential image processing procedures, e.g. verification of patient daily setup accuracy. This work was partially supported by research grant from Varian Medical System.« less

Four-Channel Biosignal Analysis and Feature Extraction for Automatic Emotion Recognition

NASA Astrophysics Data System (ADS)

Kim, Jonghwa; André, Elisabeth

This paper investigates the potential of physiological signals as a reliable channel for automatic recognition of user's emotial state. For the emotion recognition, little attention has been paid so far to physiological signals compared to audio-visual emotion channels such as facial expression or speech. All essential stages of automatic recognition system using biosignals are discussed, from recording physiological dataset up to feature-based multiclass classification. Four-channel biosensors are used to measure electromyogram, electrocardiogram, skin conductivity and respiration changes. A wide range of physiological features from various analysis domains, including time/frequency, entropy, geometric analysis, subband spectra, multiscale entropy, etc., is proposed in order to search the best emotion-relevant features and to correlate them with emotional states. The best features extracted are specified in detail and their effectiveness is proven by emotion recognition results.

Automatic-repeat-request error control schemes

NASA Technical Reports Server (NTRS)

Lin, S.; Costello, D. J., Jr.; Miller, M. J.

1983-01-01

Error detection incorporated with automatic-repeat-request (ARQ) is widely used for error control in data communication systems. This method of error control is simple and provides high system reliability. If a properly chosen code is used for error detection, virtually error-free data transmission can be attained. Various types of ARQ and hybrid ARQ schemes, and error detection using linear block codes are surveyed.

Automatic Detection of Acromegaly From Facial Photographs Using Machine Learning Methods.

PubMed

Kong, Xiangyi; Gong, Shun; Su, Lijuan; Howard, Newton; Kong, Yanguo

2018-01-01

Automatic early detection of acromegaly is theoretically possible from facial photographs, which can lessen the prevalence and increase the cure probability. In this study, several popular machine learning algorithms were used to train a retrospective development dataset consisting of 527 acromegaly patients and 596 normal subjects. We firstly used OpenCV to detect the face bounding rectangle box, and then cropped and resized it to the same pixel dimensions. From the detected faces, locations of facial landmarks which were the potential clinical indicators were extracted. Frontalization was then adopted to synthesize frontal facing views to improve the performance. Several popular machine learning methods including LM, KNN, SVM, RT, CNN, and EM were used to automatically identify acromegaly from the detected facial photographs, extracted facial landmarks, and synthesized frontal faces. The trained models were evaluated using a separate dataset, of which half were diagnosed as acromegaly by growth hormone suppression test. The best result of our proposed methods showed a PPV of 96%, a NPV of 95%, a sensitivity of 96% and a specificity of 96%. Artificial intelligence can automatically early detect acromegaly with a high sensitivity and specificity. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Investigation of an automatic trim algorithm for restructurable aircraft control

NASA Technical Reports Server (NTRS)

Weiss, J.; Eterno, J.; Grunberg, D.; Looze, D.; Ostroff, A.

1986-01-01

This paper develops and solves an automatic trim problem for restructurable aircraft control. The trim solution is applied as a feed-forward control to reject measurable disturbances following control element failures. Disturbance rejection and command following performances are recovered through the automatic feedback control redesign procedure described by Looze et al. (1985). For this project the existence of a failure detection mechanism is assumed, and methods to cope with potential detection and identification inaccuracies are addressed.

Evaluation of an improved fiberoptics luminescence skin monitor with background correction.

PubMed

Vo-Dinh, T

1987-06-01

In this work, an improved version of a fiberoptics luminescence monitor, the prototype luminoscope II, is evaluated for in situ quantitative measurements. The instrument was developed to detect traces of luminescing organic contaminants on skin. An electronic background-nulling system was designed and incorporated into the instrument to compensate for various skin background emissions. A dose-response curve for a coal liquid spotted on mouse skin was established. The results illustrated the usefulness of the instrument for in vivo detection of organic materials on laboratory mouse skin.

Pigment network-based skin cancer detection.

PubMed

Alfed, Naser; Khelifi, Fouad; Bouridane, Ahmed; Seker, Huseyin

2015-08-01

Diagnosing skin cancer in its early stages is a challenging task for dermatologists given the fact that the chance for a patient's survival is higher and hence the process of analyzing skin images and making decisions should be time efficient. Therefore, diagnosing the disease using automated and computerized systems has nowadays become essential. This paper proposes an efficient system for skin cancer detection on dermoscopic images. It has been shown that the statistical characteristics of the pigment network, extracted from the dermoscopic image, could be used as efficient discriminating features for cancer detection. The proposed system has been assessed on a dataset of 200 dermoscopic images of the `Hospital Pedro Hispano' [1] and the results of cross-validation have shown high detection accuracy.

A Plane Target Detection Algorithm in Remote Sensing Images based on Deep Learning Network Technology

NASA Astrophysics Data System (ADS)

Shuxin, Li; Zhilong, Zhang; Biao, Li

2018-01-01

Plane is an important target category in remote sensing targets and it is of great value to detect the plane targets automatically. As remote imaging technology developing continuously, the resolution of the remote sensing image has been very high and we can get more detailed information for detecting the remote sensing targets automatically. Deep learning network technology is the most advanced technology in image target detection and recognition, which provided great performance improvement in the field of target detection and recognition in the everyday scenes. We combined the technology with the application in the remote sensing target detection and proposed an algorithm with end to end deep network, which can learn from the remote sensing images to detect the targets in the new images automatically and robustly. Our experiments shows that the algorithm can capture the feature information of the plane target and has better performance in target detection with the old methods.

Automatic mine detection based on multiple features

NASA Astrophysics Data System (ADS)

Yu, Ssu-Hsin; Gandhe, Avinash; Witten, Thomas R.; Mehra, Raman K.

2000-08-01

Recent research sponsored by the Army, Navy and DARPA has significantly advanced the sensor technologies for mine detection. Several innovative sensor systems have been developed and prototypes were built to investigate their performance in practice. Most of the research has been focused on hardware design. However, in order for the systems to be in wide use instead of in limited use by a small group of well-trained experts, an automatic process for mine detection is needed to make the final decision process on mine vs. no mine easier and more straightforward. In this paper, we describe an automatic mine detection process consisting of three stage, (1) signal enhancement, (2) pixel-level mine detection, and (3) object-level mine detection. The final output of the system is a confidence measure that quantifies the presence of a mine. The resulting system was applied to real data collected using radar and acoustic technologies.

Automatically detect and track infrared small targets with kernel Fukunaga-Koontz transform and Kalman prediction.

PubMed

Liu, Ruiming; Liu, Erqi; Yang, Jie; Zeng, Yong; Wang, Fanglin; Cao, Yuan

2007-11-01

Fukunaga-Koontz transform (FKT), stemming from principal component analysis (PCA), is used in many pattern recognition and image-processing fields. It cannot capture the higher-order statistical property of natural images, so its detection performance is not satisfying. PCA has been extended into kernel PCA in order to capture the higher-order statistics. However, thus far there have been no researchers who have definitely proposed kernel FKT (KFKT) and researched its detection performance. For accurately detecting potential small targets from infrared images, we first extend FKT into KFKT to capture the higher-order statistical properties of images. Then a framework based on Kalman prediction and KFKT, which can automatically detect and track small targets, is developed. Results of experiments show that KFKT outperforms FKT and the proposed framework is competent to automatically detect and track infrared point targets.

Automatically detect and track infrared small targets with kernel Fukunaga-Koontz transform and Kalman prediction

NASA Astrophysics Data System (ADS)

Liu, Ruiming; Liu, Erqi; Yang, Jie; Zeng, Yong; Wang, Fanglin; Cao, Yuan

2007-11-01

Fukunaga-Koontz transform (FKT), stemming from principal component analysis (PCA), is used in many pattern recognition and image-processing fields. It cannot capture the higher-order statistical property of natural images, so its detection performance is not satisfying. PCA has been extended into kernel PCA in order to capture the higher-order statistics. However, thus far there have been no researchers who have definitely proposed kernel FKT (KFKT) and researched its detection performance. For accurately detecting potential small targets from infrared images, we first extend FKT into KFKT to capture the higher-order statistical properties of images. Then a framework based on Kalman prediction and KFKT, which can automatically detect and track small targets, is developed. Results of experiments show that KFKT outperforms FKT and the proposed framework is competent to automatically detect and track infrared point targets.

Fusion of cone-beam CT and 3D photographic images for soft tissue simulation in maxillofacial surgery

NASA Astrophysics Data System (ADS)

Chung, Soyoung; Kim, Joojin; Hong, Helen

2016-03-01

During maxillofacial surgery, prediction of the facial outcome after surgery is main concern for both surgeons and patients. However, registration of the facial CBCT images and 3D photographic images has some difficulties that regions around the eyes and mouth are affected by facial expressions or the registration speed is low due to their dense clouds of points on surfaces. Therefore, we propose a framework for the fusion of facial CBCT images and 3D photos with skin segmentation and two-stage surface registration. Our method is composed of three major steps. First, to obtain a CBCT skin surface for the registration with 3D photographic surface, skin is automatically segmented from CBCT images and the skin surface is generated by surface modeling. Second, to roughly align the scale and the orientation of the CBCT skin surface and 3D photographic surface, point-based registration with four corresponding landmarks which are located around the mouth is performed. Finally, to merge the CBCT skin surface and 3D photographic surface, Gaussian-weight-based surface registration is performed within narrow-band of 3D photographic surface.

Chemometric strategy for automatic chromatographic peak detection and background drift correction in chromatographic data.

PubMed

Yu, Yong-Jie; Xia, Qiao-Ling; Wang, Sheng; Wang, Bing; Xie, Fu-Wei; Zhang, Xiao-Bing; Ma, Yun-Ming; Wu, Hai-Long

2014-09-12

Peak detection and background drift correction (BDC) are the key stages in using chemometric methods to analyze chromatographic fingerprints of complex samples. This study developed a novel chemometric strategy for simultaneous automatic chromatographic peak detection and BDC. A robust statistical method was used for intelligent estimation of instrumental noise level coupled with first-order derivative of chromatographic signal to automatically extract chromatographic peaks in the data. A local curve-fitting strategy was then employed for BDC. Simulated and real liquid chromatographic data were designed with various kinds of background drift and degree of overlapped chromatographic peaks to verify the performance of the proposed strategy. The underlying chromatographic peaks can be automatically detected and reasonably integrated by this strategy. Meanwhile, chromatograms with BDC can be precisely obtained. The proposed method was used to analyze a complex gas chromatography dataset that monitored quality changes in plant extracts during storage procedure. Copyright © 2014 Elsevier B.V. All rights reserved.

Automatic detection of adverse events to predict drug label changes using text and data mining techniques.

PubMed

Gurulingappa, Harsha; Toldo, Luca; Rajput, Abdul Mateen; Kors, Jan A; Taweel, Adel; Tayrouz, Yorki

2013-11-01

The aim of this study was to assess the impact of automatically detected adverse event signals from text and open-source data on the prediction of drug label changes. Open-source adverse effect data were collected from FAERS, Yellow Cards and SIDER databases. A shallow linguistic relation extraction system (JSRE) was applied for extraction of adverse effects from MEDLINE case reports. Statistical approach was applied on the extracted datasets for signal detection and subsequent prediction of label changes issued for 29 drugs by the UK Regulatory Authority in 2009. 76% of drug label changes were automatically predicted. Out of these, 6% of drug label changes were detected only by text mining. JSRE enabled precise identification of four adverse drug events from MEDLINE that were undetectable otherwise. Changes in drug labels can be predicted automatically using data and text mining techniques. Text mining technology is mature and well-placed to support the pharmacovigilance tasks. Copyright © 2013 John Wiley & Sons, Ltd.

Detecting Cheaters without Thinking: Testing the Automaticity of the Cheater Detection Module

PubMed Central

Van Lier, Jens; Revlin, Russell; De Neys, Wim

2013-01-01

Evolutionary psychologists have suggested that our brain is composed of evolved mechanisms. One extensively studied mechanism is the cheater detection module. This module would make people very good at detecting cheaters in a social exchange. A vast amount of research has illustrated performance facilitation on social contract selection tasks. This facilitation is attributed to the alleged automatic and isolated operation of the module (i.e., independent of general cognitive capacity). This study, using the selection task, tested the critical automaticity assumption in three experiments. Experiments 1 and 2 established that performance on social contract versions did not depend on cognitive capacity or age. Experiment 3 showed that experimentally burdening cognitive resources with a secondary task had no impact on performance on the social contract version. However, in all experiments, performance on a non-social contract version did depend on available cognitive capacity. Overall, findings validate the automatic and effortless nature of social exchange reasoning. PMID:23342012

[Advances in automatic detection technology for images of thin blood film of malaria parasite].

PubMed

Juan-Sheng, Zhang; Di-Qiang, Zhang; Wei, Wang; Xiao-Guang, Wei; Zeng-Guo, Wang

2017-05-05

This paper reviews the computer vision and image analysis studies aiming at automated diagnosis or screening of malaria in microscope images of thin blood film smears. On the basis of introducing the background and significance of automatic detection technology, the existing detection technologies are summarized and divided into several steps, including image acquisition, pre-processing, morphological analysis, segmentation, count, and pattern classification components. Then, the principles and implementation methods of each step are given in detail. In addition, the promotion and application in automatic detection technology of thick blood film smears are put forwarded as questions worthy of study, and a perspective of the future work for realization of automated microscopy diagnosis of malaria is provided.

Corner detection and sorting method based on improved Harris algorithm in camera calibration

NASA Astrophysics Data System (ADS)

Xiao, Ying; Wang, Yonghong; Dan, Xizuo; Huang, Anqi; Hu, Yue; Yang, Lianxiang

2016-11-01

In traditional Harris corner detection algorithm, the appropriate threshold which is used to eliminate false corners is selected manually. In order to detect corners automatically, an improved algorithm which combines Harris and circular boundary theory of corners is proposed in this paper. After detecting accurate corner coordinates by using Harris algorithm and Forstner algorithm, false corners within chessboard pattern of the calibration plate can be eliminated automatically by using circular boundary theory. Moreover, a corner sorting method based on an improved calibration plate is proposed to eliminate false background corners and sort remaining corners in order. Experiment results show that the proposed algorithms can eliminate all false corners and sort remaining corners correctly and automatically.

Object Occlusion Detection Using Automatic Camera Calibration for a Wide-Area Video Surveillance System

PubMed Central

Jung, Jaehoon; Yoon, Inhye; Paik, Joonki

2016-01-01

This paper presents an object occlusion detection algorithm using object depth information that is estimated by automatic camera calibration. The object occlusion problem is a major factor to degrade the performance of object tracking and recognition. To detect an object occlusion, the proposed algorithm consists of three steps: (i) automatic camera calibration using both moving objects and a background structure; (ii) object depth estimation; and (iii) detection of occluded regions. The proposed algorithm estimates the depth of the object without extra sensors but with a generic red, green and blue (RGB) camera. As a result, the proposed algorithm can be applied to improve the performance of object tracking and object recognition algorithms for video surveillance systems. PMID:27347978

Double ErrP Detection for Automatic Error Correction in an ERP-Based BCI Speller.

PubMed

Cruz, Aniana; Pires, Gabriel; Nunes, Urbano J

2018-01-01

Brain-computer interface (BCI) is a useful device for people with severe motor disabilities. However, due to its low speed and low reliability, BCI still has a very limited application in daily real-world tasks. This paper proposes a P300-based BCI speller combined with a double error-related potential (ErrP) detection to automatically correct erroneous decisions. This novel approach introduces a second error detection to infer whether wrong automatic correction also elicits a second ErrP. Thus, two single-trial responses, instead of one, contribute to the final selection, improving the reliability of error detection. Moreover, to increase error detection, the evoked potential detected as target by the P300 classifier is combined with the evoked error potential at a feature-level. Discriminable error and positive potentials (response to correct feedback) were clearly identified. The proposed approach was tested on nine healthy participants and one tetraplegic participant. The online average accuracy for the first and second ErrPs were 88.4% and 84.8%, respectively. With automatic correction, we achieved an improvement around 5% achieving 89.9% in spelling accuracy for an effective 2.92 symbols/min. The proposed approach revealed that double ErrP detection can improve the reliability and speed of BCI systems.

Day, night and all-weather security surveillance automation synergy from combining two powerful technologies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morellas, Vassilios; Johnson, Andrew; Johnston, Chris

2006-07-01

Thermal imaging is rightfully a real-world technology proven to bring confidence to daytime, night-time and all weather security surveillance. Automatic image processing intrusion detection algorithms are also a real world technology proven to bring confidence to system surveillance security solutions. Together, day, night and all weather video imagery sensors and automated intrusion detection software systems create the real power to protect early against crime, providing real-time global homeland protection, rather than simply being able to monitor and record activities for post event analysis. These solutions, whether providing automatic security system surveillance at airports (to automatically detect unauthorized aircraft takeoff andmore » landing activities) or at high risk private, public or government facilities (to automatically detect unauthorized people or vehicle intrusion activities) are on the move to provide end users the power to protect people, capital equipment and intellectual property against acts of vandalism and terrorism. As with any technology, infrared sensors and automatic image intrusion detection systems for global homeland security protection have clear technological strengths and limitations compared to other more common day and night vision technologies or more traditional manual man-in-the-loop intrusion detection security systems. This paper addresses these strength and limitation capabilities. False Alarm (FAR) and False Positive Rate (FPR) is an example of some of the key customer system acceptability metrics and Noise Equivalent Temperature Difference (NETD) and Minimum Resolvable Temperature are examples of some of the sensor level performance acceptability metrics. (authors)« less

Automatic enforcement and highway safety.

DOT National Transportation Integrated Search

2011-05-01

The objectives of this research are to: 1. Identify aspects of the automatic detection of red light running that the public finds offensive or problematical, and quantify the level of opposition on each aspect. 2. Identify aspects of the automatic de...

Automatic detection of electric power troubles (AI application)

NASA Technical Reports Server (NTRS)

Wang, Caroline; Zeanah, Hugh; Anderson, Audie; Patrick, Clint

1987-01-01

The design goals for the Automatic Detection of Electric Power Troubles (ADEPT) were to enhance Fault Diagnosis Techniques in a very efficient way. ADEPT system was designed in two modes of operation: (1) Real time fault isolation, and (2) a local simulator which simulates the models theoretically.

Automatic food detection in egocentric images using artificial intelligence technology

USDA-ARS?s Scientific Manuscript database

Our objective was to develop an artificial intelligence (AI)-based algorithm which can automatically detect food items from images acquired by an egocentric wearable camera for dietary assessment. To study human diet and lifestyle, large sets of egocentric images were acquired using a wearable devic...

[Skin cell response after jellyfish sting].

PubMed

Adamicová, Katarína; Výbohová, Desanka; Fetisovová, Želmíra; Nováková, Elena; Mellová, Yvetta

2016-01-01

Jellyfish burning is not commonly part of the professional finding in the central Europe health care laboratory. Holiday seaside tourism includes different and unusual presentations of diseases for our worklplaces. Sea water-sports and leisure is commonly connected with jellyfish burning and changes in the skin, that are not precisely described. Authors focused their research on detection of morphological and quantitative changes of some inflammatory cells in the skin biopsy of a 59-years-old woman ten days after a jellyfish stinging. Because of a comparison of findings the biopsy was performed in the skin with lesional and nonlesional skin. Both excisions of the skin were tested by imunohistochemical methods to detect CD68, CD163, CD30, CD4, CD3, CD8, CD20 a CD1a, to detect histiocytes, as well as several clones of lymphocytes and Langerhans cells (antigen presenting cells of skin), CD 117, toluidin blue and chloracetase esterase to detect mastocytes and neutrophils. Material was tested by immunofluorescent methods to detect IgA, IgM, IgG, C3, C4, albumin and fibrinogen. Representative view-fields were documented by microscope photocamera Leica DFC 420 C. Registered photos from both samples of the skin were processed by morphometrical analysis by the Vision Assistant software. A student t-test was used for statistical analysis of reached results. Mean values of individual found cells in the sample with lesion and without lesion were as follows: CD117 -2.64/0.37, CD68-6.86/1.63, CD163-3.13/2.23, CD30-1.36/0.02, CD4-3.51/0.32, CD8-8.22/0.50, CD3-10.69/0.66, CD20-0.56/0.66, CD1a-7.97/0.47 respectively. Generally mild elevation of eosinofils in lesional skin was detected. Increased values of tested cells seen in excision from lesional skin when compared with nonlesional ones were statistically significant in eight case at the level p = 0.033 to 0.001. A not statistically significant difference was found only in the group of CD163+ histiocytes. Authors detected numbers of inflammatory cells in lesional skin after the stinging by a jellyfish and compared them with the numbers of cells in the nonlesional skin of the same patient. Statistically significant differences were seen in the level of selected inflammation cells and numerically documented changes of cellularity in the inflammatory focus were caused by a hypersensitivity reaction after jellyfish injury in the period of 10 days after attack.

Development and psychometric testing of the 'Motivation and Self-Efficacy in Early Detection of Skin Lesions' index.

PubMed

Dyson, Judith; Cowdell, Fiona

2014-12-01

To develop and psychometrically test the Motivation and Self-Efficacy in Early Detection of Skin Lesions Index. Skin cancer is the most frequently diagnosed cancer worldwide. The primary strategy used to prevent skin cancer is promotion of sun avoidance and the use of sun protection. However, despite costly and extensive campaigns, cases of skin cancer continue to increase. If found and treated early, skin cancer is curable. Early detection is, therefore, very important. The study was conducted in 2013. Instrument Development. A literature review and a survey identified barriers (factors that hinder) and levers (factors that help) to skin self-examination. These were categorized according to a the Theoretical Domains Framework and this formed the basis of an instrument, which was tested for validity and reliability using confirmatory factor analysis and Cronbach's alpha respectively. A five-factor 20-item instrument was used that tested well for reliability and construct validity. Test-retest reliability was good for all items and domains. The five factors were: (i) Outcome expectancies; (ii) Intention; (iii) Self-efficacy; (iv) Social influences; (v) Memory. The Motivation and Self-Efficacy in Early Detection of Skin Lesions Index provides a reliable and valid method of assessing barriers and levers to skin self-examination. The next step is to design a theory-based intervention that can be tailored according to individual determinants to behaviour change identified by this instrument. © 2014 John Wiley & Sons Ltd.

Nevirapine bioactivation and covalent binding in the skin.

PubMed

Sharma, Amy M; Klarskov, Klaus; Uetrecht, Jack

2013-03-18

Nevirapine (NVP) treatment is associated with serious skin rashes that appear to be immune-mediated. We previously developed a rat model of this skin rash that is immune-mediated and is very similar to the rash in humans. Treatment of rats with the major NVP metabolite, 12-OH-NVP, also caused the rash. Most idiosyncratic drug reactions are caused by reactive metabolites; 12-OH-NVP forms a benzylic sulfate, which was detected in the blood of animals treated with NVP or 12-OH-NVP. This sulfate is presumably formed in the liver; however, the skin also has significant sulfotransferase activity. In this study, we used a serum against NVP to detect covalent binding in the skin of rats. There was a large artifact band in immunoblots of whole skin homogenates that interfered with detection of covalent binding; however, when the skin was separated into dermal and epidermal fractions, covalent binding was clearly present in the epidermis, which is also the location of sulfotransferases. In contrast to rats, treatment of mice with NVP did not result in covalent binding in the skin or skin rash. Although the reaction of 12-OH-NVP sulfate with nucleophiles such as glutathione is slow, incubation of this sulfate with homogenized human and rat skin led to extensive covalent binding. Incubations of 12-OH-NVP with the soluble fraction from a 9,000g centrifugation (S9) of rat or human skin homogenate in the presence of 3'-phosphoadenosine-5'-phosphosulfate (PAPS) produced extensive covalent binding, but no covalent binding was detected with mouse skin S9, which suggests that the reason mice do not develop a rash is that they lack the required sulfotransferase. This is the first study to report covalent binding of NVP to rat and human skin. These data provide strong evidence that covalent binding of NVP in the skin is due to 12-OH-NVP sulfate, which is likely responsible for NVP-induced skin rash. Sulfation may represent a bioactivation pathway for other drugs that cause a skin rash.

Comprehensive eye evaluation algorithm

NASA Astrophysics Data System (ADS)

Agurto, C.; Nemeth, S.; Zamora, G.; Vahtel, M.; Soliz, P.; Barriga, S.

2016-03-01

In recent years, several research groups have developed automatic algorithms to detect diabetic retinopathy (DR) in individuals with diabetes (DM), using digital retinal images. Studies have indicated that diabetics have 1.5 times the annual risk of developing primary open angle glaucoma (POAG) as do people without DM. Moreover, DM patients have 1.8 times the risk for age-related macular degeneration (AMD). Although numerous investigators are developing automatic DR detection algorithms, there have been few successful efforts to create an automatic algorithm that can detect other ocular diseases, such as POAG and AMD. Consequently, our aim in the current study was to develop a comprehensive eye evaluation algorithm that not only detects DR in retinal images, but also automatically identifies glaucoma suspects and AMD by integrating other personal medical information with the retinal features. The proposed system is fully automatic and provides the likelihood of each of the three eye disease. The system was evaluated in two datasets of 104 and 88 diabetic cases. For each eye, we used two non-mydriatic digital color fundus photographs (macula and optic disc centered) and, when available, information about age, duration of diabetes, cataracts, hypertension, gender, and laboratory data. Our results show that the combination of multimodal features can increase the AUC by up to 5%, 7%, and 8% in the detection of AMD, DR, and glaucoma respectively. Marked improvement was achieved when laboratory results were combined with retinal image features.

SkinScan©: A PORTABLE LIBRARY FOR MELANOMA DETECTION ON HANDHELD DEVICES

PubMed Central

Wadhawan, Tarun; Situ, Ning; Lancaster, Keith; Yuan, Xiaojing; Zouridakis, George

2011-01-01

We have developed a portable library for automated detection of melanoma termed SkinScan© that can be used on smartphones and other handheld devices. Compared to desktop computers, embedded processors have limited processing speed, memory, and power, but they have the advantage of portability and low cost. In this study we explored the feasibility of running a sophisticated application for automated skin cancer detection on an Apple iPhone 4. Our results demonstrate that the proposed library with the advanced image processing and analysis algorithms has excellent performance on handheld and desktop computers. Therefore, deployment of smartphones as screening devices for skin cancer and other skin diseases can have a significant impact on health care delivery in underserved and remote areas. PMID:21892382

Detection of canine skin and subcutaneous tumors by visible and near-infrared diffuse reflectance spectroscopy

NASA Astrophysics Data System (ADS)

Cugmas, Blaž; Plavec, Tanja; Bregar, Maksimilijan; Naglič, Peter; Pernuš, Franjo; Likar, Boštjan; Bürmen, Miran

2015-03-01

Cancer is the main cause of canine morbidity and mortality. The existing evaluation of tumors requires an experienced veterinarian and usually includes invasive procedures (e.g., fine-needle aspiration) that can be unpleasant for the dog and the owner. We investigate visible and near-infrared diffuse reflectance spectroscopy (DRS) as a noninvasive optical technique for evaluation and detection of canine skin and subcutaneous tumors ex vivo and in vivo. The optical properties of tumors and skin were calculated in a spectrally constrained manner, using a lookup table-based inverse model. The obtained optical properties were analyzed and compared among different tumor groups. The calculated parameters of the absorption and reduced scattering coefficients were subsequently used for detection of malignant skin and subcutaneous tumors. The detection sensitivity and specificity of malignant tumors ex vivo were 90.0% and 73.5%, respectively, while corresponding detection sensitivity and specificity of malignant tumors in vivo were 88.4% and 54.6%, respectively. The obtained results show that the DRS is a promising noninvasive optical technique for detection and classification of malignant and benign canine skin and subcutaneous tumors. The method should be further investigated on tumors with common origin.

Obscenity Detection Using Haar-Like Features and Gentle Adaboost Classifier

PubMed Central

Min, Yang; Zhu, Dingju

2014-01-01

Large exposure of skin area of an image is considered obscene. This only fact may lead to many false images having skin-like objects and may not detect those images which have partially exposed skin area but have exposed erotogenic human body parts. This paper presents a novel method for detecting nipples from pornographic image contents. Nipple is considered as an erotogenic organ to identify pornographic contents from images. In this research Gentle Adaboost (GAB) haar-cascade classifier and haar-like features used for ensuring detection accuracy. Skin filter prior to detection made the system more robust. The experiment showed that, considering accuracy, haar-cascade classifier performs well, but in order to satisfy detection time, train-cascade classifier is suitable. To validate the results, we used 1198 positive samples containing nipple objects and 1995 negative images. The detection rates for haar-cascade and train-cascade classifiers are 0.9875 and 0.8429, respectively. The detection time for haar-cascade is 0.162 seconds and is 0.127 seconds for train-cascade classifier. PMID:25003153

Improved wheal detection from skin prick test images

NASA Astrophysics Data System (ADS)

Bulan, Orhan

2014-03-01

Skin prick test is a commonly used method for diagnosis of allergic diseases (e.g., pollen allergy, food allergy, etc.) in allergy clinics. The results of this test are erythema and wheal provoked on the skin where the test is applied. The sensitivity of the patient against a specific allergen is determined by the physical size of the wheal, which can be estimated from images captured by digital cameras. Accurate wheal detection from these images is an important step for precise estimation of wheal size. In this paper, we propose a method for improved wheal detection on prick test images captured by digital cameras. Our method operates by first localizing the test region by detecting calibration marks drawn on the skin. The luminance variation across the localized region is eliminated by applying a color transformation from RGB to YCbCr and discarding the luminance channel. We enhance the contrast of the captured images for the purpose of wheal detection by performing principal component analysis on the blue-difference (Cb) and red-difference (Cr) color channels. We finally, perform morphological operations on the contrast enhanced image to detect the wheal on the image plane. Our experiments performed on images acquired from 36 different patients show the efficiency of the proposed method for wheal detection from skin prick test images captured in an uncontrolled environment.

Enhancement of breast periphery region in digital mammography

NASA Astrophysics Data System (ADS)

Menegatti Pavan, Ana Luiza; Vacavant, Antoine; Petean Trindade, Andre; Quini, Caio Cesar; Rodrigues de Pina, Diana

2018-03-01

Volumetric breast density has been shown to be one of the strongest risk factor for breast cancer diagnosis. This metric can be estimated using digital mammograms. During mammography acquisition, breast is compressed and part of it loses contact with the paddle, resulting in an uncompressed region in periphery with thickness variation. Therefore, reliable density estimation in the breast periphery region is a problem, which affects the accuracy of volumetric breast density measurement. The aim of this study was to enhance breast periphery to solve the problem of thickness variation. Herein, we present an automatic algorithm to correct breast periphery thickness without changing pixel value from internal breast region. The correction pixel values from periphery was based on mean values over iso-distance lines from the breast skin-line using only adipose tissue information. The algorithm detects automatically the periphery region where thickness should be corrected. A correction factor was applied in breast periphery image to enhance the region. We also compare our contribution with two other algorithms from state-of-the-art, and we show its accuracy by means of different quality measures. Experienced radiologists subjectively evaluated resulting images from the tree methods in relation to original mammogram. The mean pixel value, skewness and kurtosis from histogram of the three methods were used as comparison metric. As a result, the methodology presented herein showed to be a good approach to be performed before calculating volumetric breast density.

Abrupt skin lesion border cutoff measurement for malignancy detection in dermoscopy images.

PubMed

Kaya, Sertan; Bayraktar, Mustafa; Kockara, Sinan; Mete, Mutlu; Halic, Tansel; Field, Halle E; Wong, Henry K

2016-10-06

Automated skin lesion border examination and analysis techniques have become an important field of research for distinguishing malignant pigmented lesions from benign lesions. An abrupt pigment pattern cutoff at the periphery of a skin lesion is one of the most important dermoscopic features for detection of neoplastic behavior. In current clinical setting, the lesion is divided into a virtual pie with eight sections. Each section is examined by a dermatologist for abrupt cutoff and scored accordingly, which can be tedious and subjective. This study introduces a novel approach to objectively quantify abruptness of pigment patterns along the lesion periphery. In the proposed approach, first, the skin lesion border is detected by the density based lesion border detection method. Second, the detected border is gradually scaled through vector operations. Then, along gradually scaled borders, pigment pattern homogeneities are calculated at different scales. Through this process, statistical texture features are extracted. Moreover, different color spaces are examined for the efficacy of texture analysis. The proposed method has been tested and validated on 100 (31 melanoma, 69 benign) dermoscopy images. Analyzed results indicate that proposed method is efficient on malignancy detection. More specifically, we obtained specificity of 0.96 and sensitivity of 0.86 for malignancy detection in a certain color space. The F-measure, harmonic mean of recall and precision, of the framework is reported as 0.87. The use of texture homogeneity along the periphery of the lesion border is an effective method to detect malignancy of the skin lesion in dermoscopy images. Among different color spaces tested, RGB color space's blue color channel is the most informative color channel to detect malignancy for skin lesions. That is followed by YCbCr color spaces Cr channel, and Cr is closely followed by the green color channel of RGB color space.

46 CFR 76.33-20 - Operation and installation.

Code of Federal Regulations, 2011 CFR

2011-10-01

... EQUIPMENT Smoke Detecting System, Details § 76.33-20 Operation and installation. (a) The system shall be so arranged and installed that the presence of smoke in any of the protected spaces will automatically be... automatically indicate the zone in which the smoke originated. The detecting cabinet shall normally be located...

46 CFR 76.33-20 - Operation and installation.

Code of Federal Regulations, 2014 CFR

2014-10-01

... EQUIPMENT Smoke Detecting System, Details § 76.33-20 Operation and installation. (a) The system shall be so arranged and installed that the presence of smoke in any of the protected spaces will automatically be... automatically indicate the zone in which the smoke originated. The detecting cabinet shall normally be located...

46 CFR 76.33-20 - Operation and installation.

Code of Federal Regulations, 2012 CFR

2012-10-01

... EQUIPMENT Smoke Detecting System, Details § 76.33-20 Operation and installation. (a) The system shall be so arranged and installed that the presence of smoke in any of the protected spaces will automatically be... automatically indicate the zone in which the smoke originated. The detecting cabinet shall normally be located...

46 CFR 76.33-20 - Operation and installation.

Code of Federal Regulations, 2013 CFR

2013-10-01

... EQUIPMENT Smoke Detecting System, Details § 76.33-20 Operation and installation. (a) The system shall be so arranged and installed that the presence of smoke in any of the protected spaces will automatically be... automatically indicate the zone in which the smoke originated. The detecting cabinet shall normally be located...

Automatic Conceptual Encoding of Printed Verbal Material: Assessment of Population Differences.

ERIC Educational Resources Information Center

Kee, Daniel W.; And Others

1984-01-01

The release from proactive interference task as used to investigate categorical encoding of items. Low socioeconomic status Black and middle socioeconomic status White children were compared. Conceptual encoding differences between these populations were not detected in automatic conceptual encoding but were detected when the free recall method…

Noninvasive detection of cardiovascular pulsations by optical Doppler techniques

NASA Astrophysics Data System (ADS)

Hong, HyunDae; Fox, Martin D.

1997-10-01

A system has been developed based on the measurement of skin surface vibration that can be used to detect the underlying vascular wall motion of superficial arteries and the chest wall. Data obtained from tissue phantoms suggested that the detected signals were related to intravascular pressure, an important clinical and physiological parameter. Unlike the conventional optical Doppler techniques that have been used to measure blood perfusion in skin layers and blood flow within superficial arteries, the present system was optimized to pick up skin vibrations. An optical interferometer with a 633-nm He:Ne laser was utilized to detect micrometer displacements of the skin surface. Motion velocity profiles of the skin surface near each superficial artery and auscultation points on a chest for the two heart valve sounds exhibited distinctive profiles. The theoretical and experimental results demonstrated that the system detected the velocity of skin movement, which is related to the time derivative of the pressure. The system also reduces the loading effect on the pulsation signals and heart sounds produced by the conventional piezoelectric vibration sensors. The system's sensitivity, which could be optimized further, was 366.2 micrometers /s for the present research. Overall, optical cardiovascular vibrometry has the potential to become a simple noninvasive approach to cardiovascular screening.

Effect of skin-transmitted vibration enhancement on vibrotactile perception.

PubMed

Tanaka, Yoshihiro; Ueda, Yuichiro; Sano, Akihito

2015-06-01

Vibration on skin elicited by the mechanical interaction of touch between the skin and an object propagates to skin far from the point of contact. This paper investigates the effect of skin-transmitted vibration on vibrotactile perception. To enhance the transmission of high-frequency vibration on the skin, stiff tape was attached to the skin so that the tape covered the bottom surface of the index finger from the periphery of the distal interphalangeal joint to the metacarpophalangeal joint. Two psychophysical experiments with high-frequency vibrotactile stimuli of 250 Hz were conducted. In the psychophysical experiments, discrimination and detection thresholds were estimated and compared between conditions of the presence or the absence of the tape (normal bare finger). A method of limits was applied for the detection threshold estimation, and the discrimination task using a reference stimulus and six test stimuli with different amplitudes was applied for the discrimination threshold estimation. The stimulation was given to bare fingertips of participants. Result showed that the detection threshold was enhanced by attaching the tape, and the discrimination threshold enhancement by attaching the tape was confirmed for participants who have relatively large discrimination threshold under normal bare finger. Then, skin-transmitted vibration was measured with an accelerometer with the psychophysical experiments. Result showed that the skin-transmitted vibration when the tape was attached to the skin was larger than that when normal bare skin. There is a correlation between the increase in skin-transmitted vibration and the enhancement of the discrimination threshold.

Skin Cancer Screening (PDQ®)—Patient Version

Cancer.gov

Having a skin exam to screen for skin cancer has not been shown to decrease your chance of dying from skin cancer. Learn about this and other tests that have been studied to detect or screen for skin cancer in this expert reviewed summary.

Automatic lumbar vertebrae detection based on feature fusion deep learning for partial occluded C-arm X-ray images.

PubMed

Yang Li; Wei Liang; Yinlong Zhang; Haibo An; Jindong Tan

2016-08-01

Automatic and accurate lumbar vertebrae detection is an essential step of image-guided minimally invasive spine surgery (IG-MISS). However, traditional methods still require human intervention due to the similarity of vertebrae, abnormal pathological conditions and uncertain imaging angle. In this paper, we present a novel convolutional neural network (CNN) model to automatically detect lumbar vertebrae for C-arm X-ray images. Training data is augmented by DRR and automatic segmentation of ROI is able to reduce the computational complexity. Furthermore, a feature fusion deep learning (FFDL) model is introduced to combine two types of features of lumbar vertebrae X-ray images, which uses sobel kernel and Gabor kernel to obtain the contour and texture of lumbar vertebrae, respectively. Comprehensive qualitative and quantitative experiments demonstrate that our proposed model performs more accurate in abnormal cases with pathologies and surgical implants in multi-angle views.

Automatic textual annotation of video news based on semantic visual object extraction

NASA Astrophysics Data System (ADS)

Boujemaa, Nozha; Fleuret, Francois; Gouet, Valerie; Sahbi, Hichem

2003-12-01

In this paper, we present our work for automatic generation of textual metadata based on visual content analysis of video news. We present two methods for semantic object detection and recognition from a cross modal image-text thesaurus. These thesaurus represent a supervised association between models and semantic labels. This paper is concerned with two semantic objects: faces and Tv logos. In the first part, we present our work for efficient face detection and recogniton with automatic name generation. This method allows us also to suggest the textual annotation of shots close-up estimation. On the other hand, we were interested to automatically detect and recognize different Tv logos present on incoming different news from different Tv Channels. This work was done jointly with the French Tv Channel TF1 within the "MediaWorks" project that consists on an hybrid text-image indexing and retrieval plateform for video news.

Identification of Borrelia protein candidates in mouse skin for potential diagnosis of disseminated Lyme borreliosis.

PubMed

Grillon, Antoine; Westermann, Benoît; Cantero, Paola; Jaulhac, Benoît; Voordouw, Maarten J; Kapps, Delphine; Collin, Elody; Barthel, Cathy; Ehret-Sabatier, Laurence; Boulanger, Nathalie

2017-12-01

In vector-borne diseases, the skin plays an essential role in the transmission of vector-borne pathogens between the vertebrate host and blood-feeding arthropods and in pathogen persistence. Borrelia burgdorferi sensu lato is a tick-borne bacterium that causes Lyme borreliosis (LB) in humans. This pathogen may establish a long-lasting infection in its natural vertebrate host where it can persist in the skin and some other organs. Using a mouse model, we demonstrate that Borrelia targets the skin regardless of the route of inoculation, and can persist there at low densities that are difficult to detect via qPCR, but that were infective for blood-feeding ticks. Application of immunosuppressive dermocorticoids at 40 days post-infection (PI) significantly enhanced the Borrelia population size in the mouse skin. We used non-targeted (Ge-LC-MS/MS) and targeted (SRM-MS) proteomics to detect several Borrelia-specific proteins in the mouse skin at 40 days PI. Detected Borrelia proteins included flagellin, VlsE and GAPDH. An important problem in LB is the lack of diagnosis methods capable of detecting active infection in humans suffering from disseminated LB. The identification of Borrelia proteins in skin biopsies may provide new approaches for assessing active infection in disseminated manifestations.

Detection of follicular transport of lidocaine and metabolism in adipose tissue in pig ear skin by DESI mass spectrometry imaging.

PubMed

D'Alvise, Janina; Mortensen, Rasmus; Hansen, Steen H; Janfelt, Christian

2014-06-01

Desorption electrospray ionization (DESI) mass spectrometry imaging is demonstrated as a detection technique for penetration experiments of drugs in skin. Lidocaine ointment was used as the model compound in ex vivo experiments with whole pig ears as the skin model. Follicular transport of lidocaine into the deeper skin layers is demonstrated for the first time. Furthermore, metabolism of lidocaine to 3-OH-lidocaine was observed in subcutaneous tissue as well as in lobules of white adipose tissue surrounding the hair follicles. These results suggest that it is advantageous to use full thickness skin, including subcutaneous tissue, for skin metabolism studies.

MRI-alone radiation therapy planning for prostate cancer: Automatic fiducial marker detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ghose, Soumya, E-mail: soumya.ghose@case.edu; Mitra, Jhimli; Rivest-Hénault, David

Purpose: The feasibility of radiation therapy treatment planning using substitute computed tomography (sCT) generated from magnetic resonance images (MRIs) has been demonstrated by a number of research groups. One challenge with an MRI-alone workflow is the accurate identification of intraprostatic gold fiducial markers, which are frequently used for prostate localization prior to each dose delivery fraction. This paper investigates a template-matching approach for the detection of these seeds in MRI. Methods: Two different gradient echo T1 and T2* weighted MRI sequences were acquired from fifteen prostate cancer patients and evaluated for seed detection. For training, seed templates from manual contoursmore » were selected in a spectral clustering manifold learning framework. This aids in clustering “similar” gold fiducial markers together. The marker with the minimum distance to a cluster centroid was selected as the representative template of that cluster during training. During testing, Gaussian mixture modeling followed by a Markovian model was used in automatic detection of the probable candidates. The probable candidates were rigidly registered to the templates identified from spectral clustering, and a similarity metric is computed for ranking and detection. Results: A fiducial detection accuracy of 95% was obtained compared to manual observations. Expert radiation therapist observers were able to correctly identify all three implanted seeds on 11 of the 15 scans (the proposed method correctly identified all seeds on 10 of the 15). Conclusions: An novel automatic framework for gold fiducial marker detection in MRI is proposed and evaluated with detection accuracies comparable to manual detection. When radiation therapists are unable to determine the seed location in MRI, they refer back to the planning CT (only available in the existing clinical framework); similarly, an automatic quality control is built into the automatic software to ensure that all gold seeds are either correctly detected or a warning is raised for further manual intervention.« less

MRI-alone radiation therapy planning for prostate cancer: Automatic fiducial marker detection.

PubMed

Ghose, Soumya; Mitra, Jhimli; Rivest-Hénault, David; Fazlollahi, Amir; Stanwell, Peter; Pichler, Peter; Sun, Jidi; Fripp, Jurgen; Greer, Peter B; Dowling, Jason A

2016-05-01

The feasibility of radiation therapy treatment planning using substitute computed tomography (sCT) generated from magnetic resonance images (MRIs) has been demonstrated by a number of research groups. One challenge with an MRI-alone workflow is the accurate identification of intraprostatic gold fiducial markers, which are frequently used for prostate localization prior to each dose delivery fraction. This paper investigates a template-matching approach for the detection of these seeds in MRI. Two different gradient echo T1 and T2* weighted MRI sequences were acquired from fifteen prostate cancer patients and evaluated for seed detection. For training, seed templates from manual contours were selected in a spectral clustering manifold learning framework. This aids in clustering "similar" gold fiducial markers together. The marker with the minimum distance to a cluster centroid was selected as the representative template of that cluster during training. During testing, Gaussian mixture modeling followed by a Markovian model was used in automatic detection of the probable candidates. The probable candidates were rigidly registered to the templates identified from spectral clustering, and a similarity metric is computed for ranking and detection. A fiducial detection accuracy of 95% was obtained compared to manual observations. Expert radiation therapist observers were able to correctly identify all three implanted seeds on 11 of the 15 scans (the proposed method correctly identified all seeds on 10 of the 15). An novel automatic framework for gold fiducial marker detection in MRI is proposed and evaluated with detection accuracies comparable to manual detection. When radiation therapists are unable to determine the seed location in MRI, they refer back to the planning CT (only available in the existing clinical framework); similarly, an automatic quality control is built into the automatic software to ensure that all gold seeds are either correctly detected or a warning is raised for further manual intervention.

46 CFR 76.05-1 - Fire detecting systems.

Code of Federal Regulations, 2010 CFR

2010-10-01

... fitted with an automatic sprinkling system, except in relatively incombustible spaces. 2 Sprinkler heads....1 Offices, lockers, and isolated storerooms Electric, pneumatic, or automatic sprinkling1 Do.1 Public spaces None required with 20-minute patrol. Electric, pneumatic, or automatic sprinkling with 1...

46 CFR 76.05-1 - Fire detecting systems.

Code of Federal Regulations, 2011 CFR

2011-10-01

... fitted with an automatic sprinkling system, except in relatively incombustible spaces. 2 Sprinkler heads....1 Offices, lockers, and isolated storerooms Electric, pneumatic, or automatic sprinkling1 Do.1 Public spaces None required with 20-minute patrol. Electric, pneumatic, or automatic sprinkling with 1...

Automatic detection of small surface targets with electro-optical sensors in a harbor environment

NASA Astrophysics Data System (ADS)

Bouma, Henri; de Lange, Dirk-Jan J.; van den Broek, Sebastiaan P.; Kemp, Rob A. W.; Schwering, Piet B. W.

2008-10-01

In modern warfare scenarios naval ships must operate in coastal environments. These complex environments, in bays and narrow straits, with cluttered littoral backgrounds and many civilian ships may contain asymmetric threats of fast targets, such as rhibs, cabin boats and jet-skis. Optical sensors, in combination with image enhancement and automatic detection, assist an operator to reduce the response time, which is crucial for the protection of the naval and land-based supporting forces. In this paper, we present our work on automatic detection of small surface targets which includes multi-scale horizon detection and robust estimation of the background intensity. To evaluate the performance of our detection technology, data was recorded with both infrared and visual-light cameras in a coastal zone and in a harbor environment. During these trials multiple small targets were used. Results of this evaluation are shown in this paper.

An effective hair detection algorithm for dermoscopic melanoma images of skin lesions

NASA Astrophysics Data System (ADS)

Chakraborti, Damayanti; Kaur, Ravneet; Umbaugh, Scott; LeAnder, Robert

2016-09-01

Dermoscopic images are obtained using the method of skin surface microscopy. Pigmented skin lesions are evaluated in terms of texture features such as color and structure. Artifacts, such as hairs, bubbles, black frames, ruler-marks, etc., create obstacles that prevent accurate detection of skin lesions by both clinicians and computer-aided diagnosis. In this article, we propose a new algorithm for the automated detection of hairs, using an adaptive, Canny edge-detection method, followed by morphological filtering and an arithmetic addition operation. The algorithm was applied to 50 dermoscopic melanoma images. In order to ascertain this method's relative detection accuracy, it was compared to the Razmjooy hair-detection method [1], using segmentation error (SE), true detection rate (TDR) and false positioning rate (FPR). The new method produced 6.57% SE, 96.28% TDR and 3.47% FPR, compared to 15.751% SE, 86.29% TDR and 11.74% FPR produced by the Razmjooy method [1]. Because of the 7.27-9.99% improvement in those parameters, we conclude that the new algorithm produces much better results for detecting thick, thin, dark and light hairs. The new method proposed here, shows an appreciable difference in the rate of detecting bubbles, as well.

Use of an automatic resistivity system for detecting abandoned mine workings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peters, W.R.; Burdick, R.G.

1983-01-01

A high-resolution earth resistivity system has been designed and constructed for use as a means of detecting abandoned coal mine workings. The automatic pole-dipole earth resistivity technique has already been applied to the detection of subsurface voids for military applications. The hardware and software of the system are described, together with applications for surveying and mapping abandoned coal mine workings. Field tests are presented to illustrate the detection of both air-filled and water-filled mine workings.

An image-based approach for automatic detecting five true-leaves stage of cotton

NASA Astrophysics Data System (ADS)

Li, Yanan; Cao, Zhiguo; Wu, Xi; Yu, Zhenghong; Wang, Yu; Bai, Xiaodong

2013-10-01

Cotton, as one of the four major economic crops, is of great significance to the development of the national economy. Monitoring cotton growth status by automatic image-based detection makes sense due to its low-cost, low-labor and the capability of continuous observations. However, little research has been done to improve close observation of different growth stages of field crops using digital cameras. Therefore, algorithms proposed by us were developed to detect the growth information and predict the starting date of cotton automatically. In this paper, we introduce an approach for automatic detecting five true-leaves stage, which is a critical growth stage of cotton. On account of the drawbacks caused by illumination and the complex background, we cannot use the global coverage as the unique standard of judgment. Consequently, we propose a new method to determine the five true-leaves stage through detecting the node number between the main stem and the side stems, based on the agricultural meteorological observation specification. The error of the results between the predicted starting date with the proposed algorithm and artificial observations is restricted to no more than one day.

Precision Targeting With a Tracking Adaptive Optics Scanning Laser Ophthalmoscope

DTIC Science & Technology

2006-01-01

automatic high- resolution mosaic generation, and automatic blink detection and tracking re-lock were also tested. The system has the potential to become an...structures can lead to earlier detection of retinal diseases such as age-related macular degeneration (AMD) and diabetic retinopathy (DR). Combined...optics systems sense perturbations in the detected wave-front and apply corrections to an optical element that flatten the wave-front and allow near

Director, Operational Test and Evaluation FY 2004 Annual Report

DTIC Science & Technology

2004-01-01

HIGH) Space Based Radar (SBR) Sensor Fuzed Weapon (SFW) P3I (CBU-97/B) Small Diameter Bomb (SDB) Secure Mobile Anti-Jam Reliable Tactical Terminal...detection, identification, and sampling capability for both fixed-site and mobile operations. The system must automatically detect and identify up to ten...staffing within the Services. SYSTEM DESCRIPTION AND MISSION The Services envision JCAD as a hand-held device that automatically detects, identifies, and

Skin Cancer Concerns in People of Color: Risk Factors and Prevention

PubMed Central

Gupta, Alpana K; Bharadwaj, Mausumi; Mehrotra, Ravi

2016-01-01

Background: Though people of color (POC) are less likely to become afflicted with skin cancer, they are much more likely to die from it due to delay in detection or presentation. Very often, skin cancer is diagnosed at a more advanced stage in POC, making treatment difficult. The purpose of this research was to improve awareness regarding skin cancers in people of color by providing recommendations to clinicians and the general public for early detection and photo protection preventive measures. Methods: Data on different types of skin cancers were presented to POC. Due to limited research, there are few resources providing insights for evaluating darkly pigmented lesions in POC. Diagnostic features for different types of skin cancers were recorded and various possible risk factors were considered. Results: This study provided directions for the prevention and early detection of skin cancer in POC based on a comprehensive review of available data. Conclusions: The increased morbidity and mortality rate associated with skin cancer in POC is due to lack of awareness, diagnosis at a more advanced stage and socioeconomic barriers hindering access to care. Raising public health concerns for skin cancer prevention strategies for all people, regardless of ethnic background and socioeconomic status, is the key to timely diagnosis and treatment. PMID:28125871

Untreated Peristomal Skin Complications among Long-Term Colorectal Cancer Survivors with Ostomies: Lessons from a Study of Family Caregiving

PubMed Central

McMullen, Carmit K.; Wasserman, Joseph; Altschuler, Andrea; Grant, Marcia; Hornbrook, Mark C.; Liljestrand, Petra; Briggs, Catherine; Krouse, Robert S.

2013-01-01

This ethnography of family caregiving explored why peristomal skin complications are both common and undertreated among colorectal cancer (CRC) survivors with intestinal ostomies. We sought to identify factors that hinder or facilitate prompt detection and treatment of ostomy and skin problems. We collected data through in-depth interviews with 31 cancer survivors and their family caregivers, fieldwork, structured assessments, and medical records review. We analyzed data using qualitative theme and matrix analyses. We found that survivors who received help changing the skin barrier around their stoma had fewer obstacles to detection and treatment of peristomal skin complications. Half of the survivors received unpaid help with ostomy care. All such help came from spouses. Married couples who collaborated in ostomy care reported that having assistance in placing the ostomy appliance helped with preventing leaks, detecting skin changes, and modifying ostomy care routines. Survivors who struggled to manage ostomy care independently reported more obstacles to alleviating and seeking treatment for skin problems. Nurses who encounter CRC survivors with ostomies can improve treatment of peristomal skin problems by asking patients and caregivers about ostomy care and skin problems, examining the peristomal area, and facilitating routine checkups with a wound, ostomy and continence nurse. PMID:22119975

Toward comprehensive detection of sight threatening retinal disease using a multiscale AM-FM methodology

NASA Astrophysics Data System (ADS)

Agurto, C.; Barriga, S.; Murray, V.; Murillo, S.; Zamora, G.; Bauman, W.; Pattichis, M.; Soliz, P.

2011-03-01

In the United States and most of the western world, the leading causes of vision impairment and blindness are age-related macular degeneration (AMD), diabetic retinopathy (DR), and glaucoma. In the last decade, research in automatic detection of retinal lesions associated with eye diseases has produced several automatic systems for detection and screening of AMD, DR, and glaucoma. However. advanced, sight-threatening stages of DR and AMD can present with lesions not commonly addressed by current approaches to automatic screening. In this paper we present an automatic eye screening system based on multiscale Amplitude Modulation-Frequency Modulation (AM-FM) decompositions that addresses not only the early stages, but also advanced stages of retinal and optic nerve disease. Ten different experiments were performed in which abnormal features such as neovascularization, drusen, exudates, pigmentation abnormalities, geographic atrophy (GA), and glaucoma were classified. The algorithm achieved an accuracy detection range of [0.77 to 0.98] area under the ROC curve for a set of 810 images. When set to a specificity value of 0.60, the sensitivity of the algorithm to the detection of abnormal features ranged between 0.88 and 1.00. Our system demonstrates that, given an appropriate training set, it is possible to use a unique algorithm to detect a broad range of eye diseases.

Adaptive Self-Tuning Networks

NASA Astrophysics Data System (ADS)

Knox, H. A.; Draelos, T.; Young, C. J.; Lawry, B.; Chael, E. P.; Faust, A.; Peterson, M. G.

2015-12-01

The quality of automatic detections from seismic sensor networks depends on a large number of data processing parameters that interact in complex ways. The largely manual process of identifying effective parameters is painstaking and does not guarantee that the resulting controls are the optimal configuration settings. Yet, achieving superior automatic detection of seismic events is closely related to these parameters. We present an automated sensor tuning (AST) system that learns near-optimal parameter settings for each event type using neuro-dynamic programming (reinforcement learning) trained with historic data. AST learns to test the raw signal against all event-settings and automatically self-tunes to an emerging event in real-time. The overall goal is to reduce the number of missed legitimate event detections and the number of false event detections. Reducing false alarms early in the seismic pipeline processing will have a significant impact on this goal. Applicable both for existing sensor performance boosting and new sensor deployment, this system provides an important new method to automatically tune complex remote sensing systems. Systems tuned in this way will achieve better performance than is currently possible by manual tuning, and with much less time and effort devoted to the tuning process. With ground truth on detections in seismic waveforms from a network of stations, we show that AST increases the probability of detection while decreasing false alarms.

Robust Spacecraft Component Detection in Point Clouds.

PubMed

Wei, Quanmao; Jiang, Zhiguo; Zhang, Haopeng

2018-03-21

Automatic component detection of spacecraft can assist in on-orbit operation and space situational awareness. Spacecraft are generally composed of solar panels and cuboidal or cylindrical modules. These components can be simply represented by geometric primitives like plane, cuboid and cylinder. Based on this prior, we propose a robust automatic detection scheme to automatically detect such basic components of spacecraft in three-dimensional (3D) point clouds. In the proposed scheme, cylinders are first detected in the iteration of the energy-based geometric model fitting and cylinder parameter estimation. Then, planes are detected by Hough transform and further described as bounded patches with their minimum bounding rectangles. Finally, the cuboids are detected with pair-wise geometry relations from the detected patches. After successive detection of cylinders, planar patches and cuboids, a mid-level geometry representation of the spacecraft can be delivered. We tested the proposed component detection scheme on spacecraft 3D point clouds synthesized by computer-aided design (CAD) models and those recovered by image-based reconstruction, respectively. Experimental results illustrate that the proposed scheme can detect the basic geometric components effectively and has fine robustness against noise and point distribution density.

Robust Spacecraft Component Detection in Point Clouds

PubMed Central

Wei, Quanmao; Jiang, Zhiguo

2018-01-01

Automatic component detection of spacecraft can assist in on-orbit operation and space situational awareness. Spacecraft are generally composed of solar panels and cuboidal or cylindrical modules. These components can be simply represented by geometric primitives like plane, cuboid and cylinder. Based on this prior, we propose a robust automatic detection scheme to automatically detect such basic components of spacecraft in three-dimensional (3D) point clouds. In the proposed scheme, cylinders are first detected in the iteration of the energy-based geometric model fitting and cylinder parameter estimation. Then, planes are detected by Hough transform and further described as bounded patches with their minimum bounding rectangles. Finally, the cuboids are detected with pair-wise geometry relations from the detected patches. After successive detection of cylinders, planar patches and cuboids, a mid-level geometry representation of the spacecraft can be delivered. We tested the proposed component detection scheme on spacecraft 3D point clouds synthesized by computer-aided design (CAD) models and those recovered by image-based reconstruction, respectively. Experimental results illustrate that the proposed scheme can detect the basic geometric components effectively and has fine robustness against noise and point distribution density. PMID:29561828

In-flight automatic detection of vigilance states using a single EEG channel.

PubMed

Sauvet, F; Bougard, C; Coroenne, M; Lely, L; Van Beers, P; Elbaz, M; Guillard, M; Leger, D; Chennaoui, M

2014-12-01

Sleepiness and fatigue can reach particularly high levels during long-haul overnight flights. Under these conditions, voluntary or even involuntary sleep periods may occur, increasing the risk of accidents. The aim of this study was to assess the performance of an in-flight automatic detection system of low-vigilance states using a single electroencephalogram channel. Fourteen healthy pilots voluntarily wore a miniaturized brain electrical activity recording device during long-haul flights ( 10 ±2.0 h, Atlantic 2 and Falcon 50 M, French naval aviation). No subject was disturbed by the equipment. Seven pilots experienced at least a period of voluntary ( 26.8 ±8.0 min, n = 4) or involuntary sleep (N1 sleep stage, 26.6 ±18.7 s, n = 7) during the flight. Automatic classification (wake/sleep) by the algorithm was made for 10-s epochs (O1-M2 or C3-M2 channel), based on comparison of means to detect changes in α, β, and θ relative power, or ratio [( α+θ)/β], or fuzzy logic fusion (α, β). Pertinence and prognostic of the algorithm were determined using epoch-by-epoch comparison with visual-scoring (two blinded readers, AASM rules). The best concordance between automatic detection and visual-scoring was observed within the O1-M2 channel, using the ratio [( α+θ )/β] ( 98.3 ±4.1% of good detection, K = 0.94 ±0.07, with a 0.04 ±0.04 false positive rate and a 0.87 ±0.10 true positive rate). Our results confirm the efficiency of a miniaturized single electroencephalographic channel recording device, associated with an automatic detection algorithm, in order to detect low-vigilance states during real flights.

Automatic internal crack detection from a sequence of infrared images with a triple-threshold Canny edge detector

NASA Astrophysics Data System (ADS)

Wang, Gaochao; Tse, Peter W.; Yuan, Maodan

2018-02-01

Visual inspection and assessment of the condition of metal structures are essential for safety. Pulse thermography produces visible infrared images, which have been widely applied to detect and characterize defects in structures and materials. When active thermography, a non-destructive testing tool, is applied, the necessity of considerable manual checking can be avoided. However, detecting an internal crack with active thermography remains difficult, since it is usually invisible in the collected sequence of infrared images, which makes the automatic detection of internal cracks even harder. In addition, the detection of an internal crack can be hindered by a complicated inspection environment. With the purpose of putting forward a robust and automatic visual inspection method, a computer vision-based thresholding method is proposed. In this paper, the image signals are a sequence of infrared images collected from the experimental setup with a thermal camera and two flash lamps as stimulus. The contrast of pixels in each frame is enhanced by the Canny operator and then reconstructed by a triple-threshold system. Two features, mean value in the time domain and maximal amplitude in the frequency domain, are extracted from the reconstructed signal to help distinguish the crack pixels from others. Finally, a binary image indicating the location of the internal crack is generated by a K-means clustering method. The proposed procedure has been applied to an iron pipe, which contains two internal cracks and surface abrasion. Some improvements have been made for the computer vision-based automatic crack detection methods. In the future, the proposed method can be applied to realize the automatic detection of internal cracks from many infrared images for the industry.

Cost-Effectiveness Analysis of a Skin Awareness Intervention for Early Detection of Skin Cancer Targeting Men Older Than 50 Years.

PubMed

Gordon, Louisa G; Brynes, Joshua; Baade, Peter D; Neale, Rachel E; Whiteman, David C; Youl, Philippa H; Aitken, Joanne F; Janda, Monika

2017-04-01

To assess the cost-effectiveness of an educational intervention encouraging self-skin examinations for early detection of skin cancers among men older than 50 years. A lifetime Markov model was constructed to combine data from the Skin Awareness Trial and other published sources. The model incorporated a health system perspective and the cost and health outcomes for melanoma, squamous and basal cell carcinomas, and benign skin lesions. Key model outcomes included Australian costs (2015), quality-adjusted life-years (QALYs), life-years, and counts of skin cancers. Univariate and probabilistic sensitivity analyses were undertaken to address parameter uncertainty. The mean cost of the intervention was A$5,298 compared with A$4,684 for usual care, whereas mean QALYs were 7.58 for the intervention group and 7.77 for the usual care group. The intervention was thus inferior to usual care. When only survival gain is considered, the model predicted the intervention would cost A$1,059 per life-year saved. The likelihood that the intervention was cost-effective up to A$50,000 per QALY gained was 43.9%. The model was stable to most data estimates; nevertheless, it relies on the specificity of clinical diagnosis of skin cancers and is subject to limited health utility data for people with skin lesions. Although the intervention improved skin checking behaviors and encouraged men to seek medical advice about suspicious lesions, the overall costs and effects from also detecting more squamous and basal cell carcinomas and benign lesions outweighed the positive health gains from detecting more thin melanomas. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

[Early detection of occupational skin diseases in sewer workers].

PubMed

Lang, V; Lauffer, F; Fincan, Y; Biedermann, T; Zink, A

2018-04-25

Skin diseases affect 30-70% of the world population, and globally, skin cancer rates are continuously increasing. In this respect, prevention programs and early detection of skin diseases are of particular importance. To screen sewer workers for skin diseases with regard to their work-related risk. Employees of the municipal utilities in Munich (Münchner Stadtentwässerung) underwent a whole-body examination of the skin, conducted by two dermatologists. In addition, all employees completed a paper-based questionnaire on risk behavior and preventive measures. We examined 81 employees (79 men, 2 women, mean age 45.7 ± 9.5 years). Skin lesions in need of treatment were found in 30.9% (n = 25): the most frequent diagnosis was mycosis pedis (16.1%). In addition, one employee was diagnosed with basal cell carcinoma and two with actinic keratoses. According to the questionnaire, 43.5% of the employees had undergone a physician-led skin cancer screening in the past, whereas sun-protection practices were rarely applied. According to our findings, employee skin cancer screening seems to be beneficial for the detection of work-related skin diseases and is associated with a high participation rate. Furthermore, the study suggests that sewer workers have a high rate of mycosis pedis, possibly a work-related effect.

Accelerometer-based automatic voice onset detection in speech mapping with navigated repetitive transcranial magnetic stimulation.

PubMed

Vitikainen, Anne-Mari; Mäkelä, Elina; Lioumis, Pantelis; Jousmäki, Veikko; Mäkelä, Jyrki P

2015-09-30

The use of navigated repetitive transcranial magnetic stimulation (rTMS) in mapping of speech-related brain areas has recently shown to be useful in preoperative workflow of epilepsy and tumor patients. However, substantial inter- and intraobserver variability and non-optimal replicability of the rTMS results have been reported, and a need for additional development of the methodology is recognized. In TMS motor cortex mappings the evoked responses can be quantitatively monitored by electromyographic recordings; however, no such easily available setup exists for speech mappings. We present an accelerometer-based setup for detection of vocalization-related larynx vibrations combined with an automatic routine for voice onset detection for rTMS speech mapping applying naming. The results produced by the automatic routine were compared with the manually reviewed video-recordings. The new method was applied in the routine navigated rTMS speech mapping for 12 consecutive patients during preoperative workup for epilepsy or tumor surgery. The automatic routine correctly detected 96% of the voice onsets, resulting in 96% sensitivity and 71% specificity. Majority (63%) of the misdetections were related to visible throat movements, extra voices before the response, or delayed naming of the previous stimuli. The no-response errors were correctly detected in 88% of events. The proposed setup for automatic detection of voice onsets provides quantitative additional data for analysis of the rTMS-induced speech response modifications. The objectively defined speech response latencies increase the repeatability, reliability and stratification of the rTMS results. Copyright © 2015 Elsevier B.V. All rights reserved.

Quality assurance using outlier detection on an automatic segmentation method for the cerebellar peduncles

NASA Astrophysics Data System (ADS)

Li, Ke; Ye, Chuyang; Yang, Zhen; Carass, Aaron; Ying, Sarah H.; Prince, Jerry L.

2016-03-01

Cerebellar peduncles (CPs) are white matter tracts connecting the cerebellum to other brain regions. Automatic segmentation methods of the CPs have been proposed for studying their structure and function. Usually the performance of these methods is evaluated by comparing segmentation results with manual delineations (ground truth). However, when a segmentation method is run on new data (for which no ground truth exists) it is highly desirable to efficiently detect and assess algorithm failures so that these cases can be excluded from scientific analysis. In this work, two outlier detection methods aimed to assess the performance of an automatic CP segmentation algorithm are presented. The first one is a univariate non-parametric method using a box-whisker plot. We first categorize automatic segmentation results of a dataset of diffusion tensor imaging (DTI) scans from 48 subjects as either a success or a failure. We then design three groups of features from the image data of nine categorized failures for failure detection. Results show that most of these features can efficiently detect the true failures. The second method—supervised classification—was employed on a larger DTI dataset of 249 manually categorized subjects. Four classifiers—linear discriminant analysis (LDA), logistic regression (LR), support vector machine (SVM), and random forest classification (RFC)—were trained using the designed features and evaluated using a leave-one-out cross validation. Results show that the LR performs worst among the four classifiers and the other three perform comparably, which demonstrates the feasibility of automatically detecting segmentation failures using classification methods.

Automatic detection and visualisation of MEG ripple oscillations in epilepsy.

PubMed

van Klink, Nicole; van Rosmalen, Frank; Nenonen, Jukka; Burnos, Sergey; Helle, Liisa; Taulu, Samu; Furlong, Paul Lawrence; Zijlmans, Maeike; Hillebrand, Arjan

2017-01-01

High frequency oscillations (HFOs, 80-500 Hz) in invasive EEG are a biomarker for the epileptic focus. Ripples (80-250 Hz) have also been identified in non-invasive MEG, yet detection is impeded by noise, their low occurrence rates, and the workload of visual analysis. We propose a method that identifies ripples in MEG through noise reduction, beamforming and automatic detection with minimal user effort. We analysed 15 min of presurgical resting-state interictal MEG data of 25 patients with epilepsy. The MEG signal-to-noise was improved by using a cross-validation signal space separation method, and by calculating ~ 2400 beamformer-based virtual sensors in the grey matter. Ripples in these sensors were automatically detected by an algorithm optimized for MEG. A small subset of the identified ripples was visually checked. Ripple locations were compared with MEG spike dipole locations and the resection area if available. Running the automatic detection algorithm resulted in on average 905 ripples per patient, of which on average 148 ripples were visually reviewed. Reviewing took approximately 5 min per patient, and identified ripples in 16 out of 25 patients. In 14 patients the ripple locations showed good or moderate concordance with the MEG spikes. For six out of eight patients who had surgery, the ripple locations showed concordance with the resection area: 4/5 with good outcome and 2/3 with poor outcome. Automatic ripple detection in beamformer-based virtual sensors is a feasible non-invasive tool for the identification of ripples in MEG. Our method requires minimal user effort and is easily applicable in a clinical setting.

Automatic Earthquake Detection and Location by Waveform coherency in Alentejo (South Portugal) Using CatchPy

NASA Astrophysics Data System (ADS)

Custodio, S.; Matos, C.; Grigoli, F.; Cesca, S.; Heimann, S.; Rio, I.

2015-12-01

Seismic data processing is currently undergoing a step change, benefitting from high-volume datasets and advanced computer power. In the last decade, a permanent seismic network of 30 broadband stations, complemented by dense temporary deployments, covered mainland Portugal. This outstanding regional coverage currently enables the computation of a high-resolution image of the seismicity of Portugal, which contributes to fitting together the pieces of the regional seismo-tectonic puzzle. Although traditional manual inspections are valuable to refine automatic results they are impracticable with the big data volumes now available. When conducted alone they are also less objective since the criteria is defined by the analyst. In this work we present CatchPy, a scanning algorithm to detect earthquakes in continuous datasets. Our main goal is to implement an automatic earthquake detection and location routine in order to have a tool to quickly process large data sets, while at the same time detecting low magnitude earthquakes (i.e. lowering the detection threshold). CatchPY is designed to produce an event database that could be easily located using existing location codes (e.g.: Grigoli et al. 2013, 2014). We use CatchPy to perform automatic detection and location of earthquakes that occurred in Alentejo region (South Portugal), taking advantage of a dense seismic network deployed in the region for two years during the DOCTAR experiment. Results show that our automatic procedure is particularly suitable for small aperture networks. The event detection is performed by continuously computing the short-term-average/long-term-average of two different characteristic functions (CFs). For the P phases we used a CF based on the vertical energy trace while for S phases we used a CF based on the maximum eigenvalue of the instantaneous covariance matrix (Vidale 1991). Seismic event location is performed by waveform coherence analysis, scanning different hypocentral coordinates (Grigoli et al. 2013, 2014). The reliability of automatic detections, phase pickings and locations are tested trough the quantitative comparison with manual results. This work is supported by project QuakeLoc, reference: PTDC/GEO-FIQ/3522/2012

Use of Glycerol as an Optical Clearing Agent for Enhancing Photonic Transference and Detection of Salmonella typhimurium through Porcine Skin

USDA-ARS?s Scientific Manuscript database

The objective of this study was to evaluate glycerol (GLY) and GLY + dimethyl sulfoxide (DMSO) to increase photonic detection of transformed Salmonella typhimurium (S. typh-lux) through porcine skin. Skin was placed on 96-well plates containing S. typh-lux, imaged (5 min) using a CCD camera, and the...

Use of Glycerol as an Optical Clearing Agent for Enhancing Photonic Transference and Detection of Salmonella typhimurium Through Porcine Skin

USDA-ARS?s Scientific Manuscript database

The objective of this study was to evaluate glycerol (GLY) and GLY + dimethyl sulfoxide (DMSO) to increase photonic detection of transformed Salmonella typhimurium (S. typh-lux) through porcine skin. Skin was placed on 96-well plates containing S. typh-lux, imaged (5 min) using a CCD camera, and the...

Comparative study of carotenoids, catalase and radical formation in human and animal skin.

PubMed

Haag, S F; Bechtel, A; Darvin, M E; Klein, F; Groth, N; Schäfer-Korting, M; Bittl, R; Lademann, J; Sterry, W; Meinke, M C

2010-01-01

Animal skin is widely used in dermatological free radical research. Porcine ear skin is a well-studied substitute for human skin. The use of bovine udder skin is rare but its high carotenoid content makes it particularly appropriate for studying the redox state of the skin. Yet, information on the suitability of animal skin for the study of external hazard effects on the redox state of human skin has been lacking. In this study, we investigated the activity of the antioxidant enzyme catalase and the carotenoid content defining the redox status as well as UV-induced radical formation of human, porcine ear and bovine udder skin ex vivo. In human skin only low levels of radical formation were detected following UV irradiation, whereas bovine skin contains the highest amount of carotenoids but the lowest amount of catalase. Porcine ear skin does not exhibit a carotenoid signal but its catalase activity is close to human skin. Therefore, radical formation can neither be correlated to the amount of catalase nor to the amount of carotenoids in the skin. All skin types can be used for electron paramagnetic resonance-based detection of radicals, but porcine skin was found to be the most suitable type. Copyright 2010 S. Karger AG, Basel.

Detecting electroporation by assessing the time constants in the exponential response of human skin to voltage controlled impulse electrical stimulation.

PubMed

Bîrlea, Sinziana I; Corley, Gavin J; Bîrlea, Nicolae M; Breen, Paul P; Quondamatteo, Fabio; OLaighin, Gearóid

2009-01-01

We propose a new method for extracting the electrical properties of human skin based on the time constant analysis of its exponential response to impulse stimulation. As a result of this analysis an adjacent finding has arisen. We have found that stratum corneum electroporation can be detected using this analysis method. We have observed that a one time-constant model is appropriate for describing the electrical properties of human skin at low amplitude applied voltages (<30V), and a two time-constant model best describes skin electrical properties at higher amplitude applied voltages (>30V). Higher voltage amplitudes (>30V) have been proven to create pores in the skin's stratum corneum which offer a new, lower resistance, pathway for the passage of current through the skin. Our data shows that when pores are formed in the stratum corneum they can be detected, in-vivo, due to the fact that a second time constant describes current flow through them.

Optical coherence tomography for the structural changes detection in aging skin

NASA Astrophysics Data System (ADS)

Cheng, Chih-Ming; Chang, Yu-Fen; Chiang, Hung-Chih; Chang, Chir-Weei

2018-01-01

Optical coherence tomography (OCT) technique is an extremely powerful tool to detect numerous ophthalmological disorders, such as retinal disorder, and can be applied on other fields. Thus, many OCT systems are developed. For assessment of the skin textures, a cross-sectional (B-scan) spectra domain OCT system is better than an en-face one. However, this kind of commercial OCT system is not available. We designed a brand-new probe of commercial OCT system for evaluating skin texture without destroying the original instrument and it can be restored in 5 minutes. This modification of OCT system retains the advantages of commercial instrument, such as reliable, stable, and safe. Furthermore, the structural changes in aging skin are easily obtained by means of our probe, including larger pores, thinning of the dermis, collagen volume loss, vessel atrophy and flattening of dermal-epidermal junction. We can use this OCT technique in the field of cosmetic medicine such as detecting the skin textures and skin care product effect followup.

Simulation study and guidelines to generate Laser-induced Surface Acoustic Waves for human skin feature detection

NASA Astrophysics Data System (ADS)

Li, Tingting; Fu, Xing; Chen, Kun; Dorantes-Gonzalez, Dante J.; Li, Yanning; Wu, Sen; Hu, Xiaotang

2015-12-01

Despite the seriously increasing number of people contracting skin cancer every year, limited attention has been given to the investigation of human skin tissues. To this regard, Laser-induced Surface Acoustic Wave (LSAW) technology, with its accurate, non-invasive and rapid testing characteristics, has recently shown promising results in biological and biomedical tissues. In order to improve the measurement accuracy and efficiency of detecting important features in highly opaque and soft surfaces such as human skin, this paper identifies the most important parameters of a pulse laser source, as well as provides practical guidelines to recommended proper ranges to generate Surface Acoustic Waves (SAWs) for characterization purposes. Considering that melanoma is a serious type of skin cancer, we conducted a finite element simulation-based research on the generation and propagation of surface waves in human skin containing a melanoma-like feature, determine best pulse laser parameter ranges of variation, simulation mesh size and time step, working bandwidth, and minimal size of detectable melanoma.

Study on the Automatic Detection Method and System of Multifunctional Hydrocephalus Shunt

NASA Astrophysics Data System (ADS)

Sun, Xuan; Wang, Guangzhen; Dong, Quancheng; Li, Yuzhong

2017-07-01

Aiming to the difficulty of micro pressure detection and the difficulty of micro flow control in the testing process of hydrocephalus shunt, the principle of the shunt performance detection was analyzed.In this study, the author analyzed the principle of several items of shunt performance detection,and used advanced micro pressure sensor and micro flow peristaltic pump to overcome the micro pressure detection and micro flow control technology.At the same time,This study also puted many common experimental projects integrated, and successfully developed the automatic detection system for a shunt performance detection function, to achieve a test with high precision, high efficiency and automation.

An automatic lightning detection and photographic system

NASA Technical Reports Server (NTRS)

Wojtasinski, R. J.; Holley, L. D.; Gray, J. L.; Hoover, R. B.

1973-01-01

Conventional 35-mm camera is activated by an electronic signal every time lightning strikes in general vicinity. Electronic circuit detects lightning by means of antenna which picks up atmospheric radio disturbances. Camera is equipped with fish-eye lense, automatic shutter advance, and small 24-hour clock to indicate time when exposures are made.

46 CFR 161.002-9 - Automatic fire detecting system, power supply.

Code of Federal Regulations, 2013 CFR

2013-10-01

... system must meet the requirements of § 113.10-9 of subchapter J (Electrical Engineering Regulations) of... 46 Shipping 6 2013-10-01 2013-10-01 false Automatic fire detecting system, power supply. 161.002-9..., CONSTRUCTION, AND MATERIALS: SPECIFICATIONS AND APPROVAL ELECTRICAL EQUIPMENT Fire-Protective Systems § 161.002...

46 CFR 161.002-9 - Automatic fire detecting system, power supply.

Code of Federal Regulations, 2014 CFR

2014-10-01

... system must meet the requirements of § 113.10-9 of subchapter J (Electrical Engineering Regulations) of... 46 Shipping 6 2014-10-01 2014-10-01 false Automatic fire detecting system, power supply. 161.002-9..., CONSTRUCTION, AND MATERIALS: SPECIFICATIONS AND APPROVAL ELECTRICAL EQUIPMENT Fire-Protective Systems § 161.002...

46 CFR 161.002-9 - Automatic fire detecting system, power supply.

Code of Federal Regulations, 2012 CFR

2012-10-01

... system must meet the requirements of § 113.10-9 of subchapter J (Electrical Engineering Regulations) of... 46 Shipping 6 2012-10-01 2012-10-01 false Automatic fire detecting system, power supply. 161.002-9..., CONSTRUCTION, AND MATERIALS: SPECIFICATIONS AND APPROVAL ELECTRICAL EQUIPMENT Fire-Protective Systems § 161.002...

Histogram-based automatic thresholding for bruise detection of apples by structured-illumination reflectance imaging

USDA-ARS?s Scientific Manuscript database

Thresholding is an important step in the segmentation of image features, and the existing methods are not all effective when the image histogram exhibits a unimodal pattern, which is common in defect detection of fruit. This study was aimed at developing a general automatic thresholding methodology ...

Detection of human papillomavirus in nonmelanoma skin cancer lesions and healthy perilesional skin in kidney transplant recipients and immunocompetent patients.

PubMed

Bernat-García, J; Morales Suárez-Varela, M; Vilata-Corell, J J; Marquina-Vila, A

2014-04-01

The influence of human papillomavirus (HPV) on the development of nonmelanoma skin cancer (NMSC) is a topic of debate. HPV types from the beta genus (HPV-β) have been most frequently associated with the development of skin cancer. To analyze the prevalence and range of HPV types in NMSC lesions and healthy perilesional skin in immunodepressed and immunocompetent patients and to evaluate the influence of various clinical factors on the prevalence of HPV in skin cancer. Nested polymerase chain reaction and sequencing were used to detect HPV in 120 NMSC samples obtained by biopsy from 30 kidney transplant recipients and 30 immunocompetent patients. In all cases, a sample was taken from the tumor site and the surrounding healthy skin. Potential confounders were assessed and the data analyzed by multivariate logistic regression. HPV DNA was detected in 44 (73.3%) of the 60 samples from immunodepressed patients and in 32 (53.3%) of the 60 samples from immunocompetent patients (adjusted odds ratio, 3.4; 95% CI, 1.2-9.6). In both groups of patients, HPV was more common in healthy perilesional skin than in lesional skin. HPV-β was the most common type isolated. We found a wide range of HPV types (mostly HPV-β) in the skin of kidney transplant recipients and immunocompetent patients with skin cancer. Copyright © 2013 Elsevier España, S.L. and AEDV. All rights reserved.

Automatic bone detection and soft tissue aware ultrasound-CT registration for computer-aided orthopedic surgery.

PubMed

Wein, Wolfgang; Karamalis, Athanasios; Baumgartner, Adrian; Navab, Nassir

2015-06-01

The transfer of preoperative CT data into the tracking system coordinates within an operating room is of high interest for computer-aided orthopedic surgery. In this work, we introduce a solution for intra-operative ultrasound-CT registration of bones. We have developed methods for fully automatic real-time bone detection in ultrasound images and global automatic registration to CT. The bone detection algorithm uses a novel bone-specific feature descriptor and was thoroughly evaluated on both in-vivo and ex-vivo data. A global optimization strategy aligns the bone surface, followed by a soft tissue aware intensity-based registration to provide higher local registration accuracy. We evaluated the system on femur, tibia and fibula anatomy in a cadaver study with human legs, where magnetically tracked bone markers were implanted to yield ground truth information. An overall median system error of 3.7 mm was achieved on 11 datasets. Global and fully automatic registration of bones aquired with ultrasound to CT is feasible, with bone detection and tracking operating in real time for immediate feedback to the surgeon.

Automatic detection of solar features in HSOS full-disk solar images using guided filter

NASA Astrophysics Data System (ADS)

Yuan, Fei; Lin, Jiaben; Guo, Jingjing; Wang, Gang; Tong, Liyue; Zhang, Xinwei; Wang, Bingxiang

2018-02-01

A procedure is introduced for the automatic detection of solar features using full-disk solar images from Huairou Solar Observing Station (HSOS), National Astronomical Observatories of China. In image preprocessing, median filter is applied to remove the noises. Guided filter is adopted to enhance the edges of solar features and restrain the solar limb darkening, which is first introduced into the astronomical target detection. Then specific features are detected by Otsu algorithm and further threshold processing technique. Compared with other automatic detection procedures, our procedure has some advantages such as real time and reliability as well as no need of local threshold. Also, it reduces the amount of computation largely, which is benefited from the efficient guided filter algorithm. The procedure has been tested on one month sequences (December 2013) of HSOS full-disk solar images and the result shows that the number of features detected by our procedure is well consistent with the manual one.

A device for the color measurement and detection of spots on the skin.

PubMed

Pladellorens, Josep; Pintó, Agustí; Segura, Jordi; Cadevall, Cristina; Antó, Joan; Pujol, Jaume; Vilaseca, Meritxell; Coll, Joaquín

2008-02-01

In this work, we present a new and fast easy-to-use device that allows the measurement of color and the detection of spots on the human skin. The developed device is highly practical for relatively untrained operators and uses inexpensive consumer equipment, such as a CCD color camera, a light source composed of LEDs and a laptop. The knowledge of the color of the skin and the detection of spots can be useful in several areas such as in dermatology applications, the cosmetics industry, the biometrics field, health care, etc. In order to perform these measurements the system takes a picture of the skin. After that, the operator selects the region of the skin to be analyzed on the displayed image and the system provides the CIELAB color coordinates, the chroma and the ITA parameter (Individual Tipology Angle), allowing the comparison with other reference images by means of CIELAB color differences. The system also detects spots, such as freckles, age spots, sunspots, pimples, black heads, etc., in a determined region, allowing the objective measurement of their size and area. The colorimetric information provided by a conventional spectrophotometer for the tested samples and the computed values obtained with the new developed system are quite similar, meaning that the developed system can be used to perform color measurements with relatively high accuracy. On the other hand, the feasibility of the system in order to detect and measure spots on the human skin has also been checked over a great amount of images, obtaining results with high precision. In this work, we present a new system that may be very useful in order to measure the color and to detect spots of the skin. Its portability and easy applicability will be very useful in dermatologic and cosmetic studies.

Automatic data processing and analysis system for monitoring region around a planned nuclear power plant

NASA Astrophysics Data System (ADS)

Kortström, Jari; Tiira, Timo; Kaisko, Outi

2016-03-01

The Institute of Seismology of University of Helsinki is building a new local seismic network, called OBF network, around planned nuclear power plant in Northern Ostrobothnia, Finland. The network will consist of nine new stations and one existing station. The network should be dense enough to provide azimuthal coverage better than 180° and automatic detection capability down to ML -0.1 within a radius of 25 km from the site.The network construction work began in 2012 and the first four stations started operation at the end of May 2013. We applied an automatic seismic signal detection and event location system to a network of 13 stations consisting of the four new stations and the nearest stations of Finnish and Swedish national seismic networks. Between the end of May and December 2013 the network detected 214 events inside the predefined area of 50 km radius surrounding the planned nuclear power plant site. Of those detections, 120 were identified as spurious events. A total of 74 events were associated with known quarries and mining areas. The average location error, calculated as a difference between the announced location from environment authorities and companies and the automatic location, was 2.9 km. During the same time period eight earthquakes between magnitude range 0.1-1.0 occurred within the area. Of these seven could be automatically detected. The results from the phase 1 stations of the OBF network indicates that the planned network can achieve its goals.

Early detection of skin cancer via terahertz spectral profiling and 3D imaging.

PubMed

Rahman, Anis; Rahman, Aunik K; Rao, Babar

2016-08-15

Terahertz scanning reflectometry, terahertz 3D imaging and terahertz time-domain spectroscopy have been used to identify features in human skin biopsy samples diagnosed for basal cell carcinoma (BCC) and compared with healthy skin samples. It was found from the 3D images that the healthy skin samples exhibit regular cellular pattern while the BCC skin samples indicate lack of regular cell pattern. The skin is a highly layered structure organ; this is evident from the thickness profile via a scan through the thickness of the healthy skin samples, where, the reflected intensity of the terahertz beam exhibits fluctuations originating from different skin layers. Compared to the healthy skin samples, the BCC samples' profiles exhibit significantly diminished layer definition; thus indicating a lack of cellular order. In addition, terahertz time-domain spectroscopy reveals significant and quantifiable differences between the healthy and BCC skin samples. Thus, a combination of three different terahertz techniques constitutes a conclusive route for detecting the BCC condition on a cellular level compared to the healthy skin. Copyright © 2016 Elsevier B.V. All rights reserved.

Ultrathin epidermal strain sensor based on an elastomer nanosheet with an inkjet-printed conductive polymer

NASA Astrophysics Data System (ADS)

Tetsu, Yuma; Yamagishi, Kento; Kato, Akira; Matsumoto, Yuya; Tsukune, Mariko; Kobayashi, Yo; Fujie, Masakatsu G.; Takeoka, Shinji; Fujie, Toshinori

2017-08-01

To minimize the interference that skin-contact strain sensors cause natural skin deformation, physical conformability to the epidermal structure is critical. Here, we developed an ultrathin strain sensor made from poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) inkjet-printed on a polystyrene-polybutadiene-polystyrene (SBS) nanosheet. The sensor, whose total thickness and gauge factor were ˜1 µm and 0.73 ± 0.10, respectively, deeply conformed to the epidermal structure and successfully detected the small skin strain (˜2%) while interfering minimally with the natural deformation of the skin. Such an epidermal strain sensor will open a new avenue for precisely detecting the motion of human skin and artificial soft-robotic skin.

High correlation of double Debye model parameters in skin cancer detection.

PubMed

Truong, Bao C Q; Tuan, H D; Fitzgerald, Anthony J; Wallace, Vincent P; Nguyen, H T

2014-01-01

The double Debye model can be used to capture the dielectric response of human skin in terahertz regime due to high water content in the tissue. The increased water proportion is widely considered as a biomarker of carcinogenesis, which gives rise of using this model in skin cancer detection. Therefore, the goal of this paper is to provide a specific analysis of the double Debye parameters in terms of non-melanoma skin cancer classification. Pearson correlation is applied to investigate the sensitivity of these parameters and their combinations to the variation in tumor percentage of skin samples. The most sensitive parameters are then assessed by using the receiver operating characteristic (ROC) plot to confirm their potential of classifying tumor from normal skin. Our positive outcomes support further steps to clinical application of terahertz imaging in skin cancer delineation.

Dense deconvolution net: Multi path fusion and dense deconvolution for high resolution skin lesion segmentation.

PubMed

He, Xinzi; Yu, Zhen; Wang, Tianfu; Lei, Baiying; Shi, Yiyan

2018-01-01

Dermoscopy imaging has been a routine examination approach for skin lesion diagnosis. Accurate segmentation is the first step for automatic dermoscopy image assessment. The main challenges for skin lesion segmentation are numerous variations in viewpoint and scale of skin lesion region. To handle these challenges, we propose a novel skin lesion segmentation network via a very deep dense deconvolution network based on dermoscopic images. Specifically, the deep dense layer and generic multi-path Deep RefineNet are combined to improve the segmentation performance. The deep representation of all available layers is aggregated to form the global feature maps using skip connection. Also, the dense deconvolution layer is leveraged to capture diverse appearance features via the contextual information. Finally, we apply the dense deconvolution layer to smooth segmentation maps and obtain final high-resolution output. Our proposed method shows the superiority over the state-of-the-art approaches based on the public available 2016 and 2017 skin lesion challenge dataset and achieves the accuracy of 96.0% and 93.9%, which obtained a 6.0% and 1.2% increase over the traditional method, respectively. By utilizing Dense Deconvolution Net, the average time for processing one testing images with our proposed framework was 0.253 s.

Chicken skin virome analyzed by high-throughput sequencing shows a composition highly different from human skin.

PubMed

Denesvre, Caroline; Dumarest, Marine; Rémy, Sylvie; Gourichon, David; Eloit, Marc

2015-10-01

Recent studies show that human skin at homeostasis is a complex ecosystem whose virome include circular DNA viruses, especially papillomaviruses and polyomaviruses. To determine the chicken skin virome in comparison with human skin virome, a chicken swabs pool sample from fifteen indoor healthy chickens of five genetic backgrounds was examined for the presence of DNA viruses by high-throughput sequencing (HTS). The results indicate a predominance of herpesviruses from the Mardivirus genus, coming from either vaccinal origin or presumably asymptomatic infection. Despite the high sensitivity of the HTS method used herein to detect small circular DNA viruses, we did not detect any papillomaviruses, polyomaviruses, or circoviruses, indicating that these viruses may not be resident of the chicken skin. The results suggest that the turkey herpesvirus is a resident of chicken skin in vaccinated chickens. This study indicates major differences between the skin viromes of chickens and humans. The origin of this difference remains to be further studied in relation with skin physiology, environment, or virus population dynamics.

TU-H-CAMPUS-JeP1-02: Fully Automatic Verification of Automatically Contoured Normal Tissues in the Head and Neck

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCarroll, R; UT Health Science Center, Graduate School of Biomedical Sciences, Houston, TX; Beadle, B

Purpose: To investigate and validate the use of an independent deformable-based contouring algorithm for automatic verification of auto-contoured structures in the head and neck towards fully automated treatment planning. Methods: Two independent automatic contouring algorithms [(1) Eclipse’s Smart Segmentation followed by pixel-wise majority voting, (2) an in-house multi-atlas based method] were used to create contours of 6 normal structures of 10 head-and-neck patients. After rating by a radiation oncologist, the higher performing algorithm was selected as the primary contouring method, the other used for automatic verification of the primary. To determine the ability of the verification algorithm to detect incorrectmore » contours, contours from the primary method were shifted from 0.5 to 2cm. Using a logit model the structure-specific minimum detectable shift was identified. The models were then applied to a set of twenty different patients and the sensitivity and specificity of the models verified. Results: Per physician rating, the multi-atlas method (4.8/5 point scale, with 3 rated as generally acceptable for planning purposes) was selected as primary and the Eclipse-based method (3.5/5) for verification. Mean distance to agreement and true positive rate were selected as covariates in an optimized logit model. These models, when applied to a group of twenty different patients, indicated that shifts could be detected at 0.5cm (brain), 0.75cm (mandible, cord), 1cm (brainstem, cochlea), or 1.25cm (parotid), with sensitivity and specificity greater than 0.95. If sensitivity and specificity constraints are reduced to 0.9, detectable shifts of mandible and brainstem were reduced by 0.25cm. These shifts represent additional safety margins which might be considered if auto-contours are used for automatic treatment planning without physician review. Conclusion: Automatically contoured structures can be automatically verified. This fully automated process could be used to flag auto-contours for special review or used with safety margins in a fully automatic treatment planning system.« less

Pornographic information of Internet views detection method based on the connected areas

NASA Astrophysics Data System (ADS)

Wang, Huibai; Fan, Ajie

2017-01-01

Nowadays online porn video broadcasting and downloading is very popular. In view of the widespread phenomenon of Internet pornography, this paper proposed a new method of pornographic video detection based on connected areas. Firstly, decode the video into a serious of static images and detect skin color on the extracted key frames. If the area of skin color reaches a certain threshold, use the AdaBoost algorithm to detect the human face. Judge the connectivity of the human face and the large area of skin color to determine whether detect the sensitive area finally. The experimental results show that the method can effectively remove the non-pornographic videos contain human who wear less. This method can improve the efficiency and reduce the workload of detection.

Optical skin biopsies by clinical CARS and multiphoton fluorescence/SHG tomography

NASA Astrophysics Data System (ADS)

König, K.; Breunig, H. G.; Bückle, R.; Kellner-Höfer, M.; Weinigel, M.; Büttner, E.; Sterry, W.; Lademann, J.

2011-06-01

The ultimate challenge for early diagnostics is label-free high-resolution intratissue imaging without taking physical biopsies. A novel hybrid femtosecond laser tomograph provides in vivo optical biopsies of human skin based on non-linear excitation of autofluorescence and the detection of lipids and water by CARS. Applications include skin cancer detection, biosafety tests of intradermal nanoparticles, and the testing of anti-aging products.

Cutaneous human papillomavirus types detected on the surface of male external genital lesions: A case series within the HPV Infection in Men Study

PubMed Central

Pierce Campbell, Christine M.; Messina, Jane L.; Stoler, Mark H.; Jukic, Drazen M.; Tommasino, Massimo; Gheit, Tarik; Rollison, Dana E.; Sichero, Laura; Sirak, Bradley A.; Ingles, Donna J.; Abrahamsen, Martha; Lu, Beibei; Villa, Luisa L.; Lazcano-Ponce, Eduardo; Giuliano, Anna R.

2013-01-01

Background Cutaneous human papillomaviruses (HPVs) may be associated with cutaneous epithelial lesions and non-melanoma skin cancers. No study has systematically evaluated the presence of genus beta [β]-HPV in male genital skin or external genital lesions (EGLs). Objectives To examine cutaneous β-HPV types detected on the surface of EGLs in men and describe their presence prior to EGL development. Study design A retrospective case series was conducted among 69 men with pathologically confirmed EGLs (n=72) who participated in the HPV Infection in Men Study. Archived exfoliated cells collected from the surface of each EGL and normal genital skin specimens 6–12 months preceding EGL development were tested for β-HPV DNA using a type-specific multiplex genotyping assay. Results β-HPV DNA was detected on 61.1% of all EGLs, with types 38 (16.7%), 5 (15.3%), and 12 (12.5%) most commonly identified. HPV prevalence differed across pathological diagnoses, with the largest number of β-HPV types detected on condylomas. Most β-HPV types were detected on normal genital skin prior to EGL development, though the prevalence was lower on EGLs compared to preceding normal genital skin. Conclusions EGLs and the normal genital skin of men harbor a large number of β-HPV types; however, it appears that β-HPVs are unrelated to EGL development in men. Despite evidence to support a causal role in skin carcinogenesis at UVR-exposed sites, cutaneous HPV appears unlikely to cause disease at the UVR-unexposed genitals. PMID:24210970

Automatic Co-Registration of QuickBird Data for Change Detection Applications

NASA Technical Reports Server (NTRS)

Bryant, Nevin A.; Logan, Thomas L.; Zobrist, Albert L.

2006-01-01

This viewgraph presentation reviews the use Automatic Fusion of Image Data System (AFIDS) for Automatic Co-Registration of QuickBird Data to ascertain if changes have occurred in images. The process is outlined, and views from Iraq and Los Angelels are shown to illustrate the process.

Using Morphed Images to Study Visual Detection of Cutaneous Melanoma Symptom Evolution

ERIC Educational Resources Information Center

Dalianis, Elizabeth A.; Critchfield, Thomas S.; Howard, Niki L.; Jordan, J. Scott; Derenne, Adam

2011-01-01

Early detection attenuates otherwise high mortality from the skin cancer melanoma, and although major melanoma symptoms are well defined, little is known about how individuals detect them. Previous research has focused on identifying static stimuli as symptomatic vs. asymptomatic, whereas under natural conditions it is "changes" in skin lesions…

A Multiple Sensor Machine Vision System for Automatic Hardwood Feature Detection

Treesearch

D. Earl Kline; Richard W. Conners; Daniel L. Schmoldt; Philip A. Araman; Robert L. Brisbin

1993-01-01

A multiple sensor machine vision prototype is being developed to scan full size hardwood lumber at industrial speeds for automatically detecting features such as knots holes, wane, stain, splits, checks, and color. The prototype integrates a multiple sensor imaging system, a materials handling system, a computer system, and application software. The prototype provides...

Detection theory for accurate and non-invasive skin cancer diagnosis using dynamic thermal imaging

PubMed Central

Godoy, Sebastián E.; Hayat, Majeed M.; Ramirez, David A.; Myers, Stephen A.; Padilla, R. Steven; Krishna, Sanjay

2017-01-01

Skin cancer is the most common cancer in the United States with over 3.5M annual cases. Presently, visual inspection by a dermatologist has good sensitivity (> 90%) but poor specificity (< 10%), especially for melanoma, which leads to a high number of unnecessary biopsies. Here we use dynamic thermal imaging (DTI) to demonstrate a rapid, accurate and non-invasive imaging system for detection of skin cancer. In DTI, the lesion is cooled down and the thermal recovery is recorded using infrared imaging. The thermal recovery curves of the suspected lesions are then utilized in the context of continuous-time detection theory in order to define an optimal statistical decision rule such that the sensitivity of the algorithm is guaranteed to be at a maximum for every prescribed false-alarm probability. The proposed methodology was tested in a pilot study including 140 human subjects demonstrating a sensitivity in excess of 99% for a prescribed specificity in excess of 99% for detection of skin cancer. To the best of our knowledge, this is the highest reported accuracy for any non-invasive skin cancer diagnosis method. PMID:28736673

Spectroscopic detection of the blanch response at the heel of the foot: a possible diagnostic for stage I pressure ulcers

NASA Astrophysics Data System (ADS)

Kohlenberg, Elicia M.; Zanca, Jeanne; Brienza, David M.; Levasseur, Michelle A.; Sowa, Michael G.

2005-09-01

Pressure ulcers (sores) can occur when there is constant pressure being applied to tissue for extended periods of time. Immobile people are particularly prone to this problem. Ideally, pressure damage is detected at an early stage, pressure relief is applied and the pressure ulcer is averted. One of the hallmarks of pressure damaged skin is an obliterated blanch response due to compromised microcirculation near the surface of the skin. Visible reflectance spectroscopy can noninvasively probe the blood circulation of the upper layers of skin by measuring the electronic transitions arising from hemoglobin, the primary oxygen carrying protein in blood. A spectroscopic test was developed on a mixed population of 30 subjects to determine if the blanch response could be detected in healthy skin with high sensitivity and specificity regardless of the pigmentation of the skin. Our results suggest that a spectroscopic based blanch response test can accurately detect the blanching of healthy tissue and has the potential to be developed into a screening test for early stage I pressure ulcers.

Findings toward the miniaturization of a laser speckle contrast device for skin roughness measurements

NASA Astrophysics Data System (ADS)

Louie, Daniel C.; Tchvialeva, Lioudmilla; Zeng, Haishan; Lee, Tim K.

2017-02-01

Skin roughness is an important parameter in the characterization of skin and skin lesions, particularly for the purposes of skin cancer detection. Our group had previously constructed a laser speckle device that can detect the roughness in microrelief of the skin. This paper reports on findings made for the further miniaturization of our existing portably-sized device. These findings include the feasibility of adopting a laser diode without temperature control, and the use of a single CCD camera for detection. The coherence length of a laser is a crucial criterion for speckle measurements as it must be within a specific range. The coherence length of a commercial grade 405 nm laser diode was found to be of an appropriate length. Also, after a short warm-up period the coherence length of the laser was found to remain relatively stable, even without temperature control. Although the laser's temperature change during operation may affect its power output and the shape of its spectrum, these are only minor factors in speckle contrast measurements. Our second finding covers a calibration curve to relate speckle measurements to roughness using only parallel polarization from one CCD camera. This was created using experimental data from skin phantoms and tested on in-vivo skin. These improvements are important steps forward in the ongoing development of the laser speckle device, especially towards a clinical device to measure skin roughness and evaluate skin lesions.

Automatic target detection using binary template matching

NASA Astrophysics Data System (ADS)

Jun, Dong-San; Sun, Sun-Gu; Park, HyunWook

2005-03-01

This paper presents a new automatic target detection (ATD) algorithm to detect targets such as battle tanks and armored personal carriers in ground-to-ground scenarios. Whereas most ATD algorithms were developed for forward-looking infrared (FLIR) images, we have developed an ATD algorithm for charge-coupled device (CCD) images, which have superior quality to FLIR images in daylight. The proposed algorithm uses fast binary template matching with an adaptive binarization, which is robust to various light conditions in CCD images and saves computation time. Experimental results show that the proposed method has good detection performance.

Automatic laser beam alignment using blob detection for an environment monitoring spectroscopy

NASA Astrophysics Data System (ADS)

Khidir, Jarjees; Chen, Youhua; Anderson, Gary

2013-05-01

This paper describes a fully automated system to align an infra-red laser beam with a small retro-reflector over a wide range of distances. The component development and test were especially used for an open-path spectrometer gas detection system. Using blob detection under OpenCV library, an automatic alignment algorithm was designed to achieve fast and accurate target detection in a complex background environment. Test results are presented to show that the proposed algorithm has been successfully applied to various target distances and environment conditions.

The isolated perfused human skin flap model: A missing link in skin penetration studies?

PubMed

Ternullo, Selenia; de Weerd, Louis; Flaten, Gøril Eide; Holsæter, Ann Mari; Škalko-Basnet, Nataša

2017-01-01

Development of effective (trans)dermal drug delivery systems requires reliable skin models to evaluate skin drug penetration. The isolated perfused human skin flap remains metabolically active tissue for up to 6h during in vitro perfusion. We introduce the isolated perfused human skin flap as a close-to-in vivo skin penetration model. To validate the model's ability to evaluate skin drug penetration the solutions of a hydrophilic (calcein) and a lipophilic (rhodamine) fluorescence marker were applied. The skin flaps were perfused with modified Krebs-Henseleit buffer (pH7.4). Infrared technology was used to monitor perfusion and to select a well-perfused skin area for administration of the markers. Flap perfusion and physiological parameters were maintained constant during the 6h experiments and the amount of markers in the perfusate was determined. Calcein was detected in the perfusate, whereas rhodamine was not detectable. Confocal images of skin cross-sections shoved that calcein was uniformly distributed through the skin, whereas rhodamine accumulated in the stratum corneum. For comparison, the penetration of both markers was evaluated on ex vivo human skin, pig skin and cellophane membrane. The proposed perfused flap model enabled us to distinguish between the penetrations of the two markers and could be a promising close-to-in vivo tool in skin penetration studies and optimization of formulations destined for skin administration. Copyright © 2016 Elsevier B.V. All rights reserved.

Melanoma Diagnosis

NASA Astrophysics Data System (ADS)

Horsch, Alexander

The chapter deals with the diagnosis of the malignant melanoma of the skin. This aggressive type of cancer with steadily growing incidence in white populations can hundred percent be cured if it is detected in an early stage. Imaging techniques, in particular dermoscopy, have contributed significantly to improvement of diagnostic accuracy in clinical settings, achieving sensitivities for melanoma experts of beyond 95% at specificities of 90% and more. Automatic computer analysis of dermoscopy images has, in preliminary studies, achieved classification rates comparable to those of experts. However, the diagnosis of melanoma requires a lot of training and experience, and at the time being, average numbers of lesions excised per histology-proven melanoma are around 30, a number which clearly is too high. Further improvements in computer dermoscopy systems and their competent use in clinical settings certainly have the potential to support efforts of improving this situation. In the chapter, medical basics, current state of melanoma diagnosis, image analysis methods, commercial dermoscopy systems, evaluation of systems, and methods and future directions are presented.

Automatic detection and notification of "wrong patient-wrong location'' errors in the operating room.

PubMed

Sandberg, Warren S; Häkkinen, Matti; Egan, Marie; Curran, Paige K; Fairbrother, Pamela; Choquette, Ken; Daily, Bethany; Sarkka, Jukka-Pekka; Rattner, David

2005-09-01

When procedures and processes to assure patient location based on human performance do not work as expected, patients are brought incrementally closer to a possible "wrong patient-wrong procedure'' error. We developed a system for automated patient location monitoring and management. Real-time data from an active infrared/radio frequency identification tracking system provides patient location data that are robust and can be compared with an "expected process'' model to automatically flag wrong-location events as soon as they occur. The system also generates messages that are automatically sent to process managers via the hospital paging system, thus creating an active alerting function to annunciate errors. We deployed the system to detect and annunciate "patient-in-wrong-OR'' events. The system detected all "wrong-operating room (OR)'' events, and all "wrong-OR'' locations were correctly assigned within 0.50+/-0.28 minutes (mean+/-SD). This corresponded to the measured latency of the tracking system. All wrong-OR events were correctly annunciated via the paging function. This experiment demonstrates that current technology can automatically collect sufficient data to remotely monitor patient flow through a hospital, provide decision support based on predefined rules, and automatically notify stakeholders of errors.

Toward a noninvasive automatic seizure control system in rats with transcranial focal stimulations via tripolar concentric ring electrodes

PubMed Central

Makeyev, Oleksandr; Liu, Xiang; Luna-Munguía, Hiram; Rogel-Salazar, Gabriela; Mucio-Ramirez, Samuel; Liu, Yuhong; Sun, Yan L.; Kay, Steven M.; Besio, Walter G.

2012-01-01

Epilepsy affects approximately one percent of the world population. Antiepileptic drugs are ineffective in approximately 30% of patients and have side effects. We are developing a noninvasive, or minimally invasive, transcranial focal electrical stimulation system through our novel tripolar concentric ring electrodes to control seizures. In this study we demonstrate feasibility of an automatic seizure control system in rats with pentylenetetrazole-induced seizures through single and multiple stimulations. These stimulations are automatically triggered by a real-time electrographic seizure activity detector based on a disjunctive combination of detections from a cumulative sum algorithm and a generalized likelihood ratio test. An average seizure onset detection accuracy of 76.14% was obtained for the test set (n = 13). Detection of electrographic seizure activity was accomplished in advance of the early behavioral seizure activity in 76.92% of the cases. Automatically triggered stimulation significantly (p = 0.001) reduced the electrographic seizure activity power in the once stimulated group compared to controls in 70% of the cases. To the best of our knowledge this is the first closed-loop automatic seizure control system based on noninvasive electrical brain stimulation using tripolar concentric ring electrode electrographic seizure activity as feedback. PMID:22772373

Toward a noninvasive automatic seizure control system in rats with transcranial focal stimulations via tripolar concentric ring electrodes.

PubMed

Makeyev, Oleksandr; Liu, Xiang; Luna-Munguía, Hiram; Rogel-Salazar, Gabriela; Mucio-Ramirez, Samuel; Liu, Yuhong; Sun, Yan L; Kay, Steven M; Besio, Walter G

2012-07-01

Epilepsy affects approximately 1% of the world population. Antiepileptic drugs are ineffective in approximately 30% of patients and have side effects. We are developing a noninvasive, or minimally invasive, transcranial focal electrical stimulation system through our novel tripolar concentric ring electrodes to control seizures. In this study, we demonstrate feasibility of an automatic seizure control system in rats with pentylenetetrazole-induced seizures through single and multiple stimulations. These stimulations are automatically triggered by a real-time electrographic seizure activity detector based on a disjunctive combination of detections from a cumulative sum algorithm and a generalized likelihood ratio test. An average seizure onset detection accuracy of 76.14% was obtained for the test set (n = 13). Detection of electrographic seizure activity was accomplished in advance of the early behavioral seizure activity in 76.92% of the cases. Automatically triggered stimulation significantly (p = 0.001) reduced the electrographic seizure activity power in the once stimulated group compared to controls in 70% of the cases. To the best of our knowledge this is the first closed-loop automatic seizure control system based on noninvasive electrical brain stimulation using tripolar concentric ring electrode electrographic seizure activity as feedback.

Automatic detection of DNA double strand breaks after irradiation using an γH2AX assay.

PubMed

Hohmann, Tim; Kessler, Jacqueline; Grabiec, Urszula; Bache, Matthias; Vordermark, Dyrk; Dehghani, Faramarz

2018-05-01

Radiation therapy belongs to the most common approaches for cancer therapy leading amongst others to DNA damage like double strand breaks (DSB). DSB can be used as a marker for the effect of radiation on cells. For visualization and assessing the extent of DNA damage the γH2AX foci assay is frequently used. The analysis of the γH2AX foci assay remains complicated as the number of γH2AX foci has to be counted. The quantification is mostly done manually, being time consuming and leading to person-dependent variations. Therefore, we present a method to automatically analyze the number of foci inside nuclei, facilitating and quickening the analysis of DSBs with high reliability in fluorescent images. First nuclei were detected in fluorescent images. Afterwards, the nuclei were analyzed independently from each other with a local thresholding algorithm. This approach allowed accounting for different levels of noise and detection of the foci inside the respective nucleus, using Hough transformation searching for circles. The presented algorithm was able to correctly classify most foci in cases of "high" and "average" image quality (sensitivity>0.8) with a low rate of false positive detections (positive predictive value (PPV)>0.98). In cases of "low" image quality the approach had a decreased sensitivity (0.7-0.9), depending on the manual control counter. The PPV remained high (PPV>0.91). Compared to other automatic approaches the presented algorithm had a higher sensitivity and PPV. The used automatic foci detection algorithm was capable of detecting foci with high sensitivity and PPV. Thus it can be used for automatic analysis of images of varying quality.

Intra- and Inter-database Study for Arabic, English, and German Databases: Do Conventional Speech Features Detect Voice Pathology?

PubMed

Ali, Zulfiqar; Alsulaiman, Mansour; Muhammad, Ghulam; Elamvazuthi, Irraivan; Al-Nasheri, Ahmed; Mesallam, Tamer A; Farahat, Mohamed; Malki, Khalid H

2017-05-01

A large population around the world has voice complications. Various approaches for subjective and objective evaluations have been suggested in the literature. The subjective approach strongly depends on the experience and area of expertise of a clinician, and human error cannot be neglected. On the other hand, the objective or automatic approach is noninvasive. Automatic developed systems can provide complementary information that may be helpful for a clinician in the early screening of a voice disorder. At the same time, automatic systems can be deployed in remote areas where a general practitioner can use them and may refer the patient to a specialist to avoid complications that may be life threatening. Many automatic systems for disorder detection have been developed by applying different types of conventional speech features such as the linear prediction coefficients, linear prediction cepstral coefficients, and Mel-frequency cepstral coefficients (MFCCs). This study aims to ascertain whether conventional speech features detect voice pathology reliably, and whether they can be correlated with voice quality. To investigate this, an automatic detection system based on MFCC was developed, and three different voice disorder databases were used in this study. The experimental results suggest that the accuracy of the MFCC-based system varies from database to database. The detection rate for the intra-database ranges from 72% to 95%, and that for the inter-database is from 47% to 82%. The results conclude that conventional speech features are not correlated with voice, and hence are not reliable in pathology detection. Copyright © 2017 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Blotch removal for old movie restoration using epitome analysis

NASA Astrophysics Data System (ADS)

Rashwan, Abdullah M.

2011-10-01

Automatic blotch removal in old movies is important in film restoration. Blotches are black or white spots randomly occurring along the movie frames. Removing these spots are obtained by first automatically detecting the blotches then interpolating them using the spatial and temporal information in current, succeeding, and preceding frames. In this paper, simplified Rank Order Detector (sROD) is used with tweaked parameters to over detect the blotches, Epitome Analysis is used for interpolating the detected blotches.

The Infrared Automatic Mass Screening (IRAMS) System For Printed Circuit Board Fault Detection

NASA Astrophysics Data System (ADS)

Hugo, Perry W.

1987-05-01

Office of the Program Manager for TMDE (OPM TMDE) has initiated a program to develop techniques for evaluating the performance of printed circuit boards (PCB's) using infrared thermal imaging. It is OPM TMDE's expectation that the standard thermal profile (STP) will become the basis for the future rapid automatic detection and isolation of gross failure mechanisms on units under test (UUT's). To accomplish this OPM TMDE has purchased two Infrared Automatic Mass Screening ( I RAMS) systems which are scheduled for delivery in 1987. The IRAMS system combines a high resolution infrared thermal imager with a test bench and diagnostic computer hardware and software. Its purpose is to rapidly and automatically compare the thermal profiles of a UUT with the STP of that unit, recalled from memory, in order to detect thermally responsive failure mechanisms in PCB's. This paper will review the IRAMS performance requirements, outline the plan for implementing the two systems and report on progress to date.

Automatic detection of cardiac cycle and measurement of the mitral annulus diameter in 4D TEE images

NASA Astrophysics Data System (ADS)

Graser, Bastian; Hien, Maximilian; Rauch, Helmut; Meinzer, Hans-Peter; Heimann, Tobias

2012-02-01

Mitral regurgitation is a wide spread problem. For successful surgical treatment quantification of the mitral annulus, especially its diameter, is essential. Time resolved 3D transesophageal echocardiography (TEE) is suitable for this task. Yet, manual measurement in four dimensions is extremely time consuming, which confirms the need for automatic quantification methods. The method we propose is capable of automatically detecting the cardiac cycle (systole or diastole) for each time step and measuring the mitral annulus diameter. This is done using total variation noise filtering, the graph cut segmentation algorithm and morphological operators. An evaluation took place using expert measurements on 4D TEE data of 13 patients. The cardiac cycle was detected correctly on 78% of all images and the mitral annulus diameter was measured with an average error of 3.08 mm. Its full automatic processing makes the method easy to use in the clinical workflow and it provides the surgeon with helpful information.

Development of an Automatic Testing Platform for Aviator's Night Vision Goggle Honeycomb Defect Inspection.

PubMed

Jian, Bo-Lin; Peng, Chao-Chung

2017-06-15

Due to the direct influence of night vision equipment availability on the safety of night-time aerial reconnaissance, maintenance needs to be carried out regularly. Unfortunately, some defects are not easy to observe or are not even detectable by human eyes. As a consequence, this study proposed a novel automatic defect detection system for aviator's night vision imaging systems AN/AVS-6(V)1 and AN/AVS-6(V)2. An auto-focusing process consisting of a sharpness calculation and a gradient-based variable step search method is applied to achieve an automatic detection system for honeycomb defects. This work also developed a test platform for sharpness measurement. It demonstrates that the honeycomb defects can be precisely recognized and the number of the defects can also be determined automatically during the inspection. Most importantly, the proposed approach significantly reduces the time consumption, as well as human assessment error during the night vision goggle inspection procedures.

Automatic updating and 3D modeling of airport information from high resolution images using GIS and LIDAR data

NASA Astrophysics Data System (ADS)

Lv, Zheng; Sui, Haigang; Zhang, Xilin; Huang, Xianfeng

2007-11-01

As one of the most important geo-spatial objects and military establishment, airport is always a key target in fields of transportation and military affairs. Therefore, automatic recognition and extraction of airport from remote sensing images is very important and urgent for updating of civil aviation and military application. In this paper, a new multi-source data fusion approach on automatic airport information extraction, updating and 3D modeling is addressed. Corresponding key technologies including feature extraction of airport information based on a modified Ostu algorithm, automatic change detection based on new parallel lines-based buffer detection algorithm, 3D modeling based on gradual elimination of non-building points algorithm, 3D change detecting between old airport model and LIDAR data, typical CAD models imported and so on are discussed in detail. At last, based on these technologies, we develop a prototype system and the results show our method can achieve good effects.

Fully automatic detection and segmentation of abdominal aortic thrombus in post-operative CTA images using Deep Convolutional Neural Networks.

PubMed

López-Linares, Karen; Aranjuelo, Nerea; Kabongo, Luis; Maclair, Gregory; Lete, Nerea; Ceresa, Mario; García-Familiar, Ainhoa; Macía, Iván; González Ballester, Miguel A

2018-05-01

Computerized Tomography Angiography (CTA) based follow-up of Abdominal Aortic Aneurysms (AAA) treated with Endovascular Aneurysm Repair (EVAR) is essential to evaluate the progress of the patient and detect complications. In this context, accurate quantification of post-operative thrombus volume is required. However, a proper evaluation is hindered by the lack of automatic, robust and reproducible thrombus segmentation algorithms. We propose a new fully automatic approach based on Deep Convolutional Neural Networks (DCNN) for robust and reproducible thrombus region of interest detection and subsequent fine thrombus segmentation. The DetecNet detection network is adapted to perform region of interest extraction from a complete CTA and a new segmentation network architecture, based on Fully Convolutional Networks and a Holistically-Nested Edge Detection Network, is presented. These networks are trained, validated and tested in 13 post-operative CTA volumes of different patients using a 4-fold cross-validation approach to provide more robustness to the results. Our pipeline achieves a Dice score of more than 82% for post-operative thrombus segmentation and provides a mean relative volume difference between ground truth and automatic segmentation that lays within the experienced human observer variance without the need of human intervention in most common cases. Copyright © 2018 Elsevier B.V. All rights reserved.

Total-body photography in skin cancer screening: the clinical utility of standardized imaging.

PubMed

Rosenberg, Alexandra; Meyerle, Jon H

2017-05-01

Early detection of skin cancer is essential to reducing morbidity and mortality from both melanoma and nonmelanoma skin cancers. Total-body skin examinations (TBSEs) may improve early detection of malignant melanomas (MMs) but are controversial due to the poor quality of data available to establish a mortality benefit from skin cancer screening. Total-body photography (TBP) promises to provide a way forward by lowering the costs of dermatologic screening while simultaneously leveraging technology to increase patient access to dermatologic care. Standardized TBP also offers the ability for dermatologists to work synergistically with modern computer technology involving algorithms capable of analyzing high-quality images to flag concerning lesions that may require closer evaluation. On a population level, inexpensive TBP has the potential to increase access to skin cancer screening and it has several specific applications in a military population. The utility of standardized TBP is reviewed in the context of skin cancer screening and teledermatology.

Three-dimensional multispectral optoacoustic mesoscopy reveals melanin and blood oxygenation in human skin in vivo.

PubMed

Schwarz, Mathias; Buehler, Andreas; Aguirre, Juan; Ntziachristos, Vasilis

2016-01-01

Optical imaging plays a major role in disease detection in dermatology. However, current optical methods are limited by lack of three-dimensional detection of pathophysiological parameters within skin. It was recently shown that single-wavelength optoacoustic (photoacoustic) mesoscopy resolves skin morphology, i.e. melanin and blood vessels within epidermis and dermis. In this work we employed illumination at multiple wavelengths for enabling three-dimensional multispectral optoacoustic mesoscopy (MSOM) of natural chromophores in human skin in vivo operating at 15-125 MHz. We employ a per-pulse tunable laser to inherently co-register spectral datasets, and reveal previously undisclosed insights of melanin, and blood oxygenation in human skin. We further reveal broadband absorption spectra of specific skin compartments. We discuss the potential of MSOM for label-free visualization of physiological biomarkers in skin in vivo. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Influence of skin type and wavelength on light wave reflectance.

PubMed

Fallow, Bennett A; Tarumi, Takashi; Tanaka, Hirofumi

2013-06-01

A new application of photoplethysmography (PPG) has emerged recently to provide the possibility of heart rate monitoring without a telemetric chest strap. The aim of this study was to determine if a new device could detect pulsation over a broad range of skin types, and what light wavelength would be most suitable for detecting the signals. A light emitting diode-based PPG system was used to detect changes in pulsatile blood flow on 23 apparently healthy individuals (11 male and 12 female, 20-59 years old) of varying skin types classified according to a questionnaire in combination with digital photographs with a skin type chart. Four different light wavelengths (470, 520, 630, and 880 nm) were tested. Normalized modulation level is calculated as the AC/DC component ratio and represents the change in flow over the underlying constant state of flow or perfusion. In the resting condition, green light wavelength (520 nm) displayed greater modulation (p < 0.001) than all the other wavelengths analyzed regardless of skin types. Type V (dark brown) skin type was significantly lower in modulation than all other skin types. In the exercise condition, both blue (470 nm) and green (520 nm) light wavelengths displayed greater signal-to-noise ratios than red (630 nm) or infrared (880 nm) light wavelengths (p < 0.001). We concluded that a PPG-based device can detect pulsation across all skin types and that a greater resolution was obtained using a green light wavelength at rest and a green or blue light wavelength during exercise.

An Analysis of the Malassezia Species Distribution in the Skin of Patients with Pityriasis Versicolor in Chengdu, China

PubMed Central

Xie, Zhen; Ran, Yuping; Zhang, Hao; Zhang, Min; Wan, Huiying; Li, Conghui

2014-01-01

Pityriasis versicolor (PV) is a common clinical problem associated with Malassezia species (Malassezia spp.). Controversies remain regarding the specific species involved in the development of PV. This study analyzed the difference in Malassezia spp. distribution in lesional and nonlesional skin in Chinese PV patients. A paired design was applied. Lesional and nonlesional scales from 24 cases were collected; real-time fluorescence quantitative PCR was used to detect 10 different Malassezia spp. In lesional skin, the highest detection rates were for M. globosa (95.8%), M. restricta (91.7%), and M. sympodialis (50.0%). In nonlesional skin, the highest detection rates were for M. globosa (87.5%), M. restricta (79.2%), and M. dermatis (33.3%). A significant difference in the detection rate was only found for M. sympodialis (50.8% versus 20.8%, P = 0.04). Compared with nonlesional skin, the amount of M. globosa, M. restricta, and M. sympodialis in lesional skin was significantly higher (3.8 ± 1.3,  2.5 ± 1.1, and 3.2 ± 1.6 times higher, resp.). The results of this study do not indicate that M. globosa and M. restricta are directly correlated with PV development; however, M. sympodialis is more likely related to PV development in Chinese individuals. PMID:25177714

An analysis of the Malassezia species distribution in the skin of patients with pityriasis versicolor in Chengdu, China.

PubMed

Xie, Zhen; Ran, Yuping; Zhang, Hao; Zhang, Min; Wan, Huiying; Li, Conghui

2014-01-01

Pityriasis versicolor (PV) is a common clinical problem associated with Malassezia species (Malassezia spp.). Controversies remain regarding the specific species involved in the development of PV. This study analyzed the difference in Malassezia spp. distribution in lesional and nonlesional skin in Chinese PV patients. A paired design was applied. Lesional and nonlesional scales from 24 cases were collected; real-time fluorescence quantitative PCR was used to detect 10 different Malassezia spp. In lesional skin, the highest detection rates were for M. globosa (95.8%), M. restricta (91.7%), and M. sympodialis (50.0%). In nonlesional skin, the highest detection rates were for M. globosa (87.5%), M. restricta (79.2%), and M. dermatis (33.3%). A significant difference in the detection rate was only found for M. sympodialis (50.8% versus 20.8%, P = 0.04). Compared with nonlesional skin, the amount of M. globosa, M. restricta, and M. sympodialis in lesional skin was significantly higher (3.8 ± 1.3,  2.5 ± 1.1, and 3.2 ± 1.6 times higher, resp.). The results of this study do not indicate that M. globosa and M. restricta are directly correlated with PV development; however, M. sympodialis is more likely related to PV development in Chinese individuals.

Comprehensive Monte-Carlo simulator for optimization of imaging parameters for high sensitivity detection of skin cancer at the THz

NASA Astrophysics Data System (ADS)

Ney, Michael; Abdulhalim, Ibrahim

2016-03-01

Skin cancer detection at its early stages has been the focus of a large number of experimental and theoretical studies during the past decades. Among these studies two prominent approaches presenting high potential are reflectometric sensing at the THz wavelengths region and polarimetric imaging techniques in the visible wavelengths. While THz radiation contrast agent and source of sensitivity to cancer related tissue alterations was considered to be mainly the elevated water content in the cancerous tissue, the polarimetric approach has been verified to enable cancerous tissue differentiation based on cancer induced structural alterations to the tissue. Combining THz with the polarimetric approach, which is considered in this study, is examined in order to enable higher detection sensitivity than previously pure reflectometric THz measurements. For this, a comprehensive MC simulation of radiative transfer in a complex skin tissue model fitted for the THz domain that considers the skin`s stratified structure, tissue material optical dispersion modeling, surface roughness, scatterers, and substructure organelles has been developed. Additionally, a narrow beam Mueller matrix differential analysis technique is suggested for assessing skin cancer induced changes in the polarimetric image, enabling the tissue model and MC simulation to be utilized for determining the imaging parameters resulting in maximal detection sensitivity.

Skin blotting: a noninvasive technique for evaluating physiological skin status.

PubMed

Minematsu, Takeo; Horii, Motoko; Oe, Makoto; Sugama, Junko; Mugita, Yuko; Huang, Lijuan; Nakagami, Gojiro; Sanada, Hiromi

2014-06-01

The skin performs important structural and physiological functions, and skin assessment represents an important step in identifying skin problems. Although noninvasive techniques for assessing skin status exist, no such techniques for monitoring its physiological status are available. This study aimed to develop a novel skin-assessment technique known as skin blotting, based on the leakage of secreted proteins from inside the skin following overhydration in mice. The applicability of this technique was further investigated in a clinical setting. Skin blotting involves 2 steps: collecting proteins by attaching a damp nitrocellulose membrane to the surface of the skin, and immunostaining the collected proteins. The authors implanted fluorescein-conjugated dextran (F-DEX)-containing agarose gels into mice and detected the tissue distribution of F-DEX under different blotting conditions. They also analyzed the correlations between inflammatory cytokine secretion and leakage following ultraviolet irradiation in mice and in relation to body mass index in humans. The F-DEX in mice was distributed in the deeper and shallower layers of skin and leaked through the transfollicular and transepidermal routes, respectively. Ultraviolet irradiation induced tumor necrosis factor secretion in the epidermis in mice, which was detected by skin blotting, whereas follicular tumor necrosis factor was associated with body mass index in obese human subjects. These results support the applicability of skin blotting for skin assessment. Skin blotting represents a noninvasive technique for assessing skin physiology and has potential as a predictive and diagnostic tool for skin disorders.

Automatic visibility retrieval from thermal camera images

NASA Astrophysics Data System (ADS)

Dizerens, Céline; Ott, Beat; Wellig, Peter; Wunderle, Stefan

2017-10-01

This study presents an automatic visibility retrieval of a FLIR A320 Stationary Thermal Imager installed on a measurement tower on the mountain Lagern located in the Swiss Jura Mountains. Our visibility retrieval makes use of edges that are automatically detected from thermal camera images. Predefined target regions, such as mountain silhouettes or buildings with high thermal differences to the surroundings, are used to derive the maximum visibility distance that is detectable in the image. To allow a stable, automatic processing, our procedure additionally removes noise in the image and includes automatic image alignment to correct small shifts of the camera. We present a detailed analysis of visibility derived from more than 24000 thermal images of the years 2015 and 2016 by comparing them to (1) visibility derived from a panoramic camera image (VISrange), (2) measurements of a forward-scatter visibility meter (Vaisala FD12 working in the NIR spectra), and (3) modeled visibility values using the Thermal Range Model TRM4. Atmospheric conditions, mainly water vapor from European Center for Medium Weather Forecast (ECMWF), were considered to calculate the extinction coefficients using MODTRAN. The automatic visibility retrieval based on FLIR A320 images is often in good agreement with the retrieval from the systems working in different spectral ranges. However, some significant differences were detected as well, depending on weather conditions, thermal differences of the monitored landscape, and defined target size.

Automated feature detection and identification in digital point-ordered signals

DOEpatents

Oppenlander, Jane E.; Loomis, Kent C.; Brudnoy, David M.; Levy, Arthur J.

1998-01-01

A computer-based automated method to detect and identify features in digital point-ordered signals. The method is used for processing of non-destructive test signals, such as eddy current signals obtained from calibration standards. The signals are first automatically processed to remove noise and to determine a baseline. Next, features are detected in the signals using mathematical morphology filters. Finally, verification of the features is made using an expert system of pattern recognition methods and geometric criteria. The method has the advantage that standard features can be, located without prior knowledge of the number or sequence of the features. Further advantages are that standard features can be differentiated from irrelevant signal features such as noise, and detected features are automatically verified by parameters extracted from the signals. The method proceeds fully automatically without initial operator set-up and without subjective operator feature judgement.

Multisource oil spill detection

NASA Astrophysics Data System (ADS)

Salberg, Arnt B.; Larsen, Siri O.; Zortea, Maciel

2013-10-01

In this paper we discuss how multisource data (wind, ocean-current, optical, bathymetric, automatic identification systems (AIS)) may be used to improve oil spill detection in SAR images, with emphasis on the use of automatic oil spill detection algorithms. We focus particularly on AIS, optical, and bathymetric data. For the AIS data we propose an algorithm for integrating AIS ship tracks into automatic oil spill detection in order to improve the confidence estimate of a potential oil spill. We demonstrate the use of ancillary data on a set of SAR images. Regarding the use of optical data, we did not observe a clear correspondence between high chlorophyll values (estimated from products derived from optical data) and observed slicks in the SAR image. Bathymetric data was shown to be a good data source for removing false detections caused by e.g. sand banks on low tide. For the AIS data we observed that a polluter could be identified for some dark slicks, however, a precise oil drift model is needed in order to identify the polluter with high certainty.

Automatic construction of a recurrent neural network based classifier for vehicle passage detection

NASA Astrophysics Data System (ADS)

Burnaev, Evgeny; Koptelov, Ivan; Novikov, German; Khanipov, Timur

2017-03-01

Recurrent Neural Networks (RNNs) are extensively used for time-series modeling and prediction. We propose an approach for automatic construction of a binary classifier based on Long Short-Term Memory RNNs (LSTM-RNNs) for detection of a vehicle passage through a checkpoint. As an input to the classifier we use multidimensional signals of various sensors that are installed on the checkpoint. Obtained results demonstrate that the previous approach to handcrafting a classifier, consisting of a set of deterministic rules, can be successfully replaced by an automatic RNN training on an appropriately labelled data.

Changes in Women’s Facial Skin Color over the Ovulatory Cycle are Not Detectable by the Human Visual System

PubMed Central

Burriss, Robert P.; Troscianko, Jolyon; Lovell, P. George; Fulford, Anthony J. C.; Stevens, Martin; Quigley, Rachael; Payne, Jenny; Saxton, Tamsin K.; Rowland, Hannah M.

2015-01-01

Human ovulation is not advertised, as it is in several primate species, by conspicuous sexual swellings. However, there is increasing evidence that the attractiveness of women’s body odor, voice, and facial appearance peak during the fertile phase of their ovulatory cycle. Cycle effects on facial attractiveness may be underpinned by changes in facial skin color, but it is not clear if skin color varies cyclically in humans or if any changes are detectable. To test these questions we photographed women daily for at least one cycle. Changes in facial skin redness and luminance were then quantified by mapping the digital images to human long, medium, and shortwave visual receptors. We find cyclic variation in skin redness, but not luminance. Redness decreases rapidly after menstrual onset, increases in the days before ovulation, and remains high through the luteal phase. However, we also show that this variation is unlikely to be detectable by the human visual system. We conclude that changes in skin color are not responsible for the effects of the ovulatory cycle on women’s attractiveness. PMID:26134671

Changes in Women's Facial Skin Color over the Ovulatory Cycle are Not Detectable by the Human Visual System.

PubMed

Burriss, Robert P; Troscianko, Jolyon; Lovell, P George; Fulford, Anthony J C; Stevens, Martin; Quigley, Rachael; Payne, Jenny; Saxton, Tamsin K; Rowland, Hannah M

2015-01-01

Human ovulation is not advertised, as it is in several primate species, by conspicuous sexual swellings. However, there is increasing evidence that the attractiveness of women's body odor, voice, and facial appearance peak during the fertile phase of their ovulatory cycle. Cycle effects on facial attractiveness may be underpinned by changes in facial skin color, but it is not clear if skin color varies cyclically in humans or if any changes are detectable. To test these questions we photographed women daily for at least one cycle. Changes in facial skin redness and luminance were then quantified by mapping the digital images to human long, medium, and shortwave visual receptors. We find cyclic variation in skin redness, but not luminance. Redness decreases rapidly after menstrual onset, increases in the days before ovulation, and remains high through the luteal phase. However, we also show that this variation is unlikely to be detectable by the human visual system. We conclude that changes in skin color are not responsible for the effects of the ovulatory cycle on women's attractiveness.

In vivo stepwise multi-photon activation fluorescence imaging of melanin in human skin

NASA Astrophysics Data System (ADS)

Lai, Zhenhua; Gu, Zetong; Abbas, Saleh; Lowe, Jared; Sierra, Heidy; Rajadhyaksha, Milind; DiMarzio, Charles

2014-03-01

The stepwise multi-photon activated fluorescence (SMPAF) of melanin is a low cost and reliable method of detecting melanin because the activation and excitation can be a continuous-wave (CW) mode near infrared (NIR) laser. Our previous work has demonstrated the melanin SMPAF images in sepia melanin, mouse hair, and mouse skin. In this study, we show the feasibility of using SMPAF to detect melanin in vivo. in vivo melanin SMPAF images of normal skin and benign nevus are demonstrated. SMPAF images add specificity for melanin detection than MPFM images and CRM images. Melanin SMPAF is a promising technology to enable early detection of melanoma for dermatologists.

[Study of automatic marine oil spills detection using imaging spectroscopy].

PubMed

Liu, De-Lian; Han, Liang; Zhang, Jian-Qi

2013-11-01

To reduce artificial auxiliary works in oil spills detection process, an automatic oil spill detection method based on adaptive matched filter is presented. Firstly, the characteristics of reflectance spectral signature of C-H bond in oil spill are analyzed. And an oil spill spectral signature extraction model is designed by using the spectral feature of C-H bond. It is then used to obtain the reference spectral signature for the following oil spill detection step. Secondly, the characteristics of reflectance spectral signature of sea water, clouds, and oil spill are compared. The bands which have large difference in reflectance spectral signatures of the sea water, clouds, and oil spill are selected. By using these bands, the sea water pixels are segmented. And the background parameters are then calculated. Finally, the classical adaptive matched filter from target detection algorithms is improved and introduced for oil spill detection. The proposed method is applied to the real airborne visible infrared imaging spectrometer (AVIRIS) hyperspectral image captured during the deepwater horizon oil spill in the Gulf of Mexico for oil spill detection. The results show that the proposed method has, high efficiency, does not need artificial auxiliary work, and can be used for automatic detection of marine oil spill.

Detection and measurement of fetal anatomies from ultrasound images using a constrained probabilistic boosting tree.

PubMed

Carneiro, Gustavo; Georgescu, Bogdan; Good, Sara; Comaniciu, Dorin

2008-09-01

We propose a novel method for the automatic detection and measurement of fetal anatomical structures in ultrasound images. This problem offers a myriad of challenges, including: difficulty of modeling the appearance variations of the visual object of interest, robustness to speckle noise and signal dropout, and large search space of the detection procedure. Previous solutions typically rely on the explicit encoding of prior knowledge and formulation of the problem as a perceptual grouping task solved through clustering or variational approaches. These methods are constrained by the validity of the underlying assumptions and usually are not enough to capture the complex appearances of fetal anatomies. We propose a novel system for fast automatic detection and measurement of fetal anatomies that directly exploits a large database of expert annotated fetal anatomical structures in ultrasound images. Our method learns automatically to distinguish between the appearance of the object of interest and background by training a constrained probabilistic boosting tree classifier. This system is able to produce the automatic segmentation of several fetal anatomies using the same basic detection algorithm. We show results on fully automatic measurement of biparietal diameter (BPD), head circumference (HC), abdominal circumference (AC), femur length (FL), humerus length (HL), and crown rump length (CRL). Notice that our approach is the first in the literature to deal with the HL and CRL measurements. Extensive experiments (with clinical validation) show that our system is, on average, close to the accuracy of experts in terms of segmentation and obstetric measurements. Finally, this system runs under half second on a standard dual-core PC computer.

Automatic Contour Tracking in Ultrasound Images

ERIC Educational Resources Information Center

Li, Min; Kambhamettu, Chandra; Stone, Maureen

2005-01-01

In this paper, a new automatic contour tracking system, EdgeTrak, for the ultrasound image sequences of human tongue is presented. The images are produced by a head and transducer support system (HATS). The noise and unrelated high-contrast edges in ultrasound images make it very difficult to automatically detect the correct tongue surfaces. In…

The Potential of Automatic Word Comparison for Historical Linguistics.

PubMed

List, Johann-Mattis; Greenhill, Simon J; Gray, Russell D

2017-01-01

The amount of data from languages spoken all over the world is rapidly increasing. Traditional manual methods in historical linguistics need to face the challenges brought by this influx of data. Automatic approaches to word comparison could provide invaluable help to pre-analyze data which can be later enhanced by experts. In this way, computational approaches can take care of the repetitive and schematic tasks leaving experts to concentrate on answering interesting questions. Here we test the potential of automatic methods to detect etymologically related words (cognates) in cross-linguistic data. Using a newly compiled database of expert cognate judgments across five different language families, we compare how well different automatic approaches distinguish related from unrelated words. Our results show that automatic methods can identify cognates with a very high degree of accuracy, reaching 89% for the best-performing method Infomap. We identify the specific strengths and weaknesses of these different methods and point to major challenges for future approaches. Current automatic approaches for cognate detection-although not perfect-could become an important component of future research in historical linguistics.

Automatic Mexico Gulf Oil Spill Detection from Radarsat-2 SAR Satellite Data Using Genetic Algorithm

NASA Astrophysics Data System (ADS)

Marghany, Maged

2016-10-01

In this work, a genetic algorithm is exploited for automatic detection of oil spills of small and large size. The route is achieved using arrays of RADARSAT-2 SAR ScanSAR Narrow single beam data obtained in the Gulf of Mexico. The study shows that genetic algorithm has automatically segmented the dark spot patches related to small and large oil spill pixels. This conclusion is confirmed by the receiveroperating characteristic (ROC) curve and ground data which have been documented. The ROC curve indicates that the existence of oil slick footprints can be identified with the area under the curve between the ROC curve and the no-discrimination line of 90%, which is greater than that of other surrounding environmental features. The small oil spill sizes represented 30% of the discriminated oil spill pixels in ROC curve. In conclusion, the genetic algorithm can be used as a tool for the automatic detection of oil spills of either small or large size and the ScanSAR Narrow single beam mode serves as an excellent sensor for oil spill patterns detection and surveying in the Gulf of Mexico.

[A wavelet-transform-based method for the automatic detection of late-type stars].

PubMed

Liu, Zhong-tian; Zhao, Rrui-zhen; Zhao, Yong-heng; Wu, Fu-chao

2005-07-01

The LAMOST project, the world largest sky survey project, urgently needs an automatic late-type stars detection system. However, to our knowledge, no effective methods for automatic late-type stars detection have been reported in the literature up to now. The present study work is intended to explore possible ways to deal with this issue. Here, by "late-type stars" we mean those stars with strong molecule absorption bands, including oxygen-rich M, L and T type stars and carbon-rich C stars. Based on experimental results, the authors find that after a wavelet transform with 5 scales on the late-type stars spectra, their frequency spectrum of the transformed coefficient on the 5th scale consistently manifests a unimodal distribution, and the energy of frequency spectrum is largely concentrated on a small neighborhood centered around the unique peak. However, for the spectra of other celestial bodies, the corresponding frequency spectrum is of multimodal and the energy of frequency spectrum is dispersible. Based on such a finding, the authors presented a wavelet-transform-based automatic late-type stars detection method. The proposed method is shown by extensive experiments to be practical and of good robustness.

Mercury and hydroquinone content of skin toning creams and cosmetic soaps, and the potential risks to the health of Ghanaian women.

PubMed

Agorku, Eric Selorm; Kwaansa-Ansah, Edward Ebow; Voegborlo, Ray Bright; Amegbletor, Pamela; Opoku, Francis

2016-01-01

In this study, sixty-two (62) skin-lightening creams and soaps were analysed for total mercury and hydroquinone levels. Total mercury was determined by the Cold Vapour Atomic Absorption Spectrophotometry using an automatic mercury analyser and hydroquinone by High Performance Liquid Chromatography. The mean concentration of total mercury in skin toning creams and cosmetic soaps were 0.098 ± 0.082 and 0.152 ± 0.126 μg/g, respectively. The mean concentration of hydroquinone was 0.243 ± 0.385 and 0.035 ± 0.021 % in skin toning creams and cosmetic soaps, respectively. All the creams and soaps analysed had mercury and hydroquinone levels below the US Food and Drug Administration's acceptable limit of 1 μg/g and 2 %, respectively. The low levels of mercury and hydroquinone in the creams and soaps analysed in this study therefore do not pose any potential risk to consumers who are mostly women in Ghana.

Needle-free injection of insulin powder: delivery efficiency and skin irritation assessment.

PubMed

Li, Chun-yu; Wang, Zhe-wei; Tu, Can; Wang, Jia-bo; Jiang, Bing-qian; Li, Qi; Zeng, Ling-na; Ma, Zhi-jie; Zhang, Ping; Zhao, Yan-ling; Zhang, Ya-ming; Yan, Dan; Tan, Rui; Xiao, Xiao-he

2014-10-01

Insulin is widely used in treating diabetes, but still needs to be administered by needle injection. This study investigated a new needle-free approach for insulin delivery. A portable powder needleless injection (PNI) device with an automatic mechanical unit was designed. Its efficiency in delivering insulin was evaluated in alloxan-induced diabetic rabbits. The skin irritation caused by the device was investigated and the results were analyzed in relation to aerodynamic parameters. Inorganic salt-carried insulin powders had hypoglycemic effects, while raw insulin powders were not effective when delivered by PNI, indicating that salt carriers play an important role in the delivery of insulin via PNI. The relative delivery efficiency of phosphate-carried insulin powder using the PNI device was 72.25%. A safety assessment test showed that three key factors (gas pressure, cylinder volume, and nozzle distance) were related to the amount of skin irritation caused by the PNI device. Optimized injection conditions caused minimal skin lesions and are safe to use in practice. The results suggest that PNI has promising prospects as a novel technology for delivering insulin and other biological drugs.

Needle-free injection of insulin powder: delivery efficiency and skin irritation assessment*

PubMed Central

Li, Chun-yu; Wang, Zhe-wei; Tu, Can; Wang, Jia-bo; Jiang, Bing-qian; Li, Qi; Zeng, Ling-na; Ma, Zhi-jie; Zhang, Ping; Zhao, Yan-ling; Zhang, Ya-ming; Yan, Dan; Tan, Rui; Xiao, Xiao-he

2014-01-01

Insulin is widely used in treating diabetes, but still needs to be administered by needle injection. This study investigated a new needle-free approach for insulin delivery. A portable powder needleless injection (PNI) device with an automatic mechanical unit was designed. Its efficiency in delivering insulin was evaluated in alloxan-induced diabetic rabbits. The skin irritation caused by the device was investigated and the results were analyzed in relation to aerodynamic parameters. Inorganic salt-carried insulin powders had hypoglycemic effects, while raw insulin powders were not effective when delivered by PNI, indicating that salt carriers play an important role in the delivery of insulin via PNI. The relative delivery efficiency of phosphate-carried insulin powder using the PNI device was 72.25%. A safety assessment test showed that three key factors (gas pressure, cylinder volume, and nozzle distance) were related to the amount of skin irritation caused by the PNI device. Optimized injection conditions caused minimal skin lesions and are safe to use in practice. The results suggest that PNI has promising prospects as a novel technology for delivering insulin and other biological drugs. PMID:25294378

Raman spectroscopic measurements of beta-carotene and lycopene in human skin

NASA Astrophysics Data System (ADS)

Darvin, M. E.; Gerzonde, I.; Ey, S.; Brandt, Nikolai N.; Albrecht, Hansjoerg; Gonchukov, Sergei A.; Sterry, Wolfram; Lademann, Juergen

2004-08-01

The antioxidant β-carotene and lycopene substances were detected non-invasively, in vivo in human skin using resonance Raman spectroscopy. Both substances were detected simultaneously. To distinguish between the substances, the Raman signals were excited at 488 nm and 514,5 nm simultaneously using a multilane Ar+ laser. The application of a fiber based optical imaging system allowed the detection of β-carotene and lycopene on any skin area. The disturbance of the measurements because of non-homogeneous skin pigmentation was avoided by using a measuring area of 28 mm2. The minimum power density for registration of the Raman signals and their optimum relation was determined. The Raman spectroscopic method is well suited for the evaluation of the efficacy of topically or systematically applied amounts of β-carotene and lycopene.

LABONFOIL: investigations regarding microfluidic skin patches for drug detection using flexible OLEDs

NASA Astrophysics Data System (ADS)

Scholles, M.; Kroker, L.; Vogel, U.; Krüger, J.; Walczak, R.; Ruano-Lopez, J.

2010-02-01

This contribution describes first results concerning the overall and especially optical system design of microfluidic skin patches for drug detection based on fluorescence analysis of sweat samples. This work has been carried out within the European project LABONFOIL which aims to develop low-cost lab-on-chip systems for four different applications, one of them for the detection of cocaine abuse by professional drivers. To date work has focused on the integrated design of the skin patch itself including methods for sweat collection as well as studies concerning the feasibility of OLEDs for optical excitation of the fluorescence signal.

Detection of melanomas by digital imaging of spectrally resolved UV light-induced autofluorescence of human skin

NASA Astrophysics Data System (ADS)

Chwirot, B. W.; Chwirot, S.; Jedrzejczyk, W.; Redzinski, J.; Raczynska, A. M.; Telega, K.

2001-07-01

We studied spectral and spatial distributions of the intensity of the ultraviolet light-excited fluorescence of human skin. Our studied performed in situ in 162 patients with malignant and non-malignant skin lesions resulted in a new method of detecting melanomas in situ using digital imaging of the spectrally resolved fluorescence. With our diagnostic algorithm we could successfully detect 88.5% of the cases of melanoma in the group of patients subject to examinations with the fluorescence method. A patent application for the method has been submitted to the Patent Office in Warsaw.

Perception-based 3D tactile rendering from a single image for human skin examinations by dynamic touch.

PubMed

Kim, K; Lee, S

2015-05-01

Diagnosis of skin conditions is dependent on the assessment of skin surface properties that are represented by more tactile properties such as stiffness, roughness, and friction than visual information. Due to this reason, adding tactile feedback to existing vision based diagnosis systems can help dermatologists diagnose skin diseases or disorders more accurately. The goal of our research was therefore to develop a tactile rendering system for skin examinations by dynamic touch. Our development consists of two stages: converting a single image to a 3D haptic surface and rendering the generated haptic surface in real-time. Converting to 3D surfaces from 2D single images was implemented with concerning human perception data collected by a psychophysical experiment that measured human visual and haptic sensibility to 3D skin surface changes. For the second stage, we utilized real skin biomechanical properties found by prior studies. Our tactile rendering system is a standalone system that can be used with any single cameras and haptic feedback devices. We evaluated the performance of our system by conducting an identification experiment with three different skin images with five subjects. The participants had to identify one of the three skin surfaces by using a haptic device (Falcon) only. No visual cue was provided for the experiment. The results indicate that our system provides sufficient performance to render discernable tactile rendering with different skin surfaces. Our system uses only a single skin image and automatically generates a 3D haptic surface based on human haptic perception. Realistic skin interactions can be provided in real-time for the purpose of skin diagnosis, simulations, or training. Our system can also be used for other applications like virtual reality and cosmetic applications. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Evaluation of an automatic MR-based gold fiducial marker localisation method for MR-only prostate radiotherapy

NASA Astrophysics Data System (ADS)

Maspero, Matteo; van den Berg, Cornelis A. T.; Zijlstra, Frank; Sikkes, Gonda G.; de Boer, Hans C. J.; Meijer, Gert J.; Kerkmeijer, Linda G. W.; Viergever, Max A.; Lagendijk, Jan J. W.; Seevinck, Peter R.

2017-10-01

An MR-only radiotherapy planning (RTP) workflow would reduce the cost, radiation exposure and uncertainties introduced by CT-MRI registrations. In the case of prostate treatment, one of the remaining challenges currently holding back the implementation of an RTP workflow is the MR-based localisation of intraprostatic gold fiducial markers (FMs), which is crucial for accurate patient positioning. Currently, MR-based FM localisation is clinically performed manually. This is sub-optimal, as manual interaction increases the workload. Attempts to perform automatic FM detection often rely on being able to detect signal voids induced by the FMs in magnitude images. However, signal voids may not always be sufficiently specific, hampering accurate and robust automatic FM localisation. Here, we present an approach that aims at automatic MR-based FM localisation. This method is based on template matching using a library of simulated complex-valued templates, and exploiting the behaviour of the complex MR signal in the vicinity of the FM. Clinical evaluation was performed on seventeen prostate cancer patients undergoing external beam radiotherapy treatment. Automatic MR-based FM localisation was compared to manual MR-based and semi-automatic CT-based localisation (the current gold standard) in terms of detection rate and the spatial accuracy and precision of localisation. The proposed method correctly detected all three FMs in 15/17 patients. The spatial accuracy (mean) and precision (STD) were 0.9 mm and 0.5 mm respectively, which is below the voxel size of 1.1 × 1.1 × 1.2 mm3 and comparable to MR-based manual localisation. FM localisation failed (3/51 FMs) in the presence of bleeding or calcifications in the direct vicinity of the FM. The method was found to be spatially accurate and precise, which is essential for clinical use. To overcome any missed detection, we envision the use of the proposed method along with verification by an observer. This will result in a semi-automatic workflow facilitating the introduction of an MR-only workflow.

Discovery and Targeted Proteomics on Cutaneous Biopsies Infected by Borrelia to Investigate Lyme Disease*

PubMed Central

Schnell, Gilles; Boeuf, Amandine; Westermann, Benoît; Jaulhac, Benoît; Lipsker, Dan; Carapito, Christine; Boulanger, Nathalie; Ehret-Sabatier, Laurence

2015-01-01

Lyme disease is the most important vector-borne disease in the Northern hemisphere and represents a major public health challenge with insufficient means of reliable diagnosis. Skin is rarely investigated in proteomics but constitutes in the case of Lyme disease the key interface where the pathogens can enter, persist, and multiply. Therefore, we investigated proteomics on skin samples to detect Borrelia proteins directly in cutaneous biopsies in a robust and specific way. We first set up a discovery gel prefractionation-LC-MS/MS approach on a murine model infected by Borrelia burgdorferi sensu stricto that allowed the identification of 25 Borrelia proteins among more than 1300 mouse proteins. Then we developed a targeted gel prefractionation-LC-selected reaction monitoring (SRM) assay to detect 9/33 Borrelia proteins/peptides in mouse skin tissue samples using heavy labeled synthetic peptides. We successfully transferred this assay from the mouse model to human skin biopsies (naturally infected by Borrelia), and we were able to detect two Borrelia proteins: OspC and flagellin. Considering the extreme variability of OspC, we developed an extended SRM assay to target a large set of variants. This assay afforded the detection of nine peptides belonging to either OspC or flagellin in human skin biopsies. We further shortened the sample preparation and showed that Borrelia is detectable in mouse and human skin biopsies by directly using a liquid digestion followed by LC-SRM analysis without any prefractionation. This study thus shows that a targeted SRM approach is a promising tool for the early direct diagnosis of Lyme disease with high sensitivity (<10 fmol of OspC/mg of human skin biopsy). PMID:25713121

Automatic detection and recognition of signs from natural scenes.

PubMed

Chen, Xilin; Yang, Jie; Zhang, Jing; Waibel, Alex

2004-01-01

In this paper, we present an approach to automatic detection and recognition of signs from natural scenes, and its application to a sign translation task. The proposed approach embeds multiresolution and multiscale edge detection, adaptive searching, color analysis, and affine rectification in a hierarchical framework for sign detection, with different emphases at each phase to handle the text in different sizes, orientations, color distributions and backgrounds. We use affine rectification to recover deformation of the text regions caused by an inappropriate camera view angle. The procedure can significantly improve text detection rate and optical character recognition (OCR) accuracy. Instead of using binary information for OCR, we extract features from an intensity image directly. We propose a local intensity normalization method to effectively handle lighting variations, followed by a Gabor transform to obtain local features, and finally a linear discriminant analysis (LDA) method for feature selection. We have applied the approach in developing a Chinese sign translation system, which can automatically detect and recognize Chinese signs as input from a camera, and translate the recognized text into English.

SU-G-JeP4-03: Anomaly Detection of Respiratory Motion by Use of Singular Spectrum Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kotoku, J; Kumagai, S; Nakabayashi, S

Purpose: The implementation and realization of automatic anomaly detection of respiratory motion is a very important technique to prevent accidental damage during radiation therapy. Here, we propose an automatic anomaly detection method using singular value decomposition analysis. Methods: The anomaly detection procedure consists of four parts:1) measurement of normal respiratory motion data of a patient2) calculation of a trajectory matrix representing normal time-series feature3) real-time monitoring and calculation of a trajectory matrix of real-time data.4) calculation of an anomaly score from the similarity of the two feature matrices. Patient motion was observed by a marker-less tracking system using a depthmore » camera. Results: Two types of motion e.g. cough and sudden stop of breathing were successfully detected in our real-time application. Conclusion: Automatic anomaly detection of respiratory motion using singular spectrum analysis was successful in the cough and sudden stop of breathing. The clinical use of this algorithm will be very hopeful. This work was supported by JSPS KAKENHI Grant Number 15K08703.« less

Quantification of regional fat volume in rat MRI

NASA Astrophysics Data System (ADS)

Sacha, Jaroslaw P.; Cockman, Michael D.; Dufresne, Thomas E.; Trokhan, Darren

2003-05-01

Multiple initiatives in the pharmaceutical and beauty care industries are directed at identifying therapies for weight management. Body composition measurements are critical for such initiatives. Imaging technologies that can be used to measure body composition noninvasively include DXA (dual energy x-ray absorptiometry) and MRI (magnetic resonance imaging). Unlike other approaches, MRI provides the ability to perform localized measurements of fat distribution. Several factors complicate the automatic delineation of fat regions and quantification of fat volumes. These include motion artifacts, field non-uniformity, brightness and contrast variations, chemical shift misregistration, and ambiguity in delineating anatomical structures. We have developed an approach to deal practically with those challenges. The approach is implemented in a package, the Fat Volume Tool, for automatic detection of fat tissue in MR images of the rat abdomen, including automatic discrimination between abdominal and subcutaneous regions. We suppress motion artifacts using masking based on detection of implicit landmarks in the images. Adaptive object extraction is used to compensate for intensity variations. This approach enables us to perform fat tissue detection and quantification in a fully automated manner. The package can also operate in manual mode, which can be used for verification of the automatic analysis or for performing supervised segmentation. In supervised segmentation, the operator has the ability to interact with the automatic segmentation procedures to touch-up or completely overwrite intermediate segmentation steps. The operator's interventions steer the automatic segmentation steps that follow. This improves the efficiency and quality of the final segmentation. Semi-automatic segmentation tools (interactive region growing, live-wire, etc.) improve both the accuracy and throughput of the operator when working in manual mode. The quality of automatic segmentation has been evaluated by comparing the results of fully automated analysis to manual analysis of the same images. The comparison shows a high degree of correlation that validates the quality of the automatic segmentation approach.

Automatic Detection and Positioning of Ground Control Points Using TerraSAR-X Multiaspect Acquisitions

NASA Astrophysics Data System (ADS)

Montazeri, Sina; Gisinger, Christoph; Eineder, Michael; Zhu, Xiao xiang

2018-05-01

Geodetic stereo Synthetic Aperture Radar (SAR) is capable of absolute three-dimensional localization of natural Persistent Scatterer (PS)s which allows for Ground Control Point (GCP) generation using only SAR data. The prerequisite for the method to achieve high precision results is the correct detection of common scatterers in SAR images acquired from different viewing geometries. In this contribution, we describe three strategies for automatic detection of identical targets in SAR images of urban areas taken from different orbit tracks. Moreover, a complete work-flow for automatic generation of large number of GCPs using SAR data is presented and its applicability is shown by exploiting TerraSAR-X (TS-X) high resolution spotlight images over the city of Oulu, Finland and a test site in Berlin, Germany.

Fetal head detection and measurement in ultrasound images by an iterative randomized Hough transform

NASA Astrophysics Data System (ADS)

Lu, Wei; Tan, Jinglu; Floyd, Randall C.

2004-05-01

This paper describes an automatic method for measuring the biparietal diameter (BPD) and head circumference (HC) in ultrasound fetal images. A total of 217 ultrasound images were segmented by using a K-Mean classifier, and the head skull was detected in 214 of the 217 cases by an iterative randomized Hough transform developed for detection of incomplete curves in images with strong noise without user intervention. The automatic measurements were compared with conventional manual measurements by sonographers and a trained panel. The inter-run variations and differences between the automatic and conventional measurements were small compared with published inter-observer variations. The results showed that the automated measurements were as reliable as the expert measurements and more consistent. This method has great potential in clinical applications.

Comparing Automatic CME Detections in Multiple LASCO and SECCHI Catalogs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hess, Phillip; Colaninno, Robin C., E-mail: phillip.hess.ctr@nrl.navy.mil, E-mail: robin.colaninno@nrl.navy.mil

With the creation of numerous automatic detection algorithms, a number of different catalogs of coronal mass ejections (CMEs) spanning the entirety of the Solar and Heliospheric Observatory ( SOHO ) Large Angle Spectrometric Coronagraph (LASCO) mission have been created. Some of these catalogs have been further expanded for use on data from the Solar Terrestrial Earth Observatory ( STEREO ) Sun Earth Connection Coronal and Heliospheric Investigation (SECCHI) as well. We compare the results from different automatic detection catalogs (Solar Eruption Event Detection System (SEEDS), Computer Aided CME Tracking (CACTus), and Coronal Image Processing (CORIMP)) to ensure the consistency ofmore » detections in each. Over the entire span of the LASCO catalogs, the automatic catalogs are well correlated with one another, to a level greater than 0.88. Focusing on just periods of higher activity, these correlations remain above 0.7. We establish the difficulty in comparing detections over the course of LASCO observations due to the change in the instrument image cadence in 2010. Without adjusting catalogs for the cadence, CME detection rates show a large spike in cycle 24, despite a notable drop in other indices of solar activity. The output from SEEDS, using a consistent image cadence, shows that the CME rate has not significantly changed relative to sunspot number in cycle 24. These data, and mass calculations from CORIMP, lead us to conclude that any apparent increase in CME rate is a result of the change in cadence. We study detection characteristics of CMEs, discussing potential physical changes in events between cycles 23 and 24. We establish that, for detected CMEs, physical parameters can also be sensitive to the cadence.« less

Detection of Onchocerca volvulus in Skin Snips by Microscopy and Real-Time Polymerase Chain Reaction: Implications for Monitoring and Evaluation Activities.

PubMed

Thiele, Elizabeth A; Cama, Vitaliano A; Lakwo, Thomson; Mekasha, Sindeaw; Abanyie, Francisca; Sleshi, Markos; Kebede, Amha; Cantey, Paul T

2016-04-01

Microscopic evaluation of skin biopsies is the monitoring and evaluation (M and E) method currently used by multiple onchocerciasis elimination programs in Africa. However, as repeated mass drug administration suppresses microfilarial loads, the sensitivity and programmatic utility of skin snip microscopy is expected to decrease. Using a pan-filarial real-time polymerase chain reaction with melt curve analysis (qPCR-MCA), we evaluated 1) the use of a single-step molecular assay for detecting and identifying Onchocerca volvulus microfilariae in residual skin snips and 2) the sensitivity of skin snip microscopy relative to qPCR-MCA. Skin snips were collected and examined with routine microscopy in hyperendemic regions of Uganda and Ethiopia (N= 500 each) and "residual" skin snips (tissue remaining after induced microfilarial emergence) were tested with qPCR-MCA. qPCR-MCA detected Onchocerca DNA in 223 residual snips: 139 of 147 microscopy(+) and 84 among microscopy(-) snips, suggesting overall sensitivity of microscopy was 62.3% (139/223) relative to qPCR-MCA (75.6% in Uganda and 28.6% in Ethiopia). These findings demonstrate the insufficient sensitivity of skin snip microscopy for reliable programmatic monitoring. Molecular tools such as qPCR-MCA can augment sensitivity and provide diagnostic confirmation of skin biopsies and will be useful for evaluation or validation of new onchocerciasis M and E tools. © The American Society of Tropical Medicine and Hygiene.

Automatic reference selection for quantitative EEG interpretation: identification of diffuse/localised activity and the active earlobe reference, iterative detection of the distribution of EEG rhythms.

PubMed

Wang, Bei; Wang, Xingyu; Ikeda, Akio; Nagamine, Takashi; Shibasaki, Hiroshi; Nakamura, Masatoshi

2014-01-01

EEG (Electroencephalograph) interpretation is important for the diagnosis of neurological disorders. The proper adjustment of the montage can highlight the EEG rhythm of interest and avoid false interpretation. The aim of this study was to develop an automatic reference selection method to identify a suitable reference. The results may contribute to the accurate inspection of the distribution of EEG rhythms for quantitative EEG interpretation. The method includes two pre-judgements and one iterative detection module. The diffuse case is initially identified by pre-judgement 1 when intermittent rhythmic waveforms occur over large areas along the scalp. The earlobe reference or averaged reference is adopted for the diffuse case due to the effect of the earlobe reference depending on pre-judgement 2. An iterative detection algorithm is developed for the localised case when the signal is distributed in a small area of the brain. The suitable averaged reference is finally determined based on the detected focal and distributed electrodes. The presented technique was applied to the pathological EEG recordings of nine patients. One example of the diffuse case is introduced by illustrating the results of the pre-judgements. The diffusely intermittent rhythmic slow wave is identified. The effect of active earlobe reference is analysed. Two examples of the localised case are presented, indicating the results of the iterative detection module. The focal and distributed electrodes are detected automatically during the repeating algorithm. The identification of diffuse and localised activity was satisfactory compared with the visual inspection. The EEG rhythm of interest can be highlighted using a suitable selected reference. The implementation of an automatic reference selection method is helpful to detect the distribution of an EEG rhythm, which can improve the accuracy of EEG interpretation during both visual inspection and automatic interpretation. Copyright © 2013 IPEM. Published by Elsevier Ltd. All rights reserved.

Integration of kerma-area product and cumulative air kerma determination into a skin dose tracking system for fluoroscopic imaging procedures

NASA Astrophysics Data System (ADS)

Vijayan, Sarath; Shankar, Alok; Rudin, Stephen; Bednarek, Daniel R.

2016-03-01

The skin dose tracking system (DTS) that we developed provides a color-coded mapping of the cumulative skin dose distribution on a 3D graphic of the patient during fluoroscopic procedures in real time. The DTS has now been modified to also calculate the kerma area product (KAP) and cumulative air kerma (CAK) for fluoroscopic interventions using data obtained in real-time from the digital bus on a Toshiba Infinix system. KAP is the integral of air kerma over the beam area and is typically measured with a large-area transmission ionization chamber incorporated into the collimator assembly. In this software, KAP is automatically determined for each x-ray pulse as the product of the air kerma/ mAs from a calibration file for the given kVp and beam filtration times the mAs per pulse times the length and width of the beam times a field nonuniformity correction factor. Field nonuniformity is primarily the result of the heel effect and the correction factor was determined from the beam profile measured using radio-chromic film. Dividing the KAP by the beam area at the interventional reference point provides the area averaged CAK. The KAP and CAK per x-ray pulse are summed after each pulse to obtain the total procedure values in real-time. The calculated KAP and CAK were compared to the values displayed by the fluoroscopy machine with excellent agreement. The DTS now is able to automatically calculate both KAP and CAK without the need for measurement by an add-on transmission ionization chamber.

First Evaluation of Infrared Thermography as a Tool for the Monitoring of Udder Health Status in Farms of Dairy Cows.

PubMed

Zaninelli, Mauro; Redaelli, Veronica; Luzi, Fabio; Bronzo, Valerio; Mitchell, Malcolm; Dell'Orto, Vittorio; Bontempo, Valentino; Cattaneo, Donata; Savoini, Giovanni

2018-03-14

The aim of the present study was to test infrared thermography (IRT), under field conditions, as a possible tool for the evaluation of cow udder health status. Thermographic images (n. 310) from different farms (n. 3) were collected and evaluated using a dedicated software application to calculate automatically and in a standardized way, thermographic indices of each udder. Results obtained have confirmed a significant relationship between udder surface skin temperature (USST) and classes of somatic cell count in collected milk samples. Sensitivity and specificity in the classification of udder health were: 78.6% and 77.9%, respectively, considering a level of somatic cell count ( SCC ) of 200,000 cells/mL as a threshold to classify a subclinical mastitis or 71.4% and 71.6%, respectively when a threshold of 400,000 cells/mL was adopted. Even though the sensitivity and specificity were lower than in other published papers dealing with non-automated analysis of IRT images, they were considered acceptable as a first field application of this new and developing technology. Future research will permit further improvements in the use of IRT, at farm level. Such improvements could be attained through further image processing and enhancement, and the application of indicators developed and tested in the present study with the purpose of developing a monitoring system for the automatic and early detection of mastitis in individual animals on commercial farms.

First Evaluation of Infrared Thermography as a Tool for the Monitoring of Udder Health Status in Farms of Dairy Cows

PubMed Central

Luzi, Fabio; Bronzo, Valerio; Mitchell, Malcolm; Dell’Orto, Vittorio; Bontempo, Valentino; Savoini, Giovanni

2018-01-01

The aim of the present study was to test infrared thermography (IRT), under field conditions, as a possible tool for the evaluation of cow udder health status. Thermographic images (n. 310) from different farms (n. 3) were collected and evaluated using a dedicated software application to calculate automatically and in a standardized way, thermographic indices of each udder. Results obtained have confirmed a significant relationship between udder surface skin temperature (USST) and classes of somatic cell count in collected milk samples. Sensitivity and specificity in the classification of udder health were: 78.6% and 77.9%, respectively, considering a level of somatic cell count (SCC) of 200,000 cells/mL as a threshold to classify a subclinical mastitis or 71.4% and 71.6%, respectively when a threshold of 400,000 cells/mL was adopted. Even though the sensitivity and specificity were lower than in other published papers dealing with non-automated analysis of IRT images, they were considered acceptable as a first field application of this new and developing technology. Future research will permit further improvements in the use of IRT, at farm level. Such improvements could be attained through further image processing and enhancement, and the application of indicators developed and tested in the present study with the purpose of developing a monitoring system for the automatic and early detection of mastitis in individual animals on commercial farms. PMID:29538352

Nearly automatic motion capture system for tracking octopus arm movements in 3D space.

PubMed

Zelman, Ido; Galun, Meirav; Akselrod-Ballin, Ayelet; Yekutieli, Yoram; Hochner, Binyamin; Flash, Tamar

2009-08-30

Tracking animal movements in 3D space is an essential part of many biomechanical studies. The most popular technique for human motion capture uses markers placed on the skin which are tracked by a dedicated system. However, this technique may be inadequate for tracking animal movements, especially when it is impossible to attach markers to the animal's body either because of its size or shape or because of the environment in which the animal performs its movements. Attaching markers to an animal's body may also alter its behavior. Here we present a nearly automatic markerless motion capture system that overcomes these problems and successfully tracks octopus arm movements in 3D space. The system is based on three successive tracking and processing stages. The first stage uses a recently presented segmentation algorithm to detect the movement in a pair of video sequences recorded by two calibrated cameras. In the second stage, the results of the first stage are processed to produce 2D skeletal representations of the moving arm. Finally, the 2D skeletons are used to reconstruct the octopus arm movement as a sequence of 3D curves varying in time. Motion tracking, segmentation and reconstruction are especially difficult problems in the case of octopus arm movements because of the deformable, non-rigid structure of the octopus arm and the underwater environment in which it moves. Our successful results suggest that the motion-tracking system presented here may be used for tracking other elongated objects.

Semi-automated algorithm for localization of dermal/epidermal junction in reflectance confocal microscopy images of human skin

NASA Astrophysics Data System (ADS)

Kurugol, Sila; Dy, Jennifer G.; Rajadhyaksha, Milind; Gossage, Kirk W.; Weissmann, Jesse; Brooks, Dana H.

2011-03-01

The examination of the dermis/epidermis junction (DEJ) is clinically important for skin cancer diagnosis. Reflectance confocal microscopy (RCM) is an emerging tool for detection of skin cancers in vivo. However, visual localization of the DEJ in RCM images, with high accuracy and repeatability, is challenging, especially in fair skin, due to low contrast, heterogeneous structure and high inter- and intra-subject variability. We recently proposed a semi-automated algorithm to localize the DEJ in z-stacks of RCM images of fair skin, based on feature segmentation and classification. Here we extend the algorithm to dark skin. The extended algorithm first decides the skin type and then applies the appropriate DEJ localization method. In dark skin, strong backscatter from the pigment melanin causes the basal cells above the DEJ to appear with high contrast. To locate those high contrast regions, the algorithm operates on small tiles (regions) and finds the peaks of the smoothed average intensity depth profile of each tile. However, for some tiles, due to heterogeneity, multiple peaks in the depth profile exist and the strongest peak might not be the basal layer peak. To select the correct peak, basal cells are represented with a vector of texture features. The peak with most similar features to this feature vector is selected. The results show that the algorithm detected the skin types correctly for all 17 stacks tested (8 fair, 9 dark). The DEJ detection algorithm achieved an average distance from the ground truth DEJ surface of around 4.7μm for dark skin and around 7-14μm for fair skin.

Comparing the diagnostic properties of skin scraping, adhesive tape, and dermoscopy in diagnosing scabies.

PubMed

Abdel-Latif, Azmy A; Elshahed, Ahmad R; Salama, Omar A; Elsaie, Mohamed L

2018-06-01

Scabies is a contagious skin infestation that mainly presents with itching at night and skin burrows that are visible to the naked eye. Diagnosing scabies with dermoscopy is still a matter of controversy. The aim of our study was to compare the diagnostic properties of adhesive tape, skin scraping, and dermoscopy in diagnosing scabies. One hundred patients with clinical presumptive diagnoses of scabies underwent skin scraping, adhesive tape testing, and dermoscopic examination. Each diagnostic procedure was performed on three different areas. Comparing the diagnostic properties of the three methods, the adhesive tape test was the most sensitive method for diagnosing scabies. Sixteen cases (16.0%) were definitely diagnosed as scabies using the adhesive tape test detecting the presence of mites or their eggs. Only 10 cases (10.0%) were definitely diagnosed as scabies using the skin scraping test detecting mites or their eggs. Dermoscopic examination suggested a diagnosis of scabies in 22 cases (22.0%), of which only 10 were definitely diagnosed as scabies by detecting mites using the adhesive tape test, skin scraping, or both. The diagnosis of scabies can only be confirmed by seeing mites. The adhesive tape test and skin scraping procedure have high specificity in diagnosing scabies, but their low sensitivity cannot exclude the possibility of scabies. Dermoscopy-guided tape testing can be a helpful tool for better diagnosis of scabies.

Percutaneous irreversible electroporation for breast tissue and breast cancer: safety, feasibility, skin effects and radiologic-pathologic correlation in an animal study.

PubMed

Li, Sheng; Chen, Fei; Shen, Lujun; Zeng, Qi; Wu, Peihong

2016-08-05

To study the safety, feasibility and skin effects of irreversible electroporation (IRE) for breast tissue and breast cancer in animal models. Eight pigs were used in this study. IRE was performed on the left breasts of the pigs with different skin-electrode distances, and the right breasts were used as controls. The electrodes were placed 1-8 mm away from the skin, with an electrode spacing of 1.5-2 cm. Imaging and pathological examinations were performed at specific time points for follow-up evaluation. Vital signs, skin damage, breast tissue changes and ablation efficacy were also closely observed. Eight rabbit models with or without VX2 breast tumor implantations were used to further assess the damage caused by and the repair of thin skin after IRE treatment for breast cancer. Contrast-enhanced ultrasound and elastosonography were used to investigate ablation efficacy and safety. During IRE, the color of the pig breast skin reversibly changed. When the skin-electrode distance was 3 mm, the breast skin clearly changed, becoming white in the center and purple in the surrounding region during IRE. One small purulent skin lesion was detected several days after IRE. When the skin-electrode distance was 5-8 mm, the breast skin became red during IRE. However, the skin architecture was normal when evaluated using gross pathology and hematoxylin-eosin staining. When the skin-electrode distance was 1 mm, skin atrophy and yellow glabrescence occurred in the rabbit breasts after IRE. When the skin-electrode distance was ≥5 mm, there was no skin damage in the rabbit model regardless of breast cancer implantation. After IRE, complete ablation of the targeted breast tissue or cancer was confirmed, and apoptosis was detected in the target tissue and outermost epidermal layer. In the ablated breasts of the surviving animals, complete mammary regeneration with normal skin and hair was observed. Furthermore, no massive fibrosis or mass formation were detected on ultrasound or through hematoxylin-eosin staining. After IRE, the skin architecture was well preserved when the skin-electrode distance was ≥5 mm. Moreover, breast regeneration occurred without mass formation or obvious fibrosis.

Development of a sensitive, generic and easy to use organophosphate skin disclosure kit.

PubMed

Worek, Franz; Wosar, Andreas; Baumann, Madlen; Thiermann, Horst; Wille, Timo

2017-10-05

Various organophosphorus compounds (OP), primarily the nerve agent VX and other V-agents, are highly toxic to humans after skin exposure. Percutaneous exposure by such OP results in a delayed onset of toxic signs which enables the initiation of specific countermeasures if contamination is detected rapidly. Presently available mobile detection systems can hardly detect skin exposure by low volatile OP. In order to fill this gap an OP skin disclosure kit was developed which should fulfill different requirements, i.e. a high sensitivity, coverage of human toxic OP, easy handling, rapid results, small dimension and weight. The kit includes a cotton swab to sample skin, human AChE as target and chemicals for a color reaction based on the Ellman assay which is recorded by visual inspection. OP is dissolved from the sampler in a test tube filled with phosphate buffer (0.1M, pH 7.4) and incubated with lyophilized human AChE for 1min. The reaction with acetylthiocholine and 5,5'-dithio-bis-2-nitrobenzoic acid (1min) results in a rich yellow color in the absence of OP and in contrast, in transparent or pale yellow buffer in the presence of OP. At the recommended conditions, the limit of detection is 100ng VX and Russian VX and 50ng Chinese VX on plain surface and 200ng VX on rat skin. With activated pesticides, paraoxon and malaoxon, a concentration of ∼10μg can be detected on plain surface. The ready-to-use kit has a weight of 16g and a size of 10×12×1cm. In the end, this kit has the potential to fill a major gap and to enable timely detection of OP skin exposure and initiation of life-saving countermeasures. Copyright © 2017 Elsevier B.V. All rights reserved.

Applications of polarization speckle in skin cancer detection and monitoring

NASA Astrophysics Data System (ADS)

Lee, Tim K.; Tchvialeva, Lioudmila; Phillips, Jamie; Louie, Daniel C.; Zhao, Jianhua; Wang, Wei; Lui, Harvey; Kalia, Sunil

2018-01-01

Polarization speckle is a rapidly developed field. Unlike laser speckle, polarization speckle consists of stochastic interference patterns with spatially random polarizations, amplitudes and phases. We have been working in this exciting research field, developing techniques to generate polarization patterns from skin. We hypothesize that polarization speckle patterns could be used in biomedical applications, especially, for detecting and monitoring skin cancers, the most common neoplasmas for white populations around the world. This paper describes our effort in developing two polarization speckle devices. One of them captures the Stokes parameters So and S1 simultaneously, and another one captures all four Stokes parameters So, S1, S2, and S3 in one-shot, within milliseconds. Hence these two devices could be used in medical clinics and assessed skin conditions in-vivo. In order to validate our hypothesis, we conducted a series of three clinical studies. These are early pilot studies, and the results suggest that the devices have potential to detect and monitor skin cancers.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ding, Fei; Jiang, Huaiguang; Tan, Jin

This paper proposes an event-driven approach for reconfiguring distribution systems automatically. Specifically, an optimal synchrophasor sensor placement (OSSP) is used to reduce the number of synchrophasor sensors while keeping the whole system observable. Then, a wavelet-based event detection and location approach is used to detect and locate the event, which performs as a trigger for network reconfiguration. With the detected information, the system is then reconfigured using the hierarchical decentralized approach to seek for the new optimal topology. In this manner, whenever an event happens the distribution network can be reconfigured automatically based on the real-time information that is observablemore » and detectable.« less

[Methods for measuring skin aging].

PubMed

Zieger, M; Kaatz, M

2016-02-01

Aging affects human skin and is becoming increasingly important with regard to medical, social and aesthetic issues. Detection of intrinsic and extrinsic components of skin aging requires reliable measurement methods. Modern techniques, e.g., based on direct imaging, spectroscopy or skin physiological measurements, provide a broad spectrum of parameters for different applications.

Detection of Melanoma Skin Cancer in Dermoscopy Images

NASA Astrophysics Data System (ADS)

Eltayef, Khalid; Li, Yongmin; Liu, Xiaohui

2017-02-01

Malignant melanoma is the most hazardous type of human skin cancer and its incidence has been rapidly increasing. Early detection of malignant melanoma in dermoscopy images is very important and critical, since its detection in the early stage can be helpful to cure it. Computer Aided Diagnosis systems can be very helpful to facilitate the early detection of cancers for dermatologists. In this paper, we present a novel method for the detection of melanoma skin cancer. To detect the hair and several noises from images, pre-processing step is carried out by applying a bank of directional filters. And therefore, Image inpainting method is implemented to fill in the unknown regions. Fuzzy C-Means and Markov Random Field methods are used to delineate the border of the lesion area in the images. The method was evaluated on a dataset of 200 dermoscopic images, and superior results were produced compared to alternative methods.

Automatic food intake detection based on swallowing sounds.

PubMed

Makeyev, Oleksandr; Lopez-Meyer, Paulo; Schuckers, Stephanie; Besio, Walter; Sazonov, Edward

2012-11-01

This paper presents a novel fully automatic food intake detection methodology, an important step toward objective monitoring of ingestive behavior. The aim of such monitoring is to improve our understanding of eating behaviors associated with obesity and eating disorders. The proposed methodology consists of two stages. First, acoustic detection of swallowing instances based on mel-scale Fourier spectrum features and classification using support vector machines is performed. Principal component analysis and a smoothing algorithm are used to improve swallowing detection accuracy. Second, the frequency of swallowing is used as a predictor for detection of food intake episodes. The proposed methodology was tested on data collected from 12 subjects with various degrees of adiposity. Average accuracies of >80% and >75% were obtained for intra-subject and inter-subject models correspondingly with a temporal resolution of 30s. Results obtained on 44.1 hours of data with a total of 7305 swallows show that detection accuracies are comparable for obese and lean subjects. They also suggest feasibility of food intake detection based on swallowing sounds and potential of the proposed methodology for automatic monitoring of ingestive behavior. Based on a wearable non-invasive acoustic sensor the proposed methodology may potentially be used in free-living conditions.

Automatic food intake detection based on swallowing sounds

PubMed Central

Makeyev, Oleksandr; Lopez-Meyer, Paulo; Schuckers, Stephanie; Besio, Walter; Sazonov, Edward

2012-01-01

This paper presents a novel fully automatic food intake detection methodology, an important step toward objective monitoring of ingestive behavior. The aim of such monitoring is to improve our understanding of eating behaviors associated with obesity and eating disorders. The proposed methodology consists of two stages. First, acoustic detection of swallowing instances based on mel-scale Fourier spectrum features and classification using support vector machines is performed. Principal component analysis and a smoothing algorithm are used to improve swallowing detection accuracy. Second, the frequency of swallowing is used as a predictor for detection of food intake episodes. The proposed methodology was tested on data collected from 12 subjects with various degrees of adiposity. Average accuracies of >80% and >75% were obtained for intra-subject and inter-subject models correspondingly with a temporal resolution of 30s. Results obtained on 44.1 hours of data with a total of 7305 swallows show that detection accuracies are comparable for obese and lean subjects. They also suggest feasibility of food intake detection based on swallowing sounds and potential of the proposed methodology for automatic monitoring of ingestive behavior. Based on a wearable non-invasive acoustic sensor the proposed methodology may potentially be used in free-living conditions. PMID:23125873

Automatic differentiation of melanoma and clark nevus skin lesions

NASA Astrophysics Data System (ADS)

LeAnder, R. W.; Kasture, A.; Pandey, A.; Umbaugh, S. E.

2007-03-01

Skin cancer is the most common form of cancer in the United States. Although melanoma accounts for just 11% of all types of skin cancer, it is responsible for most of the deaths, claiming more than 7910 lives annually. Melanoma is visually difficult for clinicians to differentiate from Clark nevus lesions which are benign. The application of pattern recognition techniques to these lesions may be useful as an educational tool for teaching physicians to differentiate lesions, as well as for contributing information about the essential optical characteristics that identify them. Purpose: This study sought to find the most effective features to extract from melanoma, melanoma in situ and Clark nevus lesions, and to find the most effective pattern-classification criteria and algorithms for differentiating those lesions, using the Computer Vision and Image Processing Tools (CVIPtools) software package. Methods: Due to changes in ambient lighting during the photographic process, color differences between images can occur. These differences were minimized by capturing dermoscopic images instead of photographic images. Differences in skin color between patients were minimized via image color normalization, by converting original color images to relative-color images. Relative-color images also helped minimize changes in color that occur due to changes in the photographic and digitization processes. Tumors in the relative-color images were segmented and morphologically filtered. Filtered, relative-color, tumor features were then extracted and various pattern-classification schemes were applied. Results: Experimentation resulted in four useful pattern classification methods, the best of which was an overall classification rate of 100% for melanoma and melanoma in situ (grouped) and 60% for Clark nevus. Conclusion: Melanoma and melanoma in situ have feature parameters and feature values that are similar enough to be considered one class of tumor that significantly differs from Clark nevus. Consequently, grouping melanoma and melanoma in situ together achieves the best results in classifying and automatically differentiating melanoma from Clark nevus lesions.

Skin dose saving of the staff in 90Y/177Lu peptide receptor radionuclide therapy with the automatic dose dispenser.

PubMed

Fioroni, Federica; Grassi, Elisa; Giorgia, Cavatorta; Sara, Rubagotti; Piccagli, Vando; Filice, Angelina; Mostacci, Domiziano; Versari, Annibale; Iori, Mauro

2016-10-01

When handling Y-labelled and Lu-labelled radiopharmaceuticals, skin exposure is mainly due to β-particles. This study aimed to investigate the equivalent dose saving of the staff when changing from an essentially manual radiolabelling procedure to an automatic dose dispenser (ADD). The chemist and physician were asked to wear thermoluminescence dosimeters on their fingertips to evaluate the quantity of Hp(0.07) on the skin. Data collected were divided into two groups: before introducing ADD (no ADD) and after introducing ADD. For the chemist, the mean values (95th percentile) of Hp(0.07) for no ADD and ADD are 0.030 (0.099) and 0.019 (0.076) mSv/GBq, respectively, for Y, and 0.022 (0.037) and 0.007 (0.023) mSv/GBq, respectively, for Lu. The reduction for ADD was significant (t-test with P<0.05) for both isotopes. The relative differences before and after ADD collected for every finger were treated using the Wilcoxon test, proving a significantly higher reduction in extremity dose to each fingertip for Lu than for Y (P<0.05). For the medical staff, the mean values of Hp(0.07) (95th percentile) for no ADD and ADD are 0.021 (0.0762) and 0.0143 (0.0565) mSv/GBq, respectively, for Y, and 0.0011 (0.00196) and 0.0009 (0.00263) mSv/GBq, respectively, for Lu. The t-test provided a P-value less than 0.05 for both isotopes, making the difference between ADD and no ADD significant. ADD positively affects the dose saving of the chemist in handling both isotopes. For the medical staff not directly involved with the introduction of the ADD system, the analysis shows a learning curve of the workers over a 5-year period. Specific devices and procedures allow staff skin dose to be limited.

Delineating the cell death mechanisms associated with skin electroporation.

PubMed

Schultheis, Katherine; Smith, Trevor R F; Kiosses, William B; Kraynyak, Kimberly A; Wong, Amelia; Oh, Janet; Broderick, Kate Elizabeth

2018-06-28

The immune responses elicited following delivery of DNA vaccines to the skin has previously been shown to be significantly enhanced by the addition of electroporation (EP) to the treatment protocol. Principally, EP increases the transfection of pDNA into the resident skin cells. In addition to increasing the levels of in vivo transfection, the physical insult induced by EP is associated with activation of innate pathways which are believed to mediate an adjuvant effect, further enhancing DNA vaccine responses. Here, we have investigated the possible mechanisms associated with this adjuvant effect, primarily focusing on the cell death pathways associated with the skin EP procedure independent of pDNA delivery. Using the minimally invasive CELLECTRA®-3P intradermal electroporation device that penetrates the epidermal and dermal layers of the skin, we have investigated apoptotic and necrotic cell death in relation to the vicinity of the electrode needles and electric field generated. Employing the well-established TUNEL assay, we detected apoptosis beginning as early as one hour after EP and peaking at the 4 hour time point. The majority of the apoptotic events were detected in the epidermal region directly adjacent to the electrode needle. Using a novel propidium iodide in vivo necrotic cell death assay, we detected necrotic events concentrated in the epidermal region adjacent to the electrode. Furthermore, we detected up-regulation of calreticulin expression on skin cells after EP, thus labeling these cells for uptake by dendritic cells and macrophages. These results allow us to delineate the cell death mechanisms occurring in the skin following intradermal EP independently of pDNA delivery. We believe these events contribute to the adjuvant effect observed following electroporation at the skin treatment site.

The use of automatic programming techniques for fault tolerant computing systems

NASA Technical Reports Server (NTRS)

Wild, C.

1985-01-01

It is conjectured that the production of software for ultra-reliable computing systems such as required by Space Station, aircraft, nuclear power plants and the like will require a high degree of automation as well as fault tolerance. In this paper, the relationship between automatic programming techniques and fault tolerant computing systems is explored. Initial efforts in the automatic synthesis of code from assertions to be used for error detection as well as the automatic generation of assertions and test cases from abstract data type specifications is outlined. Speculation on the ability to generate truly diverse designs capable of recovery from errors by exploring alternate paths in the program synthesis tree is discussed. Some initial thoughts on the use of knowledge based systems for the global detection of abnormal behavior using expectations and the goal-directed reconfiguration of resources to meet critical mission objectives are given. One of the sources of information for these systems would be the knowledge captured during the automatic programming process.

Hand motion segmentation against skin colour background in breast awareness applications.

PubMed

Hu, Yuqin; Naguib, Raouf N G; Todman, Alison G; Amin, Saad A; Al-Omishy, Hassanein; Oikonomou, Andreas; Tucker, Nick

2004-01-01

Skin colour modelling and classification play significant roles in face and hand detection, recognition and tracking. A hand is an essential tool used in breast self-examination, which needs to be detected and analysed during the process of breast palpation. However, the background of a woman's moving hand is her breast that has the same or similar colour as the hand. Additionally, colour images recorded by a web camera are strongly affected by the lighting or brightness conditions. Hence, it is a challenging task to segment and track the hand against the breast without utilising any artificial markers, such as coloured nail polish. In this paper, a two-dimensional Gaussian skin colour model is employed in a particular way to identify a breast but not a hand. First, an input image is transformed to YCbCr colour space, which is less sensitive to the lighting conditions and more tolerant of skin tone. The breast, thus detected by the Gaussian skin model, is used as the baseline or framework for the hand motion. Secondly, motion cues are used to segment the hand motion against the detected baseline. Desired segmentation results have been achieved and the robustness of this algorithm is demonstrated in this paper.

Method for automatic detection of wheezing in lung sounds.

PubMed

Riella, R J; Nohama, P; Maia, J M

2009-07-01

The present report describes the development of a technique for automatic wheezing recognition in digitally recorded lung sounds. This method is based on the extraction and processing of spectral information from the respiratory cycle and the use of these data for user feedback and automatic recognition. The respiratory cycle is first pre-processed, in order to normalize its spectral information, and its spectrogram is then computed. After this procedure, the spectrogram image is processed by a two-dimensional convolution filter and a half-threshold in order to increase the contrast and isolate its highest amplitude components, respectively. Thus, in order to generate more compressed data to automatic recognition, the spectral projection from the processed spectrogram is computed and stored as an array. The higher magnitude values of the array and its respective spectral values are then located and used as inputs to a multi-layer perceptron artificial neural network, which results an automatic indication about the presence of wheezes. For validation of the methodology, lung sounds recorded from three different repositories were used. The results show that the proposed technique achieves 84.82% accuracy in the detection of wheezing for an isolated respiratory cycle and 92.86% accuracy for the detection of wheezes when detection is carried out using groups of respiratory cycles obtained from the same person. Also, the system presents the original recorded sound and the post-processed spectrogram image for the user to draw his own conclusions from the data.

Automatic annotation of histopathological images using a latent topic model based on non-negative matrix factorization

PubMed Central

Cruz-Roa, Angel; Díaz, Gloria; Romero, Eduardo; González, Fabio A.

2011-01-01

Histopathological images are an important resource for clinical diagnosis and biomedical research. From an image understanding point of view, the automatic annotation of these images is a challenging problem. This paper presents a new method for automatic histopathological image annotation based on three complementary strategies, first, a part-based image representation, called the bag of features, which takes advantage of the natural redundancy of histopathological images for capturing the fundamental patterns of biological structures, second, a latent topic model, based on non-negative matrix factorization, which captures the high-level visual patterns hidden in the image, and, third, a probabilistic annotation model that links visual appearance of morphological and architectural features associated to 10 histopathological image annotations. The method was evaluated using 1,604 annotated images of skin tissues, which included normal and pathological architectural and morphological features, obtaining a recall of 74% and a precision of 50%, which improved a baseline annotation method based on support vector machines in a 64% and 24%, respectively. PMID:22811960

[Development of the automatic dental X-ray film processor].

PubMed

Bai, J; Chen, H

1999-07-01

This paper introduces a multiple-point detecting technique of the density of dental X-ray films. With the infrared ray multiple-point detecting technique, a single-chip microcomputer control system is used to analyze the effectiveness of the film-developing in real time in order to achieve a good image. Based on the new technology, We designed the intelligent automatic dental X-ray film processing.

Gated high speed optical detector

NASA Technical Reports Server (NTRS)

Green, S. I.; Carson, L. M.; Neal, G. W.

1973-01-01

The design, fabrication, and test of two gated, high speed optical detectors for use in high speed digital laser communication links are discussed. The optical detectors used a dynamic crossed field photomultiplier and electronics including dc bias and RF drive circuits, automatic remote synchronization circuits, automatic gain control circuits, and threshold detection circuits. The equipment is used to detect binary encoded signals from a mode locked neodynium laser.

Generating Impact Maps from Automatically Detected Bomb Craters in Aerial Wartime Images Using Marked Point Processes

NASA Astrophysics Data System (ADS)

Kruse, Christian; Rottensteiner, Franz; Hoberg, Thorsten; Ziems, Marcel; Rebke, Julia; Heipke, Christian

2018-04-01

The aftermath of wartime attacks is often felt long after the war ended, as numerous unexploded bombs may still exist in the ground. Typically, such areas are documented in so-called impact maps which are based on the detection of bomb craters. This paper proposes a method for the automatic detection of bomb craters in aerial wartime images that were taken during the Second World War. The object model for the bomb craters is represented by ellipses. A probabilistic approach based on marked point processes determines the most likely configuration of objects within the scene. Adding and removing new objects to and from the current configuration, respectively, changing their positions and modifying the ellipse parameters randomly creates new object configurations. Each configuration is evaluated using an energy function. High gradient magnitudes along the border of the ellipse are favored and overlapping ellipses are penalized. Reversible Jump Markov Chain Monte Carlo sampling in combination with simulated annealing provides the global energy optimum, which describes the conformance with a predefined model. For generating the impact map a probability map is defined which is created from the automatic detections via kernel density estimation. By setting a threshold, areas around the detections are classified as contaminated or uncontaminated sites, respectively. Our results show the general potential of the method for the automatic detection of bomb craters and its automated generation of an impact map in a heterogeneous image stock.

Rapid Detection of Trichodysplasia Spinulosa-Associated Polyomavirus in Skin Biopsy Specimen

PubMed Central

Urbano, Paulo Roberto P.; Pannuti, Cláudio Sérgio; Pierrotti, Ligia C.; David-Neto, Elias

2014-01-01

Trichodysplasia spinulosa-associated polyomavirus (TSV) is responsible for a rare skin cancer. Using metagenomic approaches, we determined the complete genome sequence of a TSV first detected in Brazil in spicules of an immunocompromised patient suspected to have trichodysplasia spinulosa. PMID:25059864

Development of a real-time PCR to detect Demodex canis DNA in different tissue samples.

PubMed

Ravera, Ivan; Altet, Laura; Francino, Olga; Bardagí, Mar; Sánchez, Armand; Ferrer, Lluís

2011-02-01

The present study reports the development of a real-time polymerase chain reaction (PCR) to detect Demodex canis DNA on different tissue samples. The technique amplifies a 166 bp of D. canis chitin synthase gene (AB 080667) and it has been successfully tested on hairs extracted with their roots and on formalin-fixed paraffin embedded skin biopsies. The real-time PCR amplified on the hairs of all 14 dogs with a firm diagnosis of demodicosis and consistently failed to amplify on negative controls. Eleven of 12 skin biopsies with a morphologic diagnosis of canine demodicosis were also positive. Sampling hairs on two skin points (lateral face and interdigital skin), D. canis DNA was detected on nine of 51 healthy dogs (17.6%) a much higher percentage than previously reported with microscopic studies. Furthermore, it is foreseen that if the number of samples were increased, the percentage of positive dogs would probably also grow. Moreover, in four of the six dogs with demodicosis, the samples taken from non-lesioned skin were positive. This finding, if confirmed in further studies, suggests that demodicosis is a generalized phenomenon in canine skin, due to proliferation of local mite populations, even though macroscopic lesions only appear in certain areas. The real-time PCR technique to detect D. canis DNA described in this work is a useful tool to advance our understanding of canine demodicosis.

Skin-Attachable, Stretchable Electrochemical Sweat Sensor for Glucose and pH Detection.

PubMed

Oh, Seung Yun; Hong, Soo Yeong; Jeong, Yu Ra; Yun, Junyeong; Park, Heun; Jin, Sang Woo; Lee, Geumbee; Oh, Ju Hyun; Lee, Hanchan; Lee, Sang-Soo; Ha, Jeong Sook

2018-04-25

As part of increased efforts to develop wearable healthcare devices for monitoring and managing physiological and metabolic information, stretchable electrochemical sweat sensors have been investigated. In this study, we report on the fabrication of a stretchable and skin-attachable electrochemical sensor for detecting glucose and pH in sweat. A patterned stretchable electrode was fabricated via layer-by-layer deposition of carbon nanotubes (CNTs) on top of patterned Au nanosheets (AuNS) prepared by filtration onto stretchable substrate. For the detection of glucose and pH, CoWO 4 /CNT and polyaniline/CNT nanocomposites were coated onto the CNT-AuNS electrodes, respectively. A reference electrode was prepared via chlorination of silver nanowires. Encapsulation of the stretchable sensor with sticky silbione led to a skin-attachable sweat sensor. Our sensor showed high performance with sensitivities of 10.89 μA mM -1 cm -2 and 71.44 mV pH -1 for glucose and pH, respectively, with mechanical stability up to 30% stretching and air stability for 10 days. The sensor also showed good adhesion even to wet skin, allowing the detection of glucose and pH in sweat from running while being attached onto the skin. This work suggests the application of our stretchable and skin-attachable electrochemical sensor to health management as a high-performance healthcare wearable device.

Automatic concrete cracks detection and mapping of terrestrial laser scan data

NASA Astrophysics Data System (ADS)

Rabah, Mostafa; Elhattab, Ahmed; Fayad, Atef

2013-12-01

Terrestrial laser scanning has become one of the standard technologies for object acquisition in surveying engineering. The high spatial resolution of imaging and the excellent capability of measuring the 3D space by laser scanning bear a great potential if combined for both data acquisition and data compilation. Automatic crack detection from concrete surface images is very effective for nondestructive testing. The crack information can be used to decide the appropriate rehabilitation method to fix the cracked structures and prevent any catastrophic failure. In practice, cracks on concrete surfaces are traced manually for diagnosis. On the other hand, automatic crack detection is highly desirable for efficient and objective crack assessment. The current paper submits a method for automatic concrete cracks detection and mapping from the data that was obtained during laser scanning survey. The method of cracks detection and mapping is achieved by three steps, namely the step of shading correction in the original image, step of crack detection and finally step of crack mapping and processing steps. The detected crack is defined in a pixel coordinate system. To remap the crack into the referred coordinate system, a reverse engineering is used. This is achieved by a hybrid concept of terrestrial laser-scanner point clouds and the corresponding camera image, i.e. a conversion from the pixel coordinate system to the terrestrial laser-scanner or global coordinate system. The results of the experiment show that the mean differences between terrestrial laser scan and the total station are about 30.5, 16.4 and 14.3 mms in x, y and z direction, respectively.

Automatic QRS complex detection using two-level convolutional neural network.

PubMed

Xiang, Yande; Lin, Zhitao; Meng, Jianyi

2018-01-29

The QRS complex is the most noticeable feature in the electrocardiogram (ECG) signal, therefore, its detection is critical for ECG signal analysis. The existing detection methods largely depend on hand-crafted manual features and parameters, which may introduce significant computational complexity, especially in the transform domains. In addition, fixed features and parameters are not suitable for detecting various kinds of QRS complexes under different circumstances. In this study, based on 1-D convolutional neural network (CNN), an accurate method for QRS complex detection is proposed. The CNN consists of object-level and part-level CNNs for extracting different grained ECG morphological features automatically. All the extracted morphological features are used by multi-layer perceptron (MLP) for QRS complex detection. Additionally, a simple ECG signal preprocessing technique which only contains difference operation in temporal domain is adopted. Based on the MIT-BIH arrhythmia (MIT-BIH-AR) database, the proposed detection method achieves overall sensitivity Sen = 99.77%, positive predictivity rate PPR = 99.91%, and detection error rate DER = 0.32%. In addition, the performance variation is performed according to different signal-to-noise ratio (SNR) values. An automatic QRS detection method using two-level 1-D CNN and simple signal preprocessing technique is proposed for QRS complex detection. Compared with the state-of-the-art QRS complex detection approaches, experimental results show that the proposed method acquires comparable accuracy.

Chest wall segmentation in automated 3D breast ultrasound scans.

PubMed

Tan, Tao; Platel, Bram; Mann, Ritse M; Huisman, Henkjan; Karssemeijer, Nico

2013-12-01

In this paper, we present an automatic method to segment the chest wall in automated 3D breast ultrasound images. Determining the location of the chest wall in automated 3D breast ultrasound images is necessary in computer-aided detection systems to remove automatically detected cancer candidates beyond the chest wall and it can be of great help for inter- and intra-modal image registration. We show that the visible part of the chest wall in an automated 3D breast ultrasound image can be accurately modeled by a cylinder. We fit the surface of our cylinder model to a set of automatically detected rib-surface points. The detection of the rib-surface points is done by a classifier using features representing local image intensity patterns and presence of rib shadows. Due to attenuation of the ultrasound signal, a clear shadow is visible behind the ribs. Evaluation of our segmentation method is done by computing the distance of manually annotated rib points to the surface of the automatically detected chest wall. We examined the performance on images obtained with the two most common 3D breast ultrasound devices in the market. In a dataset of 142 images, the average mean distance of the annotated points to the segmented chest wall was 5.59 ± 3.08 mm. Copyright © 2012 Elsevier B.V. All rights reserved.

Molecular Analysis of Malassezia Microflora on the Skin of Atopic Dermatitis Patients and Healthy Subjects

PubMed Central

Sugita, Takashi; Suto, Hajime; Unno, Tetsushi; Tsuboi, Ryoji; Ogawa, Hideoki; Shinoda, Takako; Nishikawa, Akemi

2001-01-01

Members of the genus Malassezia, lipophilic yeasts, are considered to be one of the exacerbating factors in atopic dermatitis (AD). We examined variation in cutaneous colonization by Malassezia species in AD patients and compared it with variation in healthy subjects. Samples were collected by applying transparent dressings to the skin lesions of AD patients. DNA was extracted directly from the dressings and amplified in a specific nested PCR assay. Malassezia-specific DNA was detected in all samples obtained from 32 AD patients. In particular, Malassezia globosa and M. restricta were detected in approximately 90% of the AD patients and M. furfur and M. sympodialis were detected in approximately 40% of the cases. The detection rate was not dependent on the type of skin lesion. In healthy subjects, Malassezia DNA was detected in 78% of the samples, among which M. globosa, M. restricta, and M. sympodialis were detected at frequencies ranging from 44 to 61%, with M. furfur at 11%. The diversity of Malassezia species found in AD patients was greater (2.7 species detected in each individual) than that found in healthy subjects (1.8 species per individual). Our results suggest that M. furfur, M. globosa, M. restricta, and M. sympodialis are common inhabitants of the skin of both AD patients and healthy subjects, while the skin microflora of AD patients shows more diversity than that of healthy subjects. To our knowledge, this is the first report of the use of a nested PCR as an alternative to fungal culture for analysis of the distribution of cutaneous Malassezia spp. PMID:11574560

Hydrogel-Forming Microneedle Arrays Allow Detection of Drugs and Glucose In Vivo: Potential for Use in Diagnosis and Therapeutic Drug Monitoring

PubMed Central

Caffarel-Salvador, Ester; Brady, Aaron J.; Eltayib, Eyman; Meng, Teng; Alonso-Vicente, Ana; Gonzalez-Vazquez, Patricia; Torrisi, Barbara M.; Vicente-Perez, Eva Maria; Mooney, Karen; Jones, David S.; Bell, Steven E. J.; McCoy, Colin P.; McCarthy, Helen O.; McElnay, James C.; Donnelly, Ryan F.

2015-01-01

We describe, for the first time the use of hydrogel-forming microneedle (MN) arrays for minimally-invasive extraction and quantification of drug substances and glucose from skin in vitro and in vivo. MN prepared from aqueous blends of hydrolysed poly(methyl-vinylether-co-maleic anhydride) (11.1% w/w) and poly(ethyleneglycol) 10,000 daltons (5.6% w/w) and crosslinked by esterification swelled upon skin insertion by uptake of fluid. Post-removal, theophylline and caffeine were extracted from MN and determined using HPLC, with glucose quantified using a proprietary kit. In vitro studies using excised neonatal porcine skin bathed on the underside by physiologically-relevant analyte concentrations showed rapid (5 min) analyte uptake. For example, mean concentrations of 0.16 μg/mL and 0.85 μg/mL, respectively, were detected for the lowest (5 μg/mL) and highest (35 μg/mL) Franz cell concentrations of theophylline after 5 min insertion. A mean concentration of 0.10 μg/mL was obtained by extraction of MN inserted for 5 min into skin bathed with 5 μg/mL caffeine, while the mean concentration obtained by extraction of MN inserted into skin bathed with 15 μg/mL caffeine was 0.33 μg/mL. The mean detected glucose concentration after 5 min insertion into skin bathed with 4 mmol/L was 19.46 nmol/L. The highest theophylline concentration detected following extraction from a hydrogel-forming MN inserted for 1 h into the skin of a rat dosed orally with 10 mg/kg was of 0.363 μg/mL, whilst a maximum concentration of 0.063 μg/mL was detected following extraction from a MN inserted for 1 h into the skin of a rat dosed with 5 mg/kg theophylline. In human volunteers, the highest mean concentration of caffeine detected using MN was 91.31 μg/mL over the period from 1 to 2 h post-consumption of 100 mg Proplus® tablets. The highest mean blood glucose level was 7.89 nmol/L detected 1 h following ingestion of 75 g of glucose, while the highest mean glucose concentration extracted from MN was 4.29 nmol/L, detected after 3 hours skin insertion in human volunteers. Whilst not directly correlated, concentrations extracted from MN were clearly indicative of trends in blood in both rats and human volunteers. This work strongly illustrates the potential of hydrogel-forming MN in minimally-invasive patient monitoring and diagnosis. Further studies are now ongoing to reduce clinical insertion times and develop mathematical algorithms enabling determination of blood levels directly from MN measurements. PMID:26717198

Predicting neuropathic ulceration: analysis of static temperature distributions in thermal images

NASA Astrophysics Data System (ADS)

Kaabouch, Naima; Hu, Wen-Chen; Chen, Yi; Anderson, Julie W.; Ames, Forrest; Paulson, Rolf

2010-11-01

Foot ulcers affect millions of Americans annually. Conventional methods used to assess skin integrity, including inspection and palpation, may be valuable approaches, but they usually do not detect changes in skin integrity until an ulcer has already developed. We analyze the feasibility of thermal imaging as a technique to assess the integrity of the skin and its many layers. Thermal images are analyzed using an asymmetry analysis, combined with a genetic algorithm, to examine the infrared images for early detection of foot ulcers. Preliminary results show that the proposed technique can reliably and efficiently detect inflammation and hence effectively predict potential ulceration.

Molecular and Culture-Based Assessment of the Microbial Diversity of Diabetic Chronic Foot Wounds and Contralateral Skin Sites

PubMed Central

Oates, Angela; Bowling, Frank L.; Boulton, Andrew J. M.

2012-01-01

Wound debridement samples and contralateral (healthy) skin swabs acquired from 26 patients attending a specialist foot clinic were analyzed by differential isolation and eubacterium-specific PCR-denaturing gradient gel electrophoresis (DGGE) in conjunction with DNA sequencing. Thirteen of 26 wounds harbored pathogens according to culture analyses, with Staphylococcus aureus being the most common (13/13). Candida (1/13), pseudomonas (1/13), and streptococcus (7/13) were less prevalent. Contralateral skin was associated with comparatively low densities of bacteria, and overt pathogens were not detected. According to DGGE analyses, all wounds contained significantly greater eubacterial diversity than contralateral skin (P < 0.05), although no significant difference in total eubacterial diversity was detected between wounds from which known pathogens had been isolated and those that were putatively uninfected. DGGE amplicons with homology to Staphylococcus sp. (8/13) and S. aureus (2/13) were detected in putatively infected wound samples, while Staphylococcus sp. amplicons were detected in 11/13 noninfected wounds; S. aureus was not detected in these samples. While a majority of skin-derived DGGE consortial fingerprints could be differentiated from wound profiles through principal component analysis (PCA), a large minority could not. Furthermore, wounds from which pathogens had been isolated could not be distinguished from putatively uninfected wounds on this basis. In conclusion, while chronic wounds generally harbored greater eubacterial diversity than healthy skin, the isolation of known pathogens was not associated with qualitatively distinct consortial profiles or otherwise altered diversity. The data generated support the utility of both culture and DGGE for the microbial characterization of chronic wounds. PMID:22553231

[The Value of High Frequency Color Doppler Ultrasonography in the Diagnosis of Solid Skin Tumorsa-a Preliminary Study].

PubMed

Zhong, Lin; Tang, Yuan-Jiao; Yang, Yu-Jia; Qiu, Li

2017-01-01

To explore the value of high frequency color doppler ultrasonography in differentiating benign and malignant skin solid tumors. Clinical and ultrasonic data of cutaneous solid tumors confirmed by pathology in our hospital were collected. The differences in clinical and sonographic features between benign and malignant tumors were statistically analyzed. A total of 512 patients, involving 527 cases of skin solid tumors, were enrolled in this study. The ultrasonic detected 99.43% of the cases, with 99.02% accuracy in locating the lesions. The benign and malignant tumors showed differences in patient age, location, multiple occurance, location and depth, surface skin condition, tumor size, echo, morphology, uniformity, calcification, blood flow status, tumor rear area and peripheral echo, and pathological requests ( P <0.05). High frequency ultrasound has excellent detection rate of skin tumors, which can locate invasion depth of skin accurately. Benign and malignant skin tumors show differences in a number of clinical and ultrasound features.

A new methodology for automatic detection of reference points in 3D cephalometry: A pilot study.

PubMed

Ed-Dhahraouy, Mohammed; Riri, Hicham; Ezzahmouly, Manal; Bourzgui, Farid; El Moutaoukkil, Abdelmajid

2018-04-05

The aim of this study was to develop a new method for an automatic detection of reference points in 3D cephalometry to overcome the limits of 2D cephalometric analyses. A specific application was designed using the C++ language for automatic and manual identification of 21 (reference) points on the craniofacial structures. Our algorithm is based on the implementation of an anatomical and geometrical network adapted to the craniofacial structure. This network was constructed based on the anatomical knowledge of the 3D cephalometric (reference) points. The proposed algorithm was tested on five CBCT images. The proposed approach for the automatic 3D cephalometric identification was able to detect 21 points with a mean error of 2.32mm. In this pilot study, we propose an automated methodology for the identification of the 3D cephalometric (reference) points. A larger sample will be implemented in the future to assess the method validity and reliability. Copyright © 2018 CEO. Published by Elsevier Masson SAS. All rights reserved.

On-chip skin color detection using a triple-well CMOS process

NASA Astrophysics Data System (ADS)

Boussaid, Farid; Chai, Douglas; Bouzerdoum, Abdesselam

2004-03-01

In this paper, a current-mode VLSI architecture enabling on read-out skin detection without the need for any on-chip memory elements is proposed. An important feature of the proposed architecture is that it removes the need for demosaicing. Color separation is achieved using the strong wavelength dependence of the absorption coefficient in silicon. This wavelength dependence causes a very shallow absorption of blue light and enables red light to penetrate deeply in silicon. A triple-well process, allowing a P-well to be placed inside an N-well, is chosen to fabricate three vertically integrated photodiodes acting as the RGB color detector for each pixel. Pixels of an input RGB image are classified as skin or non-skin pixels using a statistical skin color model, chosen to offer an acceptable trade-off between skin detection performance and implementation complexity. A single processing unit is used to classify all pixels of the input RGB image. This results in reduced mismatch and also in an increased pixel fill-factor. Furthermore, the proposed current-mode architecture is programmable, allowing external control of all classifier parameters to compensate for mismatch and changing lighting conditions.

Evaluation of intraepidermal nerve fibres in the skin of normal and atopic dogs.

PubMed

Laprais, Aurore; Dunston, Stanley M; Torres, Sheila M F; Favrot, Claude; Olivry, Thierry

2017-08-01

Interest in intraepidermal nerve fibres (IENFs) is rising in human medicine, because variations in fibre density occur in some diseases and these neurites might contribute to disease pathogenesis. An increase in IENF density is seen in human atopic dermatitis (AD); there are no such data in atopic dogs. To compare the prevalence of IENFs in normal and atopic canine skin. Eight millimetre skin punch biopsies were taken from six sites of 25 healthy dogs without dermatitis and compared to lesional and nonlesional skin samples of dogs with AD (23 and 14 dogs, respectively). Thirty micrometre-thick paraffin-embedded sections were stained by indirect immunofluorescence for neuronal beta-3 tubulin. Only sections with detectable dermal nerves were then screened for the presence of IENFs. IENFs were identified in all 25 normal nasal planum sections, but in only one biopsy collected from each of the normal canine haired skin (NCHS) sites. As there was no significant difference in IENF prevalence between NCHS areas, they were grouped together. The rate of detection of IENFs was significantly higher (one-tailed Fisher's test, P = 0.004) in lesional AD specimens (18 of 23; 78%) than in nonlesional AD (four of 14; 29%) and NCHS specimens (four of 111; 4%, P < 0.0001). The prevalence of IENF detection in nonlesional AD samples was significantly higher than in normal canine skin (P = 0.006). IENFs are detected more commonly in canine AD than in normal haired skin; these results are comparable to those seen for human AD. © 2017 ESVD and ACVD.

Skin penetration and kinetics of pristine fullerenes (C{sub 60}) topically exposed in industrial organic solvents

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xia, Xin R., E-mail: xia@ncsu.ed; Monteiro-Riviere, Nancy A.; Riviere, Jim E.

2010-01-01

Pristine fullerenes (C{sub 60}) in different solvents will be used in many industrial and pharmaceutical manufacturing and derivatizing processes. This report explores the impact of solvents on skin penetration of C{sub 60} from different types of industrial solvents (toluene, cyclohexane, chloroform and mineral oil). Yorkshire weanling pigs (n = 3) were topically dosed with 500 muL of 200 mug/mL C{sub 60} in a given solvent for 24 h and re-dosed daily for 4 days to simulate the worst scenario in occupational exposures. The dose sites were tape-stripped and skin biopsies were taken after 26 tape-strips for quantitative analysis. When dosedmore » in toluene, cyclohexane or chloroform, pristine fullerenes penetrated deeply into the stratum corneum, the primary barrier of skin. More C{sub 60} was detected in the stratum corneum when dosed in chloroform compared to toluene or cyclohexane. Fullerenes were not detected in the skin when dosed in mineral oil. This is the first direct evidence of solvent effects on the skin penetration of pristine fullerenes. The penetration of C{sub 60} into the stratum corneum was verified using isolated stratum corneum in vitro; the solvent effects on the stratum corneum absorption of C{sub 60} were consistent with those observed in vivo. In vitro flow-through diffusion cell experiments were conducted in pig skin and fullerenes were not detected in the receptor solutions by 24 h. The limit of detection was 0.001 mug/mL of fullerenes in 2 mL of the receptor solutions.« less

75 FR 12670 - Airworthiness Directives; The Boeing Company Model 767 Airplanes

Federal Register 2010, 2011, 2012, 2013, 2014

2010-03-17

... joints, the skin at certain external approved repairs, the skin around external features such as antennas... antennas, and at locations where external decals had been cut. We are issuing this AD to detect and correct... skin at certain external approved repairs, the skin around external features such as antennas, and the...

Medical applications of infrared thermography: A review

NASA Astrophysics Data System (ADS)

Lahiri, B. B.; Bagavathiappan, S.; Jayakumar, T.; Philip, John

2012-07-01

Abnormal body temperature is a natural indicator of illness. Infrared thermography (IRT) is a fast, passive, non-contact and non-invasive alternative to conventional clinical thermometers for monitoring body temperature. Besides, IRT can also map body surface temperature remotely. Last five decades witnessed a steady increase in the utility of thermal imaging cameras to obtain correlations between the thermal physiology and skin temperature. IRT has been successfully used in diagnosis of breast cancer, diabetes neuropathy and peripheral vascular disorders. It has also been used to detect problems associated with gynecology, kidney transplantation, dermatology, heart, neonatal physiology, fever screening and brain imaging. With the advent of modern infrared cameras, data acquisition and processing techniques, it is now possible to have real time high resolution thermographic images, which is likely to surge further research in this field. The present efforts are focused on automatic analysis of temperature distribution of regions of interest and their statistical analysis for detection of abnormalities. This critical review focuses on advances in the area of medical IRT. The basics of IRT, essential theoretical background, the procedures adopted for various measurements and applications of IRT in various medical fields are discussed in this review. Besides background information is provided for beginners for better understanding of the subject.

Within-Subject Interlaboratory Variability of QuantiFERON-TB Gold In-Tube Tests

DTIC Science & Technology

2012-09-06

QuantiFERONH-TB Gold In-Tube test (QFT-GIT) is a viable alternative to the tuberculin skin test (TST) for detecting Mycobacterium tuberculosis infection...viable alternative to the tuberculin skin test (TST) for detecting Mycobacterium tuberculosis infection. However, within-subject variability may limit test...release assays (IGRAs) are designed to detect both latent Mycobacterium tuberculosis infection (LTBI) and infections manifesting as active

A novel fully automatic scheme for fiducial marker-based alignment in electron tomography.

PubMed

Han, Renmin; Wang, Liansan; Liu, Zhiyong; Sun, Fei; Zhang, Fa

2015-12-01

Although the topic of fiducial marker-based alignment in electron tomography (ET) has been widely discussed for decades, alignment without human intervention remains a difficult problem. Specifically, the emergence of subtomogram averaging has increased the demand for batch processing during tomographic reconstruction; fully automatic fiducial marker-based alignment is the main technique in this process. However, the lack of an accurate method for detecting and tracking fiducial markers precludes fully automatic alignment. In this paper, we present a novel, fully automatic alignment scheme for ET. Our scheme has two main contributions: First, we present a series of algorithms to ensure a high recognition rate and precise localization during the detection of fiducial markers. Our proposed solution reduces fiducial marker detection to a sampling and classification problem and further introduces an algorithm to solve the parameter dependence of marker diameter and marker number. Second, we propose a novel algorithm to solve the tracking of fiducial markers by reducing the tracking problem to an incomplete point set registration problem. Because a global optimization of a point set registration occurs, the result of our tracking is independent of the initial image position in the tilt series, allowing for the robust tracking of fiducial markers without pre-alignment. The experimental results indicate that our method can achieve an accurate tracking, almost identical to the current best one in IMOD with half automatic scheme. Furthermore, our scheme is fully automatic, depends on fewer parameters (only requires a gross value of the marker diameter) and does not require any manual interaction, providing the possibility of automatic batch processing of electron tomographic reconstruction. Copyright © 2015 Elsevier Inc. All rights reserved.

Detecting skin malignancy using elastic light scattering spectroscopy

NASA Astrophysics Data System (ADS)

Canpolat, Murat; Akman, Ayşe; Çiftçioğlu, M. Akif; Alpsoy, Erkan

2007-07-01

We have used elastic light scattering spectroscopy to differentiate between malign and benign skin lesions. The system consists of a UV spectrometer, a single optical fiber probe and a laptop. The single optical fiber probe was used for both delivery and detection of white light to tissue and from the tissue. The single optical fiber probe received singly scattered photons rather than diffused photons in tissue. Therefore, the spectra are correlated with morphological differences of the cells. It has been shown that spectra of malign skin lesions are different than spectra of benign skin lesions. While slopes of the spectra taken on benign lesions or normal skin tissues were positive, slopes of the spectra taken on malign skin lesions tissues were negative. In vivo experiments were conducted on 20 lesions from 18 patients (11 men with mean age of 68 +/- 9 years and 7 women with mean age of 52 +/- 20 years) applied to the Department of Dermatology and Venerology. Before the biopsy, spectra were taken on the lesion and adjacent (approximately 1 cm distant) normal-appearing skin. Spectra of the normal skin were used as a control group. The spectra were correlated to the pathology results with sensitivity and specificity of 82% and 89%, respectively. Due to small diameter of fiber probe and limited number of sampling (15), some positive cases are missed, which is lowered the sensitivity of the system. The results are promising and could suggest that the system may be able to detect malignant skin lesion non-invasively and in real time.

Automated Detection of Actinic Keratoses in Clinical Photographs

PubMed Central

Hames, Samuel C.; Sinnya, Sudipta; Tan, Jean-Marie; Morze, Conrad; Sahebian, Azadeh; Soyer, H. Peter; Prow, Tarl W.

2015-01-01

Background Clinical diagnosis of actinic keratosis is known to have intra- and inter-observer variability, and there is currently no non-invasive and objective measure to diagnose these lesions. Objective The aim of this pilot study was to determine if automatically detecting and circumscribing actinic keratoses in clinical photographs is feasible. Methods Photographs of the face and dorsal forearms were acquired in 20 volunteers from two groups: the first with at least on actinic keratosis present on the face and each arm, the second with no actinic keratoses. The photographs were automatically analysed using colour space transforms and morphological features to detect erythema. The automated output was compared with a senior consultant dermatologist’s assessment of the photographs, including the intra-observer variability. Performance was assessed by the correlation between total lesions detected by automated method and dermatologist, and whether the individual lesions detected were in the same location as the dermatologist identified lesions. Additionally, the ability to limit false positives was assessed by automatic assessment of the photographs from the no actinic keratosis group in comparison to the high actinic keratosis group. Results The correlation between the automatic and dermatologist counts was 0.62 on the face and 0.51 on the arms, compared to the dermatologist’s intra-observer variation of 0.83 and 0.93 for the same. Sensitivity of automatic detection was 39.5% on the face, 53.1% on the arms. Positive predictive values were 13.9% on the face and 39.8% on the arms. Significantly more lesions (p<0.0001) were detected in the high actinic keratosis group compared to the no actinic keratosis group. Conclusions The proposed method was inferior to assessment by the dermatologist in terms of sensitivity and positive predictive value. However, this pilot study used only a single simple feature and was still able to achieve sensitivity of detection of 53.1% on the arms.This suggests that image analysis is a feasible avenue of investigation for overcoming variability in clinical assessment. Future studies should focus on more sophisticated features to improve sensitivity for actinic keratoses without erythema and limit false positives associated with the anatomical structures on the face. PMID:25615930

Enhanced automatic artifact detection based on independent component analysis and Renyi's entropy.

PubMed

Mammone, Nadia; Morabito, Francesco Carlo

2008-09-01

Artifacts are disturbances that may occur during signal acquisition and may affect their processing. The aim of this paper is to propose a technique for automatically detecting artifacts from the electroencephalographic (EEG) recordings. In particular, a technique based on both Independent Component Analysis (ICA) to extract artifactual signals and on Renyi's entropy to automatically detect them is presented. This technique is compared to the widely known approach based on ICA and the joint use of kurtosis and Shannon's entropy. The novel processing technique is shown to detect on average 92.6% of the artifactual signals against the average 68.7% of the previous technique on the studied available database. Moreover, Renyi's entropy is shown to be able to detect muscle and very low frequency activity as well as to discriminate them from other kinds of artifacts. In order to achieve an efficient rejection of the artifacts while minimizing the information loss, future efforts will be devoted to the improvement of blind artifact separation from EEG in order to ensure a very efficient isolation of the artifactual activity from any signals deriving from other brain tasks.

Automatic rectum limit detection by anatomical markers correlation.

PubMed

Namías, R; D'Amato, J P; del Fresno, M; Vénere, M

2014-06-01

Several diseases take place at the end of the digestive system. Many of them can be diagnosed by means of different medical imaging modalities together with computer aided detection (CAD) systems. These CAD systems mainly focus on the complete segmentation of the digestive tube. However, the detection of limits between different sections could provide important information to these systems. In this paper we present an automatic method for detecting the rectum and sigmoid colon limit using a novel global curvature analysis over the centerline of the segmented digestive tube in different imaging modalities. The results are compared with the gold standard rectum upper limit through a validation scheme comprising two different anatomical markers: the third sacral vertebra and the average rectum length. Experimental results in both magnetic resonance imaging (MRI) and computed tomography colonography (CTC) acquisitions show the efficacy of the proposed strategy in automatic detection of rectum limits. The method is intended for application to the rectum segmentation in MRI for geometrical modeling and as contextual information source in virtual colonoscopies and CAD systems. Copyright © 2014 Elsevier Ltd. All rights reserved.

Silk-molded flexible, ultrasensitive, and highly stable electronic skin for monitoring human physiological signals.

PubMed

Wang, Xuewen; Gu, Yang; Xiong, Zuoping; Cui, Zheng; Zhang, Ting

2014-03-05

Flexible and transparent E-skin devices are achieved by combining silk-molded micro-patterned polydimethylsiloxane (PDMS) with single-walled carbon nanotube (SWNT) ultrathin films. The E-skin sensing device demonstrates superior sensitivity, a very low detectable pressure limit, a fast response time, and a high stability for the detection of superslight pressures, which may broaden their potential use as cost-effective wearable electronics for healthcare applications. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Automatic tracking of wake vortices using ground-wind sensor data

DOT National Transportation Integrated Search

1977-01-03

Algorithms for automatic tracking of wake vortices using ground-wind anemometer : data are developed. Methods of bad-data suppression, track initiation, and : track termination are included. An effective sensor-failure detection-and identification : ...

Blue light-induced oxidative stress in live skin.

PubMed

Nakashima, Yuya; Ohta, Shigeo; Wolf, Alexander M

2017-07-01

Skin damage from exposure to sunlight induces aging-like changes in appearance and is attributed to the ultraviolet (UV) component of light. Photosensitized production of reactive oxygen species (ROS) by UVA light is widely accepted to contribute to skin damage and carcinogenesis, but visible light is thought not to do so. Using mice expressing redox-sensitive GFP to detect ROS, blue light could produce oxidative stress in live skin. Blue light induced oxidative stress preferentially in mitochondria, but green, red, far red or infrared light did not. Blue light-induced oxidative stress was also detected in cultured human keratinocytes, but the per photon efficacy was only 25% of UVA in human keratinocyte mitochondria, compared to 68% of UVA in mouse skin. Skin autofluorescence was reduced by blue light, suggesting flavins are the photosensitizer. Exposing human skin to the blue light contained in sunlight depressed flavin autofluorescence, demonstrating that the visible component of sunlight has a physiologically significant effect on human skin. The ROS produced by blue light is probably superoxide, but not singlet oxygen. These results suggest that blue light contributes to skin aging similar to UVA. Copyright © 2017 Elsevier Inc. All rights reserved.

Farmers sun exposure, skin protection and public health campaigns: An Australian perspective.

PubMed

Smit-Kroner, Christel; Brumby, Susan

2015-01-01

Non-melanoma skin cancer is a common and costly cancer in agricultural populations. Prevention and early detection are an effective way to decrease the burden of disease and associated costs. To examine sun exposure and skin protection practices in agricultural workers and farmers a thematic review of the literature between 1983 and 2014 was undertaken. Comparison between studies was complicated by differences in study design, definitions of skin protection, and analytic methods used. Farmers are the most exposed to harmful ultraviolet (UV) radiation of all outdoor workers and the level of reported skin protection by farmers is suboptimal. Years of public health campaigns have failed to adequately address farmers' specific needs. Increased rates of skin cancer and subsequent higher costs are expected. Estimates of sun exposure and skin protection practice indicate that protective clothing is the most promising avenue to improve on farmers' skin protection. Early detection needs to be part of public health campaigns. This review explores the quantitative data about Australian farmers and their skin protective behaviours. We investigate what the documented measurable effect of the public health campaign Slip!Slop!Slap! has had on agricultural workers and farmers and make recommendations for future focus.

Fully automatic oil spill detection from COSMO-SkyMed imagery using a neural network approach

NASA Astrophysics Data System (ADS)

Avezzano, Ruggero G.; Del Frate, Fabio; Latini, Daniele

2012-09-01

The increased amount of available Synthetic Aperture Radar (SAR) images acquired over the ocean represents an extraordinary potential for improving oil spill detection activities. On the other side this involves a growing workload on the operators at analysis centers. In addition, even if the operators go through extensive training to learn manual oil spill detection, they can provide different and subjective responses. Hence, the upgrade and improvements of algorithms for automatic detection that can help in screening the images and prioritizing the alarms are of great benefit. In the framework of an ASI Announcement of Opportunity for the exploitation of COSMO-SkyMed data, a research activity (ASI contract L/020/09/0) aiming at studying the possibility to use neural networks architectures to set up fully automatic processing chains using COSMO-SkyMed imagery has been carried out and results are presented in this paper. The automatic identification of an oil spill is seen as a three step process based on segmentation, feature extraction and classification. We observed that a PCNN (Pulse Coupled Neural Network) was capable of providing a satisfactory performance in the different dark spots extraction, close to what it would be produced by manual editing. For the classification task a Multi-Layer Perceptron (MLP) Neural Network was employed.

Automatic image enhancement based on multi-scale image decomposition

NASA Astrophysics Data System (ADS)

Feng, Lu; Wu, Zhuangzhi; Pei, Luo; Long, Xiong

2014-01-01

In image processing and computational photography, automatic image enhancement is one of the long-range objectives. Recently the automatic image enhancement methods not only take account of the globe semantics, like correct color hue and brightness imbalances, but also the local content of the image, such as human face and sky of landscape. In this paper we describe a new scheme for automatic image enhancement that considers both global semantics and local content of image. Our automatic image enhancement method employs the multi-scale edge-aware image decomposition approach to detect the underexposure regions and enhance the detail of the salient content. The experiment results demonstrate the effectiveness of our approach compared to existing automatic enhancement methods.

Visual mismatch negativity indicates automatic, task-independent detection of artistic image composition in abstract artworks.

PubMed

Menzel, Claudia; Kovács, Gyula; Amado, Catarina; Hayn-Leichsenring, Gregor U; Redies, Christoph

2018-05-06

In complex abstract art, image composition (i.e., the artist's deliberate arrangement of pictorial elements) is an important aesthetic feature. We investigated whether the human brain detects image composition in abstract artworks automatically (i.e., independently of the experimental task). To this aim, we studied whether a group of 20 original artworks elicited a visual mismatch negativity when contrasted with a group of 20 images that were composed of the same pictorial elements as the originals, but in shuffled arrangements, which destroy artistic composition. We used a passive oddball paradigm with parallel electroencephalogram recordings to investigate the detection of image type-specific properties. We observed significant deviant-standard differences for the shuffled and original images, respectively. Furthermore, for both types of images, differences in amplitudes correlated with the behavioral ratings of the images. In conclusion, we show that the human brain can detect composition-related image properties in visual artworks in an automatic fashion. Copyright © 2018 Elsevier B.V. All rights reserved.

Automatic Detection and Vulnerability Analysis of Areas Endangered by Heavy Rain

NASA Astrophysics Data System (ADS)

Krauß, Thomas; Fischer, Peter

2016-08-01

In this paper we present a new method for fully automatic detection and derivation of areas endangered by heavy rainfall based only on digital elevation models. Tracking news show that the majority of occuring natural hazards are flood events. So already many flood prediction systems were developed. But most of these existing systems for deriving areas endangered by flooding events are based only on horizontal and vertical distances to existing rivers and lakes. Typically such systems take not into account dangers arising directly from heavy rain events. In a study conducted by us together with a german insurance company a new approach for detection of areas endangered by heavy rain was proven to give a high correlation of the derived endangered areas and the losses claimed at the insurance company. Here we describe three methods for classification of digital terrain models and analyze their usability for automatic detection and vulnerability analysis for areas endangered by heavy rainfall and analyze the results using the available insurance data.

[Blood stream infection and blood culture--"progress" and "blind" in blood culture testing].

PubMed

Kobayashi, Intetsu

2005-04-01

We have investigated various types of blood culture bottles which are mainly used at present and posed problems present in the blood culture bottles. First, there are differences between resin and ecosorb in the ability to adsorb and inactivate antibiotics in the blood. Second, the delay in placing the bottle (into which blood was inoculated) to the automatic instrument (delay in the start of incubation) greatly affects the automatic detection by BACTEC system and shows false negatives. Third, when the same blood is incubated in plural bottles (aerobic and anaerobic bottles), the differences among the detected organisms in the number are comparatively high, i.e., about 40%. In addition, there are differences among the organisms in the number of days required for the detection of the organisms. In this case, the detected organisms are clearly different in many cases. The technology of blood culture has been progressed remarkably. However, the efficiency of utilization of automatic instruments for diagnosis of infection depends greatly on the ability of laboratory technicians.

Detection of exudates in fundus images using a Markovian segmentation model.

PubMed

Harangi, Balazs; Hajdu, Andras

2014-01-01

Diabetic retinopathy (DR) is one of the most common causing of vision loss in developed countries. In early stage of DR, some signs like exudates appear in the retinal images. An automatic screening system must be capable to detect these signs properly so that the treatment of the patients may begin in time. The appearance of exudates shows a rich variety regarding their shape and size making automatic detection more challenging. We propose a way for the automatic segmentation of exudates consisting of a candidate extraction step followed by exact contour detection and region-wise classification. More specifically, we extract possible exudate candidates using grayscale morphology and their proper shape is determined by a Markovian segmentation model considering edge information. Finally, we label the candidates as true or false ones by an optimally adjusted SVM classifier. For testing purposes, we considered the publicly available database DiaretDB1, where the proposed method outperformed several state-of-the-art exudate detectors.

Automatic sentence extraction for the detection of scientific paper relations

NASA Astrophysics Data System (ADS)

Sibaroni, Y.; Prasetiyowati, S. S.; Miftachudin, M.

2018-03-01

The relations between scientific papers are very useful for researchers to see the interconnection between scientific papers quickly. By observing the inter-article relationships, researchers can identify, among others, the weaknesses of existing research, performance improvements achieved to date, and tools or data typically used in research in specific fields. So far, methods that have been developed to detect paper relations include machine learning and rule-based methods. However, a problem still arises in the process of sentence extraction from scientific paper documents, which is still done manually. This manual process causes the detection of scientific paper relations longer and inefficient. To overcome this problem, this study performs an automatic sentences extraction while the paper relations are identified based on the citation sentence. The performance of the built system is then compared with that of the manual extraction system. The analysis results suggested that the automatic sentence extraction indicates a very high level of performance in the detection of paper relations, which is close to that of manual sentence extraction.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Batal, Mohamed; Département de Toxicologie et Risques Chimiques, Unité de Brûlure Chimique, Institut de Recherche Biomédicale des Armées, Antenne de La Tronche; Boudry, Isabelle

Sulfur mustard (SM) is a chemical warfare agent that targets skin where it induces large blisters. DNA alkylation is a critical step to explain SM-induced cutaneous symptoms. We determined the kinetics of formation of main SM–DNA adducts and compare it with the development of the SM-induced pathogenesis in skin. SKH-1 mice were exposed to 2, 6 and 60 mg/kg of SM and treated skin was biopsied between 6 h and 21 days. Formation of SM DNA adducts was dose-dependent with a maximum immediately after exposure. However, adducts were persistent and still detectable 21 days post-exposure. The time-dependent formation of DNAmore » adducts was also found to be correlated with the appearance of apoptotic cells. This temporal correlation suggests that these two early events are responsible for the severity of the damage to the skin. Besides, SM–DNA adducts were also detected in areas located next to contaminated zone, thus suggesting that SM diffuses in skin. Altogether, this work provides for the first time a clear picture of SM-induced genotoxicity using DNA adducts as a marker. - Highlights: • Sulfur mustard adducts are formed in DNA after skin exposure. • DNA damage formation is an early event in the pathological process of skin burn. • The amount of SM–DNA adducts is maximal at the earliest time point investigated. • Adducts are still detected 3 weeks after exposure. • Sulfur mustard diffuses in skin especially when large doses are applied.« less

Operational research on the correlation between skin diseases and HIV infection in Tigray region, Ethiopia.

PubMed

Padovese, Valeska; Racalbuto, Vincenzo; Barnabas, Gebre Ab; Morrone, Aldo

2015-10-01

In Ethiopia, skin diseases are among the leading causes of outpatient attendance to primary health service. Correlation of skin diseases and HIV has long been recognized and used to guide medical management in resource-limited settings. Therefore, this study aims to assess the correlation of skin diseases and HIV infection, to estimate epidemiological distribution in the study area, and to provide health workers of skin indicators for HIV early detection. The operational research was designed as a case-control study and carried out in three intervention districts of Tigray region; baseline and final data on skin diseases and HIV were compared with those of three control districts matched for population size, density, and environmental characteristics. Health workers of intervention districts were trained on skin diseases/STIs diagnosis and treatment. Data were collected from study and control districts and then analyzed at the Italian Dermatological Centre (IDC) in Mekele. In the research period, a total of 1044 HIV positive patients were detected. Disorders of skin and mucous membranes statistically related with HIV (P < 0.05) were tongue papillary atrophy (80%), oral hairy leukoplakia (69%), herpes zoster (66%), oral candidiasis (50%), pruritic papular eruption (43%), condylomata acuminata (38%), and telogen effluvium (27%). The high frequency of oral disorders and telogen effluvium is not described in literature and may be indicative for case detection. Operational research offers significant gains on health service delivery and outcomes at relatively low cost and in a short timeframe. © 2015 The International Society of Dermatology.

The human homeobox genes MSX-1, MSX-2, and MOX-1 are differentially expressed in the dermis and epidermis in fetal and adult skin.

PubMed

Stelnicki, E J; Kömüves, L G; Holmes, D; Clavin, W; Harrison, M R; Adzick, N S; Largman, C

1997-10-01

In order to identify homeobox genes which may regulate skin development and possibly mediate scarless fetal wound healing we have screened amplified human fetal skin cDNAs by polymerase chain reaction (PCR) using degenerate oligonucleotide primers designed against highly conserved regions within the homeobox. We identified three non-HOX homeobox genes, MSX-1, MSX-2, and MOX-1, which were differentially expressed in fetal and adult human skin. MSX-1 and MSX-2 were detected in the epidermis, hair follicles, and fibroblasts of the developing fetal skin by in situ hybridization. In contrast, MSX-1 and MSX-2 expression in adult skin was confined to epithelially derived structures. Immunohistochemical analysis of these two genes suggested that their respective homeoproteins may be differentially regulated. While Msx-1 was detected in the cell nucleus of both fetal and adult skin; Msx-2 was detected as a diffuse cytoplasmic signal in fetal epidermis and portions of the hair follicle and dermis, but was localized to the nucleus in adult epidermis. MOX-1 was expressed in a pattern similar to MSX early in gestation but then was restricted exclusively to follicular cells in the innermost layer of the outer root sheath by 21 weeks of development. Furthermore, MOX-1 expression was completely absent in adult cutaneous tissue. These data imply that each of these homeobox genes plays a specific role in skin development.

Rapid detection of trichodysplasia spinulosa-associated polyomavirus in skin biopsy specimen.

PubMed

Urbano, Paulo Roberto P; Pannuti, Cláudio Sérgio; Pierrotti, Ligia C; David-Neto, Elias; Romano, Camila Malta

2014-07-24

Trichodysplasia spinulosa-associated polyomavirus (TSV) is responsible for a rare skin cancer. Using metagenomic approaches, we determined the complete genome sequence of a TSV first detected in Brazil in spicules of an immunocompromised patient suspected to have trichodysplasia spinulosa. Copyright © 2014 Urbano et al.

Automated assessment of joint synovitis activity from medical ultrasound and power doppler examinations using image processing and machine learning methods.

PubMed

Cupek, Rafal; Ziębiński, Adam

2016-01-01

Rheumatoid arthritis is the most common rheumatic disease with arthritis, and causes substantial functional disability in approximately 50% patients after 10 years. Accurate measurement of the disease activity is crucial to provide an adequate treatment and care to the patients. The aim of this study is focused on a computer aided diagnostic system that supports an assessment of synovitis severity. This paper focus on a computer aided diagnostic system that was developed within joint Polish-Norwegian research project related to the automated assessment of the severity of synovitis. Semiquantitative ultrasound with power Doppler is a reliable and widely used method of assessing synovitis. Synovitis is estimated by ultrasound examiner using the scoring system graded from 0 to 3. Activity score is estimated on the basis of the examiner's experience or standardized ultrasound atlases. The method needs trained medical personnel and the result can be affected by a human error. The porotype of a computer-aided diagnostic system and algorithms essential for an analysis of ultrasonic images of finger joints are main scientific output of the MEDUSA project. Medusa Evaluation System prototype uses bone, skin, joint and synovitis area detectors for mutual structural model based evaluation of synovitis. Finally, several algorithms that support the semi-automatic or automatic detection of the bone region were prepared as well as a system that uses the statistical data processing approach in order to automatically localize the regions of interest. Semiquantitative ultrasound with power Doppler is a reliable and widely used method of assessing synovitis. Activity score is estimated on the basis of the examiner's experience and the result can be affected by a human error. In this paper we presented the MEDUSA project which is focused on a computer aided diagnostic system that supports an assessment of synovitis severity.

Automatic Pedestrian Crossing Detection and Impairment Analysis Based on Mobile Mapping System

NASA Astrophysics Data System (ADS)

Liu, X.; Zhang, Y.; Li, Q.

2017-09-01

Pedestrian crossing, as an important part of transportation infrastructures, serves to secure pedestrians' lives and possessions and keep traffic flow in order. As a prominent feature in the street scene, detection of pedestrian crossing contributes to 3D road marking reconstruction and diminishing the adverse impact of outliers in 3D street scene reconstruction. Since pedestrian crossing is subject to wearing and tearing from heavy traffic flow, it is of great imperative to monitor its status quo. On this account, an approach of automatic pedestrian crossing detection using images from vehicle-based Mobile Mapping System is put forward and its defilement and impairment are analyzed in this paper. Firstly, pedestrian crossing classifier is trained with low recall rate. Then initial detections are refined by utilizing projection filtering, contour information analysis, and monocular vision. Finally, a pedestrian crossing detection and analysis system with high recall rate, precision and robustness will be achieved. This system works for pedestrian crossing detection under different situations and light conditions. It can recognize defiled and impaired crossings automatically in the meanwhile, which facilitates monitoring and maintenance of traffic facilities, so as to reduce potential traffic safety problems and secure lives and property.

A Knowledge-Based Approach to Automatic Detection of Equipment Alarm Sounds in a Neonatal Intensive Care Unit Environment.

PubMed

Raboshchuk, Ganna; Nadeu, Climent; Jancovic, Peter; Lilja, Alex Peiro; Kokuer, Munevver; Munoz Mahamud, Blanca; Riverola De Veciana, Ana

2018-01-01

A large number of alarm sounds triggered by biomedical equipment occur frequently in the noisy environment of a neonatal intensive care unit (NICU) and play a key role in providing healthcare. In this paper, our work on the development of an automatic system for detection of acoustic alarms in that difficult environment is presented. Such automatic detection system is needed for the investigation of how a preterm infant reacts to auditory stimuli of the NICU environment and for an improved real-time patient monitoring. The approach presented in this paper consists of using the available knowledge about each alarm class in the design of the detection system. The information about the frequency structure is used in the feature extraction stage, and the time structure knowledge is incorporated at the post-processing stage. Several alternative methods are compared for feature extraction, modeling, and post-processing. The detection performance is evaluated with real data recorded in the NICU of the hospital, and by using both frame-level and period-level metrics. The experimental results show that the inclusion of both spectral and temporal information allows to improve the baseline detection performance by more than 60%.

Automatic Detection of Optic Disc in Retinal Image by Using Keypoint Detection, Texture Analysis, and Visual Dictionary Techniques

PubMed Central

Bayır, Şafak

2016-01-01

With the advances in the computer field, methods and techniques in automatic image processing and analysis provide the opportunity to detect automatically the change and degeneration in retinal images. Localization of the optic disc is extremely important for determining the hard exudate lesions or neovascularization, which is the later phase of diabetic retinopathy, in computer aided eye disease diagnosis systems. Whereas optic disc detection is fairly an easy process in normal retinal images, detecting this region in the retinal image which is diabetic retinopathy disease may be difficult. Sometimes information related to optic disc and hard exudate information may be the same in terms of machine learning. We presented a novel approach for efficient and accurate localization of optic disc in retinal images having noise and other lesions. This approach is comprised of five main steps which are image processing, keypoint extraction, texture analysis, visual dictionary, and classifier techniques. We tested our proposed technique on 3 public datasets and obtained quantitative results. Experimental results show that an average optic disc detection accuracy of 94.38%, 95.00%, and 90.00% is achieved, respectively, on the following public datasets: DIARETDB1, DRIVE, and ROC. PMID:27110272

A Knowledge-Based Approach to Automatic Detection of Equipment Alarm Sounds in a Neonatal Intensive Care Unit Environment

PubMed Central

Nadeu, Climent; Jančovič, Peter; Lilja, Alex Peiró; Köküer, Münevver; Muñoz Mahamud, Blanca; Riverola De Veciana, Ana

2018-01-01

A large number of alarm sounds triggered by biomedical equipment occur frequently in the noisy environment of a neonatal intensive care unit (NICU) and play a key role in providing healthcare. In this paper, our work on the development of an automatic system for detection of acoustic alarms in that difficult environment is presented. Such automatic detection system is needed for the investigation of how a preterm infant reacts to auditory stimuli of the NICU environment and for an improved real-time patient monitoring. The approach presented in this paper consists of using the available knowledge about each alarm class in the design of the detection system. The information about the frequency structure is used in the feature extraction stage, and the time structure knowledge is incorporated at the post-processing stage. Several alternative methods are compared for feature extraction, modeling, and post-processing. The detection performance is evaluated with real data recorded in the NICU of the hospital, and by using both frame-level and period-level metrics. The experimental results show that the inclusion of both spectral and temporal information allows to improve the baseline detection performance by more than 60%. PMID:29404227

Handheld dual fluorescence and reflection spectroscopy system for monitoring topical low dose ALA-PDT of actinic keratoses (AK)

NASA Astrophysics Data System (ADS)

Charamisinau, Ivan; Keymel, Kenneth; Potter, William; Oseroff, Allan R.

2006-02-01

Photodynamic therapy is an effective, minimally invasive skin cancer treatment modality with few side effects. Improved therapeutic selectivity and efficacy is expected if treatment is optimized individually for each patient based on detailed measurements prior and during the treatment. The handheld system presented allows measuring optical properties of the skin, the rate of photosensitizer photobleaching during the ALA PDT and oxygen saturation in the tissue. The photobleaching rate is monitored using fluorescence spectroscopy, where protoporphyrin IX in tissue is exited by 410 nm (blue) or 532 nm (green) laser light, and fluorescence in the 580-800 nm range is monitored. The photobleaching rate is calculated by correlating the measured spectrum with known protoporphyrin IX, photoproduct and nonspecific tissue autofluorescence spectra using correlation analysis. Double-wavelength excitation allows a rough estimation of the depth of the fluorescence source due to the significant difference in penetration depth for blue and green light. Blood concentration and oxygenation in the tissue are found from the white light reflectance spectrum in the 460-800 nm range. Known spectra for the oxy- and deoxyhemoglobin, melanin, and tissue baseline absorption and tissue scattering are substituted in nonlinear equations to find the penetration depth and diffuse reflectance coefficient. The nonlinear equation for the diffuse reflectance coefficient is solved for blood and melanin concentrations and blood oxygenation values that provide the best fit to the measured spectrum. The optical properties of the tissue obtained from the reflectance spectroscopy are used to correct the fluorescence data. A noncontact probe with 5 fibers (3 excitation and 2 detection) focused to the same 5 mm diameter spot: 2 excitation lasers, a white light lamp and a two-channel spectrometer are used. A LabView program with custom nonlinear equation solvers written in C++ automatically performs the measurements and calculations, and writes data to a database. The system is currently used in a clinical trial to find the relationship between skin pigmentation, oxygen saturation in blood, photobleaching rate and optimal fluence rate for skin cancer treatment of actinic keratoses.

Use of Munsell color charts to measure skin tone objectively in nursing home residents at risk for pressure ulcer development.

PubMed

McCreath, Heather E; Bates-Jensen, Barbara M; Nakagami, Gojiro; Patlan, Anabel; Booth, Howard; Connolly, Dana; Truong, Cyndi; Woldai, Agazi

2016-09-01

To assess the feasibility of classifying skin tone using Munsell color chart values and to compare Munsell-based skin tone categories to ethnicity/race to predict pressure ulcer risk. Pressure ulcer classification uses level of visible tissue damage, including skin discoloration over bony prominences. Prevention begins with early detection of damage. Skin discoloration in those with dark skin tones can be difficult to observe, hindering early detection. Observational cohort of 417 nursing home residents from 19 nursing homes collected between 2009-2014, with weekly skin assessments for up to 16 weeks. Assessment included forearm and buttocks skin tone based on Munsell values (Dark, Medium, Light) at three time points, ethnicity/race medical record documentation, and weekly skin assessment on trunk and heels. Inter-rater reliability was high for forearm and buttock values and skin tone. Mean Munsell buttocks values differed significantly by ethnicity/race. Across ethnicity/race, Munsell value ranges overlapped, with the greatest range among African Americans. Trunk pressure ulcer incidence varied by skin tone, regardless of ethnicity/race. In multinomial regression, skin tone was more predictive of skin damage than ethnicity/race for trunk locations but ethnicity/race was more predictive for heels. Given the overlap of Munsell values across ethnicity/race, color charts provide more objective measurement of skin tone than demographic categories. An objective measure of skin tone can improve pressure ulcer risk assessment among patients for whom current clinical guidelines are less effective. © 2016 John Wiley & Sons Ltd.

Investigating Low-Cost Optical Spectroscopy for Sensing Pressure Ulcers

NASA Astrophysics Data System (ADS)

Mirchandani, Smruti Suresh

Diffuse Reflectance Spectroscopy has been used widely to characterize tissue properties for diagnostic and therapeutic applications. This thesis focuses on the use of spectroscopy for early pressure ulcer detection. The most common early diagnosis technique for pressure ulcers is a blanch test. A major issue with a blanch test is that it is purely visual and cannot be visibly observed on dark skinned individuals. Studies have already proven that spectroscopy can be used to detect blanch response in skin across light and dark skinned individuals. The portable reflectance spectroscopy setup showed that pressure changes to the skin can be detected spectroscopically. Some work on an iPhone based spectrometer was also done to have a low-cost spectroscopy alternative to the usual DRS equipment. This study failed to develop an iPhone based spectrometer but various factors that can be changed to better this research have been mentioned in this thesis.

Psychological state estimation from physiological recordings during robot-assisted gait rehabilitation.

PubMed

Koenig, Alexander; Omlin, Ximena; Zimmerli, Lukas; Sapa, Mark; Krewer, Carmen; Bolliger, Marc; Müller, Friedemann; Riener, Robert

2011-01-01

Robot-assisted treadmill training is an established intervention used to improve walking ability in patients with neurological disorders. Although it has been shown that attention to the task is a key factor for successful rehabilitation, the psychological state of patients during robot-assisted gait therapy is often neglected. We presented 17 nondisabled subjects and 10 patients with neurological disorders a virtual-reality task with varying difficulty levels to induce feelings of being bored, excited, and overstressed. We developed an approach to automatically estimate and classify a patient's psychological state, i.e., his or her mental engagement, in real time during gait training. We used psychophysiological measurements to obtain an objective measure of the current psychological state. Automatic classification was performed by a neural network. We found that heart rate, skin conductance responses, and skin temperature can be used as markers for psychological states in the presence of physical effort induced by walking. The classifier achieved a classification error of 1.4% for nondisabled subjects and 2.1% for patients with neurological disorders. Using our new method, we processed the psychological state data in real time. Our method is a first step toward real-time auto-adaptive gait training with potential to improve rehabilitation results by optimally challenging patients at all times during exercise.

New approach for cystic fibrosis diagnosis based on chloride/potassium ratio analyzed in non-invasively obtained skin-wipe sweat samples by capillary electrophoresis with contactless conductometric detection.

PubMed

Ďurč, Pavol; Foret, František; Pokojová, Eva; Homola, Lukáš; Skřičková, Jana; Herout, Vladimír; Dastych, Milan; Vinohradská, Hana; Kubáň, Petr

2017-05-01

A new approach for sweat analysis used in cystic fibrosis (CF) diagnosis is proposed. It consists of a noninvasive skin-wipe sampling followed by analysis of target ions using capillary electrophoresis with contactless conductometric detection (C4D). The skin-wipe sampling consists of wiping a defined skin area with precleaned cotton swab moistened with 100 μL deionized water. The skin-wipe sample is then extracted for 3 min into 400 μL deionized water, and the extract is analyzed directly. The developed sampling method is cheap, simple, fast, and painless, and can replace the conventional pilocarpine-induced sweat chloride test commonly applied in CF diagnosis. The aqueous extract of the skin-wipe sample content is analyzed simultaneously by capillary electrophoresis with contactless conductometric detection using a double opposite end injection. A 20 mmol/L L-histidine/2-(N-morpholino)ethanesulfonic acid and 2 mmol/L 18-crown-6 at pH 6 electrolyte can separate all the major ions in less than 7 min. Skin-wipe sample extracts from 30 study participants-ten adult patients with CF (25-50 years old), ten pediatric patients with CF (1-15 years old), and ten healthy control individuals (1-18 years old)-were obtained and analyzed. From the analyzed ions in all samples, a significant difference between chloride and potassium concentrations was found in the CF patients and healthy controls. We propose the use of the Cl - /K + ratio rather than the absolute Cl - concentration and a cutoff value of 4 in skin-wipe sample extracts as an alternative to the conventional sweat chloride analysis. The proposed Cl - /K + ion ratio proved to be a more reliable indicator, is independent of the patient's age, and allows better differentiation between non-CF individuals and CF patients having intermediate values on the Cl - sweat test. Figure New approach for cystic fibrosis diagnosis based on skin-wipe sampling of forearm and analysis of ionic content (Cl - /K + ratio) in skin-wipe extracts by capillary electrophoresis with contactless conductometric detection.

Automatic detection of snow avalanches in continuous seismic data using hidden Markov models

NASA Astrophysics Data System (ADS)

Heck, Matthias; Hammer, Conny; van Herwijnen, Alec; Schweizer, Jürg; Fäh, Donat

2018-01-01

Snow avalanches generate seismic signals as many other mass movements. Detection of avalanches by seismic monitoring is highly relevant to assess avalanche danger. In contrast to other seismic events, signals generated by avalanches do not have a characteristic first arrival nor is it possible to detect different wave phases. In addition, the moving source character of avalanches increases the intricacy of the signals. Although it is possible to visually detect seismic signals produced by avalanches, reliable automatic detection methods for all types of avalanches do not exist yet. We therefore evaluate whether hidden Markov models (HMMs) are suitable for the automatic detection of avalanches in continuous seismic data. We analyzed data recorded during the winter season 2010 by a seismic array deployed in an avalanche starting zone above Davos, Switzerland. We re-evaluated a reference catalogue containing 385 events by grouping the events in seven probability classes. Since most of the data consist of noise, we first applied a simple amplitude threshold to reduce the amount of data. As first classification results were unsatisfying, we analyzed the temporal behavior of the seismic signals for the whole data set and found that there is a high variability in the seismic signals. We therefore applied further post-processing steps to reduce the number of false alarms by defining a minimal duration for the detected event, implementing a voting-based approach and analyzing the coherence of the detected events. We obtained the best classification results for events detected by at least five sensors and with a minimal duration of 12 s. These processing steps allowed identifying two periods of high avalanche activity, suggesting that HMMs are suitable for the automatic detection of avalanches in seismic data. However, our results also showed that more sensitive sensors and more appropriate sensor locations are needed to improve the signal-to-noise ratio of the signals and therefore the classification.

Automatic Lamp and Fan Control Based on Microcontroller

NASA Astrophysics Data System (ADS)

Widyaningrum, V. T.; Pramudita, Y. D.

2018-01-01

In general, automation can be described as a process following pre-determined sequential steps with a little or without any human exertion. Automation is provided with the use of various sensors suitable to observe the production processes, actuators and different techniques and devices. In this research, the automation system developed is an automatic lamp and an automatic fan on the smart home. Both of these systems will be processed using an Arduino Mega 2560 microcontroller. A microcontroller is used to obtain values of physical conditions through sensors connected to it. In the automatic lamp system required sensors to detect the light of the LDR (Light Dependent Resistor) sensor. While the automatic fan system required sensors to detect the temperature of the DHT11 sensor. In tests that have been done lamps and fans can work properly. The lamp can turn on automatically when the light begins to darken, and the lamp can also turn off automatically when the light begins to bright again. In addition, it can concluded also that the readings of LDR sensors are placed outside the room is different from the readings of LDR sensors placed in the room. This is because the light intensity received by the existing LDR sensor in the room is blocked by the wall of the house or by other objects. Then for the fan, it can also turn on automatically when the temperature is greater than 25°C, and the fan speed can also be adjusted. The fan may also turn off automatically when the temperature is less than equal to 25°C.

An Automatic Video Meteor Observation Using UFO Capture at the Showa Station

NASA Astrophysics Data System (ADS)

Fujiwara, Y.; Nakamura, T.; Ejiri, M.; Suzuki, H.

2012-05-01

The goal of our study is to clarify meteor activities in the southern hemi-sphere by continuous optical observations with video cameras with automatic meteor detection and recording at Syowa station, Antarctica.

Using airborne LiDAR in geoarchaeological contexts: Assessment of an automatic tool for the detection and the morphometric analysis of grazing archaeological structures (French Massif Central).

NASA Astrophysics Data System (ADS)

Roussel, Erwan; Toumazet, Jean-Pierre; Florez, Marta; Vautier, Franck; Dousteyssier, Bertrand

2014-05-01

Airborne laser scanning (ALS) of archaeological regions of interest is nowadays a widely used and established method for accurate topographic and microtopographic survey. The penetration of the vegetation cover by the laser beam allows the reconstruction of reliable digital terrain models (DTM) of forested areas where traditional prospection methods are inefficient, time-consuming and non-exhaustive. The ALS technology provides the opportunity to discover new archaeological features hidden by vegetation and provides a comprehensive survey of cultural heritage sites within their environmental context. However, the post-processing of LiDAR points clouds produces a huge quantity of data in which relevant archaeological features are not easily detectable with common visualizing and analysing tools. Undoubtedly, there is an urgent need for automation of structures detection and morphometric extraction techniques, especially for the "archaeological desert" in densely forested areas. This presentation deals with the development of automatic detection procedures applied to archaeological structures located in the French Massif Central, in the western forested part of the Puy-de-Dôme volcano between 950 and 1100 m a.s.l.. These unknown archaeological sites were discovered by the March 2011 ALS mission and display a high density of subcircular depressions with a corridor access. The spatial organization of these depressions vary from isolated to aggregated or aligned features. Functionally, they appear to be former grazing constructions built from the medieval to the modern period. Similar grazing structures are known in other locations of the French Massif Central (Sancy, Artense, Cézallier) where the ground is vegetation-free. In order to develop a reliable process of automatic detection and mapping of these archaeological structures, a learning zone has been delineated within the ALS surveyed area. The grazing features were mapped and typical morphometric attributes were calculated based on 2 methods: (i) The mapping of the archaeological structures by a human operator using common visualisation tools (DTM, multi-direction hillshading & local relief models) within a GIS environment; (ii) The automatic detection and mapping performed by a recognition algorithm based on a user defined geometric pattern of the grazing structures. The efficiency of the automatic tool has been assessed by comparing the number of structures detected and the morphometric attributes calculated by the two methods. Our results indicate that the algorithm is efficient for the detection and the location of grazing structures. Concerning the morphometric results, there is still a discrepancy between automatic and expert calculations, due to both the expert mapping choices and the algorithm calibration.

Automated coronary artery calcification detection on low-dose chest CT images

NASA Astrophysics Data System (ADS)

Xie, Yiting; Cham, Matthew D.; Henschke, Claudia; Yankelevitz, David; Reeves, Anthony P.

2014-03-01

Coronary artery calcification (CAC) measurement from low-dose CT images can be used to assess the risk of coronary artery disease. A fully automatic algorithm to detect and measure CAC from low-dose non-contrast, non-ECG-gated chest CT scans is presented. Based on the automatically detected CAC, the Agatston score (AS), mass score and volume score were computed. These were compared with scores obtained manually from standard-dose ECG-gated scans and low-dose un-gated scans of the same patient. The automatic algorithm segments the heart region based on other pre-segmented organs to provide a coronary region mask. The mitral valve and aortic valve calcification is identified and excluded. All remaining voxels greater than 180HU within the mask region are considered as CAC candidates. The heart segmentation algorithm was evaluated on 400 non-contrast cases with both low-dose and regular dose CT scans. By visual inspection, 371 (92.8%) of the segmentations were acceptable. The automated CAC detection algorithm was evaluated on 41 low-dose non-contrast CT scans. Manual markings were performed on both low-dose and standard-dose scans for these cases. Using linear regression, the correlation of the automatic AS with the standard-dose manual scores was 0.86; with the low-dose manual scores the correlation was 0.91. Standard risk categories were also computed. The automated method risk category agreed with manual markings of gated scans for 24 cases while 15 cases were 1 category off. For low-dose scans, the automatic method agreed with 33 cases while 7 cases were 1 category off.

A low cost automatic detection and ranging system for space surveillance in the medium Earth orbit region and beyond.

PubMed

Danescu, Radu; Ciurte, Anca; Turcu, Vlad

2014-02-11

The space around the Earth is filled with man-made objects, which orbit the planet at altitudes ranging from hundreds to tens of thousands of kilometers. Keeping an eye on all objects in Earth's orbit, useful and not useful, operational or not, is known as Space Surveillance. Due to cost considerations, the space surveillance solutions beyond the Low Earth Orbit region are mainly based on optical instruments. This paper presents a solution for real-time automatic detection and ranging of space objects of altitudes ranging from below the Medium Earth Orbit up to 40,000 km, based on two low cost observation systems built using commercial cameras and marginally professional telescopes, placed 37 km apart, operating as a large baseline stereovision system. The telescopes are pointed towards any visible region of the sky, and the system is able to automatically calibrate the orientation parameters using automatic matching of reference stars from an online catalog, with a very high tolerance for the initial guess of the sky region and camera orientation. The difference between the left and right image of a synchronized stereo pair is used for automatic detection of the satellite pixels, using an original difference computation algorithm that is capable of high sensitivity and a low false positive rate. The use of stereovision provides a strong means of removing false positives, and avoids the need for prior knowledge of the orbits observed, the system being able to detect at the same time all types of objects that fall within the measurement range and are visible on the image.

Automatic characterization of sleep need dissipation dynamics using a single EEG signal.

PubMed

Garcia-Molina, Gary; Bellesi, Michele; Riedner, Brady; Pastoor, Sander; Pfundtner, Stefan; Tononi, Giulio

2015-01-01

In the two-process model of sleep regulation, slow-wave activity (SWA, i.e. the EEG power in the 0.5-4 Hz frequency band) is considered a direct indicator of sleep need. SWA builds up during non-rapid eye movement (NREM) sleep, declines before the onset of rapid-eye-movement (REM) sleep, remains low during REM and the level of increase in successive NREM episodes gets progressively lower. Sleep need dissipates with a speed that is proportional to SWA and can be characterized in terms of the initial sleep need, and the decay rate. The goal in this paper is to automatically characterize sleep need from a single EEG signal acquired at a frontal location. To achieve this, a highly specific and reasonably sensitive NREM detection algorithm is proposed that leverages the concept of a single-class Kernel-based classifier. Using automatic NREM detection, we propose a method to estimate the decay rate and the initial sleep need. This method was tested on experimental data from 8 subjects who recorded EEG during three nights at home. We found that on average the estimates of the decay rate and the initial sleep need have higher values when automatic NREM detection was used as compared to manual NREM annotation. However, the average variability of these estimates across multiple nights of the same subject was lower when the automatic NREM detection classifier was used. While this method slightly over estimates the sleep need parameters, the reduced variability across subjects makes it more effective for within subject statistical comparisons of a given sleep intervention.

Automatic left-atrial segmentation from cardiac 3D ultrasound: a dual-chamber model-based approach

NASA Astrophysics Data System (ADS)

Almeida, Nuno; Sarvari, Sebastian I.; Orderud, Fredrik; Gérard, Olivier; D'hooge, Jan; Samset, Eigil

2016-04-01

In this paper, we present an automatic solution for segmentation and quantification of the left atrium (LA) from 3D cardiac ultrasound. A model-based framework is applied, making use of (deformable) active surfaces to model the endocardial surfaces of cardiac chambers, allowing incorporation of a priori anatomical information in a simple fashion. A dual-chamber model (LA and left ventricle) is used to detect and track the atrio-ventricular (AV) plane, without any user input. Both chambers are represented by parametric surfaces and a Kalman filter is used to fit the model to the position of the endocardial walls detected in the image, providing accurate detection and tracking during the whole cardiac cycle. This framework was tested in 20 transthoracic cardiac ultrasound volumetric recordings of healthy volunteers, and evaluated using manual traces of a clinical expert as a reference. The 3D meshes obtained with the automatic method were close to the reference contours at all cardiac phases (mean distance of 0.03+/-0.6 mm). The AV plane was detected with an accuracy of -0.6+/-1.0 mm. The LA volumes assessed automatically were also in agreement with the reference (mean +/-1.96 SD): 0.4+/-5.3 ml, 2.1+/-12.6 ml, and 1.5+/-7.8 ml at end-diastolic, end-systolic and pre-atrial-contraction frames, respectively. This study shows that the proposed method can be used for automatic volumetric assessment of the LA, considerably reducing the analysis time and effort when compared to manual analysis.

Nonconscious emotional activation colors first impressions: a regulatory role for conscious awareness.

PubMed

Lapate, Regina C; Rokers, Bas; Li, Tianyi; Davidson, Richard J

2014-02-01

Emotions can color people's attitudes toward unrelated objects in the environment. Existing evidence suggests that such emotional coloring is particularly strong when emotion-triggering information escapes conscious awareness. But is emotional reactivity stronger after nonconscious emotional provocation than after conscious emotional provocation, or does conscious processing specifically change the association between emotional reactivity and evaluations of unrelated objects? In this study, we independently indexed emotional reactivity and coloring as a function of emotional-stimulus awareness to disentangle these accounts. Specifically, we recorded skin-conductance responses to spiders and fearful faces, along with subsequent preferences for novel neutral faces during visually aware and unaware states. Fearful faces increased skin-conductance responses comparably in both stimulus-aware and stimulus-unaware conditions. Yet only when visual awareness was precluded did skin-conductance responses to fearful faces predict decreased likability of neutral faces. These findings suggest a regulatory role for conscious awareness in breaking otherwise automatic associations between physiological reactivity and evaluative emotional responses.

Fluorescence ratiometric classifier for the detection of skin pathologies

NASA Astrophysics Data System (ADS)

Anand, Suresh; Cicchi, Riccardo; Cosci, Alessandro; Rossari, Susanna; Kapsokalyvas, Dimitrios; Baria, Enrico; Maio, Vincenza; Massi, Daniela; De Giorgi, Vincenzo; Pimpinelli, Nicola; Pavone, Francesco S.

2015-07-01

Detection of pre-malignant lesions in skin could help in reducing the 5 year patient mortality rates and greatly advancing the quality of life. Current gold standard for the detection of skin pathologies is a tissue biopsy and followed by a series of steps before it is examined under a light microscope by a pathologist. The disadvantage with this method is its invasiveness. Light based biomedical point spectroscopic techniques offers an adjunct technique to invasive tissue pathology. In this context, we have implemented a simple multiplexed ratiometric approach (F470/F560 and F510/F580) based on fluorescence at two excitation wavelengths 378 nm and 445 nm respectively. The emission profile at these excitation wavelengths showed a shift towards the longer wavelengths for melanoma when compared with normal and nevus. At both excitation wavelengths, we observed an increased intensity ratios for normal, followed by nevus and melanoma. This intensity ratios provide a good diagnostic capability in differentiating normal, nevus and melanocytic skin lesions. This method could be applied in vivo because of the simplicity involved in discriminating normal and pathological skin tissues.

Self-efficacy moderates message-framing effects: The case of skin-cancer detection.

PubMed

van 't Riet, Jonathan; Ruiter, Robert A C; Werrij, Marieke Q; De Vries, Hein

2010-03-01

Health-promoting messages can be framed in terms of the gains associated with healthy behaviour, or the losses associated with unhealthy behaviour. Studies show inconsistent results as to which type of framing is more effective. In this study, we examined the influence of self-efficacy to perform skin self-examination on the effects of gain- and loss-framed skin-cancer detection messages among 124 university students. For participants with high self-efficacy, a loss-framed message resulted in a higher intention to perform skin self-examination than a gain-framed message. For participants with low self-efficacy, there were no differences in intention between the gain- and loss-framed message conditions. Our results suggest that self-efficacy levels play an important role in message-framing effects. For health communication strategies promoting the active detection of skin-cancer symptoms, messages stressing losses may be more effective than messages stressing gains, but only in persons with high self-efficacy. In addition, our results suggest that health promoting messages can be framed to match recipients' self-efficacy levels.

Rapid Detection of Staphylococcus aureus and Methicillin-Resistant S. aureus in Atopic Dermatitis by Using the BD Max StaphSR Assay.

PubMed

Lee, Mi Kyung; Park, Kui Young; Jin, Taewon; Kim, Ju Hee; Seo, Seong Jun

2017-07-01

Eczematous lesions of atopic dermatitis (AD) patients are known to be a source of Staphylococcus aureus (SA) transmission and might be a reservoir for community-associated methicillin-resistant SA (MRSA). The BD Max StaphSR (BD-SR) is a fully automated, multiplex real-time PCR assay for the direct detection and differentiation of SA and MRSA from nasal swab samples. We evaluated the detection rates of SA and MRSA from skin lesions of outpatients with AD using the BD-SR assay, and determined the usefulness of the BD-SR assay. A total of 244 skin swab samples (skin lesions of 213 outpatients with AD and normal skin of 31 healthy controls) were tested directly by using the BD-SR assay. Of the 213 samples from patients with AD, 69 (32.4%) were positive for SA, 6 (8.7%) of which were positive for MRSA. Only 1 (3.2%) of 31 samples from healthy controls was positive for SA. The BD-SR assay is effective for the rapid detection of SA and MRSA from skin swab samples, which can provide important information for managing patients with AD and preventing the spread of MRSA. © The Korean Society for Laboratory Medicine.

Real-time Flare Detection in Ground-Based Hα Imaging at Kanzelhöhe Observatory

NASA Astrophysics Data System (ADS)

Pötzi, W.; Veronig, A. M.; Riegler, G.; Amerstorfer, U.; Pock, T.; Temmer, M.; Polanec, W.; Baumgartner, D. J.

2015-03-01

Kanzelhöhe Observatory (KSO) regularly performs high-cadence full-disk imaging of the solar chromosphere in the Hα and Ca ii K spectral lines as well as in the solar photosphere in white light. In the frame of ESA's (European Space Agency) Space Situational Awareness (SSA) program, a new system for real-time Hα data provision and automatic flare detection was developed at KSO. The data and events detected are published in near real-time at ESA's SSA Space Weather portal (http://swe.ssa.esa.int/web/guest/kso-federated). In this article, we describe the Hα instrument, the image-recognition algorithms we developed, and the implementation into the KSO Hα observing system. We also present the evaluation results of the real-time data provision and flare detection for a period of five months. The Hα data provision worked in 99.96 % of the images, with a mean time lag of four seconds between image recording and online provision. Within the given criteria for the automatic image-recognition system (at least three Hα images are needed for a positive detection), all flares with an area ≥ 50 micro-hemispheres that were located within 60° of the solar center and occurred during the KSO observing times were detected, a number of 87 events in total. The automatically determined flare importance and brightness classes were correct in ˜ 85 %. The mean flare positions in heliographic longitude and latitude were correct to within ˜ 1°. The median of the absolute differences for the flare start and peak times from the automatic detections in comparison with the official NOAA (and KSO) visual flare reports were 3 min (1 min).

Evaluation of the Potential Risk of Hepatitis B Virus Transmission in Skin Allografting.

PubMed

Wang, D; Xie, W; Chen, T; Dong, C; Zhao, C; Tan, H; Tian, H; Xie, Q

2015-01-01

Skin transplantation is associated with potential risk of infectious disease transmission; however, the exclusion of donors owing to hepatitis B virus (HBV) infection will worsen the shortage of allograft skin supply. We report a paired study to evaluate the potential risk of HBV transmission in skin allografting. The presence of HBV DNA in the serum and skin from 37 burn patients with chronic HBV infection (CHB) was monitored by a HBV polymerase chain reaction (PCR) and the positive rates were compared by Fisher's exact probability test. There was a high consistency in the HBV serology profile between HBV DNA PCR (83.78%) and the clinical HBV test. Only 2 patients who were positive for hepatitis B surface antigen, hepatitis B e antigen, and hepatitis B core antibody had detectable HBV DNA in the skin tissue; however, no hepatitis B surface antigen was detected as examined by immunohistochemistry staining. There was a significant difference between the positive rates of HBV DNA in the serum and skin (χc(2) = 27.03; P < .001). The potential risk for HBV transmission by skin allografting is very low. Given that China has a large population of patients with HBV, the acceptance of skin from donors with CHB to the skin bank would increase the number of tissue donations to meet the urgent medical need for skin transplantation. Copyright © 2015 Elsevier Inc. All rights reserved.

Skin microrelief as a diagnostic tool (Conference Presentation)

NASA Astrophysics Data System (ADS)

Tchvialeva, Lioudmila; Phillips, Jamie; Zeng, Haishan; McLean, David; Lui, Harvey; Lee, Tim K.

2017-02-01

Skin surface roughness is an important property for differentiating skin diseases. Recently, roughness has also been identified as a potential diagnostic indicator in the early detection of skin cancer. Objective quantification is usually carried out by creating silicone replicas of the skin and then measuring the replicas. We have developed an alternative in-vivo technique to measure skin roughness based on laser speckle. Laser speckle is the interference pattern produced when coherent light is used to illuminate a rough surface and the backscattered light is imaged. Acquiring speckle contrast measurements from skin phantoms with controllable roughness, we created a calibration curve by linearly interpolating between measured points. This calibration curve accounts for internal scattering and is designed to evaluate skin microrelief whose root-mean-square roughness is in the range of 10-60 micrometers. To validate the effectiveness of our technique, we conducted a study to measure 243 skin lesions including actinic keratosis (8), basal cell carcinoma (24), malignant melanoma (31), nevus (73), squamous cell carcinoma (19), and seborrheic keratosis (79). The average roughness values ranged from 26 to 57 micrometers. Malignant melanoma was ranked as the smoothest and squamous cell carcinoma as the roughest lesion. An ANOVA test confirmed that malignant melanoma has significantly smaller roughness than other lesion types. Our results suggest that skin microrelief can be used to detect malignant melanoma from other skin conditions.

Rapid, Potentially Automatable, Method Extract Biomarkers for HPLC/ESI/MS/MS to Detect and Identify BW Agents

DTIC Science & Technology

1997-11-01

status can sometimes be reflected in the infectious potential or drug resistance of those pathogens. For example, in Mycobacterium tuberculosis ... Mycobacterium tuberculosis , its antibiotic resistance and prediction of pathogenicity amongst Mycobacterium spp. based on signature lipid biomarkers ...TITLE AND SUBTITLE Rapid, Potentially Automatable, Method Extract Biomarkers for HPLC/ESI/MS/MS to Detect and Identify BW Agents 5a. CONTRACT NUMBER 5b

Use of an automatic earth resistivity system for detection of abandoned mine workings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peters, W.R.; Burdick, R.

1982-04-01

Under the sponsorship of the US Bureau of Mines, a surface-operated automatic high resolution earth resistivity system and associated computer data processing techniques have been designed and constructed for use as a potential means of detecting abandoned coal mine workings. The hardware and software aspects of the new system are described together with applications of the method to the survey and mapping of abandoned mine workings.

Assessment of Severe Apnoea through Voice Analysis, Automatic Speech, and Speaker Recognition Techniques

NASA Astrophysics Data System (ADS)

Fernández Pozo, Rubén; Blanco Murillo, Jose Luis; Hernández Gómez, Luis; López Gonzalo, Eduardo; Alcázar Ramírez, José; Toledano, Doroteo T.

2009-12-01

This study is part of an ongoing collaborative effort between the medical and the signal processing communities to promote research on applying standard Automatic Speech Recognition (ASR) techniques for the automatic diagnosis of patients with severe obstructive sleep apnoea (OSA). Early detection of severe apnoea cases is important so that patients can receive early treatment. Effective ASR-based detection could dramatically cut medical testing time. Working with a carefully designed speech database of healthy and apnoea subjects, we describe an acoustic search for distinctive apnoea voice characteristics. We also study abnormal nasalization in OSA patients by modelling vowels in nasal and nonnasal phonetic contexts using Gaussian Mixture Model (GMM) pattern recognition on speech spectra. Finally, we present experimental findings regarding the discriminative power of GMMs applied to severe apnoea detection. We have achieved an 81% correct classification rate, which is very promising and underpins the interest in this line of inquiry.

Early Detection of Severe Apnoea through Voice Analysis and Automatic Speaker Recognition Techniques

NASA Astrophysics Data System (ADS)

Fernández, Ruben; Blanco, Jose Luis; Díaz, David; Hernández, Luis A.; López, Eduardo; Alcázar, José

This study is part of an on-going collaborative effort between the medical and the signal processing communities to promote research on applying voice analysis and Automatic Speaker Recognition techniques (ASR) for the automatic diagnosis of patients with severe obstructive sleep apnoea (OSA). Early detection of severe apnoea cases is important so that patients can receive early treatment. Effective ASR-based diagnosis could dramatically cut medical testing time. Working with a carefully designed speech database of healthy and apnoea subjects, we present and discuss the possibilities of using generative Gaussian Mixture Models (GMMs), generally used in ASR systems, to model distinctive apnoea voice characteristics (i.e. abnormal nasalization). Finally, we present experimental findings regarding the discriminative power of speaker recognition techniques applied to severe apnoea detection. We have achieved an 81.25 % correct classification rate, which is very promising and underpins the interest in this line of inquiry.

Development of methods for skin barrier peeling tests.

PubMed

Omura, Yuko; Kazuharu, Seki; Kenji, Oishi

2006-01-01

We sought to develop a more effective method to evaluate the adhesive properties of skin barriers. The experimental design used was based on 3 principles: partial control, randomization, and repetition. Using these principles, the 180-degree peeling tests were conducted as specified in a standardized methodology (JIS Z0297) to the extent possible. However, the use of a stainless steel plate as a proxy for skin barrier application may result in the stretching and breaking of the skin barrier, making it impossible to obtain suitable measurements. Tests were conducted in constant temperature/ humidity chambers using a Tensilon Automatic Elongation Tester, where a sample was fixed on the side of a sample immobilization device, a sturdy metal (aluminum) box from which the air in the box was drawn off with a vacuum pump. A fluorocarbon polymer film was applied to the adhesive surface of a sample skin barrier. The film was peeled off in the volte-face (180-degree) direction in order to measure adhesive strengths. The films exhibit such properties as (a) ease of removal from the adhesive surface, (b) no resistance to a 180-degree fold back due to the thinness and flexibility of the material, and (c) tolerance of elongation. The adhesive properties of skin barriers were measured by peeling the fluorocarbon polymers in a 180-degree direction. Twelve specimen skin barrier products were selected for measurement, providing results with satisfactory reproducibility. Results based on the conventional stainless steel plate-based testing method acted as a control. The newly developed testing method enables chronological measurement results for skin barriers applied to fluorocarbon polymer films after 24 hours, 48 hours, and longer period.

Diffuse reflectance imaging for non-melanoma skin cancer detection using laser feedback interferometry

NASA Astrophysics Data System (ADS)

Mowla, Alireza; Taimre, Thomas; Lim, Yah L.; Bertling, Karl; Wilson, Stephen J.; Prow, Tarl W.; Soyer, H. P.; Rakić, Aleksandar D.

2016-04-01

We propose a compact, self-aligned, low-cost, and versatile infrared diffuse-reflectance laser imaging system using a laser feedback interferometry technique with possible applications in in vivo biological tissue imaging and skin cancer detection. We examine the proposed technique experimentally using a three-layer agar skin phantom. A cylindrical region with a scattering rate lower than that of the surrounding normal tissue was used as a model for a non-melanoma skin tumour. The same structure was implemented in a Monte Carlo computational model. The experimental results agree well with the Monte Carlo simulations validating the theoretical basis of the technique. Results prove the applicability of the proposed technique for biological tissue imaging, with the capability of depth sectioning and a penetration depth of well over 1.2 mm into the skin phantom.

General Automatic Components of Motion Sickness

NASA Technical Reports Server (NTRS)

Suter, S.; Toscano, W. B.; Kamiya, J.; Naifeh, K.

1985-01-01

A body of investigations performed in support of experiments aboard the space shuttle, and designed to counteract the symptoms of Space Adaptation Syndrome, which resemble those of motion sickness on Earth is reviewed. For these supporting studies, the automatic manifestations of earth-based motion sickness was examined. Heart rate, respiration rate, finger pulse volume and basal skin resistance were measured on 127 men and women before, during and after exposure to nauseogenic rotating chair tests. Significant changes in all autonomic responses were observed across the tests. Significant differences in autonomic responses among groups divided according to motion sickness susceptibility were also observed. Results suggest that the examination of autonomic responses as an objective indicator of motion sickness malaise is warranted and may contribute to the overall understanding of the syndrome on Earth and in Space.

Accurate computer-aided quantification of left ventricular parameters: experience in 1555 cardiac magnetic resonance studies from the Framingham Heart Study.

PubMed

Hautvast, Gilion L T F; Salton, Carol J; Chuang, Michael L; Breeuwer, Marcel; O'Donnell, Christopher J; Manning, Warren J

2012-05-01

Quantitative analysis of short-axis functional cardiac magnetic resonance images can be performed using automatic contour detection methods. The resulting myocardial contours must be reviewed and possibly corrected, which can be time-consuming, particularly when performed across all cardiac phases. We quantified the impact of manual contour corrections on both analysis time and quantitative measurements obtained from left ventricular short-axis cine images acquired from 1555 participants of the Framingham Heart Study Offspring cohort using computer-aided contour detection methods. The total analysis time for a single case was 7.6 ± 1.7 min for an average of 221 ± 36 myocardial contours per participant. This included 4.8 ± 1.6 min for manual contour correction of 2% of all automatically detected endocardial contours and 8% of all automatically detected epicardial contours. However, the impact of these corrections on global left ventricular parameters was limited, introducing differences of 0.4 ± 4.1 mL for end-diastolic volume, -0.3 ± 2.9 mL for end-systolic volume, 0.7 ± 3.1 mL for stroke volume, and 0.3 ± 1.8% for ejection fraction. We conclude that left ventricular functional parameters can be obtained under 5 min from short-axis functional cardiac magnetic resonance images using automatic contour detection methods. Manual correction more than doubles analysis time, with minimal impact on left ventricular volumes and ejection fraction. Copyright © 2011 Wiley Periodicals, Inc.

Discrimination between basal cell carcinoma and hair follicles in skin tissue sections by Raman micro-spectroscopy

NASA Astrophysics Data System (ADS)

Larraona-Puy, M.; Ghita, A.; Zoladek, A.; Perkins, W.; Varma, S.; Leach, I. H.; Koloydenko, A. A.; Williams, H.; Notingher, I.

2011-05-01

Skin cancer is the most common human malignancy and basal cell carcinoma (BCC) represents approximately 80% of the non-melanoma cases. Current methods of treatment require histopathological evaluation of the tissues by qualified personnel. However, this method is subjective and in some cases BCC can be confused with other structures in healthy skin, including hair follicles. In this preliminary study, we investigated the potential of Raman micro-spectroscopy (RMS) to discriminate between hair follicles and BCC in skin tissue sections excised during Mohs micrographic surgery (MMS). Imaging and diagnosis of skin sections was automatically generated using ' a priori'-built spectral model based on LDA. This model had 90 ± 9% sensitivity and 85 ± 9% specificity for discrimination of BCC from dermis and epidermis. The model used selected Raman bands corresponding to the largest spectral differences between the Raman spectra of BCC and the normal skin regions, associated mainly with nucleic acids and collagen type I. Raman spectra corresponding to the epidermis regions of the hair follicles were found to be closer to those of healthy epidermis rather than BCC. Comparison between Raman spectral images and the gold standard haematoxylin and eosin (H&E) histopathology diagnosis showed good agreement. Some hair follicle regions were misclassified as BCC; regions corresponded mainly to the outermost layer of hair follicle (basal cells) which are expected to have higher nucleic acid concentration. This preliminary study shows the ability of RMS to distinguish between BCC and other tissue structures associated to healthy skin which can be confused with BCC due to their similar morphology.

An analysis of the topography, severity, potential sources of reinforcement, and treatments utilized for skin picking in Prader-Willi syndrome.

PubMed

Hustyi, Kristin M; Hammond, Jennifer L; Rezvani, Ava B; Hall, Scott S

2013-09-01

We examined the topography, severity, potential sources of reinforcement, and treatments utilized for skin-picking behavior shown by individuals with Prader-Willi syndrome (PWS). The parents of 55 individuals with PWS, aged 6-25 years, were interviewed about their child's skin-picking behavior using the Self-Injury Trauma Scale (SIT; Iwata, Pace, Kissel, Nau, & Farber, 1990) and the Functional Analysis Screening Tool (FAST; Iwata, DeLeon, & Roscoe, 2013). Results showed that skin picking in PWS occurred on the extremities (i.e., arms, legs, hands, and feet) for 75% of cases and resulted in bodily injury for 83.7% cases. Skin picking posed a high risk to the individual concerned in 41.8% of cases. Automatic sensory stimulation was identified as a potential source of reinforcement in the majority of cases (52.7%) followed by access to social attention or preferred items (36.4%). Treatments utilized by parents were primarily behavioral strategies (56.3%) followed by basic first aid (54.5%). There were no differences in the topography, severity or potential source of reinforcement between those with the deletion (DEL) subtype and those with the uniparental disomy (UPD) subtype. Taken together, these data indicate that skin picking shown by individuals with PWS is a particularly severe and intractable behavioral issue that may be maintained by (as yet unknown) sensory consequences. Further studies to identify the determinants of skin picking in PWS are therefore needed. The implications for interventions are discussed. Copyright © 2013 Elsevier Ltd. All rights reserved.

Tier-scalable reconnaissance: the future in autonomous C4ISR systems has arrived: progress towards an outdoor testbed

NASA Astrophysics Data System (ADS)

Fink, Wolfgang; Brooks, Alexander J.-W.; Tarbell, Mark A.; Dohm, James M.

2017-05-01

Autonomous reconnaissance missions are called for in extreme environments, as well as in potentially hazardous (e.g., the theatre, disaster-stricken areas, etc.) or inaccessible operational areas (e.g., planetary surfaces, space). Such future missions will require increasing degrees of operational autonomy, especially when following up on transient events. Operational autonomy encompasses: (1) Automatic characterization of operational areas from different vantages (i.e., spaceborne, airborne, surface, subsurface); (2) automatic sensor deployment and data gathering; (3) automatic feature extraction including anomaly detection and region-of-interest identification; (4) automatic target prediction and prioritization; (5) and subsequent automatic (re-)deployment and navigation of robotic agents. This paper reports on progress towards several aspects of autonomous C4ISR systems, including: Caltech-patented and NASA award-winning multi-tiered mission paradigm, robotic platform development (air, ground, water-based), robotic behavior motifs as the building blocks for autonomous tele-commanding, and autonomous decision making based on a Caltech-patented framework comprising sensor-data-fusion (feature-vectors), anomaly detection (clustering and principal component analysis), and target prioritization (hypothetical probing).

Photogrammetric 3d Acquisition and Analysis of Medicamentous Induced Pilomotor Reflex ("goose Bumps")

NASA Astrophysics Data System (ADS)

Schneider, D.; Hecht, A.

2016-06-01

In a current study at the University Hospital Dresden, Department of Neurology, the autonomous function of nerve fibres of the human skin is investigated. For this purpose, a specific medicament is applied on a small area of the skin of a test person which results in a local reaction (goose bumps). Based on the extent of the area, where the stimulation of the nerve fibres is visible, it can be concluded how the nerve function of the skin works. The aim of the investigation described in the paper is to generate 3D data of these goose bumps. Therefore, the paper analyses and compares different photogrammetric surface measurement techniques in regard to their suitability for the 3D acquisition of silicone imprints of the human skin. Furthermore, an appropriate processing procedure for analysing the recorded point cloud data is developed and presented. It was experimentally proven that by using (low-cost) photogrammetric techniques medicamentous induced goose bumps can be acquired in three dimensions and can be analysed almost fully automatically from the perspective of medical research questions. The relative accuracy was determined with 1% (RMSE) of the area resp. the volume of an individual goose bump.

Community Perceptions of Specific Skin Features of Possible Melanoma

ERIC Educational Resources Information Center

Baade, Peter D.; Balanda, Kevin P.; Stanton, Warren R.; Lowe, John B.; Del Mar, Chris B.

2004-01-01

Background: Melanoma can be curable if detected early. One component of detecting melanoma is an awareness of the important features of the disease. It is currently not clear which features the community view as indicative of melanoma. Objective: To investigate which features of the skin members of an urban community believe may indicate skin…

Clinical Anaemia Detection in Children of Varied Skin Complexion: A Community-based Study in Southeast, Nigeria.

PubMed

Ughasoro, Maduka Donatus; Madu, Anazoeze Jude; Kela-Eke, Iheoma Clara

2017-02-01

Clinicians rely on clinical detection of pallor to diagnose anaemia. This makes it important to evaluate the effect of different skin complexions on the accuracy of the pallor in diagnosing anaemia in children. Clinicians conducted blind-independent physical examination, and their reports were compared with HemoCue 301 haemoglobin estimated with. The sensitivity and specificity were calculated. A total of 573 children were reviewed by 27 healthcare workers. The prevalence of anaemia was high. The highest prevalence was among children between the age of 4 and 12 months (urban 63.4% and rural 69.2%). Anaemia was detected better among dark-skinned children. Conjunctivae and palm pallor had the highest sensitivity (78.6% and 69.2%, respectively). Clinical pallor is a good screening assessment for anaemia but not diagnostic. Its sensitivity and specificity vary among different sites and skin complexions. Thus combining findings at any of the sites can improve detection of anaemia in children. © The Author [2016]. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Hyperspectral Image Analysis for Skin Tumor Detection

NASA Astrophysics Data System (ADS)

Kong, Seong G.; Park, Lae-Jeong

This chapter presents hyperspectral imaging of fluorescence for nonin-vasive detection of tumorous tissue on mouse skin. Hyperspectral imaging sensors collect two-dimensional (2D) image data of an object in a number of narrow, adjacent spectral bands. This high-resolution measurement of spectral information reveals a continuous emission spectrum for each image pixel useful for skin tumor detection. The hyperspectral image data used in this study are fluorescence intensities of a mouse sample consisting of 21 spectral bands in the visible spectrum of wavelengths ranging from 440 to 640 nm. Fluorescence signals are measured using a laser excitation source with the center wavelength of 337 nm. An acousto-optic tunable filter is used to capture individual spectral band images at a 10-nm resolution. All spectral band images are spatially registered with the reference band image at 490 nm to obtain exact pixel correspondences by compensating the offsets caused during the image capture procedure. The support vector machines with polynomial kernel functions provide decision boundaries with a maximum separation margin to classify malignant tumor and normal tissue from the observed fluorescence spectral signatures for skin tumor detection.

[Study on Intelligent Automatic Tracking Radiation Protection Curtain].

PubMed

Zhao, Longyang; Han, Jindong; Ou, Minjian; Chen, Jinlong

2015-09-01

In order to overcome the shortcomings of traditional X-ray inspection taking passive protection mode, this paper combines the automatic control technology, puts forward a kind of active protection X-ray equipment. The device of automatic detection of patients receiving X-ray irradiation part, intelligent adjustment in patients and shooting device between automatic tracking radiation protection device height. The device has the advantages of automatic adjustment, anti-radiation device, reduce the height of non-irradiated area X-ray radiation and improve the work efficiency. Testing by the professional organization, the device can decrease more than 90% of X-ray dose for patients with non-irradiated area.

Automatic Microaneurysms Detection Based on Multifeature Fusion Dictionary Learning

PubMed Central

Wang, Zhenzhu; Du, Wenyou

2017-01-01

Recently, microaneurysm (MA) detection has attracted a lot of attention in the medical image processing community. Since MAs can be seen as the earliest lesions in diabetic retinopathy, their detection plays a critical role in diabetic retinopathy diagnosis. In this paper, we propose a novel MA detection approach named multifeature fusion dictionary learning (MFFDL). The proposed method consists of four steps: preprocessing, candidate extraction, multifeature dictionary learning, and classification. The novelty of our proposed approach lies in incorporating the semantic relationships among multifeatures and dictionary learning into a unified framework for automatic detection of MAs. We evaluate the proposed algorithm by comparing it with the state-of-the-art approaches and the experimental results validate the effectiveness of our algorithm. PMID:28421125

Automatic Microaneurysms Detection Based on Multifeature Fusion Dictionary Learning.

PubMed

Zhou, Wei; Wu, Chengdong; Chen, Dali; Wang, Zhenzhu; Yi, Yugen; Du, Wenyou

2017-01-01

Recently, microaneurysm (MA) detection has attracted a lot of attention in the medical image processing community. Since MAs can be seen as the earliest lesions in diabetic retinopathy, their detection plays a critical role in diabetic retinopathy diagnosis. In this paper, we propose a novel MA detection approach named multifeature fusion dictionary learning (MFFDL). The proposed method consists of four steps: preprocessing, candidate extraction, multifeature dictionary learning, and classification. The novelty of our proposed approach lies in incorporating the semantic relationships among multifeatures and dictionary learning into a unified framework for automatic detection of MAs. We evaluate the proposed algorithm by comparing it with the state-of-the-art approaches and the experimental results validate the effectiveness of our algorithm.

Protecting against cyber threats in networked information systems

NASA Astrophysics Data System (ADS)

Ertoz, Levent; Lazarevic, Aleksandar; Eilertson, Eric; Tan, Pang-Ning; Dokas, Paul; Kumar, Vipin; Srivastava, Jaideep

2003-07-01

This paper provides an overview of our efforts in detecting cyber attacks in networked information systems. Traditional signature based techniques for detecting cyber attacks can only detect previously known intrusions and are useless against novel attacks and emerging threats. Our current research at the University of Minnesota is focused on developing data mining techniques to automatically detect attacks against computer networks and systems. This research is being conducted as a part of MINDS (Minnesota Intrusion Detection System) project at the University of Minnesota. Experimental results on live network traffic at the University of Minnesota show that the new techniques show great promise in detecting novel intrusions. In particular, during the past few months our techniques have been successful in automatically identifying several novel intrusions that could not be detected using state-of-the-art tools such as SNORT.

Home-use cancer detecting band aid

NASA Astrophysics Data System (ADS)

Zalevsky, Zeev; Rudnitsky, Arkady; Sheinman, Victor; Tzoy, Andrey; Toktosunov, Aitmamat; Adashov, Arkady

2016-03-01

In this paper we present a novel concept in which special band aid is developed for early detection of cancer. The band aid contains an array of micro needles with small detection array connected to each needle which inspects the color of the surface of the skin versus time after being pinched with the needles. We were able to show in pre-clinical trials that the color varies differently if the skin is close to tumor tissue.

Skin secretion peptides: the molecular facet of the deimatic behavior of the four-eyed frog, Physalaemus nattereri (Anura, Leptodactylidae).

PubMed

Barbosa, Eder Alves; Iembo, Tatiane; Martins, Graciella Ribeiro; Silva, Luciano Paulino; Prates, Maura Vianna; Andrade, Alan Carvalho; Bloch, Carlos

2015-11-15

Amphibians can produce a large amount of bioactive peptides over the skin. In order to map the precise tissue localization of these compounds and evaluate their functions, mass spectrometry imaging (MSI) and gene expression studies were used to investigate a possible correlation between molecules involved in the antimicrobial defense mechanisms and anti-predatory behavior by Physalaemus nattereri. Total skin secretion of P. nattereri was analyzed by classical Protein Chemistry and proteomic techniques. Intact inguinal macroglands were dissected from the rest of the skin and both tissues were analyzed by MSI and real-time polymerase chain reaction (RT-PCR) experiments. Peptides were primarily identified by de novo sequencing, automatic Edman degradation and cDNA data. Fifteen bradykinin (BK)-related peptides and two antimicrobial peptides were sequenced and mapped by MSI on the inguinal macrogland and the rest of P. nattereri skin. RT-PCR results revealed that BK-related peptide levels of expression were about 30,000 times higher on the inguinal macroglands than on the any other region of the skin, whilst antimicrobial peptide ions appear to be evenly distributed in both investigated regions. The presence of antimicrobial peptides in all investigated tissue regions is in accordance with the defensive role against microorganisms thoroughly demonstrated in the literature, whereas BK-related molecules are largely found on the inguinal macroglands suggesting an intriguing link between their noxious activities against potential predators of P. nattereri and the frog's deimatic behavior. Copyright © 2015 John Wiley & Sons, Ltd.

Self-Powered Implantable Skin-Like Glucometer for Real-Time Detection of Blood Glucose Level In Vivo

NASA Astrophysics Data System (ADS)

Zhang, Wanglinhan; Zhang, Linlin; Gao, Huiling; Yang, Wenyan; Wang, Shuai; Xing, Lili; Xue, Xinyu

2018-06-01

Implantable bioelectronics for analyzing physiological biomarkers has recently been recognized as a promising technique in medical treatment or diagnostics. In this study, we developed a self-powered implantable skin-like glucometer for real-time detection of blood glucose level in vivo. Based on the piezo-enzymatic-reaction coupling effect of GOx@ZnO nanowire, the device under an applied deformation can actively output piezoelectric signal containing the glucose-detecting information. No external electricity power source or battery is needed for this device, and the outputting piezoelectric voltage acts as both the biosensing signal and electricity power. A practical application of the skin-like glucometer implanted in mouse body for detecting blood glucose level has been simply demonstrated. These results provide a new technique path for diabetes prophylaxis and treatment.

Advanced Spectroscopy Technique for Biomedicine

NASA Astrophysics Data System (ADS)

Zhao, Jianhua; Zeng, Haishan

This chapter presents an overview of the applications of optical spectroscopy in biomedicine. We focus on the optical design aspects of advanced biomedical spectroscopy systems, Raman spectroscopy system in particular. Detailed components and system integration are provided. As examples, two real-time in vivo Raman spectroscopy systems, one for skin cancer detection and the other for endoscopic lung cancer detection, and an in vivo confocal Raman spectroscopy system for skin assessment are presented. The applications of Raman spectroscopy in cancer diagnosis of the skin, lung, colon, oral cavity, gastrointestinal tract, breast, and cervix are summarized.

Comparison Of Semi-Automatic And Automatic Slick Detection Algorithms For Jiyeh Power Station Oil Spill, Lebanon

NASA Astrophysics Data System (ADS)

Osmanoglu, B.; Ozkan, C.; Sunar, F.

2013-10-01

After air strikes on July 14 and 15, 2006 the Jiyeh Power Station started leaking oil into the eastern Mediterranean Sea. The power station is located about 30 km south of Beirut and the slick covered about 170 km of coastline threatening the neighboring countries Turkey and Cyprus. Due to the ongoing conflict between Israel and Lebanon, cleaning efforts could not start immediately resulting in 12 000 to 15 000 tons of fuel oil leaking into the sea. In this paper we compare results from automatic and semi-automatic slick detection algorithms. The automatic detection method combines the probabilities calculated for each pixel from each image to obtain a joint probability, minimizing the adverse effects of atmosphere on oil spill detection. The method can readily utilize X-, C- and L-band data where available. Furthermore wind and wave speed observations can be used for a more accurate analysis. For this study, we utilize Envisat ASAR ScanSAR data. A probability map is generated based on the radar backscatter, effect of wind and dampening value. The semi-automatic algorithm is based on supervised classification. As a classifier, Artificial Neural Network Multilayer Perceptron (ANN MLP) classifier is used since it is more flexible and efficient than conventional maximum likelihood classifier for multisource and multi-temporal data. The learning algorithm for ANN MLP is chosen as the Levenberg-Marquardt (LM). Training and test data for supervised classification are composed from the textural information created from SAR images. This approach is semiautomatic because tuning the parameters of classifier and composing training data need a human interaction. We point out the similarities and differences between the two methods and their results as well as underlining their advantages and disadvantages. Due to the lack of ground truth data, we compare obtained results to each other, as well as other published oil slick area assessments.

Automatic detection of apical roots in oral radiographs

NASA Astrophysics Data System (ADS)

Wu, Yi; Xie, Fangfang; Yang, Jie; Cheng, Erkang; Megalooikonomou, Vasileios; Ling, Haibin

2012-03-01

The apical root regions play an important role in analysis and diagnosis of many oral diseases. Automatic detection of such regions is consequently the first step toward computer-aided diagnosis of these diseases. In this paper we propose an automatic method for periapical root region detection by using the state-of-theart machine learning approaches. Specifically, we have adapted the AdaBoost classifier for apical root detection. One challenge in the task is the lack of training cases especially for diseased ones. To handle this problem, we boost the training set by including more root regions that are close to the annotated ones and decompose the original images to randomly generate negative samples. Based on these training samples, the Adaboost algorithm in combination with Haar wavelets is utilized in this task to train an apical root detector. The learned detector usually generates a large amount of true and false positives. In order to reduce the number of false positives, a confidence score for each candidate detection result is calculated for further purification. We first merge the detected regions by combining tightly overlapped detected candidate regions and then we use the confidence scores from the Adaboost detector to eliminate the false positives. The proposed method is evaluated on a dataset containing 39 annotated digitized oral X-Ray images from 21 patients. The experimental results show that our approach can achieve promising detection accuracy.

Detecting brain tumor in pathological slides using hyperspectral imaging

PubMed Central

Ortega, Samuel; Fabelo, Himar; Camacho, Rafael; de la Luz Plaza, María; Callicó, Gustavo M.; Sarmiento, Roberto

2018-01-01

Hyperspectral imaging (HSI) is an emerging technology for medical diagnosis. This research work presents a proof-of-concept on the use of HSI data to automatically detect human brain tumor tissue in pathological slides. The samples, consisting of hyperspectral cubes collected from 400 nm to 1000 nm, were acquired from ten different patients diagnosed with high-grade glioma. Based on the diagnosis provided by pathologists, a spectral library of normal and tumor tissues was created and processed using three different supervised classification algorithms. Results prove that HSI is a suitable technique to automatically detect high-grade tumors from pathological slides. PMID:29552415

Detecting brain tumor in pathological slides using hyperspectral imaging.

PubMed

Ortega, Samuel; Fabelo, Himar; Camacho, Rafael; de la Luz Plaza, María; Callicó, Gustavo M; Sarmiento, Roberto

2018-02-01

Hyperspectral imaging (HSI) is an emerging technology for medical diagnosis. This research work presents a proof-of-concept on the use of HSI data to automatically detect human brain tumor tissue in pathological slides. The samples, consisting of hyperspectral cubes collected from 400 nm to 1000 nm, were acquired from ten different patients diagnosed with high-grade glioma. Based on the diagnosis provided by pathologists, a spectral library of normal and tumor tissues was created and processed using three different supervised classification algorithms. Results prove that HSI is a suitable technique to automatically detect high-grade tumors from pathological slides.

Raman spectroscopy reveals biophysical markers in skin cancer surgical margins

NASA Astrophysics Data System (ADS)

Feng, Xu; Moy, Austin J.; Nguyen, Hieu T. M.; Zhang, Yao; Fox, Matthew C.; Sebastian, Katherine R.; Reichenberg, Jason S.; Markey, Mia K.; Tunnell, James W.

2018-02-01

The recurrence rate of nonmelanoma skin cancer is highly related to the residual tumor after surgery. Although tissueconserving surgery, such as Mohs surgery, is a standard method for the treatment of nonmelanoma skin cancer, they are limited by lengthy and costly frozen-section histopathology. Raman spectroscopy (RS) is proving to be an objective, sensitive, and non-destructive tool for detecting skin cancer. Previous studies demonstrated the high sensitivity of RS in detecting tumor margins of basal cell carcinoma (BCC). However, those studies rely on statistical classification models and do not elucidate the skin biophysical composition. As a result, we aim to discover the biophysical differences between BCC and primary normal skin structures (including epidermis, dermis, hair follicle, sebaceous gland and fat). We obtained freshly resected ex vivo skin samples from fresh resection specimens from 14 patients undergoing Mohs surgery. Raman images were acquired from regions containing one or more structures using a custom built 830nm confocal Raman microscope. The spectra were grouped using K-means clustering analysis and annotated as either BCC or each of the five normal structures by comparing with the histopathology image of the serial section. The spectral data were then fit by a previously established biophysical model with eight primary skin constituents. Our results show that BCC has significant differences in the fit coefficients of nucleus, collagen, triolein, keratin and elastin compared with normal structures. Our study reveals RS has the potential to detect biophysical changes in resection margins, and supports the development of diagnostic algorithms for future intraoperative implementation of RS during Mohs surgery.

Thermographic techniques and adapted algorithms for automatic detection of foreign bodies in food

NASA Astrophysics Data System (ADS)

Meinlschmidt, Peter; Maergner, Volker

2003-04-01

At the moment foreign substances in food are detected mainly by using mechanical and optical methods as well as ultrasonic technique and than they are removed from the further process. These techniques detect a large portion of the foreign substances due to their different mass (mechanical sieving), their different colour (optical method) and their different surface density (ultrasonic detection). Despite the numerous different methods a considerable portion of the foreign substances remain undetected. In order to recognise materials still undetected, a complementary detection method would be desirable removing the foreign substances not registered by the a.m. methods from the production process. In a project with 13 partner from the food industry, the Fraunhofer - Institut für Holzforschung (WKI) and the Technische Unsiversität are trying to adapt thermography for the detection of foreign bodies in the food industry. After the initial tests turned out to be very promising for the differentiation of food stuffs and foreign substances, more and detailed investigation were carried out to develop suitable algorithms for automatic detection of foreign bodies. In order to achieve -besides the mere visual detection of foreign substances- also an automatic detection under production conditions, numerous experiences in image processing and pattern recognition are exploited. Results for the detection of foreign bodies will be presented at the conference showing the different advantages and disadvantages of using grey - level, statistical and morphological image processing techniques.

Automatic Fault Recognition of Photovoltaic Modules Based on Statistical Analysis of Uav Thermography

NASA Astrophysics Data System (ADS)

Kim, D.; Youn, J.; Kim, C.

2017-08-01

As a malfunctioning PV (Photovoltaic) cell has a higher temperature than adjacent normal cells, we can detect it easily with a thermal infrared sensor. However, it will be a time-consuming way to inspect large-scale PV power plants by a hand-held thermal infrared sensor. This paper presents an algorithm for automatically detecting defective PV panels using images captured with a thermal imaging camera from an UAV (unmanned aerial vehicle). The proposed algorithm uses statistical analysis of thermal intensity (surface temperature) characteristics of each PV module to verify the mean intensity and standard deviation of each panel as parameters for fault diagnosis. One of the characteristics of thermal infrared imaging is that the larger the distance between sensor and target, the lower the measured temperature of the object. Consequently, a global detection rule using the mean intensity of all panels in the fault detection algorithm is not applicable. Therefore, a local detection rule based on the mean intensity and standard deviation range was developed to detect defective PV modules from individual array automatically. The performance of the proposed algorithm was tested on three sample images; this verified a detection accuracy of defective panels of 97 % or higher. In addition, as the proposed algorithm can adjust the range of threshold values for judging malfunction at the array level, the local detection rule is considered better suited for highly sensitive fault detection compared to a global detection rule.

Waste grape skins: evaluation of safety aspects for the production of functional powders and extracts for the food sector.

PubMed

Moncalvo, Alessandro; Marinoni, Laura; Dordoni, Roberta; Duserm Garrido, Guillermo; Lavelli, Vera; Spigno, Giorgia

2016-07-01

Skin powders and aqueous alcohol extracts were obtained from waste marcs from different grape varieties (Barbera, Nebbiolo, Pinot Noir, Chardonnay, Moscato and Müller-Thurgau). Both skins and extracts were analysed for the content of chemical contaminants: ochratoxin A (OTA), biogenic amines (BIAs), pesticides and metals. OTA was detected in low concentrations in Barbera, Moscato and Nebbiolo skins, but only in Barbera and Moscato extracts. Cadaverine, putrescine, ethanolamine and ethylamine were found in extracts at very low levels, while potential allergenic amines, tyramine and histamine, were never detected. Different pesticides were present in both skins and extracts. Pb and Cd were found in trace only in the powders, and K, Ca and Mg were the most abundant elements in both skin powders and extracts. Concentrations of the different contaminants were related to fibre content or total phenolics content of powders and extracts, respectively, in order to evaluate their use in the food sector.

Fabrication of High-Sensitivity Skin-Attachable Temperature Sensors with Bioinspired Microstructured Adhesive.

PubMed

Oh, Ju Hyun; Hong, Soo Yeong; Park, Heun; Jin, Sang Woo; Jeong, Yu Ra; Oh, Seung Yun; Yun, Junyeong; Lee, Hanchan; Kim, Jung Wook; Ha, Jeong Sook

2018-02-28

In this study, we demonstrate the fabrication of a highly sensitive flexible temperature sensor with a bioinspired octopus-mimicking adhesive. A resistor-type temperature sensor consisting of a composite of poly(N-isopropylacrylamide) (pNIPAM)-temperature sensitive hydrogel, poly(3,4-ethylenedioxythiophene) polystyrene sulfonate, and carbon nanotubes exhibits a very high thermal sensitivity of 2.6%·°C -1 between 25 and 40 °C so that the change in skin temperature of 0.5 °C can be accurately detected. At the same time, the polydimethylsiloxane adhesive layer of octopus-mimicking rim structure coated with pNIPAM is fabricated through the formation of a single mold by utilizing undercut phenomenon in photolithography. The fabricated sensor shows stable and reproducible detection of skin temperature under repeated attachment/detachment cycles onto skin without any skin irritation for a long time. This work suggests a high potential application of our skin-attachable temperature sensor to wearable devices for medical and health-care monitoring.

Semi-automated non-invasive diagnostics method for melanoma differentiation from nevi and pigmented basal cell carcinomas

NASA Astrophysics Data System (ADS)

Lihacova, I.; Bolocko, K.; Lihachev, A.

2017-12-01

The incidence of skin cancer is still increasing mostly in in industrialized countries with light- skinned people. Late tumour detection is the main reason of the high mortality associated with skin cancer. The accessibility of early diagnostics of skin cancer in Latvia is limited by several factors, such as high cost of dermatology services, long queues on state funded oncologist examinations, as well as inaccessibility of oncologists in the countryside regions - this is an actual clinical problem. The new strategies and guidelines for skin cancer early detection and post-surgical follow-up intend to realize the full body examination (FBE) by primary care physicians (general practitioners, interns) in combination with classical dermoscopy. To implement this approach, a semi- automated method was established. Developed software analyses the combination of 3 optical density images at 540 nm, 650 nm, and 950 nm from pigmented skin malformations and classifies them into three groups- nevi, pigmented basal cell carcinoma or melanoma.

A quantitative and non-contact technique to characterise microstructural variations of skin tissues during photo-damaging process based on Mueller matrix polarimetry.

PubMed

Dong, Yang; He, Honghui; Sheng, Wei; Wu, Jian; Ma, Hui

2017-10-31

Skin tissue consists of collagen and elastic fibres, which are highly susceptible to damage when exposed to ultraviolet radiation (UVR), leading to skin aging and cancer. However, a lack of non-invasive detection methods makes determining the degree of UVR damage to skin in real time difficult. As one of the fundamental features of light, polarization can be used to develop imaging techniques capable of providing structural information about tissues. In particular, Mueller matrix polarimetry is suitable for detecting changes in collagen and elastic fibres. Here, we demonstrate a novel, quantitative, non-contact and in situ technique based on Mueller matrix polarimetry for monitoring the microstructural changes of skin tissues during UVR-induced photo-damaging. We measured the Mueller matrices of nude mouse skin samples, then analysed the transformed parameters to characterise microstructural changes during the skin photo-damaging and self-repairing processes. Comparisons between samples with and without the application of a sunscreen showed that the Mueller matrix-derived parameters are potential indicators for fibrous microstructure in skin tissues. Histological examination and Monte Carlo simulations confirmed the relationship between the Mueller matrix parameters and changes to fibrous structures. This technique paves the way for non-contact evaluation of skin structure in cosmetics and dermatological health.

CXCL1 and CXCR2 as potential markers for vital reactions in skin contusions.

PubMed

He, Jie-Tao; Huang, Hong-Yan; Qu, Dong; Xue, Ye; Zhang, Kai-Kai; Xie, Xiao-Li; Wang, Qi

2018-06-01

Detection of the vitality of wounds is one of the most important issues in forensic practice. This study investigated mRNA and protein levels of CXCL1 and CXCR2 in skin wounds in mice and humans. Western blot analysis of CXCL1 and CXCR2 protein levels showed no difference between wounded and intact skin. However, mRNA levels demonstrated higher expression of CXCL1 and CXCR2 in contused mouse and human skin, compared with intact skin. At postmortem there were no remarkable changes in CXCL1 and CXCR2 mRNA levels in contused mouse skin. Increased mRNA expression was observed in contused mouse skin up to 96 h and 72 h after death for CXCL1 and CXCR2 respectively. In human samples of wounded skin, increased CXCL1 mRNA levels were detected up to 48 h after autopsy in all 5 cases, while increased CXCR2 mRNA levels were observed 48 h after autopsy in 4 of 5 cases. These findings suggest that the levels of CXCL1 and CXCR2 mRNA present in contused skin can be used as potential markers for a vital reaction in forensic practice.

Patient-specific quantification of image quality: An automated method for measuring spatial resolution in clinical CT images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sanders, Jeremiah, E-mail: jeremiah.sanders@duke.e

Purpose: To develop and validate an automated technique for evaluating the spatial resolution characteristics of clinical computed tomography (CT) images. Methods: Twenty one chest and abdominopelvic clinical CT datasets were examined in this study. An algorithm was developed to extract a CT resolution index (RI) analogous to the modulation transfer function from clinical CT images by measuring the edge-spread function (ESF) across the patient’s skin. A polygon mesh of the air-skin boundary was created. The faces of the mesh were then used to measure the ESF across the air-skin interface. The ESF was differentiated to obtain the line-spread function (LSF),more » and the LSF was Fourier transformed to obtain the RI. The algorithm’s ability to detect the radial dependence of the RI was investigated. RIs measured with the proposed method were compared with a conventional phantom-based method across two reconstruction algorithms (FBP and iterative) using the spatial frequency at 50% RI, f{sub 50}, as the metric for comparison. Three reconstruction kernels were investigated for each reconstruction algorithm. Finally, an observer study was conducted to determine if observers could visually perceive the differences in the measured blurriness of images reconstructed with a given reconstruction method. Results: RI measurements performed with the proposed technique exhibited the expected dependencies on the image reconstruction. The measured f{sub 50} values increased with harder kernels for both FBP and iterative reconstruction. Furthermore, the proposed algorithm was able to detect the radial dependence of the RI. Patient-specific measurements of the RI were comparable to the phantom-based technique, but the patient data exhibited a large spread in the measured f{sub 50}, indicating that some datasets were blurrier than others even when the projection data were reconstructed with the same reconstruction algorithm and kernel. Results from the observer study substantiated this finding. Conclusions: Clinically informed, patient-specific spatial resolution can be measured from clinical datasets. The method is sufficiently sensitive to reflect changes in spatial resolution due to different reconstruction parameters. The method can be applied to automatically assess the spatial resolution of patient images and quantify dependencies that may not be captured in phantom data.« less

Biomechanical Skin Property Evaluation for Wounds Treated With Synthetic and Biosynthetic Wound Dressings and a Newly Developed Collagen Matrix During Healing of Superficial Skin Defects in a Rat Models.

PubMed

Held, Manuel; Engelke, Anne-Sophie; Tolzmann, Dascha Sophie; Rahmanian-Schwarz, Afshin; Schaller, Hans-Eberhard; Rothenberger, Jens

2016-09-01

There is a high prevalence of superficial wounds such as partial-thickness burns. Treatment of these wounds frequently includes temporary application of wound dressings. The aim of this study was to compare a newly developed collagen matrix with commonly used temporary skin dressings for treatment of partial-thickness skin defects. Through a skin dermatome, 42 standardized superficial skin defects were generated on the back of 28 adult male Lewis rats. The wounds were treated with a synthetic wound dressing (Suprathel, Polymedics Innovations Inc, Woodstock, GA) (n = 14), a biosynthetic skin dressing (Biobrane, Smith & Nephew, Hull, UK) (n = 14), or a newly developed bovine collagen matrix, Collagen Cell Carrier (Viscofan BioEngineering, Weinheim, Germany) (n = 14). Biomechanical properties of the skin were determined and compared every 10 days over a 3-month period of using the Cutometer MPA 580 (Courage + Khazaka Electronic GmbH, Cologne, Germany). As opposed to healthy skin, statistically significant differences were detected between days 10 and 30, and between days 60 and 80, for calculated elasticity (Ue), firmness of skin (R0), and overall elasticity (R8). After 3 months, no statistically significant differences in skin elasticity were detected between the different wound dressings. The presented results give an opportunity to compare the wound dressings used for treatment with respect to skin elasticity and reveal the potential of the bovine collagen matrix in the treatment of superficial skin defects; therefore the results facilitate further evaluation of collagen matrix in surgical applications and regenerative medicine.

Development of an Automatic Detection Program of Halo CMEs

NASA Astrophysics Data System (ADS)

Choi, K.; Park, M. Y.; Kim, J.

2017-12-01

The front-side halo CMEs are the major cause for large geomagnetic storms. Halo CMEs can result in damage to satellites, communication, electrical transmission lines and power systems. Thus automated techniques for detecting and analysing Halo CMEs from coronagraph data are of ever increasing importance for space weather monitoring and forecasting. In this study, we developed the algorithm that can automatically detect and do image processing the Halo CMEs in the images from the LASCO C3 coronagraph on board the SOHO spacecraft. With the detection algorithm, we derived the geometric and kinematical parameters of halo CMEs, such as source location, width, actual CME speed and arrival time at 21.5 solar radii.

Non-invasive, investigative methods in skin aging.

PubMed

Longo, C; Ciardo, S; Pellacani, G

2015-12-01

A precise and noninvasive quantification of aging is of outmost importance for in vivo assessment of the skin aging "stage", and thus acts to minimize it. Several bioengineering methods have been proposed to objectively, precisely, and non-invasively measure skin aging, and to detect early skin damage, that is sub-clinically observable. In this review we have described the most relevant methods that have emerged from recently introduced technologies, aiming at quantitatively assessing the effects of aging on the skin.

Systems and methods for data quality control and cleansing

DOEpatents

Wenzel, Michael; Boettcher, Andrew; Drees, Kirk; Kummer, James

2016-05-31

A method for detecting and cleansing suspect building automation system data is shown and described. The method includes using processing electronics to automatically determine which of a plurality of error detectors and which of a plurality of data cleansers to use with building automation system data. The method further includes using processing electronics to automatically detect errors in the data and cleanse the data using a subset of the error detectors and a subset of the cleansers.

Automatic Detection of Electric Power Troubles (ADEPT)

NASA Technical Reports Server (NTRS)

Wang, Caroline; Zeanah, Hugh; Anderson, Audie; Patrick, Clint; Brady, Mike; Ford, Donnie

1988-01-01

Automatic Detection of Electric Power Troubles (A DEPT) is an expert system that integrates knowledge from three different suppliers to offer an advanced fault-detection system. It is designed for two modes of operation: real time fault isolation and simulated modeling. Real time fault isolation of components is accomplished on a power system breadboard through the Fault Isolation Expert System (FIES II) interface with a rule system developed in-house. Faults are quickly detected and displayed and the rules and chain of reasoning optionally provided on a laser printer. This system consists of a simulated space station power module using direct-current power supplies for solar arrays on three power buses. For tests of the system's ablilty to locate faults inserted via switches, loads are configured by an INTEL microcomputer and the Symbolics artificial intelligence development system. As these loads are resistive in nature, Ohm's Law is used as the basis for rules by which faults are located. The three-bus system can correct faults automatically where there is a surplus of power available on any of the three buses. Techniques developed and used can be applied readily to other control systems requiring rapid intelligent decisions. Simulated modeling, used for theoretical studies, is implemented using a modified version of Kennedy Space Center's KATE (Knowledge-Based Automatic Test Equipment), FIES II windowing, and an ADEPT knowledge base.

Unification of automatic target tracking and automatic target recognition

NASA Astrophysics Data System (ADS)

Schachter, Bruce J.

2014-06-01

The subject being addressed is how an automatic target tracker (ATT) and an automatic target recognizer (ATR) can be fused together so tightly and so well that their distinctiveness becomes lost in the merger. This has historically not been the case outside of biology and a few academic papers. The biological model of ATT∪ATR arises from dynamic patterns of activity distributed across many neural circuits and structures (including retina). The information that the brain receives from the eyes is "old news" at the time that it receives it. The eyes and brain forecast a tracked object's future position, rather than relying on received retinal position. Anticipation of the next moment - building up a consistent perception - is accomplished under difficult conditions: motion (eyes, head, body, scene background, target) and processing limitations (neural noise, delays, eye jitter, distractions). Not only does the human vision system surmount these problems, but it has innate mechanisms to exploit motion in support of target detection and classification. Biological vision doesn't normally operate on snapshots. Feature extraction, detection and recognition are spatiotemporal. When vision is viewed as a spatiotemporal process, target detection, recognition, tracking, event detection and activity recognition, do not seem as distinct as they are in current ATT and ATR designs. They appear as similar mechanism taking place at varying time scales. A framework is provided for unifying ATT and ATR.

Automatic Detection of Electric Power Troubles (ADEPT)

NASA Astrophysics Data System (ADS)

Wang, Caroline; Zeanah, Hugh; Anderson, Audie; Patrick, Clint; Brady, Mike; Ford, Donnie

1988-11-01

Automatic Detection of Electric Power Troubles (A DEPT) is an expert system that integrates knowledge from three different suppliers to offer an advanced fault-detection system. It is designed for two modes of operation: real time fault isolation and simulated modeling. Real time fault isolation of components is accomplished on a power system breadboard through the Fault Isolation Expert System (FIES II) interface with a rule system developed in-house. Faults are quickly detected and displayed and the rules and chain of reasoning optionally provided on a laser printer. This system consists of a simulated space station power module using direct-current power supplies for solar arrays on three power buses. For tests of the system's ablilty to locate faults inserted via switches, loads are configured by an INTEL microcomputer and the Symbolics artificial intelligence development system. As these loads are resistive in nature, Ohm's Law is used as the basis for rules by which faults are located. The three-bus system can correct faults automatically where there is a surplus of power available on any of the three buses. Techniques developed and used can be applied readily to other control systems requiring rapid intelligent decisions. Simulated modeling, used for theoretical studies, is implemented using a modified version of Kennedy Space Center's KATE (Knowledge-Based Automatic Test Equipment), FIES II windowing, and an ADEPT knowledge base.

Reducing covert self-injurious behavior maintained by automatic reinforcement through a variable momentary DRO procedure.

PubMed

Toussaint, Karen A; Tiger, Jeffrey H

2012-01-01

Covert self-injurious behavior (i.e., behavior that occurs in the absence of other people) can be difficult to treat. Traditional treatments typically have involved sophisticated methods of observation and often have employed positive punishment procedures. The current study evaluated the effectiveness of a variable momentary differential reinforcement contingency in the treatment of covert self-injury. Neither positive punishment nor extinction was required to produce decreased skin picking.

The application of feature selection to the development of Gaussian process models for percutaneous absorption.

PubMed

Lam, Lun Tak; Sun, Yi; Davey, Neil; Adams, Rod; Prapopoulou, Maria; Brown, Marc B; Moss, Gary P

2010-06-01

The aim was to employ Gaussian processes to assess mathematically the nature of a skin permeability dataset and to employ these methods, particularly feature selection, to determine the key physicochemical descriptors which exert the most significant influence on percutaneous absorption, and to compare such models with established existing models. Gaussian processes, including automatic relevance detection (GPRARD) methods, were employed to develop models of percutaneous absorption that identified key physicochemical descriptors of percutaneous absorption. Using MatLab software, the statistical performance of these models was compared with single linear networks (SLN) and quantitative structure-permeability relationships (QSPRs). Feature selection methods were used to examine in more detail the physicochemical parameters used in this study. A range of statistical measures to determine model quality were used. The inherently nonlinear nature of the skin data set was confirmed. The Gaussian process regression (GPR) methods yielded predictive models that offered statistically significant improvements over SLN and QSPR models with regard to predictivity (where the rank order was: GPR > SLN > QSPR). Feature selection analysis determined that the best GPR models were those that contained log P, melting point and the number of hydrogen bond donor groups as significant descriptors. Further statistical analysis also found that great synergy existed between certain parameters. It suggested that a number of the descriptors employed were effectively interchangeable, thus questioning the use of models where discrete variables are output, usually in the form of an equation. The use of a nonlinear GPR method produced models with significantly improved predictivity, compared with SLN or QSPR models. Feature selection methods were able to provide important mechanistic information. However, it was also shown that significant synergy existed between certain parameters, and as such it was possible to interchange certain descriptors (i.e. molecular weight and melting point) without incurring a loss of model quality. Such synergy suggested that a model constructed from discrete terms in an equation may not be the most appropriate way of representing mechanistic understandings of skin absorption.

Automatic detection and quantitative analysis of cells in the mouse primary motor cortex

NASA Astrophysics Data System (ADS)

Meng, Yunlong; He, Yong; Wu, Jingpeng; Chen, Shangbin; Li, Anan; Gong, Hui

2014-09-01

Neuronal cells play very important role on metabolism regulation and mechanism control, so cell number is a fundamental determinant of brain function. Combined suitable cell-labeling approaches with recently proposed three-dimensional optical imaging techniques, whole mouse brain coronal sections can be acquired with 1-μm voxel resolution. We have developed a completely automatic pipeline to perform cell centroids detection, and provided three-dimensional quantitative information of cells in the primary motor cortex of C57BL/6 mouse. It involves four principal steps: i) preprocessing; ii) image binarization; iii) cell centroids extraction and contour segmentation; iv) laminar density estimation. Investigations on the presented method reveal promising detection accuracy in terms of recall and precision, with average recall rate 92.1% and average precision rate 86.2%. We also analyze laminar density distribution of cells from pial surface to corpus callosum from the output vectorizations of detected cell centroids in mouse primary motor cortex, and find significant cellular density distribution variations in different layers. This automatic cell centroids detection approach will be beneficial for fast cell-counting and accurate density estimation, as time-consuming and error-prone manual identification is avoided.

Optical Interferometric Measurement of Skin Vibration for the Diagnosis of Cardiovascular Diseases.

NASA Astrophysics Data System (ADS)

Hong, Hyundae

A system has been developed based on the measurement of skin surface vibration which is related to the underlying vascular wall motion for the superficial arteries and coronary movement for the chest wall. Data obtained suggests that the information detected by such measurements can be related to the derivative of the intravascular pressure, an important physiological parameter. These results are in contrast to conventional optical Doppler techniques which have been utilized to measure blood perfusion in the skin layers and blood flow within the superficial arteries. These techniques relied on the interaction between incident photons and moving red blood cells. The present system uses an optical interferometer with a 633 nm HeNe laser to detect μm displacements of the skin surface. A photodiode detects an optical Doppler shift signal of frequency, 2 v/ lambda, where v and lambda are the skin vibration velocity and the wavelength of the laser, respectively. The electronic processing system we developed enhances, cleans and processes the raw Doppler signal to produce two main outputs: Doppler audio, and a time domain profile of the skin velocity. The audio signal changes its tone according to the velocity of skin movement which is related to the first derivative of the intravascular pressure, and the internal structure of the intervening tissue layers between the vessel and the surface. The results obtained demonstrated that the skin velocity waveforms near each artery and the chest signals at the auscultation points for the four heart valve sounds were unique in their profiles. It also proved to be possible to measure the magnitude, harmonics, and the cardiovascular propagation delay for pulse waves. The theoretical and experimental results demonstrated that the system detected the skin velocity, which is related to the time derivative of the pressure. It also reduces the loading effect on the pulsation signals and heart sounds produced by the conventional piezoelectric vibration sensors. The system sensitivity, which could potentially be optimized further was 366.2 mum/sec for the present research. Overall, optical cardiovascular vibrometry has the potential to become a simple non invasive approach to cardiovascular screening.

Evaluation of the association between fecal excretion of Mycobacterium avium subsp paratuberculosis and detection in colostrum and on teat skin surfaces of dairy cows

USDA-ARS?s Scientific Manuscript database

Objective—To evaluate the association between fecal excretion of Mycobacterium avium subsp paratuberculosis (MAP) by dairy cows in the periparturient period and detection of MAP DNA in colostrum specimens and on teat skin surfaces. Design—Cross-sectional study. Animals—112 Holstein cows. Procedures—...

Association of Skin Examination Behaviors and Thinner Nodular vs Superficial Spreading Melanoma at Diagnosis.

PubMed

Dessinioti, Clio; Geller, Alan C; Stergiopoulou, Aravella; Swetter, Susan M; Baltas, Eszter; Mayer, Jonathan E; Johnson, Timothy M; Talaganis, John; Trakatelli, Myrto; Tsoutsos, Dimitrios; Tsourouflis, Gerasimos; Stratigos, Alexander J

2018-04-18

Early melanoma detection strategies include skin self-examination (SSE), physician skin examination (PSE), and promotion of patient knowledge about skin cancer. To investigate the association of SSE, PSE, and patient attitudes with the detection of thinner superficial spreading melanoma (SSM) and nodular melanoma (NM), the latter of which tends to elude early detection. This cross-sectional, questionnaire-based, multicenter study identified patients with newly diagnosed cutaneous melanoma at 4 referral hospital centers in the United States, Greece, and Hungary. Among 920 patients with a primary invasive melanoma, 685 patients with SSM or NM subtype were included. A standardized questionnaire was used to record sociodemographic information, SSE and PSE practices, and patient perceptions in the year prior to diagnosis. Data were analyzed according to histologic thickness, with a 2-mm cutoff for thinner SSM and NM. Of 685 participants (mean [SD] age, 55.6 [15.1] years; 318 [46%] female), thinner melanoma was detected in 437 of 538 SSM (81%) and in 40 of 147 NM (27%). Patients who routinely performed SSE were more likely to be diagnosed with thinner SSM (odds ratio [OR], 2.61; 95% CI, 1.14-5.40) but not thinner NM (OR, 2.39; 95% CI, 0.84-6.80). Self-detected clinical warning signs (eg, elevation and onset of pain) were markers of thicker SSM and NM. Whole-body PSE was associated with a 2-fold increase in detection of thinner SSM (OR, 2.25; 95% CI, 1.16-4.35) and thinner NM (OR, 2.67; 95% CI, 1.05-6.82). Patient attitudes and perceptions focusing on increased interest in skin cancer were associated with the detection of thinner NM. Our findings underscore the importance of complementary practices by patients and physicians for the early detection of melanoma, including regular whole-body PSE, SSE, and increased patient awareness.

Determination of organochlorine pesticides in skins and leather by gas chromatography.

PubMed

Font, J; Marsal, A

1998-06-19

The simultaneous determination of residues of lindane (gamma-HCH) and 10 other organochlorine pesticides (OCPs) in skins and leather was carried out by gas chromatography (GC) with electron-capture detection (ECD). GC with mass spectrometric detection was used to identity confirmation. Samples were extracted with hexane. The extracts were concentrated, and cleaned up on a Florisil column. Dibromooctafluorobiphenyl was added as internal standard. Hide fortifications of 0.5 an d5.0 ppm yielded average lindane recoveries of 98% and 96%, respectively. OCPs was determined in 57 samples of skins purchased from American, European and African countries in 1996-1997. OCPs were not detected in any of the American and European samples. Residues of lindane were found in 56% of African samples.

Automating mouse weighing in group homecages with Raspberry Pi micro-computers.

PubMed

Noorshams, Omid; Boyd, Jamie D; Murphy, Timothy H

2017-06-15

Operant training systems make use of water or food restriction and make it necessary to weigh animals to ensure compliance with experimental endpoints. In other applications periodic weighing is necessary to assess drug side-effects, or as an endpoint in feeding experiments. Periodic weighing while essential can disrupt animal circadian rhythms and social structure. Automatic weighing system within paired mouse homecages. Up to 10 mice freely move between two cages (28×18×9cm) which were connected by a weighing chamber mounted on a load cell. Each mouse was identified using an RFID tag placed under the skin of the neck. A single-board computer (Raspberry Pi; RPi) controls the task, logging RFID tag, load cell weights, and time stamps from each RFID detection until the animal leaves the chamber. Collected data were statistically analyzed to estimate mouse weights. We anticipate integration with tasks where automated imaging or behaviour is assessed in homecages. Mice frequently move between the two cages, an average of 42+-16 times/day/mouse at which time we obtained weights. We report accurate determination of mouse weight and long term monitoring over 53days. Comparison with existing methods Although commercial systems are available for automatically weighing rodents, they only work with single animals, or are not open source nor cost effective for specific custom application. This automated system permits automated weighing of mice ∼40 times per day. The system employs inexpensive hardware and open-source Python code. Copyright © 2017 Elsevier B.V. All rights reserved.

Structural Integrity Evaluation of the Lear Fan 2100 Aircraft

NASA Technical Reports Server (NTRS)

Kan, H. P.; Dyer, T. A.

1996-01-01

An in-situ nondestructive inspection was conducted to detect manufacturing and assembly induced defects in the upper two wing surfaces (skin s) and upper fuselage skin of the Lear Fan 2100 aircraft E009. The effects of the defects, detected during the inspection, on the integrity of the structure was analytically evaluated. A systematic evaluation was also conducted to determine the damage tolerance capability of the upper wing skin against impact threats and assembly induced damage. The upper wing skin was divided into small regions for damage tolerance evaluations. Structural reliability, margin of safety, allowable strains, and allowable damage size were computed. The results indicated that the impact damage threat imposed on composite military aircraft structures is too severe for the Lear Fan 2100 upper wing skin. However, the structural integrity is not significantly degraded by the assembly induced damage for properly assembled structures, such as the E009 aircraft.

Detection of Treponema pallidum subsp. pallidum from Skin Lesions, Serum, and Cerebrospinal Fluid in an Infant with Congenital Syphilis after Clindamycin Treatment of the Mother during Pregnancy▿

PubMed Central

Woznicová, Vladana; Šmajs, David; Wechsler, Dan; Matějková, Petra; Flasarová, Magdalena

2007-01-01

We report here a case of congenital syphilis in a newborn after clindamycin treatment in pregnancy. Using PCR detection of tmpC (TP0319) and DNA sequencing of the genes TP0136 and TP0548, DNA sequences identical to Treponema pallidum subsp. pallidum strain SS14 were detected in the infant's skin lesions, serum, and cerebrospinal fluid. PMID:17151205

Automatic three-dimensional measurement of large-scale structure based on vision metrology.

PubMed

Zhu, Zhaokun; Guan, Banglei; Zhang, Xiaohu; Li, Daokui; Yu, Qifeng

2014-01-01

All relevant key techniques involved in photogrammetric vision metrology for fully automatic 3D measurement of large-scale structure are studied. A new kind of coded target consisting of circular retroreflective discs is designed, and corresponding detection and recognition algorithms based on blob detection and clustering are presented. Then a three-stage strategy starting with view clustering is proposed to achieve automatic network orientation. As for matching of noncoded targets, the concept of matching path is proposed, and matches for each noncoded target are found by determination of the optimal matching path, based on a novel voting strategy, among all possible ones. Experiments on a fixed keel of airship have been conducted to verify the effectiveness and measuring accuracy of the proposed methods.

Automatic extraction of road features in urban environments using dense ALS data

NASA Astrophysics Data System (ADS)

Soilán, Mario; Truong-Hong, Linh; Riveiro, Belén; Laefer, Debra

2018-02-01

This paper describes a methodology that automatically extracts semantic information from urban ALS data for urban parameterization and road network definition. First, building façades are segmented from the ground surface by combining knowledge-based information with both voxel and raster data. Next, heuristic rules and unsupervised learning are applied to the ground surface data to distinguish sidewalk and pavement points as a means for curb detection. Then radiometric information was employed for road marking extraction. Using high-density ALS data from Dublin, Ireland, this fully automatic workflow was able to generate a F-score close to 95% for pavement and sidewalk identification with a resolution of 20 cm and better than 80% for road marking detection.

Automatic Emboli Detection System for the Artificial Heart

NASA Astrophysics Data System (ADS)

Steifer, T.; Lewandowski, M.; Karwat, P.; Gawlikowski, M.

In spite of the progress in material engineering and ventricular assist devices construction, thromboembolism remains the most crucial problem in mechanical heart supporting systems. Therefore, the ability to monitor the patient's blood for clot formation should be considered an important factor in development of heart supporting systems. The well-known methods for automatic embolus detection are based on the monitoring of the ultrasound Doppler signal. A working system utilizing ultrasound Doppler is being developed for the purpose of flow estimation and emboli detection in the clinical artificial heart ReligaHeart EXT. Thesystem will be based on the existing dual channel multi-gate Doppler device with RF digital processing. A specially developed clamp-on cannula probe, equipped with 2 - 4 MHz piezoceramic transducers, enables easy system setup. We present the issuesrelated to the development of automatic emboli detection via Doppler measurements. We consider several algorithms for the flow estimation and emboli detection. We discuss their efficiency and confront them with the requirements of our experimental setup. Theoretical considerations are then met with preliminary experimental findings from a) flow studies with blood mimicking fluid and b) in-vitro flow studies with animal blood. Finally, we discuss some more methodological issues - we consider several possible approaches to the problem of verification of the accuracy of the detection system.