Kinematic measurements of the vocal-fold displacement waveform in typical children and adult populations: quantification of high-speed endoscopic videos.

PubMed

Patel, Rita; Donohue, Kevin D; Unnikrishnan, Harikrishnan; Kryscio, Richard J

2015-04-01

This article presents a quantitative method for assessing instantaneous and average lateral vocal-fold motion from high-speed digital imaging, with a focus on developmental changes in vocal-fold kinematics during childhood. Vocal-fold vibrations were analyzed for 28 children (aged 5-11 years) and 28 adults (aged 21-45 years) without voice disorders. The following kinematic features were analyzed from the vocal-fold displacement waveforms: relative velocity-based features (normalized average and peak opening and closing velocities), relative acceleration-based features (normalized peak opening and closing accelerations), speed quotient, and normalized peak displacement. Children exhibited significantly larger normalized peak displacements, normalized average and peak opening velocities, normalized average and peak closing velocities, peak opening and closing accelerations, and speed quotient compared to adult women. Values of normalized average closing velocity and speed quotient were higher in children compared to adult men. When compared to adult men, developing children typically have higher estimates of kinematic features related to normalized displacement and its derivatives. In most cases, the kinematic features of children are closer to those of adult men than adult women. Even though boys experience greater changes in glottal length and pitch as they mature, results indicate that girls experience greater changes in kinematic features compared to boys.

Longitudinal MRI assessment: the identification of relevant features in the development of Posterior Fossa Syndrome in children

NASA Astrophysics Data System (ADS)

Spiteri, M.; Lewis, E.; Windridge, D.; Avula, S.

2015-03-01

Up to 25% of children who undergo brain tumour resection surgery in the posterior fossa develop posterior fossa syndrome (PFS). This syndrome is characterised by mutism and disturbance in speech. Our hypothesis is that there is a correlation between PFS and the occurrence of hypertrophic olivary degeneration (HOD) in lobes within the posterior fossa, known as the inferior olivary nuclei (ION). HOD is exhibited as an increase in size and intensity of the ION on an MR image. Intra-operative MRI (IoMRI) is used during surgical procedures at the Alder Hey Children's Hospital, Liver- pool, England, in the treatment of Posterior Fossa tumours and allows visualisation of the brain during surgery. The final MR scan on the IoMRI allows early assessment of the ION immediately after the surgical procedure. The longitudinal MRI data of 28 patients was analysed in a collaborative study with Alder Hey Children's Hospital, in order to identify the most relevant imaging features that relate to the development of PFS, specifically related to HOD. A semi-automated segmentation process was carried out to delineate the ION on each MRI. Feature selection techniques were used to identify the most relevant features amongst the MRI data, demographics and clinical data provided by the hospital. A support vector machine (SVM) was used to analyse the discriminative ability of the selected features. The results indicate the presence of HOD as the most efficient feature that correlates with the development of PFS, followed by the change in intensity and size of the ION and whether HOD occurred bilaterally or unilaterally.

Insights into multimodal imaging classification of ADHD

PubMed Central

Colby, John B.; Rudie, Jeffrey D.; Brown, Jesse A.; Douglas, Pamela K.; Cohen, Mark S.; Shehzad, Zarrar

2012-01-01

Attention deficit hyperactivity disorder (ADHD) currently is diagnosed in children by clinicians via subjective ADHD-specific behavioral instruments and by reports from the parents and teachers. Considering its high prevalence and large economic and societal costs, a quantitative tool that aids in diagnosis by characterizing underlying neurobiology would be extremely valuable. This provided motivation for the ADHD-200 machine learning (ML) competition, a multisite collaborative effort to investigate imaging classifiers for ADHD. Here we present our ML approach, which used structural and functional magnetic resonance imaging data, combined with demographic information, to predict diagnostic status of individuals with ADHD from typically developing (TD) children across eight different research sites. Structural features included quantitative metrics from 113 cortical and non-cortical regions. Functional features included Pearson correlation functional connectivity matrices, nodal and global graph theoretical measures, nodal power spectra, voxelwise global connectivity, and voxelwise regional homogeneity. We performed feature ranking for each site and modality using the multiple support vector machine recursive feature elimination (SVM-RFE) algorithm, and feature subset selection by optimizing the expected generalization performance of a radial basis function kernel SVM (RBF-SVM) trained across a range of the top features. Site-specific RBF-SVMs using these optimal feature sets from each imaging modality were used to predict the class labels of an independent hold-out test set. A voting approach was used to combine these multiple predictions and assign final class labels. With this methodology we were able to predict diagnosis of ADHD with 55% accuracy (versus a 39% chance level in this sample), 33% sensitivity, and 80% specificity. This approach also allowed us to evaluate predictive structural and functional features giving insight into abnormal brain circuitry in ADHD. PMID:22912605

Multiparametric MRI characterization and prediction in autism spectrum disorder using graph theory and machine learning.

PubMed

Zhou, Yongxia; Yu, Fang; Duong, Timothy

2014-01-01

This study employed graph theory and machine learning analysis of multiparametric MRI data to improve characterization and prediction in autism spectrum disorders (ASD). Data from 127 children with ASD (13.5±6.0 years) and 153 age- and gender-matched typically developing children (14.5±5.7 years) were selected from the multi-center Functional Connectome Project. Regional gray matter volume and cortical thickness increased, whereas white matter volume decreased in ASD compared to controls. Small-world network analysis of quantitative MRI data demonstrated decreased global efficiency based on gray matter cortical thickness but not with functional connectivity MRI (fcMRI) or volumetry. An integrative model of 22 quantitative imaging features was used for classification and prediction of phenotypic features that included the autism diagnostic observation schedule, the revised autism diagnostic interview, and intelligence quotient scores. Among the 22 imaging features, four (caudate volume, caudate-cortical functional connectivity and inferior frontal gyrus functional connectivity) were found to be highly informative, markedly improving classification and prediction accuracy when compared with the single imaging features. This approach could potentially serve as a biomarker in prognosis, diagnosis, and monitoring disease progression.

Distinct phenotype clusters in childhood inflammatory brain diseases: implications for diagnostic evaluation.

PubMed

Cellucci, Tania; Tyrrell, Pascal N; Twilt, Marinka; Sheikh, Shehla; Benseler, Susanne M

2014-03-01

To identify distinct clusters of children with inflammatory brain diseases based on clinical, laboratory, and imaging features at presentation, to assess which features contribute strongly to the development of clusters, and to compare additional features between the identified clusters. A single-center cohort study was performed with children who had been diagnosed as having an inflammatory brain disease between June 1, 1989 and December 31, 2010. Demographic, clinical, laboratory, neuroimaging, and histologic data at diagnosis were collected. K-means cluster analysis was performed to identify clusters of patients based on their presenting features. Associations between the clusters and patient variables, such as diagnoses, were determined. A total of 147 children (50% female; median age 8.8 years) were identified: 105 with primary central nervous system (CNS) vasculitis, 11 with secondary CNS vasculitis, 8 with neuronal antibody syndromes, 6 with postinfectious syndromes, and 17 with other inflammatory brain diseases. Three distinct clusters were identified. Paresis and speech deficits were the most common presenting features in cluster 1. Children in cluster 2 were likely to present with behavior changes, cognitive dysfunction, and seizures, while those in cluster 3 experienced ataxia, vision abnormalities, and seizures. Lesions seen on T2/fluid-attenuated inversion recovery sequences of magnetic resonance imaging were common in all clusters, but unilateral ischemic lesions were more prominent in cluster 1. The clusters were associated with specific diagnoses and diagnostic test results. Children with inflammatory brain diseases presented with distinct phenotypical patterns that are associated with specific diagnoses. This information may inform the development of a diagnostic classification of childhood inflammatory brain diseases and suggest that specific pathways of diagnostic evaluation are warranted. Copyright © 2014 by the American College of Rheumatology.

Beyond Representation: Exploring Drawing as Part of Children's Meaning-Making

ERIC Educational Resources Information Center

Darling-McQuistan, Kirsten

2017-01-01

Drawing is an everyday feature of primary school classrooms. All too often however, its role within the classroom is limited to a "representational" one, used to demonstrate the accuracy of children's images and representations of the world. Furthermore, drawings, which most closely "match" objective, dominant perspectives are…

Kinematic Measurements of the Vocal-Fold Displacement Waveform in Typical Children and Adult Populations: Quantification of High-Speed Endoscopic Videos

PubMed Central

Donohue, Kevin D.; Unnikrishnan, Harikrishnan; Kryscio, Richard J.

2015-01-01

Purpose This article presents a quantitative method for assessing instantaneous and average lateral vocal-fold motion from high-speed digital imaging, with a focus on developmental changes in vocal-fold kinematics during childhood. Method Vocal-fold vibrations were analyzed for 28 children (aged 5–11 years) and 28 adults (aged 21–45 years) without voice disorders. The following kinematic features were analyzed from the vocal-fold displacement waveforms: relative velocity-based features (normalized average and peak opening and closing velocities), relative acceleration-based features (normalized peak opening and closing accelerations), speed quotient, and normalized peak displacement. Results Children exhibited significantly larger normalized peak displacements, normalized average and peak opening velocities, normalized average and peak closing velocities, peak opening and closing accelerations, and speed quotient compared to adult women. Values of normalized average closing velocity and speed quotient were higher in children compared to adult men. Conclusions When compared to adult men, developing children typically have higher estimates of kinematic features related to normalized displacement and its derivatives. In most cases, the kinematic features of children are closer to those of adult men than adult women. Even though boys experience greater changes in glottal length and pitch as they mature, results indicate that girls experience greater changes in kinematic features compared to boys. PMID:25652615

Dance and Imagery--The Link between Movement and Imagination.

ERIC Educational Resources Information Center

Smith, Karen Lynn, Ed.; And Others

1990-01-01

This feature examines the diverse nature of imagery, how images work, and the use of imagery--in creative dance for children, to enhance alignment, and as a therapeutic device. Also explored are creative visualization and research tools for observing and categorizing the use of images by dance teachers. (IAH)

Dose assessment of digital tomosynthesis in pediatric imaging

NASA Astrophysics Data System (ADS)

Gislason, Amber; Elbakri, Idris A.; Reed, Martin

2009-02-01

We investigated the potential for digital tomosynthesis (DT) to reduce pediatric x-ray dose while maintaining image quality. We utilized the DT feature (VolumeRadTM) on the GE DefiniumTM 8000 flat panel system installed in the Winnipeg Children's Hospital. Facial bones, cervical spine, thoracic spine, and knee of children aged 5, 10, and 15 years were represented by acrylic phantoms for DT dose measurements. Effective dose was estimated for DT and for corresponding digital radiography (DR) and computed tomography (CT) patient image sets. Anthropomorphic phantoms of selected body parts were imaged by DR, DT, and CT. Pediatric radiologists rated visualization of selected anatomic features in these images. Dose and image quality comparisons between DR, DT, and CT determined the usefulness of tomosynthesis for pediatric imaging. CT effective dose was highest; total DR effective dose was not always lowest - depending how many projections were in the DR image set. For the cervical spine, DT dose was close to and occasionally lower than DR dose. Expert radiologists rated visibility of the central facial complex in a skull phantom as better than DR and comparable to CT. Digital tomosynthesis has a significantly lower dose than CT. This study has demonstrated DT shows promise to replace CT for some facial bones and spinal diagnoses. Other clinical applications will be evaluated in the future.

Normal Rates of Neuroradiological Findings in Children with High Functioning Autism

ERIC Educational Resources Information Center

Vasa, Roma A.; Ranta, Marin; Huisman, Thierry A. G. M.; Pinto, Pedro S.; Tillman, Rachael M.; Mostofsky, Stewart H.

2012-01-01

Magnetic resonance imaging (MRI) has been used to analyze highly specific volumetric and morphological features of the brains of individuals with autism spectrum disorder (ASD). To date, there are few comprehensive studies examining the prevalence of neuroradiologic findings seen on routine MRI scans in children with ASD. This study examined the…

Disrupted white matter connectivity underlying developmental dyslexia: A machine learning approach.

PubMed

Cui, Zaixu; Xia, Zhichao; Su, Mengmeng; Shu, Hua; Gong, Gaolang

2016-04-01

Developmental dyslexia has been hypothesized to result from multiple causes and exhibit multiple manifestations, implying a distributed multidimensional effect on human brain. The disruption of specific white-matter (WM) tracts/regions has been observed in dyslexic children. However, it remains unknown if developmental dyslexia affects the human brain WM in a multidimensional manner. Being a natural tool for evaluating this hypothesis, the multivariate machine learning approach was applied in this study to compare 28 school-aged dyslexic children with 33 age-matched controls. Structural magnetic resonance imaging (MRI) and diffusion tensor imaging were acquired to extract five multitype WM features at a regional level: white matter volume, fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity. A linear support vector machine (LSVM) classifier achieved an accuracy of 83.61% using these MRI features to distinguish dyslexic children from controls. Notably, the most discriminative features that contributed to the classification were primarily associated with WM regions within the putative reading network/system (e.g., the superior longitudinal fasciculus, inferior fronto-occipital fasciculus, thalamocortical projections, and corpus callosum), the limbic system (e.g., the cingulum and fornix), and the motor system (e.g., the cerebellar peduncle, corona radiata, and corticospinal tract). These results were well replicated using a logistic regression classifier. These findings provided direct evidence supporting a multidimensional effect of developmental dyslexia on WM connectivity of human brain, and highlighted the involvement of WM tracts/regions beyond the well-recognized reading system in dyslexia. Finally, the discriminating results demonstrated a potential of WM neuroimaging features as imaging markers for identifying dyslexic individuals. © 2016 Wiley Periodicals, Inc.

Using ICT to Foster (Pre) Reading and Writing Skills in Young Children

ERIC Educational Resources Information Center

Voogt, Joke; McKenney, Susan

2008-01-01

This study examines how technology can support the development of emergent reading and writing skills in four- to five-year-old children. The research was conducted with PictoPal, an intervention which features a software package that uses images and text in three main activity areas: reading, writing, and authentic applications. This article…

Just Like All the Other Humans? Analyzing Images of Scientists in Children's Trade Books

ERIC Educational Resources Information Center

Rawson, Casey H.; McCool, Megan Astolfi

2014-01-01

Despite the efforts of researchers and national science organizations to recruit more women and minorities into the science and engineering workforce, these fields are still largely dominated by White males. Research suggests that children's mental prototypes of the scientist include a variety of negative and stereotypical features that may…

Reduced White Matter Connectivity in the Corpus Callosum of Children with Tourette Syndrome

ERIC Educational Resources Information Center

Plessen, Kerstin J.; Gruner, Renate; Lundervold, Arvid; Hirsch, Jochen G.; Xu, Dongrong; Bansal, Ravi; Hammar, Asa; Lundervold, Astri J.; Wentzel-Larsen, Tore; Lie, Stein Atle; Gass, Achim; Peterson, Bradley S.; Hugdahl, Kenneth

2006-01-01

Background: Brain imaging studies have revealed anatomical anomalies in the brains of individuals with Tourette syndrome (TS). Prefrontal regions have been found to be larger and the corpus callosum (CC) area smaller in children and young adults with TS compared with healthy control subjects, and these anatomical features have been understood to…

Paediatric acquired demyelinating syndromes: incidence, clinical and magnetic resonance imaging features.

PubMed

Absoud, Michael; Lim, Ming J; Chong, Wui K; De Goede, Christian G; Foster, Katharine; Gunny, Roxana; Hemingway, Cheryl; Jardine, Philip E; Kneen, Rachel; Likeman, Marcus; Nischal, Ken K; Pike, Michael G; Sibtain, Naomi A; Whitehouse, William P; Cummins, Carole; Wassmer, Evangeline

2013-01-01

Changing trends in multiple sclerosis (MS) epidemiology may first be apparent in the childhood population affected with first onset acquired demyelinating syndromes (ADSs). We aimed to determine the incidence, clinical, investigative and magnetic resonance imaging (MRI) features of childhood central nervous system ADSs in the British Isles for the first time. We conducted a population active surveillance study. All paediatricians, and ophthalmologists (n = 4095) were sent monthly reporting cards (September 2009-September 2010). International Paediatric MS Study Group 2007 definitions and McDonald 2010 MS imaging criteria were used for acute disseminated encephalomyelitis (ADEM), clinically isolated syndrome (CIS) and neuromyelitis optica (NMO). Clinicians completed a standard questionnaire and provided an MRI copy for review. Card return rates were 90%, with information available for 200/222 positive notifications (90%). After exclusion of cases, 125 remained (age range 1.3-15.9), with CIS in 66.4%, ADEM in 32.0% and NMO in 1.6%. The female-to-male ratio in children older than 10 years (n = 63) was 1.52:1 (p = 0.045). The incidence of first onset ADS in children aged 1-15 years old was 9.83 per million children per year (95% confidence interval [CI] 8.18-11.71). A trend towards higher incidence rates of ADS in children of South Asian and Black ethnicity was observed compared with White children. Importantly, a number of MRI characteristics distinguished ADEM from CIS cases. Of CIS cases with contrast imaging, 26% fulfilled McDonald 2010 MS diagnostic criteria. We report the highest surveillance incidence rates of childhood ADS. Paediatric MS diagnosis at first ADS presentation has implications for clinical practice and clinical trial design.

The perception of children's computer-imaged facial profiles by patients, mothers and clinicians.

PubMed

Miner, Robert M; Anderson, Nina K; Evans, Carla A; Giddon, Donald B

2007-11-01

To demonstrate the usefulness of a new imaging system for comparing the morphometric bases of children's self-perception of their facial profile with the perceptions of their mothers and treating clinicians. Rather than choosing among a series of static images, a computer imaging program was developed to elicit a range of acceptable responses or tolerance for change from which a midpoint of acceptability was derived. Using the method of Giddon et al, three profile features (upper and lower lips and mandible) from standardized images of 24 patients aged 8- 15 years were distorted and presented to patients, parents, and clinicians in random order as slowly moving images (four frames per second) from retrusive and protrusive extremes. Subjects clicked the mouse when the image became acceptable and released it when it was no longer acceptable. Subjects responded similarly to a neutral facial profile. Patients and their mothers overestimated the protrusiveness of the mandible of the actual pretreatment profile. Consistent with related studies, mothers had a smaller tolerance for change in the soft tissue profile than the children or clinicians. The magnitudes of the children's self-preference and preferred change in a neutral face were also significantly correlated. Both patients and mothers preferred a more protrusive profile than that of the actual or neutral face for the patient and neutral face. Imaging software can be used with children to compare their preferences with those of parents and clinicians to facilitate treatment planning and patient satisfaction.

Texture feature extraction based on wavelet transform and gray-level co-occurrence matrices applied to osteosarcoma diagnosis.

PubMed

Hu, Shan; Xu, Chao; Guan, Weiqiao; Tang, Yong; Liu, Yana

2014-01-01

Osteosarcoma is the most common malignant bone tumor among children and adolescents. In this study, image texture analysis was made to extract texture features from bone CR images to evaluate the recognition rate of osteosarcoma. To obtain the optimal set of features, Sym4 and Db4 wavelet transforms and gray-level co-occurrence matrices were applied to the image, with statistical methods being used to maximize the feature selection. To evaluate the performance of these methods, a support vector machine algorithm was used. The experimental results demonstrated that the Sym4 wavelet had a higher classification accuracy (93.44%) than the Db4 wavelet with respect to osteosarcoma occurrence in the epiphysis, whereas the Db4 wavelet had a higher classification accuracy (96.25%) for osteosarcoma occurrence in the diaphysis. Results including accuracy, sensitivity, specificity and ROC curves obtained using the wavelets were all higher than those obtained using the features derived from the GLCM method. It is concluded that, a set of texture features can be extracted from the wavelets and used in computer-aided osteosarcoma diagnosis systems. In addition, this study also confirms that multi-resolution analysis is a useful tool for texture feature extraction during bone CR image processing.

Brain tumour classification and abnormality detection using neuro-fuzzy technique and Otsu thresholding.

PubMed

Renjith, Arokia; Manjula, P; Mohan Kumar, P

2015-01-01

Brain tumour is one of the main causes for an increase in transience among children and adults. This paper proposes an improved method based on Magnetic Resonance Imaging (MRI) brain image classification and image segmentation approach. Automated classification is encouraged by the need of high accuracy when dealing with a human life. The detection of the brain tumour is a challenging problem, due to high diversity in tumour appearance and ambiguous tumour boundaries. MRI images are chosen for detection of brain tumours, as they are used in soft tissue determinations. First of all, image pre-processing is used to enhance the image quality. Second, dual-tree complex wavelet transform multi-scale decomposition is used to analyse texture of an image. Feature extraction extracts features from an image using gray-level co-occurrence matrix (GLCM). Then, the Neuro-Fuzzy technique is used to classify the stages of brain tumour as benign, malignant or normal based on texture features. Finally, tumour location is detected using Otsu thresholding. The classifier performance is evaluated based on classification accuracies. The simulated results show that the proposed classifier provides better accuracy than previous method.

A diagnosis model for early Tourette syndrome children based on brain structural network characteristics

NASA Astrophysics Data System (ADS)

Wen, Hongwei; Liu, Yue; Wang, Jieqiong; Zhang, Jishui; Peng, Yun; He, Huiguang

2016-03-01

Tourette syndrome (TS) is a childhood-onset neurobehavioral disorder characterized by the presence of multiple motor and vocal tics. Tic generation has been linked to disturbed networks of brain areas involved in planning, controlling and execution of action. The aim of our work is to select topological characteristics of structural network which were most efficient for estimating the classification models to identify early TS children. Here we employed the diffusion tensor imaging (DTI) and deterministic tractography to construct the structural networks of 44 TS children and 48 age and gender matched healthy children. We calculated four different connection matrices (fiber number, mean FA, averaged fiber length weighted and binary matrices) and then applied graph theoretical methods to extract the regional nodal characteristics of structural network. For each weighted or binary network, nodal degree, nodal efficiency and nodal betweenness were selected as features. Support Vector Machine Recursive Feature Extraction (SVM-RFE) algorithm was used to estimate the best feature subset for classification. The accuracy of 88.26% evaluated by a nested cross validation was achieved on combing best feature subset of each network characteristic. The identified discriminative brain nodes mostly located in the basal ganglia and frontal cortico-cortical networks involved in TS children which was associated with tic severity. Our study holds promise for early identification and predicting prognosis of TS children.

MR image analytics to characterize upper airway architecture in children with OSAS

NASA Astrophysics Data System (ADS)

Tong, Yubing; Udupa, Jayaram K.; Torigian, Drew A.; Matsumoto, Monica M. S.; Sin, Sanghun; Arens, Raanan

2015-03-01

Mechanisms leading to Obstructive Sleep Apnea Syndrome (OSAS) in obese children are not well understood. We previously analyzed polysomnographic and demographic data to study the anatomical characteristics of the upper airway and body composition in two groups of obese children with and without OSAS, where object volume was evaluated. In this paper, in order to better understand the disease we expand the analysis considering a variety of features that include object-specific features such as size, surface area, sphericity, and image intensity properties of fourteen objects in the vicinity of the upper airway, as well as inter-object relationships such as distance between objects. Our preliminary results indicate several interesting phenomena: volumes and surface areas of adenoid and tonsils increase statistically significantly in OSAS. Standardized T2-weighted MR image intensities differ statistically significantly between the two groups, implying that perhaps intrinsic tissue composition undergoes changes in OSAS. Inter-object distances are significantly different between the two groups for object pairs (skin, oropharynx), (skin, fat pad), (skin, soft palate), (mandible, tongue), (oropharynx, soft palate), (left tonsil, oropharynx), (left tonsil, fat pad) and (left tonsil, right tonsil). We conclude that treatment methods for OSAS such as adenotonsillectomy should respect proportional object size relationships and spatial arrangement of objects as they exist in control subjects.

Sensitivity to Spacing Changes in Faces and Nonface Objects in Preschool-Aged Children and Adults

ERIC Educational Resources Information Center

Cassia, Viola Macchi; Turati, Chiara; Schwarzer, Gudrun

2011-01-01

Sensitivity to variations in the spacing of features in faces and a class of nonface objects (i.e., frontal images of cars) was tested in 3- and 4-year-old children and adults using a delayed or simultaneous two-alternative forced choice matching-to-sample task. In the adults, detection of spacing information was robust against exemplar…

[Vertical retraction syndrome caused by anomalous orbital structures].

PubMed

Yang, Qiong; Jiao, Yong-hong; Man, Feng-yuan; Wang, Zhen-chang; Chang, Qing-lin; Lu, Wei; Wang, Jing-hui; Zhao, Kan-xing

2011-11-01

To described the clinical feature and MRI imaging of six children with vertical retraction syndrome. Six children with unilateral vertical retraction syndrome between 15 months and 8 years of age, mean age was (5.01 ± 1.27) years old. Strabismus examination included diopter, prism diopters, eye movement examination, binocular vision and fundus examination. Imaging of the ocular motor nerves at the brainstem was performed in 0.8 mm thickness image planes using 3D-FIESTA sequence, the orbits were imaged with FSE T1, T2WI using surface coils, and within 2.0 mm thick planes. Four children showed hypertropia, characterized by limited depression, a light retraction of the globe during downward gaze and eyelid lag. The MRI imaging showed anomalous orbital structure in the superonasal quadrant that between medial rectus and superior rectus or adjacent to the superior rectus. Two children showed intermittent exotropia, characterized by limited elevation, retraction of the globe and narrowing of the palpebral fissure during upward gaze. The MRI imaging showed anomalous orbital structure was present in the inferotemporal quadrant, one originate in inferior rectus and another close to the lateral rectus. Anomalous orbital structures are a main cause of vertical retraction syndrome. The presence of specific unusual eye movement and MRI imaging may assist in diagnosis. When the eyelid lag was found since the early age, anomalous orbital structures were implied.

The association between sleep-disordered breathing and magnetic resonance imaging findings in a pediatric cohort with Chiari 1 malformation

PubMed Central

Amin, Reshma; Sayal, Priya; Sayal, Aarti; Massicote, Colin; Pham, Robin; Al-Saleh, Suhail; Drake, James; Narang, Indra

2015-01-01

BACKGROUND: The prevalence of sleep-disordered breathing (SDB) reported in the literature for Chiari malformation type 1 (CM1) is uniformly high (24% to 70%). In Canada, there is limited access to pediatric polysomnography (PSG). Therefore, the identification of clinical features would be invaluable for triaging these children. OBJECTIVE: To identify demographic features, clinical symptoms/signs and radiological findings associated with SDB in a large pediatric cohort with CM1. METHODS: A retrospective review was conducted on children with CM1 who underwent baseline PSG. Data were collected on patient demographics (age, sex, weight, height, body mass index), clinical symptoms (chart review and clinical questionnaires), diagnostic imaging of the brain and cervicothoracic spine, and medical history at the time of referral. RESULTS: A total of 68 children were included in the review. The mean (± SD) age of the children at the time of PSG was 7.33±4.01 years; 56% (n=38) were male. There was a 49% prevalence of SDB in this cohort based on the overall apnea-hypopnea index. Obstructive sleep apnea was the predominant type of SDB. Tonsillar herniation was significantly correlated with obstructive apnea-hypopnea index (r=0.24; P=0.036). CONCLUSIONS: A direct relationship between the degree of cerebellar tonsillar herniation and obstructive sleep apnea was demonstrated. However, further prospective studies that include neurophysiological assessment are needed to further translate the central nervous system imaging findings to predict the presence of SDB. PMID:25379655

Imaging of American football injuries in children.

PubMed

Podberesky, Daniel J; Unsell, Bryan J; Anton, Christopher G

2009-12-01

It is estimated that 3.2 million children ages 6 to 14 years participated in organized youth football in the United States in 2007. Approximately 240,000 children play football in the nation's largest youth football organization, with tackle divisions starting at age 5 years. The number of children playing unsupervised football is much higher, and the overall number of children participating in American football is increasing. Sports are the leading cause of injury-related emergency room visits for teenagers, and football is a leading precipitating athletic activity for these visits. Football is also the most hazardous organized sports in the United States. Though most pediatric football-related injuries are minor, such as abrasions, sprains, and strains of the extremities, football accounts for more major and catastrophic injuries than any other sport. Given football's popularity with children in the United States, combined with the high rate of injury associated with participation in this activity, radiologists should be familiar with the imaging features and injury patterns seen in this patient population.

The use of neuroimaging in the management of chronic headache in children in clinical practice versus clinical practice guidelines.

PubMed

Prpić, Igor; Ahel, Tea; Rotim, Krešimir; Gajski, Domagoj; Vukelić, Petar; Sasso, Antun

2014-12-01

In daily practice, neuroimaging studies are frequently performed for the management of childhood headache. The aim of this study was to determine whether there is significant discrepancy between clinical practice and clinical practice guidelines on the indications for neuroimaging studies. Medical records of children with chronic headache, aged 2 to 18 years and treated at Rijeka University Hospital Center, Kantrida Department of Pediatrics, were retrospectively reviewed. Indications for brain magnetic resonance imaging and computed tomography (MRI/CT) scanning were reviewed and compared with clinical practice guidelines. Brain imaging was performed in 164 (76.3%) of 215 children, MRI in 93 (56.7%) and CT in 71 (43.3%) children. Indications for brain MRI/CT were as follows: anxiety and/or insistence by the child's family (71.3%), presence of associated features suggesting neurologic dysfunction (13.4%), age under 5 years (12.8%) and abnormal neurologic examination (2.4%). The majority of children (71.4%) had normal neuroimaging findings. In the rest of imaging studies (28.1%), MRI/CT revealed different intracerebral/extracerebral findings not influencing changes in headache management. Only one (0.60%) patient required change in headache management after MRI/CT. Study results proved that, despite available evidence-based clinical guidelines, brain imaging in children with chronic headaches is overused, mostly in order to decrease anxiety of the family/patient.

Influenza-associated Encephalitis/Encephalopathy Identified by the Australian Childhood Encephalitis Study 2013-2015.

PubMed

Britton, Philip N; Dale, Russell C; Blyth, Christopher C; Macartney, Kristine; Crawford, Nigel W; Marshall, Helen; Clark, Julia E; Elliott, Elizabeth J; Webster, Richard I; Cheng, Allen C; Booy, Robert; Jones, Cheryl A

2017-11-01

Influenza-associated encephalitis/encephalopathy (IAE) is an important cause of acute encephalitis syndrome in children. IAE includes a series of clinicoradiologic syndromes or acute encephalopathy syndromes that have been infrequently reported outside East Asia. We aimed to describe cases of IAE identified by the Australian Childhood Encephalitis study. Children ≤ 14 years of age with suspected encephalitis were prospectively identified in 5 hospitals in Australia. Demographic, clinical, laboratory, imaging, and outcome at discharge data were reviewed by an expert panel and cases were categorized by using predetermined case definitions. We extracted cases associated with laboratory identification of influenza virus for this analysis; among these cases, specific IAE syndromes were identified where clinical and radiologic features were consistent with descriptions in the published literature. We identified 13 cases of IAE during 3 southern hemisphere influenza seasons at 5 tertiary children's hospitals in Australia; 8 children with specific acute encephalopathy syndromes including: acute necrotizing encephalopathy, acute encephalopathy with biphasic seizures and late diffusion restriction, mild encephalopathy with reversible splenial lesion, and hemiconvulsion-hemiplegia syndrome. Use of influenza-specific antiviral therapy and prior influenza vaccination were infrequent. In contrast, death or significant neurologic morbidity occurred in 7 of the 13 children (54%). The conditions comprising IAE are heterogeneous with varied clinical features, magnetic resonance imaging changes, and outcomes. Overall, outcome of IAE is poor emphasizing the need for optimized prevention, early recognition, and empiric management.

[Brain Organization of the Preparation for Visual Recognition in Preadolescent Children].

PubMed

Farber, D A; Kurganskii, A V; Petrenko, N E

2015-01-01

The brain organization of the process of preparation for the perception of incomplete images fragmented to different extents. The functional connections of ventrolateral and dorsoventral cortical zones with other zones in 10-11-year-old and 11-12-year-old children were studied at three successive stages of the preparation for the perception of incomplete images. These data were compared with those obtained for adults. In order to reveal the effect of preparatory processes on the image recognition, we also analyzed the regional event-related potentials. In adults, the functional interaction between dorsolateral and ventrolateral prefrontal cortex and other cortical zones of the right hemisphere was found to be enhanced at the stage of waiting for not-yet-recognizable image, while in the left hemisphere the links became stronger shortly before the successful recognition of a stimulus. In children the stage-related changes in functional interactions are similar in both hemispheres, with peak of interaction activity.at the stage preceding the successful recognition. It was found that in 11-12-year-old children the ventrolateral cortex is involved in both preparatory stage and recognition processes to a smaller extent as compared with adults and 10-11-year-old children. At the same time, the group of 11-12-year-old children had more mature pattern of the dorsolateral cortex involvement, which provided more effective recognition of incomplete images in this group as compared with 10-11-year-old children. It is suggested that the features of the brain organization of visual recognition and preceding preparatory processes in 11-12-year-old children are caused by multidirectional effects of sex hormones on the functioning of different zones of the prefrontal cortex at early stages of sexual maturation.

Computer-aided bone age assessment for ethnically diverse older children using integrated fuzzy logic system

NASA Astrophysics Data System (ADS)

Ma, Kevin; Moin, Paymann; Zhang, Aifeng; Liu, Brent

2010-03-01

Bone Age Assessment (BAA) of children is a clinical procedure frequently performed in pediatric radiology to evaluate the stage of skeletal maturation based on the left hand x-ray radiograph. The current BAA standard in the US is using the Greulich & Pyle (G&P) Hand Atlas, which was developed fifty years ago and was only based on Caucasian population from the Midwest US. To bring the BAA procedure up-to-date with today's population, a Digital Hand Atlas (DHA) consisting of 1400 hand images of normal children of different ethnicities, age, and gender. Based on the DHA and to solve inter- and intra-observer reading discrepancies, an automatic computer-aided bone age assessment system has been developed and tested in clinical environments. The algorithm utilizes features extracted from three regions of interests: phalanges, carpal, and radius. The features are aggregated into a fuzzy logic system, which outputs the calculated bone age. The previous BAA system only uses features from phalanges and carpal, thus BAA result for children over age of 15 is less accurate. In this project, the new radius features are incorporated into the overall BAA system. The bone age results, calculated from the new fuzzy logic system, are compared against radiologists' readings based on G&P atlas, and exhibits an improvement in reading accuracy for older children.

Alteration in the number and integrity of white matter tracts in the preterm: A quantitative diffusion tensor imaging and diffusion fibre tractography in children

PubMed Central

Sreedharan, Ruma M; Aiyappan, Subramonium; Roy, N

2017-01-01

Purpose: Periventricular white matter is most commonly injured in preterm babies with hypoxia. To assess white matter damage, we decided to perform diffusion tensor imaging (DTI) in preterm children with history of hypoxia and magnetic resonance imaging (MRI) features of periventricular leukomalacia (PVL) (PTH). We hypothesized that the PTH have reduced number of white matter fibres compared to age matched pre term children without hypoxia (PTHO), and also depending on the severity of PVL, there could be reduction in the number of fibres as well. Materials and Methods: The present study was carried out at the Government Medical College, Thiruvananthapuram. DTI was performed on 15 PTH and 15 PTHO. We measured number of fibres and fractional anisotropy of corpus callosum (CC) and optic radiations (OR). Results: There was significant difference between two groups with regard OR (P < 0.001). The mean number of OR fibres in cases and control was 104 ± 28.44 (mean ± SD) and 578 ± 286 (mean ± SD), respectively. The mean number of CC in cases was 953 ± 429 and in controls was 1625 ± 116 with a P value <0.56. No significant difference in FA was seen between cases and controls (P = 0.94). Conclusions: Preterm children with history of hypoxia and MRI features of PVL show reduced number of CC and OR compared to preterm children without hypoxia. There was significant correlation between PVL severity and number of OR fibres which could be due to the preferential involvement of periventricular white matter, in which OR has a major contribution. PMID:28744069

Fast content-based image retrieval using dynamic cluster tree

NASA Astrophysics Data System (ADS)

Chen, Jinyan; Sun, Jizhou; Wu, Rongteng; Zhang, Yaping

2008-03-01

A novel content-based image retrieval data structure is developed in present work. It can improve the searching efficiency significantly. All images are organized into a tree, in which every node is comprised of images with similar features. Images in a children node have more similarity (less variance) within themselves in relative to its parent. It means that every node is a cluster and each of its children nodes is a sub-cluster. Information contained in a node includes not only the number of images, but also the center and the variance of these images. Upon the addition of new images, the tree structure is capable of dynamically changing to ensure the minimization of total variance of the tree. Subsequently, a heuristic method has been designed to retrieve the information from this tree. Given a sample image, the probability of a tree node that contains the similar images is computed using the center of the node and its variance. If the probability is higher than a certain threshold, this node will be recursively checked to locate the similar images. So will its children nodes if their probability is also higher than that threshold. If no sufficient similar images were founded, a reduced threshold value would be adopted to initiate a new seeking from the root node. The search terminates when it found sufficient similar images or the threshold value is too low to give meaningful sense. Experiments have shown that the proposed dynamic cluster tree is able to improve the searching efficiency notably.

Less is More: How manipulative features affect children’s learning from picture books

PubMed Central

Tare, Medha; Chiong, Cynthia; Ganea, Patricia; DeLoache, Judy

2010-01-01

Picture books are ubiquitous in young children’s lives and are assumed to support children’s acquisition of information about the world. Given their importance, relatively little research has directly examined children’s learning from picture books. We report two studies examining children’s acquisition of labels and facts from picture books that vary on two dimensions: iconicity of the pictures and presence of manipulative features (or “pop-ups”). In Study 1, 20-month-old children generalized novel labels less well when taught from a book with manipulative features than from standard picture books without such elements. In Study 2, 30- and 36-month-old children learned fewer facts when taught from a manipulative picture book with drawings than from a standard picture book with realistic images and no manipulative features. The results of the two studies indicate that children’s learning from picture books is facilitated by realistic illustrations, but impeded by manipulative features. PMID:20948970

[A comparative analysis of anti-N-methyl-D-aspartate receptor encephalitis with or without abnormal findings on cranial magnetic resonance imaging].

PubMed

Zhang, Jian-Zhao; Chen, Qian; Zheng, Ping; Xie, Li-Na; Yi, Xiao-Li; Ren, Hai-Tao; Yang, Jian

2018-01-01

To investigate the clinical features of children with anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis with normal or abnormal cranial magnetic resonance imaging (MRI) findings via a comparative analysis. A retrospective analysis was performed for the clinical data of 33 children with anti-NMDAR encephalitis. The clinical features and prognosis were compared between the children with normal and abnormal cranial MRI findings. In the 33 children with anti-NMDAR encephalitis, the most common initial symptoms were seizures (61%) and involuntary movement (61%), followed by language disorder (54%), mental and behavioral abnormalities (52%), and disturbance of consciousness (30%). All children had positive anti-NMDAR antibody in the cerebrospinal fluid, and 29 children (88%) had positive serum antibody. Of all the children, 15 (46%) had increased leukocytes in the cerebrospinal fluid, 3 (9%) had an increase in protein, and 29 (88%) had positive oligoclonal band; 26 children (79%) had electroencephalographic abnormalities (epileptic wave, slow wave, or a combination of these two types of waves). One child experienced respiratory failure. One child was found to have germinoma in the sellar region during follow-up. Of all the 33 children, 13 (39%) had abnormal cranial MRI findings, with hypointensity or isointensity on T1W1 and hyperintensity on T2WI and T2-FLAIR; 2 children had dural enhancement. As for the location of lesion, 5 children (38%) had lesions in the temporal lobe, 3 (23%) in the frontal lobe, 3 (23%) in the basal ganglia, 2 (15%) in the parietal lobe, 2 (15%) in the occipital lobe, 2 (15%) in the brainstem, 1 (8%) in the thalamus, and 1 (8%) in the cerebellum. Among the 13 children with abnormal cranial MRI findings, 5 (38%) had lesions mainly in the grey matter and 8 (62%) had lesions mainly in the white matter. Compared with the children with normal cranial MRI findings, the children with abnormal cranial MRI findings had significantly higher proportion of children with prodromal infection, incidence rate of disturbance of consciousness, probability of recurrence, Glasgow score, incidence rate of increased leukocytes in the cerebrospinal fluid, and application rate of second-line treatment (P<0.05). Children with anti-NMDAR encephalitis and abnormal cranial MRI findings have certain clinical features, which may provide guidance for the evaluation of disease conditions and the selection of diagnostic and treatment measures.

A small pons as a characteristic finding in Down syndrome: A quantitative MRI study.

PubMed

Fujii, Yuta; Aida, Noriko; Niwa, Tetsu; Enokizono, Mikako; Nozawa, Kumiko; Inoue, Tomio

2017-04-01

Down syndrome (DS) is the most common chromosomal aberration, but the characteristics of the brainstem component in this condition during childhood (from newborn to preteen stages) have not been clarified. To evaluate the morphological features of the brainstem in DS on magnetic resonance imaging (MRI). MRIs for 32 children with DS (16 boys and girls each; age range, 0-11years) without major brain insults, and 32 age-matched controls (16 boys and girls each) were retrospectively analyzed. Height, width, and area of the midbrain, pons, and medulla oblongata were measured on sagittal T1-weighted images; these were compared in children with DS and age-matched controls. The ratios of the brainstem to the size of the posterior fossa (BS/PF index) were calculated; these were also compared in the children with DS and the control group. The width and area of the midbrain; height, width, area of the pons; and area of the medulla oblongata were significantly smaller in children with DS than in control children (P<0.05); the area of the pons, particularly for the ventral part, showed the largest differences in the mean relative differences. The BS/PF indices of the height, width, and area of the pons were significantly smaller in children with DS than in the control group (P<0.01). However, the BS/PF indices for the midbrain and the medulla oblongata did not differ between these two groups. Children with DS may have small brainstems, particularly in the pons; this may be a characteristic morphological feature of the brainstem on MRI in childhood including neonates. Copyright © 2016 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

Pediatric lymphangiectasia: an imaging spectrum.

PubMed

Malone, Ladonna J; Fenton, Laura Z; Weinman, Jason P; Anagnost, Miran R; Browne, Lorna P

2015-04-01

Lymphangiectasia is a rarely encountered lymphatic dysplasia characterized by lymphatic dilation without proliferation. Although it can occur anywhere, the most common locations are the central conducting lymphatics and the pulmonary and intestinal lymphatic networks. Recent advances in lymphatic interventions have resulted in an increased reliance on imaging to characterize patterns of disease. To describe the patient populations, underlying conditions, and imaging features of lymphangiectasia encountered at a tertiary pediatric institution over a 10-year period and correlate these with pathology and patient outcomes. We retrospectively reviewed the pathology database from 2002 to 2012 to identify patients with pathologically or surgically proven lymphangiectasia who had undergone cross-sectional imaging. Medical records were reviewed for patient demographics, underlying conditions, treatment and outcome. Thirteen children were identified, ranging in age from 1 month to 16 years. Five had pulmonary lymphangiectasia, four intestinal and four diffuse involvement. Pulmonary imaging findings include diffuse or segmental interlobular septal thickening, pleural effusions and dilated mediastinal lymphatics. Intestinal imaging findings include focal or diffuse bowel wall thickening with central lymphatic dilation. Diffuse involvement included dilation of the central lymphatics and involvement of more than one organ system. Children with infantile presentation and diffuse pulmonary, intestinal or diffuse lymphatic abnormalities had a high mortality rate. Children with later presentations and segmental involvement demonstrated clinical improvement with occasional regression of disease. Three children with dilated central lymphatics on imaging underwent successful lymphatic duct ligation procedures with improved clinical course. Lymphangiectasia is a complex disorder with a spectrum of presentations, imaging appearances, treatments and outcomes. Cross-sectional imaging techniques distinguish segmental involvement of a single system (pulmonary or intestinal) from diffuse disease and may show dilated central conducting lymphatics, which may benefit from interventions such as ligation or occlusion.

Interactive stereo games to improve vision in children with amblyopia using dichoptic stimulation

NASA Astrophysics Data System (ADS)

Herbison, Nicola; Ash, Isabel M.; MacKeith, Daisy; Vivian, Anthony; Purdy, Jonathan H.; Fakis, Apostolos; Cobb, Sue V.; Hepburn, Trish; Eastgate, Richard M.; Gregson, Richard M.; Foss, Alexander J. E.

2015-03-01

Amblyopia is a common condition affecting 2% of all children and traditional treatment consists of either wearing a patch or penalisation. We have developed a treatment using stereo technology, not to provide a 3D image but to allow dichoptic stimulation. This involves presenting an image with the same background to both eyes but with features of interest removed from the image presented to the normal eye with the aim to preferentially stimulated visual development in the amblyopic, or lazy, eye. Our system, called I-BiT can use either a game or a video (DVD) source as input. Pilot studies show that this treatment is effective with short treatment times and has proceeded to randomised controlled clinical trial. The early indications are that the treatment has a high degree of acceptability and corresponding good compliance.

Skeletal age assessment in children using an open compact MRI system.

PubMed

Terada, Yasuhiko; Kono, Saki; Tamada, Daiki; Uchiumi, Tomomi; Kose, Katsumi; Miyagi, Ryo; Yamabe, Eiko; Yoshioka, Hiroshi

2013-06-01

MRI may be a noninvasive and alternative tool for skeletal age assessment in children, although few studies have reported on this topic. In this article, skeletal age was assessed over a wide range of ages using an open, compact MRI optimized for the imaging of a child's hand and wrist, and its validity was evaluated. MR images and their three-dimensional segmentation visualized detailed skeletal features of each bone in the hand and wrist. Skeletal age was then independently scored from the MR images by two raters, according to the Tanner-Whitehouse Japan system. The skeletal age assessed by MR rating demonstrated a strong positive correlation with chronological age. The intrarater and inter-rater reproducibilities were significantly high. These results demonstrate the validity and reliability of skeletal age assessment using MRI. Copyright © 2012 Wiley Periodicals, Inc.

Stereoscopic augmented reality using ultrasound volume rendering for laparoscopic surgery in children

NASA Astrophysics Data System (ADS)

Oh, Jihun; Kang, Xin; Wilson, Emmanuel; Peters, Craig A.; Kane, Timothy D.; Shekhar, Raj

2014-03-01

In laparoscopic surgery, live video provides visualization of the exposed organ surfaces in the surgical field, but is unable to show internal structures beneath those surfaces. The laparoscopic ultrasound is often used to visualize the internal structures, but its use is limited to intermittent confirmation because of the need for an extra hand to maneuver the ultrasound probe. Other limitations of using ultrasound are the difficulty of interpretation and the need for an extra port. The size of the ultrasound transducer may also be too large for its usage in small children. In this paper, we report on an augmented reality (AR) visualization system that features continuous hands-free volumetric ultrasound scanning of the surgical anatomy and video imaging from a stereoscopic laparoscope. The acquisition of volumetric ultrasound image is realized by precisely controlling a back-and-forth movement of an ultrasound transducer mounted on a linear slider. Furthermore, the ultrasound volume is refreshed several times per minute. This scanner will sit outside of the body in the envisioned use scenario and could be even integrated into the operating table. An overlay of the maximum intensity projection (MIP) of ultrasound volume on the laparoscopic stereo video through geometric transformations features an AR visualization system particularly suitable for children, because ultrasound is radiation-free and provides higher-quality images in small patients. The proposed AR representation promises to be better than the AR representation using ultrasound slice data.

Unusual presentation of a skull base mass lesion in sarcoidosis mimicking malignant neoplasm: a case report.

PubMed

Shijo, Katsunori; Moro, Nobuhiro; Sasano, Mari; Watanabe, Mitsuru; Yagasaki, Hiroshi; Takahashi, Shori; Homma, Taku; Yoshino, Atsuo

2018-05-29

Sarcoidosis is a multi-organ disease of unknown etiology characterised by the presence of epithelioid granulomas, without caseous necrosis. Systemic sarcoidosis is rare among children, while neurosarcoidosis in children is even rarer whether it is systemic or not. We described the case of a 12-year-old boy who presented with monocular vision loss accompanied by unusual MRI features of an extensive meningeal infiltrating mass lesion. The patient underwent surgical resection (biopsy) via a frontotemporal craniotomy to establish a definitive diagnosis based on the histopathology, since neurosarcoidosis remains a very difficult diagnosis to establish from neuroradiogenic imagings. Based on the histopathology of the resected mass lesion, neurosarcoidosis was diagnosed. On follow-up after 3 months of steroid therapy, the patient displayed a good response on the imaging studies. MRI revealed that the preexisting mass lesion had regressed extremely. We also conducted a small literature review on imaging studies, manifestations, appropriate treatments, etc., in particular neurosarcoidosis including children. Although extremely rare, neurosarcoidosis, even in children, should be considered in the differential diagnosis of skull base mass lesions to avoid unnecessary aggressive surgery and delay in treatment, since surgery may have little role in the treatment of sarcoidosis.

SU-E-I-68: Practical Considerations On Implementation of the Image Gently Pediatric CT Protocols

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

Zhang, J; Adams, C; Lumby, C

Purpose: One limitation associated with the Image Gently pediatric CT protocols is practical implementation of the recommended manual techniques. Inconsistency as a result of different practice is a possibility among technologist. An additional concern is the added risk of data error that would result in over or underexposure. The Automatic Exposure Control (AEC) features automatically reduce radiation for children. However, they do not work efficiently for the patients of very small size and relative large size. This study aims to implement the Image Gently pediatric CT protocols in the practical setting while maintaining the use of AEC features for pediatricmore » patients of varying size. Methods: Anthropomorphological abdomen phantoms were scanned in a CT scanner using the Image Gently pediatric protocols, the AEC technique with a fixed adult baseline, and automatic protocols with various baselines. The baselines were adjusted corresponding to patient age, weight and posterioranterior thickness to match the Image Gently pediatric CT manual techniques. CTDIvol was recorded for each examination. Image noise was measured and recorded for image quality comparison. Clinical images were evaluated by pediatric radiologists. Results: By adjusting vendor default baselines used in the automatic techniques, radiation dose and image quality can match those of the Image Gently manual techniques. In practice, this can be achieved by dividing pediatric patients into three major groups for technologist reference: infant, small child, and large child. Further division can be done but will increase the number of CT protocols. For each group, AEC can efficiently adjust acquisition techniques for children. This implementation significantly overcomes the limitation of the Image Gently manual techniques. Conclusion: Considering the effectiveness in clinical practice, Image Gently Pediatric CT protocols can be implemented in accordance with AEC techniques, with adjusted baselines, to achieve the goal of providing the most appropriate radiation dose for pediatric patients of varying sizes.« less

HIV-associated salivary gland disease--clinical or imaging diagnosis?

PubMed

da Silva Rath, Inês Beatriz; Beltrame, Ana Paula C A; Carvalho, Aroldo P; Schaeffer, Marcela B; Almeida, Izabel C S

2015-07-01

This work aimed at studying the salivary gland disease (SGD) as it relates to associated factors, such as persistent generalised lymphadenopathy (PGL), lymphocytic interstitial pneumonia (LIP), clinical and immunological features of AIDS, and salivary flow rate and pH, as well as at exploring the relationship between the clinical diagnosis and the imaging diagnosis by ultrasound (US) examination of the parotid glands. Information regarding the observation of parotid gland enlargement, PGL, LIP, and clinical and immunological features of AIDS was gathered from medical records, and a saliva sample for unstimulated salivary flow rate and pH measurement was collected from 142 children aged 3 through 10 years treated at the Department of Infectious Diseases of Joana de Gusmão Children's Hospital, Florianópolis, SC, Brazil. High-resolution ultrasonography was performed in 58 children. Pearson's chi-square test and t-test were used to evaluate the association between the variables. A significant association was found between SGD and LIP. Ultrasound revealed a 50% higher incidence of SGD that was not reported in the patients' records. US examination proved to be essential for the correct diagnosis and monitoring of the progression of HIV/SGD. © 2014 BSPD, IAPD and John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Dwarfism with gloomy face: a new syndrome with features of 3-M syndrome.

PubMed Central

Le Merrer, M; Brauner, R; Maroteaux, P

1991-01-01

Nine children with primordial dwarfism are described and a new syndrome is delineated. The significant features of this syndrome include facial dysmorphism with gloomy face and very short stature, but no radiological abnormality or hormone deficiency. Mental development is normal. The mode of inheritance seems to be autosomal recessive because of consanguinity in three of the four sibships. Some overlap with the 3-M syndrome is discussed but the autonomy of the gloomy face syndrome seems to be real. Images PMID:2051454

Automated diagnosis of fetal alcohol syndrome using 3D facial image analysis

PubMed Central

Fang, Shiaofen; McLaughlin, Jason; Fang, Jiandong; Huang, Jeffrey; Autti-Rämö, Ilona; Fagerlund, Åse; Jacobson, Sandra W.; Robinson, Luther K.; Hoyme, H. Eugene; Mattson, Sarah N.; Riley, Edward; Zhou, Feng; Ward, Richard; Moore, Elizabeth S.; Foroud, Tatiana

2012-01-01

Objectives Use three-dimensional (3D) facial laser scanned images from children with fetal alcohol syndrome (FAS) and controls to develop an automated diagnosis technique that can reliably and accurately identify individuals prenatally exposed to alcohol. Methods A detailed dysmorphology evaluation, history of prenatal alcohol exposure, and 3D facial laser scans were obtained from 149 individuals (86 FAS; 63 Control) recruited from two study sites (Cape Town, South Africa and Helsinki, Finland). Computer graphics, machine learning, and pattern recognition techniques were used to automatically identify a set of facial features that best discriminated individuals with FAS from controls in each sample. Results An automated feature detection and analysis technique was developed and applied to the two study populations. A unique set of facial regions and features were identified for each population that accurately discriminated FAS and control faces without any human intervention. Conclusion Our results demonstrate that computer algorithms can be used to automatically detect facial features that can discriminate FAS and control faces. PMID:18713153

Curved reformat of the paediatric brain MRI into a 'flat-earth map' - standardised method for demonstrating cortical surface atrophy resulting from hypoxic-ischaemic encephalopathy.

PubMed

Simpson, Ewan; Andronikou, Savvas; Vedajallam, Schadie; Chacko, Anith; Thai, Ngoc Jade

2016-09-01

Hypoxic-ischaemic encephalopathy is optimally imaged with brain MRI in the neonatal period. However neuroimaging is often also performed later in childhood (e.g., when parents seek compensation in cases of alleged birth asphyxia). We describe a standardised technique for creating two curved reconstructions of the cortical surface to show the characteristic surface changes of hypoxic-ischaemic encephalopathy in children imaged after the neonatal period. The technique was applied for 10 cases of hypoxic-ischaemic encephalopathy and also for age-matched healthy children to assess the visibility of characteristic features of hypoxic-ischaemic encephalopathy. In the abnormal brains, fissural or sulcal widening was seen in all cases and ulegyria was identifiable in 7/10. These images could be used as a visual aid for communicating MRI findings to clinicians and other interested parties.

Automated scoring of regional lung perfusion in children from contrast enhanced 3D MRI

NASA Astrophysics Data System (ADS)

Heimann, Tobias; Eichinger, Monika; Bauman, Grzegorz; Bischoff, Arved; Puderbach, Michael; Meinzer, Hans-Peter

2012-03-01

MRI perfusion images give information about regional lung function and can be used to detect pulmonary pathologies in cystic fibrosis (CF) children. However, manual assessment of the percentage of pathologic tissue in defined lung subvolumes features large inter- and intra-observer variation, making it difficult to determine disease progression consistently. We present an automated method to calculate a regional score for this purpose. First, lungs are located based on thresholding and morphological operations. Second, statistical shape models of left and right children's lungs are initialized at the determined locations and used to precisely segment morphological images. Segmentation results are transferred to perfusion maps and employed as masks to calculate perfusion statistics. An automated threshold to determine pathologic tissue is calculated and used to determine accurate regional scores. We evaluated the method on 10 MRI images and achieved an average surface distance of less than 1.5 mm compared to manual reference segmentations. Pathologic tissue was detected correctly in 9 cases. The approach seems suitable for detecting early signs of CF and monitoring response to therapy.

Atypical Activations of Fronto-Cerebellar Regions During Forethought in Parents of Children With ADHD.

PubMed

Rapin, Lucile; Poissant, Hélène; Mendrek, Adrianna

2017-10-01

Although several studies suggest heritability of ADHD, only a few investigations of possible associations between people at risk and neural abnormalities in ADHD exist. In this study, we tested whether parents of children with ADHD would show atypical patterns of cerebral activations during forethought, a feature of working memory. Using Functional Magnetic Resonance Imaging (fMRI), we compared 12 parents of children with ADHD and 9 parents of control children during a forethought task. Parents of children with ADHD exhibited significantly increased neural activations in the posterior lobes of the cerebellum and in the left inferior frontal gyrus, relative to parents of control children. These findings are consistent with previous reports in children and suggest the fronto-cerebellar circuit's abnormalities during forethought in parents of children with ADHD. Future studies of people at risk of ADHD are needed to fully understand the extent of the fronto-cerebellar heritability.

Acute pediatric encephalitis neuroimaging: single-institution series as part of the California encephalitis project.

PubMed

Bykowski, Julie; Kruk, Peter; Gold, Jeffrey J; Glaser, Carol A; Sheriff, Heather; Crawford, John R

2015-06-01

Diagnosing pediatric encephalitis is challenging because of varied clinical presentation, nonspecific neuroimaging features, and rare confirmation of causality. We reviewed acute neuroimaging of children with clinically suspected encephalitis to identify findings that may correlate with etiology and length of stay. Imaging of 141 children with clinically suspected encephalitis as part of The California Encephalitis Project from 2005 to 2012 at a single institution was reviewed to compare the extent of neuroimaging abnormalities to patient age, gender, length of stay, and unknown, possible, or confirmed pathogen. Scan review was blinded and categorized by extent and distribution of abnormal findings. Abnormal findings were evident on 23% (22/94) of computed tomography and 50% (67/134) of magnetic resonance imaging studies in the acute setting. Twenty children with normal admission computed tomography had abnormal findings on magnetic resonance imaging performed within 2 days. Length of stay was significantly longer among children with abnormal acute magnetic resonance imaging (P < 0.001) and correlated with increased complexity (Spearman rho = 0.4, P < 0.001) categorized as: no imaging abnormality, meningeal enhancement and/or focal nonenhancing lesion, multifocal lesions, confluent lesions, and lesions plus diffusion restriction, hemorrhage, or hydrocephalus. There was no correlation between neuroimaging findings and an identifiable pathogen (P = 0.8). Abnormal magnetic resonance imaging findings are more common than abnormal computed tomography findings in pediatric encephalitis. Increasing complexity of magnetic resonance imaging findings correlated with disease severity as evidenced by longer length of stay, but were not specific for an identifiable pathogen using a standardized diagnostic encephalitis panel. Copyright © 2015 Elsevier Inc. All rights reserved.

Guanidinoacetate Methyltransferase (GAMT) Deficiency: Late Onset of Movement Disorder and Preserved Expressive Language

ERIC Educational Resources Information Center

O'Rourke, Declan J.; Ryan, Stephanie; Salomons, Gajja; Jakobs, Cornelis; Monavari, Ahmad; King, Mary D.

2009-01-01

Guanidinoacetate methyltransferase (GAMT) deficiency is a disorder of creatine biosynthesis, characterized by early-onset learning disability and epilepsy in most affected children. Severe expressive language delay is a constant feature even in the mildest clinical phenotypes. We report the clinical, biochemical, imaging, and treatment data of two…

Cortical Gray Matter in Attention-Deficit/Hyperactivity Disorder: A Structural Magnetic Resonance Imaging Study

ERIC Educational Resources Information Center

Batty, Martin J.; Liddle, Elizabeth B.; Pitiot, Alain; Toro, Roberto; Groom, Madeleine J.; Scerif, Gaia; Liotti, Mario; Liddle, Peter F.; Paus, Tomas; Hollis, Chris

2010-01-01

Objective: Previous studies have shown smaller brain volume and less gray matter in children with attention-deficit/hyperactivity disorder (ADHD). Relatively few morphological studies have examined structures thought to subserve inhibitory control, one of the diagnostic features of ADHD. We examined one such region, the pars opercularis,…

MR Image Analytics to Characterize the Upper Airway Structure in Obese Children with Obstructive Sleep Apnea Syndrome

PubMed Central

Tong, Yubing; Udupa, Jayaram K.; Sin, Sanghun; Liu, Zhengbing; Wileyto, E. Paul; Torigian, Drew A.; Arens, Raanan

2016-01-01

Purpose Quantitative image analysis in previous research in obstructive sleep apnea syndrome (OSAS) has focused on the upper airway or several objects in its immediate vicinity and measures of object size. In this paper, we take a more general approach of considering all major objects in the upper airway region and measures pertaining to their individual morphological properties, their tissue characteristics revealed by image intensities, and the 3D architecture of the object assembly. We propose a novel methodology to select a small set of salient features from this large collection of measures and demonstrate the ability of these features to discriminate with very high prediction accuracy between obese OSAS and obese non-OSAS groups. Materials and Methods Thirty children were involved in this study with 15 in the obese OSAS group with an apnea-hypopnea index (AHI) = 14.4 ± 10.7) and 15 in the obese non-OSAS group with an AHI = 1.0 ± 1.0 (p<0.001). Subjects were between 8–17 years and underwent T1- and T2-weighted magnetic resonance imaging (MRI) of the upper airway during wakefulness. Fourteen objects in the vicinity of the upper airways were segmented in these images and a total of 159 measurements were derived from each subject image which included object size, surface area, volume, sphericity, standardized T2-weighted image intensity value, and inter-object distances. A small set of discriminating features was identified from this set in several steps. First, a subset of measures that have a low level of correlation among the measures was determined. A heat map visualization technique that allows grouping of parameters based on correlations among them was used for this purpose. Then, through T-tests, another subset of measures which are capable of separating the two groups was identified. The intersection of these subsets yielded the final feature set. The accuracy of these features to perform classification of unseen images into the two patient groups was tested by using logistic regression and multi-fold cross validation. Results A set of 16 features identified with low inter-feature correlation (< 0.36) yielded a high classification accuracy of 96% with sensitivity and specificity of 97.8% and 94.4%, respectively. In addition to the previously observed increase in linear size, surface area, and volume of adenoid, tonsils, and fat pad in OSAS, the following new markers have been found. Standardized T2-weighted image intensities differed between the two groups for the entire neck body region, pharynx, and nasopharynx, possibly indicating changes in object tissue characteristics. Fat pad and oropharynx become less round or more complex in shape in OSAS. Fat pad and tongue move closer in OSAS, and so also oropharynx and tonsils and fat pad and tonsils. In contrast, fat pad and oropharynx move farther apart from the skin object. Conclusions The study has found several new anatomic bio-markers of OSAS. Changes in standardized T2-weighted image intensities in objects may imply that intrinsic tissue composition undergoes changes in OSAS. The results on inter-object distances imply that treatment methods should respect the relationships that exist among objects and not just their size. The proposed method of analysis may lead to an improved understanding of the mechanisms underlying OSAS. PMID:27487240

Evaluation Children with Global Developmental Delay: A Prospective Study at Sultan Qaboos University Hospital, Oman

PubMed Central

Koul, Roshan; Al-Yahmedy, Mohammed; Al-Futaisi, Amna

2012-01-01

Objective A prospective study was designed to analyze risk factors and clinical features in children with global developmental delay (GDD) at our hospital. No previous data is available on GDD from Oman. Methods This study was conducted at Sultan Qaboos University Hospital from January 2008 until June 2009. All the children aged 5 years or less, referred with suspected GDD were included in the study. Data was analyzed to determine the underlying etiology. The children with neurodegenerative disease and muscular dystrophy were excluded from the study. Results One hundred and ten children, 59 males (53.6%) and 51 females (46.4%) were included in the study. The mean age at initial evaluation was 13.29 months. An underlying etiology was determined in 79 (71.8%) children. Perinatal history was associated with significant difference in detection of etiology (p=0.039). Abnormal neurological examination was a significant factor in detection of the underlying etiology. Magnetic resonance imaging (MRI) in 105 children and metabolic screening in 93 children were the most frequently ordered investigations. Abnormal imaging, MRI (p=0.001), CT scan (p=0.036) and metabolic screening (p=0.034) were significantly associated with detection of etiology. Conclusion Etiology was detected in 71.8% of the children. MRI was the most significant investigation to detect the abnormality. PMID:23071884

Medulloblastoma with Atypical Dynamic Imaging Changes: Case Report with Literature Review.

PubMed

Song, Shuang-Shuang; Wang, Jian-Hong; Fu, Wei-Wei; Li, Ying; Sui, Qing-Lan; Liu, Xue-Jun

2017-09-01

We analyzed a case of medulloblastoma with atypical dynamic imaging changes retrospectively to summarize the atypical magnetic resonance imaging (MRI) features of medulloblastoma by reviewing the literature. An atypical case of medulloblastoma in the cerebellar hemisphere confirmed by pathology was analyzed retrospectively, and the literature about it was reviewed. The radiologic findings of the patient were based on 3 examinations. The first examination showed that the cortex of the bilateral cerebellar hemisphere had diffuse nodular thickening, with a high signal on diffusion-weighted imaging and significant enhancement. Contrast enhancement MRI 1 year later showed the signal of cerebellar hemisphere returned to normal but revealed an enhanced nodule. A reexamination 6 months later showed an irregular mass with a high-density shadow in the cerebellar vermis on CT scan. The T2-weighted image revealed multiple degenerative cysts, and the mass had significant enhancement. The radiologic characteristics of atypical medulloblastomas vary in adults and children. Understanding the radiologic characteristics of medulloblastomas, such as MRI features, age of onset, and location of atypical medulloblastomas, can help improve the diagnosis of medulloblastomas. Copyright © 2017. Published by Elsevier Inc.

A Statistical Skull Geometry Model for Children 0-3 Years Old

PubMed Central

Li, Zhigang; Park, Byoung-Keon; Liu, Weiguo; Zhang, Jinhuan; Reed, Matthew P.; Rupp, Jonathan D.; Hoff, Carrie N.; Hu, Jingwen

2015-01-01

Head injury is the leading cause of fatality and long-term disability for children. Pediatric heads change rapidly in both size and shape during growth, especially for children under 3 years old (YO). To accurately assess the head injury risks for children, it is necessary to understand the geometry of the pediatric head and how morphologic features influence injury causation within the 0–3 YO population. In this study, head CT scans from fifty-six 0–3 YO children were used to develop a statistical model of pediatric skull geometry. Geometric features important for injury prediction, including skull size and shape, skull thickness and suture width, along with their variations among the sample population, were quantified through a series of image and statistical analyses. The size and shape of the pediatric skull change significantly with age and head circumference. The skull thickness and suture width vary with age, head circumference and location, which will have important effects on skull stiffness and injury prediction. The statistical geometry model developed in this study can provide a geometrical basis for future development of child anthropomorphic test devices and pediatric head finite element models. PMID:25992998

A statistical skull geometry model for children 0-3 years old.

PubMed

Li, Zhigang; Park, Byoung-Keon; Liu, Weiguo; Zhang, Jinhuan; Reed, Matthew P; Rupp, Jonathan D; Hoff, Carrie N; Hu, Jingwen

2015-01-01

Head injury is the leading cause of fatality and long-term disability for children. Pediatric heads change rapidly in both size and shape during growth, especially for children under 3 years old (YO). To accurately assess the head injury risks for children, it is necessary to understand the geometry of the pediatric head and how morphologic features influence injury causation within the 0-3 YO population. In this study, head CT scans from fifty-six 0-3 YO children were used to develop a statistical model of pediatric skull geometry. Geometric features important for injury prediction, including skull size and shape, skull thickness and suture width, along with their variations among the sample population, were quantified through a series of image and statistical analyses. The size and shape of the pediatric skull change significantly with age and head circumference. The skull thickness and suture width vary with age, head circumference and location, which will have important effects on skull stiffness and injury prediction. The statistical geometry model developed in this study can provide a geometrical basis for future development of child anthropomorphic test devices and pediatric head finite element models.

An advanced design of non-radioactive image capturing and management system for applications in non-invasive skin disorder diagnosis

NASA Astrophysics Data System (ADS)

Liu, Carol Y. B.; Luk, David C. K.; Zhou, Kany S. Y.; So, Bryan M. K.; Louie, Derek C. H.

2015-03-01

Due to the increasing incidences of malignant melanoma, there is a rising demand for assistive technologies for its early diagnosis and improving the survival rate. The commonly used visual screening method is with limited accuracy as the early phase of melanoma shares many clinical features with an atypical nevus, while conventional dermoscopes are not user-friendly in terms of setup time and operations. Therefore, the development of an intelligent and handy system to assist the accurate screening and long-term monitoring of melanocytic skin lesions is crucial for early diagnosis and prevention of melanoma. In this paper, an advanced design of non-invasive and non-radioactive dermoscopy system was reported. Computer-aided simulations were conducted for optimizing the optical design and uniform illumination distribution. Functional prototype and the software system were further developed, which could enable image capturing at 10x amplified and general modes, convenient data transmission, analysis of dermoscopic features (e.g., asymmetry, border irregularity, color, diameter and dermoscopic structure) for assisting the early detection of melanoma, extract patient information (e.g. code, lesion location) and integrate with dermoscopic images, thus further support long term monitoring of diagnostic analysis results. A clinical trial study was further conducted on 185 Chinese children (0-18 years old). The results showed that for all subjects, skin conditions diagnosed based on the developed system accurately confirmed the diagnoses by conventional clinical procedures. Besides, clinical analysis on dermoscopic features and a potential standard approach by the developed system to support identifying specific melanocytic patterns for dermoscopic examination in Chinese children were also reported.

Novel method to predict body weight in children based on age and morphological facial features.

PubMed

Huang, Ziyin; Barrett, Jeffrey S; Barrett, Kyle; Barrett, Ryan; Ng, Chee M

2015-04-01

A new and novel approach of predicting the body weight of children based on age and morphological facial features using a three-layer feed-forward artificial neural network (ANN) model is reported. The model takes in four parameters, including age-based CDC-inferred median body weight and three facial feature distances measured from digital facial images. In this study, thirty-nine volunteer subjects with age ranging from 6-18 years old and BW ranging from 18.6-96.4 kg were used for model development and validation. The final model has a mean prediction error of 0.48, a mean squared error of 18.43, and a coefficient of correlation of 0.94. The model shows significant improvement in prediction accuracy over several age-based body weight prediction methods. Combining with a facial recognition algorithm that can detect, extract and measure the facial features used in this study, mobile applications that incorporate this body weight prediction method may be developed for clinical investigations where access to scales is limited. © 2014, The American College of Clinical Pharmacology.

Extrahepatic Portal Vein Obstruction in Children: Role of Preoperative Imaging.

PubMed

Achar, Shashidhar; Dutta, Hemonta Kumar; Gogoi, Rudra Kanta

2017-01-01

Extrahepatic portal vein obstruction (EHPVO) is characterized by features of recent thrombosis or portal hypertension with portal cavernoma as a sequel of portal vein obstruction. Imaging of spleno-portal axis is the mainstay for the diagnosis of EHPVO. The aim of this study is to analyze the role of imaging in the preoperative assessment of the portal venous system in children with EHPVO. A hospital-based cross-sectional study was conducted on twenty children with EHPVO aged between 1 and 18 years over a period of 1 year. The children were evaluated clinically, followed by upper gastrointestinal endoscopy. Radiological assessment included imaging of the main portal vein, its right and left branches, splenic vein, and superior mesenteric vein using color Doppler ultrasonography (CDUSG) and magnetic resonance portovenogram (MRP). Evidence of portal biliopathy, status of collaterals, and possible sites for portosystemic shunt surgery were also examined. All the patients presented in chronic stage with portal cavernoma and only one patient (5%) had bland thrombus associated with cavernoma. The CDUSG and MRPs had a sensitivity of 66.6-90% and 96.7% and specificity of 91.5% and 98.3% respectively with regard to the assessment of the extent of thrombus formation and flow in the portal venous system. Both the modalities were found to be complementary to each other in preoperative assessment of EHPVO. However, the sensitivity of MRP was slightly superior to CDUSG in detecting occlusion and identifying portosystemic collaterals and dilated intrahepatic biliary radicals. Results of the present study indicate that MRP is well suited and superior to CDUSG in the preoperative imaging of patients with EHPVO.

Focus on the Family: New Images of Parents and Children in the 1980's.

ERIC Educational Resources Information Center

Bane, Mary Jo; And Others

The present and future of the American family are discussed in a collection of four papers. The first paper, by Mary Jo Bane, identifies trends in demographic and structural features of families, including fertility rates, marriage trends, divorce rates, household headship rates, and the proportion of women in the labor force. Societies' changing…

Metrics and textural features of MRI diffusion to improve classification of pediatric posterior fossa tumors.

PubMed

Rodriguez Gutierrez, D; Awwad, A; Meijer, L; Manita, M; Jaspan, T; Dineen, R A; Grundy, R G; Auer, D P

2014-05-01

Qualitative radiologic MR imaging review affords limited differentiation among types of pediatric posterior fossa brain tumors and cannot detect histologic or molecular subtypes, which could help to stratify treatment. This study aimed to improve current posterior fossa discrimination of histologic tumor type by using support vector machine classifiers on quantitative MR imaging features. This retrospective study included preoperative MRI in 40 children with posterior fossa tumors (17 medulloblastomas, 16 pilocytic astrocytomas, and 7 ependymomas). Shape, histogram, and textural features were computed from contrast-enhanced T2WI and T1WI and diffusivity (ADC) maps. Combinations of features were used to train tumor-type-specific classifiers for medulloblastoma, pilocytic astrocytoma, and ependymoma types in separation and as a joint posterior fossa classifier. A tumor-subtype classifier was also produced for classic medulloblastoma. The performance of different classifiers was assessed and compared by using randomly selected subsets of training and test data. ADC histogram features (25th and 75th percentiles and skewness) yielded the best classification of tumor type (on average >95.8% of medulloblastomas, >96.9% of pilocytic astrocytomas, and >94.3% of ependymomas by using 8 training samples). The resulting joint posterior fossa classifier correctly assigned >91.4% of the posterior fossa tumors. For subtype classification, 89.4% of classic medulloblastomas were correctly classified on the basis of ADC texture features extracted from the Gray-Level Co-Occurence Matrix. Support vector machine-based classifiers using ADC histogram features yielded very good discrimination among pediatric posterior fossa tumor types, and ADC textural features show promise for further subtype discrimination. These findings suggest an added diagnostic value of quantitative feature analysis of diffusion MR imaging in pediatric neuro-oncology. © 2014 by American Journal of Neuroradiology.

Using computerized games to teach face recognition skills to children with autism spectrum disorder: the Let's Face It! program.

PubMed

Tanaka, James W; Wolf, Julie M; Klaiman, Cheryl; Koenig, Kathleen; Cockburn, Jeffrey; Herlihy, Lauren; Brown, Carla; Stahl, Sherin; Kaiser, Martha D; Schultz, Robert T

2010-08-01

An emerging body of evidence indicates that relative to typically developing children, children with autism are selectively impaired in their ability to recognize facial identity. A critical question is whether face recognition skills can be enhanced through a direct training intervention. In a randomized clinical trial, children diagnosed with autism spectrum disorder were pre-screened with a battery of subtests (the Let's Face It! Skills battery) examining face and object processing abilities. Participants who were significantly impaired in their face processing abilities were assigned to either a treatment or a waitlist group. Children in the treatment group (N = 42) received 20 hours of face training with the Let's Face It! (LFI!) computer-based intervention. The LFI! program is comprised of seven interactive computer games that target the specific face impairments associated with autism, including the recognition of identity across image changes in expression, viewpoint and features, analytic and holistic face processing strategies and attention to information in the eye region. Time 1 and Time 2 performance for the treatment and waitlist groups was assessed with the Let's Face It! Skills battery. The main finding was that relative to the control group (N = 37), children in the face training group demonstrated reliable improvements in their analytic recognition of mouth features and holistic recognition of a face based on its eyes features. These results indicate that a relatively short-term intervention program can produce measurable improvements in the face recognition skills of children with autism. As a treatment for face processing deficits, the Let's Face It! program has advantages of being cost-free, adaptable to the specific learning needs of the individual child and suitable for home and school applications.

Three-Dimensional Virtual Sonographic Cystoscopy for Detection of Ureterocele in Duplicated Collecting Systems in Children.

PubMed

Nabavizadeh, Behnam; Mozafarpour, Sarah; Hosseini Sharifi, Seyed Hossein; Nabavizadeh, Reza; Abbasioun, Reza; Kajbafzadeh, Abdol-Mohammad

2018-03-01

Ureterocele is a sac-like dilatation of terminal ureter. Precise anatomic delineation is of utmost importance to proceed with the surgical plan, particularly in the ectopic subtype. However, the level of ureterocele extension is not always elucidated by the existing imaging modalities and even by conventional cystoscopy, which is considered as the gold standard for evaluation of ureterocele. This study aims to evaluate the accuracy of three-dimensional virtual sonographic cystoscopy (VSC) in the characterization of ureterocele in duplex collecting systems. Sixteen children with a mean age of 5.1 (standard deviation 1.96) years with transabdominal ultrasonography-proven duplex system and ureterocele were included. They underwent VSC by a single pediatric radiologist. All of them subsequently had conventional cystoscopy, and the results were compared in terms of ureterocele features including anatomy, number, size, location, and extension. Three-dimensional VSC was well tolerated in all cases without any complication. Image quality was suboptimal in 2 of 16 patients. Out of the remaining 14 cases, VSC had a high accuracy in characterization of the ureterocele features (93%). Only the extension of one ureterocele was not precisely detected by VSC. The results of this study suggest three-dimensional sonography as a promising noninvasive diagnostic modality in the evaluation of ectopic ureterocele in children. © 2017 by the American Institute of Ultrasound in Medicine.

Morphologic Features of the Amygdala and Hippocampus in Children and Adults With Tourette Syndrome

PubMed Central

Peterson, Bradley S.; Choi, HuiMahn A.; Hao, Xuejun; Amat, Jose A.; Zhu, Hongtu; Whiteman, Ronald; Liu, Jun; Xu, Dongrong; Bansal, Ravi

2008-01-01

Context Limbic portions of cortical-subcortical circuits are likely involved in the pathogenesis of Tourette syndrome (TS). They are anatomically, developmentally, neurochemically, and functionally related to the basal ganglia, and the basal ganglia are thought to produce the symptoms of tics, obsessive-compulsive disorder, and attention-deficit/hyperactivity disorder that commonly affect persons with TS. Objective To study the morphologic features of the hippocampus and amygdala in children and adults with TS. Design A cross-sectional, case-control study using anatomical magnetic resonance imaging. Setting University research center. Participants A total of 282 individuals (154 patients with TS and 128 controls) aged 6 to 63 years. Main Outcome Measures Volumes and measures of surface morphologic features of the hippocampus and amygdala. Results The overall volumes of the hippocampus and amygdala were significantly larger in the TS group. Surface analyses suggested that the increased volumes in the TS group derived primarily from the head and medial surface of the hippocampus (over the length of the dentate gyrus) and the dorsal and ventral surfaces of the amygdala (over its basolateral and central nuclei). Volumes of these subregions declined with age in the TS group but not in controls, so the subregions were significantly larger in children with TS but significantly smaller in adults with TS than in their control counterparts. In children and adults, volumes in these subregions correlated inversely with the severity of tic, obsessive-compulsive disorder, and attention-deficit/hyperactivity disorder symptoms, suggesting that enlargement of the subregions may have a compensatory and neuromodulatory effect on tic-related symptoms. Conclusion These findings are consistent with the known plasticity of the dentate gyrus and with findings from previous imaging studies suggesting the presence of failed compensatory plasticity in adults with TS who have not experienced the usual decline in symptoms during adolescence. PMID:17984397

In vivo cellular-resolution retinal imaging in infants and children using an ultracompact handheld probe

NASA Astrophysics Data System (ADS)

Larocca, Francesco; Nankivil, Derek; Dubose, Theodore; Toth, Cynthia A.; Farsiu, Sina; Izatt, Joseph A.

2016-09-01

Enabled by adaptive optics, retinal photoreceptor cell imaging is changing our understanding of retinal structure and function, as well as the pathogenesis of numerous ocular diseases. To date, use of this technology has been limited to cooperative adult subjects due to the size, weight and inconvenience of the equipment, thus excluding study of retinal maturation during human development. Here, we report the design and operation of a handheld probe that can perform both scanning laser ophthalmoscopy and optical coherence tomography of the parafoveal photoreceptor structure in infants and children without the need for adaptive optics. The probe, featuring a compact optical design weighing only 94 g, was able to quantify packing densities of parafoveal cone photoreceptors and visualize cross-sectional photoreceptor substructure in children with ages ranging from 14 months to 12 years. The probe will benefit paediatric research by improving the understanding of retinal development, maldevelopment and early onset of disease during human growth.

Bone metabolism in oxalosis: a single-center study using new imaging techniques and biomarkers.

PubMed

Bacchetta, Justine; Fargue, Sonia; Boutroy, Stéphanie; Basmaison, Odile; Vilayphiou, Nicolas; Plotton, Ingrid; Guebre-Egziabher, Fitsum; Dohin, Bruno; Kohler, Rémi; Cochat, Pierre

2010-06-01

The deposition of calcium oxalate crystals in the kidney and bone is a hallmark of primary hyperoxaluria type 1 (PH1). We report here an evaluation of the bone status of 12 PH1 children based on bone biomarkers [parathyroid hormone, vitamin D, fibroblast growth factor 23 (FGF23)] and radiological assessments (skeletal age, three-dimensional high-resolution peripheral quantitative computed tomography, HR-pQCT) carried out within the framework of a cross-sectional single-center study. The controls consisted of healthy and children with chronic kidney disease already enrolled in local bone and mineral metabolism studies. The mean age (+ or - standard deviation) age of the patients was 99 (+ or - 63) months. Six children suffered from fracture. Bone maturation was accelerated in five patients, four of whom were <5 years. The combination of new imaging techniques and biomarkers highlighted new and unexplained features of PH1: advanced skeletal age in young PH1 patients, increased FGF23 levels and decreased total volumetric bone mineral density with bone microarchitecture alteration.

Identifying Children With Poor Cochlear Implantation Outcomes Using Massively Parallel Sequencing

PubMed Central

Wu, Chen-Chi; Lin, Yin-Hung; Liu, Tien-Chen; Lin, Kai-Nan; Yang, Wei-Shiung; Hsu, Chuan-Jen; Chen, Pei-Lung; Wu, Che-Ming

2015-01-01

Abstract Cochlear implantation is currently the treatment of choice for children with severe to profound hearing impairment. However, the outcomes with cochlear implants (CIs) vary significantly among recipients. The purpose of the present study is to identify the genetic determinants of poor CI outcomes. Twelve children with poor CI outcomes (the “cases”) and 30 “matched controls” with good CI outcomes were subjected to comprehensive genetic analyses using massively parallel sequencing, which targeted 129 known deafness genes. Audiological features, imaging findings, and auditory/speech performance with CIs were then correlated to the genetic diagnoses. We identified genetic variants which are associated with poor CI outcomes in 7 (58%) of the 12 cases; 4 cases had bi-allelic PCDH15 pathogenic mutations and 3 cases were homozygous for the DFNB59 p.G292R variant. Mutations in the WFS1, GJB3, ESRRB, LRTOMT, MYO3A, and POU3F4 genes were detected in 7 (23%) of the 30 matched controls. The allele frequencies of PCDH15 and DFNB59 variants were significantly higher in the cases than in the matched controls (both P < 0.001). In the 7 CI recipients with PCDH15 or DFNB59 variants, otoacoustic emissions were absent in both ears, and imaging findings were normal in all 7 implanted ears. PCDH15 or DFNB59 variants are associated with poor CI performance, yet children with PCDH15 or DFNB59 variants might show clinical features indistinguishable from those of other typical pediatric CI recipients. Accordingly, genetic examination is indicated in all CI candidates before operation. PMID:26166082

Congenital portosystemic shunts with and without gastrointestinal bleeding - case series.

PubMed

Gong, Ying; Zhu, Hui; Chen, Jun; Chen, Qi; Ji, Min; Pa, Mier; Zheng, Shan; Qiao, Zhongwei

2015-12-01

The clinical presentation of congenital portosystemic shunt is variable and gastrointestinal bleeding is an uncommon presentation. To describe the imaging features of congenital portosystemic shunt as it presented in 11 children with (n = 6) and without gastrointestinal bleeding (n = 5). We performed a retrospective study on a clinical and imaging dataset of 11 children diagnosed with congenital portosystemic shunt. A total of 11 children with congenital portosystemic shunt were included in this study, 7 with extrahepatic portosystemic shunts and 4 with intrahepatic portosystemic shunts. Six patients with gastrointestinal bleeding had an extrahepatic portosystemic shunt, and the imaging results showed that the shunts originated from the splenomesenteric junction (n = 5) or splenic vein (n = 1) and connected to the internal iliac vein. Among the five cases of congenital portosystemic shunt without gastrointestinal bleeding, one case was an extrahepatic portosystemic shunt and the other four were intrahepatic portosystemic shunts. Most congenital portosystemic shunt patients with gastrointestinal bleeding had a shunt that drained portal blood into the iliac vein via an inferior mesenteric vein. This type of shunt was uncommon, but the concomitant rate of gastrointestinal bleeding with this type of shunt was high.

Multi-threshold white matter structural networks fusion for accurate diagnosis of Tourette syndrome children

NASA Astrophysics Data System (ADS)

Wen, Hongwei; Liu, Yue; Wang, Shengpei; Li, Zuoyong; Zhang, Jishui; Peng, Yun; He, Huiguang

2017-03-01

Tourette syndrome (TS) is a childhood-onset neurobehavioral disorder. To date, TS is still misdiagnosed due to its varied presentation and lacking of obvious clinical symptoms. Therefore, studies of objective imaging biomarkers are of great importance for early TS diagnosis. As tic generation has been linked to disturbed structural networks, and many efforts have been made recently to investigate brain functional or structural networks using machine learning methods, for the purpose of disease diagnosis. However, few studies were related to TS and some drawbacks still existed in them. Therefore, we propose a novel classification framework integrating a multi-threshold strategy and a network fusion scheme to address the preexisting drawbacks. Here we used diffusion MRI probabilistic tractography to construct the structural networks of 44 TS children and 48 healthy children. We ameliorated the similarity network fusion algorithm specially to fuse the multi-threshold structural networks. Graph theoretical analysis was then implemented, and nodal degree, nodal efficiency and nodal betweenness centrality were selected as features. Finally, support vector machine recursive feature extraction (SVM-RFE) algorithm was used for feature selection, and then optimal features are fed into SVM to automatically discriminate TS children from controls. We achieved a high accuracy of 89.13% evaluated by a nested cross validation, demonstrated the superior performance of our framework over other comparison methods. The involved discriminative regions for classification primarily located in the basal ganglia and frontal cortico-cortical networks, all highly related to the pathology of TS. Together, our study may provide potential neuroimaging biomarkers for early-stage TS diagnosis.

Pediatric art preferences: countering the "one-size-fits-all" approach.

PubMed

Nanda, Upali; Chanaud, Cheryl M; Brown, Linda; Hart, Robyn; Hathorn, Kathy

2009-01-01

To determine the stated art preferences of pediatric patients through an art survey and determine whether preferences vary, with different age groups associated with different stages of cognitive development. Exposure to visual art has been shown to have an impact on improved health and satisfaction outcomes. However, there is little literature on the effect of art on pediatric patients. While designing pediatric wards, a common assumption is to use fantasy and Disney-like themes; but research across all age groups on whether children prefer these themes is limited. A survey including 20 images with a variety of subject matter and styles was administered to 64 pediatric inpatients (ages 5-17) at Memorial Hermann Hospital in Houston, TX. Children were asked to rate the selection of, and their emotional response to, the images in the survey. Qualitative comments were recorded. Results were analyzed for each of the three age groups (5-6, 7-10, and 11-17 years) according to Piaget's developmental stages, as well as across all age groups. There were significant differences in art preferences across the different age groups, especially with respect to child art (art created by children). Overall, the results for 5-10-year-olds were more significant than those for 11-17-year-olds (adolescents). Nature elements were preferred across all age groups, but all nature images were not rated similarly. Images that were bright and colorful were rated better than images that were pale. The presence of a strong context that children could associate with was a defining feature of preferred images. Content drove preference more than style, though color was a key determinant. Comments on the artwork tended to be more objective/absolute for the youngest patients and more subjective/relative for the oldest. The combination of bright colors, engaging themes, and nature content is consistently highly rated by pediatric patients. However, pediatric preferences vary significantly among the three operational stages, so one should be careful before using the "one-size-fits-all" approach. Child art, typically used in pediatric wards, is better suited for younger children than for older children.

EnLightenment: High resolution smartphone microscopy as an educational and public engagement platform.

PubMed

Wicks, Laura C; Cairns, Gemma S; Melnyk, Jacob; Bryce, Scott; Duncan, Rory R; Dalgarno, Paul A

2017-01-01

We developed a simple, cost-effective smartphone microscopy platform for use in educational and public engagement programs. We demonstrated its effectiveness, and potential for citizen science through a national imaging initiative, EnLightenment . The cost effectiveness of the instrument allowed for the program to deliver over 500 microscopes to more than 100 secondary schools throughout Scotland, targeting 1000's of 12-14 year olds. Through careful, quantified, selection of a high power, low-cost objective lens, our smartphone microscope has an imaging resolution of microns, with a working distance of 3 mm. It is therefore capable of imaging single cells and sub-cellular features, and retains usability for young children. The microscopes were designed in kit form and provided an interdisciplinary educational tool. By providing full lesson plans and support material, we developed a framework to explore optical design, microscope performance, engineering challenges on construction and real-world applications in life sciences, biological imaging, marine biology, art, and technology. A national online imaging competition framed EnLightenment ; with over 500 high quality images submitted of diverse content, spanning multiple disciplines. With examples of cellular and sub-cellular features clearly identifiable in some submissions, we show how young public can use these instruments for research-level imaging applications, and the potential of the instrument for citizen science programs.

Distinct brain imaging characteristics of autoantibody-mediated CNS conditions and multiple sclerosis.

PubMed

Jurynczyk, Maciej; Geraldes, Ruth; Probert, Fay; Woodhall, Mark R; Waters, Patrick; Tackley, George; DeLuca, Gabriele; Chandratre, Saleel; Leite, Maria I; Vincent, Angela; Palace, Jacqueline

2017-03-01

Brain imaging characteristics of MOG antibody disease are largely unknown and it is unclear whether they differ from those of multiple sclerosis and AQP4 antibody disease. The aim of this study was to identify brain imaging discriminators between those three inflammatory central nervous system diseases in adults and children to support diagnostic decisions, drive antibody testing and generate disease mechanism hypotheses. Clinical brain scans of 83 patients with brain lesions (67 in the training and 16 in the validation cohort, 65 adults and 18 children) with MOG antibody (n = 26), AQP4 antibody disease (n = 26) and multiple sclerosis (n = 31) recruited from Oxford neuromyelitis optica and multiple sclerosis clinical services were retrospectively and anonymously scored on a set of 29 predefined magnetic resonance imaging features by two independent raters. Principal component analysis was used to perform an overview of patients without a priori knowledge of the diagnosis. Orthogonal partial least squares discriminant analysis was used to build models separating diagnostic groups and identify best classifiers, which were then tested on an independent cohort set. Adults and children with MOG antibody disease frequently had fluffy brainstem lesions, often located in pons and/or adjacent to fourth ventricle. Children across all conditions showed more frequent bilateral, large, brainstem and deep grey matter lesions. MOG antibody disease spontaneously separated from multiple sclerosis but overlapped with AQP4 antibody disease. Multiple sclerosis was discriminated from MOG antibody disease and from AQP4 antibody disease with high predictive values, while MOG antibody disease could not be accurately discriminated from AQP4 antibody disease. Best classifiers between MOG antibody disease and multiple sclerosis were similar in adults and children, and included ovoid lesions adjacent to the body of lateral ventricles, Dawson's fingers, T1 hypointense lesions (multiple sclerosis), fluffy lesions and three lesions or less (MOG antibody). In the validation cohort patients with antibody-mediated conditions were differentiated from multiple sclerosis with high accuracy. Both antibody-mediated conditions can be clearly separated from multiple sclerosis on conventional brain imaging, both in adults and children. The overlap between MOG antibody oligodendrocytopathy and AQP4 antibody astrocytopathy suggests that the primary immune target is not the main substrate for brain lesion characteristics. This is also supported by the clear distinction between multiple sclerosis and MOG antibody disease both considered primary demyelinating conditions. We identify discriminatory features, which may be useful in classifying atypical multiple sclerosis, seronegative neuromyelitis optica spectrum disorders and relapsing acute disseminated encephalomyelitis, and characterizing cohorts for antibody discovery. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Idiopathic infantile arterial calcification in two siblings: failure of treatment with diphosphonate.

PubMed Central

Stuart, G; Wren, C; Bain, H

1990-01-01

Two siblings with idiopathic infantile arterial calcification are reported. The fetal and postnatal echocardiographic features were a large pericardial effusion, thickened pulmonary and aortic valves, poor pulsation of the descending aorta, and calcification of the great vessels. In one patient calcification was first detected at 33 weeks' gestation. Despite treatment with disodium etidronate both children died. Images PMID:2118367

Bedside functional brain imaging in critically-ill children using high-density EEG source modeling and multi-modal sensory stimulation.

PubMed

Eytan, Danny; Pang, Elizabeth W; Doesburg, Sam M; Nenadovic, Vera; Gavrilovic, Bojan; Laussen, Peter; Guerguerian, Anne-Marie

2016-01-01

Acute brain injury is a common cause of death and critical illness in children and young adults. Fundamental management focuses on early characterization of the extent of injury and optimizing recovery by preventing secondary damage during the days following the primary injury. Currently, bedside technology for measuring neurological function is mainly limited to using electroencephalography (EEG) for detection of seizures and encephalopathic features, and evoked potentials. We present a proof of concept study in patients with acute brain injury in the intensive care setting, featuring a bedside functional imaging set-up designed to map cortical brain activation patterns by combining high density EEG recordings, multi-modal sensory stimulation (auditory, visual, and somatosensory), and EEG source modeling. Use of source-modeling allows for examination of spatiotemporal activation patterns at the cortical region level as opposed to the traditional scalp potential maps. The application of this system in both healthy and brain-injured participants is demonstrated with modality-specific source-reconstructed cortical activation patterns. By combining stimulation obtained with different modalities, most of the cortical surface can be monitored for changes in functional activation without having to physically transport the subject to an imaging suite. The results in patients in an intensive care setting with anatomically well-defined brain lesions suggest a topographic association between their injuries and activation patterns. Moreover, we report the reproducible application of a protocol examining a higher-level cortical processing with an auditory oddball paradigm involving presentation of the patient's own name. This study reports the first successful application of a bedside functional brain mapping tool in the intensive care setting. This application has the potential to provide clinicians with an additional dimension of information to manage critically-ill children and adults, and potentially patients not suited for magnetic resonance imaging technologies.

MRI findings in 6 cases of children by inadvertent ingestion of diphenoxylate-atropine.

PubMed

Xiao, Lianxiang; Lin, Xiangtao; Cao, Jinfeng; Wang, Xueyu; Wu, Lebin

2011-09-01

Compound diphenoxylate (diphenoxylate-atropine) poisoning can cause toxic encephalopathy in children, and magnetic resonance imaging (MRI) of the brain in this condition has not been reported. This study is to analyze brain MRI findings and to investigate the relations between MRI features and possible pathophysiological changes in children. Six children accidentally swallowed compound diphenoxylate, 4 males, 2 females, aged 20-46 months, average 33 months. Quantity of ingested diphenoxylate-atropine was from 6 to 30 tablets, each tablet contains diphenoxylate 2.5mg and atropine 0.025 mg. These patients were referred to our hospital within 24h after diphenoxylate-atropine ingestion, and underwent brain MRI scan within 24-72 h after emergency treatment. The characteristics of conventional MRI were analyzed. These pediatric patients had various symptoms of opioid intoxication and atropine toxicity. Brain MRI showed abnormal low signal intensity on T1-weighted images (T1WI) and abnormal high signal intensity on T2-weighted images (T2WI) and fluid-attenuated inversion recovery (FLAIR) imaging in bilateral in all cases; abnormal high signal intensity on T1WI, T2WI and FLAIR in 4 cases. Encephalomalacia was observed in 3 cases during follow-up. In the early stage of compound diphenoxylate poisoning in children, multiple extensive edema-necrosis and hemorrhagic-necrosis focus were observed in basic nucleus, pallium and cerebellum, these resulted in the corresponding brain dysfunction with encephalomalacia. MRI scan in the early stage in this condition may provide evidences of brain impairment, and is beneficial for the early diagnosis, treatment and prognosis assessment. Crown Copyright © 2010. Published by Elsevier Ireland Ltd. All rights reserved.

Clinical and neuroimaging profile of HIV-1 encephalopathy in infancy and childhood in a sub-Saharan African country.

PubMed

G Mariam, Ayle; Assefa, Getachew

2012-10-01

Neurological dysfunction in AIDS is common, occurring in as many as eighty percent of children. Thus, it is important to recognize the central nervous system imaging appearance of HIV, in particular those of HIV encephalopathy, as this is an AIDS defining illness and with distinct neuro-imaging features essential for early diagnosis and timely therapeutic intervention To identify the clinical features in HIV-1 infection of the central nervous system and their associated neuroradiological correlates. Retrospective review of the records of all children with HIV-1 encephalopathy identified among children with neurological and developmental problems and who were on follow up at a child development and neurology clinic in an African city. A total of 22 children (10 male and 12 female) with HIV-1 encephalopathy were identified among 2382 children with various forms of neurological and developmental problems and who were on follow up at a child development and neurology clinic for a little bit over eight years period. All the children acquired the infection vertically. The age range of these children was between 10 months to 14 years. The median age was 5.6 years. The mean duration of symptom was 3.2 years. Global delay or regression in development along with signs of pyramidal tract involvement and seizures were the commonest clinical signs observed in these children. Neuro-behavioral problems were commonly observed among preschool and school aged children. In older children and preadolescents focal seizures with or with out neurologic deficit and neuroradiological findings were common. Nonhemorrhagic stroke was rare and occurred in one child and another child had cortical blindness. Three children had no neurological deficit. Rapid progression of the disease carried grave prognosis. Opportunistic infections and tumors of the central nervous system were also uncommon among these children. Brain volume loss with dilatation of the lateral ventricle, bilateral symmetrical or asymmetrical calcification of the basal ganglia and periventricular involvement of the white matter were the commonest neuro-radiological findings observed in these children. Atrophy of the brain with dilatation of the lateral ventricles and calcification of the basal ganglia and peri-ventricular involvement of the white matter were the commonest neuro-radiological findings in children with HIV-1 encephalopathy. Similarly global delay or regression in development along with pyramidal tract signs and seizures were the commonest neurological findings. Behavioral problems were common in preschool and school aged children. Focal seizures were common in older children and preadolescents. Rapid progression of the disease carried grave prognosis.

Seckel syndrome: an overdiagnosed syndrome.

PubMed Central

Thompson, E; Pembrey, M

1985-01-01

Five children in whom a diagnosis of Seckel syndrome had previously been made were re-examined in the genetic unit. One child had classical Seckel syndrome, a sib pair had the features of the syndrome with less severe short stature, and in two children the diagnosis was not confirmed. Seckel syndrome is only one of a group of low birth weight microcephalic dwarfism and careful attention should be paid to fulfillment of the major criteria defined by Seckel before the diagnosis is made. There remains a heterogeneous group of low birth weight microcephalic dwarfism yet to be defined. Images PMID:4040172

Merging Dietary Assessment with the Adolescent Lifestyle

PubMed Central

Schap, TusaRebecca E; Zhu, Fengqing M; Delp, Edward J; Boushey, Carol J

2013-01-01

The use of image-based dietary assessment methods shows promise for improving dietary self-report among children. The Technology Assisted Dietary Assessment (TADA) food record application is a self-administered food record specifically designed to address the burden and human error associated with conventional methods of dietary assessment. Users would take images of foods and beverages at all eating occasions using a mobile telephone or mobile device with an integrated camera, (e.g., Apple iPhone, Google Nexus One, Apple iPod Touch). Once the images are taken, the images are transferred to a back-end server for automated analysis. The first step in this process is image analysis, i.e., segmentation, feature extraction, and classification, allows for automated food identification. Portion size estimation is also automated via segmentation and geometric shape template modeling. The results of the automated food identification and volume estimation can be indexed with the Food and Nutrient Database for Dietary Studies (FNDDS) to provide a detailed diet analysis for use in epidemiologic or intervention studies. Data collected during controlled feeding studies in a camp-like setting have allowed for formative evaluation and validation of the TADA food record application. This review summarizes the system design and the evidence-based development of image-based methods for dietary assessment among children. PMID:23489518

Together I Can! Joint Attention Boosts 3- to 4-Year-Olds' Performance in a Verbal False-Belief Test.

PubMed

Psouni, Elia; Falck, Andreas; Boström, Leni; Persson, Martin; Sidén, Lisa; Wallin, Maria

2018-04-20

Effects of joint attention were addressed on 3- to 4-year-olds' performance in a verbal false-Belief Test (FBT), featuring the experimenter as co-watcher rather than narrator. In two experiments, children (N = 183) watched a filmed-FBT jointly with a test leader, disjointed from a test leader, or alone. Children attending jointly with a test leader were more likely to pass the FBT compared with normative data and to spontaneously recall information indicating false-belief understanding, suggesting that joint attention strengthens the plausibility of the FBT and renders plot-critical information more salient. In a third experiment (N = 59), results were replicated using a typical, image-based FBT. Overall findings highlight the profound impact of experimenter as social context in verbal FBTs, and link recall of specific story features to false-belief understanding. © 2018 Society for Research in Child Development.

Anophthalmos, microphthalmos, and Coloboma in the United kingdom: clinical features, results of investigations, and early management.

PubMed

Shah, Shaheen P; Taylor, Amy E; Sowden, Jane C; Ragge, Nicky; Russell-Eggitt, Isabelle; Rahi, Jugnoo S; Gilbert, Clare E

2012-02-01

To describe the clinical features of children with anophthalmos, microphthalmos, and typical coloboma (AMC). Descriptive, observational, cross-sectional study of the United Kingdom. A total of 135 children with AMC newly diagnosed over an 18-month period beginning in October 2006. Cases were identified using active surveillance through an established ophthalmic surveillance system. Eligible cases were followed up 6 months after first notification. Phenotypic characteristics, both ocular and systemic, clinical investigations, causes, and interventions. A total of 210 eyes (of 135 children) were affected by AMC, of which 153 had isolated coloboma or coloboma with microphthalmos. The most common colobomatous anomaly was a chorioretinal defect present in 109 eyes (71.2%). Some 44% of children were bilaterally visually impaired. Systemic abnormalities were present in 59.7% of children, with craniofacial anomalies being the most common. Children with bilateral disease had a 2.7 times higher odds (95% confidence interval, 1.3-5.5, P = 0.006) of having systemic involvement than unilaterally affected children. Neurologic imaging was the most frequent investigation (58.5%) performed. Less than one third (30.3%) of the children with microphthalmos had ocular axial lengths measured. Eight children had confirmed genetic mutations. Approximately half (49.2%) of the children required ocular intervention. Colobomatous defects were the most common phenotype within this spectrum of anomalies in the United Kingdom. The high frequency of posterior segment colobomatous involvement means that a dilated fundal examination should be made in all cases. The significant visual and systemic morbidity in affected children underlines the importance of a multidisciplinary approach to management. Copyright © 2012 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

"Let It Go": Exploring the Image of the Child as a Producer, Consumer, and Inventor

ERIC Educational Resources Information Center

Rowsell, Jennifer; Harwood, Debra

2015-01-01

iPads are increasingly being put in the hands of children in schools and educational contexts, yet there continues to be larger questions about how they fit into the fabric of daily classroom life and what new stories will emerge (de Certeau, 1984, 1984/2000). In this article, we feature vignettes of data from a 2-year government-funded research…

Estimation of trabecular bone parameters in children from multisequence MRI using texture-based regression

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

Lekadir, Karim, E-mail: karim.lekadir@upf.edu; Hoogendoorn, Corné; Armitage, Paul

Purpose: This paper presents a statistical approach for the prediction of trabecular bone parameters from low-resolution multisequence magnetic resonance imaging (MRI) in children, thus addressing the limitations of high-resolution modalities such as HR-pQCT, including the significant exposure of young patients to radiation and the limited applicability of such modalities to peripheral bones in vivo. Methods: A statistical predictive model is constructed from a database of MRI and HR-pQCT datasets, to relate the low-resolution MRI appearance in the cancellous bone to the trabecular parameters extracted from the high-resolution images. The description of the MRI appearance is achieved between subjects by usingmore » a collection of feature descriptors, which describe the texture properties inside the cancellous bone, and which are invariant to the geometry and size of the trabecular areas. The predictive model is built by fitting to the training data a nonlinear partial least square regression between the input MRI features and the output trabecular parameters. Results: Detailed validation based on a sample of 96 datasets shows correlations >0.7 between the trabecular parameters predicted from low-resolution multisequence MRI based on the proposed statistical model and the values extracted from high-resolution HRp-QCT. Conclusions: The obtained results indicate the promise of the proposed predictive technique for the estimation of trabecular parameters in children from multisequence MRI, thus reducing the need for high-resolution radiation-based scans for a fragile population that is under development and growth.« less

Relation between brain architecture and mathematical ability in children: a DBM study.

PubMed

Han, Zhaoying; Davis, Nicole; Fuchs, Lynn; Anderson, Adam W; Gore, John C; Dawant, Benoit M

2013-12-01

Population-based studies indicate that between 5 and 9 percent of US children exhibit significant deficits in mathematical reasoning, yet little is understood about the brain morphological features related to mathematical performances. In this work, deformation-based morphometry (DBM) analyses have been performed on magnetic resonance images of the brains of 79 third graders to investigate whether there is a correlation between brain morphological features and mathematical proficiency. Group comparison was also performed between Math Difficulties (MD-worst math performers) and Normal Controls (NC), where each subgroup consists of 20 age and gender matched subjects. DBM analysis is based on the analysis of the deformation fields generated by non-rigid registration algorithms, which warp the individual volumes to a common space. To evaluate the effect of registration algorithms on DBM results, five nonrigid registration algorithms have been used: (1) the Adaptive Bases Algorithm (ABA); (2) the Image Registration Toolkit (IRTK); (3) the FSL Nonlinear Image Registration Tool; (4) the Automatic Registration Tool (ART); and (5) the normalization algorithm available in SPM8. The deformation field magnitude (DFM) was used to measure the displacement at each voxel, and the Jacobian determinant (JAC) was used to quantify local volumetric changes. Results show there are no statistically significant volumetric differences between the NC and the MD groups using JAC. However, DBM analysis using DFM found statistically significant anatomical variations between the two groups around the left occipital-temporal cortex, left orbital-frontal cortex, and right insular cortex. Regions of agreement between at least two algorithms based on voxel-wise analysis were used to define Regions of Interest (ROIs) to perform an ROI-based correlation analysis on all 79 volumes. Correlations between average DFM values and standard mathematical scores over these regions were found to be significant. We also found that the choice of registration algorithm has an impact on DBM-based results, so we recommend using more than one algorithm when conducting DBM studies. To the best of our knowledge, this is the first study that uses DBM to investigate brain anatomical features related to mathematical performance in a relatively large population of children. © 2013.

Imaging pediatric magnet ingestion with surgical-pathological correlation.

PubMed

Otjen, Jeffrey P; Rohrmann, Charles A; Iyer, Ramesh S

2013-07-01

Foreign body ingestion is a common problem in the pediatric population and a frequent cause for emergency room visits. Magnets are common household objects that when ingested can bring about severe, possibly fatal gastrointestinal complications. Radiography is an integral component of the management of these children. Pediatric and emergency radiologists alike must be aware of imaging manifestations of magnet ingestion, as their identification drives decision-making for consulting surgeons and gastroenterologists. Radiology can thus substantially augment the clinical history and physical exam, facilitating appropriate management. This manuscript sequentially presents cases of magnet ingestion featuring imaging findings coupled with surgical and pathological correlation. Each case is presented to highlight ways in which the radiologist can make impactful contributions to diagnosis and management. Clinical overview with pitfalls of magnet ingestion imaging and an imaging decision tree will also be presented.

Computer-aided Prognosis of Neuroblastoma on Whole-slide Images: Classification of Stromal Development

PubMed Central

Sertel, O.; Kong, J.; Shimada, H.; Catalyurek, U.V.; Saltz, J.H.; Gurcan, M.N.

2009-01-01

We are developing a computer-aided prognosis system for neuroblastoma (NB), a cancer of the nervous system and one of the most malignant tumors affecting children. Histopathological examination is an important stage for further treatment planning in routine clinical diagnosis of NB. According to the International Neuroblastoma Pathology Classification (the Shimada system), NB patients are classified into favorable and unfavorable histology based on the tissue morphology. In this study, we propose an image analysis system that operates on digitized H&E stained whole-slide NB tissue samples and classifies each slide as either stroma-rich or stroma-poor based on the degree of Schwannian stromal development. Our statistical framework performs the classification based on texture features extracted using co-occurrence statistics and local binary patterns. Due to the high resolution of digitized whole-slide images, we propose a multi-resolution approach that mimics the evaluation of a pathologist such that the image analysis starts from the lowest resolution and switches to higher resolutions when necessary. We employ an offine feature selection step, which determines the most discriminative features at each resolution level during the training step. A modified k-nearest neighbor classifier is used to determine the confidence level of the classification to make the decision at a particular resolution level. The proposed approach was independently tested on 43 whole-slide samples and provided an overall classification accuracy of 88.4%. PMID:20161324

Clinical and Imaging Findings in Childhood Posterior Reversible Encephalopathy Syndrome

PubMed Central

GUNGOR, Serdal; KILIC, Betul; TABEL, Yilmaz; SELIMOGLU, Ayse; OZGEN, Unsal; YILMAZ, Sezai

2018-01-01

Objective Posterior reversible encephalopathy syndrome (PRES) is characterized by typical radiologic findings in the posterior regions of the cerebral hemispheres and cerebellum. The symptoms include headache, nausea, vomiting, visual disturbances, focal neurologic deficits, and seizures. The aim of this study is to evaluate the clinical and radiological features of PRES in children and to emphasize the recognition of atypical features. Materials & Methods We retrospectively examined 23 children with PRES from Mar 2010-Apr 2015 in Inonu University Turgut Ozal Medical Center in Turkey. We compared the clinical features and cranial MRI findings between underlying diseases of PRES. Results The most common precipitating factors were hypertension (78.2%) and medications, namely immunosuppressive and antineoplastic agents (60.8%). Manifestations included mental changes (100%), seizures (95.6%), headache (60.8%), and visual disturbances (21.7%) of mean 3.6 (range 1-10) days' duration. Cranial magnetic resonance imaging (MRI) showed bilateral occipital lesions in all patients, associated in 82.6% with less typical distribution of lesions in frontal, temporal or parietal lobes, cerebellum, corpus callosum, basal ganglia, thalamus, and brain stem. Frontal involvement was predominant, observed in 56.5% of patients. Clinical recovery was followed by radiologic resolution in all patients. Conclusion PRES is often unsuspected by the clinician, thus radiologists may be the first to suggest this diagnosis on an MRI obtained for seizures or encephalopathy. Atypical MRI finding is seen quite often. Rapid diagnosis and treatment are required to avoid a devastating outcome. PMID:29379559

Data mining for average images in a digital hand atlas

NASA Astrophysics Data System (ADS)

Zhang, Aifeng; Cao, Fei; Pietka, Ewa; Liu, Brent J.; Huang, H. K.

2004-04-01

Bone age assessment is a procedure performed in pediatric patients to quickly evaluate parameters of maturation and growth from a left hand and wrist radiograph. Pietka and Cao have developed a Computer-aided diagnosis (CAD) method of bone age assessment based on a digital hand atlas. The aim of this paper is to extend their work by automatically select the best representative image from a group of normal children based on specific bony features that reflect skeletal maturity. The group can be of any ethnic origin and gender from one year to 18 year old in the digital atlas. This best representative image is defined as the "average" image of the group that can be augmented to Piekta and Cao's method to facilitate in the bone age assessment process.

Juvenile Osteochondritis Dissecans: Correlation Between Histopathology and MRI.

PubMed

Zbojniewicz, Andrew M; Stringer, Keith F; Laor, Tal; Wall, Eric J

2015-07-01

The objective of our study was to correlate specimens of juvenile osteochondritis dissecans (OCD) lesions of the knee to MRI examinations to elucidate the histopathologic basis of characteristic imaging features. Five children (three boys and two girls; age range, 12-13 years old) who underwent transarticular biopsy of juvenile OCD lesions of the knee were retrospectively included in this study. Two radiologists reviewed the MRI examinations and a pathologist reviewed the histopathologic specimens and recorded characteristic features. Digital specimen photographs were calibrated to the size of the respective MR image with the use of a reference scale. Photographs were rendered semitransparent and over-laid onto the MR image with the location chosen on the basis of the site of the prior biopsy. A total of seven biopsy specimens were included. On MRI, all lesions showed cystlike foci in the subchondral bone, bone marrow edema pattern on proton density-or T2-weighted images, and relatively thick unossified epiphyseal cartilage. In four patients, a laminar signal intensity pattern was seen, and two patients had multiple breaks in the subchondral bone plate. Fibrovascular tissue was found at histopathology in all patients. Cleft spaces near the cartilage-bone interface and were seen in all patients while chondrocyte cloning was present in most cases. Focal bone necrosis and inflammation were infrequent MRI findings. Precise correlation of the MRI appearance to the histopathologic overlays consistently was found. A direct correlation exists between the histopathologic findings and the MRI features in patients with juvenile OCD. Additional studies are needed to correlate these MRI features with juvenile OCD healing success rates.

Automated detection of retinal whitening in malarial retinopathy

NASA Astrophysics Data System (ADS)

Joshi, V.; Agurto, C.; Barriga, S.; Nemeth, S.; Soliz, P.; MacCormick, I.; Taylor, T.; Lewallen, S.; Harding, S.

2016-03-01

Cerebral malaria (CM) is a severe neurological complication associated with malarial infection. Malaria affects approximately 200 million people worldwide, and claims 600,000 lives annually, 75% of whom are African children under five years of age. Because most of these mortalities are caused by the high incidence of CM misdiagnosis, there is a need for an accurate diagnostic to confirm the presence of CM. The retinal lesions associated with malarial retinopathy (MR) such as retinal whitening, vessel discoloration, and hemorrhages, are highly specific to CM, and their detection can improve the accuracy of CM diagnosis. This paper will focus on development of an automated method for the detection of retinal whitening which is a unique sign of MR that manifests due to retinal ischemia resulting from CM. We propose to detect the whitening region in retinal color images based on multiple color and textural features. First, we preprocess the image using color and textural features of the CMYK and CIE-XYZ color spaces to minimize camera reflex. Next, we utilize color features of the HSL, CMYK, and CIE-XYZ channels, along with the structural features of difference of Gaussians. A watershed segmentation algorithm is used to assign each image region a probability of being inside the whitening, based on extracted features. The algorithm was applied to a dataset of 54 images (40 with whitening and 14 controls) that resulted in an image-based (binary) classification with an AUC of 0.80. This provides 88% sensitivity at a specificity of 65%. For a clinical application that requires a high specificity setting, the algorithm can be tuned to a specificity of 89% at a sensitivity of 82%. This is the first published method for retinal whitening detection and combining it with the detection methods for vessel discoloration and hemorrhages can further improve the detection accuracy for malarial retinopathy.

Analysis of high-speed digital phonoscopy pediatric images

NASA Astrophysics Data System (ADS)

Unnikrishnan, Harikrishnan; Donohue, Kevin D.; Patel, Rita R.

2012-02-01

The quantitative characterization of vocal fold (VF) motion can greatly enhance the diagnosis and treatment of speech pathologies. The recent availability of high-speed systems has created new opportunities to understand VF dynamics. This paper presents quantitative methods for analyzing VF dynamics with high-speed digital phonoscopy, with a focus on expected VF changes during childhood. A robust method for automatic VF edge tracking during phonation is introduced and evaluated against 4 expert human observers. Results from 100 test frames show a subpixel difference between the VF edges selected by algorithm and expert observers. Waveforms created from the VF edge displacement are used to created motion features with limited sensitivity to variations of camera resolution on the imaging plane. New features are introduced based on acceleration ratios of critical points over each phonation cycle, which have the potential for studying issues related to impact stress. A novel denoising and hybrid interpolation/extrapolation scheme is also introduced to reduce the impact of quantization errors and large sampling intervals relative to the phonation cycle. Features extracted from groups of 4 adults and 5 children show large differences for features related to asymmetry between the right and left fold and consistent differences for impact acceleration ratio.

EnLightenment: High resolution smartphone microscopy as an educational and public engagement platform

PubMed Central

Wicks, Laura C.; Cairns, Gemma S.; Melnyk, Jacob; Bryce, Scott; Duncan, Rory R.; Dalgarno, Paul A.

2018-01-01

We developed a simple, cost-effective smartphone microscopy platform for use in educational and public engagement programs. We demonstrated its effectiveness, and potential for citizen science through a national imaging initiative, EnLightenment. The cost effectiveness of the instrument allowed for the program to deliver over 500 microscopes to more than 100 secondary schools throughout Scotland, targeting 1000’s of 12-14 year olds. Through careful, quantified, selection of a high power, low-cost objective lens, our smartphone microscope has an imaging resolution of microns, with a working distance of 3 mm. It is therefore capable of imaging single cells and sub-cellular features, and retains usability for young children. The microscopes were designed in kit form and provided an interdisciplinary educational tool. By providing full lesson plans and support material, we developed a framework to explore optical design, microscope performance, engineering challenges on construction and real-world applications in life sciences, biological imaging, marine biology, art, and technology. A national online imaging competition framed EnLightenment ; with over 500 high quality images submitted of diverse content, spanning multiple disciplines. With examples of cellular and sub-cellular features clearly identifiable in some submissions, we show how young public can use these instruments for research-level imaging applications, and the potential of the instrument for citizen science programs. PMID:29623296

Seizure drawings: insight into the self-image of children with epilepsy.

PubMed

Stafstrom, Carl E; Havlena, Janice

2003-02-01

Epilepsy is a chronic disorder that is associated with numerous psychological challenges, especially in children. Drawings have been underutilized as a method to obtain insight into psychological issues in children with epilepsy. We asked 105 children with epilepsy, ages 5 to 18 years, to draw a picture of what it is like to have a seizure. Across ages and epilepsy syndromes, the drawings showed evidence of impaired self-concept, low self-esteem, and a sense of helplessness and vulnerability. Overall, the drawings of human figures were less developed than expected for chronological age. In some drawings, indicators of underlying depression were found. When considered by epilepsy syndrome or seizure type, some specific artistic features were noted. Children with simple partial (motor) seizures drew distorted body parts, especially limbs. Those with complex partial seizures depicted sensory symptoms and mental status changes such as confusion. Children with generalized tonic-clonic seizures showed shaking extremities. Drawings by children with absence seizures illustrated mainly staring. In conclusion, drawings are a powerful method to examine the self-concept of children with epilepsy and gain insight into their feelings about themselves and their world.

Neuroradiology and histopathology in two cases of adult medulloblastoma.

PubMed

Romero-Rojas, Alfredo E; Diaz-Perez, Julio A; Raju, Sharat; Lozano-Castillo, Alfonso

2014-04-01

Medulloblastoma (MB) is the most common central nervous system neoplasm in children and only rarely presents in the adult population. Recent molecular biology findings have characterized MB as a heterogeneous neoplasm distinguished by well-defined tumour subsets each with specific histologic and molecular features. Available immunohistochemical stains can now be used to differentiate the distinct molecular types of MB. This report analyzed the histopathologic and neuroradiologic features of two new cases of adult MB. Imaging studies in these patients revealed the morphological appearance of high-grade, well-circumscribed heterogeneous tumours with necrosis, located laterally within the posterior cranial fossa. Histopathology of resected samples demonstrated high-grade tumours (WHO grade IV) containing sheets of undifferentiated neural cells with high mitotic activity and evidence of necrosis. The histopathologic and molecular characteristics of these cases of MB are reviewed for potential applications in new molecular methods of imaging.

Ultrasound and MRI predictors of surgical bowel resection in pediatric Crohn disease.

PubMed

Rosenbaum, Daniel G; Conrad, Maire A; Biko, David M; Ruchelli, Eduardo D; Kelsen, Judith R; Anupindi, Sudha A

2017-01-01

Imaging predictors for surgery in children with Crohn disease are lacking. To identify imaging features of the terminal ileum on short-interval bowel ultrasound (US) and MR enterography (MRE) in children with Crohn disease requiring surgical bowel resection and those managed by medical therapy alone. This retrospective study evaluated patients 18 years and younger with Crohn disease undergoing short-interval bowel US and MRE (within 2 months of one another), as well as subsequent ileocecectomy or endoscopy within 3 months of imaging. Appearance of the terminal ileum on both modalities was compared between surgical patients and those managed with medical therapy, with the following parameters assessed: bowel wall thickness, mural stratification, vascularity, fibrofatty proliferation, abscess, fistula and stricture on bowel US; bowel wall thickness, T2 ratio, enhancement pattern, mesenteric edema, fibrofatty proliferation, abscess, fistula and stricture on MRE. A two-sided t-test was used to compare means, a Mann-Whitney U analysis was used for non-parametric parameter scores, and a chi-square or two-sided Fisher exact test compared categorical variables. Imaging findings in surgical patients were correlated with location-matched histopathological scores of inflammation and fibrosis using a scoring system adapted from the Simple Endoscopic Score for Crohn Disease, and a Spearman rank correlation coefficient was used to compare inflammation and fibrosis on histopathology. Twenty-two surgical patients (mean age: 16.5 years; male/female: 13/9) and 20 nonsurgical patients (mean age: 14.8; M/F: 8/12) were included in the final analysis. On US, the surgical group demonstrated significantly increased mean bowel wall thickness (6.1 mm vs. 4.7 mm for the nonsurgical group; P = 0.01), loss of mural stratification (odds ratio [OR] = 6.3; 95% confidence interval [CI]: 1.4-28.4; P = 0.02) and increased fibrofatty proliferation (P = 0.04). On MRE, the surgical group showed increased mean bowel wall thickness (9.1 mm vs. 7.2 mm for the nonsurgical group; P = 0.02), increased mean T2 ratio (4.6 vs. 3.6 for the nonsurgical group; P = 0.03), different enhancement patterns (P = 0.03), increased mesenteric edema (P = 0.001) and increased stricture formation (OR = 8.2; 95% CI: 1.8-36.4; P = 0.005). Nineteen of 22 ileocecectomy specimens showed severe inflammation and 21/22 showed severe fibrosis, with significant correlation between inflammation and fibrosis scores (ρ = 0.55; P = 0.008); however, correlation with imaging findings was limited by the uniformity of findings on histopathology. Children with terminal ileal Crohn disease requiring surgical bowel resection demonstrate more severe manifestations of imaging features traditionally associated with both active inflammation and chronic fibrosis than those managed medically on US and MRE, findings that are corroborated by histopathology. These features may potentially serve as imaging biomarkers indicating the necessity for surgical intervention.

Images as a Resource for Supporting Vocabulary Learning: A Multimodal Analysis of Thai EFL Tablet Apps for Primary School Children

ERIC Educational Resources Information Center

Vungthong, Sompatu; Djonov, Emilia; Torr, Jane

2017-01-01

In 2011, the Thai government introduced a national project, One Tablet per Child (OTPC), with the aim of supporting students' learning in the digital world. The project commenced with Grade 1 in 2012 and Grade 2 in 2013. The applications embedded in the OTPC tablet given to each child feature multimedia teaching applications (apps) on various…

Portal vascular anomalies in Down syndrome: spectrum of clinical presentation and management approach.

PubMed

Golewale, Nazar; Paltiel, Harriet J; Fishman, Steven J; Alomari, Ahmad I

2010-08-01

The occurrence of portal vascular anomalies in Down syndrome has been sporadically reported in the literature. These rare disorders have a wide spectrum of anatomical and clinical presentations. The aim of this communication was to describe the clinical course, imaging features, and management approaches in patients with this association. We conducted a comprehensive search of the databases of the Vascular Anomalies Center and the Department of Radiology at Children's Hospital Boston for patients with Down syndrome and portal vascular anomalies. Medical records and imaging studies of varying modalities were reviewed. Three children with Down syndrome and portal anomalies (portosystemic shunt, simple arterioportal shunt, complex arterioportal shunt) were managed at our institution. The portosystemic shunt was clinically insignificant and resolved without any intervention. The simple arterioportal shunt was successfully treated with embolization. The complex arterioportal shunt was associated with major congenital cardiac defects and the child ultimately expired despite a decrease in the arterioportal shunting after embolization. Three is a wide spectrum of clinical and anatomical features of portal vascular shunts in Down syndrome. The management approach should be tailored based on the severity of symptoms. Percutaneous embolization can offer a safe, effective, and minimally invasive alternative to the surgical approach in selective cases. Copyright 2010 Elsevier Inc. All rights reserved.

Outcome of Transsphenoidal Surgery for Cushing Disease: A Single-Center Experience Over 32 Years.

PubMed

Chandler, William F; Barkan, Ariel L; Hollon, Todd; Sakharova, Alla; Sack, Jayson; Brahma, Barunashish; Schteingart, David E

2016-02-01

Transsphenoidal surgery is the standard approach for treating Cushing disease. Evidence is needed to document effectiveness. To analyze results of transsphenoidal surgery in 276 consecutive patients, including 19 children. Medical records were reviewed for patients treated initially with surgery for Cushing disease from 1980 to 2012. Radiographic features, pathology, remissions, recurrences, and complications were recorded. Patients were categorized for statistical analysis based on tumor size (microadenomas, macroadenomas, and negative imaging) and remission type (type 1 = morning cortisol ≤3 μg/dL; type 2 = morning cortisol normal). Females comprised 78% of patients and were older than men. Imaging showed 50% microadenomas, 13% macroadenomas, and 37% negative for tumor. Remission rates for microadenomas, macroadenomas, and negative imaging were 89%, 66%, and 71%, respectively. Patients with microadenomas were more likely to have type 1 remission. Pathology showed adrenocorticotropic hormone-secreting adenomas in 82% of microadenomas, in 100% of macroadenomas, and in 43% of negative imaging. The incidence of hyperplasia was 8%. The finding of hyperplasia or no tumor on pathology predicted treatment failure. The recurrence rate was 17%, with an average time to recurrence of 4.0 years. Patients with type 1 remission had a lower rate of recurrence (13% type 1 vs 50% type 2) and a longer time to recurrence. Children had similar imaging findings, remission rates, and pathology. There were no operative deaths. Transsphenoidal surgery provides a safe and effective treatment for Cushing disease. For both adults and children, the best outcomes occurred in patients with microadenomas and/or those with type 1 remission.

Post-infectious bronchiolitis obliterans in children: CT features that predict responsiveness to pulse methylprednisolone.

PubMed

Yoon, H M; Lee, J S; Hwang, J-Y; Cho, Y A; Yoon, H-K; Yu, J; Hong, S-J; Yoon, C H

2015-05-01

Intravenous pulse methylprednisolone therapy (IPMT) is an important treatment option for post-infectious obliterative bronchiolitis (OB), although it must be used carefully and only in selected patients because of its drawbacks. This study evaluated whether CT and clinical features of children with post-infectious OB can predict their responsiveness to IPMT. We searched the medical records for patients (less than 18 years of age) who were diagnosed with post-infectious OB between January 2000 and December 2011. 17 children who received IPMT were included in this study. All underwent chest CT before and after IPMT. The radiological features seen on pre-treatment CT were recorded. The air-trapping area percentages on pre- and post-treatment CT images were determined. The nine patients who exhibited decreased air trapping on post-treatment CT scans relative to pre-treatment scans were classed as responders. The patient ages and time from initial pneumonia to IPMT were recorded. All responders and only four non-responders had thickened bronchial walls before treatment (p = 0.029). The two groups did not differ significantly in terms of bronchiolitis, bronchiectasis or the extent of air trapping, although the responders had a significantly shorter median interval between initial pneumonia and IPMT (4 vs 50 months; p = 0.005) and were significantly younger (median, 2.0 vs 7.5 years; p = 0.048). Immediate IPMT may improve the degree of air trapping in children with post-infectious OB if they show a thickened bronchial wall on CT. Children with post-infectious OB may respond favourably to IPMT when pre-treatment CT indicates bronchial-wall thickening.

Topologic analysis and comparison of brain activation in children with epilepsy versus controls: an fMRI study

NASA Astrophysics Data System (ADS)

Oweis, Khalid J.; Berl, Madison M.; Gaillard, William D.; Duke, Elizabeth S.; Blackstone, Kaitlin; Loew, Murray H.; Zara, Jason M.

2010-03-01

This paper describes the development of novel computer-aided analysis algorithms to identify the language activation patterns at a certain Region of Interest (ROI) in Functional Magnetic Resonance Imaging (fMRI). Previous analysis techniques have been used to compare typical and pathologic activation patterns in fMRI images resulting from identical tasks but none of them analyzed activation topographically in a quantitative manner. This paper presents new analysis techniques and algorithms capable of identifying a pattern of language activation associated with localization related epilepsy. fMRI images of 64 healthy individuals and 31 patients with localization related epilepsy have been studied and analyzed on an ROI basis. All subjects are right handed with normal MRI scans and have been classified into three age groups (4-6, 7-9, 10-12 years). Our initial efforts have focused on investigating activation in the Left Inferior Frontal Gyrus (LIFG). A number of volumetric features have been extracted from the data. The LIFG has been cut into slices and the activation has been investigated topographically on a slice by slice basis. Overall, a total of 809 features have been extracted, and correlation analysis was applied to eliminate highly correlated features. Principal Component analysis was then applied to account only for major components in the data and One-Way Analysis of Variance (ANOVA) has been applied to test for significantly different features between normal and patient groups. Twenty Nine features have were found to be significantly different (p<0.05) between patient and control groups

Age-related functional brain changes in young children.

PubMed

Long, Xiangyu; Benischek, Alina; Dewey, Deborah; Lebel, Catherine

2017-07-15

Brain function and structure change significantly during the toddler and preschool years. However, most studies focus on older or younger children, so the specific nature of these changes is unclear. In the present study, we analyzed 77 functional magnetic resonance imaging datasets from 44 children aged 2-6 years. We extracted measures of both local (amplitude of low frequency fluctuation and regional homogeneity) and global (eigenvector centrality mapping) activity and connectivity, and examined their relationships with age using robust linear correlation analysis and strict control for head motion. Brain areas within the default mode network and the frontoparietal network, such as the middle frontal gyrus, the inferior parietal lobule and the posterior cingulate cortex, showed increases in local and global functional features with age. Several brain areas such as the superior parietal lobule and superior temporal gyrus presented opposite development trajectories of local and global functional features, suggesting a shifting connectivity framework in early childhood. This development of functional connectivity in early childhood likely underlies major advances in cognitive abilities, including language and development of theory of mind. These findings provide important insight into the development patterns of brain function during the preschool years, and lay the foundation for future studies of altered brain development in young children with brain disorders or injury. Copyright © 2017 Elsevier Inc. All rights reserved.

Merging dietary assessment with the adolescent lifestyle.

PubMed

Schap, T E; Zhu, F; Delp, E J; Boushey, C J

2014-01-01

The use of image-based dietary assessment methods shows promise for improving dietary self-report among children. The Technology Assisted Dietary Assessment (TADA) food record application is a self-administered food record specifically designed to address the burden and human error associated with conventional methods of dietary assessment. Users would take images of foods and beverages at all eating occasions using a mobile telephone or mobile device with an integrated camera [e.g. Apple iPhone, Apple iPod Touch (Apple Inc., Cupertino, CA, USA); Nexus One (Google, Mountain View, CA, USA)]. Once the images are taken, the images are transferred to a back-end server for automated analysis. The first step in this process is image analysis (i.e. segmentation, feature extraction and classification), which allows for automated food identification. Portion size estimation is also automated via segmentation and geometric shape template modeling. The results of the automated food identification and volume estimation can be indexed with the Food and Nutrient Database for Dietary Studies to provide a detailed diet analysis for use in epidemiological or intervention studies. Data collected during controlled feeding studies in a camp-like setting have allowed for formative evaluation and validation of the TADA food record application. This review summarises the system design and the evidence-based development of image-based methods for dietary assessment among children. © 2013 The Authors Journal of Human Nutrition and Dietetics © 2013 The British Dietetic Association Ltd.

A 13-15/21 Translocation Chromosome in Carrier Father and Mongol Son

PubMed Central

Sergovich, Frederick R.; Soltan, Hubert C.; Carr, David H.

1962-01-01

Cytogenetic and dermatoglyphic features were studied in a family in which the mongoloid propositus inherited a 13-15/21 translocation chromosome from his father. Seven other healthy male carriers scattered throughout the pedigree produced nine chromosomally normal children and five carrier children in addition to the mongoloid propositus. These results show that carrier males do not necessarily produce an unusually large proportion of carrier children as previous reports would indicate. Dermatoglyphic studies showed that translocation carriers in this family have neither significantly more centralized nor less centralized palmar axial triradii than non-carrier relatives. No direct evidence was therefore found for the hypothesis that an allele is present on chromosome 21 which influences the height of the triradius. ImagesFig. 1Fig. 2Fig. 3 PMID:13988069

Toward Dysfunctional Connectivity: A Review of Neuroimaging Findings in Pediatric Major Depressive Disorder

PubMed Central

Hulvershorn, Leslie; Cullen, Kathryn; Anand, Amit

2011-01-01

Child and adolescent psychiatric neuroimaging research typically lags behind similar advances in adult disorders. While the pediatric depression imaging literature is less developed, a recent surge in interest has created the need for a synthetic review of this work. Major findings from pediatric volumetric and functional magnetic resonance imaging (fMRI), magnetic resonance spectroscopy (MRS), diffusion tensor imaging (DTI) and resting state functional connectivity studies converge to implicate a corticolimbic network of key areas that work together to mediate the task of emotion regulation. Imaging the brain of children and adolescents with unipolar depression began with volumetric studies of isolated brain regions that served to identify key prefrontal, cingulate and limbic nodes of depression-related circuitry elucidated from more recent advances in DTI and functional connectivity imaging. Systematic review of these studies preliminarily suggests developmental differences between findings in youth and adults, including prodromal neurobiological features, along with some continuity across development. PMID:21901425

Psychoradiologic Utility of MR Imaging for Diagnosis of Attention Deficit Hyperactivity Disorder: A Radiomics Analysis.

PubMed

Sun, Huaiqiang; Chen, Ying; Huang, Qiang; Lui, Su; Huang, Xiaoqi; Shi, Yan; Xu, Xin; Sweeney, John A; Gong, Qiyong

2018-05-01

Purpose To identify cerebral radiomic features related to diagnosis and subtyping of attention deficit hyperactivity disorder (ADHD) and to build and evaluate classification models for ADHD diagnosis and subtyping on the basis of the identified features. Materials and Methods A consecutive cohort of 83 age- and sex-matched children with newly diagnosed and never-treated ADHD (mean age 10.83 years ± 2.30; range, 7-14 years; 71 boys, 40 with ADHD-inattentive [ADHD-I] and 43 with ADHD-combined [ADHD-C, or inattentive and hyperactive]) and 87 healthy control subjects (mean age, 11.21 years ± 2.51; range, 7-15 years; 72 boys) underwent anatomic and diffusion-tensor magnetic resonance (MR) imaging. Features representing the shape properties of gray matter and diffusion properties of white matter were extracted for each participant. The initial feature set was input into an all-relevant feature selection procedure within cross-validation loops to identify features with significant discriminative power for diagnosis and subtyping. Random forest classifiers were constructed and evaluated on the basis of identified features. Results No overall difference was found between children with ADHD and control subjects in total brain volume (1069830.00 mm 3 ± 90743.36 vs 1079 213.00 mm 3 ± 92742.25, respectively; P = .51) or total gray and white matter volume (611978.10 mm 3 ± 51622.81 vs 616960.20 mm 3 ± 51872.93, respectively; P = .53; 413532.00 mm 3 ± 41 114.33 vs 418173.60 mm 3 ± 42395.48, respectively; P = .47). The mean classification accuracy achieved with classifiers to discriminate patients with ADHD from control subjects was 73.7%. Alteration in cortical shape in the left temporal lobe, bilateral cuneus, and regions around the left central sulcus contributed significantly to group discrimination. The mean classification accuracy with classifiers to discriminate ADHD-I from ADHD-C was 80.1%, with significant discriminating features located in the default mode network and insular cortex. Conclusion The results of this study provide preliminary evidence that cerebral morphometric alterations can allow discrimination between patients with ADHD and control subjects and also between the most common ADHD subtypes. By identifying features relevant for diagnosis and subtyping, these findings may advance the understanding of neurodevelopmental alterations related to ADHD. © RSNA, 2017 Online supplemental material is available for this article.

Pediatric functional magnetic resonance neuroimaging: tactics for encouraging task compliance.

PubMed

Schlund, Michael W; Cataldo, Michael F; Siegle, Greg J; Ladouceur, Cecile D; Silk, Jennifer S; Forbes, Erika E; McFarland, Ashley; Iyengar, Satish; Dahl, Ronald E; Ryan, Neal D

2011-05-06

Neuroimaging technology has afforded advances in our understanding of normal and pathological brain function and development in children and adolescents. However, noncompliance involving the inability to remain in the magnetic resonance imaging (MRI) scanner to complete tasks is one common and significant problem. Task noncompliance is an especially significant problem in pediatric functional magnetic resonance imaging (fMRI) research because increases in noncompliance produces a greater risk that a study sample will not be representative of the study population. In this preliminary investigation, we describe the development and application of an approach for increasing the number of fMRI tasks children complete during neuroimaging. Twenty-eight healthy children ages 9-13 years participated. Generalization of the approach was examined in additional fMRI and event-related potential investigations with children at risk for depression, children with anxiety and children with depression (N=120). Essential features of the approach include a preference assessment for identifying multiple individualized rewards, increasing reinforcement rates during imaging by pairing tasks with chosen rewards and presenting a visual 'road map' listing tasks, rewards and current progress. Our results showing a higher percentage of fMRI task completion by healthy children provides proof of concept data for the recommended tactics. Additional support was provided by results showing our approach generalized to several additional fMRI and event-related potential investigations and clinical populations. We proposed that some forms of task noncompliance may emerge from less than optimal reward protocols. While our findings may not directly support the effectiveness of the multiple reward compliance protocol, increased attention to how rewards are selected and delivered may aid cooperation with completing fMRI tasks. The proposed approach contributes to the pediatric neuroimaging literature by providing a useful way to conceptualize and measure task noncompliance and by providing simple cost effective tactics for improving the effectiveness of common reward-based protocols.

Pediatric functional magnetic resonance neuroimaging: tactics for encouraging task compliance

PubMed Central

2011-01-01

Background Neuroimaging technology has afforded advances in our understanding of normal and pathological brain function and development in children and adolescents. However, noncompliance involving the inability to remain in the magnetic resonance imaging (MRI) scanner to complete tasks is one common and significant problem. Task noncompliance is an especially significant problem in pediatric functional magnetic resonance imaging (fMRI) research because increases in noncompliance produces a greater risk that a study sample will not be representative of the study population. Method In this preliminary investigation, we describe the development and application of an approach for increasing the number of fMRI tasks children complete during neuroimaging. Twenty-eight healthy children ages 9-13 years participated. Generalization of the approach was examined in additional fMRI and event-related potential investigations with children at risk for depression, children with anxiety and children with depression (N = 120). Essential features of the approach include a preference assessment for identifying multiple individualized rewards, increasing reinforcement rates during imaging by pairing tasks with chosen rewards and presenting a visual 'road map' listing tasks, rewards and current progress. Results Our results showing a higher percentage of fMRI task completion by healthy children provides proof of concept data for the recommended tactics. Additional support was provided by results showing our approach generalized to several additional fMRI and event-related potential investigations and clinical populations. Discussion We proposed that some forms of task noncompliance may emerge from less than optimal reward protocols. While our findings may not directly support the effectiveness of the multiple reward compliance protocol, increased attention to how rewards are selected and delivered may aid cooperation with completing fMRI tasks Conclusion The proposed approach contributes to the pediatric neuroimaging literature by providing a useful way to conceptualize and measure task noncompliance and by providing simple cost effective tactics for improving the effectiveness of common reward-based protocols. PMID:21548928

Postoperative intraspinal subdural collections after pediatric posterior fossa tumor resection: incidence, imaging, and clinical features.

PubMed

Harreld, J H; Mohammed, N; Goldsberry, G; Li, X; Li, Y; Boop, F; Patay, Z

2015-05-01

Postoperative intraspinal subdural collections in children after posterior fossa tumor resection may temporarily hinder metastasis detection by MR imaging or CSF analysis, potentially impacting therapy. We investigated the incidence, imaging and clinical features, predisposing factors, and time course of these collections after posterior fossa tumor resection. Retrospective review of postoperative spine MRI in 243 children (5.5 ± 4.6 years of age) from our clinical data base postresection of posterior fossa tumors from October 1994 to August 2010 yielded 37 (6.0 ± 4.8 years of age) subjects positive for postoperative intraspinal subdural collections. Their extent and signal properties were recorded for postoperative (37/37), preoperative (15/37), and follow-up spine (35/37) MRI. Risk factors were compared with age-matched internal controls (n = 37, 5.9 ± 4.5 years of age). Associations of histology, hydrocephalus and cerebellar tonsillar herniation, and postoperative intracranial subdural collections with postoperative intraspinal subdural collections were assessed by the Fisher exact test or χ(2) test. The association between preoperative tumor volume and postoperative intraspinal subdural collections was assessed by the Wilcoxon rank sum test. The overall incidence of postoperative intraspinal subdural collections was 37/243 (15.2%), greatest ≤7 days postoperatively (36%); 97% were seen 0-41 days postoperatively (12.9 ± 11.0 days). They were T2 hyperintense and isointense to CSF on T1WI, homogeneously enhanced, and resolved on follow-up MR imaging (35/35). None were symptomatic. They were associated with intracranial subdural collections (P = .0011) and preoperative tonsillar herniation (P = .0228). Postoperative intraspinal subdural collections are infrequent and clinically silent, resolve spontaneously, and have a distinctive appearance. Preoperative tonsillar herniation appears to be a predisposing factor. In this series, repeat MR imaging by 4 weeks documented improvement or resolution of these collections in 88%. © 2015 by American Journal of Neuroradiology.

Test and evaluation of the 2.4-micron photorefractor ocular screening system

NASA Technical Reports Server (NTRS)

Richardson, J. R.

1985-01-01

An improved 2.4-m photorefractor ocular screening system was tested and evaluated. The photorefractor system works on the principal of obtaining a colored photograph of both human eyes; and, by analysis of the retinal reflex images, certain ocular defects can be detected such a refractive error, strabismus, and lens obstructions. The 2.4-m photorefractory system uses a 35-mm camera with a telephoto lens and an electronic flash attachment. Retinal reflex images obtained from the new 2.4-m system are significantly improved over earlier systems in image quality. Other features were also improved, notably portability and reduction in mass. A total of 706 school age children were photorefracted, 211 learning disabled and 495 middle school students. The total students having abnormal retinal reflexes were 156 or 22 percent, and 133 or 85 percent of the abnormal had refractive error indicated. Ophthalmological examination was performed on 60 of these students and refractive error was verified in 57 or 95 percent of those examined. The new 2.4-m system has a NASA patent pending and is authorized by the FDA. It provides a reliable means of rapidly screening the eyes of children and young adults for vision problems. It is especially useful for infants and other non-communicative children who cannot be screened by the more conventional methods such as the familiar E chart.

Acute pancreatitis in children and adolescents

PubMed Central

Suzuki, Mitsuyoshi; Sai, Jin Kan; Shimizu, Toshiaki

2014-01-01

In this Topic Highlight, the causes, diagnosis, and treatment of acute pancreatitis in children are discussed. Acute pancreatitis should be considered during the differential diagnosis of abdominal pain in children and requires prompt treatment because it may become life-threatening. The etiology, clinical manifestations, and course of acute pancreatitis in children are often different than in adults. Therefore, the specific features of acute pancreatitis in children must be considered. The etiology of acute pancreatitis in children is often drugs, infections, trauma, or anatomic abnormalities. Diagnosis is based on clinical symptoms (such as abdominal pain and vomiting), serum pancreatic enzyme levels, and imaging studies. Several scoring systems have been proposed for the assessment of severity, which is useful for selecting treatments and predicting prognosis. The basic pathogenesis of acute pancreatitis does not greatly differ between adults and children, and the treatments for adults and children are similar. In large part, our understanding of the pathology, optimal treatment, assessment of severity, and outcome of acute pancreatitis in children is taken from the adult literature. However, we often find that the common management of adult pancreatitis is difficult to apply to children. With advances in diagnostic techniques and treatment methods, severe acute pancreatitis in children is becoming better understood and more controllable. PMID:25400985

A rare presentation of craniopharyngioma: delayed puberty

PubMed Central

İnci, Mehmet Fatih; Özkan, Fuat; Bozkurt, Selim; Demir, Caner Feyzi

2012-01-01

Craniopharyngiomas are the most frequently encountered suprasellar tumours in children. Owing to the slow growth rate of these tumours, they are often quite large before becoming symptomatic. They are more common among children and older adults (55–74 years). Depending upon the direction of growth and tumour size, craniopharyngiomas can affect the hypothalamus, pituitary stalk, optic nerves and chiasm and carotid arteries. Compression of these neural and vascular structures frequently precipitates endocrine disorders, visual loss and an increased intracranial pressure. Hypopituitarism leading to a delayed puberty is a rare presentation of craniopharyngioma. The diagnosis of craniopharyngioma is usually made with the classic radiological imaging features based on CT and MRI. PMID:23195827

Congenital choristomas of the oral cavity in children.

PubMed

Chai, Raymond L; Ozolek, John A; Branstetter, Barton F; Mehta, Deepak K; Simons, Jeffrey P

2011-10-01

To review our institutional experience with oral cavity choristomas in children. Retrospective case series and medical record review. Medical records including clinic notes, operative reports, radiologic studies, and pathology specimens were reviewed. All imaging studies and pathology material were reviewed by a head and neck radiologist and pediatric pathologist, respectively. Sixteen patients (10 males and 6 females) with congenital oral cavity choristomas were identified. Mean age at diagnosis was 1.8 months. Location of the lesions included tongue (n = 9) and floor of mouth (n = 7). Preoperative imaging included magnetic resonance imaging (n = 6), computed tomography (n = 5), plain radiography (n = 1), and no imaging (n = 4). Radiographically, the lesions were consistently lobular with well-defined margins, but other imaging features often mimicked other masses that can arise in the tongue and floor of mouth. Symptoms were present in five of 16 patients and included difficulty feeding, swelling with upper respiratory infection, and partial airway obstruction. Complete surgical excision was performed in 15 of 16 patients; mean age at the time of surgery was 12.7 months. One patient underwent marsupialization. No complications were noted perioperatively. No recurrences of choristoma were seen. On histologic examination, the predominant component was cystic with cyst linings of respiratory epithelium (n = 5), gastric (foveolar) epithelium (n = 1), or both (n = 10). This study supports surgical excision as an effective intervention for children with oral cavity choristomas. Because the etiology of these cysts is unknown and diagnostic terminology is widely variable, we propose a more descriptive diagnosis based on the histology (i.e., lingual choristoma [or lingual developmental cyst] with respiratory epithelium or lingual choristoma [or lingual developmental cyst] with gastric epithelium). Copyright © 2011 The American Laryngological, Rhinological, and Otological Society, Inc.

MR of the pituitary in patients with Prader-Willi syndrome: size determination and imaging findings.

PubMed

Miller, L; Angulo, M; Price, D; Taneja, S

1996-01-01

Prader-Willi syndrome (PWS) is an unusual genetic disorder characterized by short stature, obesity, hypogonadism, hypotonia, cognitive impairment, and dysmorphic facies. There is an interstitial deletion of the proximal long arm of chromosome 15 in about 70 % of patients. Some of these clinical features suggest a central hypothalamic/pituitary dysfunction, and recent investigations have demonstrated a marked impairment in spontaneous growth hormone (GH) secretion. We studied 15 GH-deficient PWS patients by magnetic resonance imaging (MRI) to determine whether there was a diminution in the gross morphological size of the anterior pituitary gland, the site of GH synthesis. We also set out to catalog the pertinent imaging findings in this patient population. Our results indicate that this is the first report documenting pituitary size by MRI in PWS patients. No statistically significant difference was found in the height of the anterior pituitary gland in PWS patients compared with either normal children or children with isolated GH deficiency. An interesting imaging finding is that three of 15 patients (20 %) demonstrated complete absence of the posterior pituitary bright spot (PPBS), and a fourth patient demonstrated a small PPBS. These observations reflect an objective physiologic disturbance in the hypothalamus. The clinical and radiologic implications of these findings are discussed.

Revisiting the fear of snakes in children: the role of aposematic signalling.

PubMed

Souchet, Jérémie; Aubret, Fabien

2016-11-25

Why humans fear snakes is an old, yet unresolved debate. Its innate origin from evolutionary causes is debated against the powerful influence early experience, culture, media and religion may have on people's aversion to snakes. Here we show that the aversion to snakes in human beings may have been mistaken for an aversion to aposematic signals that are commonly displayed by snakes. A total of 635 children were asked to rate single item images as "nice" or "mean". Snakes, pets and smiley emoticon items were not rated as "mean" unless they displayed subtle aposematic signals in the form of triangular (rather than round) shapes. Another 722 children were shown images featuring two items and asked which item was "nice" and which item was "mean". This context dependent comparison triggered even sharper responses to aposematic signals. We hypothesise that early primates evolved an aversion for aposematic signals in the form of potentially harmful triangular shapes such as teeth, claws or spikes, not for snakes per se. Further, we hypothesise that this adaptation was in turn exploited by snakes in their anti-predatory threat display as a triangular head or dorsal zig-zag pattern, and is currently the basis for efficient international road-danger signalling.

The assessment of facial variation in 4747 British school children.

PubMed

Toma, Arshed M; Zhurov, Alexei I; Playle, Rebecca; Marshall, David; Rosin, Paul L; Richmond, Stephen

2012-12-01

The aim of this study is to identify key components contributing to facial variation in a large population-based sample of 15.5-year-old children (2514 females and 2233 males). The subjects were recruited from the Avon Longitudinal Study of Parents and Children. Three-dimensional facial images were obtained for each subject using two high-resolution Konica Minolta laser scanners. Twenty-one reproducible facial landmarks were identified and their coordinates were recorded. The facial images were registered using Procrustes analysis. Principal component analysis was then employed to identify independent groups of correlated coordinates. For the total data set, 14 principal components (PCs) were identified which explained 82 per cent of the total variance, with the first three components accounting for 46 per cent of the variance. Similar results were obtained for males and females separately with only subtle gender differences in some PCs. Facial features may be treated as a multidimensional statistical continuum with respect to the PCs. The first three PCs characterize the face in terms of height, width, and prominence of the nose. The derived PCs may be useful to identify and classify faces according to a scale of normality.

Inner ear dysplasia is common in children with Down syndrome (trisomy 21).

PubMed

Blaser, Susan; Propst, Evan J; Martin, Daniel; Feigenbaum, Annette; James, Adrian L; Shannon, Patrick; Papsin, Blake C

2006-12-01

Middle and external ear anomalies are well recognized in Down syndrome (DS, trisomy 21). Inner ear anomalies are much less frequently described. This study reviews inner ear morphology on imaging to determine the prevalence of cochlear and vestibular anomalies in children with DS. The authors conducted a retrospective review of imaging features of (DS) inner ear structures. Fifty-nine sequential patients with DS with imaging of the inner ear were identified by a radiology report text search program. Quantitative biometric assessment of the inner ear was performed on patients with high-resolution computed tomography or magnetic resonance images of the petrous bone. Petrous imaging was performed for evaluation of inflammatory disease or hearing loss. Spinal imaging, which included petrous views, was performed in most cases to exclude C1 to 2 dislocation, a potential complication of DS. Measurements were compared with normative data. Inner ear dysplasia is much more common in DS than previously reported. Inner ear structures are universally hypoplastic. Vestibular malformations are particularly common and a small bony island of the lateral semicircular canal (<3 mm in diameter) appears highly typical. Additional findings in some patients were persistent lateral semicircular anlage with fusion of the lateral semicircular canal and vestibule into a single cavity, vestibular aqueduct and endolymphatic sac fossa enlargement, cochlear nerve canal hypoplasia, and stenosis or duplication of the internal auditory canal. Stenosis of the external meatus, poor mastoid pneumatization, middle ear and mastoid opacification, and cholesteatoma were common, as expected.

Emotional responses to food, body dissatisfaction and other eating disorder features in children, adolescents and young adults.

PubMed

McNamara, Caroline; Hay, Phillipa; Katsikitis, Mary; Chur-Hansen, Anna

2008-01-01

We aimed to assess and compare emotional responses to different foods in relationship to eating disorder and associated features, across gender and age groups. We hypothesized that negative emotional responses to images of foods would be higher in (i) those with higher body dissatisfaction and (ii) older females. Five hundred and thirty-six (18% Grade 5, 39% Grade 8 or 9, and 43% Grade 11 or 12) school, and 93 university students participated. Emotive responses to images of foods were assessed with a PowerPoint presentation of 16 differing food and four 'neutral' images shown over 30s intervals. Responses were rated on three 10-cm visual analog scales measuring levels of happiness, fear and disgust. Body image concern was assessed with the nine-item body dissatisfaction subscale of the EDI and eating disorder symptoms with the Eating Disorder Examination Questionnaire. With increasing age all three emotional responses towards food fell and body dissatisfaction increased. Compared to females, males showed significantly higher levels of a 'happy' response to food, and in adult females a fear emotive response correlated positively with eating concern and body dissatisfaction. In men, positive emotive responses to food may be indicative of broader factors that reduce their vulnerability to eating disorders.

Application of optical longitudinal tomography for dental introscopy

NASA Astrophysics Data System (ADS)

Levin, Gennady G.; Burgansky, Alexander A.; Levandovski, Alexei G.

1997-08-01

A new method of dental introscopy in-vitro is suggested by the authors. This method implies the usage of longitudinal tomography techniques and is characterized by non-invasive and non-harmful diagnostics features, as well as interactive regime of image reconstruction which lets an operator (doctor) to control the diagnostics process in real time. He-Ne laser emission is used for obtaining of the projections. By the means of longitudinal tomography, images of different sections of an object (tooth) can be reconstructed. An experiment was held by the authors in which 100 projections of a tooth (premolar) were obtained and images of 10 different sections were reconstructed. These images were later compared to real sections of the tooth. This experiment proved that optical longitudinal tomography can be successfully used for dental introscopy. Authors claim that optical tomographic methods can be used for diagnostics of other biological objects as well. Such objects are characterized by spatial geometrical anisotropy (tubular bones, phalanxes of fingers, penis, etc.). It is especially promising to use this method for children's dentistry. the authors discuss some features of the data acquisition system for optical longitudinal tomography. Reconstruction algorithms are described. The results of experimental reconstruction are presented and advantages of this diagnostics method are discussed.

Classification of coronary artery tissues using optical coherence tomography imaging in Kawasaki disease

NASA Astrophysics Data System (ADS)

Abdolmanafi, Atefeh; Prasad, Arpan Suravi; Duong, Luc; Dahdah, Nagib

2016-03-01

Intravascular imaging modalities, such as Optical Coherence Tomography (OCT) allow nowadays improving diagnosis, treatment, follow-up, and even prevention of coronary artery disease in the adult. OCT has been recently used in children following Kawasaki disease (KD), the most prevalent acquired coronary artery disease during childhood with devastating complications. The assessment of coronary artery layers with OCT and early detection of coronary sequelae secondary to KD is a promising tool for preventing myocardial infarction in this population. More importantly, OCT is promising for tissue quantification of the inner vessel wall, including neo intima luminal myofibroblast proliferation, calcification, and fibrous scar deposits. The goal of this study is to classify the coronary artery layers of OCT imaging obtained from a series of KD patients. Our approach is focused on developing a robust Random Forest classifier built on the idea of randomly selecting a subset of features at each node and based on second- and higher-order statistical texture analysis which estimates the gray-level spatial distribution of images by specifying the local features of each pixel and extracting the statistics from their distribution. The average classification accuracy for intima and media are 76.36% and 73.72% respectively. Random forest classifier with texture analysis promises for classification of coronary artery tissue.

[X-ray computed tomographic aspects of spinal aneurysmal cysts in children].

PubMed

Bernard, C; Hoeffel, J C; Marchal, A L; Vergnat, C; Régent, D

1985-10-01

The interest of CT imaging in a case of aneurysmal bone cyst of the posterior arch of the 6th cervical vertebra in a 10 y.o. child is underlined. The value of intra tumoral densities which are relatively low, inferior to 100 Hounsfield unit is stressed but the most contributory feature in this case was the presence of a fluid level inside the cyst due to different densities of fluid components into the cyst.

Body image perceptions in Western and post-communist countries: a cross-cultural pilot study of children and parents.

PubMed

Humenikova, Lenka; Gates, Gail E

2008-07-01

The development of an unrealistic ideal body image and body size dissatisfaction among children is common in Western countries, including the USA and many European nations. However, little is known about children's body image perceptions in post-communist countries. This pilot study evaluated body image perceptions in a sample of Czech school-aged children and their parents and compared them with the perceptions of American children and parents. Ninety-seven Czech and 45 American 4th-6th graders and their parents from eight urban schools participated in this study. A previously developed silhouette body image instrument was utilized in a parent questionnaire and during child interviews to measure perceived and ideal body image perceptions of children and parents. Descriptive statistics, independent t-tests and paired t-tests were used to compare differences between children's and parents' perceived and ideal body image perceptions. Associations between body image perceptions and other variables were explored using bivariate correlations. American children had a thinner ideal body image compared with Czech children (P < 0.05). However, a larger proportion of Czech boys desired to be thinner compared with American boys (34.2% vs. 20%). Parent's ideal body image for their children did not differ by nationality (P = 0.858). While the pressure on children to look thinner was apparent among both American and Czech children, Czech children considered a larger body size as more ideal. A future study should evaluate body image perceptions and factors influencing these perceptions in a representative sample of Czech children and parents.

Altered brain structural networks in attention deficit/hyperactivity disorder children revealed by cortical thickness.

PubMed

Liu, Tian; Chen, Yanni; Li, Chenxi; Li, Youjun; Wang, Jue

2017-07-04

This study investigated the cortical thickness and topological features of human brain anatomical networks related to attention deficit/hyperactivity disorder. Data were collected from 40 attention deficit/hyperactivity disorder children and 40 normal control children. Interregional correlation matrices were established by calculating the correlations of cortical thickness between all pairs of cortical regions (68 regions) of the whole brain. Further thresholds were applied to create binary matrices to construct a series of undirected and unweighted graphs, and global, local, and nodal efficiencies were computed as a function of the network cost. These experimental results revealed abnormal cortical thickness and correlations in attention deficit/hyperactivity disorder, and showed that the brain structural networks of attention deficit/hyperactivity disorder subjects had inefficient small-world topological features. Furthermore, their topological properties were altered abnormally. In particular, decreased global efficiency combined with increased local efficiency in attention deficit/hyperactivity disorder children led to a disorder-related shift of the network topological structure toward regular networks. In addition, nodal efficiency, cortical thickness, and correlation analyses revealed that several brain regions were altered in attention deficit/hyperactivity disorder patients. These findings are in accordance with a hypothesis of dysfunctional integration and segregation of the brain in patients with attention deficit/hyperactivity disorder and provide further evidence of brain dysfunction in attention deficit/hyperactivity disorder patients by observing cortical thickness on magnetic resonance imaging.

Own- and other-race face identity recognition in children: the effects of pose and feature composition.

PubMed

Anzures, Gizelle; Kelly, David J; Pascalis, Olivier; Quinn, Paul C; Slater, Alan M; de Viviés, Xavier; Lee, Kang

2014-02-01

We used a matching-to-sample task and manipulated facial pose and feature composition to examine the other-race effect (ORE) in face identity recognition between 5 and 10 years of age. Overall, the present findings provide a genuine measure of own- and other-race face identity recognition in children that is independent of photographic and image processing. The current study also confirms the presence of an ORE in children as young as 5 years of age using a recognition paradigm that is sensitive to their developing cognitive abilities. In addition, the present findings show that with age, increasing experience with familiar classes of own-race faces and further lack of experience with unfamiliar classes of other-race faces serves to maintain the ORE between 5 and 10 years of age rather than exacerbate the effect. All age groups also showed a differential effect of stimulus facial pose in their recognition of the internal regions of own- and other-race faces. Own-race inner faces were remembered best when three-quarter poses were used during familiarization and frontal poses were used during the recognition test. In contrast, other-race inner faces were remembered best when frontal poses were used during familiarization and three-quarter poses were used during the recognition test. Thus, children encode and/or retrieve own- and other-race faces from memory in qualitatively different ways.

Own- and other-race face identity recognition in children: The effects of pose and feature composition

PubMed Central

Anzures, Gizelle; Kelly, David J.; Pascalis, Olivier; Quinn, Paul C.; Slater, Alan M.; de Viviés, Xavier; Lee, Kang

2013-01-01

We used a matching-to-sample task and manipulated facial pose and feature composition to examine the other-race effect (ORE) in face identity recognition between 5 and 10 years of age. Overall, the present findings provide a genuine measure of own- and other-race face identity recognition in children that is independent of photographic and image processing. The present study also confirms the presence of an ORE in children as young as 5 years of age using a recognition paradigm that is sensitive to their developing cognitive abilities. In addition, the present findings show that with age, increasing experience with familiar classes of own-race faces and further lack of experience with unfamiliar classes of other-race faces serves to maintain the ORE between 5 to 10 years of age rather than exacerbate the effect. All age groups also showed a differential effect of stimulus facial pose in their recognition of the internal regions of own- and other-race faces. Own-race inner faces were remembered best when three-quarter poses were used during familiarization and frontal poses were used during the recognition test. In contrast, other-race inner faces were remembered best when frontal poses were used during familiarization and three-quarter poses were used during the recognition test. Thus, children encode and/or retrieve own- and other-race faces from memory in qualitatively different ways. PMID:23731287

Clinical features and neuroimaging (CT and MRI) findings in presumed Zika virus related congenital infection and microcephaly: retrospective case series study.

PubMed

de Fatima Vasco Aragao, Maria; van der Linden, Vanessa; Brainer-Lima, Alessandra Mertens; Coeli, Regina Ramos; Rocha, Maria Angela; Sobral da Silva, Paula; Durce Costa Gomes de Carvalho, Maria; van der Linden, Ana; Cesario de Holanda, Arthur; Valenca, Marcelo Moraes

2016-04-13

To report radiological findings observed in computed tomography (CT) and magnetic resonance imaging (MRI) scans of the first cases of congenital infection and microcephaly presumably associated with the Zika virus in the current Brazilian epidemic. Retrospective study with a case series. Association for Assistance of Disabled Children (AACD), Pernambuco state, Brazil. 23 children with a diagnosis of congenital infection presumably associated with the Zika virus during the Brazilian microcephaly epidemic. Types of abnormalities and the radiological pattern of lesions identified on CT and MRI brain scans. Six of the 23 children tested positive for IgM antibodies to Zika virus in cerebrospinal fluid. The other 17 children met the protocol criteria for congenital infection presumably associated with the Zika virus, even without being tested for IgM antibodies to the virus--the test was not yet available on a routine basis. Of the 23 children, 15 underwent CT, seven underwent both CT and MRI, and one underwent MRI. Of the 22 children who underwent CT, all had calcifications in the junction between cortical and subcortical white matter, 21 (95%) had malformations of cortical development, 20 (91%) had a decreased brain volume, 19 (86%) had ventriculomegaly, and 11 (50%) had hypoplasia of the cerebellum or brainstem. Of the eight children who underwent MRI, all had calcifications in the junction between cortical and subcortical white matter, malformations of cortical development occurring predominantly in the frontal lobes, and ventriculomegaly. Seven of the eight (88%) children had enlarged cisterna magna, seven (88%) delayed myelination, and six each (75%) a moderate to severe decrease in brain volume, simplified gyral pattern, and abnormalities of the corpus callosum (38% hypogenesis and 38% hypoplasia). Malformations were symmetrical in 75% of the cases. Severe cerebral damage was found on imaging in most of the children in this case series with congenital infection presumably associated with the Zika virus. The features most commonly found were brain calcifications in the junction between cortical and subcortical white matter associated with malformations of cortical development, often with a simplified gyral pattern and predominance of pachygyria or polymicrogyria in the frontal lobes. Additional findings were enlarged cisterna magna, abnormalities of corpus callosum (hypoplasia or hypogenesis), ventriculomegaly, delayed myelination, and hypoplasia of the cerebellum and the brainstem. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Clinical features and neuroimaging (CT and MRI) findings in presumed Zika virus related congenital infection and microcephaly: retrospective case series study

PubMed Central

van der Linden, Vanessa; Brainer-Lima, Alessandra Mertens; Coeli, Regina Ramos; Rocha, Maria Angela; Sobral da Silva, Paula; Durce Costa Gomes de Carvalho, Maria; van der Linden, Ana; Cesario de Holanda, Arthur; Valenca, Marcelo Moraes

2016-01-01

Objective To report radiological findings observed in computed tomography (CT) and magnetic resonance imaging (MRI) scans of the first cases of congenital infection and microcephaly presumably associated with the Zika virus in the current Brazilian epidemic. Design Retrospective study with a case series. Setting Association for Assistance of Disabled Children (AACD), Pernambuco state, Brazil. Participants 23 children with a diagnosis of congenital infection presumably associated with the Zika virus during the Brazilian microcephaly epidemic. Main outcome measures Types of abnormalities and the radiological pattern of lesions identified on CT and MRI brain scans. Results Six of the 23 children tested positive for IgM antibodies to Zika virus in cerebrospinal fluid. The other 17 children met the protocol criteria for congenital infection presumably associated with the Zika virus, even without being tested for IgM antibodies to the virus—the test was not yet available on a routine basis. Of the 23 children, 15 underwent CT, seven underwent both CT and MRI, and one underwent MRI. Of the 22 children who underwent CT, all had calcifications in the junction between cortical and subcortical white matter, 21 (95%) had malformations of cortical development, 20 (91%) had a decreased brain volume, 19 (86%) had ventriculomegaly, and 11 (50%) had hypoplasia of the cerebellum or brainstem. Of the eight children who underwent MRI, all had calcifications in the junction between cortical and subcortical white matter, malformations of cortical development occurring predominantly in the frontal lobes, and ventriculomegaly. Seven of the eight (88%) children had enlarged cisterna magna, seven (88%) delayed myelination, and six each (75%) a moderate to severe decrease in brain volume, simplified gyral pattern, and abnormalities of the corpus callosum (38% hypogenesis and 38% hypoplasia). Malformations were symmetrical in 75% of the cases. Conclusion Severe cerebral damage was found on imaging in most of the children in this case series with congenital infection presumably associated with the Zika virus. The features most commonly found were brain calcifications in the junction between cortical and subcortical white matter associated with malformations of cortical development, often with a simplified gyral pattern and predominance of pachygyria or polymicrogyria in the frontal lobes. Additional findings were enlarged cisterna magna, abnormalities of corpus callosum (hypoplasia or hypogenesis), ventriculomegaly, delayed myelination, and hypoplasia of the cerebellum and the brainstem. PMID:27075009

Natural image classification driven by human brain activity

NASA Astrophysics Data System (ADS)

Zhang, Dai; Peng, Hanyang; Wang, Jinqiao; Tang, Ming; Xue, Rong; Zuo, Zhentao

2016-03-01

Natural image classification has been a hot topic in computer vision and pattern recognition research field. Since the performance of an image classification system can be improved by feature selection, many image feature selection methods have been developed. However, the existing supervised feature selection methods are typically driven by the class label information that are identical for different samples from the same class, ignoring with-in class image variability and therefore degrading the feature selection performance. In this study, we propose a novel feature selection method, driven by human brain activity signals collected using fMRI technique when human subjects were viewing natural images of different categories. The fMRI signals associated with subjects viewing different images encode the human perception of natural images, and therefore may capture image variability within- and cross- categories. We then select image features with the guidance of fMRI signals from brain regions with active response to image viewing. Particularly, bag of words features based on GIST descriptor are extracted from natural images for classification, and a sparse regression base feature selection method is adapted to select image features that can best predict fMRI signals. Finally, a classification model is built on the select image features to classify images without fMRI signals. The validation experiments for classifying images from 4 categories of two subjects have demonstrated that our method could achieve much better classification performance than the classifiers built on image feature selected by traditional feature selection methods.

Low back pain in school-age children: risk factors, clinical features and diagnostic managment.

PubMed

Boćkowski, L; Sobaniec, W; Kułak, W; Smigielska-Kuzia, J; Sendrowski, K; Roszkowska, M

2007-01-01

Low back pain (LBP) is common in adult population, and it is becoming a serious health concern in adolescents. On surveys, about every fifth child in the school-age reports LBP. The study objective was to analysis the natural history, risk factors, clinical symptoms, causes and diagnostic management in school-age children hospitalized with LBP. The study group consisted of 36 patients at the age between 10 and 18 years, 22 girls and 14 boys suffering from LBP hospitalized in our Department of Pediatric Neurology and Rehabilitation in years 2000-2004. The mean age of clinical onset of LBP in our group was 14.7 years, earlier in girls, later in boys. We find the family history of LBP in 50% children. Most frequent factors associated with LBP were: spina bifida (16.7%) and incorrect posture (13.9%). Half of patients pointed the factor initialising LBP: rapid, incoordinated move (39%) or heavy load rise (11%). 58% of patients present the symptoms of ischialgia. Diagnostic imaging showed disc protrusion in 11 children (31%) 6 in computed tomography, 4 in magnetic resonance imaging and 1 in X-Ray examination only. Other causes of LBP included: spondylolysis in 2 patients, Scheuermann disease in one case and juvenile reumatoid arthritis in one case. Some school-age children suffering on low back pain, particulary with sciatic neuralgia symptoms seek medical care in hospital. Althought the main causes are mechanical, associated with lack of physical activity or strenous exercise, serious diagnostic managment is strongly recommended.

Presentation, course, and outcome of postneonatal presentations of vein of Galen malformation: a large, single-institution case series.

PubMed

Gopalan, Vignesh; Rennie, Adam; Robertson, Fergus; Kanagarajah, Lakshmi; Toolis, Claire; Bhate, Sanjay; Ganesan, Vijeya

2018-04-01

To describe presentation, clinical course, and outcome in postneonatal presentations of vein of Galen malformation (VGM). Children older than 28 days presenting with VGM (from 2006-2016) were included. Notes/scans were reviewed. Outcome was dichotomized into 'good' or 'poor' using the Recovery and Recurrence Questionnaire. Logistic regression was performed to explore relationships between clinico-radiological features and outcome. Thirty-one children (18 males, 13 females) were included, presenting at a median age of 9.6 months (range 1.2mo-11y 7mo), most commonly with macrocrania (n=24) and prominent facial veins (n=9). Seven had evidence of cardiac failure. VGM morphology was choroidal in 19. Hydrocephalus (n=24) and loss of white matter volume (n=15) were the most common imaging abnormalities. Twenty-nine patients underwent glue embolization (median two per child). Angiographic shunt closure was achieved in 21 out of 28 survivors. Three children died of intracranial haemorrhage (1y, 6y, and 30d after embolization). Ten patients underwent neurosurgical procedures; to treat haemorrhage in four, and hydrocephalus in the rest. Outcome was categorized as good in 20 out of 28 survivors, but this was not predictable on the basis of the variables listed above. Postneonatally presenting VGM has distinctive clinico-radiological features, attributable to venous hypertension. Endovascular treatment is associated with good outcomes, but more specific prognostic prediction was not possible within this cohort. Clinical and radiological features in older children with vein of Galen malformation relate to venous hypertension. Outcome is good in most cases with endovascular therapy. Mortality is low but is related to intracranial haemorrhage. © 2018 Mac Keith Press.

[Pheochromocytoma and paraganglioma in childhood: a report of 2 cases report].

PubMed

Mosquera Gorostidi, A; Justo Ranera, A; Zakirian Denis, S E; González Temprano, N; Sagaseta de Ilúrdoz Uranga, M; Molina Garicano, J

2015-01-01

Pheochromocytomas and paragangliomas are rare neuroendocrine tumors in children and most of them are sporadic. However, they represent the most common endocrine tumor in childhood, and hereditary tumor syndromes are most relevant in these age. Advances in genetic, biochemistry and imaging techniques have revised the management of these tumors; thus A biochemical study should be always initiated once the clinical diagnosis is suspected, followed by imaging and molecular studies, particularly in the context of known familial disease. The diagnostic and therapeutic features are reviewed after the presentation of two clinical cases, where the second one is a patient with type 1 Neurofibromatosis. Copyright © 2014. Published by Elsevier Espana.

Hippocampal-neocortical functional reorganization underlies children's cognitive development.

PubMed

Qin, Shaozheng; Cho, Soohyun; Chen, Tianwen; Rosenberg-Lee, Miriam; Geary, David C; Menon, Vinod

2014-09-01

The importance of the hippocampal system for rapid learning and memory is well recognized, but its contributions to a cardinal feature of children's cognitive development-the transition from procedure-based to memory-based problem-solving strategies-are unknown. Here we show that the hippocampal system is pivotal to this strategic transition. Longitudinal functional magnetic resonance imaging (fMRI) in 7-9-year-old children revealed that the transition from use of counting to memory-based retrieval parallels increased hippocampal and decreased prefrontal-parietal engagement during arithmetic problem solving. Longitudinal improvements in retrieval-strategy use were predicted by increased hippocampal-neocortical functional connectivity. Beyond childhood, retrieval-strategy use continued to improve through adolescence into adulthood and was associated with decreased activation but more stable interproblem representations in the hippocampus. Our findings provide insights into the dynamic role of the hippocampus in the maturation of memory-based problem solving and establish a critical link between hippocampal-neocortical reorganization and children's cognitive development.

[Risk factors for interictal epileptiform discharges on electroencephalogram in children with spastic hemiplegic cerebral palsy].

PubMed

Li, Su-Yun; Qian, Xu-Guang; Zhao, Yi-Li; Fu, Wen-Jie; Tan, Xiao-Ru; Liu, Zhen-Huan

2015-12-01

To investigate the clinical symptoms and features of interictal epileptiform discharges (IED) on electroencephalogram (EEG) in children with spastic hemiplegic cerebral palsy (CP) and to analyze the risk factors for IED. Eighty-three children with spastic hemiplegic CP were recruited, and their clinical data, results of video-electroencephalogram, imaging findings, and cognitive levels were collected. The influencing factors for IED were determined by multiple logistic regression analysis. The incidence of epilepsy was 13% in children with spastic hemiplegic CP; 34% of these cases had IED. The incidence of epilepsy in children with IED (32%) was significantly higher than that in those without IED (4%) (P<0.01). The incidence of IED in children with complications and brain cortex impairment increased significantly (P<0.01). The incidence of IED varied significantly between patients with different cognitive levels (P<0.01). Brain cortex impairment (OR=11.521) and low cognitive level (OR=2.238)were risk factors for IED in children with spastic hemiplegic CP (P<0.05). Spastic hemiplegic CP is often found with IED on EEG, and the incidence of epilepsy is higher in children with IED than in those without IED. Brain cortex impairment and low cognitive level have predictive values for IED in children with spastic hemiplegic CP.

Competitive Advantage of PET/MRI

PubMed Central

Jadvar, Hossein; Colletti, Patrick M.

2013-01-01

Multimodality imaging has made great strides in the imaging evaluation of patients with a variety of diseases. Positron emission tomography/computed tomography (PET/CT) is now established as the imaging modality of choice in many clinical conditions, particularly in oncology. While the initial development of combined PET/magnetic resonance imaging (PET/MRI) was in the preclinical arena, hybrid PET/MR scanners are now available for clinical use. PET/MRI combines the unique features of MRI including excellent soft tissue contrast, diffusion-weighted imaging, dynamic contrast-enhanced imaging, fMRI and other specialized sequences as well as MR spectroscopy with the quantitative physiologic information that is provided by PET. Most evidence for the potential clinical utility of PET/MRI is based on studies performed with side-by-side comparison or software-fused MRI and PET images. Data on distinctive utility of hybrid PET/MRI are rapidly emerging. There are potential competitive advantages of PET/MRI over PET/CT. In general, PET/MRI may be preferred over PET/CT where the unique features of MRI provide more robust imaging evaluation in certain clinical settings. The exact role and potential utility of simultaneous data acquisition in specific research and clinical settings will need to be defined. It may be that simultaneous PET/MRI will be best suited for clinical situations that are disease-specific, organ-specific, related to diseases of the children or in those patients undergoing repeated imaging for whom cumulative radiation dose must be kept as low as reasonably achievable. PET/MRI also offers interesting opportunities for use of dual modality probes. Upon clear definition of clinical utility, other important and practical issues related to business operational model, clinical workflow and reimbursement will also be resolved. PMID:23791129

Competitive advantage of PET/MRI.

PubMed

Jadvar, Hossein; Colletti, Patrick M

2014-01-01

Multimodality imaging has made great strides in the imaging evaluation of patients with a variety of diseases. Positron emission tomography/computed tomography (PET/CT) is now established as the imaging modality of choice in many clinical conditions, particularly in oncology. While the initial development of combined PET/magnetic resonance imaging (PET/MRI) was in the preclinical arena, hybrid PET/MR scanners are now available for clinical use. PET/MRI combines the unique features of MRI including excellent soft tissue contrast, diffusion-weighted imaging, dynamic contrast-enhanced imaging, fMRI and other specialized sequences as well as MR spectroscopy with the quantitative physiologic information that is provided by PET. Most evidence for the potential clinical utility of PET/MRI is based on studies performed with side-by-side comparison or software-fused MRI and PET images. Data on distinctive utility of hybrid PET/MRI are rapidly emerging. There are potential competitive advantages of PET/MRI over PET/CT. In general, PET/MRI may be preferred over PET/CT where the unique features of MRI provide more robust imaging evaluation in certain clinical settings. The exact role and potential utility of simultaneous data acquisition in specific research and clinical settings will need to be defined. It may be that simultaneous PET/MRI will be best suited for clinical situations that are disease-specific, organ-specific, related to diseases of the children or in those patients undergoing repeated imaging for whom cumulative radiation dose must be kept as low as reasonably achievable. PET/MRI also offers interesting opportunities for use of dual modality probes. Upon clear definition of clinical utility, other important and practical issues related to business operational model, clinical workflow and reimbursement will also be resolved. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Baby schema in human and animal faces induces cuteness perception and gaze allocation in children.

PubMed

Borgi, Marta; Cogliati-Dezza, Irene; Brelsford, Victoria; Meints, Kerstin; Cirulli, Francesca

2014-01-01

The baby schema concept was originally proposed as a set of infantile traits with high appeal for humans, subsequently shown to elicit caretaking behavior and to affect cuteness perception and attentional processes. However, it is unclear whether the response to the baby schema may be extended to the human-animal bond context. Moreover, questions remain as to whether the cute response is constant and persistent or whether it changes with development. In the present study we parametrically manipulated the baby schema in images of humans, dogs, and cats. We analyzed responses of 3-6 year-old children, using both explicit (i.e., cuteness ratings) and implicit (i.e., eye gaze patterns) measures. By means of eye-tracking, we assessed children's preferential attention to images varying only for the degree of baby schema and explored participants' fixation patterns during a cuteness task. For comparative purposes, cuteness ratings were also obtained in a sample of adults. Overall our results show that the response to an infantile facial configuration emerges early during development. In children, the baby schema affects both cuteness perception and gaze allocation to infantile stimuli and to specific facial features, an effect not simply limited to human faces. In line with previous research, results confirm human positive appraisal toward animals and inform both educational and therapeutic interventions involving pets, helping to minimize risk factors (e.g., dog bites).

"For Jimmy and the boys and girls of America": publicizing childhood cancers in twentieth-century America.

PubMed

Krueger, Gretchen

2007-01-01

This paper examines a collection of images of children printed in cancer education and fund-raising materials distributed by voluntary health organizations, released by public relations departments of specialized cancer hospitals, and featured in popular magazines and newspapers beginning in the late 1940s. Children represented only a small fraction of all persons with cancer, yet they became a key component of the media campaign for the disease. What narratives were embedded in the photographs and profiles? Like the March of Dimes' use of young polio patients to promote their programs, "poster children" were strategically used throughout the mid-to-late twentieth century to advance principles of early cancer detection and prompt treatment; to illustrate or, at times, exaggerate promising biomedical advances in the field; and to elicit emotional responses and donations from a wide audience during the escalation of the war against cancer.

Three-dimensional textural features of conventional MRI improve diagnostic classification of childhood brain tumours.

PubMed

Fetit, Ahmed E; Novak, Jan; Peet, Andrew C; Arvanitits, Theodoros N

2015-09-01

The aim of this study was to assess the efficacy of three-dimensional texture analysis (3D TA) of conventional MR images for the classification of childhood brain tumours in a quantitative manner. The dataset comprised pre-contrast T1 - and T2-weighted MRI series obtained from 48 children diagnosed with brain tumours (medulloblastoma, pilocytic astrocytoma and ependymoma). 3D and 2D TA were carried out on the images using first-, second- and higher order statistical methods. Six supervised classification algorithms were trained with the most influential 3D and 2D textural features, and their performances in the classification of tumour types, using the two feature sets, were compared. Model validation was carried out using the leave-one-out cross-validation (LOOCV) approach, as well as stratified 10-fold cross-validation, in order to provide additional reassurance. McNemar's test was used to test the statistical significance of any improvements demonstrated by 3D-trained classifiers. Supervised learning models trained with 3D textural features showed improved classification performances to those trained with conventional 2D features. For instance, a neural network classifier showed 12% improvement in area under the receiver operator characteristics curve (AUC) and 19% in overall classification accuracy. These improvements were statistically significant for four of the tested classifiers, as per McNemar's tests. This study shows that 3D textural features extracted from conventional T1 - and T2-weighted images can improve the diagnostic classification of childhood brain tumours. Long-term benefits of accurate, yet non-invasive, diagnostic aids include a reduction in surgical procedures, improvement in surgical and therapy planning, and support of discussions with patients' families. It remains necessary, however, to extend the analysis to a multicentre cohort in order to assess the scalability of the techniques used. Copyright © 2015 John Wiley & Sons, Ltd.

Unsupervised feature learning for autonomous rock image classification

NASA Astrophysics Data System (ADS)

Shu, Lei; McIsaac, Kenneth; Osinski, Gordon R.; Francis, Raymond

2017-09-01

Autonomous rock image classification can enhance the capability of robots for geological detection and enlarge the scientific returns, both in investigation on Earth and planetary surface exploration on Mars. Since rock textural images are usually inhomogeneous and manually hand-crafting features is not always reliable, we propose an unsupervised feature learning method to autonomously learn the feature representation for rock images. In our tests, rock image classification using the learned features shows that the learned features can outperform manually selected features. Self-taught learning is also proposed to learn the feature representation from a large database of unlabelled rock images of mixed class. The learned features can then be used repeatedly for classification of any subclass. This takes advantage of the large dataset of unlabelled rock images and learns a general feature representation for many kinds of rocks. We show experimental results supporting the feasibility of self-taught learning on rock images.

Atypical magnetic resonance imaging features in subacute sclerosing panencephalitis.

PubMed

Das, Biplab; Goyal, Manoj Kumar; Modi, Manish; Mehta, Sahil; Chakravarthi, Sudheer; Lal, Vivek; Vyas, Sameer

2016-01-01

Subacute sclerosing panencephalitis (SSPE) is rare chronic, progressive encephalitis that affects primarily children and young adults, caused by a persistent infection with measles virus. No cure for SSPE exists, but the condition can be managed by medication if treatment is started at an early stage. Heterogeneity of imaging findings in SSPE is not very uncommon. But pial and gyral enhancements are very rarely noticed. Significant asymmetric onset as well as pial-gyral enhancements is not reported. Herein we present a case of 16 years adolescent of SSPE having remarkable asymmetric pial-gyral enhancements, which were misinterpreted as tubercular infection. Early diagnosis and treatment is encouraging in SSPE, although it is not curable with current therapy. Clinico-radiological and electrophysiological correlation is very important in diagnosis of SSPE, more gravely in patients having atypical image findings as in our index case.

Leigh syndrome: MRI findings in two children.

PubMed

Kartikasalwah, Al; Lh, Ngu

2010-01-01

Leigh syndrome is a progressive neurodegenerative disorder of childhood. The symmetrical necrotic lesions in the basal ganglia and/or brainstem which appear as hyperintense lesions on T2-weighted MRI is characteristic and one of the essential diagnostic criteria. Recognising this MR imaging pattern in a child with neurological problems should prompt the clinician to investigate for Leigh syndrome. We present here two cases of Leigh syndrome due to different biochemical/genetic defects, and discuss the subtle differences in their MR neuroimaging features.

Online coupled camera pose estimation and dense reconstruction from video

DOEpatents

Medioni, Gerard; Kang, Zhuoliang

2016-11-01

A product may receive each image in a stream of video image of a scene, and before processing the next image, generate information indicative of the position and orientation of an image capture device that captured the image at the time of capturing the image. The product may do so by identifying distinguishable image feature points in the image; determining a coordinate for each identified image feature point; and for each identified image feature point, attempting to identify one or more distinguishable model feature points in a three dimensional (3D) model of at least a portion of the scene that appears likely to correspond to the identified image feature point. Thereafter, the product may find each of the following that, in combination, produce a consistent projection transformation of the 3D model onto the image: a subset of the identified image feature points for which one or more corresponding model feature points were identified; and, for each image feature point that has multiple likely corresponding model feature points, one of the corresponding model feature points. The product may update a 3D model of at least a portion of the scene following the receipt of each video image and before processing the next video image base on the generated information indicative of the position and orientation of the image capture device at the time of capturing the received image. The product may display the updated 3D model after each update to the model.

The syndrome of perisylvian polymicrogyria with congenital arthrogryposis.

PubMed

Poduri, Annapurna; Chitsazzadeh, Vida; D'Arrigo, Stefano; Fedrizzi, Ermellina; Pantaleoni, Chiara; Riva, Daria; Busse, Claudia; Küster, Helmut; Duplessis, Adre; Gaitanis, John; Sahin, Mustafa; Garganta, Cheryl; Topcu, Meral; Dies, Kira A; Barry, Brenda J; Partlow, Jennifer; Barkovich, A James; Walsh, Christopher A; Chang, Bernard S

2010-08-01

Bilateral perisylvian polymicrogyria (BPP) is a well-recognized malformation of cortical development commonly associated with epilepsy, cognitive impairment, and oromotor apraxia. Reports have suggested the association of BPP with arthrogryposis multiplex congenita. We sought to investigate the clinical, electrophysiological, and neuroradiological features of this combined syndrome to determine if there are unique features that distinguish BPP with arthrogryposis from BPP alone. Cases of BPP with congenital arthrogryposis were identified from a large research database of individuals with polymicrogyria. Clinical features (including oromotor function, seizures, and joint contractures), MR brain imaging, and results of neuromuscular testing were reviewed. Ten cases of BPP with congenital arthrogryposis were identified. Most cases had some degree of oromotor apraxia. Only a few had seizures, but a majority of cases were still young children. Electrophysiological studies provided evidence for lower motor neuron or peripheral nervous system involvement. On brain imaging, bilateral polymicrogyria (PMG) centered along the Sylvian fissures was seen, with variable extension frontally or parietally; no other cortical malformations were present. We did not identify obvious neuroimaging features that distinguish this syndrome from that of BPP without arthrogryposis. The clinical and neuroimaging features of the syndrome of BPP with congenital arthrogryposis appear similar to those seen in cases of isolated BPP without joint contractures, but electrophysiological studies often demonstrate coexistent lower motor neuron or peripheral nervous system pathology. These findings suggest that BPP with arthrogryposis may have a genetic etiology with effects at two levels of the neuraxis. Copyright 2009 Elsevier B.V. All rights reserved.

Diagnosing aneurysmal and unicameral bone cysts with magnetic resonance imaging.

PubMed

Sullivan, R J; Meyer, J S; Dormans, J P; Davidson, R S

1999-09-01

The differential between aneurysmal bone cysts and unicameral bone cysts usually is clear clinically and radiographically. Occasionally there are cases in which the diagnosis is not clear. Because natural history and treatment are different, the ability to distinguish between these two entities before surgery is important. The authors reviewed, in a blinded fashion, the preoperative magnetic resonance images to investigate criteria that could be used to differentiate between the two lesions. All patients had operative or pathologic confirmation of an aneurysmal bone cyst or unicameral bone cyst. The authors analyzed the preoperative magnetic resonance images of 14 patients with diagnostically difficult bone cysts (eight children with unicameral bone cysts and six children with aneurysmal bone cysts) and correlated these findings with diagnosis after biopsy or cyst aspiration and contrast injection. The presence of a double density fluid level within the lesion strongly indicated that the lesion was an aneurysmal bone cyst, rather than a unicameral bone cyst. Other criteria that suggested the lesion was an aneurysmal bone cyst were the presence of septations within the lesion and signal characteristics of low intensity on T1 images and high intensity on T2 images. The authors identified a way of helping to differentiate between aneurysmal bone cysts and unicameral bone cysts on magnetic resonance images. Double density fluid level, septation, and low signal on T1 images and high signal on T2 images strongly suggest the bone cyst in question is an aneurysmal bone cyst, rather than a unicameral bone cyst. This may be helpful before surgery for the child who has a cystic lesion for which radiographic features do not allow a clear differentiation of unicameral bone cyst from aneurysmal bone cyst.

The Role of Book Features in Young Children's Transfer of Information from Picture Books to Real-World Contexts

PubMed Central

Strouse, Gabrielle A.; Nyhout, Angela; Ganea, Patricia A.

2018-01-01

Picture books are an important source of new language, concepts, and lessons for young children. A large body of research has documented the nature of parent-child interactions during shared book reading. A new body of research has begun to investigate the features of picture books that support children's learning and transfer of that information to the real world. In this paper, we discuss how children's symbolic development, analogical reasoning, and reasoning about fantasy may constrain their ability to take away content information from picture books. We then review the nascent body of findings that has focused on the impact of picture book features on children's learning and transfer of words and letters, science concepts, problem solutions, and morals from picture books. In each domain of learning we discuss how children's development may interact with book features to impact their learning. We conclude that children's ability to learn and transfer content from picture books can be disrupted by some book features and research should directly examine the interaction between children's developing abilities and book characteristics on children's learning. PMID:29467690

The Role of Book Features in Young Children's Transfer of Information from Picture Books to Real-World Contexts.

PubMed

Strouse, Gabrielle A; Nyhout, Angela; Ganea, Patricia A

2018-01-01

Picture books are an important source of new language, concepts, and lessons for young children. A large body of research has documented the nature of parent-child interactions during shared book reading. A new body of research has begun to investigate the features of picture books that support children's learning and transfer of that information to the real world. In this paper, we discuss how children's symbolic development, analogical reasoning, and reasoning about fantasy may constrain their ability to take away content information from picture books. We then review the nascent body of findings that has focused on the impact of picture book features on children's learning and transfer of words and letters, science concepts, problem solutions, and morals from picture books. In each domain of learning we discuss how children's development may interact with book features to impact their learning. We conclude that children's ability to learn and transfer content from picture books can be disrupted by some book features and research should directly examine the interaction between children's developing abilities and book characteristics on children's learning.

Enhancing the Early Reading Skills: Examining the Print Features of Preschool Children's Book

ERIC Educational Resources Information Center

Cetin, Ozlem Simsek; Bay, Neslihan

2015-01-01

The purpose of this study is to examine the uses of print features in preschool children's books in the US and Turkey, in order to helping adults to understand print features and supporting children's print awareness. In this context, two hundred children's books was randomly selected from the US and Turkey. Document analysis was used for…

[Central diabetes insipidus: diagnostic difficulties].

PubMed

Matoussi, N; Aissa, K; Fitouri, Z; Hajji, M; Makni, S; Bellagha, I; Ben Becher, S

2008-06-01

Central diabetes insipidus is rare in children. Characteristic features include polyuria and polydipsia due to arginine vasopressin deficiency. The differential diagnosis of polyuric states may be difficult. Etiologic diagnosis of central diabetes insipidus may be an equally difficult task. To specify the difficulties encountered in the diagnosis of central diabetes insipidus and to point out features of the etiologic work-up and of long-term follow-up of children with idiopathic central diabetes insipidus. A retrospective study of 12 children admitted with a polyuria/polydipsia syndrome to the pediatric - consultation and emergency unit of the children's hospital of Tunis between 1988 and 2005. Children with acquired nephrogenic central diabetes insipidus were excluded. Fourteen-hour fluid restriction test and/or desmopressin test were used without plasma vasopressin measurement. Eight patients were classified as having central diabetes insipidus, which was severe in seven children and partial in one girl. One patient was classified as having primary polydipsia. The diagnosis remains unclear in three patients. The etiological work-up in eight patients with central diabetes insipidus enabled the identification of Langerhan's-cell histiocytosis in two patients and neurosurgical trauma in one. The cause was considered idiopathic in five patients. The median follow-up of the five patients with idiopathic central diabetes insipidus was five years two months plus or minus six years seven months (range five months, 14.5 years). During this follow-up, neither brain magnetic resonance imaging scans findings nor anterior pituitary function have changed. Fluid restriction and desmopressin tests did not enable an accurate distinction between partial diabetes insipidus and primary polydipsia. Regular surveillance is warranted in patients with idiopathic central diabetes insipidus to identify potential etiologies.

Librarian's Image in Children's Fiction.

ERIC Educational Resources Information Center

Kitchen, Barbara

The image of the librarian has engendered much discussion among professional librarians. Children's fiction and picture books are good mediums in which to examine the image of the librarian, since they provide impressionable children some of their earliest cultural knowledge. Children's authors can supply powerful images by means of text and…

Image ratio features for facial expression recognition application.

PubMed

Song, Mingli; Tao, Dacheng; Liu, Zicheng; Li, Xuelong; Zhou, Mengchu

2010-06-01

Video-based facial expression recognition is a challenging problem in computer vision and human-computer interaction. To target this problem, texture features have been extracted and widely used, because they can capture image intensity changes raised by skin deformation. However, existing texture features encounter problems with albedo and lighting variations. To solve both problems, we propose a new texture feature called image ratio features. Compared with previously proposed texture features, e.g., high gradient component features, image ratio features are more robust to albedo and lighting variations. In addition, to further improve facial expression recognition accuracy based on image ratio features, we combine image ratio features with facial animation parameters (FAPs), which describe the geometric motions of facial feature points. The performance evaluation is based on the Carnegie Mellon University Cohn-Kanade database, our own database, and the Japanese Female Facial Expression database. Experimental results show that the proposed image ratio feature is more robust to albedo and lighting variations, and the combination of image ratio features and FAPs outperforms each feature alone. In addition, we study asymmetric facial expressions based on our own facial expression database and demonstrate the superior performance of our combined expression recognition system.

Scalable High Performance Image Registration Framework by Unsupervised Deep Feature Representations Learning

PubMed Central

Wu, Guorong; Kim, Minjeong; Wang, Qian; Munsell, Brent C.

2015-01-01

Feature selection is a critical step in deformable image registration. In particular, selecting the most discriminative features that accurately and concisely describe complex morphological patterns in image patches improves correspondence detection, which in turn improves image registration accuracy. Furthermore, since more and more imaging modalities are being invented to better identify morphological changes in medical imaging data,, the development of deformable image registration method that scales well to new image modalities or new image applications with little to no human intervention would have a significant impact on the medical image analysis community. To address these concerns, a learning-based image registration framework is proposed that uses deep learning to discover compact and highly discriminative features upon observed imaging data. Specifically, the proposed feature selection method uses a convolutional stacked auto-encoder to identify intrinsic deep feature representations in image patches. Since deep learning is an unsupervised learning method, no ground truth label knowledge is required. This makes the proposed feature selection method more flexible to new imaging modalities since feature representations can be directly learned from the observed imaging data in a very short amount of time. Using the LONI and ADNI imaging datasets, image registration performance was compared to two existing state-of-the-art deformable image registration methods that use handcrafted features. To demonstrate the scalability of the proposed image registration framework image registration experiments were conducted on 7.0-tesla brain MR images. In all experiments, the results showed the new image registration framework consistently demonstrated more accurate registration results when compared to state-of-the-art. PMID:26552069

Scalable High-Performance Image Registration Framework by Unsupervised Deep Feature Representations Learning.

PubMed

Wu, Guorong; Kim, Minjeong; Wang, Qian; Munsell, Brent C; Shen, Dinggang

2016-07-01

Feature selection is a critical step in deformable image registration. In particular, selecting the most discriminative features that accurately and concisely describe complex morphological patterns in image patches improves correspondence detection, which in turn improves image registration accuracy. Furthermore, since more and more imaging modalities are being invented to better identify morphological changes in medical imaging data, the development of deformable image registration method that scales well to new image modalities or new image applications with little to no human intervention would have a significant impact on the medical image analysis community. To address these concerns, a learning-based image registration framework is proposed that uses deep learning to discover compact and highly discriminative features upon observed imaging data. Specifically, the proposed feature selection method uses a convolutional stacked autoencoder to identify intrinsic deep feature representations in image patches. Since deep learning is an unsupervised learning method, no ground truth label knowledge is required. This makes the proposed feature selection method more flexible to new imaging modalities since feature representations can be directly learned from the observed imaging data in a very short amount of time. Using the LONI and ADNI imaging datasets, image registration performance was compared to two existing state-of-the-art deformable image registration methods that use handcrafted features. To demonstrate the scalability of the proposed image registration framework, image registration experiments were conducted on 7.0-T brain MR images. In all experiments, the results showed that the new image registration framework consistently demonstrated more accurate registration results when compared to state of the art.

The semiology of febrile seizures: Focal features are frequent.

PubMed

Takasu, Michihiko; Kubota, Tetsuo; Tsuji, Takeshi; Kurahashi, Hirokazu; Numoto, Shingo; Watanabe, Kazuyoshi; Okumura, Akihisa

2017-08-01

To clarify the semiology of febrile seizures (FS) and to determine the frequency of FS with symptoms suggestive of focal onset. FS symptoms in children were reported within 24h of seizure onset by the parents using a structured questionnaire consisting principally of closed-ended questions. We focused on events at seizure commencement, including changes in behavior and facial expression, and ocular and oral symptoms. We also investigated the autonomic and motor symptoms developing during seizures. The presence or absence of focal and limbic features was determined for each patient. The associations of certain focal and limbic features with patient characteristics were assessed. Information was obtained on FS in 106 children. Various events were recorded at seizure commencement. Behavioral changes were observed in 35 children, changes in facial expression in 53, ocular symptoms in 78, and oral symptoms in 90. In terms of events during seizures, autonomic symptoms were recognized in 78, and convulsive motor symptoms were recognized in 68 children. Focal features were evident in 81 children; 38 children had two or more such features. Limbic features were observed in 44 children, 9 of whom had two or more such features. There was no significant relationship between any patient characteristic and the numbers of focal or limbic features. The semiology of FS varied widely among children, and symptoms suggestive of focal onset were frequent. FS of focal onset may be more common than is generally thought. Copyright © 2017 Elsevier Inc. All rights reserved.

Imaging in juvenile idiopathic arthritis with a focus on ultrasonography.

PubMed

Laurell, Louise; Court-Payen, Michel; Boesen, Mikael; Fasth, Anders

2013-01-01

Early therapeutic intervention and use of new highly efficacious treatments have improved the outcome in many patients with juvenile idiopathic arthritis (JIA), but have also led to the need for more precise methods to evaluate disease activity. In adult rheumatology, numerous studies have established the importance of magnetic resonance imaging (MRI) and ultrasonography (US), and MRI is considered the reference standard. Nevertheless, due to differences in disease characteristics and the unique features of the growing skeleton, the findings obtained in adults are not directly applicable to children and adolescents. For paediatric patients, US offers specific advantages over MRI, because it is non-invasive, does not require sedation or general anesthesia (which facilitates repeated examinations for follow-up), is quickly accessible bedside, and is easy to combine with clinical assessment (interactivity). Agitation of the patient is rarely a problem, and hence young children can be seated on a parent's lap or play while being examined, and multiple locations can be assessed during a single session. Furthermore, modern high-frequency US transducers used by experienced US examiners can provide unsurpassed resolution of the superficial musculoskeletal structures in children. US is also the best available technique for imaging guidance of steroid injections. Unfortunately, there are still no validated MRI or US scoring systems for evaluating inflammatory and joint damage abnormalities in JIA, and few US studies have been conducted. Sonographic assessment of disease activity has, however, been proven to be more informative than clinical examination and is also readily available at points of care. This review summarises the literature on imaging in JIA, focusing on US and the important role this technique will play in JIA in the future.

Integration of internal and external facial features in 8- to 10-year-old children and adults.

PubMed

Meinhardt-Injac, Bozana; Persike, Malte; Meinhardt, Günter

2014-06-01

Investigation of whole-part and composite effects in 4- to 6-year-old children gave rise to claims that face perception is fully mature within the first decade of life (Crookes & McKone, 2009). However, only internal features were tested, and the role of external features was not addressed, although external features are highly relevant for holistic face perception (Sinha & Poggio, 1996; Axelrod & Yovel, 2010, 2011). In this study, 8- to 10-year-old children and adults performed a same-different matching task with faces and watches. In this task participants attended to either internal or external features. Holistic face perception was tested using a congruency paradigm, in which face and non-face stimuli either agreed or disagreed in both features (congruent contexts) or just in the attended ones (incongruent contexts). In both age groups, pronounced context congruency and inversion effects were found for faces, but not for watches. These findings indicate holistic feature integration for faces. While inversion effects were highly similar in both age groups, context congruency effects were stronger for children. Moreover, children's face matching performance was generally better when attending to external compared to internal features. Adults tended to perform better when attending to internal features. Our results indicate that both adults and 8- to 10-year-old children integrate external and internal facial features into holistic face representations. However, in children's face representations external features are much more relevant. These findings suggest that face perception is holistic but still not adult-like at the end of the first decade of life. Copyright © 2014 Elsevier B.V. All rights reserved.

Image search engine with selective filtering and feature-element-based classification

NASA Astrophysics Data System (ADS)

Li, Qing; Zhang, Yujin; Dai, Shengyang

2001-12-01

With the growth of Internet and storage capability in recent years, image has become a widespread information format in World Wide Web. However, it has become increasingly harder to search for images of interest, and effective image search engine for the WWW needs to be developed. We propose in this paper a selective filtering process and a novel approach for image classification based on feature element in the image search engine we developed for the WWW. First a selective filtering process is embedded in a general web crawler to filter out the meaningless images with GIF format. Two parameters that can be obtained easily are used in the filtering process. Our classification approach first extract feature elements from images instead of feature vectors. Compared with feature vectors, feature elements can better capture visual meanings of the image according to subjective perception of human beings. Different from traditional image classification method, our classification approach based on feature element doesn't calculate the distance between two vectors in the feature space, while trying to find associations between feature element and class attribute of the image. Experiments are presented to show the efficiency of the proposed approach.

Broad autism phenotype features of Chinese parents with autistic children and their associations with severity of social impairment in probands.

PubMed

Shi, Li-Juan; Ou, Jian-Jun; Gong, Jing-Bo; Wang, Su-Hong; Zhou, Yuan-Yue; Zhu, Fu-Rong; Liu, Xu-Dong; Zhao, Jing-Ping; Luo, Xue-Rong

2015-07-23

Parents of children with autism have higher rates of broad autism phenotype (BAP) features than parents of typically developing children (TDC) in Western countries. This study was designed to examine the rate of BAP features in parents of children with autism and the relationship between parental BAP and the social impairment of their children in a Chinese sample. A total of 299 families with autistic children and 274 families with TDC participated in this study. Parents were assessed using the Broad Autism Phenotype Questionnaire (BAPQ), which includes self-report, informant-report, and best-estimate versions. Children were assessed using the Chinese version of the Social Responsiveness Scale (SRS). Parents of children with autism were significantly more likely to have BAP features than were parents of TDC; mothers and fathers in families with autistic children had various BAP features. The total scores of the informant and best-estimate BAPQ versions for fathers were significantly associated with their children's SRS total scores in the autism group, whereas the total scores of the three BAPQ versions for mothers were significantly associated with their children's SRS total scores in the TDC group. In the autism group, the total SRS scores of children with "BAP present" parents (informant and best-estimate) were higher than the total SRS scores of children with"BAP absent" parents. In the TDC group, the total SRS scores of children with "BAP present" parents were higher than the total SRS scores of children with"BAP absent" parents (best-estimate). Parents of autistic children were found to have higher rates of BAP than parents of TDC in a sample of Chinese parents. The BAP features of parents are associated with their children's social functioning in both autism families and TDC families, but the patterns of the associations are different.

Mother-child conversations about safety: implications for socializing safety values in children.

PubMed

O'Neal, Elizabeth E; Plumert, Jodie M

2014-05-01

This study examined how mothers socialize their children about safety through conversations about potentially unsafe activities. Mothers and their 8- and 10-year-old children discussed and rated the safety of 12 photographs depicting another same-gender child engaged in potentially dangerous activities. Conversations usually unfolded with children giving the first rating or rationale, followed by additional discussion between the mother and child. Mothers and children relied on 2 main types of rationales to justify their ratings: potential outcomes of the activity and specific features of the situation (dangerous and nondangerous). Mothers (but not children) used dangerous feature rationales more often than dangerous outcome rationales. When disagreements arose, mothers typically guided children to adopt their own rating rather than the child's rating. Additionally, children who used more nondangerous feature and outcome rationales had experienced more injuries requiring medical attention. Mothers' focus on dangerous features appears to reflect their efforts to help children make causal connections between dangerous elements of the situation and adverse outcomes that might result.

Emotional textile image classification based on cross-domain convolutional sparse autoencoders with feature selection

NASA Astrophysics Data System (ADS)

Li, Zuhe; Fan, Yangyu; Liu, Weihua; Yu, Zeqi; Wang, Fengqin

2017-01-01

We aim to apply sparse autoencoder-based unsupervised feature learning to emotional semantic analysis for textile images. To tackle the problem of limited training data, we present a cross-domain feature learning scheme for emotional textile image classification using convolutional autoencoders. We further propose a correlation-analysis-based feature selection method for the weights learned by sparse autoencoders to reduce the number of features extracted from large size images. First, we randomly collect image patches on an unlabeled image dataset in the source domain and learn local features with a sparse autoencoder. We then conduct feature selection according to the correlation between different weight vectors corresponding to the autoencoder's hidden units. We finally adopt a convolutional neural network including a pooling layer to obtain global feature activations of textile images in the target domain and send these global feature vectors into logistic regression models for emotional image classification. The cross-domain unsupervised feature learning method achieves 65% to 78% average accuracy in the cross-validation experiments corresponding to eight emotional categories and performs better than conventional methods. Feature selection can reduce the computational cost of global feature extraction by about 50% while improving classification performance.

Textural features for radar image analysis

NASA Technical Reports Server (NTRS)

Shanmugan, K. S.; Narayanan, V.; Frost, V. S.; Stiles, J. A.; Holtzman, J. C.

1981-01-01

Texture is seen as an important spatial feature useful for identifying objects or regions of interest in an image. While textural features have been widely used in analyzing a variety of photographic images, they have not been used in processing radar images. A procedure for extracting a set of textural features for characterizing small areas in radar images is presented, and it is shown that these features can be used in classifying segments of radar images corresponding to different geological formations.

Characterization of Long Working Distance Optical Coherence Tomography for Imaging of Pediatric Retinal Pathology.

PubMed

Qian, Ruobing; Carrasco-Zevallos, Oscar M; Mangalesh, Shwetha; Sarin, Neeru; Vajzovic, Lejla; Farsiu, Sina; Izatt, Joseph A; Toth, Cynthia A

2017-10-01

We determined the feasibility of fovea and optic nerve head imaging with a long working distance (LWD) swept source optical coherence tomography (OCT) prototype in adults, teenagers, and young children. A prototype swept source OCT system with a LWD (defined as distance from the last optical element of the imaging system to the eye) of 350 mm with custom fixation targets was developed to facilitate imaging of children. Imaging was performed in 49 participants from three age groups: 26 adults, 16 children 13 to 18 years old (teenagers), and seven children under 6 years old (young children) under an approved institutional review board protocol. The imaging goal was to acquire high quality scans of the fovea and optic nerve in each eye in the shortest time possible. OCT B-scans and volumes of the fovea and optic nerve head of each eligible eye were captured and graded based on four categories (lateral and axial centration, contrast, and resolution) and on ability to determine presence or absence of pathology. LWD-OCT imaging was successful in 88 of 94 eligible eyes, including seven of 10 eyes of young children. Of the successfully acquired OCT images, 83% of B-scan and volumetric images, including 86% from young children, were graded as high-quality scans. Pathology was observed in high-quality OCT images. The prototype LWD-OCT system achieved high quality retinal imaging of adults, teenagers, and some young children with and without pathology with reasonable alignment time. The LWD-OCT system can facilitate imaging in children.

Characterization of Long Working Distance Optical Coherence Tomography for Imaging of Pediatric Retinal Pathology

PubMed Central

Qian, Ruobing; Carrasco-Zevallos, Oscar M.; Mangalesh, Shwetha; Sarin, Neeru; Vajzovic, Lejla; Farsiu, Sina; Izatt, Joseph A.; Toth, Cynthia A.

2017-01-01

Purpose We determined the feasibility of fovea and optic nerve head imaging with a long working distance (LWD) swept source optical coherence tomography (OCT) prototype in adults, teenagers, and young children. Methods A prototype swept source OCT system with a LWD (defined as distance from the last optical element of the imaging system to the eye) of 350 mm with custom fixation targets was developed to facilitate imaging of children. Imaging was performed in 49 participants from three age groups: 26 adults, 16 children 13 to 18 years old (teenagers), and seven children under 6 years old (young children) under an approved institutional review board protocol. The imaging goal was to acquire high quality scans of the fovea and optic nerve in each eye in the shortest time possible. OCT B-scans and volumes of the fovea and optic nerve head of each eligible eye were captured and graded based on four categories (lateral and axial centration, contrast, and resolution) and on ability to determine presence or absence of pathology. Results LWD-OCT imaging was successful in 88 of 94 eligible eyes, including seven of 10 eyes of young children. Of the successfully acquired OCT images, 83% of B-scan and volumetric images, including 86% from young children, were graded as high-quality scans. Pathology was observed in high-quality OCT images. Conclusions The prototype LWD-OCT system achieved high quality retinal imaging of adults, teenagers, and some young children with and without pathology with reasonable alignment time. Translational Relevance The LWD-OCT system can facilitate imaging in children. PMID:29057163

Neuroimaging Feature Terminology: A Controlled Terminology for the Annotation of Brain Imaging Features.

PubMed

Iyappan, Anandhi; Younesi, Erfan; Redolfi, Alberto; Vrooman, Henri; Khanna, Shashank; Frisoni, Giovanni B; Hofmann-Apitius, Martin

2017-01-01

Ontologies and terminologies are used for interoperability of knowledge and data in a standard manner among interdisciplinary research groups. Existing imaging ontologies capture general aspects of the imaging domain as a whole such as methodological concepts or calibrations of imaging instruments. However, none of the existing ontologies covers the diagnostic features measured by imaging technologies in the context of neurodegenerative diseases. Therefore, the Neuro-Imaging Feature Terminology (NIFT) was developed to organize the knowledge domain of measured brain features in association with neurodegenerative diseases by imaging technologies. The purpose is to identify quantitative imaging biomarkers that can be extracted from multi-modal brain imaging data. This terminology attempts to cover measured features and parameters in brain scans relevant to disease progression. In this paper, we demonstrate the systematic retrieval of measured indices from literature and how the extracted knowledge can be further used for disease modeling that integrates neuroimaging features with molecular processes.

Combining Deep and Handcrafted Image Features for Presentation Attack Detection in Face Recognition Systems Using Visible-Light Camera Sensors

PubMed Central

Nguyen, Dat Tien; Pham, Tuyen Danh; Baek, Na Rae; Park, Kang Ryoung

2018-01-01

Although face recognition systems have wide application, they are vulnerable to presentation attack samples (fake samples). Therefore, a presentation attack detection (PAD) method is required to enhance the security level of face recognition systems. Most of the previously proposed PAD methods for face recognition systems have focused on using handcrafted image features, which are designed by expert knowledge of designers, such as Gabor filter, local binary pattern (LBP), local ternary pattern (LTP), and histogram of oriented gradients (HOG). As a result, the extracted features reflect limited aspects of the problem, yielding a detection accuracy that is low and varies with the characteristics of presentation attack face images. The deep learning method has been developed in the computer vision research community, which is proven to be suitable for automatically training a feature extractor that can be used to enhance the ability of handcrafted features. To overcome the limitations of previously proposed PAD methods, we propose a new PAD method that uses a combination of deep and handcrafted features extracted from the images by visible-light camera sensor. Our proposed method uses the convolutional neural network (CNN) method to extract deep image features and the multi-level local binary pattern (MLBP) method to extract skin detail features from face images to discriminate the real and presentation attack face images. By combining the two types of image features, we form a new type of image features, called hybrid features, which has stronger discrimination ability than single image features. Finally, we use the support vector machine (SVM) method to classify the image features into real or presentation attack class. Our experimental results indicate that our proposed method outperforms previous PAD methods by yielding the smallest error rates on the same image databases. PMID:29495417

The role of external features in face recognition with central vision loss: A pilot study

PubMed Central

Bernard, Jean-Baptiste; Chung, Susana T.L.

2016-01-01

Purpose We evaluated how the performance for recognizing familiar face images depends on the internal (eyebrows, eyes, nose, mouth) and external face features (chin, outline of face, hairline) in individuals with central vision loss. Methods In Experiment 1, we measured eye movements for four observers with central vision loss to determine whether they fixated more often on the internal or the external features of face images while attempting to recognize the images. We then measured the accuracy for recognizing face images that contained only the internal, only the external, or both internal and external features (Experiment 2), and for hybrid images where the internal and external features came from two different source images (Experiment 3), for five observers with central vision loss and four age-matched control observers. Results When recognizing familiar face images, approximately 40% of the fixations of observers with central vision loss were centered on the external features of faces. The recognition accuracy was higher for images containing only external features (66.8±3.3% correct) than for images containing only internal features (35.8±15.0%), a finding contradicting that of control observers. For hybrid face images, observers with central vision loss responded more accurately to the external features (50.4±17.8%) than to the internal features (9.3±4.9%), while control observers did not show the same bias toward responding to the external features. Conclusions Contrary to people with normal vision who rely more on the internal features of face images for recognizing familiar faces, individuals with central vision loss show a higher dependence on using external features of face images. PMID:26829260

The Role of External Features in Face Recognition with Central Vision Loss.

PubMed

Bernard, Jean-Baptiste; Chung, Susana T L

2016-05-01

We evaluated how the performance of recognizing familiar face images depends on the internal (eyebrows, eyes, nose, mouth) and external face features (chin, outline of face, hairline) in individuals with central vision loss. In experiment 1, we measured eye movements for four observers with central vision loss to determine whether they fixated more often on the internal or the external features of face images while attempting to recognize the images. We then measured the accuracy for recognizing face images that contained only the internal, only the external, or both internal and external features (experiment 2) and for hybrid images where the internal and external features came from two different source images (experiment 3) for five observers with central vision loss and four age-matched control observers. When recognizing familiar face images, approximately 40% of the fixations of observers with central vision loss was centered on the external features of faces. The recognition accuracy was higher for images containing only external features (66.8 ± 3.3% correct) than for images containing only internal features (35.8 ± 15.0%), a finding contradicting that of control observers. For hybrid face images, observers with central vision loss responded more accurately to the external features (50.4 ± 17.8%) than to the internal features (9.3 ± 4.9%), whereas control observers did not show the same bias toward responding to the external features. Contrary to people with normal vision who rely more on the internal features of face images for recognizing familiar faces, individuals with central vision loss show a higher dependence on using external features of face images.

Combining Deep and Handcrafted Image Features for Presentation Attack Detection in Face Recognition Systems Using Visible-Light Camera Sensors.

PubMed

Nguyen, Dat Tien; Pham, Tuyen Danh; Baek, Na Rae; Park, Kang Ryoung

2018-02-26

Although face recognition systems have wide application, they are vulnerable to presentation attack samples (fake samples). Therefore, a presentation attack detection (PAD) method is required to enhance the security level of face recognition systems. Most of the previously proposed PAD methods for face recognition systems have focused on using handcrafted image features, which are designed by expert knowledge of designers, such as Gabor filter, local binary pattern (LBP), local ternary pattern (LTP), and histogram of oriented gradients (HOG). As a result, the extracted features reflect limited aspects of the problem, yielding a detection accuracy that is low and varies with the characteristics of presentation attack face images. The deep learning method has been developed in the computer vision research community, which is proven to be suitable for automatically training a feature extractor that can be used to enhance the ability of handcrafted features. To overcome the limitations of previously proposed PAD methods, we propose a new PAD method that uses a combination of deep and handcrafted features extracted from the images by visible-light camera sensor. Our proposed method uses the convolutional neural network (CNN) method to extract deep image features and the multi-level local binary pattern (MLBP) method to extract skin detail features from face images to discriminate the real and presentation attack face images. By combining the two types of image features, we form a new type of image features, called hybrid features, which has stronger discrimination ability than single image features. Finally, we use the support vector machine (SVM) method to classify the image features into real or presentation attack class. Our experimental results indicate that our proposed method outperforms previous PAD methods by yielding the smallest error rates on the same image databases.

Reading strategies in Spanish developmental dyslexics.

PubMed

Suárez-Coalla, Paz; Cuetos, Fernando

2012-07-01

Cross-linguistic studies suggest that the orthographic system determines the reading performance of dyslexic children. In opaque orthographies, the fundamental feature of developmental dyslexia is difficulty in reading accuracy, whereas slower reading speed is more common in transparent orthographies. The aim of the current study was to examine the extent to which different variables of words affect reaction times and articulation times in developmental dyslexics. A group of 19 developmental dyslexics of different ages and an age-matched group of 19 children without reading disabilities completed a word naming task. The children were asked to read 100 nouns that differed in length, frequency, age of acquisition, imageability, and orthographic neighborhood. The stimuli were presented on a laptop computer, and the responses were recorded using DMDX software. We conducted analyses of mixed-effects models to determine which variables influenced reading times in dyslexic children. We found that word naming skills in dyslexic children are affected predominantly by length, while in non-dyslexics children the principal variable is the age of acquisition, a lexical variable. These findings suggest that Spanish-speaking developmental dyslexics use a sublexical procedure for reading words, which is reflected in slower speed when reading long words. In contrast, normal children use a lexical strategy, which is frequently observed in readers of opaque languages.

Atypical magnetic resonance imaging features in subacute sclerosing panencephalitis

PubMed Central

Das, Biplab; Goyal, Manoj Kumar; Modi, Manish; Mehta, Sahil; Chakravarthi, Sudheer; Lal, Vivek; Vyas, Sameer

2016-01-01

Objectives: Subacute sclerosing panencephalitis (SSPE) is rare chronic, progressive encephalitis that affects primarily children and young adults, caused by a persistent infection with measles virus. No cure for SSPE exists, but the condition can be managed by medication if treatment is started at an early stage. Methods and Results: Heterogeneity of imaging findings in SSPE is not very uncommon. But pial and gyral enhancements are very rarely noticed. Significant asymmetric onset as well as pial-gyral enhancements is not reported. Herein we present a case of 16 years adolescent of SSPE having remarkable asymmetric pial-gyral enhancements, which were misinterpreted as tubercular infection. Conclusion: Early diagnosis and treatment is encouraging in SSPE, although it is not curable with current therapy. Clinico-radiological and electrophysiological correlation is very important in diagnosis of SSPE, more gravely in patients having atypical image findings as in our index case. PMID:27293348

Caregiver Strain and Sensory Features in Children with Autism Spectrum Disorder and Other Developmental Disabilities

ERIC Educational Resources Information Center

Kirby, Anne V.; White, Tamira J.; Baranek, Grace T.

2015-01-01

Caring for children with disabilities contributes to increased levels of parent stress or caregiver strain. However, the potential relationship of sensory features to strain among caregivers of children with autism spectrum disorder (ASD) and other developmental disabilities (DD) is unknown. Sensory features include overreactions, underreactions,…

Model-Based Learning of Local Image Features for Unsupervised Texture Segmentation

NASA Astrophysics Data System (ADS)

Kiechle, Martin; Storath, Martin; Weinmann, Andreas; Kleinsteuber, Martin

2018-04-01

Features that capture well the textural patterns of a certain class of images are crucial for the performance of texture segmentation methods. The manual selection of features or designing new ones can be a tedious task. Therefore, it is desirable to automatically adapt the features to a certain image or class of images. Typically, this requires a large set of training images with similar textures and ground truth segmentation. In this work, we propose a framework to learn features for texture segmentation when no such training data is available. The cost function for our learning process is constructed to match a commonly used segmentation model, the piecewise constant Mumford-Shah model. This means that the features are learned such that they provide an approximately piecewise constant feature image with a small jump set. Based on this idea, we develop a two-stage algorithm which first learns suitable convolutional features and then performs a segmentation. We note that the features can be learned from a small set of images, from a single image, or even from image patches. The proposed method achieves a competitive rank in the Prague texture segmentation benchmark, and it is effective for segmenting histological images.

A brief review on the use of functional near-infrared spectroscopy (fNIRS) for language imaging studies in human newborns and adults.

PubMed

Quaresima, Valentina; Bisconti, Silvia; Ferrari, Marco

2012-05-01

Upon stimulation, real time maps of cortical hemodynamic responses can be obtained by non-invasive functional near-infrared spectroscopy (fNIRS) which measures changes in oxygenated and deoxygenated hemoglobin after positioning multiple sources and detectors over the human scalp. The current commercially available transportable fNIRS systems have a time resolution of 1-10 Hz, a depth sensitivity of about 1.5 cm, and a spatial resolution of about 1cm. The goal of this brief review is to report infants, children and adults fNIRS language studies. Since 1998, 60 studies have been published on cortical activation in the brain's classic language areas in children/adults as well as newborns using fNIRS instrumentations of different complexity. In addition, the basic principles of fNIRS including features, strengths, advantages, and limitations are summarized in terms that can be understood even by non specialists. Future prospects of fNIRS in the field of language processing imaging are highlighted. Copyright © 2011 Elsevier Inc. All rights reserved.

Effects of Vocal Fold Nodules on Glottal Cycle Measurements Derived from High-Speed Videoendoscopy in Children

PubMed Central

2016-01-01

The goal of this study is to quantify the effects of vocal fold nodules on vibratory motion in children using high-speed videoendoscopy. Differences in vibratory motion were evaluated in 20 children with vocal fold nodules (5–11 years) and 20 age and gender matched typically developing children (5–11 years) during sustained phonation at typical pitch and loudness. Normalized kinematic features of vocal fold displacements from the mid-membranous vocal fold point were extracted from the steady-state high-speed video. A total of 12 kinematic features representing spatial and temporal characteristics of vibratory motion were calculated. Average values and standard deviations (cycle-to-cycle variability) of the following kinematic features were computed: normalized peak displacement, normalized average opening velocity, normalized average closing velocity, normalized peak closing velocity, speed quotient, and open quotient. Group differences between children with and without vocal fold nodules were statistically investigated. While a moderate effect size was observed for the spatial feature of speed quotient, and the temporal feature of normalized average closing velocity in children with nodules compared to vocally normal children, none of the features were statistically significant between the groups after Bonferroni correction. The kinematic analysis of the mid-membranous vocal fold displacement revealed that children with nodules primarily differ from typically developing children in closing phase kinematics of the glottal cycle, whereas the opening phase kinematics are similar. Higher speed quotients and similar opening phase velocities suggest greater relative forces are acting on vocal fold in the closing phase. These findings suggest that future large-scale studies should focus on spatial and temporal features related to the closing phase of the glottal cycle for differentiating the kinematics of children with and without vocal fold nodules. PMID:27124157

Processing Dynamic Image Sequences from a Moving Sensor.

DTIC Science & Technology

1984-02-01

65 Roadsign Image Sequence ..... ................ ... 70 Roadsign Sequence with Redundant Features .. ........ . 79 Roadsign Subimage...Selected Feature Error Values .. ........ 66 2c. Industrial Image Selected Feature Local Search Values. .. .... 67 3ab. Roadsign Image Error Values...72 3c. Roadsign Image Local Search Values ............. 73 4ab. Roadsign Redundant Feature Error Values. ............ 8 4c. Roadsign

Use of Diagnostic Imaging in the Evaluation of Gastrointestinal Tract Duplications

PubMed Central

Laskowska, Katarzyna; Gałązka, Przemysław; Daniluk-Matraś, Irena; Leszczyński, Waldemar; Serafin, Zbigniew

2014-01-01

Summary Background Gastrointestinal tract duplication is a rare malformation associated with the presence of additional segment of the fetal gut. The aim of this study was to retrospectively review clinical features and imaging findings in intraoperatively confirmed cases of gastrointestinal tract duplication in children. Material/Methods The analysis included own material from the years 2002–2012. The analyzed group included 14 children, among them 8 boys and 6 girls. The youngest patient was diagnosed at the age of three weeks, and the oldest at 12 years of age. Results The duplication cysts were identified in the esophagus (n=2), stomach (n=5), duodenum (n=1), terminal ileum (n=5), and rectum (n=1). In four cases, the duplication coexisted with other anomalies, such as patent urachus, Meckel’s diverticulum, mesenteric cyst, and accessory pancreas. Clinical manifestation of gastrointestinal duplication cysts was variable, and some of them were detected accidently. Thin- or thick-walled cystic structures adjacent to the wall of neighboring gastrointestinal segment were documented on diagnostic imaging. Conclusions Ultrasound and computed tomography are the methods of choice in the evaluation of gastrointestinal duplication cysts. Apart from the diagnosis of the duplication cyst, an important issue is the detection of concomitant developmental pathologies, including pancreatic heterotopy. PMID:25114725

n-SIFT: n-dimensional scale invariant feature transform.

PubMed

Cheung, Warren; Hamarneh, Ghassan

2009-09-01

We propose the n-dimensional scale invariant feature transform (n-SIFT) method for extracting and matching salient features from scalar images of arbitrary dimensionality, and compare this method's performance to other related features. The proposed features extend the concepts used for 2-D scalar images in the computer vision SIFT technique for extracting and matching distinctive scale invariant features. We apply the features to images of arbitrary dimensionality through the use of hyperspherical coordinates for gradients and multidimensional histograms to create the feature vectors. We analyze the performance of a fully automated multimodal medical image matching technique based on these features, and successfully apply the technique to determine accurate feature point correspondence between pairs of 3-D MRI images and dynamic 3D + time CT data.

Image processing for hazard recognition in on-board weather radar

NASA Technical Reports Server (NTRS)

Kelly, Wallace E. (Inventor); Rand, Timothy W. (Inventor); Uckun, Serdar (Inventor); Ruokangas, Corinne C. (Inventor)

2003-01-01

A method of providing weather radar images to a user includes obtaining radar image data corresponding to a weather radar image to be displayed. The radar image data is image processed to identify a feature of the weather radar image which is potentially indicative of a hazardous weather condition. The weather radar image is displayed to the user along with a notification of the existence of the feature which is potentially indicative of the hazardous weather condition. Notification can take the form of textual information regarding the feature, including feature type and proximity information. Notification can also take the form of visually highlighting the feature, for example by forming a visual border around the feature. Other forms of notification can also be used.

Histological Image Feature Mining Reveals Emergent Diagnostic Properties for Renal Cancer

PubMed Central

Kothari, Sonal; Phan, John H.; Young, Andrew N.; Wang, May D.

2016-01-01

Computer-aided histological image classification systems are important for making objective and timely cancer diagnostic decisions. These systems use combinations of image features that quantify a variety of image properties. Because researchers tend to validate their diagnostic systems on specific cancer endpoints, it is difficult to predict which image features will perform well given a new cancer endpoint. In this paper, we define a comprehensive set of common image features (consisting of 12 distinct feature subsets) that quantify a variety of image properties. We use a data-mining approach to determine which feature subsets and image properties emerge as part of an “optimal” diagnostic model when applied to specific cancer endpoints. Our goal is to assess the performance of such comprehensive image feature sets for application to a wide variety of diagnostic problems. We perform this study on 12 endpoints including 6 renal tumor subtype endpoints and 6 renal cancer grade endpoints. Keywords-histology, image mining, computer-aided diagnosis PMID:28163980

Blind image quality assessment based on aesthetic and statistical quality-aware features

NASA Astrophysics Data System (ADS)

Jenadeleh, Mohsen; Masaeli, Mohammad Masood; Moghaddam, Mohsen Ebrahimi

2017-07-01

The main goal of image quality assessment (IQA) methods is the emulation of human perceptual image quality judgments. Therefore, the correlation between objective scores of these methods with human perceptual scores is considered as their performance metric. Human judgment of the image quality implicitly includes many factors when assessing perceptual image qualities such as aesthetics, semantics, context, and various types of visual distortions. The main idea of this paper is to use a host of features that are commonly employed in image aesthetics assessment in order to improve blind image quality assessment (BIQA) methods accuracy. We propose an approach that enriches the features of BIQA methods by integrating a host of aesthetics image features with the features of natural image statistics derived from multiple domains. The proposed features have been used for augmenting five different state-of-the-art BIQA methods, which use statistical natural scene statistics features. Experiments were performed on seven benchmark image quality databases. The experimental results showed significant improvement of the accuracy of the methods.

Congenital Zika syndrome with arthrogryposis: retrospective case series study.

PubMed

van der Linden, Vanessa; Filho, Epitacio Leite Rolim; Lins, Otavio Gomes; van der Linden, Ana; Aragão, Maria de Fátima Viana Vasco; Brainer-Lima, Alessandra Mertens; Cruz, Danielle Di Cavalcanti Sousa; Rocha, Maria Angela Wanderley; Sobral da Silva, Paula Fabiana; Carvalho, Maria Durce Costa Gomes; do Amaral, Fernando José; Gomes, Joelma Arruda; Ribeiro de Medeiros, Igor Colaço; Ventura, Camila V; Ramos, Regina Coeli

2016-08-09

To describe the clinical, radiological, and electromyographic features in a series of children with joint contractures (arthrogryposis) associated with congenital infection presumably caused by Zika virus. Retrospective case series study. Association for Assistance of Disabled Children, Pernambuco state, Brazil. Seven children with arthrogryposis and a diagnosis of congenital infection presumably caused by Zika virus during the Brazilian microcephaly epidemic. Main clinical, radiological, and electromyographic findings, and likely correlation between clinical and primary neurological abnormalities. The brain images of all seven children were characteristic of congenital infection and arthrogryposis. Two children tested positive for IgM to Zika virus in the cerebrospinal fluid. Arthrogryposis was present in the arms and legs of six children (86%) and the legs of one child (14%). Hip radiographs showed bilateral dislocation in seven children, subluxation of the knee associated with genu valgus in three children (43%), which was bilateral in two (29%). All the children underwent high definition ultrasonography of the joints, and there was no evidence of abnormalities. Moderate signs of remodeling of the motor units and a reduced recruitment pattern were found on needle electromyography (monopolar). Five of the children underwent brain computed tomography (CT) and magnetic resonance imaging (MRI) and the remaining two CT only. All presented malformations of cortical development, calcifications predominantly in the cortex and subcortical white matter (especially in the junction between the cortex and white matter), reduction in brain volume, ventriculomegaly, and hypoplasia of the brainstem and cerebellum. MRI of the spine in four children showed apparent thinning of the cord and reduced ventral roots. Congenital Zika syndrome should be added to the differential diagnosis of congenital infections and arthrogryposis. The arthrogryposis was unrelated to the abnormalities of the joints themselves, but was possibly of neurogenic origin, with chronic involvement of central and peripheral motor neurones leading to deformities as a result of fixed postures in utero. Based on the neurophysiological observations, we suggest two possible mechanisms: tropism of neurones, with involvement of peripheral and central motor neurones, or a relation with vascular disorders. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Congenital Zika syndrome with arthrogryposis: retrospective case series study

PubMed Central

Filho, Epitacio Leite Rolim; Lins, Otavio Gomes; Aragão, Maria de Fátima Viana Vasco; Brainer-Lima, Alessandra Mertens; Cruz, Danielle Di Cavalcanti Sousa; Rocha, Maria Angela Wanderley; Sobral da Silva, Paula Fabiana; Carvalho, Maria Durce Costa Gomes; do Amaral, Fernando José; Gomes, Joelma Arruda; Ribeiro de Medeiros, Igor Colaço; Ventura, Camila V; Ramos, Regina Coeli

2016-01-01

Objective To describe the clinical, radiological, and electromyographic features in a series of children with joint contractures (arthrogryposis) associated with congenital infection presumably caused by Zika virus. Design Retrospective case series study. Setting Association for Assistance of Disabled Children, Pernambuco state, Brazil. Participants Seven children with arthrogryposis and a diagnosis of congenital infection presumably caused by Zika virus during the Brazilian microcephaly epidemic. Main outcome measures Main clinical, radiological, and electromyographic findings, and likely correlation between clinical and primary neurological abnormalities. Results The brain images of all seven children were characteristic of congenital infection and arthrogryposis. Two children tested positive for IgM to Zika virus in the cerebrospinal fluid. Arthrogryposis was present in the arms and legs of six children (86%) and the legs of one child (14%). Hip radiographs showed bilateral dislocation in seven children, subluxation of the knee associated with genu valgus in three children (43%), which was bilateral in two (29%). All the children underwent high definition ultrasonography of the joints, and there was no evidence of abnormalities. Moderate signs of remodeling of the motor units and a reduced recruitment pattern were found on needle electromyography (monopolar). Five of the children underwent brain computed tomography (CT) and magnetic resonance imaging (MRI) and the remaining two CT only. All presented malformations of cortical development, calcifications predominantly in the cortex and subcortical white matter (especially in the junction between the cortex and white matter), reduction in brain volume, ventriculomegaly, and hypoplasia of the brainstem and cerebellum. MRI of the spine in four children showed apparent thinning of the cord and reduced ventral roots. Conclusions Congenital Zika syndrome should be added to the differential diagnosis of congenital infections and arthrogryposis. The arthrogryposis was unrelated to the abnormalities of the joints themselves, but was possibly of neurogenic origin, with chronic involvement of central and peripheral motor neurones leading to deformities as a result of fixed postures in utero. Based on the neurophysiological observations, we suggest two possible mechanisms: tropism of neurones, with involvement of peripheral and central motor neurones, or a relation with vascular disorders. PMID:27509902

Children's Image of God and Their Parents: Explorations in Children's Spirituality

ERIC Educational Resources Information Center

Baring, Rito

2012-01-01

Exploring children's image of God and parents has invited interest among program preparers for children's spirituality in the Philippines. This research seeks to find out the fundamental orientation of children's image of God as well as their perceptions of father and mother from 241 fifth graders in three selected government primary schools in…

Two sibs who are double heterozygotes for achondroplasia and pseudoachondroplastic dysplasia.

PubMed Central

Woods, C G; Rogers, J G; Mayne, V

1994-01-01

We report a family in which two sibs have both achondroplasia and pseudoachondroplastic dysplasia. The mother has achondroplasia and the father has pseudoachondroplastic dysplasia, which he had inherited from his father. Both children appeared typical of achondroplasia at birth. By 1 1/2 years they had developed a fixed lumbar kyphosis with gibbus and had additional x ray changes unusual for just achondroplasia and suggestive of pseudoachondroplastic dysplasia. Subsequently both children have shown characteristic features of both conditions and have grown less well than expected for achondroplasia. Radiographs show the striking synergistic effects of the two conditions. MRI in both sibs confirmed brain stem compression at the foramen magnum. This may be an important complication and should be actively sought in any double heterozygote. Images PMID:7966194

Radiomic biomarkers from PET/CT multi-modality fusion images for the prediction of immunotherapy response in advanced non-small cell lung cancer patients

NASA Astrophysics Data System (ADS)

Mu, Wei; Qi, Jin; Lu, Hong; Schabath, Matthew; Balagurunathan, Yoganand; Tunali, Ilke; Gillies, Robert James

2018-02-01

Purpose: Investigate the ability of using complementary information provided by the fusion of PET/CT images to predict immunotherapy response in non-small cell lung cancer (NSCLC) patients. Materials and methods: We collected 64 patients diagnosed with primary NSCLC treated with anti PD-1 checkpoint blockade. Using PET/CT images, fused images were created following multiple methodologies, resulting in up to 7 different images for the tumor region. Quantitative image features were extracted from the primary image (PET/CT) and the fused images, which included 195 from primary images and 1235 features from the fusion images. Three clinical characteristics were also analyzed. We then used support vector machine (SVM) classification models to identify discriminant features that predict immunotherapy response at baseline. Results: A SVM built with 87 fusion features and 13 primary PET/CT features on validation dataset had an accuracy and area under the ROC curve (AUROC) of 87.5% and 0.82, respectively, compared to a model built with 113 original PET/CT features on validation dataset 78.12% and 0.68. Conclusion: The fusion features shows better ability to predict immunotherapy response prediction compared to individual image features.

Gross feature recognition of Anatomical Images based on Atlas grid (GAIA): Incorporating the local discrepancy between an atlas and a target image to capture the features of anatomic brain MRI.

PubMed

Qin, Yuan-Yuan; Hsu, Johnny T; Yoshida, Shoko; Faria, Andreia V; Oishi, Kumiko; Unschuld, Paul G; Redgrave, Graham W; Ying, Sarah H; Ross, Christopher A; van Zijl, Peter C M; Hillis, Argye E; Albert, Marilyn S; Lyketsos, Constantine G; Miller, Michael I; Mori, Susumu; Oishi, Kenichi

2013-01-01

We aimed to develop a new method to convert T1-weighted brain MRIs to feature vectors, which could be used for content-based image retrieval (CBIR). To overcome the wide range of anatomical variability in clinical cases and the inconsistency of imaging protocols, we introduced the Gross feature recognition of Anatomical Images based on Atlas grid (GAIA), in which the local intensity alteration, caused by pathological (e.g., ischemia) or physiological (development and aging) intensity changes, as well as by atlas-image misregistration, is used to capture the anatomical features of target images. As a proof-of-concept, the GAIA was applied for pattern recognition of the neuroanatomical features of multiple stages of Alzheimer's disease, Huntington's disease, spinocerebellar ataxia type 6, and four subtypes of primary progressive aphasia. For each of these diseases, feature vectors based on a training dataset were applied to a test dataset to evaluate the accuracy of pattern recognition. The feature vectors extracted from the training dataset agreed well with the known pathological hallmarks of the selected neurodegenerative diseases. Overall, discriminant scores of the test images accurately categorized these test images to the correct disease categories. Images without typical disease-related anatomical features were misclassified. The proposed method is a promising method for image feature extraction based on disease-related anatomical features, which should enable users to submit a patient image and search past clinical cases with similar anatomical phenotypes.

Recognition of blurred images by the method of moments.

PubMed

Flusser, J; Suk, T; Saic, S

1996-01-01

The article is devoted to the feature-based recognition of blurred images acquired by a linear shift-invariant imaging system against an image database. The proposed approach consists of describing images by features that are invariant with respect to blur and recognizing images in the feature space. The PSF identification and image restoration are not required. A set of symmetric blur invariants based on image moments is introduced. A numerical experiment is presented to illustrate the utilization of the invariants for blurred image recognition. Robustness of the features is also briefly discussed.

Scattering features for lung cancer detection in fibered confocal fluorescence microscopy images.

PubMed

Rakotomamonjy, Alain; Petitjean, Caroline; Salaün, Mathieu; Thiberville, Luc

2014-06-01

To assess the feasibility of lung cancer diagnosis using fibered confocal fluorescence microscopy (FCFM) imaging technique and scattering features for pattern recognition. FCFM imaging technique is a new medical imaging technique for which interest has yet to be established for diagnosis. This paper addresses the problem of lung cancer detection using FCFM images and, as a first contribution, assesses the feasibility of computer-aided diagnosis through these images. Towards this aim, we have built a pattern recognition scheme which involves a feature extraction stage and a classification stage. The second contribution relies on the features used for discrimination. Indeed, we have employed the so-called scattering transform for extracting discriminative features, which are robust to small deformations in the images. We have also compared and combined these features with classical yet powerful features like local binary patterns (LBP) and their variants denoted as local quinary patterns (LQP). We show that scattering features yielded to better recognition performances than classical features like LBP and their LQP variants for the FCFM image classification problems. Another finding is that LBP-based and scattering-based features provide complementary discriminative information and, in some situations, we empirically establish that performance can be improved when jointly using LBP, LQP and scattering features. In this work we analyze the joint capability of FCFM images and scattering features for lung cancer diagnosis. The proposed method achieves a good recognition rate for such a diagnosis problem. It also performs well when used in conjunction with other features for other classical medical imaging classification problems. Copyright © 2014 Elsevier B.V. All rights reserved.

Content Based Image Retrieval by Using Color Descriptor and Discrete Wavelet Transform.

PubMed

Ashraf, Rehan; Ahmed, Mudassar; Jabbar, Sohail; Khalid, Shehzad; Ahmad, Awais; Din, Sadia; Jeon, Gwangil

2018-01-25

Due to recent development in technology, the complexity of multimedia is significantly increased and the retrieval of similar multimedia content is a open research problem. Content-Based Image Retrieval (CBIR) is a process that provides a framework for image search and low-level visual features are commonly used to retrieve the images from the image database. The basic requirement in any image retrieval process is to sort the images with a close similarity in term of visually appearance. The color, shape and texture are the examples of low-level image features. The feature plays a significant role in image processing. The powerful representation of an image is known as feature vector and feature extraction techniques are applied to get features that will be useful in classifying and recognition of images. As features define the behavior of an image, they show its place in terms of storage taken, efficiency in classification and obviously in time consumption also. In this paper, we are going to discuss various types of features, feature extraction techniques and explaining in what scenario, which features extraction technique will be better. The effectiveness of the CBIR approach is fundamentally based on feature extraction. In image processing errands like object recognition and image retrieval feature descriptor is an immense among the most essential step. The main idea of CBIR is that it can search related images to an image passed as query from a dataset got by using distance metrics. The proposed method is explained for image retrieval constructed on YCbCr color with canny edge histogram and discrete wavelet transform. The combination of edge of histogram and discrete wavelet transform increase the performance of image retrieval framework for content based search. The execution of different wavelets is additionally contrasted with discover the suitability of specific wavelet work for image retrieval. The proposed algorithm is prepared and tried to implement for Wang image database. For Image Retrieval Purpose, Artificial Neural Networks (ANN) is used and applied on standard dataset in CBIR domain. The execution of the recommended descriptors is assessed by computing both Precision and Recall values and compared with different other proposed methods with demonstrate the predominance of our method. The efficiency and effectiveness of the proposed approach outperforms the existing research in term of average precision and recall values.

The development of organized visual search

PubMed Central

Woods, Adam J.; Goksun, Tilbe; Chatterjee, Anjan; Zelonis, Sarah; Mehta, Anika; Smith, Sabrina E.

2013-01-01

Visual search plays an important role in guiding behavior. Children have more difficulty performing conjunction search tasks than adults. The present research evaluates whether developmental differences in children's ability to organize serial visual search (i.e., search organization skills) contribute to performance limitations in a typical conjunction search task. We evaluated 134 children between the ages of 2 and 17 on separate tasks measuring search for targets defined by a conjunction of features or by distinct features. Our results demonstrated that children organize their visual search better as they get older. As children's skills at organizing visual search improve they become more accurate at locating targets with conjunction of features amongst distractors, but not for targets with distinct features. Developmental limitations in children's abilities to organize their visual search of the environment are an important component of poor conjunction search in young children. In addition, our findings provide preliminary evidence that, like other visuospatial tasks, exposure to reading may influence children's spatial orientation to the visual environment when performing a visual search. PMID:23584560

System and method for the detection of anomalies in an image

DOEpatents

Prasad, Lakshman; Swaminarayan, Sriram

2013-09-03

Preferred aspects of the present invention can include receiving a digital image at a processor; segmenting the digital image into a hierarchy of feature layers comprising one or more fine-scale features defining a foreground object embedded in one or more coarser-scale features defining a background to the one or more fine-scale features in the segmentation hierarchy; detecting a first fine-scale foreground feature as an anomaly with respect to a first background feature within which it is embedded; and constructing an anomalous feature layer by synthesizing spatially contiguous anomalous fine-scale features. Additional preferred aspects of the present invention can include detecting non-pervasive changes between sets of images in response at least in part to one or more difference images between the sets of images.

A comparison study of image features between FFDM and film mammogram images

PubMed Central

Jing, Hao; Yang, Yongyi; Wernick, Miles N.; Yarusso, Laura M.; Nishikawa, Robert M.

2012-01-01

Purpose: This work is to provide a direct, quantitative comparison of image features measured by film and full-field digital mammography (FFDM). The purpose is to investigate whether there is any systematic difference between film and FFDM in terms of quantitative image features and their influence on the performance of a computer-aided diagnosis (CAD) system. Methods: The authors make use of a set of matched film-FFDM image pairs acquired from cadaver breast specimens with simulated microcalcifications consisting of bone and teeth fragments using both a GE digital mammography system and a screen-film system. To quantify the image features, the authors consider a set of 12 textural features of lesion regions and six image features of individual microcalcifications (MCs). The authors first conduct a direct comparison on these quantitative features extracted from film and FFDM images. The authors then study the performance of a CAD classifier for discriminating between MCs and false positives (FPs) when the classifier is trained on images of different types (film, FFDM, or both). Results: For all the features considered, the quantitative results show a high degree of correlation between features extracted from film and FFDM, with the correlation coefficients ranging from 0.7326 to 0.9602 for the different features. Based on a Fisher sign rank test, there was no significant difference observed between the features extracted from film and those from FFDM. For both MC detection and discrimination of FPs from MCs, FFDM had a slight but statistically significant advantage in performance; however, when the classifiers were trained on different types of images (acquired with FFDM or SFM) for discriminating MCs from FPs, there was little difference. Conclusions: The results indicate good agreement between film and FFDM in quantitative image features. While FFDM images provide better detection performance in MCs, FFDM and film images may be interchangeable for the purposes of training CAD algorithms, and a single CAD algorithm may be applied to either type of images. PMID:22830771

Feature-based Alignment of Volumetric Multi-modal Images

PubMed Central

Toews, Matthew; Zöllei, Lilla; Wells, William M.

2014-01-01

This paper proposes a method for aligning image volumes acquired from different imaging modalities (e.g. MR, CT) based on 3D scale-invariant image features. A novel method for encoding invariant feature geometry and appearance is developed, based on the assumption of locally linear intensity relationships, providing a solution to poor repeatability of feature detection in different image modalities. The encoding method is incorporated into a probabilistic feature-based model for multi-modal image alignment. The model parameters are estimated via a group-wise alignment algorithm, that iteratively alternates between estimating a feature-based model from feature data, then realigning feature data to the model, converging to a stable alignment solution with few pre-processing or pre-alignment requirements. The resulting model can be used to align multi-modal image data with the benefits of invariant feature correspondence: globally optimal solutions, high efficiency and low memory usage. The method is tested on the difficult RIRE data set of CT, T1, T2, PD and MP-RAGE brain images of subjects exhibiting significant inter-subject variability due to pathology. PMID:24683955

[Application of computer-aided osteotomy template design in treatment of developmental dysplasia of the hip with steel osteotomy].

PubMed

Tong, Kuang; Zhang, Yuanzhi; Zhang, Sheng; Yu, Bin

2013-06-01

To provide an accurate method for osteotomy in the treatment of developmental dysplasia of the hip with steel osteotomy by three-dimensional reconstruction and Reverse Engineering technique. Between January 2011 and December 2012, 13 children with developmental dysplasia of the hip underwent steel osteotomy. 3D CT scan pelvic images were obtained and transferred via a DICOM network into a computer workstation to construct 3D models of the hip using Materialise Mimics 14.1 software in STL format. These models were imported into Imageware 12.0 software for steel osteotomy simulation until a stable hip was attained in the anatomical position for dislocation or subluxation of the hip in older children. The osteotomy navigational templates were designed according to the anatomical features after a stable hip was reconstructed. These navigational templates were manufactured using a rapid prototyping technique. The reconstruction hips in these children show good matching property and acetabulum cover. The computer-aided design of osteotomy template provides personalized and accurate solutions in the treatment of developmental dysplasia of the hip with steel osteotomy in older children.

Childhood maltreatment and its link to borderline personality disorder features in children: A systematic review approach.

PubMed

Ibrahim, Jeyda; Cosgrave, Nicola; Woolgar, Matthew

2018-01-01

Borderline personality disorder has repeatedly been associated with a history of maltreatment in childhood; however, research on maltreatment and its link to borderline features in children is limited. The aim of this review is to synthesise the existing data on the association between maltreatment and borderline features in childhood. In total, 10 studies were included in this systematic review. Studies indicated that children with borderline features were more likely to have a history of maltreatment, and that children who had been maltreated were more likely to present with borderline features. Other risk factors such as cognitive and executive functioning deficits, parental dysfunction and genetic vulnerability were also identified across studies. This review adds to the literature by highlighting maltreatment as a risk factor for borderline features in childhood. Longitudinal research is required to establish the link between childhood borderline features and adult borderline features. Implications for early identification, prevention and intervention services are discussed.

Diagnostic methods and recommendations for the cerebral creatine deficiency syndromes.

PubMed

Clark, Joseph F; Cecil, Kim M

2015-03-01

Primary care pediatricians and a variety of specialist physicians strive to define an accurate diagnosis for children presenting with impairment of expressive speech and delay in achieving developmental milestones. Within the past two decades, a group of disorders featuring this presentation have been identified as cerebral creatine deficiency syndromes (CCDS). Patients with these disorders were initially discerned using proton magnetic resonance spectroscopy of the brain within a magnetic resonance imaging (MRI) examination. The objective of this review is to provide the clinician with an overview of the current information available on identifying and treating these conditions. We explain the salient features of creatine metabolism, synthesis, and transport required for normal development. We propose diagnostic approaches for confirming a CCDS diagnosis. Finally, we describe treatment approaches for managing patients with these conditions.

Perception of Suprasegmental Features of Speech by Children with Cochlear Implants and Children with Hearing Aids

ERIC Educational Resources Information Center

Most, Tova; Peled, Miriam

2007-01-01

This study assessed perception of suprasegmental features of speech by 30 prelingual children with sensorineural hearing loss. Ten children had cochlear implants (CIs), and 20 children wore hearing aids (HA): 10 with severe hearing loss and 10 with profound hearing loss. Perception of intonation, syllable stress, word emphasis, and word pattern…

Acquired pathology of the pediatric spine and spinal cord.

PubMed

Palasis, Susan; Hayes, Laura L

2015-09-01

Pediatric spine pathology poses a diagnostic challenge for radiologists. Acquired spine pathology often yields nonspecific signs and symptoms in children, especially in the younger age groups, and diagnostic delay can carry significant morbidity. This review is focused on some of the more common diagnostic dilemmas we face when attempting to evaluate and diagnose acquired pediatric spine anomalies in daily practice. An understanding of some of the key differentiating features of these disease processes in conjunction with pertinent history, physical exam, and advanced imaging techniques can indicate the correct diagnosis.

Neuroimaging Feature Terminology: A Controlled Terminology for the Annotation of Brain Imaging Features

PubMed Central

Iyappan, Anandhi; Younesi, Erfan; Redolfi, Alberto; Vrooman, Henri; Khanna, Shashank; Frisoni, Giovanni B.; Hofmann-Apitius, Martin

2017-01-01

Ontologies and terminologies are used for interoperability of knowledge and data in a standard manner among interdisciplinary research groups. Existing imaging ontologies capture general aspects of the imaging domain as a whole such as methodological concepts or calibrations of imaging instruments. However, none of the existing ontologies covers the diagnostic features measured by imaging technologies in the context of neurodegenerative diseases. Therefore, the Neuro-Imaging Feature Terminology (NIFT) was developed to organize the knowledge domain of measured brain features in association with neurodegenerative diseases by imaging technologies. The purpose is to identify quantitative imaging biomarkers that can be extracted from multi-modal brain imaging data. This terminology attempts to cover measured features and parameters in brain scans relevant to disease progression. In this paper, we demonstrate the systematic retrieval of measured indices from literature and how the extracted knowledge can be further used for disease modeling that integrates neuroimaging features with molecular processes. PMID:28731430

Features of childhood Sjögren's syndrome in comparison to adult Sjögren's syndrome: considerations in establishing child-specific diagnostic criteria.

PubMed

Yokogawa, Naoto; Lieberman, Scott M; Sherry, David D; Vivino, Frederick B

2016-01-01

To describe the clinical features of childhood Sjögren's syndrome (SS) in comparison to adult SS and to evaluate possible child-specific modifications to existing adult criteria for use in diagnosing childhood SS. We retrospectively identified children (age <18 years) with SS and compared the clinical, laboratory, and histopathological features of these children based on presence or absence of parotitis. We compared these features to adults with SS and evaluated the applicability of existing classification criteria in diagnosing childhood SS. Child-specific modifications to existing criteria were evaluated. Twenty-six children were included in our childhood SS group. Sixteen children had parotitis at or before presentation. Absence of parotitis was associated with greater degree of organ damage based on SS disease damage index. Compared to 413 adult SS patients, childhood SS was more commonly associated with parotitis, positive serologies, neurologic and nephrologic manifestations, and non-specific features (fever, lymphadenopathy) but less commonly associated with dry mouth and dry eyes. Only a minority of these children met previously established criteria for adult SS. Inclusion of child-specific features such as parotitis and the presence of any focal lymphocytic sialadenitis on minor salivary gland biopsy increased the proportion of children meeting these criteria. Childhood SS features may be different than adult SS features necessitating child-specific criteria for better diagnosis of childhood SS, a key step towards better understanding the features, prognosis, and outcomes in this disease.

Saliency image of feature building for image quality assessment

NASA Astrophysics Data System (ADS)

Ju, Xinuo; Sun, Jiyin; Wang, Peng

2011-11-01

The purpose and method of image quality assessment are quite different for automatic target recognition (ATR) and traditional application. Local invariant feature detectors, mainly including corner detectors, blob detectors and region detectors etc., are widely applied for ATR. A saliency model of feature was proposed to evaluate feasibility of ATR in this paper. The first step consisted of computing the first-order derivatives on horizontal orientation and vertical orientation, and computing DoG maps in different scales respectively. Next, saliency images of feature were built based auto-correlation matrix in different scale. Then, saliency images of feature of different scales amalgamated. Experiment were performed on a large test set, including infrared images and optical images, and the result showed that the salient regions computed by this model were consistent with real feature regions computed by mostly local invariant feature extraction algorithms.

Deep Multimodal Distance Metric Learning Using Click Constraints for Image Ranking.

PubMed

Yu, Jun; Yang, Xiaokang; Gao, Fei; Tao, Dacheng

2017-12-01

How do we retrieve images accurately? Also, how do we rank a group of images precisely and efficiently for specific queries? These problems are critical for researchers and engineers to generate a novel image searching engine. First, it is important to obtain an appropriate description that effectively represent the images. In this paper, multimodal features are considered for describing images. The images unique properties are reflected by visual features, which are correlated to each other. However, semantic gaps always exist between images visual features and semantics. Therefore, we utilize click feature to reduce the semantic gap. The second key issue is learning an appropriate distance metric to combine these multimodal features. This paper develops a novel deep multimodal distance metric learning (Deep-MDML) method. A structured ranking model is adopted to utilize both visual and click features in distance metric learning (DML). Specifically, images and their related ranking results are first collected to form the training set. Multimodal features, including click and visual features, are collected with these images. Next, a group of autoencoders is applied to obtain initially a distance metric in different visual spaces, and an MDML method is used to assign optimal weights for different modalities. Next, we conduct alternating optimization to train the ranking model, which is used for the ranking of new queries with click features. Compared with existing image ranking methods, the proposed method adopts a new ranking model to use multimodal features, including click features and visual features in DML. We operated experiments to analyze the proposed Deep-MDML in two benchmark data sets, and the results validate the effects of the method.

Discriminative feature representation: an effective postprocessing solution to low dose CT imaging

NASA Astrophysics Data System (ADS)

Chen, Yang; Liu, Jin; Hu, Yining; Yang, Jian; Shi, Luyao; Shu, Huazhong; Gui, Zhiguo; Coatrieux, Gouenou; Luo, Limin

2017-03-01

This paper proposes a concise and effective approach termed discriminative feature representation (DFR) for low dose computerized tomography (LDCT) image processing, which is currently a challenging problem in medical imaging field. This DFR method assumes LDCT images as the superposition of desirable high dose CT (HDCT) 3D features and undesirable noise-artifact 3D features (the combined term of noise and artifact features induced by low dose scan protocols), and the decomposed HDCT features are used to provide the processed LDCT images with higher quality. The target HDCT features are solved via the DFR algorithm using a featured dictionary composed by atoms representing HDCT features and noise-artifact features. In this study, the featured dictionary is efficiently built using physical phantom images collected from the same CT scanner as the target clinical LDCT images to process. The proposed DFR method also has good robustness in parameter setting for different CT scanner types. This DFR method can be directly applied to process DICOM formatted LDCT images, and has good applicability to current CT systems. Comparative experiments with abdomen LDCT data validate the good performance of the proposed approach. This research was supported by National Natural Science Foundation under grants (81370040, 81530060), the Fundamental Research Funds for the Central Universities, and the Qing Lan Project in Jiangsu Province.

WND-CHARM: Multi-purpose image classification using compound image transforms

PubMed Central

Orlov, Nikita; Shamir, Lior; Macura, Tomasz; Johnston, Josiah; Eckley, D. Mark; Goldberg, Ilya G.

2008-01-01

We describe a multi-purpose image classifier that can be applied to a wide variety of image classification tasks without modifications or fine-tuning, and yet provide classification accuracy comparable to state-of-the-art task-specific image classifiers. The proposed image classifier first extracts a large set of 1025 image features including polynomial decompositions, high contrast features, pixel statistics, and textures. These features are computed on the raw image, transforms of the image, and transforms of transforms of the image. The feature values are then used to classify test images into a set of pre-defined image classes. This classifier was tested on several different problems including biological image classification and face recognition. Although we cannot make a claim of universality, our experimental results show that this classifier performs as well or better than classifiers developed specifically for these image classification tasks. Our classifier’s high performance on a variety of classification problems is attributed to (i) a large set of features extracted from images; and (ii) an effective feature selection and weighting algorithm sensitive to specific image classification problems. The algorithms are available for free download from openmicroscopy.org. PMID:18958301

A study of T2-weighted MR image texture features and diffusion-weighted MR image features for computer-aided diagnosis of prostate cancer

NASA Astrophysics Data System (ADS)

Peng, Yahui; Jiang, Yulei; Antic, Tatjana; Giger, Maryellen L.; Eggener, Scott; Oto, Aytekin

2013-02-01

The purpose of this study was to study T2-weighted magnetic resonance (MR) image texture features and diffusionweighted (DW) MR image features in distinguishing prostate cancer (PCa) from normal tissue. We collected two image datasets: 23 PCa patients (25 PCa and 23 normal tissue regions of interest [ROIs]) imaged with Philips MR scanners, and 30 PCa patients (41 PCa and 26 normal tissue ROIs) imaged with GE MR scanners. A radiologist drew ROIs manually via consensus histology-MR correlation conference with a pathologist. A number of T2-weighted texture features and apparent diffusion coefficient (ADC) features were investigated, and linear discriminant analysis (LDA) was used to combine select strong image features. Area under the receiver operating characteristic (ROC) curve (AUC) was used to characterize feature effectiveness in distinguishing PCa from normal tissue ROIs. Of the features studied, ADC 10th percentile, ADC average, and T2-weighted sum average yielded AUC values (+/-standard error) of 0.95+/-0.03, 0.94+/-0.03, and 0.85+/-0.05 on the Phillips images, and 0.91+/-0.04, 0.89+/-0.04, and 0.70+/-0.06 on the GE images, respectively. The three-feature combination yielded AUC values of 0.94+/-0.03 and 0.89+/-0.04 on the Phillips and GE images, respectively. ADC 10th percentile, ADC average, and T2-weighted sum average, are effective in distinguishing PCa from normal tissue, and appear robust in images acquired from Phillips and GE MR scanners.

Imaging Features of the Brain, Cerebral Vessels and Spine in Pediatric Tuberculous Meningitis with Associated Hydrocephalus

PubMed Central

Rohlwink, Ursula K; Kilborn, Tracy; Wieselthaler, Nicky; Banderker, Ebrahim; Zwane, Eugene; Figaji, Anthony A.

2016-01-01

Background Pediatric tuberculous meningitis leads to high rates of mortality and morbidity. Prompt diagnosis and initiation of treatment are challenging; imaging findings play a key role in establishing the presumptive diagnosis. General brain imaging findings are well reported; however, specific data on cerebral vascular and spinal involvement in children are sparse. Methods This prospective cohort study examined admission and follow up computed tomography brain scans and magnetic resonance imaging scans of the brain, cerebral vessels (magnetic resonance angiogram) and spine at 3 weeks in children treated for tuberculous meningitis with hydrocephalus (inclusion criteria). Exclusion criteria were no hydrocephalus on admission, treatment of hydrocephalus or commencement of anti-TB treatment before study enrolment. Imaging findings were examined in association with outcome at 6 months. Results Forty-four patients (median age 3.3 [0.3-13.1] years) with definite (54%) or probable tuberculous meningitis were enrolled. Good clinical outcome was reported in 72%; the mortality rate was 16%. Infarcts were reported in 66% of patients and were predictive of poor outcome. Magnetic resonance angiogram abnormalities were reported in 55% of patients. Delayed tuberculomas developed in 11% of patients (after starting treatment). Spinal pathology was more common than expected, occurring in 76% of patients. Exudate in the spinal canal increased the difficulty of lumbar puncture and correlated with high cerebrospinal fluid protein content. Conclusion Tuberculous meningitis involves extensive pathology in the central nervous system. Severe infarction was predictive of poor outcome although this was not the case for angiographic abnormalities. Spinal disease occurs commonly and has important implications for diagnosis and treatment. Comprehensive imaging of the brain, spine and cerebral vessels adds insight into disease pathophysiology. PMID:27213261

Imaging Features of the Brain, Cerebral Vessels and Spine in Pediatric Tuberculous Meningitis With Associated Hydrocephalus.

PubMed

Rohlwink, Ursula K; Kilborn, Tracy; Wieselthaler, Nicky; Banderker, Ebrahim; Zwane, Eugene; Figaji, Anthony A

2016-10-01

Pediatric tuberculous meningitis (TBM) leads to high rates of mortality and morbidity. Prompt diagnosis and initiation of treatment are challenging; imaging findings play a key role in establishing the presumptive diagnosis. General brain imaging findings are well reported; however, specific data on cerebral vascular and spinal involvement in children are sparse. This prospective cohort study examined admission and followed up computed tomography brain scans and magnetic resonance imaging scans of the brain, cerebral vessels (magnetic resonance angiogram) and spine at 3 weeks in children treated for TBM with hydrocephalus (HCP; inclusion criteria). Exclusion criteria were no HCP on admission, treatment of HCP or commencement of antituberculosis treatment before study enrollment. Imaging findings were examined in association with outcome at 6 months. Forty-four patients (median age 3.3 [0.3-13.1] years) with definite (54%) or probable TBM were enrolled. Good clinical outcome was reported in 72%; the mortality rate was 16%. Infarcts were reported in 66% of patients and were predictive of poor outcome. Magnetic resonance angiogram abnormalities were reported in 55% of patients. Delayed tuberculomas developed in 11% of patients (after starting treatment). Spinal pathology was more common than expected, occurring in 76% of patients. Exudate in the spinal canal increased the difficulty of lumbar puncture and correlated with high cerebrospinal fluid protein content. TBM involves extensive pathology in the central nervous system. Severe infarction was predictive of poor outcome although this was not the case for angiographic abnormalities. Spinal disease occurs commonly and has important implications for diagnosis and treatment. Comprehensive imaging of the brain, spine and cerebral vessels adds insight into disease pathophysiology.

A Pilot Study of the Attractive Features of Active Videogames Among Chinese Primary School Children.

PubMed

Lau, Patrick W C; Lau, Erica Y; Wang, Jing Jing; Choi, Cheong-Rak; Kim, Chang Gyun

2017-04-01

The present study (1) explored the attractive features that affect Chinese primary school children's preferences of active videogames (AVGs) and (2) contrasted these findings with those in the Western literature. A total of 22 Chinese primary school children were recruited and interviewed. Four AVGs (Wii "Boxing," "Wii Fit™ Plus Obstacle Run"; "EyeToy Knockout", "EyeToy Keep ups") from two commercial consoles (Nintendo® Wii™ and Sony PlayStation ® 2 "EyeToy ® ") were employed. Participants used four selected AVGs for 3 minutes each. After each play period, children (1) described the strengths and weaknesses of each game as well as rated the attractive features of each game based on a 16-item questionnaire and (2) rated up to 5 items that were most influential regarding their AVG preferences. Participants indicated that control was the most significant feature, followed by feedback, goal, and graphics. The top five rated features imply that the perception of competence was the most appealing aspect and expected outcome of Chinese children who play AVGs. Compared with the Western findings regarding attractive AVG features, the present study found certain similarities as well as significant differences among Chinese AVG players. Based on the present study, control, feedback, goal, and graphics are the most significant features that attract Chinese children to play AVGs. Physical exertion, social interaction, competition, and learning outcomes, which are valued according to Western studies, were not mentioned as significant features by Chinese children. These findings demonstrate a need to investigate the effect of cultural background in AVG study design.

Young Children's Ability to Match Facial Features Typical of Race.

ERIC Educational Resources Information Center

Lacoste, Ronald J.

This study examined (1) the ability of 3- and 4-year-old children to racially classify Negro and Caucasian facial features in the absence of skin color as a racial cue; and (2) the relative value attached to the facial features of Negro and Caucasian races. Subjects were 21 middle income, Caucasian children from a privately owned nursery school in…

Variable Use of Features Associated with African American English by Typically Developing Children

ERIC Educational Resources Information Center

Jackson, Janice E.; Pearson, Barbara Zurer

2010-01-01

Purpose: The well-known decline in the use of African American English (AAE) features by groups of school-aged AAE-speaking children was reexamined for patterns of overt-, zero-, and mixed-marking for individual features and individual speakers. Methods: Seven hundred twenty-nine typically developing children between the ages of 4 and 12--511…

MR imaging for detection of trampoline injuries in children.

PubMed

Hauth, E; Jaeger, H; Luckey, P; Beer, M

2017-01-18

The recreational use of trampolines is an increasingly popular activity among children and adolescents. Several studies reported about radiological findings in trampoline related injuries in children. The following publication presents our experience with MRI for detection of trampoline injuries in children. 20 children (mean 9.2 years, range: 4-15 years) who had undergone an MRI study for detection of suspected trampoline injuries within one year were included. 9/20 (45%) children had a radiograph as the first imaging modality in conjunction with primary care. In 11/20 (55%) children MR imaging was performed as the first modality. MR imaging was performed on two 1.5 T scanners with 60 and 70 cm bore design respectively without sedation. In 9/20 (45%) children the injury mechanism was a collision with another child. 7/20 (35%) children experienced leg pain several hours to one day after using the trampoline without acute accident and 4/20 (20%) children described a fall from the trampoline to the ground. All plain radiographs were performed in facilities outside the study centre and all were classified as having no pathological findings. In contrast, MR imaging detected injuries in 15/20 (75%) children. Lower extremity injuries were the most common findings, observed in 12/15 (80%) children. Amongst these, injuries of the ankle and foot were diagnosed in 7/15 (47%) patients. Fractures of the proximal tibial metaphysis were observed in 3/15 children. One child had developed a thoracic vertebral fracture. The two remaining children experienced injuries to the sacrum and a soft tissue injury of the thumb respectively. Seven children described clinical symptoms without an overt accident. Here, fractures of the proximal tibia were observed in 2 children, a hip joint effusion in another 2, and an injury of the ankle and foot in 1 child. There were no associated spinal cord injuries, no fracture dislocations, no vascular injuries and no head and neck injuries. In the majority of children referred for MR imaging with pain after trampoline MR imaging detects injuries. These injuries are often not visible on plain radiographs. Therefore we recommend a generous use of MR imaging in these children after initial negative plain radiography.

TU-F-CAMPUS-J-05: Effect of Uncorrelated Noise Texture On Computed Tomography Quantitative Image Features

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

Oliver, J; Budzevich, M; Moros, E

Purpose: To investigate the relationship between quantitative image features (i.e. radiomics) and statistical fluctuations (i.e. electronic noise) in clinical Computed Tomography (CT) using the standardized American College of Radiology (ACR) CT accreditation phantom and patient images. Methods: Three levels of uncorrelated Gaussian noise were added to CT images of phantom and patients (20) acquired in static mode and respiratory tracking mode. We calculated the noise-power spectrum (NPS) of the original CT images of the phantom, and of the phantom images with added Gaussian noise with means of 50, 80, and 120 HU. Concurrently, on patient images (original and noise-added images),more » image features were calculated: 14 shape, 19 intensity (1st order statistics from intensity volume histograms), 18 GLCM features (2nd order statistics from grey level co-occurrence matrices) and 11 RLM features (2nd order statistics from run-length matrices). These features provide the underlying structural information of the images. GLCM (size 128x128) was calculated with a step size of 1 voxel in 13 directions and averaged. RLM feature calculation was performed in 13 directions with grey levels binning into 128 levels. Results: Adding the electronic noise to the images modified the quality of the NPS, shifting the noise from mostly correlated to mostly uncorrelated voxels. The dramatic increase in noise texture did not affect image structure/contours significantly for patient images. However, it did affect the image features and textures significantly as demonstrated by GLCM differences. Conclusion: Image features are sensitive to acquisition factors (simulated by adding uncorrelated Gaussian noise). We speculate that image features will be more difficult to detect in the presence of electronic noise (an uncorrelated noise contributor) or, for that matter, any other highly correlated image noise. This work focuses on the effect of electronic, uncorrelated, noise and future work shall examine the influence of changes in quantum noise on the features. J. Oliver was supported by NSF FGLSAMP BD award HRD #1139850 and the McKnight Doctoral Fellowship.« less

Feature maps driven no-reference image quality prediction of authentically distorted images

NASA Astrophysics Data System (ADS)

Ghadiyaram, Deepti; Bovik, Alan C.

2015-03-01

Current blind image quality prediction models rely on benchmark databases comprised of singly and synthetically distorted images, thereby learning image features that are only adequate to predict human perceived visual quality on such inauthentic distortions. However, real world images often contain complex mixtures of multiple distortions. Rather than a) discounting the effect of these mixtures of distortions on an image's perceptual quality and considering only the dominant distortion or b) using features that are only proven to be efficient for singly distorted images, we deeply study the natural scene statistics of authentically distorted images, in different color spaces and transform domains. We propose a feature-maps-driven statistical approach which avoids any latent assumptions about the type of distortion(s) contained in an image, and focuses instead on modeling the remarkable consistencies in the scene statistics of real world images in the absence of distortions. We design a deep belief network that takes model-based statistical image features derived from a very large database of authentically distorted images as input and discovers good feature representations by generalizing over different distortion types, mixtures, and severities, which are later used to learn a regressor for quality prediction. We demonstrate the remarkable competence of our features for improving automatic perceptual quality prediction on a benchmark database and on the newly designed LIVE Authentic Image Quality Challenge Database and show that our approach of combining robust statistical features and the deep belief network dramatically outperforms the state-of-the-art.

Imitative or Iconoclastic? How Young Children Use Ready-Made Images in Digital Art

ERIC Educational Resources Information Center

Sakr, Mona; Connelly, Vincent; Wild, Mary

2018-01-01

Digital art-making tends to foreground the inclusion of ready-made images in children's art. While some lament children's use of such images, suggesting that they constrain creativity and expression, others have argued that ready-made digital materials offer children the opportunity to create innovative and potentially iconoclastic artefacts…

MIBG avidity correlates with clinical features, tumor biology, and outcomes in neuroblastoma: A report from the Children's Oncology Group.

PubMed

DuBois, Steven G; Mody, Rajen; Naranjo, Arlene; Van Ryn, Collin; Russ, Douglas; Oldridge, Derek; Kreissman, Susan; Baker, David L; Parisi, Marguerite; Shulkin, Barry L; Bai, Harrison; Diskin, Sharon J; Batra, Vandana; Maris, John M; Park, Julie R; Matthay, Katherine K; Yanik, Gregory

2017-11-01

Prior studies suggest that neuroblastomas that do not accumulate metaiodobenzylguanidine (MIBG) on diagnostic imaging (MIBG non-avid) may have more favorable features compared with MIBG avid tumors. We compared clinical features, biologic features, and clinical outcomes between patients with MIBG nonavid and MIBG avid neuroblastoma. Patients had metastatic high- or intermediate-risk neuroblastoma and were treated on Children's Oncology Group protocols A3973 or A3961. Comparisons of clinical and biologic features according to MIBG avidity were made with chi-squared or Fisher exact tests. Event-free (EFS) and overall (OS) survival compared using log-rank tests and modeled using Cox models. Thirty of 343 patients (8.7%) had MIBG nonavid disease. Patients with nonavid tumors were less likely to have adrenal primary tumors (34.5 vs. 57.2%; P = 0.019), bone metastases (36.7 vs. 61.7%; P = 0.008), or positive urine catecholamines (66.7 vs. 91.0%; P < 0.001) compared with patients with MIBG avid tumors. Nonavid tumors were more likely to be MYCN amplified (53.8 vs. 32.6%; P = 0.030) and had lower norepinephrine transporter expression. Patients with MIBG nonavid disease had a 5-year EFS of 50.0% compared with 38.7% for patients with MIBG avid disease (P = 0.028). On multivariate testing in high-risk patients, MIBG avidity was the sole adverse prognostic factor for EFS identified (hazard ratio 1.77; 95% confidence interval 1.04-2.99; P = 0.034). Patients with MIBG nonavid neuroblastoma have lower rates of adrenal primary tumors, bone metastasis, and catecholamine secretion. Despite being more likely to have MYCN-amplified tumors, these patients have superior outcomes compared with patients with MIBG avid disease. © 2017 Wiley Periodicals, Inc.

Image segmentation-based robust feature extraction for color image watermarking

NASA Astrophysics Data System (ADS)

Li, Mianjie; Deng, Zeyu; Yuan, Xiaochen

2018-04-01

This paper proposes a local digital image watermarking method based on Robust Feature Extraction. The segmentation is achieved by Simple Linear Iterative Clustering (SLIC) based on which an Image Segmentation-based Robust Feature Extraction (ISRFE) method is proposed for feature extraction. Our method can adaptively extract feature regions from the blocks segmented by SLIC. This novel method can extract the most robust feature region in every segmented image. Each feature region is decomposed into low-frequency domain and high-frequency domain by Discrete Cosine Transform (DCT). Watermark images are then embedded into the coefficients in the low-frequency domain. The Distortion-Compensated Dither Modulation (DC-DM) algorithm is chosen as the quantization method for embedding. The experimental results indicate that the method has good performance under various attacks. Furthermore, the proposed method can obtain a trade-off between high robustness and good image quality.

Infrared and Visual Image Fusion through Fuzzy Measure and Alternating Operators

PubMed Central

Bai, Xiangzhi

2015-01-01

The crucial problem of infrared and visual image fusion is how to effectively extract the image features, including the image regions and details and combine these features into the final fusion result to produce a clear fused image. To obtain an effective fusion result with clear image details, an algorithm for infrared and visual image fusion through the fuzzy measure and alternating operators is proposed in this paper. Firstly, the alternating operators constructed using the opening and closing based toggle operator are analyzed. Secondly, two types of the constructed alternating operators are used to extract the multi-scale features of the original infrared and visual images for fusion. Thirdly, the extracted multi-scale features are combined through the fuzzy measure-based weight strategy to form the final fusion features. Finally, the final fusion features are incorporated with the original infrared and visual images using the contrast enlargement strategy. All the experimental results indicate that the proposed algorithm is effective for infrared and visual image fusion. PMID:26184229

Infrared and Visual Image Fusion through Fuzzy Measure and Alternating Operators.

PubMed

Bai, Xiangzhi

2015-07-15

The crucial problem of infrared and visual image fusion is how to effectively extract the image features, including the image regions and details and combine these features into the final fusion result to produce a clear fused image. To obtain an effective fusion result with clear image details, an algorithm for infrared and visual image fusion through the fuzzy measure and alternating operators is proposed in this paper. Firstly, the alternating operators constructed using the opening and closing based toggle operator are analyzed. Secondly, two types of the constructed alternating operators are used to extract the multi-scale features of the original infrared and visual images for fusion. Thirdly, the extracted multi-scale features are combined through the fuzzy measure-based weight strategy to form the final fusion features. Finally, the final fusion features are incorporated with the original infrared and visual images using the contrast enlargement strategy. All the experimental results indicate that the proposed algorithm is effective for infrared and visual image fusion.

Imaging of Kingella kingae musculoskeletal infections in children: a series of 5 cases.

PubMed

Nguyen, Jie C; Rebsamen, Susan L; Tuite, Michael J; Davis, J Muse; Rosas, Humberto G

2018-06-16

Kingella kingae musculoskeletal infections continue to be under-diagnosed and there remains a paucity of literature on its imaging features. The purpose of this manuscript is to review the imaging, clinical, and laboratory findings of microbiology-proven K. kingae infections. A retrospective review of musculoskeletal infections between January 1, 2013 and Dec 31, 2016 yielded 134 patients from whom 5 patients had confirmed K. kingae infections (3 boys and 2 girls, mean age of 16 months, range 9-38 months). Picture archiving and communication system and electronic medical records were reviewed. At presentation, none of the patients had a fever and not all patients had abnormal inflammatory markers. Three patients had septic arthritis (2 knee and 1 sternomanubrial joints), one had epiphyseal osteomyelitis, and one had lumbar spondylodiscitis. The case of epiphyseal osteomyelitis of the distal humerus also had elbow joint involvement. A combination of radiography (n = 4), ultrasound (n = 2), and magnetic resonance (MR) imaging (n = 5) were performed. Prominent synovial thickening was observed for both knee and elbow joints and extensive regional myositis for all except for the patient with sternomanubrial joint infection. The diagnosis of K. kingae infection resulted in a change in the antibiotic regimen in 80% of the patients. Disproportionate synovial thickening, prominent peri-articular myositis, and/or characteristic sites of involvement demonstrating imaging features of infection or inflammation in a young child with mild infectious symptoms and elevated inflammatory markers should invoke the possibility of an underlying K. kingae infection.

Assessing speech perception in children with cochlear implants using a modified hybrid visual habituation procedure.

PubMed

Core, Cynthia; Brown, Janean W; Larsen, Michael D; Mahshie, James

2014-01-01

The objectives of this research were to determine whether an adapted version of a Hybrid Visual Habituation procedure could be used to assess speech perception of phonetic and prosodic features of speech (vowel height, lexical stress, and intonation) in individual pre-school-age children who use cochlear implants. Nine children ranging in age from 3;4 to 5;5 participated in this study. Children were prelingually deaf and used cochlear implants and had no other known disabilities. Children received two speech feature tests using an adaptation of a Hybrid Visual Habituation procedure. Seven of the nine children demonstrated perception of at least one speech feature using this procedure using results from a Bayesian linear regression analysis. At least one child demonstrated perception of each speech feature using this assessment procedure. An adapted version of the Hybrid Visual Habituation Procedure with an appropriate statistical analysis provides a way to assess phonetic and prosodicaspects of speech in pre-school-age children who use cochlear implants.

Classification of fresh and frozen-thawed pork muscles using visible and near infrared hyperspectral imaging and textural analysis.

PubMed

Pu, Hongbin; Sun, Da-Wen; Ma, Ji; Cheng, Jun-Hu

2015-01-01

The potential of visible and near infrared hyperspectral imaging was investigated as a rapid and nondestructive technique for classifying fresh and frozen-thawed meats by integrating critical spectral and image features extracted from hyperspectral images in the region of 400-1000 nm. Six feature wavelengths (400, 446, 477, 516, 592 and 686 nm) were identified using uninformative variable elimination and successive projections algorithm. Image textural features of the principal component images from hyperspectral images were obtained using histogram statistics (HS), gray level co-occurrence matrix (GLCM) and gray level-gradient co-occurrence matrix (GLGCM). By these spectral and textural features, probabilistic neural network (PNN) models for classification of fresh and frozen-thawed pork meats were established. Compared with the models using the optimum wavelengths only, optimum wavelengths with HS image features, and optimum wavelengths with GLCM image features, the model integrating optimum wavelengths with GLGCM gave the highest classification rate of 93.14% and 90.91% for calibration and validation sets, respectively. Results indicated that the classification accuracy can be improved by combining spectral features with textural features and the fusion of critical spectral and textural features had better potential than single spectral extraction in classifying fresh and frozen-thawed pork meat. Copyright © 2014 Elsevier Ltd. All rights reserved.

Fusion of infrared polarization and intensity images based on improved toggle operator

NASA Astrophysics Data System (ADS)

Zhu, Pan; Ding, Lei; Ma, Xiaoqing; Huang, Zhanhua

2018-01-01

Integration of infrared polarization and intensity images has been a new topic in infrared image understanding and interpretation. The abundant infrared details and target from infrared image and the salient edge and shape information from polarization image should be preserved or even enhanced in the fused result. In this paper, a new fusion method is proposed for infrared polarization and intensity images based on the improved multi-scale toggle operator with spatial scale, which can effectively extract the feature information of source images and heavily reduce redundancy among different scale. Firstly, the multi-scale image features of infrared polarization and intensity images are respectively extracted at different scale levels by the improved multi-scale toggle operator. Secondly, the redundancy of the features among different scales is reduced by using spatial scale. Thirdly, the final image features are combined by simply adding all scales of feature images together, and a base image is calculated by performing mean value weighted method on smoothed source images. Finally, the fusion image is obtained by importing the combined image features into the base image with a suitable strategy. Both objective assessment and subjective vision of the experimental results indicate that the proposed method obtains better performance in preserving the details and edge information as well as improving the image contrast.

Method for the reduction of image content redundancy in large image databases

DOEpatents

Tobin, Kenneth William; Karnowski, Thomas P.

2010-03-02

A method of increasing information content for content-based image retrieval (CBIR) systems includes the steps of providing a CBIR database, the database having an index for a plurality of stored digital images using a plurality of feature vectors, the feature vectors corresponding to distinct descriptive characteristics of the images. A visual similarity parameter value is calculated based on a degree of visual similarity between features vectors of an incoming image being considered for entry into the database and feature vectors associated with a most similar of the stored images. Based on said visual similarity parameter value it is determined whether to store or how long to store the feature vectors associated with the incoming image in the database.

A natural-color mapping for single-band night-time image based on FPGA

NASA Astrophysics Data System (ADS)

Wang, Yilun; Qian, Yunsheng

2018-01-01

A natural-color mapping for single-band night-time image method based on FPGA can transmit the color of the reference image to single-band night-time image, which is consistent with human visual habits and can help observers identify the target. This paper introduces the processing of the natural-color mapping algorithm based on FPGA. Firstly, the image can be transformed based on histogram equalization, and the intensity features and standard deviation features of reference image are stored in SRAM. Then, the real-time digital images' intensity features and standard deviation features are calculated by FPGA. At last, FPGA completes the color mapping through matching pixels between images using the features in luminance channel.

Behavioral features of CHARGE syndrome: parents' perspectives of three children with CHARGE syndrome.

PubMed

Lauger, Kimberly; Cornelius, Nancy; Keedy, Wendy

2005-03-15

As the population first diagnosed with CHARGE Syndrome has aged, information has emerged about specific behavioral features of this syndrome. Once the medical features are managed, it is the behavioral features that interfere with our children's ability to form reciprocal relationships, to gain formal communication skills, to make the educational gains they are cognitively capable of, and to ultimately care for themselves. In telling the informal case studies of our children, we hope their behavioral commonalities, in spite of their medical and educational differences, will be apparent as well as the complexity of the multiple types of behavior observed. We remain hopeful that answers can be found that will help our children and our families cope with this very debilitating feature of CHARGE. Copyright (c) 2005 Wiley-Liss, Inc.

The relationship study between image features and detection probability based on psychology experiments

NASA Astrophysics Data System (ADS)

Lin, Wei; Chen, Yu-hua; Wang, Ji-yuan; Gao, Hong-sheng; Wang, Ji-jun; Su, Rong-hua; Mao, Wei

2011-04-01

Detection probability is an important index to represent and estimate target viability, which provides basis for target recognition and decision-making. But it will expend a mass of time and manpower to obtain detection probability in reality. At the same time, due to the different interpretation of personnel practice knowledge and experience, a great difference will often exist in the datum obtained. By means of studying the relationship between image features and perception quantity based on psychology experiments, the probability model has been established, in which the process is as following.Firstly, four image features have been extracted and quantified, which affect directly detection. Four feature similarity degrees between target and background were defined. Secondly, the relationship between single image feature similarity degree and perception quantity was set up based on psychological principle, and psychological experiments of target interpretation were designed which includes about five hundred people for interpretation and two hundred images. In order to reduce image features correlativity, a lot of artificial synthesis images have been made which include images with single brightness feature difference, images with single chromaticity feature difference, images with single texture feature difference and images with single shape feature difference. By analyzing and fitting a mass of experiments datum, the model quantitys have been determined. Finally, by applying statistical decision theory and experimental results, the relationship between perception quantity with target detection probability has been found. With the verification of a great deal of target interpretation in practice, the target detection probability can be obtained by the model quickly and objectively.

Enhancing facial features by using clear facial features

NASA Astrophysics Data System (ADS)

Rofoo, Fanar Fareed Hanna

2017-09-01

The similarity of features between individuals of same ethnicity motivated the idea of this project. The idea of this project is to extract features of clear facial image and impose them on blurred facial image of same ethnic origin as an approach to enhance a blurred facial image. A database of clear images containing 30 individuals equally divided to five different ethnicities which were Arab, African, Chines, European and Indian. Software was built to perform pre-processing on images in order to align the features of clear and blurred images. And the idea was to extract features of clear facial image or template built from clear facial images using wavelet transformation to impose them on blurred image by using reverse wavelet. The results of this approach did not come well as all the features did not align together as in most cases the eyes were aligned but the nose or mouth were not aligned. Then we decided in the next approach to deal with features separately but in the result in some cases a blocky effect was present on features due to not having close matching features. In general the available small database did not help to achieve the goal results, because of the number of available individuals. The color information and features similarity could be more investigated to achieve better results by having larger database as well as improving the process of enhancement by the availability of closer matches in each ethnicity.

It's What's on the Outside that Matters: An Advantage for External Features in Children's Word Recognition

ERIC Educational Resources Information Center

Webb, Tessa M.; Beech, John R.; Mayall, Kate M.; Andrews, Antony S.

2006-01-01

The relative importance of internal and external letter features of words in children's developing reading was investigated to clarify further the nature of early featural analysis. In Experiment 1, 72 6-, 8-, and 10-year-olds read aloud words displayed as wholes, external features only (central features missing, thereby preserving word shape…

Speak Out for Children. Winter 1992/1993 through Summer/Fall 1994.

ERIC Educational Resources Information Center

Levy, David L., Ed.; Diamond, Elliott H., Ed.

1993-01-01

"Speak Out for Children" is the quarterly newsletter of the Children's Rights Council (CRC), which is concerned with the healthy development of children of divorced and separated parents. The newsletter consists of feature articles and regular sections and columns. Feature articles of Volume 8, Number 1 are: "The Controversial Truth: Two-Parent…

In Vivo Measurement of Pediatric Vocal Fold Motion Using Structured Light Laser Projection

PubMed Central

Patel, Rita R.; Donohue, Kevin D.; Lau, Daniel; Unnikrishnan, Harikrishnan

2013-01-01

Summary Objective The aim of the study was to present the development of a miniature structured light laser projection endoscope and to quantify vocal fold length and vibratory features related to impact stress of the pediatric glottis using high-speed imaging. Study Design The custom-developed laser projection system consists of a green laser with a 4-mm diameter optics module at the tip of the endoscope, projecting 20 vertical laser lines on the glottis. Measurements of absolute phonatory vocal fold length, membranous vocal fold length, peak amplitude, amplitude-to-length ratio, average closing velocity, and impact velocity were obtained in five children (6–9 years), two adult male and three adult female participants without voice disorders, and one child (10 years) with bilateral vocal fold nodules during modal phonation. Results Independent measurements made on the glottal length of a vocal fold phantom demonstrated a 0.13 mm bias error with a standard deviation of 0.23 mm, indicating adequate precision and accuracy for measuring vocal fold structures and displacement. First, in vivo measurements of amplitude-to-length ratio, peak closing velocity, and impact velocity during phonation in pediatric population and a child with vocal fold nodules are reported. Conclusion The proposed laser projection system can be used to obtain in vivo measurements of absolute length and vibratory features in children and adults. Children have large amplitude-to-length ratio compared with typically developing adults, whereas nodules result in larger peak amplitude, amplitude-to-length ratio, average closing velocity, and impact velocity compared with typically developing children. PMID:23809569

[Image Feature Extraction and Discriminant Analysis of Xinjiang Uygur Medicine Based on Color Histogram].

PubMed

Hamit, Murat; Yun, Weikang; Yan, Chuanbo; Kutluk, Abdugheni; Fang, Yang; Alip, Elzat

2015-06-01

Image feature extraction is an important part of image processing and it is an important field of research and application of image processing technology. Uygur medicine is one of Chinese traditional medicine and researchers pay more attention to it. But large amounts of Uygur medicine data have not been fully utilized. In this study, we extracted the image color histogram feature of herbal and zooid medicine of Xinjiang Uygur. First, we did preprocessing, including image color enhancement, size normalizition and color space transformation. Then we extracted color histogram feature and analyzed them with statistical method. And finally, we evaluated the classification ability of features by Bayes discriminant analysis. Experimental results showed that high accuracy for Uygur medicine image classification was obtained by using color histogram feature. This study would have a certain help for the content-based medical image retrieval for Xinjiang Uygur medicine.

Decomposition and extraction: a new framework for visual classification.

PubMed

Fang, Yuqiang; Chen, Qiang; Sun, Lin; Dai, Bin; Yan, Shuicheng

2014-08-01

In this paper, we present a novel framework for visual classification based on hierarchical image decomposition and hybrid midlevel feature extraction. Unlike most midlevel feature learning methods, which focus on the process of coding or pooling, we emphasize that the mechanism of image composition also strongly influences the feature extraction. To effectively explore the image content for the feature extraction, we model a multiplicity feature representation mechanism through meaningful hierarchical image decomposition followed by a fusion step. In particularly, we first propose a new hierarchical image decomposition approach in which each image is decomposed into a series of hierarchical semantical components, i.e, the structure and texture images. Then, different feature extraction schemes can be adopted to match the decomposed structure and texture processes in a dissociative manner. Here, two schemes are explored to produce property related feature representations. One is based on a single-stage network over hand-crafted features and the other is based on a multistage network, which can learn features from raw pixels automatically. Finally, those multiple midlevel features are incorporated by solving a multiple kernel learning task. Extensive experiments are conducted on several challenging data sets for visual classification, and experimental results demonstrate the effectiveness of the proposed method.

Black Toenail Sign in MELAS Syndrome.

PubMed

Whitehead, Matthew T; Wien, Michael; Lee, Bonmyong; Bass, Nancy; Gropman, Andrea

2017-10-01

Mitochondrial encephalopathy with lactic acidosis and stroke-like episodes (MELAS) syndrome is a mitochondrial disorder often causing progressive brain injury that is not confined to large arterial territories. Severe insults ultimately lead to gyral necrosis affecting the cortex and juxtacortical white matter; the neuroimaging correlate is partial gyral signal suppression on T2/FLAIR sequences that resemble black toenails. We aimed to characterize the imaging features and the natural history of MELAS-related gyral necrosis. Databases at two children's hospitals were searched for brain magnetic resonance imaging studies of individuals with MELAS. Examinations with motion artifact and those lacking T2/FLAIR sequences were excluded. The location, the cumulative number, and the maximum transverse diameter of necrotic gyral lesions were assessed using T2-weighted images and T2/FLAIR sequences. Wilcoxon signed-rank test was employed to evaluate the relationship between disease duration and the number of necrotic lesions. One hundred twenty-four examinations from patients with 14 unique MELAS patients (16 ± 3 years) were evaluated. Six of the eight patients who developed brain lesions also developed gyral necroses (mean 13, range 0 to 44). Necrotic lesions varied in maximal diameter from 4 to 25 mm. Cumulative necrotic lesions correlated with disease duration (P < 0.001). The black toenail sign signifying gyral necrosis is a common imaging feature in individuals with MELAS syndrome. The extent of gyral necrosis correlates with disease duration. Copyright © 2017 Elsevier Inc. All rights reserved.

Clinical and magnetic resonance imaging findings in patients with Leigh syndrome and SURF1 mutations.

PubMed

Sonam, Kothari; Khan, Nahid Akthar; Bindu, Parayil Sankaran; Taly, Arun B; Gayathri, N; Bharath, M M Srinivas; Govindaraju, C; Arvinda, H R; Nagappa, Madhu; Sinha, Sanjib; Thangaraj, K

2014-10-01

Mutation in the SURF1 is one of the most common nuclear mutations associated with Leigh syndrome and cytochrome c oxidase deficiency. This study aims to describe the phenotypic and imaging features in four patients with Leigh syndrome and novel SURF1 mutation. The study included four patients with Leigh syndrome and SURF1 mutations identified from a cohort of 25 children with Leigh syndrome seen over a period of six years (2006-2012). All the patients underwent a detailed neurological assessment, muscle biopsy, and sequencing of the complete mitochondrial genome and SURF1. Three patients had classical presentation of Leigh syndrome. The fourth patient had a later age of onset with ataxia as the presenting manifestation and a stable course. Hypertrichosis, facial dysmorphism and hypopigmentation were the additional phenotypic features noted. On magnetic resonance imaging all patients had brainstem and cerebellar involvement and two had basal ganglia involvement in addition. The bilateral symmetrical hypertrophic olivary degeneration in these patients was striking. The SURF1 analysis identified previously unreported mutations in all the patients. On follow-up three patients expired and one had a stable course. Patients with Leigh syndrome and SURF1 mutation often have skin and hair abnormalities. Bilateral symmetrical hypertrophic olivary degeneration was a consistent finding on magnetic resonance imaging in these patients. Copyright © 2013 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

Image feature detection and extraction techniques performance evaluation for development of panorama under different light conditions

NASA Astrophysics Data System (ADS)

Patil, Venkat P.; Gohatre, Umakant B.

2018-04-01

The technique of obtaining a wider field-of-view of an image to get high resolution integrated image is normally required for development of panorama of a photographic images or scene from a sequence of part of multiple views. There are various image stitching methods developed recently. For image stitching five basic steps are adopted stitching which are Feature detection and extraction, Image registration, computing homography, image warping and Blending. This paper provides review of some of the existing available image feature detection and extraction techniques and image stitching algorithms by categorizing them into several methods. For each category, the basic concepts are first described and later on the necessary modifications made to the fundamental concepts by different researchers are elaborated. This paper also highlights about the some of the fundamental techniques for the process of photographic image feature detection and extraction methods under various illumination conditions. The Importance of Image stitching is applicable in the various fields such as medical imaging, astrophotography and computer vision. For comparing performance evaluation of the techniques used for image features detection three methods are considered i.e. ORB, SURF, HESSIAN and time required for input images feature detection is measured. Results obtained finally concludes that for daylight condition, ORB algorithm found better due to the fact that less tome is required for more features extracted where as for images under night light condition it shows that SURF detector performs better than ORB/HESSIAN detectors.

Computer-aided prognosis on breast cancer with hematoxylin and eosin histopathology images: A review.

PubMed

Chen, Jia-Mei; Li, Yan; Xu, Jun; Gong, Lei; Wang, Lin-Wei; Liu, Wen-Lou; Liu, Juan

2017-03-01

With the advance of digital pathology, image analysis has begun to show its advantages in information analysis of hematoxylin and eosin histopathology images. Generally, histological features in hematoxylin and eosin images are measured to evaluate tumor grade and prognosis for breast cancer. This review summarized recent works in image analysis of hematoxylin and eosin histopathology images for breast cancer prognosis. First, prognostic factors for breast cancer based on hematoxylin and eosin histopathology images were summarized. Then, usual procedures of image analysis for breast cancer prognosis were systematically reviewed, including image acquisition, image preprocessing, image detection and segmentation, and feature extraction. Finally, the prognostic value of image features and image feature-based prognostic models was evaluated. Moreover, we discussed the issues of current analysis, and some directions for future research.

Automatic brain tumor detection in MRI: methodology and statistical validation

NASA Astrophysics Data System (ADS)

Iftekharuddin, Khan M.; Islam, Mohammad A.; Shaik, Jahangheer; Parra, Carlos; Ogg, Robert

2005-04-01

Automated brain tumor segmentation and detection are immensely important in medical diagnostics because it provides information associated to anatomical structures as well as potential abnormal tissue necessary to delineate appropriate surgical planning. In this work, we propose a novel automated brain tumor segmentation technique based on multiresolution texture information that combines fractal Brownian motion (fBm) and wavelet multiresolution analysis. Our wavelet-fractal technique combines the excellent multiresolution localization property of wavelets to texture extraction of fractal. We prove the efficacy of our technique by successfully segmenting pediatric brain MR images (MRIs) from St. Jude Children"s Research Hospital. We use self-organizing map (SOM) as our clustering tool wherein we exploit both pixel intensity and multiresolution texture features to obtain segmented tumor. Our test results show that our technique successfully segments abnormal brain tissues in a set of T1 images. In the next step, we design a classifier using Feed-Forward (FF) neural network to statistically validate the presence of tumor in MRI using both the multiresolution texture and the pixel intensity features. We estimate the corresponding receiver operating curve (ROC) based on the findings of true positive fractions and false positive fractions estimated from our classifier at different threshold values. An ROC, which can be considered as a gold standard to prove the competence of a classifier, is obtained to ascertain the sensitivity and specificity of our classifier. We observe that at threshold 0.4 we achieve true positive value of 1.0 (100%) sacrificing only 0.16 (16%) false positive value for the set of 50 T1 MRI analyzed in this experiment.

Qualitative Analysis of Cognitive Interviews With School Children: A Web-Based Food Intake Questionnaire

PubMed Central

Kupek, Emil

2016-01-01

Background The use of computers to administer dietary assessment questionnaires has shown potential, particularly due to the variety of interactive features that can attract and sustain children’s attention. Cognitive interviews can help researchers to gain insights into how children understand and elaborate their response processes in this type of questionnaire. Objective To present the cognitive interview results of children who answered the WebCAAFE, a Web-based questionnaire, to obtain an in-depth understanding of children’s response processes. Methods Cognitive interviews were conducted with children (using a pretested interview script). Analyses were carried out using thematic analysis within a grounded theory framework of inductive coding. Results A total of 40 children participated in the study, and 4 themes were identified: (1) the meaning of words, (2) understanding instructions, (3) ways to resolve possible problems, and (4) suggestions for improving the questionnaire. Most children understood questions that assessed nutritional intake over the past 24 hours, although the structure of the questionnaire designed to facilitate recall of dietary intake was not always fully understood. Younger children (7 and 8 years old) had more difficulty relating the food images to mixed dishes and foods eaten with bread (eg, jam, cheese). Children were able to provide suggestions for improving future versions of the questionnaire. Conclusions More attention should be paid to children aged 8 years or below, as they had the greatest difficulty completing the WebCAAFE. PMID:27895005

Enhancement of morphological and vascular features in OCT images using a modified Bayesian residual transform

PubMed Central

Tan, Bingyao; Wong, Alexander; Bizheva, Kostadinka

2018-01-01

A novel image processing algorithm based on a modified Bayesian residual transform (MBRT) was developed for the enhancement of morphological and vascular features in optical coherence tomography (OCT) and OCT angiography (OCTA) images. The MBRT algorithm decomposes the original OCT image into multiple residual images, where each image presents information at a unique scale. Scale selective residual adaptation is used subsequently to enhance morphological features of interest, such as blood vessels and tissue layers, and to suppress irrelevant image features such as noise and motion artefacts. The performance of the proposed MBRT algorithm was tested on a series of cross-sectional and enface OCT and OCTA images of retina and brain tissue that were acquired in-vivo. Results show that the MBRT reduces speckle noise and motion-related imaging artefacts locally, thus improving significantly the contrast and visibility of morphological features in the OCT and OCTA images. PMID:29760996

Abdominal MR imaging in children: motion compensation, sequence optimization, and protocol organization.

PubMed

Chavhan, Govind B; Babyn, Paul S; Vasanawala, Shreyas S

2013-05-01

Familiarity with basic sequence properties and their trade-offs is necessary for radiologists performing abdominal magnetic resonance (MR) imaging. Acquiring diagnostic-quality MR images in the pediatric abdomen is challenging due to motion, inability to breath hold, varying patient size, and artifacts. Motion-compensation techniques (eg, respiratory gating, signal averaging, suppression of signal from moving tissue, swapping phase- and frequency-encoding directions, use of faster sequences with breath holding, parallel imaging, and radial k-space filling) can improve image quality. Each of these techniques is more suitable for use with certain sequences and acquisition planes and in specific situations and age groups. Different T1- and T2-weighted sequences work better in different age groups and with differing acquisition planes and have specific advantages and disadvantages. Dynamic imaging should be performed differently in younger children than in older children. In younger children, the sequence and the timing of dynamic phases need to be adjusted. Different sequences work better in smaller children and in older children because of differing breath-holding ability, breathing patterns, field of view, and use of sedation. Hence, specific protocols should be maintained for younger children and older children. Combining longer-higher-resolution sequences and faster-lower-resolution sequences helps acquire diagnostic-quality images in a reasonable time. © RSNA, 2013.

Quantitative imaging features: extension of the oncology medical image database

NASA Astrophysics Data System (ADS)

Patel, M. N.; Looney, P. T.; Young, K. C.; Halling-Brown, M. D.

2015-03-01

Radiological imaging is fundamental within the healthcare industry and has become routinely adopted for diagnosis, disease monitoring and treatment planning. With the advent of digital imaging modalities and the rapid growth in both diagnostic and therapeutic imaging, the ability to be able to harness this large influx of data is of paramount importance. The Oncology Medical Image Database (OMI-DB) was created to provide a centralized, fully annotated dataset for research. The database contains both processed and unprocessed images, associated data, and annotations and where applicable expert determined ground truths describing features of interest. Medical imaging provides the ability to detect and localize many changes that are important to determine whether a disease is present or a therapy is effective by depicting alterations in anatomic, physiologic, biochemical or molecular processes. Quantitative imaging features are sensitive, specific, accurate and reproducible imaging measures of these changes. Here, we describe an extension to the OMI-DB whereby a range of imaging features and descriptors are pre-calculated using a high throughput approach. The ability to calculate multiple imaging features and data from the acquired images would be valuable and facilitate further research applications investigating detection, prognosis, and classification. The resultant data store contains more than 10 million quantitative features as well as features derived from CAD predictions. Theses data can be used to build predictive models to aid image classification, treatment response assessment as well as to identify prognostic imaging biomarkers.

Pott's disease in Moroccan children: clinical features and investigation of the interleukin-12/interferon-γ pathway.

PubMed

El Azbaoui, S; Alaoui Mrani, N; Sabri, A; Jouhadi, Z; Ailal, F; Bousfiha, A A; Najib, J; El Hafidi, N; Deswarte, C; Schurr, E; Bustamante, J; Boisson-Dupuis, S; Casanova, J-L; Abel, L; El Baghdadi, J

2015-12-01

Tuberculosis spondylodiscitis (TS), or Pott's disease, an extra-pulmonary form of tuberculosis (TB), is rare and difficult to diagnose in children. Some cases of severe TB in children were recently explained by inborn errors of immunity affecting the interleukin-12/interferon-gamma (IL-12/IFN-γ) axis. To analyse clinical data on Moroccan children with TS, and to perform immunological and genetic explorations of the IL-12/IFN-γ axis. We studied nine children with TS diagnosed between 2012 and 2014. We investigated the IL-12/IFN-γ circuit by both whole-blood assays and sequencing of the coding regions of 14 core genes of this pathway. A diagnosis of TS was based on a combination of clinical, biological, histological and radiological data. QuantiFERON(®)-TB Gold In-Tube results were positive in 75% of patients. Whole-blood assays showed normal IL-12 and IFN-γ production in all but one patient, who displayed impaired decreased response to IL-12. No candidate disease-causing mutations were detected in the exonic regions of the 14 genes. TS diagnosis in children remains challenging, and is based largely on imaging. Further investigations of TS in children are required to determine the role of genetic defects in pathways that may or may not be related to the IL-12/IFN-γ axis.

Childhood-onset Takayasu arteritis: an update.

PubMed

Mathew, Ashish J; Goel, Ruchika; Kumar, Sathish; Danda, Debashish

2016-02-01

Childhood-onset Takayasu arteritis (c-TA) is a distinct subset affecting a wide age group, ranging from young infants to adolescents and it differs from adult TA in many aspects. There is scarcity of data on c-TA worldwide. The disease is classified using the European League Against Rheumatism/Pediatric Rheumatology International Trials Organization/Pediatric Rheumatology European Society criteria. The non-specific nature of presenting complaints and lack of appropriate biomarkers delay the early diagnosis of this illness and many children present with complications, which become irreversible once they set in. One of the largest cohorts of 40 children with c-TA from our center reports hypertension as the commonest presenting feature. Systemic symptoms like headache, fever and weight loss are also described. Assessment of disease in c-TA is done by correlating clinical features with raised inflammatory markers. Advanced imaging plays an important role in diagnosis. In c-TA, the role of magnetic resonance angiography is advocated, taking into consideration the enormous amount of radiation exposure with other modalities. Complications of c-TA include cardiovascular, pulmonary, neurological and those arising secondary to long-term steroid and immunosuppression therapy. © 2015 Asia Pacific League of Associations for Rheumatology and Wiley Publishing Asia Pty Ltd.

The Role of Feature Type and Causal Status in 4-5-Year-Old Children's Biological Categorizations

ERIC Educational Resources Information Center

Meunier, Benjamin; Cordier, Francoise

2009-01-01

The present study investigated the role of the causal status of features and feature type in biological categorizations by young children. Study 1 showed that 5-year-olds are more strongly influenced by causal features than effect features; 4-year-olds exhibit no such tendency. There therefore appears to be a conceptual change between the ages of…

A standardised protocol for texture feature analysis of endoscopic images in gynaecological cancer.

PubMed

Neofytou, Marios S; Tanos, Vasilis; Pattichis, Marios S; Pattichis, Constantinos S; Kyriacou, Efthyvoulos C; Koutsouris, Dimitris D

2007-11-29

In the development of tissue classification methods, classifiers rely on significant differences between texture features extracted from normal and abnormal regions. Yet, significant differences can arise due to variations in the image acquisition method. For endoscopic imaging of the endometrium, we propose a standardized image acquisition protocol to eliminate significant statistical differences due to variations in: (i) the distance from the tissue (panoramic vs close up), (ii) difference in viewing angles and (iii) color correction. We investigate texture feature variability for a variety of targets encountered in clinical endoscopy. All images were captured at clinically optimum illumination and focus using 720 x 576 pixels and 24 bits color for: (i) a variety of testing targets from a color palette with a known color distribution, (ii) different viewing angles, (iv) two different distances from a calf endometrial and from a chicken cavity. Also, human images from the endometrium were captured and analysed. For texture feature analysis, three different sets were considered: (i) Statistical Features (SF), (ii) Spatial Gray Level Dependence Matrices (SGLDM), and (iii) Gray Level Difference Statistics (GLDS). All images were gamma corrected and the extracted texture feature values were compared against the texture feature values extracted from the uncorrected images. Statistical tests were applied to compare images from different viewing conditions so as to determine any significant differences. For the proposed acquisition procedure, results indicate that there is no significant difference in texture features between the panoramic and close up views and between angles. For a calibrated target image, gamma correction provided an acquired image that was a significantly better approximation to the original target image. In turn, this implies that the texture features extracted from the corrected images provided for better approximations to the original images. Within the proposed protocol, for human ROIs, we have found that there is a large number of texture features that showed significant differences between normal and abnormal endometrium. This study provides a standardized protocol for avoiding any significant texture feature differences that may arise due to variability in the acquisition procedure or the lack of color correction. After applying the protocol, we have found that significant differences in texture features will only be due to the fact that the features were extracted from different types of tissue (normal vs abnormal).

The Children's Body Image Scale: reliability and use with international standards for body mass index.

PubMed

Truby, Helen; Paxton, Susan J

2008-03-01

To test the reliability of the Children's Body Image Scale (CBIS) and assess its usefulness in the context of new body size charts for children. Participants were 281 primary schoolchildren with 50% being retested after 3 weeks. The CBIS figure scale was compared with a range of international body mass index (BMI) reference standards. Children had a high degree of body image dissatisfaction. The test-retest reliability of the CBIS was supported. The CBIS is a useful tool for assessing body image in children with sound scale properties. It can also be used to identify the body size of children, which lies outside the healthy weight range of BMI.

MR imaging features associated with distant metastasis-free survival of patients with invasive breast cancer: a case-control study.

PubMed

Song, Sung Eun; Shin, Sung Ui; Moon, Hyeong-Gon; Ryu, Han Suk; Kim, Kwangsoo; Moon, Woo Kyung

2017-04-01

Preoperative breast magnetic resonance (MR) imaging features of primary breast cancers may have the potential to act as prognostic biomarkers by providing morphologic and kinetic features representing inter- or intra-tumor heterogeneity. Recent radiogenomic studies reveal that several radiologist-annotated image features are associated with genes or signal pathways involved in tumor progression, treatment resistance, and distant metastasis (DM). We investigate whether preoperative breast MR imaging features are associated with worse DM-free survival in patients with invasive breast cancer. Of the 3536 patients with primary breast cancers who underwent preoperative MR imaging between 2003 and 2009, 147 patients with DM were identified and one-to-one matched with control patients (n = 147) without DM according to clinical-pathologic variables. Three radiologists independently reviewed the MR images of 294 patients, and the association of DM-free survival with MR imaging and clinical-pathologic features was assessed using Cox proportional hazard models. Of MR imaging features, rim enhancement (hazard ratio [HR], 1.83 [95% confidence interval, CI 1.29, 2.51]; p = 0.001) and peritumoral edema (HR, 1.48 [95% CI 1.03, 2.11]; p = 0.032) were the significant features associated with worse DM-free survival. The significant MR imaging features, however, were different between breast cancer subtypes and stages. Preoperative breast MR imaging features of rim enhancement and peritumoral edema may be used as prognostic biomarkers that help predict DM risk in patients with breast cancer, thereby potentially enabling improved personalized treatment and monitoring strategies for individual patients.

Adapting Local Features for Face Detection in Thermal Image.

PubMed

Ma, Chao; Trung, Ngo Thanh; Uchiyama, Hideaki; Nagahara, Hajime; Shimada, Atsushi; Taniguchi, Rin-Ichiro

2017-11-27

A thermal camera captures the temperature distribution of a scene as a thermal image. In thermal images, facial appearances of different people under different lighting conditions are similar. This is because facial temperature distribution is generally constant and not affected by lighting condition. This similarity in face appearances is advantageous for face detection. To detect faces in thermal images, cascade classifiers with Haar-like features are generally used. However, there are few studies exploring the local features for face detection in thermal images. In this paper, we introduce two approaches relying on local features for face detection in thermal images. First, we create new feature types by extending Multi-Block LBP. We consider a margin around the reference and the generally constant distribution of facial temperature. In this way, we make the features more robust to image noise and more effective for face detection in thermal images. Second, we propose an AdaBoost-based training method to get cascade classifiers with multiple types of local features. These feature types have different advantages. In this way we enhance the description power of local features. We did a hold-out validation experiment and a field experiment. In the hold-out validation experiment, we captured a dataset from 20 participants, comprising 14 males and 6 females. For each participant, we captured 420 images with 10 variations in camera distance, 21 poses, and 2 appearances (participant with/without glasses). We compared the performance of cascade classifiers trained by different sets of the features. The experiment results showed that the proposed approaches effectively improve the performance of face detection in thermal images. In the field experiment, we compared the face detection performance in realistic scenes using thermal and RGB images, and gave discussion based on the results.

Generating description with multi-feature fusion and saliency maps of image

NASA Astrophysics Data System (ADS)

Liu, Lisha; Ding, Yuxuan; Tian, Chunna; Yuan, Bo

2018-04-01

Generating description for an image can be regard as visual understanding. It is across artificial intelligence, machine learning, natural language processing and many other areas. In this paper, we present a model that generates description for images based on RNN (recurrent neural network) with object attention and multi-feature of images. The deep recurrent neural networks have excellent performance in machine translation, so we use it to generate natural sentence description for images. The proposed method uses single CNN (convolution neural network) that is trained on ImageNet to extract image features. But we think it can not adequately contain the content in images, it may only focus on the object area of image. So we add scene information to image feature using CNN which is trained on Places205. Experiments show that model with multi-feature extracted by two CNNs perform better than which with a single feature. In addition, we make saliency weights on images to emphasize the salient objects in images. We evaluate our model on MSCOCO based on public metrics, and the results show that our model performs better than several state-of-the-art methods.

Speech-feature discrimination in children with Asperger syndrome as determined with the multi-feature mismatch negativity paradigm.

PubMed

Kujala, T; Kuuluvainen, S; Saalasti, S; Jansson-Verkasalo, E; von Wendt, L; Lepistö, T

2010-09-01

Asperger syndrome, belonging to the autistic spectrum of disorders, involves deficits in social interaction and prosodic use of language but normal development of formal language abilities. Auditory processing involves both hyper- and hypoactive reactivity to acoustic changes. Responses composed of mismatch negativity (MMN) and obligatory components were recorded for five types of deviations in syllables (vowel, vowel duration, consonant, syllable frequency, syllable intensity) with the multi-feature paradigm from 8-12-year old children with Asperger syndrome. Children with Asperger syndrome had larger MMNs for intensity and smaller MMNs for frequency changes than typically developing children, whereas no MMN group differences were found for the other deviant stimuli. Furthermore, children with Asperger syndrome performed more poorly than controls in Comprehension of Instructions subtest of a language test battery. Cortical speech-sound discrimination is aberrant in children with Asperger syndrome. This is evident both as hypersensitive and depressed neural reactions to speech-sound changes, and is associated with features (frequency, intensity) which are relevant for prosodic processing. The multi-feature MMN paradigm, which includes variation and thereby resembles natural speech hearing circumstances, suggests abnormal pattern of speech discrimination in Asperger syndrome, including both hypo- and hypersensitive responses for speech features. 2010 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Detecting Image Splicing Using Merged Features in Chroma Space

PubMed Central

Liu, Guangjie; Dai, Yuewei

2014-01-01

Image splicing is an image editing method to copy a part of an image and paste it onto another image, and it is commonly followed by postprocessing such as local/global blurring, compression, and resizing. To detect this kind of forgery, the image rich models, a feature set successfully used in the steganalysis is evaluated on the splicing image dataset at first, and the dominant submodel is selected as the first kind of feature. The selected feature and the DCT Markov features are used together to detect splicing forgery in the chroma channel, which is convinced effective in splicing detection. The experimental results indicate that the proposed method can detect splicing forgeries with lower error rate compared to the previous literature. PMID:24574877

Detecting image splicing using merged features in chroma space.

PubMed

Xu, Bo; Liu, Guangjie; Dai, Yuewei

2014-01-01

Image splicing is an image editing method to copy a part of an image and paste it onto another image, and it is commonly followed by postprocessing such as local/global blurring, compression, and resizing. To detect this kind of forgery, the image rich models, a feature set successfully used in the steganalysis is evaluated on the splicing image dataset at first, and the dominant submodel is selected as the first kind of feature. The selected feature and the DCT Markov features are used together to detect splicing forgery in the chroma channel, which is convinced effective in splicing detection. The experimental results indicate that the proposed method can detect splicing forgeries with lower error rate compared to the previous literature.

Content-based cell pathology image retrieval by combining different features

NASA Astrophysics Data System (ADS)

Zhou, Guangquan; Jiang, Lu; Luo, Limin; Bao, Xudong; Shu, Huazhong

2004-04-01

Content Based Color Cell Pathology Image Retrieval is one of the newest computer image processing applications in medicine. Recently, some algorithms have been developed to achieve this goal. Because of the particularity of cell pathology images, the result of the image retrieval based on single characteristic is not satisfactory. A new method for pathology image retrieval by combining color, texture and morphologic features to search cell images is proposed. Firstly, nucleus regions of leukocytes in images are automatically segmented by K-mean clustering method. Then single leukocyte region is detected by utilizing thresholding algorithm segmentation and mathematics morphology. The features that include color, texture and morphologic features are extracted from single leukocyte to represent main attribute in the search query. The features are then normalized because the numerical value range and physical meaning of extracted features are different. Finally, the relevance feedback system is introduced. So that the system can automatically adjust the weights of different features and improve the results of retrieval system according to the feedback information. Retrieval results using the proposed method fit closely with human perception and are better than those obtained with the methods based on single feature.

Robust image features: concentric contrasting circles and their image extraction

NASA Astrophysics Data System (ADS)

Gatrell, Lance B.; Hoff, William A.; Sklair, Cheryl W.

1992-03-01

Many computer vision tasks can be simplified if special image features are placed on the objects to be recognized. A review of special image features that have been used in the past is given and then a new image feature, the concentric contrasting circle, is presented. The concentric contrasting circle image feature has the advantages of being easily manufactured, easily extracted from the image, robust extraction (true targets are found, while few false targets are found), it is a passive feature, and its centroid is completely invariant to the three translational and one rotational degrees of freedom and nearly invariant to the remaining two rotational degrees of freedom. There are several examples of existing parallel implementations which perform most of the extraction work. Extraction robustness was measured by recording the probability of correct detection and the false alarm rate in a set of images of scenes containing mockups of satellites, fluid couplings, and electrical components. A typical application of concentric contrasting circle features is to place them on modeled objects for monocular pose estimation or object identification. This feature is demonstrated on a visually challenging background of a specular but wrinkled surface similar to a multilayered insulation spacecraft thermal blanket.

Efficient and robust model-to-image alignment using 3D scale-invariant features.

PubMed

Toews, Matthew; Wells, William M

2013-04-01

This paper presents feature-based alignment (FBA), a general method for efficient and robust model-to-image alignment. Volumetric images, e.g. CT scans of the human body, are modeled probabilistically as a collage of 3D scale-invariant image features within a normalized reference space. Features are incorporated as a latent random variable and marginalized out in computing a maximum a posteriori alignment solution. The model is learned from features extracted in pre-aligned training images, then fit to features extracted from a new image to identify a globally optimal locally linear alignment solution. Novel techniques are presented for determining local feature orientation and efficiently encoding feature intensity in 3D. Experiments involving difficult magnetic resonance (MR) images of the human brain demonstrate FBA achieves alignment accuracy similar to widely-used registration methods, while requiring a fraction of the memory and computation resources and offering a more robust, globally optimal solution. Experiments on CT human body scans demonstrate FBA as an effective system for automatic human body alignment where other alignment methods break down. Copyright © 2012 Elsevier B.V. All rights reserved.

Efficient and Robust Model-to-Image Alignment using 3D Scale-Invariant Features

PubMed Central

Toews, Matthew; Wells, William M.

2013-01-01

This paper presents feature-based alignment (FBA), a general method for efficient and robust model-to-image alignment. Volumetric images, e.g. CT scans of the human body, are modeled probabilistically as a collage of 3D scale-invariant image features within a normalized reference space. Features are incorporated as a latent random variable and marginalized out in computing a maximum a-posteriori alignment solution. The model is learned from features extracted in pre-aligned training images, then fit to features extracted from a new image to identify a globally optimal locally linear alignment solution. Novel techniques are presented for determining local feature orientation and efficiently encoding feature intensity in 3D. Experiments involving difficult magnetic resonance (MR) images of the human brain demonstrate FBA achieves alignment accuracy similar to widely-used registration methods, while requiring a fraction of the memory and computation resources and offering a more robust, globally optimal solution. Experiments on CT human body scans demonstrate FBA as an effective system for automatic human body alignment where other alignment methods break down. PMID:23265799

Temporal Features of Word-Initial /s/+Stop Clusters in Bilingual Mandarin-English Children and Monolingual English Children and Adults

ERIC Educational Resources Information Center

Yang, Jing

2018-01-01

This study investigated the durational features of English word-initial /s/+stop clusters produced by bilingual Mandarin (L1)-English (L2) children and monolingual English children and adults. The participants included two groups of five- to six-year-old bilingual children: low proficiency in the L2 (Bi-low) and high proficiency in the L2…

Image Registration Algorithm Based on Parallax Constraint and Clustering Analysis

NASA Astrophysics Data System (ADS)

Wang, Zhe; Dong, Min; Mu, Xiaomin; Wang, Song

2018-01-01

To resolve the problem of slow computation speed and low matching accuracy in image registration, a new image registration algorithm based on parallax constraint and clustering analysis is proposed. Firstly, Harris corner detection algorithm is used to extract the feature points of two images. Secondly, use Normalized Cross Correlation (NCC) function to perform the approximate matching of feature points, and the initial feature pair is obtained. Then, according to the parallax constraint condition, the initial feature pair is preprocessed by K-means clustering algorithm, which is used to remove the feature point pairs with obvious errors in the approximate matching process. Finally, adopt Random Sample Consensus (RANSAC) algorithm to optimize the feature points to obtain the final feature point matching result, and the fast and accurate image registration is realized. The experimental results show that the image registration algorithm proposed in this paper can improve the accuracy of the image matching while ensuring the real-time performance of the algorithm.

Beauty and thinness messages in children's media: a content analysis.

PubMed

Herbozo, Sylvia; Tantleff-Dunn, Stacey; Gokee-Larose, Jessica; Thompson, J Kevin

2004-01-01

Research suggests that young children have body image concerns, such as a desire for thinness and an avoidance of obesity. Surprisingly, few studies have investigated how children's body preferences and stereotypes are influenced by media aimed at children. In order to gain a better understanding of the content of such media, a content analysis was used to examine body image-related messages in popular children's videos and books. Results indicated that messages emphasizing the importance of physical appearance and portraying body stereotypes are present in many children's videos but relatively few books. Of the videos examined, the ones that exhibited the most body image-related messages were Cinderella and The Little Mermaid. Indian in the Cupboard and ET were the videos with the least number of body image-related messages. Of the books studied, the one with the highest number of body image-related messages was Rapunzel. Ginger and The Stinky Cheese Man were the only books studied that did not exhibit body image-related messages. Implications of an association of beauty and thinness in children's media are explored.

Medical image retrieval system using multiple features from 3D ROIs

NASA Astrophysics Data System (ADS)

Lu, Hongbing; Wang, Weiwei; Liao, Qimei; Zhang, Guopeng; Zhou, Zhiming

2012-02-01

Compared to a retrieval using global image features, features extracted from regions of interest (ROIs) that reflect distribution patterns of abnormalities would benefit more for content-based medical image retrieval (CBMIR) systems. Currently, most CBMIR systems have been designed for 2D ROIs, which cannot reflect 3D anatomical features and region distribution of lesions comprehensively. To further improve the accuracy of image retrieval, we proposed a retrieval method with 3D features including both geometric features such as Shape Index (SI) and Curvedness (CV) and texture features derived from 3D Gray Level Co-occurrence Matrix, which were extracted from 3D ROIs, based on our previous 2D medical images retrieval system. The system was evaluated with 20 volume CT datasets for colon polyp detection. Preliminary experiments indicated that the integration of morphological features with texture features could improve retrieval performance greatly. The retrieval result using features extracted from 3D ROIs accorded better with the diagnosis from optical colonoscopy than that based on features from 2D ROIs. With the test database of images, the average accuracy rate for 3D retrieval method was 76.6%, indicating its potential value in clinical application.

Evaluation of a web based informatics system with data mining tools for predicting outcomes with quantitative imaging features in stroke rehabilitation clinical trials

NASA Astrophysics Data System (ADS)

Wang, Ximing; Kim, Bokkyu; Park, Ji Hoon; Wang, Erik; Forsyth, Sydney; Lim, Cody; Ravi, Ragini; Karibyan, Sarkis; Sanchez, Alexander; Liu, Brent

2017-03-01

Quantitative imaging biomarkers are used widely in clinical trials for tracking and evaluation of medical interventions. Previously, we have presented a web based informatics system utilizing quantitative imaging features for predicting outcomes in stroke rehabilitation clinical trials. The system integrates imaging features extraction tools and a web-based statistical analysis tool. The tools include a generalized linear mixed model(GLMM) that can investigate potential significance and correlation based on features extracted from clinical data and quantitative biomarkers. The imaging features extraction tools allow the user to collect imaging features and the GLMM module allows the user to select clinical data and imaging features such as stroke lesion characteristics from the database as regressors and regressands. This paper discusses the application scenario and evaluation results of the system in a stroke rehabilitation clinical trial. The system was utilized to manage clinical data and extract imaging biomarkers including stroke lesion volume, location and ventricle/brain ratio. The GLMM module was validated and the efficiency of data analysis was also evaluated.

An Evaluation of Feature Learning Methods for High Resolution Image Classification

NASA Astrophysics Data System (ADS)

Tokarczyk, P.; Montoya, J.; Schindler, K.

2012-07-01

Automatic image classification is one of the fundamental problems of remote sensing research. The classification problem is even more challenging in high-resolution images of urban areas, where the objects are small and heterogeneous. Two questions arise, namely which features to extract from the raw sensor data to capture the local radiometry and image structure at each pixel or segment, and which classification method to apply to the feature vectors. While classifiers are nowadays well understood, selecting the right features remains a largely empirical process. Here we concentrate on the features. Several methods are evaluated which allow one to learn suitable features from unlabelled image data by analysing the image statistics. In a comparative study, we evaluate unsupervised feature learning with different linear and non-linear learning methods, including principal component analysis (PCA) and deep belief networks (DBN). We also compare these automatically learned features with popular choices of ad-hoc features including raw intensity values, standard combinations like the NDVI, a few PCA channels, and texture filters. The comparison is done in a unified framework using the same images, the target classes, reference data and a Random Forest classifier.

Gender Recognition from Human-Body Images Using Visible-Light and Thermal Camera Videos Based on a Convolutional Neural Network for Image Feature Extraction

PubMed Central

Nguyen, Dat Tien; Kim, Ki Wan; Hong, Hyung Gil; Koo, Ja Hyung; Kim, Min Cheol; Park, Kang Ryoung

2017-01-01

Extracting powerful image features plays an important role in computer vision systems. Many methods have previously been proposed to extract image features for various computer vision applications, such as the scale-invariant feature transform (SIFT), speed-up robust feature (SURF), local binary patterns (LBP), histogram of oriented gradients (HOG), and weighted HOG. Recently, the convolutional neural network (CNN) method for image feature extraction and classification in computer vision has been used in various applications. In this research, we propose a new gender recognition method for recognizing males and females in observation scenes of surveillance systems based on feature extraction from visible-light and thermal camera videos through CNN. Experimental results confirm the superiority of our proposed method over state-of-the-art recognition methods for the gender recognition problem using human body images. PMID:28335510

Gender Recognition from Human-Body Images Using Visible-Light and Thermal Camera Videos Based on a Convolutional Neural Network for Image Feature Extraction.

PubMed

Nguyen, Dat Tien; Kim, Ki Wan; Hong, Hyung Gil; Koo, Ja Hyung; Kim, Min Cheol; Park, Kang Ryoung

2017-03-20

Extracting powerful image features plays an important role in computer vision systems. Many methods have previously been proposed to extract image features for various computer vision applications, such as the scale-invariant feature transform (SIFT), speed-up robust feature (SURF), local binary patterns (LBP), histogram of oriented gradients (HOG), and weighted HOG. Recently, the convolutional neural network (CNN) method for image feature extraction and classification in computer vision has been used in various applications. In this research, we propose a new gender recognition method for recognizing males and females in observation scenes of surveillance systems based on feature extraction from visible-light and thermal camera videos through CNN. Experimental results confirm the superiority of our proposed method over state-of-the-art recognition methods for the gender recognition problem using human body images.

A comparative study for chest radiograph image retrieval using binary texture and deep learning classification.

PubMed

Anavi, Yaron; Kogan, Ilya; Gelbart, Elad; Geva, Ofer; Greenspan, Hayit

2015-08-01

In this work various approaches are investigated for X-ray image retrieval and specifically chest pathology retrieval. Given a query image taken from a data set of 443 images, the objective is to rank images according to similarity. Different features, including binary features, texture features, and deep learning (CNN) features are examined. In addition, two approaches are investigated for the retrieval task. One approach is based on the distance of image descriptors using the above features (hereon termed the "descriptor"-based approach); the second approach ("classification"-based approach) is based on a probability descriptor, generated by a pair-wise classification of each two classes (pathologies) and their decision values using an SVM classifier. Best results are achieved using deep learning features in a classification scheme.

Automated Recognition of 3D Features in GPIR Images

NASA Technical Reports Server (NTRS)

Park, Han; Stough, Timothy; Fijany, Amir

2007-01-01

A method of automated recognition of three-dimensional (3D) features in images generated by ground-penetrating imaging radar (GPIR) is undergoing development. GPIR 3D images can be analyzed to detect and identify such subsurface features as pipes and other utility conduits. Until now, much of the analysis of GPIR images has been performed manually by expert operators who must visually identify and track each feature. The present method is intended to satisfy a need for more efficient and accurate analysis by means of algorithms that can automatically identify and track subsurface features, with minimal supervision by human operators. In this method, data from multiple sources (for example, data on different features extracted by different algorithms) are fused together for identifying subsurface objects. The algorithms of this method can be classified in several different ways. In one classification, the algorithms fall into three classes: (1) image-processing algorithms, (2) feature- extraction algorithms, and (3) a multiaxis data-fusion/pattern-recognition algorithm that includes a combination of machine-learning, pattern-recognition, and object-linking algorithms. The image-processing class includes preprocessing algorithms for reducing noise and enhancing target features for pattern recognition. The feature-extraction algorithms operate on preprocessed data to extract such specific features in images as two-dimensional (2D) slices of a pipe. Then the multiaxis data-fusion/ pattern-recognition algorithm identifies, classifies, and reconstructs 3D objects from the extracted features. In this process, multiple 2D features extracted by use of different algorithms and representing views along different directions are used to identify and reconstruct 3D objects. In object linking, which is an essential part of this process, features identified in successive 2D slices and located within a threshold radius of identical features in adjacent slices are linked in a directed-graph data structure. Relative to past approaches, this multiaxis approach offers the advantages of more reliable detections, better discrimination of objects, and provision of redundant information, which can be helpful in filling gaps in feature recognition by one of the component algorithms. The image-processing class also includes postprocessing algorithms that enhance identified features to prepare them for further scrutiny by human analysts (see figure). Enhancement of images as a postprocessing step is a significant departure from traditional practice, in which enhancement of images is a preprocessing step.

A Novel Image Retrieval Based on Visual Words Integration of SIFT and SURF

PubMed Central

Ali, Nouman; Bajwa, Khalid Bashir; Sablatnig, Robert; Chatzichristofis, Savvas A.; Iqbal, Zeshan; Rashid, Muhammad; Habib, Hafiz Adnan

2016-01-01

With the recent evolution of technology, the number of image archives has increased exponentially. In Content-Based Image Retrieval (CBIR), high-level visual information is represented in the form of low-level features. The semantic gap between the low-level features and the high-level image concepts is an open research problem. In this paper, we present a novel visual words integration of Scale Invariant Feature Transform (SIFT) and Speeded-Up Robust Features (SURF). The two local features representations are selected for image retrieval because SIFT is more robust to the change in scale and rotation, while SURF is robust to changes in illumination. The visual words integration of SIFT and SURF adds the robustness of both features to image retrieval. The qualitative and quantitative comparisons conducted on Corel-1000, Corel-1500, Corel-2000, Oliva and Torralba and Ground Truth image benchmarks demonstrate the effectiveness of the proposed visual words integration. PMID:27315101

The Words of Children's Television.

ERIC Educational Resources Information Center

Rice, Mabel L.

1984-01-01

Dialog features--communication flow, language structures, and meaning/content--and nonverbal formal features of six children's television programs are examined to determine if there is dialog simplification, if certain dialog characteristics differentiate among shows sampled, and if there are different combinations of linguistic features and…

Intrinsic feature-based pose measurement for imaging motion compensation

DOEpatents

Baba, Justin S.; Goddard, Jr., James Samuel

2014-08-19

Systems and methods for generating motion corrected tomographic images are provided. A method includes obtaining first images of a region of interest (ROI) to be imaged and associated with a first time, where the first images are associated with different positions and orientations with respect to the ROI. The method also includes defining an active region in the each of the first images and selecting intrinsic features in each of the first images based on the active region. Second, identifying a portion of the intrinsic features temporally and spatially matching intrinsic features in corresponding ones of second images of the ROI associated with a second time prior to the first time and computing three-dimensional (3D) coordinates for the portion of the intrinsic features. Finally, the method includes computing a relative pose for the first images based on the 3D coordinates.

Model-based vision for space applications

NASA Technical Reports Server (NTRS)

Chaconas, Karen; Nashman, Marilyn; Lumia, Ronald

1992-01-01

This paper describes a method for tracking moving image features by combining spatial and temporal edge information with model based feature information. The algorithm updates the two-dimensional position of object features by correlating predicted model features with current image data. The results of the correlation process are used to compute an updated model. The algorithm makes use of a high temporal sampling rate with respect to spatial changes of the image features and operates in a real-time multiprocessing environment. Preliminary results demonstrate successful tracking for image feature velocities between 1.1 and 4.5 pixels every image frame. This work has applications for docking, assembly, retrieval of floating objects and a host of other space-related tasks.

Image processing based automatic diagnosis of glaucoma using wavelet features of segmented optic disc from fundus image.

PubMed

Singh, Anushikha; Dutta, Malay Kishore; ParthaSarathi, M; Uher, Vaclav; Burget, Radim

2016-02-01

Glaucoma is a disease of the retina which is one of the most common causes of permanent blindness worldwide. This paper presents an automatic image processing based method for glaucoma diagnosis from the digital fundus image. In this paper wavelet feature extraction has been followed by optimized genetic feature selection combined with several learning algorithms and various parameter settings. Unlike the existing research works where the features are considered from the complete fundus or a sub image of the fundus, this work is based on feature extraction from the segmented and blood vessel removed optic disc to improve the accuracy of identification. The experimental results presented in this paper indicate that the wavelet features of the segmented optic disc image are clinically more significant in comparison to features of the whole or sub fundus image in the detection of glaucoma from fundus image. Accuracy of glaucoma identification achieved in this work is 94.7% and a comparison with existing methods of glaucoma detection from fundus image indicates that the proposed approach has improved accuracy of classification. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Image counter-forensics based on feature injection

NASA Astrophysics Data System (ADS)

Iuliani, M.; Rossetto, S.; Bianchi, T.; De Rosa, Alessia; Piva, A.; Barni, M.

2014-02-01

Starting from the concept that many image forensic tools are based on the detection of some features revealing a particular aspect of the history of an image, in this work we model the counter-forensic attack as the injection of a specific fake feature pointing to the same history of an authentic reference image. We propose a general attack strategy that does not rely on a specific detector structure. Given a source image x and a target image y, the adversary processes x in the pixel domain producing an attacked image ~x, perceptually similar to x, whose feature f(~x) is as close as possible to f(y) computed on y. Our proposed counter-forensic attack consists in the constrained minimization of the feature distance Φ(z) =│ f(z) - f(y)│ through iterative methods based on gradient descent. To solve the intrinsic limit due to the numerical estimation of the gradient on large images, we propose the application of a feature decomposition process, that allows the problem to be reduced into many subproblems on the blocks the image is partitioned into. The proposed strategy has been tested by attacking three different features and its performance has been compared to state-of-the-art counter-forensic methods.

Health journalism in the service of power: 'moral complacency' and the Hebrew media in the Gaza-Israel conflict.

PubMed

Birenbaum-Carmeli, Daphna

2014-05-01

The power of health news as a vehicle in the production of meaning in the service of power is the core of this article. Tracking the media coverage of a medical service, it shows how a routine practice can be invoked at a time of armed conflict so as to enhance a benevolent state image. The case at hand is the medical treatment of Gaza children in Israeli hospitals. A series of Internet searches revealed a group of publications on the subject in the Hebrew media, during and shortly after Israel's assault on Gaza in the winter of 2008-2009. In the press articles the treatments were invariably constituted as the epitome of Israel's compassion towards the enemy's children. This image relied, however, on a simultaneous silencing of other aspects of these treatments, which would have challenged this image. The monolithic depictions give rise to the notion of reversed moral panic or 'moral complacency', wherein the media amplifies a little-known social phenomenon into an epitome of societal values and charges it with significance on a national scale. The article ends with considering some features that possibly render health news an especially convenient domain for state-supportive media presentations. © 2014 The Author. Sociology of Health & Illness © 2014 Foundation for the Sociology of Health & Illness/John Wiley & Sons Ltd.

Improved parallel image reconstruction using feature refinement.

PubMed

Cheng, Jing; Jia, Sen; Ying, Leslie; Liu, Yuanyuan; Wang, Shanshan; Zhu, Yanjie; Li, Ye; Zou, Chao; Liu, Xin; Liang, Dong

2018-07-01

The aim of this study was to develop a novel feature refinement MR reconstruction method from highly undersampled multichannel acquisitions for improving the image quality and preserve more detail information. The feature refinement technique, which uses a feature descriptor to pick up useful features from residual image discarded by sparsity constrains, is applied to preserve the details of the image in compressed sensing and parallel imaging in MRI (CS-pMRI). The texture descriptor and structure descriptor recognizing different types of features are required for forming the feature descriptor. Feasibility of the feature refinement was validated using three different multicoil reconstruction methods on in vivo data. Experimental results show that reconstruction methods with feature refinement improve the quality of reconstructed image and restore the image details more accurately than the original methods, which is also verified by the lower values of the root mean square error and high frequency error norm. A simple and effective way to preserve more useful detailed information in CS-pMRI is proposed. This technique can effectively improve the reconstruction quality and has superior performance in terms of detail preservation compared with the original version without feature refinement. Magn Reson Med 80:211-223, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Change Detection in Uav Video Mosaics Combining a Feature Based Approach and Extended Image Differencing

NASA Astrophysics Data System (ADS)

Saur, Günter; Krüger, Wolfgang

2016-06-01

Change detection is an important task when using unmanned aerial vehicles (UAV) for video surveillance. We address changes of short time scale using observations in time distances of a few hours. Each observation (previous and current) is a short video sequence acquired by UAV in near-Nadir view. Relevant changes are, e.g., recently parked or moved vehicles. Examples for non-relevant changes are parallaxes caused by 3D structures of the scene, shadow and illumination changes, and compression or transmission artifacts. In this paper we present (1) a new feature based approach to change detection, (2) a combination with extended image differencing (Saur et al., 2014), and (3) the application to video sequences using temporal filtering. In the feature based approach, information about local image features, e.g., corners, is extracted in both images. The label "new object" is generated at image points, where features occur in the current image and no or weaker features are present in the previous image. The label "vanished object" corresponds to missing or weaker features in the current image and present features in the previous image. This leads to two "directed" change masks and differs from image differencing where only one "undirected" change mask is extracted which combines both label types to the single label "changed object". The combination of both algorithms is performed by merging the change masks of both approaches. A color mask showing the different contributions is used for visual inspection by a human image interpreter.

Dialect Density in Bilingual Puerto Rican Spanish-English Speaking Children

PubMed Central

Fabiano-Smith, Leah; Shuriff, Rebecca; Barlow, Jessica A.; Goldstein, Brian A.

2014-01-01

It is still largely unknown how the two phonological systems of bilingual children interact. In this exploratory study, we examine children's use of dialect features to determine how their speech sound systems interact. Six monolingual Puerto Rican Spanish-speaking children and 6 bilingual Puerto Rican Spanish-English speaking children, ages 5-7 years, were included in the current study. Children's single word productions were analyzed for (1) dialect density and (2) frequency of occurrence of dialect features (after Oetting & McDonald, 2002). Nonparametric statistical analyses were used to examine differences within and across language groups. Results indicated that monolinguals and bilinguals exhibited similar dialect density, but differed on the types of dialect features used. Findings are discussed within the theoretical framework of the Dual Systems Model (Paradis, 2001) of language acquisition in bilingual children. PMID:25009677

The Biological Categorizations Made by 4 and 5-Year-Old Children: The Role of Feature Type versus Their Causal Status

ERIC Educational Resources Information Center

Meunier, Benjamin; Cordier, Francoise

2008-01-01

The present study here investigated the role of the causal status of features and feature type in biological categorizations by young children. Study 1 showed that 5-year-olds are more strongly influenced by causal features than effect features. 4-year-olds exhibit no such tendency. There, therefore, appears to be a conceptual change between the…

Tracking features in retinal images of adaptive optics confocal scanning laser ophthalmoscope using KLT-SIFT algorithm

PubMed Central

Li, Hao; Lu, Jing; Shi, Guohua; Zhang, Yudong

2010-01-01

With the use of adaptive optics (AO), high-resolution microscopic imaging of living human retina in the single cell level has been achieved. In an adaptive optics confocal scanning laser ophthalmoscope (AOSLO) system, with a small field size (about 1 degree, 280 μm), the motion of the eye severely affects the stabilization of the real-time video images and results in significant distortions of the retina images. In this paper, Scale-Invariant Feature Transform (SIFT) is used to abstract stable point features from the retina images. Kanade-Lucas-Tomasi(KLT) algorithm is applied to track the features. With the tracked features, the image distortion in each frame is removed by the second-order polynomial transformation, and 10 successive frames are co-added to enhance the image quality. Features of special interest in an image can also be selected manually and tracked by KLT. A point on a cone is selected manually, and the cone is tracked from frame to frame. PMID:21258443

[FEATURES OF CLINICAL COURSE OF INFECTIOUS MONONUCLEOSIS IN CHILDREN DEPENDENT ON ETIOLOGY].

PubMed

Kharchenko, Iu P; Zarets'ka, A V; Slobodnichenko, L M; Iurchenko, I V

2015-01-01

The article highlights the clinical features of infectious mononucleosis in children (based on the analysis of the data for children of different ages treated in Odessa clinical hospital of infectious diseases in connection with infectious mononucleosis) based on etiological factors.

Webcam classification using simple features

NASA Astrophysics Data System (ADS)

Pramoun, Thitiporn; Choe, Jeehyun; Li, He; Chen, Qingshuang; Amornraksa, Thumrongrat; Lu, Yung-Hsiang; Delp, Edward J.

2015-03-01

Thousands of sensors are connected to the Internet and many of these sensors are cameras. The "Internet of Things" will contain many "things" that are image sensors. This vast network of distributed cameras (i.e. web cams) will continue to exponentially grow. In this paper we examine simple methods to classify an image from a web cam as "indoor/outdoor" and having "people/no people" based on simple features. We use four types of image features to classify an image as indoor/outdoor: color, edge, line, and text. To classify an image as having people/no people we use HOG and texture features. The features are weighted based on their significance and combined. A support vector machine is used for classification. Our system with feature weighting and feature combination yields 95.5% accuracy.

Image segmentation using association rule features.

PubMed

Rushing, John A; Ranganath, Heggere; Hinke, Thomas H; Graves, Sara J

2002-01-01

A new type of texture feature based on association rules is described. Association rules have been used in applications such as market basket analysis to capture relationships present among items in large data sets. It is shown that association rules can be adapted to capture frequently occurring local structures in images. The frequency of occurrence of these structures can be used to characterize texture. Methods for segmentation of textured images based on association rule features are described. Simulation results using images consisting of man made and natural textures show that association rule features perform well compared to other widely used texture features. Association rule features are used to detect cumulus cloud fields in GOES satellite images and are found to achieve higher accuracy than other statistical texture features for this problem.

How Visuo-Spatial Mental Imagery Develops: Image Generation and Maintenance

PubMed Central

Wimmer, Marina C.; Maras, Katie L.; Robinson, Elizabeth J; Doherty, Martin J; Pugeault, Nicolas

2015-01-01

Two experiments examined the nature of visuo-spatial mental imagery generation and maintenance in 4-, 6-, 8-, 10-year old children and adults (N = 211). The key questions were how image generation and maintenance develop (Experiment 1) and how accurately children and adults coordinate mental and visually perceived images (Experiment 2). Experiment 1 indicated that basic image generation and maintenance abilities are present at 4 years of age but the precision with which images are generated and maintained improves particularly between 4 and 8 years. In addition to increased precision, Experiment 2 demonstrated that generated and maintained mental images become increasingly similar to visually perceived objects. Altogether, findings suggest that for simple tasks demanding image generation and maintenance, children attain adult-like precision younger than previously reported. This research also sheds new light on the ability to coordinate mental images with visual images in children and adults. PMID:26562296

The Research of Feature Extraction Method of Liver Pathological Image Based on Multispatial Mapping and Statistical Properties

PubMed Central

Liu, Huiling; Xia, Bingbing; Yi, Dehui

2016-01-01

We propose a new feature extraction method of liver pathological image based on multispatial mapping and statistical properties. For liver pathological images of Hematein Eosin staining, the image of R and B channels can reflect the sensitivity of liver pathological images better, while the entropy space and Local Binary Pattern (LBP) space can reflect the texture features of the image better. To obtain the more comprehensive information, we map liver pathological images to the entropy space, LBP space, R space, and B space. The traditional Higher Order Local Autocorrelation Coefficients (HLAC) cannot reflect the overall information of the image, so we propose an average correction HLAC feature. We calculate the statistical properties and the average gray value of pathological images and then update the current pixel value as the absolute value of the difference between the current pixel gray value and the average gray value, which can be more sensitive to the gray value changes of pathological images. Lastly the HLAC template is used to calculate the features of the updated image. The experiment results show that the improved features of the multispatial mapping have the better classification performance for the liver cancer. PMID:27022407

SU-F-R-52: A Comparison of the Performance of Radiomic Features From Free Breathing and 4DCT Scans in Predicting Disease Recurrence in Lung Cancer SBRT Patients

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

Huynh, E; Coroller, T; Narayan, V

Purpose: There is a clinical need to identify patients who are at highest risk of recurrence after being treated with stereotactic body radiation therapy (SBRT). Radiomics offers a non-invasive approach by extracting quantitative features from medical images based on tumor phenotype that is predictive of an outcome. Lung cancer patients treated with SBRT routinely undergo free breathing (FB image) and 4DCT (average intensity projection (AIP) image) scans for treatment planning to account for organ motion. The aim of the current study is to evaluate and compare the prognostic performance of radiomic features extracted from FB and AIP images in lungmore » cancer patients treated with SBRT to identify which image type would generate an optimal predictive model for recurrence. Methods: FB and AIP images of 113 Stage I-II NSCLC patients treated with SBRT were analysed. The prognostic performance of radiomic features for distant metastasis (DM) was evaluated by their concordance index (CI). Radiomic features were compared with conventional imaging metrics (e.g. diameter). All p-values were corrected for multiple testing using the false discovery rate. Results: All patients received SBRT and 20.4% of patients developed DM. From each image type (FB or AIP), nineteen radiomic features were selected based on stability and variance. Both image types had five common and fourteen different radiomic features. One FB (CI=0.70) and five AIP (CI range=0.65–0.68) radiomic features were significantly prognostic for DM (p<0.05). None of the conventional features derived from FB images (range CI=0.60–0.61) were significant but all AIP conventional features were (range CI=0.64–0.66). Conclusion: Features extracted from different types of CT scans have varying prognostic performances. AIP images contain more prognostic radiomic features for DM than FB images. These methods can provide personalized medicine approaches at low cost, as FB and AIP data are readily available within a large number of radiation oncology departments. R.M. had consulting interest with Amgen (ended in 2015).« less

Quality assessment of remote sensing image fusion using feature-based fourth-order correlation coefficient

NASA Astrophysics Data System (ADS)

Ma, Dan; Liu, Jun; Chen, Kai; Li, Huali; Liu, Ping; Chen, Huijuan; Qian, Jing

2016-04-01

In remote sensing fusion, the spatial details of a panchromatic (PAN) image and the spectrum information of multispectral (MS) images will be transferred into fused images according to the characteristics of the human visual system. Thus, a remote sensing image fusion quality assessment called feature-based fourth-order correlation coefficient (FFOCC) is proposed. FFOCC is based on the feature-based coefficient concept. Spatial features related to spatial details of the PAN image and spectral features related to the spectrum information of MS images are first extracted from the fused image. Then, the fourth-order correlation coefficient between the spatial and spectral features is calculated and treated as the assessment result. FFOCC was then compared with existing widely used indices, such as Erreur Relative Globale Adimensionnelle de Synthese, and quality assessed with no reference. Results of the fusion and distortion experiments indicate that the FFOCC is consistent with subjective evaluation. FFOCC significantly outperforms the other indices in evaluating fusion images that are produced by different fusion methods and that are distorted in spatial and spectral features by blurring, adding noise, and changing intensity. All the findings indicate that the proposed method is an objective and effective quality assessment for remote sensing image fusion.

SU-E-J-260: Quantitative Image Feature Analysis of Multiphase Liver CT for Hepatocellular Carcinoma (HCC) in Radiation Therapy

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

Choi, W; Wang, J; Lu, W

Purpose: To identify the effective quantitative image features (radiomics features) for prediction of response, survival, recurrence and metastasis of hepatocellular carcinoma (HCC) in radiotherapy. Methods: Multiphase contrast enhanced liver CT images were acquired in 16 patients with HCC on pre and post radiation therapy (RT). In this study, arterial phase CT images were selected to analyze the effectiveness of image features for the prediction of treatment outcome of HCC to RT. Response evaluated by RECIST criteria, survival, local recurrence (LR), distant metastasis (DM) and liver metastasis (LM) were examined. A radiation oncologist manually delineated the tumor and normal liver onmore » pre and post CT scans, respectively. Quantitative image features were extracted to characterize the intensity distribution (n=8), spatial patterns (texture, n=36), and shape (n=16) of the tumor and liver, respectively. Moreover, differences between pre and post image features were calculated (n=120). A total of 360 features were extracted and then analyzed by unpaired student’s t-test to rank the effectiveness of features for the prediction of response. Results: The five most effective features were selected for prediction of each outcome. Significant predictors for tumor response and survival are changes in tumor shape (Second Major Axes Length, p= 0.002; Eccentricity, p=0.0002), for LR, liver texture (Standard Deviation (SD) of High Grey Level Run Emphasis and SD of Entropy, both p=0.005) on pre and post CT images, for DM, tumor texture (SD of Entropy, p=0.01) on pre CT image and for LM, liver (Mean of Cluster Shade, p=0.004) and tumor texture (SD of Entropy, p=0.006) on pre CT image. Intensity distribution features were not significant (p>0.09). Conclusion: Quantitative CT image features were found to be potential predictors of the five endpoints of HCC in RT. This work was supported in part by the National Cancer Institute Grant R01CA172638.« less

A novel content-based medical image retrieval method based on query topic dependent image features (QTDIF)

NASA Astrophysics Data System (ADS)

Xiong, Wei; Qiu, Bo; Tian, Qi; Mueller, Henning; Xu, Changsheng

2005-04-01

Medical image retrieval is still mainly a research domain with a large variety of applications and techniques. With the ImageCLEF 2004 benchmark, an evaluation framework has been created that includes a database, query topics and ground truth data. Eleven systems (with a total of more than 50 runs) compared their performance in various configurations. The results show that there is not any one feature that performs well on all query tasks. Key to successful retrieval is rather the selection of features and feature weights based on a specific set of input features, thus on the query task. In this paper we propose a novel method based on query topic dependent image features (QTDIF) for content-based medical image retrieval. These feature sets are designed to capture both inter-category and intra-category statistical variations to achieve good retrieval performance in terms of recall and precision. We have used Gaussian Mixture Models (GMM) and blob representation to model medical images and construct the proposed novel QTDIF for CBIR. Finally, trained multi-class support vector machines (SVM) are used for image similarity ranking. The proposed methods have been tested over the Casimage database with around 9000 images, for the given 26 image topics, used for imageCLEF 2004. The retrieval performance has been compared with the medGIFT system, which is based on the GNU Image Finding Tool (GIFT). The experimental results show that the proposed QTDIF-based CBIR can provide significantly better performance than systems based general features only.

Getting To Know You: Profiles of Children's Authors Featured in "Language Arts" 1985-90.

ERIC Educational Resources Information Center

Kiefer, Barbara, Comp.

This book is a selection of profiles of children's authors featured in the journal "Language Arts" over the years. The book's 12 individual profiles highlight some of the real people who contribute to children's book publishing, provide a sample of a few of the many genres of books available for children, and give an insight into the…

Radiological Evaluation of Ambiguous Genitalia with Various Imaging Modalities

NASA Astrophysics Data System (ADS)

Ravi, N.; Bindushree, Kadakola

2012-07-01

Disorders of sex development (DSDs) are congenital conditions in which the development of chromosomal, gonadal, or anatomic sex is atypical. These can be classified broadly into four categories on the basis of gonadal histologic features: female pseudohermaphroditism (46,XX with two ovaries); male pseudohermaphroditism (46,XY with two testes); true hermaphroditism (ovotesticular DSD) (both ovarian and testicular tissues); and gonadal dysgenesis, either mixed (a testis and a streak gonad) or pure (bilateral streak gonads). Imaging plays an important role in demonstrating the anatomy and associated anomalies. Ultrasonography is the primary modality for demonstrating internal organs and magnetic resonance imaging is used as an adjunct modality to assess for internal gonads and genitalia. Early and appropriate gender assignment is necessary for healthy physical and psychologic development of children with ambiguous genitalia. Gender assignment can be facilitated with a team approach that involves a pediatric endocrinologist, geneticist, urologist, psychiatrist, social worker, neonatologist, nurse, and radiologist, allowing timely diagnosis and proper management. We describe case series on ambiguous genitalia presented to our department who were evaluated with multiple imaging modalities.

Study on Hybrid Image Search Technology Based on Texts and Contents

NASA Astrophysics Data System (ADS)

Wang, H. T.; Ma, F. L.; Yan, C.; Pan, H.

2018-05-01

Image search was studied first here based on texts and contents, respectively. The text-based image feature extraction was put forward by integrating the statistical and topic features in view of the limitation of extraction of keywords only by means of statistical features of words. On the other hand, a search-by-image method was put forward based on multi-feature fusion in view of the imprecision of the content-based image search by means of a single feature. The layered-searching method depended on primarily the text-based image search method and additionally the content-based image search was then put forward in view of differences between the text-based and content-based methods and their difficult direct fusion. The feasibility and effectiveness of the hybrid search algorithm were experimentally verified.

From the children's perspective: What are candy, snacks, and meals?

PubMed

Adams, Elizabeth L; Savage, Jennifer S

2017-09-01

There remains a lack of consensus on what distinguishes candy (i.e. features sugar as a principal ingredient, also called sweets or lollies), snack foods, and foods served at meals; therefore, this study examined characteristics elementary-aged children use to distinguish between these food categories. Participants were children aged 5-8 years (N = 41). Children were given 39 cards, each containing an image of a common American food (e.g. ice cream, fruit). Children sorted each card into either a "snack" or "candy" pile followed by a semi-structured one-on-one interview to identify children's perceptions of candy, snack foods, and foods served at meals. Verbatim transcripts were coded using a grounded theory approach to derive major themes. All children classified foods such as crackers and dry cereal as snacks; all children classified foods such as skittles and solid chocolate as candy. There was less agreement for "dessert like foods," such as cookies and ice cream, whereby some children classified these foods as candy and others as snacks. Specifically, more children categorized ice cream and chocolate chip cookies as candy (61% and 63%, respectively), than children who categorized these as snack foods (39% and 36%, respectively). Qualitative interviews revealed 4 overarching themes that distinguished among candy, snack foods, and food served at meals: (1) taste, texture, and type; (2) portion size; (3) perception of health; and (4) time of day. Children categorized a variety of foods as both a candy and a snack. Accurate measurement of candy and snack consumption is needed through the use of clear, consistent terminology and comprehensive diet assessment tools. Intervention messaging should clearly distinguish between candy, snack foods, and foods served at meals to improve children's eating behavior. Copyright © 2017 Elsevier Ltd. All rights reserved.

Radiogenomics of hepatocellular carcinoma: multiregion analysis-based identification of prognostic imaging biomarkers by integrating gene data—a preliminary study

NASA Astrophysics Data System (ADS)

Xia, Wei; Chen, Ying; Zhang, Rui; Yan, Zhuangzhi; Zhou, Xiaobo; Zhang, Bo; Gao, Xin

2018-02-01

Our objective was to identify prognostic imaging biomarkers for hepatocellular carcinoma in contrast-enhanced computed tomography (CECT) with biological interpretations by associating imaging features and gene modules. We retrospectively analyzed 371 patients who had gene expression profiles. For the 38 patients with CECT imaging data, automatic intra-tumor partitioning was performed, resulting in three spatially distinct subregions. We extracted a total of 37 quantitative imaging features describing intensity, geometry, and texture from each subregion. Imaging features were selected after robustness and redundancy analysis. Gene modules acquired from clustering were chosen for their prognostic significance. By constructing an association map between imaging features and gene modules with Spearman rank correlations, the imaging features that significantly correlated with gene modules were obtained. These features were evaluated with Cox’s proportional hazard models and Kaplan-Meier estimates to determine their prognostic capabilities for overall survival (OS). Eight imaging features were significantly correlated with prognostic gene modules, and two of them were associated with OS. Among these, the geometry feature volume fraction of the subregion, which was significantly correlated with all prognostic gene modules representing cancer-related interpretation, was predictive of OS (Cox p  =  0.022, hazard ratio  =  0.24). The texture feature cluster prominence in the subregion, which was correlated with the prognostic gene module representing lipid metabolism and complement activation, also had the ability to predict OS (Cox p  =  0.021, hazard ratio  =  0.17). Imaging features depicting the volume fraction and textural heterogeneity in subregions have the potential to be predictors of OS with interpretable biological meaning.

Discrimination of single features and conjunctions by children.

PubMed

Taylor, M J; Chevalier, H; Lobaugh, N J

2003-12-01

Stimuli that are discriminated by a conjunction of features can show more rapid early processing in adults. To determine how this facilitation effect develops, the processing of visual features and their conjunction was examined in 7-12-year-old children. The children completed a series of tasks in which they made a target-non-target judgement as a function of shape only, colour only or shape and colour features, while event-related potentials were recorded. To assess early stages of feature processing the posteriorly distributed P1 and N1 were analysed. Attentional effects were seen for both components. P1 had a shorter latency and P1 and N1 had larger amplitudes to targets than non-targets. Task effects were driven by the conjunction task. P1 amplitude was largest, while N1 amplitude was smallest for the conjunction targets. In contrast to larger left-sided N1 in adults, N1 had a symmetrical distribution in the children. N1 latency was shortest for the conjunction targets in the 9-10-year olds and 11-12-year olds, demonstrating facilitation in children, but which continued to develop over the pre-teen years. These data underline the sensitivity of early stages of processing to both top-down modulations and the parallel binding of non-spatial features in young children. Furthermore, facilitation effects, increased speed of processing when features need to be conjoined, mature in mid-childhood, arguing against a hierarchical model of visual processing, and supporting a rapid, integrated facilitative model.

Negative emotion evoked by viewing snakes has a motivating effect on cognitive processing in human children with or without intellectual disability.

PubMed

Masataka, Nobuo

2017-06-01

It is well known that prioritization of the processing of threatening stimuli generally induces deleterious effects on task performance. However, a study recently reported that emotion (possibly fear) evoked by viewing images of snakes exerts a facilitating effect upon making judgments of the images' color in neurotypical adults and schoolchildren. Here, the author has attempted to confirm the relevance of this notion in children with and without intellectual disability. The author here compared the reaction time required to name the colors of snake and flower images between children with Down syndrome (DS) and mental age matched, typically-developing (TD) children. Snake images were responded to faster than flower images in both the groups, while the children with DS tended to respond more slowly overall. As in TD children, negative emotion can have a motivating effect on cognitive processing in children with DS. Some implications of the findings are pointed out with respect to the lower-level task persistence as a characteristic motivational orientation in children with DS.

Perception of suprasegmental features of speech by children with cochlear implants and children with hearing AIDS.

PubMed

Most, Tova; Peled, Miriam

2007-01-01

This study assessed perception of suprasegmental features of speech by 30 prelingual children with sensorineural hearing loss. Ten children had cochlear implants (CIs), and 20 children wore hearing aids (HA): 10 with severe hearing loss and 10 with profound hearing loss. Perception of intonation, syllable stress, word emphasis, and word pattern was assessed. Results revealed that the two HA groups significantly outperformed the CI group in perceiving both intonation and stress. Within each group, word pattern was perceived best, and then intonation and emphasis, with syllable stress perceived poorest. No significant correlation emerged between age at implantation and perception of the various suprasegmental features, possibly due to participants' relatively late age at implantation. Results indicated that CI use did not show an advantage over HA use in the perception of suprasegmental features of speech. Future research should continue to explore variables that might improve this perception.

Efficient moving target analysis for inverse synthetic aperture radar images via joint speeded-up robust features and regular moment

NASA Astrophysics Data System (ADS)

Yang, Hongxin; Su, Fulin

2018-01-01

We propose a moving target analysis algorithm using speeded-up robust features (SURF) and regular moment in inverse synthetic aperture radar (ISAR) image sequences. In our study, we first extract interest points from ISAR image sequences by SURF. Different from traditional feature point extraction methods, SURF-based feature points are invariant to scattering intensity, target rotation, and image size. Then, we employ a bilateral feature registering model to match these feature points. The feature registering scheme can not only search the isotropic feature points to link the image sequences but also reduce the error matching pairs. After that, the target centroid is detected by regular moment. Consequently, a cost function based on correlation coefficient is adopted to analyze the motion information. Experimental results based on simulated and real data validate the effectiveness and practicability of the proposed method.

Terrain detection and classification using single polarization SAR

DOEpatents

Chow, James G.; Koch, Mark W.

2016-01-19

The various technologies presented herein relate to identifying manmade and/or natural features in a radar image. Two radar images (e.g., single polarization SAR images) can be captured for a common scene. The first image is captured at a first instance and the second image is captured at a second instance, whereby the duration between the captures are of sufficient time such that temporal decorrelation occurs for natural surfaces in the scene, and only manmade surfaces, e.g., a road, produce correlated pixels. A LCCD image comprising the correlated and decorrelated pixels can be generated from the two radar images. A median image can be generated from a plurality of radar images, whereby any features in the median image can be identified. A superpixel operation can be performed on the LCCD image and the median image, thereby enabling a feature(s) in the LCCD image to be classified.

Structural brain imaging correlates of ASD and ADHD across the lifespan: a hypothesis-generating review on developmental ASD-ADHD subtypes.

PubMed

Rommelse, Nanda; Buitelaar, Jan K; Hartman, Catharina A

2017-02-01

We hypothesize that it is plausible that biologically distinct developmental ASD-ADHD subtypes are present, each characterized by a distinct time of onset of symptoms, progression and combination of symptoms. The aim of the present narrative review was to explore if structural brain imaging studies may shed light on key brain areas that are linked to both ASD and ADHD symptoms and undergo significant changes during development. These findings may possibly pinpoint to brain mechanisms underlying differential developmental ASD-ADHD subtypes. To this end we brought together the literature on ASD and ADHD structural brain imaging symptoms and particularly highlight the adolescent years and beyond. Findings indicate that the vast majority of existing MRI studies has been cross-sectional and conducted in children, and sometimes did include adolescents as well, but without explicitly documenting on this age group. MRI studies documenting on age effects in adults with ASD and/or ADHD are rare, and if age is taken into account, only linear effects are examined. Data from various studies suggest that a crucial distinctive feature underlying different developmental ASD-ADHD subtypes may be the differential developmental thinning patterns of the anterior cingulate cortex and related connections towards other prefrontal regions. These regions are crucial for the development of cognitive/effortful control and socio-emotional functioning, with impairments in these features as key to both ASD and ADHD.

Secure image retrieval with multiple keys

NASA Astrophysics Data System (ADS)

Liang, Haihua; Zhang, Xinpeng; Wei, Qiuhan; Cheng, Hang

2018-03-01

This article proposes a secure image retrieval scheme under a multiuser scenario. In this scheme, the owner first encrypts and uploads images and their corresponding features to the cloud; then, the user submits the encrypted feature of the query image to the cloud; next, the cloud compares the encrypted features and returns encrypted images with similar content to the user. To find the nearest neighbor in the encrypted features, an encryption with multiple keys is proposed, in which the query feature of each user is encrypted by his/her own key. To improve the key security and space utilization, global optimization and Gaussian distribution are, respectively, employed to generate multiple keys. The experiments show that the proposed encryption can provide effective and secure image retrieval for each user and ensure confidentiality of the query feature of each user.

Minimizing the semantic gap in biomedical content-based image retrieval

NASA Astrophysics Data System (ADS)

Guan, Haiying; Antani, Sameer; Long, L. Rodney; Thoma, George R.

2010-03-01

A major challenge in biomedical Content-Based Image Retrieval (CBIR) is to achieve meaningful mappings that minimize the semantic gap between the high-level biomedical semantic concepts and the low-level visual features in images. This paper presents a comprehensive learning-based scheme toward meeting this challenge and improving retrieval quality. The article presents two algorithms: a learning-based feature selection and fusion algorithm and the Ranking Support Vector Machine (Ranking SVM) algorithm. The feature selection algorithm aims to select 'good' features and fuse them using different similarity measurements to provide a better representation of the high-level concepts with the low-level image features. Ranking SVM is applied to learn the retrieval rank function and associate the selected low-level features with query concepts, given the ground-truth ranking of the training samples. The proposed scheme addresses four major issues in CBIR to improve the retrieval accuracy: image feature extraction, selection and fusion, similarity measurements, the association of the low-level features with high-level concepts, and the generation of the rank function to support high-level semantic image retrieval. It models the relationship between semantic concepts and image features, and enables retrieval at the semantic level. We apply it to the problem of vertebra shape retrieval from a digitized spine x-ray image set collected by the second National Health and Nutrition Examination Survey (NHANES II). The experimental results show an improvement of up to 41.92% in the mean average precision (MAP) over conventional image similarity computation methods.

Feature Matching of Historical Images Based on Geometry of Quadrilaterals

NASA Astrophysics Data System (ADS)

Maiwald, F.; Schneider, D.; Henze, F.; Münster, S.; Niebling, F.

2018-05-01

This contribution shows an approach to match historical images from the photo library of the Saxon State and University Library Dresden (SLUB) in the context of a historical three-dimensional city model of Dresden. In comparison to recent images, historical photography provides diverse factors which make an automatical image analysis (feature detection, feature matching and relative orientation of images) difficult. Due to e.g. film grain, dust particles or the digitalization process, historical images are often covered by noise interfering with the image signal needed for a robust feature matching. The presented approach uses quadrilaterals in image space as these are commonly available in man-made structures and façade images (windows, stones, claddings). It is explained how to generally detect quadrilaterals in images. Consequently, the properties of the quadrilaterals as well as the relationship to neighbouring quadrilaterals are used for the description and matching of feature points. The results show that most of the matches are robust and correct but still small in numbers.

SU-E-QI-17: Dependence of 3D/4D PET Quantitative Image Features On Noise

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

Oliver, J; Budzevich, M; Zhang, G

2014-06-15

Purpose: Quantitative imaging is a fast evolving discipline where a large number of features are extracted from images; i.e., radiomics. Some features have been shown to have diagnostic, prognostic and predictive value. However, they are sensitive to acquisition and processing factors; e.g., noise. In this study noise was added to positron emission tomography (PET) images to determine how features were affected by noise. Methods: Three levels of Gaussian noise were added to 8 lung cancer patients PET images acquired in 3D mode (static) and using respiratory tracking (4D); for the latter images from one of 10 phases were used. Amore » total of 62 features: 14 shape, 19 intensity (1stO), 18 GLCM textures (2ndO; from grey level co-occurrence matrices) and 11 RLM textures (2ndO; from run-length matrices) features were extracted from segmented tumors. Dimensions of GLCM were 256×256, calculated using 3D images with a step size of 1 voxel in 13 directions. Grey levels were binned into 256 levels for RLM and features were calculated in all 13 directions. Results: Feature variation generally increased with noise. Shape features were the most stable while RLM were the most unstable. Intensity and GLCM features performed well; the latter being more robust. The most stable 1stO features were compactness, maximum and minimum length, standard deviation, root-mean-squared, I30, V10-V90, and entropy. The most stable 2ndO features were entropy, sum-average, sum-entropy, difference-average, difference-variance, difference-entropy, information-correlation-2, short-run-emphasis, long-run-emphasis, and run-percentage. In general, features computed from images from one of the phases of 4D scans were more stable than from 3D scans. Conclusion: This study shows the need to characterize image features carefully before they are used in research and medical applications. It also shows that the performance of features, and thereby feature selection, may be assessed in part by noise analysis.« less

Moore-Federman syndrome and acromicric dysplasia: are they the same entity?

PubMed Central

Winter, R M; Patton, M A; Challener, J; Mueller, R F; Baraitser, M

1989-01-01

Four unrelated patients are reported with short stature, stiffness of the joints, short fingers, inability to make a fist, and thickened skin on the forearms. Investigations have failed to show a lysosomal storage disorder and radiographs show non-specific changes with a delayed carpal bone age. The clinical features in the four children are very similar to the recently described acromicric dysplasia. There are also similarities to Moore-Federman syndrome which has only been described in one family. The case is made that acromicric dysplasia and Moore-Federman syndrome are the same entity. Images PMID:2732993

Thanatophoric Dwarfism

PubMed Central

Shah, K.; Astley, R.; Cameron, A. H.

1973-01-01

A review of the radiographs of children previously classified as achondroplasiacs revealed six thanatophoric dwarfs. The main radiological differentiating features were the greater degree of shortening of the long bones, including the fibula, the curvature of the femora, the very small size of the thorax and, particularly, the very narrow ossified elements of the vertebral bodies. Perhaps the most important aspect of differential diagnosis lies in recognition in utero. The reported association with clover-leaf deformity of the skull in sibs provides the strongest evidence for genetic differentiation from classical achondroplasia. More evidence might be obtained by a widespread search through hospital radiological museums. Images PMID:4204337

Evidence of Diplopia in Children's Headache Drawings Helps to Differentiate Pseudotumor Cerebri From Migraine.

PubMed

Lee, Erica B; Edelman, Fredrick S; Stafstrom, Carl E

2018-02-01

This study aimed to determine whether children's headache drawings can distinguish between pseudotumor cerebri and migraine. Headache features associated with pseudotumor cerebri (pseudotumor; idiopathic intracranial hypertension) are nonspecific and are difficult to distinguish clinically from migraines. Children's headache drawings have a high predictive value for migraine versus nonmigraine headaches. We hypothesized that drawings could help to differentiate pediatric headaches due to pseudotumor cerebri from those associated with migraines. Children aged six to 18 years old attending university hospital pediatric neurology clinics were asked to draw a picture of how their headache feels. From our database of children's headache drawings, pictures by children with clinically diagnosed pseudotumor were compared with migraine drawings. Headache drawings of 21 children (16 females) with pseudotumor were compared with those of 518 children with migraine. Pseudotumor drawings depicted a variety of symptoms including pounding pain (n = 11), pressure-like pain (n = 3), photophobia (3), dizziness (1), and recumbency (1). Severe pain indicators included hammers, bombs, anvil, and vise grip. Positive visual phenomena included scintillations, scotomata, or blurring (n = 8). Negative visual phenomena included field defects (n = 2). Pseudotumor drawings were similar to migraine drawings except that 6 of 21 pseudotumor drawings (28.6%) depicted diplopia (crossed eyes, double images), whereas only three of 518 migraine drawings (0.6%) depicted diplopia (P < 0.000001). Diplopia was depicted in a significantly higher percentage of pseudotumor drawings than migraine drawings. In all other respects, headache drawings by children with pseudotumor cerebri were similar to those drawn by children with migraine. Copyright © 2017 Elsevier Inc. All rights reserved.

Analysis of imaging characteristics of primary malignant bone tumors in children

PubMed Central

Sun, Yingwei; Liu, Xueyong; Pan, Shinong; Deng, Chunbo; Li, Xiaohan; Guo, Qiyong

2017-01-01

The present study aimed to investigate the imaging characteristics of primary malignant bone tumors in children. The imaging results of 34 children with primary malignant bone tumors confirmed by histopathological diagnosis between March 2008 and January 2014 were retrospectively analyzed. In total, 25 patients had osteosarcoma, with radiography and computed tomography (CT) showing osteolytic bone destruction or/and osteoblastic bone sclerosis, an aggressive periosteal reaction, a soft-tissue mass and cancerous bone. The tumors appeared as mixed magnetic resonance imaging (MRI) signals that were inhomogeneously enhanced. A total of 5 patients presented with Ewing sarcoma, with radiography and CT showing invasive bone destruction and a soft-tissue mass. Of the 5 cases, 2 showed a laminar periosteal reaction. The tumors were shown to have mixed low signal on T1-weighted images (T1WI) and high signal on T2-weighted images (T2WI); 1 case showed marked inhomogeneous enhancement. Another 3 patients exhibited chondrosarcoma. Of these cases, 1 was adjacent to the cortex of the proximal tibia, and presented with local cortical bone destruction and a soft-tissue mass containing scattered punctate and amorphous calcifications. MRI revealed mixed low T1 signal and high T2 signals. Another case was located in the medullary cavity of the distal femur, with radiography revealing a localized periosteal reaction. The tumor appeared with mixed MRI signals, and with involvement of the epiphysis and epiphyseal plates. Radiography and CT of the third case showed bone destruction in the right pubic ramus, with patchy punctate, cambered calcifications in the soft-tissue mass. MRI of the soft-tissue mass revealed isointensity on T1WI and heterogeneous hyperintensity on T2WI. Ossifications and the septum appeared as low T1WI and T2WI. Of the 34 patients, 1 patient presented with lymphoma involving the T12, L1 and L2 vertebrae. CT showed vertebral bone destruction, a soft-tissue mass and a compression fracture of L1. MRI showed a soft-tissue mass with low T1 signal and high T2 signal and marked inhomogeneous enhancement. Overall, osteosarcoma was the most common primary malignant bone tumor, followed by Ewing sarcoma, chondrosarcoma and lymphoma. Osteoblastic or osteolytic bone destruction, an invasive periosteal reaction, soft-tissue masses, a tumor matrix and inhomogeneous enhancement were important imaging features of malignant bone tumors. PMID:29113210

Container Surface Evaluation by Function Estimation

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

Wendelberger, James G.

Container images are analyzed for specific surface features, such as, pits, cracks, and corrosion. The detection of these features is confounded with complicating features. These complication features include: shape/curvature, welds, edges, scratches, foreign objects among others. A method is provided to discriminate between the various features. The method consists of estimating the image background, determining a residual image and post processing to determine the features present. The methodology is not finalized but demonstrates the feasibility of a method to determine the kind and size of the features present.

Examining the Impact of Maternal Individual Features on Children's Behavioral Problems in Adoptive Families: The Role of Maternal Temperament and Neurobiological Markers.

PubMed

Ozturk, Yagmur; Barone, Virginia; Barone, Lavinia

2018-01-24

The first year after adoption constitutes a sensitive period for both strengthening the new emotional bond in the family and checking its appropriate development by adoption services. A key variable for children's catch-up are adoptive parents' socioemotional and individual features. The aim of this study is to investigate links between adoptive mothers' individual features and behavioral problems in their children in the first year after adoption placement, by testing the moderating role of both age at adoption and maternal genetic polymorphisms. Seventy-eight adoptive mothers completed temperament and genetic measures. Mothers showed a specific pattern of interaction between basic temperament traits and genetic markers in their assessment of children's behavioral problems; dopamine D4 receptor gene and children's age at adoption are two moderators in the association in which mothers' temperament was affecting the evaluation of their children's behavioral problems. Findings highlight a still undervalued area of parenting resources in the process of post-institutionalized children's catch-up after adoption placement, by showing how individual features count in the commonly measured variable of children's behavioral and emotional problems. This could help in orienting identification and choice of key variables for family assessment after adoption placement, thus contributing in fostering children's healthy development.

SEGMA: An Automatic SEGMentation Approach for Human Brain MRI Using Sliding Window and Random Forests

PubMed Central

Serag, Ahmed; Wilkinson, Alastair G.; Telford, Emma J.; Pataky, Rozalia; Sparrow, Sarah A.; Anblagan, Devasuda; Macnaught, Gillian; Semple, Scott I.; Boardman, James P.

2017-01-01

Quantitative volumes from brain magnetic resonance imaging (MRI) acquired across the life course may be useful for investigating long term effects of risk and resilience factors for brain development and healthy aging, and for understanding early life determinants of adult brain structure. Therefore, there is an increasing need for automated segmentation tools that can be applied to images acquired at different life stages. We developed an automatic segmentation method for human brain MRI, where a sliding window approach and a multi-class random forest classifier were applied to high-dimensional feature vectors for accurate segmentation. The method performed well on brain MRI data acquired from 179 individuals, analyzed in three age groups: newborns (38–42 weeks gestational age), children and adolescents (4–17 years) and adults (35–71 years). As the method can learn from partially labeled datasets, it can be used to segment large-scale datasets efficiently. It could also be applied to different populations and imaging modalities across the life course. PMID:28163680

Large Margin Multi-Modal Multi-Task Feature Extraction for Image Classification.

PubMed

Yong Luo; Yonggang Wen; Dacheng Tao; Jie Gui; Chao Xu

2016-01-01

The features used in many image analysis-based applications are frequently of very high dimension. Feature extraction offers several advantages in high-dimensional cases, and many recent studies have used multi-task feature extraction approaches, which often outperform single-task feature extraction approaches. However, most of these methods are limited in that they only consider data represented by a single type of feature, even though features usually represent images from multiple modalities. We, therefore, propose a novel large margin multi-modal multi-task feature extraction (LM3FE) framework for handling multi-modal features for image classification. In particular, LM3FE simultaneously learns the feature extraction matrix for each modality and the modality combination coefficients. In this way, LM3FE not only handles correlated and noisy features, but also utilizes the complementarity of different modalities to further help reduce feature redundancy in each modality. The large margin principle employed also helps to extract strongly predictive features, so that they are more suitable for prediction (e.g., classification). An alternating algorithm is developed for problem optimization, and each subproblem can be efficiently solved. Experiments on two challenging real-world image data sets demonstrate the effectiveness and superiority of the proposed method.

Content based image retrieval using local binary pattern operator and data mining techniques.

PubMed

Vatamanu, Oana Astrid; Frandeş, Mirela; Lungeanu, Diana; Mihalaş, Gheorghe-Ioan

2015-01-01

Content based image retrieval (CBIR) concerns the retrieval of similar images from image databases, using feature vectors extracted from images. These feature vectors globally define the visual content present in an image, defined by e.g., texture, colour, shape, and spatial relations between vectors. Herein, we propose the definition of feature vectors using the Local Binary Pattern (LBP) operator. A study was performed in order to determine the optimum LBP variant for the general definition of image feature vectors. The chosen LBP variant is then subsequently used to build an ultrasound image database, and a database with images obtained from Wireless Capsule Endoscopy. The image indexing process is optimized using data clustering techniques for images belonging to the same class. Finally, the proposed indexing method is compared to the classical indexing technique, which is nowadays widely used.

Hierarchical content-based image retrieval by dynamic indexing and guided search

NASA Astrophysics Data System (ADS)

You, Jane; Cheung, King H.; Liu, James; Guo, Linong

2003-12-01

This paper presents a new approach to content-based image retrieval by using dynamic indexing and guided search in a hierarchical structure, and extending data mining and data warehousing techniques. The proposed algorithms include: a wavelet-based scheme for multiple image feature extraction, the extension of a conventional data warehouse and an image database to an image data warehouse for dynamic image indexing, an image data schema for hierarchical image representation and dynamic image indexing, a statistically based feature selection scheme to achieve flexible similarity measures, and a feature component code to facilitate query processing and guide the search for the best matching. A series of case studies are reported, which include a wavelet-based image color hierarchy, classification of satellite images, tropical cyclone pattern recognition, and personal identification using multi-level palmprint and face features.

Categorizing biomedicine images using novel image features and sparse coding representation

PubMed Central

2013-01-01

Background Images embedded in biomedical publications carry rich information that often concisely summarize key hypotheses adopted, methods employed, or results obtained in a published study. Therefore, they offer valuable clues for understanding main content in a biomedical publication. Prior studies have pointed out the potential of mining images embedded in biomedical publications for automatically understanding and retrieving such images' associated source documents. Within the broad area of biomedical image processing, categorizing biomedical images is a fundamental step for building many advanced image analysis, retrieval, and mining applications. Similar to any automatic categorization effort, discriminative image features can provide the most crucial aid in the process. Method We observe that many images embedded in biomedical publications carry versatile annotation text. Based on the locations of and the spatial relationships between these text elements in an image, we thus propose some novel image features for image categorization purpose, which quantitatively characterize the spatial positions and distributions of text elements inside a biomedical image. We further adopt a sparse coding representation (SCR) based technique to categorize images embedded in biomedical publications by leveraging our newly proposed image features. Results we randomly selected 990 images of the JPG format for use in our experiments where 310 images were used as training samples and the rest were used as the testing cases. We first segmented 310 sample images following the our proposed procedure. This step produced a total of 1035 sub-images. We then manually labeled all these sub-images according to the two-level hierarchical image taxonomy proposed by [1]. Among our annotation results, 316 are microscopy images, 126 are gel electrophoresis images, 135 are line charts, 156 are bar charts, 52 are spot charts, 25 are tables, 70 are flow charts, and the remaining 155 images are of the type "others". A serial of experimental results are obtained. Firstly, each image categorizing results is presented, and next image categorizing performance indexes such as precision, recall, F-score, are all listed. Different features which include conventional image features and our proposed novel features indicate different categorizing performance, and the results are demonstrated. Thirdly, we conduct an accuracy comparison between support vector machine classification method and our proposed sparse representation classification method. At last, our proposed approach is compared with three peer classification method and experimental results verify our impressively improved performance. Conclusions Compared with conventional image features that do not exploit characteristics regarding text positions and distributions inside images embedded in biomedical publications, our proposed image features coupled with the SR based representation model exhibit superior performance for classifying biomedical images as demonstrated in our comparative benchmark study. PMID:24565470

Hemorrhage detection in MRI brain images using images features

NASA Astrophysics Data System (ADS)

Moraru, Luminita; Moldovanu, Simona; Bibicu, Dorin; Stratulat (Visan), Mirela

2013-11-01

The abnormalities appear frequently on Magnetic Resonance Images (MRI) of brain in elderly patients presenting either stroke or cognitive impairment. Detection of brain hemorrhage lesions in MRI is an important but very time-consuming task. This research aims to develop a method to extract brain tissue features from T2-weighted MR images of the brain using a selection of the most valuable texture features in order to discriminate between normal and affected areas of the brain. Due to textural similarity between normal and affected areas in brain MR images these operation are very challenging. A trauma may cause microstructural changes, which are not necessarily perceptible by visual inspection, but they could be detected by using a texture analysis. The proposed analysis is developed in five steps: i) in the pre-processing step: the de-noising operation is performed using the Daubechies wavelets; ii) the original images were transformed in image features using the first order descriptors; iii) the regions of interest (ROIs) were cropped from images feature following up the axial symmetry properties with respect to the mid - sagittal plan; iv) the variation in the measurement of features was quantified using the two descriptors of the co-occurrence matrix, namely energy and homogeneity; v) finally, the meaningful of the image features is analyzed by using the t-test method. P-value has been applied to the pair of features in order to measure they efficacy.

Tissue feature-based intra-fractional motion tracking for stereoscopic x-ray image guided radiotherapy

NASA Astrophysics Data System (ADS)

Xie, Yaoqin; Xing, Lei; Gu, Jia; Liu, Wu

2013-06-01

Real-time knowledge of tumor position during radiation therapy is essential to overcome the adverse effect of intra-fractional organ motion. The goal of this work is to develop a tumor tracking strategy by effectively utilizing the inherent image features of stereoscopic x-ray images acquired during dose delivery. In stereoscopic x-ray image guided radiation delivery, two orthogonal x-ray images are acquired either simultaneously or sequentially. The essence of markerless tumor tracking is the reliable identification of inherent points with distinct tissue features on each projection image and their association between two images. The identification of the feature points on a planar x-ray image is realized by searching for points with high intensity gradient. The feature points are associated by using the scale invariance features transform descriptor. The performance of the proposed technique is evaluated by using images of a motion phantom and four archived clinical cases acquired using either a CyberKnife equipped with a stereoscopic x-ray imaging system, or a LINAC equipped with an onboard kV imager and an electronic portal imaging device. In the phantom study, the results obtained using the proposed method agree with the measurements to within 2 mm in all three directions. In the clinical study, the mean error is 0.48 ± 0.46 mm for four patient data with 144 sequential images. In this work, a tissue feature-based tracking method for stereoscopic x-ray image guided radiation therapy is developed. The technique avoids the invasive procedure of fiducial implantation and may greatly facilitate the clinical workflow.

Neural network-based feature point descriptors for registration of optical and SAR images

NASA Astrophysics Data System (ADS)

Abulkhanov, Dmitry; Konovalenko, Ivan; Nikolaev, Dmitry; Savchik, Alexey; Shvets, Evgeny; Sidorchuk, Dmitry

2018-04-01

Registration of images of different nature is an important technique used in image fusion, change detection, efficient information representation and other problems of computer vision. Solving this task using feature-based approaches is usually more complex than registration of several optical images because traditional feature descriptors (SIFT, SURF, etc.) perform poorly when images have different nature. In this paper we consider the problem of registration of SAR and optical images. We train neural network to build feature point descriptors and use RANSAC algorithm to align found matches. Experimental results are presented that confirm the method's effectiveness.

SU-F-R-35: Repeatability of Texture Features in T1- and T2-Weighted MR Images

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

Mahon, R; Weiss, E; Karki, K

Purpose: To evaluate repeatability of lung tumor texture features from inspiration/expiration MR image pairs for potential use in patient specific care models and applications. Repeatability is a desirable and necessary characteristic of features included in such models. Methods: T1-weighted Volumetric Interpolation Breath-Hold Examination (VIBE) and/or T2-weighted MRI scans were acquired for 15 patients with non-small cell lung cancer before and during radiotherapy for a total of 32 and 34 same session inspiration-expiration breath-hold image pairs respectively. Bias correction was applied to the VIBE (VIBE-BC) and T2-weighted (T2-BC) images. Fifty-nine texture features at five wavelet decomposition ratios were extracted from themore » delineated primary tumor including: histogram(HIST), gray level co-occurrence matrix(GLCM), gray level run length matrix(GLRLM), gray level size zone matrix(GLSZM), and neighborhood gray tone different matrix (NGTDM) based features. Repeatability of the texture features for VIBE, VIBE-BC, T2-weighted, and T2-BC image pairs was evaluated by the concordance correlation coefficient (CCC) between corresponding image pairs, with a value greater than 0.90 indicating repeatability. Results: For the VIBE image pairs, the percentage of repeatable texture features by wavelet ratio was between 20% and 24% of the 59 extracted features; the T2-weighted image pairs exhibited repeatability in the range of 44–49%. The percentage dropped to 10–20% for the VIBE-BC images, and 12–14% for the T2-BC images. In addition, five texture features were found to be repeatable in all four image sets including two GLRLM, two GLZSM, and one NGTDN features. No single texture feature category was repeatable among all three image types; however, certain categories performed more consistently on a per image type basis. Conclusion: We identified repeatable texture features on T1- and T2-weighted MRI scans. These texture features should be further investigated for use in specific applications such as tissue classification and changes during radiation therapy utilizing a standard imaging protocol. Authors have the following disclosures: a research agreement with Philips Medical systems (Hugo, Weiss), a license agreement with Varian Medical Systems (Hugo, Weiss), research grants from the National Institute of Health (Hugo, Weiss), UpToDate royalties (Weiss), and none(Mahon, Ford, Karki). Authors have no potential conflicts of interest to disclose.« less

Method and apparatus for detecting a desired behavior in digital image data

DOEpatents

Kegelmeyer, Jr., W. Philip

1997-01-01

A method for detecting stellate lesions in digitized mammographic image data includes the steps of prestoring a plurality of reference images, calculating a plurality of features for each of the pixels of the reference images, and creating a binary decision tree from features of randomly sampled pixels from each of the reference images. Once the binary decision tree has been created, a plurality of features, preferably including an ALOE feature (analysis of local oriented edges), are calculated for each of the pixels of the digitized mammographic data. Each of these plurality of features of each pixel are input into the binary decision tree and a probability is determined, for each of the pixels, corresponding to the likelihood of the presence of a stellate lesion, to create a probability image. Finally, the probability image is spatially filtered to enforce local consensus among neighboring pixels and the spatially filtered image is output.

Method and apparatus for detecting a desired behavior in digital image data

DOEpatents

Kegelmeyer, Jr., W. Philip

1997-01-01

A method for detecting stellate lesions in digitized mammographic image data includes the steps of prestoring a plurality of reference images, calculating a plurality of features for each of the pixels of the reference images, and creating a binary decision tree from features of randomly sampled pixels from each of the reference images. Once the binary decision tree has been created, a plurality of features, preferably including an ALOE feature (analysis of local oriented edges), are calculated for each of the pixels of the digitized mammographic data. Each of these plurality of features of each pixel are input into the binary decision tree and a probability is determined, for each of the pixels, corresponding to the likelihood of the presence of a stellate lesion, to create a probability image. Finally, the probability image is spacially filtered to enforce local consensus among neighboring pixels and the spacially filtered image is output.

SKL algorithm based fabric image matching and retrieval

NASA Astrophysics Data System (ADS)

Cao, Yichen; Zhang, Xueqin; Ma, Guojian; Sun, Rongqing; Dong, Deping

2017-07-01

Intelligent computer image processing technology provides convenience and possibility for designers to carry out designs. Shape analysis can be achieved by extracting SURF feature. However, high dimension of SURF feature causes to lower matching speed. To solve this problem, this paper proposed a fast fabric image matching algorithm based on SURF K-means and LSH algorithm. By constructing the bag of visual words on K-Means algorithm, and forming feature histogram of each image, the dimension of SURF feature is reduced at the first step. Then with the help of LSH algorithm, the features are encoded and the dimension is further reduced. In addition, the indexes of each image and each class of image are created, and the number of matching images is decreased by LSH hash bucket. Experiments on fabric image database show that this algorithm can speed up the matching and retrieval process, the result can satisfy the requirement of dress designers with accuracy and speed.

World Wide Web Based Image Search Engine Using Text and Image Content Features

NASA Astrophysics Data System (ADS)

Luo, Bo; Wang, Xiaogang; Tang, Xiaoou

2003-01-01

Using both text and image content features, a hybrid image retrieval system for Word Wide Web is developed in this paper. We first use a text-based image meta-search engine to retrieve images from the Web based on the text information on the image host pages to provide an initial image set. Because of the high-speed and low cost nature of the text-based approach, we can easily retrieve a broad coverage of images with a high recall rate and a relatively low precision. An image content based ordering is then performed on the initial image set. All the images are clustered into different folders based on the image content features. In addition, the images can be re-ranked by the content features according to the user feedback. Such a design makes it truly practical to use both text and image content for image retrieval over the Internet. Experimental results confirm the efficiency of the system.

Flow-like Features On Europa

NASA Technical Reports Server (NTRS)

1997-01-01

This image shows features on Jupiter's moon Europa that may be 'flows' from ice volcanoes. It was taken by the Galileo spacecraft solid state imaging (CCD) system during its seventh orbit around Jupiter. North is to the top of the image. The sun illuminates the scene from the left, showing features with shapes similar to lava flows on Earth. Two such features can be seen in the northwest corner of the image. The southern feature appears to have flowed over a ridge along its western edge. Scientists use these types of relationships to determine which feature formed first. In this case, the ridge probably formed before the flow-like feature that covers it.

The image, centered at 22.6 degrees north latitude and 106.7 degrees west longitude, covers an area of 180 by 215 kilometers (112 by 134 miles). The smallest distinguishable features in the image are about 1.1 kilometers (0.7 miles) across. This image was obtained on April 28, 1997, when Galileo was 27,590 kilometers (16,830 miles) from Europa.

The Jet Propulsion Laboratory, Pasadena, CA manages the Galileo mission for NASA's Office of Space Science, Washington, DC. JPL is an operating division of California Institute of Technology (Caltech).

This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at URL http://galileo.jpl.nasa.gov. Background information and educational context for the images can be found at URL http://www.jpl.nasa.gov/galileo/sepo

Three-dimensional facial analysis of Chinese children with repaired unilateral cleft lip and palate

NASA Astrophysics Data System (ADS)

Othman, Siti Adibah; Aidil Koay, Noor Airin

2016-08-01

We analyzed the facial features of Chinese children with repaired unilateral cleft lip and palate (UCLP) and compared them with a normal control group using a three-dimensional (3D) stereophotogrammetry camera. This cross-sectional study examined 3D measurements of the facial surfaces of 20 Chinese children with repaired UCLP and 40 unaffected Chinese children aged 7 to 12 years old, which were captured using the VECTRA 3D five-pod photosystem and analyzed using Mirror software. Twenty-five variables and two ratios were compared between both groups using independent t-test. Intra- and inter-observer reliability was determined using ten randomly selected images and analyzed using intra-class correlation coefficient test (ICC). The level of significance was set at p < 0.0018. Intra- and inter-observers’ reliability was considered fair to excellent with an ICC value ranging from 0.54 to 0.99. Statistically significant differences (p < 0.0018) were found mainly in the nasolabial region. The cleft group exhibited wider alar base root width, flattened nose and broader nostril floor width on the cleft side. They tended to have shorter upper lip length and thinner upper vermillion thickness. Faces of Chinese children with repaired UCLP displayed meaningful differences when compared to the normal group especially in the nasolabial regions.

Localized Misfolding Within Broca's Area as a Distinctive Feature of Autistic Disorder.

PubMed

Brun, Lucile; Auzias, Guillaume; Viellard, Marine; Villeneuve, Nathalie; Girard, Nadine; Poinso, François; Da Fonseca, David; Deruelle, Christine

2016-03-01

Recent neuroimaging studies suggest that autism spectrum disorder results from abnormalities in the cortical folding pattern. Usual morphometric measurements have failed to provide reliable neuroanatomic markers. Here, we propose that sulcal pits, which are the deepest points in each fold, are suitable candidates to uncover this atypical cortical folding. Sulcal pits were extracted from a magnetic resonance imaging database of 102 children (1.5-10 years old) distributed in three groups: children with autistic disorder (n = 59), typically developing children (n = 22), and children with pervasive developmental disorder not otherwise specified (n = 21). The geometrical properties of sulcal pits were compared between these three groups. Fold-level analyses revealed a reduced pit depth in the left ascending ramus of the Sylvian fissure in children with autistic disorder only. The depth of this central fold of Broca's area was correlated with the social communication impairments that are characteristic of the pathology. Our findings support an atypical gyrogenesis of this specific fold in autistic disorder that could be used for differential diagnosis. Sulcal pits constitute valuable markers of the cortical folding dynamics and could help for the early detection of atypical brain maturation. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Diffusion Tensor Image Registration Using Hybrid Connectivity and Tensor Features

PubMed Central

Wang, Qian; Yap, Pew-Thian; Wu, Guorong; Shen, Dinggang

2014-01-01

Most existing diffusion tensor imaging (DTI) registration methods estimate structural correspondences based on voxelwise matching of tensors. The rich connectivity information that is given by DTI, however, is often neglected. In this article, we propose to integrate complementary information given by connectivity features and tensor features for improved registration accuracy. To utilize connectivity information, we place multiple anchors representing different brain anatomies in the image space, and define the connectivity features for each voxel as the geodesic distances from all anchors to the voxel under consideration. The geodesic distance, which is computed in relation to the tensor field, encapsulates information of brain connectivity. We also extract tensor features for every voxel to reflect the local statistics of tensors in its neighborhood. We then combine both connectivity features and tensor features for registration of tensor images. From the images, landmarks are selected automatically and their correspondences are determined based on their connectivity and tensor feature vectors. The deformation field that deforms one tensor image to the other is iteratively estimated and optimized according to the landmarks and their associated correspondences. Experimental results show that, by using connectivity features and tensor features simultaneously, registration accuracy is increased substantially compared with the cases using either type of features alone. PMID:24293159

Quantitative 3-D Imaging, Segmentation and Feature Extraction of the Respiratory System in Small Mammals for Computational Biophysics Simulations

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

Trease, Lynn L.; Trease, Harold E.; Fowler, John

2007-03-15

One of the critical steps toward performing computational biology simulations, using mesh based integration methods, is in using topologically faithful geometry derived from experimental digital image data as the basis for generating the computational meshes. Digital image data representations contain both the topology of the geometric features and experimental field data distributions. The geometric features that need to be captured from the digital image data are three-dimensional, therefore the process and tools we have developed work with volumetric image data represented as data-cubes. This allows us to take advantage of 2D curvature information during the segmentation and feature extraction process.more » The process is basically: 1) segmenting to isolate and enhance the contrast of the features that we wish to extract and reconstruct, 2) extracting the geometry of the features in an isosurfacing technique, and 3) building the computational mesh using the extracted feature geometry. “Quantitative” image reconstruction and feature extraction is done for the purpose of generating computational meshes, not just for producing graphics "screen" quality images. For example, the surface geometry that we extract must represent a closed water-tight surface.« less

Tumor recognition in wireless capsule endoscopy images using textural features and SVM-based feature selection.

PubMed

Li, Baopu; Meng, Max Q-H

2012-05-01

Tumor in digestive tract is a common disease and wireless capsule endoscopy (WCE) is a relatively new technology to examine diseases for digestive tract especially for small intestine. This paper addresses the problem of automatic recognition of tumor for WCE images. Candidate color texture feature that integrates uniform local binary pattern and wavelet is proposed to characterize WCE images. The proposed features are invariant to illumination change and describe multiresolution characteristics of WCE images. Two feature selection approaches based on support vector machine, sequential forward floating selection and recursive feature elimination, are further employed to refine the proposed features for improving the detection accuracy. Extensive experiments validate that the proposed computer-aided diagnosis system achieves a promising tumor recognition accuracy of 92.4% in WCE images on our collected data.

Glutaric aciduria type 1: neuroimaging features with clinical correlation.

PubMed

Mohammad, Shaimaa Abdelsattar; Abdelkhalek, Heba Salah; Ahmed, Khaled A; Zaki, Osama K

2015-10-01

Glutaric aciduria type 1 is a rare neurometabolic disease with high morbidity. To describe the MR imaging abnormalities in glutaric aciduria type 1 and to identify any association between the clinical and imaging features. MRI scans of 29 children (mean age: 16.9 months) with confirmed diagnosis of glutaric aciduria type 1 were retrospectively reviewed. Gray matter and white matter scores were calculated based on a previously published pattern-recognition approach of assessing leukoencephalopathies. Hippocampal formation and opercular topography were assessed in relation to the known embryological basis. MRI scores were correlated with morbidity score. The most consistent MRI abnormality was widened operculum with dilatation of the subarachnoid spaces surrounding underdeveloped frontotemporal lobes. Incomplete hippocampal inversion was also seen. The globus pallidus was the most frequently involved gray matter structure (86%). In addition to the central tegmental tract, white matter abnormalities preferentially involved the central and periventricular regions. The morbidity score correlated with the gray matter abnormality score (P = 0.004). Patients with dystonia had higher gray matter and morbidity scores. Morbidity is significantly correlated with abnormality of gray matter, rather than white matter, whether secondary to acute encephalopathic crisis or insidious onset disease.

Is Trypophobia a Phobia?

PubMed

Can, Wang; Zhuoran, Zhao; Zheng, Jin

2017-04-01

In the past 10 years, thousands of people have claimed to be affected by trypophobia, which is the fear of objects with small holes. Recent research suggests that people do not fear the holes; rather, images of clustered holes, which share basic visual characteristics with venomous organisms, lead to nonconscious fear. In the present study, both self-reported measures and the Preschool Single Category Implicit Association Test were adapted for use with preschoolers to investigate whether discomfort related to trypophobic stimuli was grounded in their visual features or based on a nonconsciously associated fear of venomous animals. The results indicated that trypophobic stimuli were associated with discomfort in children. This discomfort seemed to be related to the typical visual characteristics and pattern properties of trypophobic stimuli rather than to nonconscious associations with venomous animals. The association between trypophobic stimuli and venomous animals vanished when the typical visual characteristics of trypophobic features were removed from colored photos of venomous animals. Thus, the discomfort felt toward trypophobic images might be an instinctive response to their visual characteristics rather than the result of a learned but nonconscious association with venomous animals. Therefore, it is questionable whether it is justified to legitimize trypophobia.

Hyperspectral remote sensing image retrieval system using spectral and texture features.

PubMed

Zhang, Jing; Geng, Wenhao; Liang, Xi; Li, Jiafeng; Zhuo, Li; Zhou, Qianlan

2017-06-01

Although many content-based image retrieval systems have been developed, few studies have focused on hyperspectral remote sensing images. In this paper, a hyperspectral remote sensing image retrieval system based on spectral and texture features is proposed. The main contributions are fourfold: (1) considering the "mixed pixel" in the hyperspectral image, endmembers as spectral features are extracted by an improved automatic pixel purity index algorithm, then the texture features are extracted with the gray level co-occurrence matrix; (2) similarity measurement is designed for the hyperspectral remote sensing image retrieval system, in which the similarity of spectral features is measured with the spectral information divergence and spectral angle match mixed measurement and in which the similarity of textural features is measured with Euclidean distance; (3) considering the limited ability of the human visual system, the retrieval results are returned after synthesizing true color images based on the hyperspectral image characteristics; (4) the retrieval results are optimized by adjusting the feature weights of similarity measurements according to the user's relevance feedback. The experimental results on NASA data sets can show that our system can achieve comparable superior retrieval performance to existing hyperspectral analysis schemes.

The role of landscape spatial patterns on obesity in Hispanic children residing in inner-city neighborhoods.

PubMed

Kim, Jun-Hyun; Lee, Chanam; Olvara, Norma E; Ellis, Christopher D

2014-11-01

Childhood obesity and its comorbidities have become major public health challenges in the US. While previous studies have investigated the roles of land uses and transportation infrastructure on obesity, limited research has examined the influence of landscape spatial patterns. The purpose of this study was to examine the association between landscape spatial patterns and obesity in Hispanic children. Participants included 61 fourth- and fifth-grade Hispanic children from inner-city neighborhoods in Houston, TX. BMI z-scores were computed based on objectively-measured height and weight from each child. Parental and child surveys provided sociodemographic and physical activity data. Landscape indices were used to measure the quality of landscape spatial patterns surrounding each child's home by utilizing Geographic Information Systems and remote sensing analyses using aerial photo images. After controlling for sociodemographic factors, in the half-mile airline buffer, more tree patches and well-connected landscape patterns were negatively correlated with their BMI z-scores. Furthermore, larger sizes of urban forests and tree patches were negatively associated with children's BMI z-scores in the half-mile network buffer assessment. This study suggests that urban greenery requires further attention in studies aimed at identifying environmental features that reduce childhood obesity.

Obesity, body image, and its impact on children's eating and exercise behaviors in China: A nationwide longitudinal study.

PubMed

Min, Jungwon; Yan, Alice Fang; Wang, Vivian H C; Wang, Youfa

2018-01-01

Body image seems to mediate the association between obesity and health behaviors as well as weight control attempts. We examined the distribution of children's body image by demographic characteristics and their subsequent associations with eating, exercise, and weight change. Child body image and health behaviors from the China Health National Survey 2000-2011 were assessed at baseline and in follow-up for 6- to 17-year-old children during 2000-2011 using mixed models. There was a large discrepancy between children's actual weight status (overweight: 16.9%) vs. self-rated body image (fat: 2.4% in 2011). Less than 1% of children desired a fat body; girls were more likely to want to be thin (52.5% vs. 40.9%) than boys. About 11% of children needed to lose weight in order to be at their desired baseline. During follow-up, those needing weight loss to be as desired were more likely to attempt dieting to change their weight (OR, 95% CI=1.9, 1.1-3.5 in boys; 1.7, 1.1-2.5 in girls) and less likely to feel they had enough physical activity (OR, 95% CI=0.5, 0.4-0.7 in boys; 0.6, 0.5-0.9 in girls), although their weight gain had been significantly higher than those having consistent self and desired body images (β [SE]=0.4 [0.1] in boys; 0.2 [0.1] in girls, all p<0.05). However, no significant difference was shown in subsequent health behaviors among overweight children by body image discrepancy. The discrepancy in self vs. desired body image motivated children to change their obesity-related health behaviors among non-overweight children in China. Copyright © 2017 Elsevier Inc. All rights reserved.

Pornographic image detection with Gabor filters

NASA Astrophysics Data System (ADS)

Durrell, Kevan; Murray, Daniel J. C.

2002-04-01

As Internet-enabled computers become ubiquitous in homes, schools, and other publicly accessible locations, there are more people 'surfing the net' who would prefer not to be exposed to offensive material. There is a lot of material freely available on the Internet that we, as a responsible and caring society, would like to keep our children from viewing. Pornographic image content is one category of material over which we would like some control. We have been conducting experiments to determine the effectiveness of using characteristic feature vectors and neural networks to identify semantic image content. This paper will describe our approach to identifying pornographic images using Gabor filters, Principal Component Analysis (PCA), Correllograms, and Neural Networks. In brief, we used a set of 5,000 typical images available from the Internet, 20% of which were judged to be pornographic, to train a neural network. We then apply the trained neural network to feature vectors from images that had not been used in training. We measure our performance as Recall, how many of the verification images labeled pornographic were correctly identified, and Precision, how many images deemed pornographic by the neural network are in fact pornographic. The set of images that were used in the experiment described in this paper for its training and validation sets are freely available on the Internet. Freely available is an important qualifier, since high-resolution, studio-quality pornographic images are often protected by portals that charge members a fee to gain access to their material. Although this is not a hard and fast rule, many of the pornographic images that are available easily and without charge on the Internet are of low image quality. Some of these images are collages or contain textual elements or have had their resolution intentionally lowered to reduce their file size. These are the offensive images that a user, without a credit card, might inadvertently come across on the Internet. Identifying this type of pornographic pictures of low image quality poses particular challenges for any detection software. This paper will address some of the challenges and hurdles we faced in designing and carrying out our experiments. The paper will also discuss the main results of our experiments, as well as some confounds that, at present, limit the effectiveness of our approach to identifying pornographic images, and some directions that may be taken in future research.

Effects of a Parenting Intervention on Features of Psychopathy in Children

ERIC Educational Resources Information Center

McDonald, Renee; Dodson, Mary Catherine; Rosenfield, David; Jouriles, Ernest N.

2011-01-01

This study examined whether Project Support, a parenting intervention shown to reduce child conduct problems, also exerts positive effects on features of psychopathy in children. Participants were 66 families (mothers and children) recruited from domestic violence shelters who participated in a randomized controlled trial evaluating Project…

Beliefs about the Realism of Television Programs Featuring Families.

ERIC Educational Resources Information Center

Dorr, Aimee; And Others

When children watch television, they can assess the reality of what they are seeing. Content judged unreal may have less influence on viewers than does content judged real. This study examines children's reality judgments about television series featuring families with children. Participants included twenty-seven 7-year-olds, nineteen…

A method for fast automated microscope image stitching.

PubMed

Yang, Fan; Deng, Zhen-Sheng; Fan, Qiu-Hong

2013-05-01

Image stitching is an important technology to produce a panorama or larger image by combining several images with overlapped areas. In many biomedical researches, image stitching is highly desirable to acquire a panoramic image which represents large areas of certain structures or whole sections, while retaining microscopic resolution. In this study, we develop a fast normal light microscope image stitching algorithm based on feature extraction. At first, an algorithm of scale-space reconstruction of speeded-up robust features (SURF) was proposed to extract features from the images to be stitched with a short time and higher repeatability. Then, the histogram equalization (HE) method was employed to preprocess the images to enhance their contrast for extracting more features. Thirdly, the rough overlapping zones of the images preprocessed were calculated by phase correlation, and the improved SURF was used to extract the image features in the rough overlapping areas. Fourthly, the features were corresponded by matching algorithm and the transformation parameters were estimated, then the images were blended seamlessly. Finally, this procedure was applied to stitch normal light microscope images to verify its validity. Our experimental results demonstrate that the improved SURF algorithm is very robust to viewpoint, illumination, blur, rotation and zoom of the images and our method is able to stitch microscope images automatically with high precision and high speed. Also, the method proposed in this paper is applicable to registration and stitching of common images as well as stitching the microscope images in the field of virtual microscope for the purpose of observing, exchanging, saving, and establishing a database of microscope images. Copyright © 2013 Elsevier Ltd. All rights reserved.

Information based universal feature extraction

NASA Astrophysics Data System (ADS)

Amiri, Mohammad; Brause, Rüdiger

2015-02-01

In many real world image based pattern recognition tasks, the extraction and usage of task-relevant features are the most crucial part of the diagnosis. In the standard approach, they mostly remain task-specific, although humans who perform such a task always use the same image features, trained in early childhood. It seems that universal feature sets exist, but they are not yet systematically found. In our contribution, we tried to find those universal image feature sets that are valuable for most image related tasks. In our approach, we trained a neural network by natural and non-natural images of objects and background, using a Shannon information-based algorithm and learning constraints. The goal was to extract those features that give the most valuable information for classification of visual objects hand-written digits. This will give a good start and performance increase for all other image learning tasks, implementing a transfer learning approach. As result, in our case we found that we could indeed extract features which are valid in all three kinds of tasks.

Reliability of magnetic resonance imaging for the detection of hypopituitarism in children with optic nerve hypoplasia.

PubMed

Ramakrishnaiah, Raghu H; Shelton, Julie B; Glasier, Charles M; Phillips, Paul H

2014-01-01

It is essential to identify hypopituitarism in children with optic nerve hypoplasia (ONH) because they are at risk for developmental delay, seizures, or death. The purpose of this study is to determine the reliability of neurohypophyseal abnormalities on magnetic resonance imaging (MRI) for the detection of hypopituitarism in children with ONH. Cross-sectional study. One hundred one children with clinical ONH who underwent MRI of the brain and orbits and a detailed pediatric endocrinologic evaluation. Magnetic resonance imaging studies were performed on 1.5-Tesla scanners. The imaging protocol included sagittal T1-weighted images, axial fast fluid-attenuated inversion-recovery/T2-weighted images, and diffusion-weighted images of the brain. Orbital imaging included fat-saturated axial and coronal images and high-resolution axial T2-weighted images. The MRI studies were reviewed by 2 pediatric neuroradiologists for optic nerve hypoplasia, absent or ectopic posterior pituitary, absent pituitary infundibulum, absent septum pellucidum, migration anomalies, and hemispheric injury. Medical records were reviewed for clinical examination findings and endocrinologic status. All patients underwent a clinical evaluation by a pediatric endocrinologist and a standardized panel of serologic testing that included serum insulin-like growth factor-1, insulin-like growth factor binding protein-3, prolactin, cortisol, adrenocorticotropic hormone, thyroid-stimulating hormone, and free thyroxine levels. Radiologists were masked to patients' endocrinologic status and funduscopic findings. Sensitivity and specificity of MRI findings for the detection of hypopituitarism. Neurohypophyseal abnormalities, including absent pituitary infundibulum, ectopic posterior pituitary bright spot, and absent posterior pituitary bright spot, occurred in 33 children. Magnetic resonance imaging disclosed neurohypophyseal abnormalities in 27 of the 28 children with hypopituitarism (sensitivity, 96%). A normal neurohypophysis occurred in 67 of 73 children with normal endocrinologic function (specificity, 92%). Neurohypophyseal abnormalities on MRI are sensitive and specific indicators of hypopituitarism in children with ONH. Copyright © 2014 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

A fast and automatic mosaic method for high-resolution satellite images

NASA Astrophysics Data System (ADS)

Chen, Hongshun; He, Hui; Xiao, Hongyu; Huang, Jing

2015-12-01

We proposed a fast and fully automatic mosaic method for high-resolution satellite images. First, the overlapped rectangle is computed according to geographical locations of the reference and mosaic images and feature points on both the reference and mosaic images are extracted by a scale-invariant feature transform (SIFT) algorithm only from the overlapped region. Then, the RANSAC method is used to match feature points of both images. Finally, the two images are fused into a seamlessly panoramic image by the simple linear weighted fusion method or other method. The proposed method is implemented in C++ language based on OpenCV and GDAL, and tested by Worldview-2 multispectral images with a spatial resolution of 2 meters. Results show that the proposed method can detect feature points efficiently and mosaic images automatically.

The Psychological Reality of Phonetic Features in Children.

ERIC Educational Resources Information Center

Zagar, Linda L.; Locke, John L.

1986-01-01

Ten linguistically normal four to five year olds were trained to associate consonantal features of voicing, manner, and place of articulation with cups of particular location and color. It was concluded that phonetic features are of limited availability to children in associative tasks and that their clinical value with phonologically disordered…

Morphological Feature Extraction for Automatic Registration of Multispectral Images

NASA Technical Reports Server (NTRS)

Plaza, Antonio; LeMoigne, Jacqueline; Netanyahu, Nathan S.

2007-01-01

The task of image registration can be divided into two major components, i.e., the extraction of control points or features from images, and the search among the extracted features for the matching pairs that represent the same feature in the images to be matched. Manual extraction of control features can be subjective and extremely time consuming, and often results in few usable points. On the other hand, automated feature extraction allows using invariant target features such as edges, corners, and line intersections as relevant landmarks for registration purposes. In this paper, we present an extension of a recently developed morphological approach for automatic extraction of landmark chips and corresponding windows in a fully unsupervised manner for the registration of multispectral images. Once a set of chip-window pairs is obtained, a (hierarchical) robust feature matching procedure, based on a multiresolution overcomplete wavelet decomposition scheme, is used for registration purposes. The proposed method is validated on a pair of remotely sensed scenes acquired by the Advanced Land Imager (ALI) multispectral instrument and the Hyperion hyperspectral instrument aboard NASA's Earth Observing-1 satellite.

Natural image statistics and low-complexity feature selection.

PubMed

Vasconcelos, Manuela; Vasconcelos, Nuno

2009-02-01

Low-complexity feature selection is analyzed in the context of visual recognition. It is hypothesized that high-order dependences of bandpass features contain little information for discrimination of natural images. This hypothesis is characterized formally by the introduction of the concepts of conjunctive interference and decomposability order of a feature set. Necessary and sufficient conditions for the feasibility of low-complexity feature selection are then derived in terms of these concepts. It is shown that the intrinsic complexity of feature selection is determined by the decomposability order of the feature set and not its dimension. Feature selection algorithms are then derived for all levels of complexity and are shown to be approximated by existing information-theoretic methods, which they consistently outperform. The new algorithms are also used to objectively test the hypothesis of low decomposability order through comparison of classification performance. It is shown that, for image classification, the gain of modeling feature dependencies has strongly diminishing returns: best results are obtained under the assumption of decomposability order 1. This suggests a generic law for bandpass features extracted from natural images: that the effect, on the dependence of any two features, of observing any other feature is constant across image classes.

The Use of Enteric Contrast Media for Diagnostic CT, MRI, and Ultrasound in Infants and Children: A Practical Approach.

PubMed

Callahan, Michael J; Talmadge, Jennifer M; MacDougall, Robert; Buonomo, Carlo; Taylor, George A

2016-05-01

Enteric contrast media are commonly administered for diagnostic cross-sectional imaging studies in the pediatric population. The purpose of this manuscript is to review the use of enteric contrast media for CT, MRI, and ultrasound in infants, children, and adolescents and to share our experiences at a large tertiary care pediatric teaching hospital. The use of enteric contrast material for diagnostic imaging in infants and children continues to evolve with advances in imaging technology and available enteric contrast media. Many principles of enteric contrast use in pediatric imaging are similar to those in adult imaging, but important differences must be kept in mind when imaging the gastrointestinal tract in infants and children, and practical ways to optimize the imaging examination and the patient experience should be employed where possible.

Color image definition evaluation method based on deep learning method

NASA Astrophysics Data System (ADS)

Liu, Di; Li, YingChun

2018-01-01

In order to evaluate different blurring levels of color image and improve the method of image definition evaluation, this paper proposed a method based on the depth learning framework and BP neural network classification model, and presents a non-reference color image clarity evaluation method. Firstly, using VGG16 net as the feature extractor to extract 4,096 dimensions features of the images, then the extracted features and labeled images are employed in BP neural network to train. And finally achieve the color image definition evaluation. The method in this paper are experimented by using images from the CSIQ database. The images are blurred at different levels. There are 4,000 images after the processing. Dividing the 4,000 images into three categories, each category represents a blur level. 300 out of 400 high-dimensional features are trained in VGG16 net and BP neural network, and the rest of 100 samples are tested. The experimental results show that the method can take full advantage of the learning and characterization capability of deep learning. Referring to the current shortcomings of the major existing image clarity evaluation methods, which manually design and extract features. The method in this paper can extract the images features automatically, and has got excellent image quality classification accuracy for the test data set. The accuracy rate is 96%. Moreover, the predicted quality levels of original color images are similar to the perception of the human visual system.

Analysis of pseudocolor transformations of ERTS-1 images of Southern California area. [geological faults and lineaments

NASA Technical Reports Server (NTRS)

Merifield, P. M. (Principal Investigator); Lamar, D. L.; Stratton, R. H.; Lamar, J. V.; Gazley, C., Jr.

1974-01-01

The author has identified the following significant results. Representative faults and lineaments, natural features on the Mojave Desert, and cultural features of the southern California area were studied on ERTS-1 images. The relative appearances of the features were compared on a band 4 and 5 subtraction image, its pseudocolor transformation, and pseudocolor images of bands 4, 5, and 7. Selected features were also evaluated in a test given students at the University of California, Los Angeles. Observations and the test revealed no significant improvement in the ability to detect and locate faults and lineaments on the pseudocolor transformations. With the exception of dry lake surfaces, no enhancement of the features studied was observed on the bands 4 and 5 subtraction images. Geologic and geographic features characterized by minor tonal differences on relatively flat surfaces were enhanced on some of the pseudocolor images.

Multiple Hypotheses Image Segmentation and Classification With Application to Dietary Assessment

PubMed Central

Zhu, Fengqing; Bosch, Marc; Khanna, Nitin; Boushey, Carol J.; Delp, Edward J.

2016-01-01

We propose a method for dietary assessment to automatically identify and locate food in a variety of images captured during controlled and natural eating events. Two concepts are combined to achieve this: a set of segmented objects can be partitioned into perceptually similar object classes based on global and local features; and perceptually similar object classes can be used to assess the accuracy of image segmentation. These ideas are implemented by generating multiple segmentations of an image to select stable segmentations based on the classifier’s confidence score assigned to each segmented image region. Automatic segmented regions are classified using a multichannel feature classification system. For each segmented region, multiple feature spaces are formed. Feature vectors in each of the feature spaces are individually classified. The final decision is obtained by combining class decisions from individual feature spaces using decision rules. We show improved accuracy of segmenting food images with classifier feedback. PMID:25561457

On the appropriate feature for general SAR image registration

NASA Astrophysics Data System (ADS)

Li, Dong; Zhang, Yunhua

2012-09-01

An investigation to the appropriate feature for SAR image registration is conducted. The commonly-used features such as tie points, Harris corner, the scale invariant feature transform (SIFT), and the speeded up robust feature (SURF) are comprehensively evaluated in terms of several criteria such as the geometrical invariance of feature, the extraction speed, the localization accuracy, the geometrical invariance of descriptor, the matching speed, the robustness to decorrelation, and the flexibility to image speckling. It is shown that SURF outperforms others. It is particularly indicated that SURF has good flexibility to image speckling because the Fast-Hessian detector of SURF has a potential relation with the refined Lee filter. It is recommended to perform SURF on the oversampled image with unaltered sampling step so as to improve the subpixel registration accuracy and speckle immunity. Thus SURF is more appropriate and competent for general SAR image registration.

Change Detection of High-Resolution Remote Sensing Images Based on Adaptive Fusion of Multiple Features

NASA Astrophysics Data System (ADS)

Wang, G. H.; Wang, H. B.; Fan, W. F.; Liu, Y.; Chen, C.

2018-04-01

In view of the traditional change detection algorithm mainly depends on the spectral information image spot, failed to effectively mining and fusion of multi-image feature detection advantage, the article borrows the ideas of object oriented analysis proposed a multi feature fusion of remote sensing image change detection algorithm. First by the multi-scale segmentation of image objects based; then calculate the various objects of color histogram and linear gradient histogram; utilizes the color distance and edge line feature distance between EMD statistical operator in different periods of the object, using the adaptive weighted method, the color feature distance and edge in a straight line distance of combination is constructed object heterogeneity. Finally, the curvature histogram analysis image spot change detection results. The experimental results show that the method can fully fuse the color and edge line features, thus improving the accuracy of the change detection.

No-reference image quality assessment based on statistics of convolution feature maps

NASA Astrophysics Data System (ADS)

Lv, Xiaoxin; Qin, Min; Chen, Xiaohui; Wei, Guo

2018-04-01

We propose a Convolutional Feature Maps (CFM) driven approach to accurately predict image quality. Our motivation bases on the finding that the Nature Scene Statistic (NSS) features on convolution feature maps are significantly sensitive to distortion degree of an image. In our method, a Convolutional Neural Network (CNN) is trained to obtain kernels for generating CFM. We design a forward NSS layer which performs on CFM to better extract NSS features. The quality aware features derived from the output of NSS layer is effective to describe the distortion type and degree an image suffered. Finally, a Support Vector Regression (SVR) is employed in our No-Reference Image Quality Assessment (NR-IQA) model to predict a subjective quality score of a distorted image. Experiments conducted on two public databases demonstrate the promising performance of the proposed method is competitive to state of the art NR-IQA methods.

Multiple hypotheses image segmentation and classification with application to dietary assessment.

PubMed

Zhu, Fengqing; Bosch, Marc; Khanna, Nitin; Boushey, Carol J; Delp, Edward J

2015-01-01

We propose a method for dietary assessment to automatically identify and locate food in a variety of images captured during controlled and natural eating events. Two concepts are combined to achieve this: a set of segmented objects can be partitioned into perceptually similar object classes based on global and local features; and perceptually similar object classes can be used to assess the accuracy of image segmentation. These ideas are implemented by generating multiple segmentations of an image to select stable segmentations based on the classifier's confidence score assigned to each segmented image region. Automatic segmented regions are classified using a multichannel feature classification system. For each segmented region, multiple feature spaces are formed. Feature vectors in each of the feature spaces are individually classified. The final decision is obtained by combining class decisions from individual feature spaces using decision rules. We show improved accuracy of segmenting food images with classifier feedback.

Nutrition-related claims on children's cereals: what do they mean to parents and do they influence willingness to buy?

PubMed

Harris, Jennifer L; Thompson, Jacqueline M; Schwartz, Marlene B; Brownell, Kelly D

2011-12-01

To examine parents' beliefs about the meaning of common front-of-package nutrition-related claims on children's cereals and determine whether the claims would make them more willing to buy the cereals. Parents viewed images of box fronts for children's cereals of below-average nutritional quality, as assessed by a validated nutrient profiling model. These boxes featured various nutrition-related claims including 'supports your child's immunity', 'whole grain', 'fibre', 'calcium and vitamin D' and 'organic'. Participants were provided possible meanings for these claims and asked to select any that applied with the option to write in additional meanings. They also indicated how the claim would affect their willingness to buy the product. Online survey. Parents with children between the ages of 2 and 11 years (n 306) recruited through an online panel. The majority of parents misinterpreted the meaning of claims commonly used on children's cereals. They inferred that cereals with claims were more nutritious overall and might provide specific health-related benefits for their children; and these beliefs predicted greater willingness to buy the cereals. These findings indicate that common front-of-package nutrition-related claims are potentially misleading, especially when placed on products with high levels of nutrients to limit (e.g. sugar, sodium) and low levels of other nutrients to encourage (e.g. fibre, protein). Additional regulation is needed to protect consumers in the USA.

Temporal features of word-initial /s/+stop clusters in bilingual Mandarin-English children and monolingual English children and adults.

PubMed

Yang, Jing

2018-03-01

This study investigated the durational features of English word-initial /s/+stop clusters produced by bilingual Mandarin (L1)-English (L2) children and monolingual English children and adults. The participants included two groups of five- to six-year-old bilingual children: low proficiency in the L2 (Bi-low) and high proficiency in the L2 (Bi-high), one group of age-matched English children, and one group of English adults. Each participant produced a list of English words containing /sp, st, sk/ at the word-initial position followed by /a, i, u/, respectively. The absolute durations of the clusters and cluster elements and the durational proportions of elements to the overall cluster were measured. The results revealed that Bi-high children behaved similarly to the English monolinguals whereas Bi-low children used a different strategy of temporal organization to coordinate the cluster components in comparison to the English monolinguals and Bi-high children. The influence of language experience and continuing development of temporal features in children were discussed.

[Research Progress of Multi-Model Medical Image Fusion at Feature Level].

PubMed

Zhang, Junjie; Zhou, Tao; Lu, Huiling; Wang, Huiqun

2016-04-01

Medical image fusion realizes advantage integration of functional images and anatomical images.This article discusses the research progress of multi-model medical image fusion at feature level.We firstly describe the principle of medical image fusion at feature level.Then we analyze and summarize fuzzy sets,rough sets,D-S evidence theory,artificial neural network,principal component analysis and other fusion methods’ applications in medical image fusion and get summery.Lastly,we in this article indicate present problems and the research direction of multi-model medical images in the future.

Automated simultaneous multiple feature classification of MTI data

NASA Astrophysics Data System (ADS)

Harvey, Neal R.; Theiler, James P.; Balick, Lee K.; Pope, Paul A.; Szymanski, John J.; Perkins, Simon J.; Porter, Reid B.; Brumby, Steven P.; Bloch, Jeffrey J.; David, Nancy A.; Galassi, Mark C.

2002-08-01

Los Alamos National Laboratory has developed and demonstrated a highly capable system, GENIE, for the two-class problem of detecting a single feature against a background of non-feature. In addition to the two-class case, however, a commonly encountered remote sensing task is the segmentation of multispectral image data into a larger number of distinct feature classes or land cover types. To this end we have extended our existing system to allow the simultaneous classification of multiple features/classes from multispectral data. The technique builds on previous work and its core continues to utilize a hybrid evolutionary-algorithm-based system capable of searching for image processing pipelines optimized for specific image feature extraction tasks. We describe the improvements made to the GENIE software to allow multiple-feature classification and describe the application of this system to the automatic simultaneous classification of multiple features from MTI image data. We show the application of the multiple-feature classification technique to the problem of classifying lava flows on Mauna Loa volcano, Hawaii, using MTI image data and compare the classification results with standard supervised multiple-feature classification techniques.

Feature extraction based on extended multi-attribute profiles and sparse autoencoder for remote sensing image classification

NASA Astrophysics Data System (ADS)

Teffahi, Hanane; Yao, Hongxun; Belabid, Nasreddine; Chaib, Souleyman

2018-02-01

The satellite images with very high spatial resolution have been recently widely used in image classification topic as it has become challenging task in remote sensing field. Due to a number of limitations such as the redundancy of features and the high dimensionality of the data, different classification methods have been proposed for remote sensing images classification particularly the methods using feature extraction techniques. This paper propose a simple efficient method exploiting the capability of extended multi-attribute profiles (EMAP) with sparse autoencoder (SAE) for remote sensing image classification. The proposed method is used to classify various remote sensing datasets including hyperspectral and multispectral images by extracting spatial and spectral features based on the combination of EMAP and SAE by linking them to kernel support vector machine (SVM) for classification. Experiments on new hyperspectral image "Huston data" and multispectral image "Washington DC data" shows that this new scheme can achieve better performance of feature learning than the primitive features, traditional classifiers and ordinary autoencoder and has huge potential to achieve higher accuracy for classification in short running time.

Images of Childhood and the Implied Reader in Young Children's Information Books

ERIC Educational Resources Information Center

Larkin-Lieffers, Patricia A.

2010-01-01

Images of childhood are ideas and expectations of childhood and children, and are reflections of individual perception and cultural ideologies. In writing children's books, authors draw on their conscious and unconscious thoughts of childhood to create an implied reader. In this paper I investigate images of childhood through examination of the…

A pilot study regarding basic knowledge of "cortical visual impairment in children" among ophthalmologists.

PubMed

Maitreya, Amit; Rawat, Darshika; Pandey, Shubham

2018-02-01

A pilot study was done to evaluate knowledge regarding "cortical visual impairment (CVI) in children" among ophthalmologists. This study was conducted during the annual conference of a zonal ophthalmological society. All ophthalmologists who attended the conference were requested to participate in this study. Those who agreed were given a validated questionnaire to assess knowledge regarding CVI. Cronbach's alpha of the questionnaire was 0.6. Participants were asked to respond to multiple choice questions by choosing the single best option. The responses obtained were then evaluated. The total number of registered delegates in the conference was 448. A total of 103 ophthalmologists showed interest to participate in the study with a response rate of 22.9%. Only 89/103 interested delegates were included in the study as remaining were unaware of CVI. No participant gave correct answers to all questions. Although more than 80% of them knew the most common association (87%) and site of pathology (84%), only 52% were sure about clinical features and even lesser respondents (39%) knew that magnetic resonance imaging is the correct investigation of choice. The majority responded correctly that these children need eye examination (89%) and can be managed by rehabilitation through multidisciplinary approach (82%), but only 58% could recognize differential diagnoses and had a correct idea regarding the prognosis of CVI. There was no correlation between the number of patients diagnosed per month by the respondent with knowledge of the disease. In this pilot study, ophthalmologists were found to have limited knowledge regarding clinical features, investigation, differential diagnosis, and visual prognosis of CVI in children. There is a need to improve awareness regarding CVI among ophthalmologists.

In Vivo measurement of pediatric vocal fold motion using structured light laser projection.

PubMed

Patel, Rita R; Donohue, Kevin D; Lau, Daniel; Unnikrishnan, Harikrishnan

2013-07-01

The aim of the study was to present the development of a miniature structured light laser projection endoscope and to quantify vocal fold length and vibratory features related to impact stress of the pediatric glottis using high-speed imaging. The custom-developed laser projection system consists of a green laser with a 4-mm diameter optics module at the tip of the endoscope, projecting 20 vertical laser lines on the glottis. Measurements of absolute phonatory vocal fold length, membranous vocal fold length, peak amplitude, amplitude-to-length ratio, average closing velocity, and impact velocity were obtained in five children (6-9 years), two adult male and three adult female participants without voice disorders, and one child (10 years) with bilateral vocal fold nodules during modal phonation. Independent measurements made on the glottal length of a vocal fold phantom demonstrated a 0.13mm bias error with a standard deviation of 0.23mm, indicating adequate precision and accuracy for measuring vocal fold structures and displacement. First, in vivo measurements of amplitude-to-length ratio, peak closing velocity, and impact velocity during phonation in pediatric population and a child with vocal fold nodules are reported. The proposed laser projection system can be used to obtain in vivo measurements of absolute length and vibratory features in children and adults. Children have large amplitude-to-length ratio compared with typically developing adults, whereas nodules result in larger peak amplitude, amplitude-to-length ratio, average closing velocity, and impact velocity compared with typically developing children. Copyright © 2013 The Voice Foundation. Published by Mosby, Inc. All rights reserved.

Pseudotumour cerebri in children: Aetiology, clinical features, and progression.

PubMed

Mosquera Gorostidi, A; Iridoy Zulet, M; Azcona Ganuza, G; Gembero Esarte, E; Yoldi Petri, M E; Aguilera Albesa, S

2017-01-09

The definition, associated aetiologies, diagnosis, and treatment of idiopathic intracranial hypertension, or pseudotumour cerebri (PTC), are constantly being revised in the paediatric population. Our study included children younger than 15 years old with PTC and attended at a reference hospital in the past 12 years. We analysed the clinical and epidemiological features of our sample and the diagnostic and treatment approaches. PTC was defined as presence of intracranial hypertension (CSF opening pressure>25cmH 2 O) and absence of space-occupying lesions in brain MR images. A total of 12 children with PTC were included; mean age was 10 years and 90% were girls. Weight was normal in all patients. Eighty-two percent of the patients had symptoms: headache (66%), diplopia (8%), and visual loss (8%). All of them displayed papilloedema (17% unilaterally). Lumbar puncture (LP) provided the diagnosis in all cases and 91% showed no relevant MRI findings. A potential cause of PTC was identified in 5 cases: pharmacological treatment in 2 and infection (Mycoplasma pneumoniae [M. pneumoniae]) in 3. Ninety-one per cent of the patients received treatment: 75% underwent several LPs and 42% received acetazolamide and/or prednisone. Outcomes were favourable in all cases. The incidence of PTC was estimated at approximately 1 case per 100 000 children/years, in line with data reported by previous studies. Overweight was not found to be a risk factor for PTC in this population. M. pneumoniae infection may trigger PTC and cause recurrences at later stages. The absence of symptoms seems to be independent from the degree of intracranial hypertension. Acetazolamide treatment is effective in most cases, and it represents a viable alternative to repeated LP. Copyright © 2016 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.

Plaque echodensity and textural features are associated with histologic carotid plaque instability.

PubMed

Doonan, Robert J; Gorgui, Jessica; Veinot, Jean P; Lai, Chi; Kyriacou, Efthyvoulos; Corriveau, Marc M; Steinmetz, Oren K; Daskalopoulou, Stella S

2016-09-01

Carotid plaque echodensity and texture features predict cerebrovascular symptomatology. Our purpose was to determine the association of echodensity and textural features obtained from a digital image analysis (DIA) program with histologic features of plaque instability as well as to identify the specific morphologic characteristics of unstable plaques. Patients scheduled to undergo carotid endarterectomy were recruited and underwent carotid ultrasound imaging. DIA was performed to extract echodensity and textural features using Plaque Texture Analysis software (LifeQ Medical Ltd, Nicosia, Cyprus). Carotid plaque surgical specimens were obtained and analyzed histologically. Principal component analysis (PCA) was performed to reduce imaging variables. Logistic regression models were used to determine if PCA variables and individual imaging variables predicted histologic features of plaque instability. Image analysis data from 160 patients were analyzed. Individual imaging features of plaque echolucency and homogeneity were associated with a more unstable plaque phenotype on histology. These results were independent of age, sex, and degree of carotid stenosis. PCA reduced 39 individual imaging variables to five PCA variables. PCA1 and PCA2 were significantly associated with overall plaque instability on histology (both P = .02), whereas PCA3 did not achieve statistical significance (P = .07). DIA features of carotid plaques are associated with histologic plaque instability as assessed by multiple histologic features. Importantly, unstable plaques on histology appear more echolucent and homogeneous on ultrasound imaging. These results are independent of stenosis, suggesting that image analysis may have a role in refining the selection of patients who undergo carotid endarterectomy. Copyright © 2016 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

SU-E-I-01: Iterative CBCT Reconstruction with a Feature-Preserving Penalty

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

Lyu, Q; Li, B; Southern Medical University, Guangzhou

2015-06-15

Purpose: Low-dose CBCT is desired in various clinical applications. Iterative image reconstruction algorithms have shown advantages in suppressing noise in low-dose CBCT. However, due to the smoothness constraint enforced during the reconstruction process, edges may be blurred and image features may lose in the reconstructed image. In this work, we proposed a new penalty design to preserve image features in the image reconstructed by iterative algorithms. Methods: Low-dose CBCT is reconstructed by minimizing the penalized weighted least-squares (PWLS) objective function. Binary Robust Independent Elementary Features (BRIEF) of the image were integrated into the penalty of PWLS. BRIEF is a generalmore » purpose point descriptor that can be used to identify important features of an image. In this work, BRIEF distance of two neighboring pixels was used to weigh the smoothing parameter in PWLS. For pixels of large BRIEF distance, weaker smooth constraint will be enforced. Image features will be better preserved through such a design. The performance of the PWLS algorithm with BRIEF penalty was evaluated by a CatPhan 600 phantom. Results: The image quality reconstructed by the proposed PWLS-BRIEF algorithm is superior to that by the conventional PWLS method and the standard FDK method. At matched noise level, edges in PWLS-BRIEF reconstructed image are better preserved. Conclusion: This study demonstrated that the proposed PWLS-BRIEF algorithm has great potential on preserving image features in low-dose CBCT.« less

Baby schema modulates the brain reward system in nulliparous women.

PubMed

Glocker, Melanie L; Langleben, Daniel D; Ruparel, Kosha; Loughead, James W; Valdez, Jeffrey N; Griffin, Mark D; Sachser, Norbert; Gur, Ruben C

2009-06-02

Ethologist Konrad Lorenz defined the baby schema ("Kindchenschema") as a set of infantile physical features, such as round face and big eyes, that is perceived as cute and motivates caretaking behavior in the human, with the evolutionary function of enhancing offspring survival. The neural basis of this fundamental altruistic instinct is not well understood. Prior studies reported a pattern of brain response to pictures of children, but did not dissociate the brain response to baby schema from the response to children. Using functional magnetic resonance imaging and controlled manipulation of the baby schema in infant faces, we found that baby schema activates the nucleus accumbens, a key structure of the mesocorticolimbic system mediating reward processing and appetitive motivation, in nulliparous women. Our findings suggest that engagement of the mesocorticolimbic system is the neurophysiologic mechanism by which baby schema promotes human caregiving, regardless of kinship.

Lung magnetic resonance imaging for pneumonia in children.

PubMed

Liszewski, Mark C; Görkem, Süreyya; Sodhi, Kushaljit S; Lee, Edward Y

2017-10-01

Technical factors have historically limited the role of MRI in the evaluation of pneumonia in children in routine clinical practice. As imaging technology has advanced, recent studies utilizing practical MR imaging protocols have shown MRI to be an accurate potential alternative to CT for the evaluation of pneumonia and its complications. This article provides up-to-date MR imaging techniques that can be implemented in most radiology departments to evaluate pneumonia in children. Imaging findings in pneumonia on MRI are also reviewed. In addition, the current literature describing the diagnostic performance of MRI for pneumonia is discussed. Furthermore, potential risks and limitations of MRI for the evaluation of pneumonia in children are described.

Children's and adults' memory for emotional pictures: examining age-related patterns using the Developmental Affective Photo System.

PubMed

Cordon, Ingrid M; Melinder, Annika M D; Goodman, Gail S; Edelstein, Robin S

2013-02-01

Two studies were conducted to examine theoretical questions about children's and adults' memory for emotional visual stimuli. In Study 1, 7- to 9-year-olds and adults (N=172) participated in the initial creation of the Developmental Affective Photo System (DAPS). Ratings of emotional valence, arousal, and complexity were obtained. In Study 2, DAPS pictures were presented to 20 8- to 12-year-olds and 30 adults, followed by a recognition memory test. Children and adults recognized aversive images better than neutral images. Moreover, children and adults recognized high and moderate arousal images more accurately than low arousal images. Adults' memory for neutral images exceeded that of children, but there were no developmental differences in memory for aversive pictures. Theoretical and methodological implications are discussed. Copyright © 2012 Elsevier Inc. All rights reserved.

Uniform competency-based local feature extraction for remote sensing images

NASA Astrophysics Data System (ADS)

Sedaghat, Amin; Mohammadi, Nazila

2018-01-01

Local feature detectors are widely used in many photogrammetry and remote sensing applications. The quantity and distribution of the local features play a critical role in the quality of the image matching process, particularly for multi-sensor high resolution remote sensing image registration. However, conventional local feature detectors cannot extract desirable matched features either in terms of the number of correct matches or the spatial and scale distribution in multi-sensor remote sensing images. To address this problem, this paper proposes a novel method for uniform and robust local feature extraction for remote sensing images, which is based on a novel competency criterion and scale and location distribution constraints. The proposed method, called uniform competency (UC) local feature extraction, can be easily applied to any local feature detector for various kinds of applications. The proposed competency criterion is based on a weighted ranking process using three quality measures, including robustness, spatial saliency and scale parameters, which is performed in a multi-layer gridding schema. For evaluation, five state-of-the-art local feature detector approaches, namely, scale-invariant feature transform (SIFT), speeded up robust features (SURF), scale-invariant feature operator (SFOP), maximally stable extremal region (MSER) and hessian-affine, are used. The proposed UC-based feature extraction algorithms were successfully applied to match various synthetic and real satellite image pairs, and the results demonstrate its capability to increase matching performance and to improve the spatial distribution. The code to carry out the UC feature extraction is available from href="https://www.researchgate.net/publication/317956777_UC-Feature_Extraction.

Diabetic Rethinopathy Screening by Bright Lesions Extraction from Fundus Images

NASA Astrophysics Data System (ADS)

Hanđsková, Veronika; Pavlovičova, Jarmila; Oravec, Miloš; Blaško, Radoslav

2013-09-01

Retinal images are nowadays widely used to diagnose many diseases, for example diabetic retinopathy. In our work, we propose the algorithm for the screening application, which identifies the patients with such severe diabetic complication as diabetic retinopathy is, in early phase. In the application we use the patient's fundus photography without any additional examination by an ophtalmologist. After this screening identification, other examination methods should be considered and the patient's follow-up by a doctor is necessary. Our application is composed of three principal modules including fundus image preprocessing, feature extraction and feature classification. Image preprocessing module has the role of luminance normalization, contrast enhancement and optical disk masking. Feature extraction module includes two stages: bright lesions candidates localization and candidates feature extraction. We selected 16 statistical and structural features. For feature classification, we use multilayer perceptron (MLP) with one hidden layer. We classify images into two classes. Feature classification efficiency is about 93 percent.

SU-D-BRA-04: Computerized Framework for Marker-Less Localization of Anatomical Feature Points in Range Images Based On Differential Geometry Features for Image-Guided Radiation Therapy

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

Soufi, M; Arimura, H; Toyofuku, F

Purpose: To propose a computerized framework for localization of anatomical feature points on the patient surface in infrared-ray based range images by using differential geometry (curvature) features. Methods: The general concept was to reconstruct the patient surface by using a mathematical modeling technique for the computation of differential geometry features that characterize the local shapes of the patient surfaces. A region of interest (ROI) was firstly extracted based on a template matching technique applied on amplitude (grayscale) images. The extracted ROI was preprocessed for reducing temporal and spatial noises by using Kalman and bilateral filters, respectively. Next, a smooth patientmore » surface was reconstructed by using a non-uniform rational basis spline (NURBS) model. Finally, differential geometry features, i.e. the shape index and curvedness features were computed for localizing the anatomical feature points. The proposed framework was trained for optimizing shape index and curvedness thresholds and tested on range images of an anthropomorphic head phantom. The range images were acquired by an infrared ray-based time-of-flight (TOF) camera. The localization accuracy was evaluated by measuring the mean of minimum Euclidean distances (MMED) between reference (ground truth) points and the feature points localized by the proposed framework. The evaluation was performed for points localized on convex regions (e.g. apex of nose) and concave regions (e.g. nasofacial sulcus). Results: The proposed framework has localized anatomical feature points on convex and concave anatomical landmarks with MMEDs of 1.91±0.50 mm and 3.70±0.92 mm, respectively. A statistically significant difference was obtained between the feature points on the convex and concave regions (P<0.001). Conclusion: Our study has shown the feasibility of differential geometry features for localization of anatomical feature points on the patient surface in range images. The proposed framework might be useful for tasks involving feature-based image registration in range-image guided radiation therapy.« less

Target recognition of ladar range images using slice image: comparison of four improved algorithms

NASA Astrophysics Data System (ADS)

Xia, Wenze; Han, Shaokun; Cao, Jingya; Wang, Liang; Zhai, Yu; Cheng, Yang

2017-07-01

Compared with traditional 3-D shape data, ladar range images possess properties of strong noise, shape degeneracy, and sparsity, which make feature extraction and representation difficult. The slice image is an effective feature descriptor to resolve this problem. We propose four improved algorithms on target recognition of ladar range images using slice image. In order to improve resolution invariance of the slice image, mean value detection instead of maximum value detection is applied in these four improved algorithms. In order to improve rotation invariance of the slice image, three new improved feature descriptors-which are feature slice image, slice-Zernike moments, and slice-Fourier moments-are applied to the last three improved algorithms, respectively. Backpropagation neural networks are used as feature classifiers in the last two improved algorithms. The performance of these four improved recognition systems is analyzed comprehensively in the aspects of the three invariances, recognition rate, and execution time. The final experiment results show that the improvements for these four algorithms reach the desired effect, the three invariances of feature descriptors are not directly related to the final recognition performance of recognition systems, and these four improved recognition systems have different performances under different conditions.

Evaluation of Fourier transform coefficients for the diagnosis of rheumatoid arthritis from diffuse optical tomography images

NASA Astrophysics Data System (ADS)

Montejo, Ludguier D.; Jia, Jingfei; Kim, Hyun K.; Hielscher, Andreas H.

2013-03-01

We apply the Fourier Transform to absorption and scattering coefficient images of proximal interphalangeal (PIP) joints and evaluate the performance of these coefficients as classifiers using receiver operator characteristic (ROC) curve analysis. We find 25 features that yield a Youden index over 0.7, 3 features that yield a Youden index over 0.8, and 1 feature that yields a Youden index over 0.9 (90.0% sensitivity and 100% specificity). In general, scattering coefficient images yield better one-dimensional classifiers compared to absorption coefficient images. Using features derived from scattering coefficient images we obtain an average Youden index of 0.58 +/- 0.16, and an average Youden index of 0.45 +/- 0.15 when using features from absorption coefficient images.

Method for indexing and retrieving manufacturing-specific digital imagery based on image content

DOEpatents

Ferrell, Regina K.; Karnowski, Thomas P.; Tobin, Jr., Kenneth W.

2004-06-15

A method for indexing and retrieving manufacturing-specific digital images based on image content comprises three steps. First, at least one feature vector can be extracted from a manufacturing-specific digital image stored in an image database. In particular, each extracted feature vector corresponds to a particular characteristic of the manufacturing-specific digital image, for instance, a digital image modality and overall characteristic, a substrate/background characteristic, and an anomaly/defect characteristic. Notably, the extracting step includes generating a defect mask using a detection process. Second, using an unsupervised clustering method, each extracted feature vector can be indexed in a hierarchical search tree. Third, a manufacturing-specific digital image associated with a feature vector stored in the hierarchicial search tree can be retrieved, wherein the manufacturing-specific digital image has image content comparably related to the image content of the query image. More particularly, can include two data reductions, the first performed based upon a query vector extracted from a query image. Subsequently, a user can select relevant images resulting from the first data reduction. From the selection, a prototype vector can be calculated, from which a second-level data reduction can be performed. The second-level data reduction can result in a subset of feature vectors comparable to the prototype vector, and further comparable to the query vector. An additional fourth step can include managing the hierarchical search tree by substituting a vector average for several redundant feature vectors encapsulated by nodes in the hierarchical search tree.

Imaging Characteristics of Children with Auditory Neuropathy Spectrum Disorder

PubMed Central

Roche, Joseph P.; Huang, Benjamin Y.; Castillo, Mauricio; Bassim, Marc K.; Adunka, Oliver F.; Buchman, Craig A.

2013-01-01

Objective To identify and define the imaging characteristics of children with auditory neuropathy spectrum disorder (ANSD). Design Retrospective medical records review and analysis of both temporal bone computed tomography (CT) and magnetic resonance images (MRI) in from children with the diagnosis of ANSD. Setting Tertiary referral center. Patients 118 children with the electrophysiological characteristics of ANSD with available imaging studies for review. Interventions Two neuroradiologists and a neurotologist reviewed each study and consensus descriptions were established. Main outcome measures The type and number of imaging findings were tabulated. Results Sixty-eight (64%) MRIs revealed at least one imaging abnormality while selective use of CT identified 23 (55%) with anomalies. The most prevalent MRI findings included cochlear nerve deficiency (n=51; 28% of 183 nerves), brain abnormalities (n=42; 40% of 106 brains) and prominent temporal horns (n=33, 16% of 212 temporal lobes). The most prevalent CT finding from selective use of CT was cochlear dysplasia (n=13; 31%). Conclusions MRI will identify many abnormalities in children with ANSD that are not readily discernable on CT. Specifically, both developmental and acquired abnormalities of the brain, posterior cranial fossa, and cochlear nerves are not uncommonly seen in this patient population. Inner ear anomalies are well delineated using either imaging modality. Since many of the central nervous system findings identified in this study using MRI can alter the treatment and prognosis for these children, we believe that MRI should be the initial imaging study of choice for children with ANSD. PMID:20593543

Contour-based image warping

NASA Astrophysics Data System (ADS)

Chan, Kwai H.; Lau, Rynson W.

1996-09-01

Image warping concerns about transforming an image from one spatial coordinate to another. It is widely used for the vidual effect of deforming and morphing images in the film industry. A number of warping techniques have been introduced, which are mainly based on the corresponding pair mapping of feature points, feature vectors or feature patches (mostly triangular or quadrilateral). However, very often warping of an image object with an arbitrary shape is required. This requires a warping technique which is based on boundary contour instead of feature points or feature line-vectors. In addition, when feature point or feature vector based techniques are used, approximation of the object boundary by using point or vectors is required. In this case, the matching process of the corresponding pairs will be very time consuming if a fine approximation is required. In this paper, we propose a contour-based warping technique for warping image objects with arbitrary shapes. The novel idea of the new method is the introduction of mathematical morphology to allow a more flexible control of image warping. Two morphological operators are used as contour determinators. The erosion operator is used to warp image contents which are inside a user specified contour while the dilation operation is used to warp image contents which are outside of the contour. This new method is proposed to assist further development of a semi-automatic motion morphing system when accompanied with robust feature extractors such as deformable template or active contour model.

Multiview Locally Linear Embedding for Effective Medical Image Retrieval

PubMed Central

Shen, Hualei; Tao, Dacheng; Ma, Dianfu

2013-01-01

Content-based medical image retrieval continues to gain attention for its potential to assist radiological image interpretation and decision making. Many approaches have been proposed to improve the performance of medical image retrieval system, among which visual features such as SIFT, LBP, and intensity histogram play a critical role. Typically, these features are concatenated into a long vector to represent medical images, and thus traditional dimension reduction techniques such as locally linear embedding (LLE), principal component analysis (PCA), or laplacian eigenmaps (LE) can be employed to reduce the “curse of dimensionality”. Though these approaches show promising performance for medical image retrieval, the feature-concatenating method ignores the fact that different features have distinct physical meanings. In this paper, we propose a new method called multiview locally linear embedding (MLLE) for medical image retrieval. Following the patch alignment framework, MLLE preserves the geometric structure of the local patch in each feature space according to the LLE criterion. To explore complementary properties among a range of features, MLLE assigns different weights to local patches from different feature spaces. Finally, MLLE employs global coordinate alignment and alternating optimization techniques to learn a smooth low-dimensional embedding from different features. To justify the effectiveness of MLLE for medical image retrieval, we compare it with conventional spectral embedding methods. We conduct experiments on a subset of the IRMA medical image data set. Evaluation results show that MLLE outperforms state-of-the-art dimension reduction methods. PMID:24349277

A liver cirrhosis classification on B-mode ultrasound images by the use of higher order local autocorrelation features

NASA Astrophysics Data System (ADS)

Sasaki, Kenya; Mitani, Yoshihiro; Fujita, Yusuke; Hamamoto, Yoshihiko; Sakaida, Isao

2017-02-01

In this paper, in order to classify liver cirrhosis on regions of interest (ROIs) images from B-mode ultrasound images, we have proposed to use the higher order local autocorrelation (HLAC) features. In a previous study, we tried to classify liver cirrhosis by using a Gabor filter based approach. However, the classification performance of the Gabor feature was poor from our preliminary experimental results. In order accurately to classify liver cirrhosis, we examined to use the HLAC features for liver cirrhosis classification. The experimental results show the effectiveness of HLAC features compared with the Gabor feature. Furthermore, by using a binary image made by an adaptive thresholding method, the classification performance of HLAC features has improved.

Orientation Modeling for Amateur Cameras by Matching Image Line Features and Building Vector Data

NASA Astrophysics Data System (ADS)

Hung, C. H.; Chang, W. C.; Chen, L. C.

2016-06-01

With the popularity of geospatial applications, database updating is getting important due to the environmental changes over time. Imagery provides a lower cost and efficient way to update the database. Three dimensional objects can be measured by space intersection using conjugate image points and orientation parameters of cameras. However, precise orientation parameters of light amateur cameras are not always available due to their costliness and heaviness of precision GPS and IMU. To automatize data updating, the correspondence of object vector data and image may be built to improve the accuracy of direct georeferencing. This study contains four major parts, (1) back-projection of object vector data, (2) extraction of image feature lines, (3) object-image feature line matching, and (4) line-based orientation modeling. In order to construct the correspondence of features between an image and a building model, the building vector features were back-projected onto the image using the initial camera orientation from GPS and IMU. Image line features were extracted from the imagery. Afterwards, the matching procedure was done by assessing the similarity between the extracted image features and the back-projected ones. Then, the fourth part utilized line features in orientation modeling. The line-based orientation modeling was performed by the integration of line parametric equations into collinearity condition equations. The experiment data included images with 0.06 m resolution acquired by Canon EOS Mark 5D II camera on a Microdrones MD4-1000 UAV. Experimental results indicate that 2.1 pixel accuracy may be reached, which is equivalent to 0.12 m in the object space.

Quantitative radiomics studies for tissue characterization: a review of technology and methodological procedures.

PubMed

Larue, Ruben T H M; Defraene, Gilles; De Ruysscher, Dirk; Lambin, Philippe; van Elmpt, Wouter

2017-02-01

Quantitative analysis of tumour characteristics based on medical imaging is an emerging field of research. In recent years, quantitative imaging features derived from CT, positron emission tomography and MR scans were shown to be of added value in the prediction of outcome parameters in oncology, in what is called the radiomics field. However, results might be difficult to compare owing to a lack of standardized methodologies to conduct quantitative image analyses. In this review, we aim to present an overview of the current challenges, technical routines and protocols that are involved in quantitative imaging studies. The first issue that should be overcome is the dependency of several features on the scan acquisition and image reconstruction parameters. Adopting consistent methods in the subsequent target segmentation step is evenly crucial. To further establish robust quantitative image analyses, standardization or at least calibration of imaging features based on different feature extraction settings is required, especially for texture- and filter-based features. Several open-source and commercial software packages to perform feature extraction are currently available, all with slightly different functionalities, which makes benchmarking quite challenging. The number of imaging features calculated is typically larger than the number of patients studied, which emphasizes the importance of proper feature selection and prediction model-building routines to prevent overfitting. Even though many of these challenges still need to be addressed before quantitative imaging can be brought into daily clinical practice, radiomics is expected to be a critical component for the integration of image-derived information to personalize treatment in the future.

Classification of yeast cells from image features to evaluate pathogen conditions

NASA Astrophysics Data System (ADS)

van der Putten, Peter; Bertens, Laura; Liu, Jinshuo; Hagen, Ferry; Boekhout, Teun; Verbeek, Fons J.

2007-01-01

Morphometrics from images, image analysis, may reveal differences between classes of objects present in the images. We have performed an image-features-based classification for the pathogenic yeast Cryptococcus neoformans. Building and analyzing image collections from the yeast under different environmental or genetic conditions may help to diagnose a new "unseen" situation. Diagnosis here means that retrieval of the relevant information from the image collection is at hand each time a new "sample" is presented. The basidiomycetous yeast Cryptococcus neoformans can cause infections such as meningitis or pneumonia. The presence of an extra-cellular capsule is known to be related to virulence. This paper reports on the approach towards developing classifiers for detecting potentially more or less virulent cells in a sample, i.e. an image, by using a range of features derived from the shape or density distribution. The classifier can henceforth be used for automating screening and annotating existing image collections. In addition we will present our methods for creating samples, collecting images, image preprocessing, identifying "yeast cells" and creating feature extraction from the images. We compare various expertise based and fully automated methods of feature selection and benchmark a range of classification algorithms and illustrate successful application to this particular domain.

Speech feature discrimination in deaf children following cochlear implantation

NASA Astrophysics Data System (ADS)

Bergeson, Tonya R.; Pisoni, David B.; Kirk, Karen Iler

2002-05-01

Speech feature discrimination is a fundamental perceptual skill that is often assumed to underlie word recognition and sentence comprehension performance. To investigate the development of speech feature discrimination in deaf children with cochlear implants, we conducted a retrospective analysis of results from the Minimal Pairs Test (Robbins et al., 1988) selected from patients enrolled in a longitudinal study of speech perception and language development. The MP test uses a 2AFC procedure in which children hear a word and select one of two pictures (bat-pat). All 43 children were prelingually deafened, received a cochlear implant before 6 years of age or between ages 6 and 9, and used either oral or total communication. Children were tested once every 6 months to 1 year for 7 years; not all children were tested at each interval. By 2 years postimplant, the majority of these children achieved near-ceiling levels of discrimination performance for vowel height, vowel place, and consonant manner. Most of the children also achieved plateaus but did not reach ceiling performance for consonant place and voicing. The relationship between speech feature discrimination, spoken word recognition, and sentence comprehension will be discussed. [Work supported by NIH/NIDCD Research Grant No. R01DC00064 and NIH/NIDCD Training Grant No. T32DC00012.

Study of Automatic Image Rectification and Registration of Scanned Historical Aerial Photographs

NASA Astrophysics Data System (ADS)

Chen, H. R.; Tseng, Y. H.

2016-06-01

Historical aerial photographs directly provide good evidences of past times. The Research Center for Humanities and Social Sciences (RCHSS) of Taiwan Academia Sinica has collected and scanned numerous historical maps and aerial images of Taiwan and China. Some maps or images have been geo-referenced manually, but most of historical aerial images have not been registered since there are no GPS or IMU data for orientation assisting in the past. In our research, we developed an automatic process of matching historical aerial images by SIFT (Scale Invariant Feature Transform) for handling the great quantity of images by computer vision. SIFT is one of the most popular method of image feature extracting and matching. This algorithm extracts extreme values in scale space into invariant image features, which are robust to changing in rotation scale, noise, and illumination. We also use RANSAC (Random sample consensus) to remove outliers, and obtain good conjugated points between photographs. Finally, we manually add control points for registration through least square adjustment based on collinear equation. In the future, we can use image feature points of more photographs to build control image database. Every new image will be treated as query image. If feature points of query image match the features in database, it means that the query image probably is overlapped with control images.With the updating of database, more and more query image can be matched and aligned automatically. Other research about multi-time period environmental changes can be investigated with those geo-referenced temporal spatial data.

Computer Presentational Features for Young Children's Preferential Selection and Recall of Information.

ERIC Educational Resources Information Center

Calvert, Sandra L.; And Others

The purpose of this study was to examine the impact of visual and auditory presentational features on young children's selection and memory for verbally presented content. Assessed as a function of action and sound were preschool children's preferential selection and recall of words presented in a computer microworld. A computer microworld…

Speak Out for Children. Winter 1995 through Summer 1995.

ERIC Educational Resources Information Center

Levy, David L., Ed.

1995-01-01

These three newsletter issues, published by the Children's Rights Council (CRC), are concerned with the healthy development of children of divorced and separated parents. Feature articles in issue number 1 of this volume are: (1) "Commission to Focus on Custody/Access"; and (2) "Congress to Move on Welfare Reform." Feature articles in issue number…

Children's Performance in Mental Rotation Tasks: Orientation-Free Features Flatten the Slope

ERIC Educational Resources Information Center

Perrucci, Vittore; Agnoli, Franca; Albiero, Paolo

2008-01-01

Studies of the development of mental rotation have yielded conflicting results, apparently because different mental rotation tasks draw on different cognitive abilities. Children may compare two stimuli at different orientations without mental rotation if the stimuli contain orientation-free features. Two groups of children (78 6-year-olds and 92…

How Children Use Examples to Make Conditional Predictions

ERIC Educational Resources Information Center

Kalish, Charles W.

2010-01-01

Two experiments explored children's and adults' use of examples to make conditional predictions. In Experiment 1 adults (N = 20) but not 4-year-olds (N = 21) or 8-year-olds (N =1 8) distinguished predictable from unpredictable features when features were partially correlated (e.g., necessary but not sufficient). Children did make reliable…

Children's Narrative Structure: How Do Japanese Children Talk About Their Own Stories?

ERIC Educational Resources Information Center

Minami, Masahiko

The conversational narratives of 17 Japanese children aged 5 to 9 were analyzed using stanza analysis. Three distinctive features emerged: (1) the narratives are exceptionally succinct; (2) they are usually free-standing collections of three experiences; and (3) stanzas almost always consist of three lines. These features reflect the basic…

Can radiomics features be reproducibly measured from CBCT images for patients with non-small cell lung cancer?

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

Fave, Xenia, E-mail: xjfave@mdanderson.org; Fried, David; Mackin, Dennis

Purpose: Increasing evidence suggests radiomics features extracted from computed tomography (CT) images may be useful in prognostic models for patients with nonsmall cell lung cancer (NSCLC). This study was designed to determine whether such features can be reproducibly obtained from cone-beam CT (CBCT) images taken using medical Linac onboard-imaging systems in order to track them through treatment. Methods: Test-retest CBCT images of ten patients previously enrolled in a clinical trial were retrospectively obtained and used to determine the concordance correlation coefficient (CCC) for 68 different texture features. The volume dependence of each feature was also measured using the Spearman rankmore » correlation coefficient. Features with a high reproducibility (CCC > 0.9) that were not due to volume dependence in the patient test-retest set were further examined for their sensitivity to differences in imaging protocol, level of scatter, and amount of motion by using two phantoms. The first phantom was a texture phantom composed of rectangular cartridges to represent different textures. Features were measured from two cartridges, shredded rubber and dense cork, in this study. The texture phantom was scanned with 19 different CBCT imagers to establish the features’ interscanner variability. The effect of scatter on these features was studied by surrounding the same texture phantom with scattering material (rice and solid water). The effect of respiratory motion on these features was studied using a dynamic-motion thoracic phantom and a specially designed tumor texture insert of the shredded rubber material. The differences between scans acquired with different Linacs and protocols, varying amounts of scatter, and with different levels of motion were compared to the mean intrapatient difference from the test-retest image set. Results: Of the original 68 features, 37 had a CCC >0.9 that was not due to volume dependence. When the Linac manufacturer and imaging protocol were kept consistent, 4–13 of these 37 features passed our criteria for reproducibility more than 50% of the time, depending on the manufacturer-protocol combination. Almost all of the features changed substantially when scatter material was added around the phantom. For the dense cork, 23 features passed in the thoracic scans and 11 features passed in the head scans when the differences between one and two layers of scatter were compared. Using the same test for the shredded rubber, five features passed the thoracic scans and eight features passed the head scans. Motion substantially impacted the reproducibility of the features. With 4 mm of motion, 12 features from the entire volume and 14 features from the center slice measurements were reproducible. With 6–8 mm of motion, three features (Laplacian of Gaussian filtered kurtosis, gray-level nonuniformity, and entropy), from the entire volume and seven features (coarseness, high gray-level run emphasis, gray-level nonuniformity, sum-average, information measure correlation, scaled mean, and entropy) from the center-slice measurements were considered reproducible. Conclusions: Some radiomics features are robust to the noise and poor image quality of CBCT images when the imaging protocol is consistent, relative changes in the features are used, and patients are limited to those with less than 1 cm of motion.« less

Why are dunkels sticky? Preschoolers infer functionality and intentional creation for artifact properties learned from generic language.

PubMed

Cimpian, Andrei; Cadena, Cristina

2010-10-01

Artifacts pose a potential learning problem for children because the mapping between their features and their functions is often not transparent. In solving this problem, children are likely to rely on a number of information sources (e.g., others' actions, affordances). We argue that children's sensitivity to nuances in the language used to describe artifacts is an important, but so far unacknowledged, piece of this puzzle. Specifically, we hypothesize that children are sensitive to whether an unfamiliar artifact's features are highlighted using generic (e.g., "Dunkels are sticky") or non-generic (e.g., "This dunkel is sticky") language. Across two studies, older-but not younger-preschoolers who heard such features introduced via generic statements inferred that they are a functional part of the artifact's design more often than children who heard the same features introduced via non-generic statements. The ability to pick up on this linguistic cue may expand considerably the amount of conceptual information about artifacts that children derive from conversations with adults. Copyright 2010 Elsevier B.V. All rights reserved.

Cone Beam Computed Tomographic imaging in orthodontics.

PubMed

Scarfe, W C; Azevedo, B; Toghyani, S; Farman, A G

2017-03-01

Over the last 15 years, cone beam computed tomographic (CBCT) imaging has emerged as an important supplemental radiographic technique for orthodontic diagnosis and treatment planning, especially in situations which require an understanding of the complex anatomic relationships and surrounding structures of the maxillofacial skeleton. CBCT imaging provides unique features and advantages to enhance orthodontic practice over conventional extraoral radiographic imaging. While it is the responsibility of each practitioner to make a decision, in tandem with the patient/family, consensus-derived, evidence-based clinical guidelines are available to assist the clinician in the decision-making process. Specific recommendations provide selection guidance based on variables such as phase of treatment, clinically-assessed treatment difficulty, the presence of dental and/or skeletal modifying conditions, and pathology. CBCT imaging in orthodontics should always be considered wisely as children have conservatively, on average, a three to five times greater radiation risk compared with adults for the same exposure. The purpose of this paper is to provide an understanding of the operation of CBCT equipment as it relates to image quality and dose, highlight the benefits of the technique in orthodontic practice, and provide guidance on appropriate clinical use with respect to radiation dose and relative risk, particularly for the paediatric patient. © 2017 Australian Dental Association.

Age-related interference from irrelevant distracters in visual feature search among heterogeneous distracters.

PubMed

Merrill, Edward C; Conners, Frances A

2013-08-01

We evaluated age-related variations in the influence of heterogeneous distracters during feature target. Participants in three age groups-6-year-old children, 9-year-old children, and young adults-completed three conditions of search. In a singleton search condition, participants searched for a circle among squares of the same color. In two feature mode search conditions, participants searched for a gray circle or a black circle among gray and black squares. Singleton search was performed at the same level of efficiency for all age groups. In contrast, the two feature mode search conditions yielded age-related performance differences in both conditions. Younger children exhibited a steeper slope than young adults when searching for a gray or black circle. Older children exhibited a steeper slope than young adults when searching for a gray circle but not when searching for a black circle. We concluded that these differences revealed age-related improvements in the relative abilities of adults and children to execute attentional control processes during visual search. In particular, it appears that children found it more difficult to maintain the goal of searching for a circle target than adults and were distracted by the presence of the irrelevant feature dimension of color. Published by Elsevier Inc.

Automatic brain MR image denoising based on texture feature-based artificial neural networks.

PubMed

Chang, Yu-Ning; Chang, Herng-Hua

2015-01-01

Noise is one of the main sources of quality deterioration not only for visual inspection but also in computerized processing in brain magnetic resonance (MR) image analysis such as tissue classification, segmentation and registration. Accordingly, noise removal in brain MR images is important for a wide variety of subsequent processing applications. However, most existing denoising algorithms require laborious tuning of parameters that are often sensitive to specific image features and textures. Automation of these parameters through artificial intelligence techniques will be highly beneficial. In the present study, an artificial neural network associated with image texture feature analysis is proposed to establish a predictable parameter model and automate the denoising procedure. In the proposed approach, a total of 83 image attributes were extracted based on four categories: 1) Basic image statistics. 2) Gray-level co-occurrence matrix (GLCM). 3) Gray-level run-length matrix (GLRLM) and 4) Tamura texture features. To obtain the ranking of discrimination in these texture features, a paired-samples t-test was applied to each individual image feature computed in every image. Subsequently, the sequential forward selection (SFS) method was used to select the best texture features according to the ranking of discrimination. The selected optimal features were further incorporated into a back propagation neural network to establish a predictable parameter model. A wide variety of MR images with various scenarios were adopted to evaluate the performance of the proposed framework. Experimental results indicated that this new automation system accurately predicted the bilateral filtering parameters and effectively removed the noise in a number of MR images. Comparing to the manually tuned filtering process, our approach not only produced better denoised results but also saved significant processing time.

Non-rigid registration of 3D ultrasound for neurosurgery using automatic feature detection and matching.

PubMed

Machado, Inês; Toews, Matthew; Luo, Jie; Unadkat, Prashin; Essayed, Walid; George, Elizabeth; Teodoro, Pedro; Carvalho, Herculano; Martins, Jorge; Golland, Polina; Pieper, Steve; Frisken, Sarah; Golby, Alexandra; Wells, William

2018-06-04

The brain undergoes significant structural change over the course of neurosurgery, including highly nonlinear deformation and resection. It can be informative to recover the spatial mapping between structures identified in preoperative surgical planning and the intraoperative state of the brain. We present a novel feature-based method for achieving robust, fully automatic deformable registration of intraoperative neurosurgical ultrasound images. A sparse set of local image feature correspondences is first estimated between ultrasound image pairs, after which rigid, affine and thin-plate spline models are used to estimate dense mappings throughout the image. Correspondences are derived from 3D features, distinctive generic image patterns that are automatically extracted from 3D ultrasound images and characterized in terms of their geometry (i.e., location, scale, and orientation) and a descriptor of local image appearance. Feature correspondences between ultrasound images are achieved based on a nearest-neighbor descriptor matching and probabilistic voting model similar to the Hough transform. Experiments demonstrate our method on intraoperative ultrasound images acquired before and after opening of the dura mater, during resection and after resection in nine clinical cases. A total of 1620 automatically extracted 3D feature correspondences were manually validated by eleven experts and used to guide the registration. Then, using manually labeled corresponding landmarks in the pre- and post-resection ultrasound images, we show that our feature-based registration reduces the mean target registration error from an initial value of 3.3 to 1.5 mm. This result demonstrates that the 3D features promise to offer a robust and accurate solution for 3D ultrasound registration and to correct for brain shift in image-guided neurosurgery.

Stability of deep features across CT scanners and field of view using a physical phantom

NASA Astrophysics Data System (ADS)

Paul, Rahul; Shafiq-ul-Hassan, Muhammad; Moros, Eduardo G.; Gillies, Robert J.; Hall, Lawrence O.; Goldgof, Dmitry B.

2018-02-01

Radiomics is the process of analyzing radiological images by extracting quantitative features for monitoring and diagnosis of various cancers. Analyzing images acquired from different medical centers is confounded by many choices in acquisition, reconstruction parameters and differences among device manufacturers. Consequently, scanning the same patient or phantom using various acquisition/reconstruction parameters as well as different scanners may result in different feature values. To further evaluate this issue, in this study, CT images from a physical radiomic phantom were used. Recent studies showed that some quantitative features were dependent on voxel size and that this dependency could be reduced or removed by the appropriate normalization factor. Deep features extracted from a convolutional neural network, may also provide additional features for image analysis. Using a transfer learning approach, we obtained deep features from three convolutional neural networks pre-trained on color camera images. An we examination of the dependency of deep features on image pixel size was done. We found that some deep features were pixel size dependent, and to remove this dependency we proposed two effective normalization approaches. For analyzing the effects of normalization, a threshold has been used based on the calculated standard deviation and average distance from a best fit horizontal line among the features' underlying pixel size before and after normalization. The inter and intra scanner dependency of deep features has also been evaluated.

Automatic Image Registration of Multimodal Remotely Sensed Data with Global Shearlet Features

NASA Technical Reports Server (NTRS)

Murphy, James M.; Le Moigne, Jacqueline; Harding, David J.

2015-01-01

Automatic image registration is the process of aligning two or more images of approximately the same scene with minimal human assistance. Wavelet-based automatic registration methods are standard, but sometimes are not robust to the choice of initial conditions. That is, if the images to be registered are too far apart relative to the initial guess of the algorithm, the registration algorithm does not converge or has poor accuracy, and is thus not robust. These problems occur because wavelet techniques primarily identify isotropic textural features and are less effective at identifying linear and curvilinear edge features. We integrate the recently developed mathematical construction of shearlets, which is more effective at identifying sparse anisotropic edges, with an existing automatic wavelet-based registration algorithm. Our shearlet features algorithm produces more distinct features than wavelet features algorithms; the separation of edges from textures is even stronger than with wavelets. Our algorithm computes shearlet and wavelet features for the images to be registered, then performs least squares minimization on these features to compute a registration transformation. Our algorithm is two-staged and multiresolution in nature. First, a cascade of shearlet features is used to provide a robust, though approximate, registration. This is then refined by registering with a cascade of wavelet features. Experiments across a variety of image classes show an improved robustness to initial conditions, when compared to wavelet features alone.

Automatic Image Registration of Multi-Modal Remotely Sensed Data with Global Shearlet Features

PubMed Central

Murphy, James M.; Le Moigne, Jacqueline; Harding, David J.

2017-01-01

Automatic image registration is the process of aligning two or more images of approximately the same scene with minimal human assistance. Wavelet-based automatic registration methods are standard, but sometimes are not robust to the choice of initial conditions. That is, if the images to be registered are too far apart relative to the initial guess of the algorithm, the registration algorithm does not converge or has poor accuracy, and is thus not robust. These problems occur because wavelet techniques primarily identify isotropic textural features and are less effective at identifying linear and curvilinear edge features. We integrate the recently developed mathematical construction of shearlets, which is more effective at identifying sparse anisotropic edges, with an existing automatic wavelet-based registration algorithm. Our shearlet features algorithm produces more distinct features than wavelet features algorithms; the separation of edges from textures is even stronger than with wavelets. Our algorithm computes shearlet and wavelet features for the images to be registered, then performs least squares minimization on these features to compute a registration transformation. Our algorithm is two-staged and multiresolution in nature. First, a cascade of shearlet features is used to provide a robust, though approximate, registration. This is then refined by registering with a cascade of wavelet features. Experiments across a variety of image classes show an improved robustness to initial conditions, when compared to wavelet features alone. PMID:29123329

SU-D-BRA-07: A Phantom Study to Assess the Variability in Radiomics Features Extracted From Cone-Beam CT Images

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

Fave, X; Fried, D; UT Health Science Center Graduate School of Biomedical Sciences, Houston, TX

2015-06-15

Purpose: Several studies have demonstrated the prognostic potential for texture features extracted from CT images of non-small cell lung cancer (NSCLC) patients. The purpose of this study was to determine if these features could be extracted with high reproducibility from cone-beam CT (CBCT) images in order for features to be easily tracked throughout a patient’s treatment. Methods: Two materials in a radiomics phantom, designed to approximate NSCLC tumor texture, were used to assess the reproducibility of 26 features. This phantom was imaged on 9 CBCT scanners, including Elekta and Varian machines. Thoracic and head imaging protocols were acquired on eachmore » machine. CBCT images from 27 NSCLC patients imaged using the thoracic protocol on Varian machines were obtained for comparison. The variance for each texture measured from these patients was compared to the variance in phantom values for different manufacturer/protocol subsets. Levene’s test was used to identify features which had a significantly smaller variance in the phantom scans versus the patient data. Results: Approximately half of the features (13/26 for material1 and 15/26 for material2) had a significantly smaller variance (p<0.05) between Varian thoracic scans of the phantom compared to patient scans. Many of these same features remained significant for the head scans on Varian (12/26 and 8/26). However, when thoracic scans from Elekta and Varian were combined, only a few features were still significant (4/26 and 5/26). Three features (skewness, coarsely filtered mean and standard deviation) were significant in almost all manufacturer/protocol subsets. Conclusion: Texture features extracted from CBCT images of a radiomics phantom are reproducible and show significantly less variation than the same features measured from patient images when images from the same manufacturer or with similar parameters are used. Reproducibility between CBCT scanners may be high enough to allow the extraction of meaningful texture values for patients. This project was funded in part by the Cancer Prevention Research Institute of Texas (CPRIT). Xenia Fave is a recipient of the American Association of Physicists in Medicine Graduate Fellowship.« less

Prediction of cognitive and motor development in preterm children using exhaustive feature selection and cross-validation of near-term white matter microstructure.

PubMed

Schadl, Kornél; Vassar, Rachel; Cahill-Rowley, Katelyn; Yeom, Kristin W; Stevenson, David K; Rose, Jessica

2018-01-01

Advanced neuroimaging and computational methods offer opportunities for more accurate prognosis. We hypothesized that near-term regional white matter (WM) microstructure, assessed on diffusion tensor imaging (DTI), using exhaustive feature selection with cross-validation would predict neurodevelopment in preterm children. Near-term MRI and DTI obtained at 36.6 ± 1.8 weeks postmenstrual age in 66 very-low-birth-weight preterm neonates were assessed. 60/66 had follow-up neurodevelopmental evaluation with Bayley Scales of Infant-Toddler Development, 3rd-edition (BSID-III) at 18-22 months. Linear models with exhaustive feature selection and leave-one-out cross-validation computed based on DTI identified sets of three brain regions most predictive of cognitive and motor function; logistic regression models were computed to classify high-risk infants scoring one standard deviation below mean. Cognitive impairment was predicted (100% sensitivity, 100% specificity; AUC = 1) by near-term right middle-temporal gyrus MD, right cingulate-cingulum MD, left caudate MD. Motor impairment was predicted (90% sensitivity, 86% specificity; AUC = 0.912) by left precuneus FA, right superior occipital gyrus MD, right hippocampus FA. Cognitive score variance was explained (29.6%, cross-validated Rˆ2 = 0.296) by left posterior-limb-of-internal-capsule MD, Genu RD, right fusiform gyrus AD. Motor score variance was explained (31.7%, cross-validated Rˆ2 = 0.317) by left posterior-limb-of-internal-capsule MD, right parahippocampal gyrus AD, right middle-temporal gyrus AD. Search in large DTI feature space more accurately identified neonatal neuroimaging correlates of neurodevelopment.

WE-E-17A-02: Predictive Modeling of Outcome Following SABR for NSCLC Based On Radiomics of FDG-PET Images

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

Li, R; Aguilera, T; Shultz, D

2014-06-15

Purpose: This study aims to develop predictive models of patient outcome by extracting advanced imaging features (i.e., Radiomics) from FDG-PET images. Methods: We acquired pre-treatment PET scans for 51 stage I NSCLC patients treated with SABR. We calculated 139 quantitative features from each patient PET image, including 5 morphological features, 8 statistical features, 27 texture features, and 100 features from the intensity-volume histogram. Based on the imaging features, we aim to distinguish between 2 risk groups of patients: those with regional failure or distant metastasis versus those without. We investigated 3 pattern classification algorithms: linear discriminant analysis (LDA), naive Bayesmore » (NB), and logistic regression (LR). To avoid the curse of dimensionality, we performed feature selection by first removing redundant features and then applying sequential forward selection using the wrapper approach. To evaluate the predictive performance, we performed 10-fold cross validation with 1000 random splits of the data and calculated the area under the ROC curve (AUC). Results: Feature selection identified 2 texture features (homogeneity and/or wavelet decompositions) for NB and LR, while for LDA SUVmax and one texture feature (correlation) were identified. All 3 classifiers achieved statistically significant improvements over conventional PET imaging metrics such as tumor volume (AUC = 0.668) and SUVmax (AUC = 0.737). Overall, NB achieved the best predictive performance (AUC = 0.806). This also compares favorably with MTV using the best threshold at an SUV of 11.6 (AUC = 0.746). At a sensitivity of 80%, NB achieved 69% specificity, while SUVmax and tumor volume only had 36% and 47% specificity. Conclusion: Through a systematic analysis of advanced PET imaging features, we are able to build models with improved predictive value over conventional imaging metrics. If validated in a large independent cohort, the proposed techniques could potentially aid in identifying patients who might benefit from adjuvant therapy.« less

3D Texture Features Mining for MRI Brain Tumor Identification

NASA Astrophysics Data System (ADS)

Rahim, Mohd Shafry Mohd; Saba, Tanzila; Nayer, Fatima; Syed, Afraz Zahra

2014-03-01

Medical image segmentation is a process to extract region of interest and to divide an image into its individual meaningful, homogeneous components. Actually, these components will have a strong relationship with the objects of interest in an image. For computer-aided diagnosis and therapy process, medical image segmentation is an initial mandatory step. Medical image segmentation is a sophisticated and challenging task because of the sophisticated nature of the medical images. Indeed, successful medical image analysis heavily dependent on the segmentation accuracy. Texture is one of the major features to identify region of interests in an image or to classify an object. 2D textures features yields poor classification results. Hence, this paper represents 3D features extraction using texture analysis and SVM as segmentation technique in the testing methodologies.

Haralick texture features from apparent diffusion coefficient (ADC) MRI images depend on imaging and pre-processing parameters.

PubMed

Brynolfsson, Patrik; Nilsson, David; Torheim, Turid; Asklund, Thomas; Karlsson, Camilla Thellenberg; Trygg, Johan; Nyholm, Tufve; Garpebring, Anders

2017-06-22

In recent years, texture analysis of medical images has become increasingly popular in studies investigating diagnosis, classification and treatment response assessment of cancerous disease. Despite numerous applications in oncology and medical imaging in general, there is no consensus regarding texture analysis workflow, or reporting of parameter settings crucial for replication of results. The aim of this study was to assess how sensitive Haralick texture features of apparent diffusion coefficient (ADC) MR images are to changes in five parameters related to image acquisition and pre-processing: noise, resolution, how the ADC map is constructed, the choice of quantization method, and the number of gray levels in the quantized image. We found that noise, resolution, choice of quantization method and the number of gray levels in the quantized images had a significant influence on most texture features, and that the effect size varied between different features. Different methods for constructing the ADC maps did not have an impact on any texture feature. Based on our results, we recommend using images with similar resolutions and noise levels, using one quantization method, and the same number of gray levels in all quantized images, to make meaningful comparisons of texture feature results between different subjects.

Texture Feature Analysis for Different Resolution Level of Kidney Ultrasound Images

NASA Astrophysics Data System (ADS)

Kairuddin, Wan Nur Hafsha Wan; Mahmud, Wan Mahani Hafizah Wan

2017-08-01

Image feature extraction is a technique to identify the characteristic of the image. The objective of this work is to discover the texture features that best describe a tissue characteristic of a healthy kidney from ultrasound (US) image. Three ultrasound machines that have different specifications are used in order to get a different quality (different resolution) of the image. Initially, the acquired images are pre-processed to de-noise the speckle to ensure the image preserve the pixels in a region of interest (ROI) for further extraction. Gaussian Low- pass Filter is chosen as the filtering method in this work. 150 of enhanced images then are segmented by creating a foreground and background of image where the mask is created to eliminate some unwanted intensity values. Statistical based texture features method is used namely Intensity Histogram (IH), Gray-Level Co-Occurance Matrix (GLCM) and Gray-level run-length matrix (GLRLM).This method is depends on the spatial distribution of intensity values or gray levels in the kidney region. By using One-Way ANOVA in SPSS, the result indicated that three features (Contrast, Difference Variance and Inverse Difference Moment Normalized) from GLCM are not statistically significant; this concludes that these three features describe a healthy kidney characteristics regardless of the ultrasound image quality.

Freezing effect on bread appearance evaluated by digital imaging

NASA Astrophysics Data System (ADS)

Zayas, Inna Y.

1999-01-01

In marketing channels, bread is sometimes delivered in a frozen sate for distribution. Changes occur in physical dimensions, crumb grain and appearance of slices. Ten loaves, twelve bread slices per loaf were scanned for digital image analysis and then frozen in a commercial refrigerator. The bread slices were stored for four weeks scanned again, permitted to thaw and scanned a third time. Image features were extracted, to determine shape, size and image texture of the slices. Different thresholds of grey levels were set to detect changes that occurred in crumb, images were binarized at these settings. The number of pixels falling into these gray level settings were determined for each slice. Image texture features of subimages of each slice were calculated to quantify slice crumb grain. The image features of the slice size showed shrinking of bread slices, as a results of freezing and storage, although shape of slices did not change markedly. Visible crumb texture changes occurred and these changes were depicted by changes in image texture features. Image texture features showed that slice crumb changed differently at the center of a slice compared to a peripheral area close to the crust. Image texture and slice features were sufficient for discrimination of slices before and after freezing and after thawing.

Multiclass Classification for the Differential Diagnosis on the ADHD Subtypes Using Recursive Feature Elimination and Hierarchical Extreme Learning Machine: Structural MRI Study

PubMed Central

Qureshi, Muhammad Naveed Iqbal; Min, Beomjun; Jo, Hang Joon; Lee, Boreom

2016-01-01

The classification of neuroimaging data for the diagnosis of certain brain diseases is one of the main research goals of the neuroscience and clinical communities. In this study, we performed multiclass classification using a hierarchical extreme learning machine (H-ELM) classifier. We compared the performance of this classifier with that of a support vector machine (SVM) and basic extreme learning machine (ELM) for cortical MRI data from attention deficit/hyperactivity disorder (ADHD) patients. We used 159 structural MRI images of children from the publicly available ADHD-200 MRI dataset. The data consisted of three types, namely, typically developing (TDC), ADHD-inattentive (ADHD-I), and ADHD-combined (ADHD-C). We carried out feature selection by using standard SVM-based recursive feature elimination (RFE-SVM) that enabled us to achieve good classification accuracy (60.78%). In this study, we found the RFE-SVM feature selection approach in combination with H-ELM to effectively enable the acquisition of high multiclass classification accuracy rates for structural neuroimaging data. In addition, we found that the most important features for classification were the surface area of the superior frontal lobe, and the cortical thickness, volume, and mean surface area of the whole cortex. PMID:27500640

Multiclass Classification for the Differential Diagnosis on the ADHD Subtypes Using Recursive Feature Elimination and Hierarchical Extreme Learning Machine: Structural MRI Study.

PubMed

Qureshi, Muhammad Naveed Iqbal; Min, Beomjun; Jo, Hang Joon; Lee, Boreom

2016-01-01

The classification of neuroimaging data for the diagnosis of certain brain diseases is one of the main research goals of the neuroscience and clinical communities. In this study, we performed multiclass classification using a hierarchical extreme learning machine (H-ELM) classifier. We compared the performance of this classifier with that of a support vector machine (SVM) and basic extreme learning machine (ELM) for cortical MRI data from attention deficit/hyperactivity disorder (ADHD) patients. We used 159 structural MRI images of children from the publicly available ADHD-200 MRI dataset. The data consisted of three types, namely, typically developing (TDC), ADHD-inattentive (ADHD-I), and ADHD-combined (ADHD-C). We carried out feature selection by using standard SVM-based recursive feature elimination (RFE-SVM) that enabled us to achieve good classification accuracy (60.78%). In this study, we found the RFE-SVM feature selection approach in combination with H-ELM to effectively enable the acquisition of high multiclass classification accuracy rates for structural neuroimaging data. In addition, we found that the most important features for classification were the surface area of the superior frontal lobe, and the cortical thickness, volume, and mean surface area of the whole cortex.

A novel image registration approach via combining local features and geometric invariants

PubMed Central

Lu, Yan; Gao, Kun; Zhang, Tinghua; Xu, Tingfa

2018-01-01

Image registration is widely used in many fields, but the adaptability of the existing methods is limited. This work proposes a novel image registration method with high precision for various complex applications. In this framework, the registration problem is divided into two stages. First, we detect and describe scale-invariant feature points using modified computer vision-oriented fast and rotated brief (ORB) algorithm, and a simple method to increase the performance of feature points matching is proposed. Second, we develop a new local constraint of rough selection according to the feature distances. Evidence shows that the existing matching techniques based on image features are insufficient for the images with sparse image details. Then, we propose a novel matching algorithm via geometric constraints, and establish local feature descriptions based on geometric invariances for the selected feature points. Subsequently, a new price function is constructed to evaluate the similarities between points and obtain exact matching pairs. Finally, we employ the progressive sample consensus method to remove wrong matches and calculate the space transform parameters. Experimental results on various complex image datasets verify that the proposed method is more robust and significantly reduces the rate of false matches while retaining more high-quality feature points. PMID:29293595

Prevalence and prognostic value of echocardiographic screening for rheumatic heart disease

PubMed Central

Kotit, Susy; Said, Karim; ElFaramawy, Amr; Mahmoud, Hani; Phillips, David I W; Yacoub, Magdi H

2017-01-01

Objective Rheumatic heart disease (RHD) remains a major health problem in many low-income and middle-income countries. The use of echocardiographic imaging suggests that subclinical disease is far more widespread than previously appreciated, but little is known as to how these mild forms of RHD progress. We have determined the prevalence of subclinical RHD in a large group of schoolchildren in Aswan, Egypt and have evaluated its subsequent progression. Methods Echocardiographic screening was performed on 3062 randomly selected schoolchildren, aged 5–15 years, in Aswan, Egypt. Follow-up of children with a definite or borderline diagnosis of RHD was carried out 48–60 months later to determine how the valvular abnormalities altered and to evaluate the factors influencing progression. Results Sixty children were initially diagnosed with definite RHD (19.6 per 1000 children) and 35 with borderline disease (11.4 per 1000); most had mitral valve disease. Of the 72 children followed up progression was documented in 14 children (19.4%) and regression in 30 (41.7%) children. Boys had lower rates of progression while older children had lower rates of regression. Functional defects of the valve even in the presence of structural features were associated with lower rates of progression and higher rates of regression than structural changes. Conclusions RHD has a high prevalence in Egypt. Although a high proportion of the abnormalities originally detected persisted at follow-up, both progression and regression of valve lesions were demonstrated. PMID:29344370

Modeling Face Identification Processing in Children and Adults.

ERIC Educational Resources Information Center

Schwarzer, Gudrun; Massaro, Dominic W.

2001-01-01

Two experiments studied whether and how 5-year-olds integrate single facial features to identify faces. Results indicated that children could evaluate and integrate information from eye and mouth features to identify a face when salience of features was varied. A weighted Fuzzy Logical Model of Perception fit better than a Single Channel Model,…

Stickler Syndrome

MedlinePlus

... Children who have Stickler syndrome often have distinctive facial features — prominent eyes, a small nose with a scooped ... develop ear infections than are children with normal facial features. Deafness. Hearing loss may worsen with time and ...

Playground usage and physical activity levels of children based on playground spatial features.

PubMed

Reimers, Anne K; Knapp, Guido

2017-01-01

Being outdoors is one of the strongest correlates of physical activity in children. Playgrounds are spaces especially designed to enable and foster physical activity in children. This study aimed to analyze the relationship between the spatial features of public playgrounds and the usage and physical activity levels of children playing in them. A quantitative, observational study was conducted of ten playgrounds in one district of a middle-sized town in Germany. Playground spatial features were captured using an audit instrument and the playground manual of the town. Playground usage and physical activity levels of children were assessed using a modified version of the System for Observing Play and Leisure Activity in Youth. Negative binomial models were used to analyze the count data. The number of children using the playgrounds and the number of children actively playing in them were higher in those with more varied facilities and without naturalness. Girls played more actively in playgrounds without multi-purpose areas. Cleanliness, esthetics, play facility quality, division of functional areas and playground size were not related to any outcome variable. Playground spatial features are related to playground usage and activity levels of the children in the playgrounds. Playgrounds should offer a wide variety of play facilities and provide spaces for diverse play activities to respond to the needs of large numbers of different children and to provide activity-friendly areas enabling their healthy development.

A short feature vector for image matching: The Log-Polar Magnitude feature descriptor

PubMed Central

Hast, Anders; Wählby, Carolina; Sintorn, Ida-Maria

2017-01-01

The choice of an optimal feature detector-descriptor combination for image matching often depends on the application and the image type. In this paper, we propose the Log-Polar Magnitude feature descriptor—a rotation, scale, and illumination invariant descriptor that achieves comparable performance to SIFT on a large variety of image registration problems but with much shorter feature vectors. The descriptor is based on the Log-Polar Transform followed by a Fourier Transform and selection of the magnitude spectrum components. Selecting different frequency components allows optimizing for image patterns specific for a particular application. In addition, by relying only on coordinates of the found features and (optionally) feature sizes our descriptor is completely detector independent. We propose 48- or 56-long feature vectors that potentially can be shortened even further depending on the application. Shorter feature vectors result in better memory usage and faster matching. This combined with the fact that the descriptor does not require a time-consuming feature orientation estimation (the rotation invariance is achieved solely by using the magnitude spectrum of the Log-Polar Transform) makes it particularly attractive to applications with limited hardware capacity. Evaluation is performed on the standard Oxford dataset and two different microscopy datasets; one with fluorescence and one with transmission electron microscopy images. Our method performs better than SURF and comparable to SIFT on the Oxford dataset, and better than SIFT on both microscopy datasets indicating that it is particularly useful in applications with microscopy images. PMID:29190737

The effects of variations in parameters and algorithm choices on calculated radiomics feature values: initial investigations and comparisons to feature variability across CT image acquisition conditions

NASA Astrophysics Data System (ADS)

Emaminejad, Nastaran; Wahi-Anwar, Muhammad; Hoffman, John; Kim, Grace H.; Brown, Matthew S.; McNitt-Gray, Michael

2018-02-01

Translation of radiomics into clinical practice requires confidence in its interpretations. This may be obtained via understanding and overcoming the limitations in current radiomic approaches. Currently there is a lack of standardization in radiomic feature extraction. In this study we examined a few factors that are potential sources of inconsistency in characterizing lung nodules, such as 1)different choices of parameters and algorithms in feature calculation, 2)two CT image dose levels, 3)different CT reconstruction algorithms (WFBP, denoised WFBP, and Iterative). We investigated the effect of variation of these factors on entropy textural feature of lung nodules. CT images of 19 lung nodules identified from our lung cancer screening program were identified by a CAD tool and contours provided. The radiomics features were extracted by calculating 36 GLCM based and 4 histogram based entropy features in addition to 2 intensity based features. A robustness index was calculated across different image acquisition parameters to illustrate the reproducibility of features. Most GLCM based and all histogram based entropy features were robust across two CT image dose levels. Denoising of images slightly improved robustness of some entropy features at WFBP. Iterative reconstruction resulted in improvement of robustness in a fewer times and caused more variation in entropy feature values and their robustness. Within different choices of parameters and algorithms texture features showed a wide range of variation, as much as 75% for individual nodules. Results indicate the need for harmonization of feature calculations and identification of optimum parameters and algorithms in a radiomics study.

Alexnet Feature Extraction and Multi-Kernel Learning for Objectoriented Classification

NASA Astrophysics Data System (ADS)

Ding, L.; Li, H.; Hu, C.; Zhang, W.; Wang, S.

2018-04-01

In view of the fact that the deep convolutional neural network has stronger ability of feature learning and feature expression, an exploratory research is done on feature extraction and classification for high resolution remote sensing images. Taking the Google image with 0.3 meter spatial resolution in Ludian area of Yunnan Province as an example, the image segmentation object was taken as the basic unit, and the pre-trained AlexNet deep convolution neural network model was used for feature extraction. And the spectral features, AlexNet features and GLCM texture features are combined with multi-kernel learning and SVM classifier, finally the classification results were compared and analyzed. The results show that the deep convolution neural network can extract more accurate remote sensing image features, and significantly improve the overall accuracy of classification, and provide a reference value for earthquake disaster investigation and remote sensing disaster evaluation.

Contextualized Emotional Images in Children's Dreams: Psychological Adjustment in Conditions of Military Trauma

ERIC Educational Resources Information Center

Helminen, Elisa; Punamaki, Raija-Leena

2008-01-01

This study examines the impact of military trauma on contextualized emotional images in children's dreams, and the function of the intensity and valence of the emotional images in protecting mental health from negative trauma impact. Participants were 345 Palestinian children and adolescents (aged 5-16 years) belonging to high trauma (Gaza) and…

Gender Differences in Peer and Parental Influences: Body Image Disturbance, Self-Worth, and Psychological Functioning in Preadolescent Children.

ERIC Educational Resources Information Center

Phares, Vicky; Steinberg, Ari R.; Thompson, J. Kevin

2004-01-01

The connections between body image disturbance and psychological functioning have been well established in samples of older adolescent girls and young women. Little is known, however, about body image in younger children. In particular, little is known about possible gender differences in preadolescent children. The current study explored…

Evidence-based guideline summary: Evaluation, diagnosis, and management of congenital muscular dystrophy

PubMed Central

Kang, Peter B.; Morrison, Leslie; Iannaccone, Susan T.; Graham, Robert J.; Bönnemann, Carsten G.; Rutkowski, Anne; Hornyak, Joseph; Wang, Ching H.; North, Kathryn; Oskoui, Maryam; Getchius, Thomas S.D.; Cox, Julie A.; Hagen, Erin E.; Gronseth, Gary; Griggs, Robert C.

2015-01-01

Objective: To delineate optimal diagnostic and therapeutic approaches to congenital muscular dystrophy (CMD) through a systematic review and analysis of the currently available literature. Methods: Relevant, peer-reviewed research articles were identified using a literature search of the MEDLINE, EMBASE, and Scopus databases. Diagnostic and therapeutic data from these articles were extracted and analyzed in accordance with the American Academy of Neurology classification of evidence schemes for diagnostic, prognostic, and therapeutic studies. Recommendations were linked to the strength of the evidence, other related literature, and general principles of care. Results: The geographic and ethnic backgrounds, clinical features, brain imaging studies, muscle imaging studies, and muscle biopsies of children with suspected CMD help predict subtype-specific diagnoses. Genetic testing can confirm some subtype-specific diagnoses, but not all causative genes for CMD have been described. Seizures and respiratory complications occur in specific subtypes. There is insufficient evidence to determine the efficacy of various treatment interventions to optimize respiratory, orthopedic, and nutritional outcomes, and more data are needed regarding complications. Recommendations: Multidisciplinary care by experienced teams is important for diagnosing and promoting the health of children with CMD. Accurate assessment of clinical presentations and genetic data will help in identifying the correct subtype-specific diagnosis in many cases. Multiorgan system complications occur frequently; surveillance and prompt interventions are likely to be beneficial for affected children. More research is needed to fill gaps in knowledge regarding this category of muscular dystrophies. PMID:25825463

[Maternal perception of her child's weight and unrelated children less than 1 year old].

PubMed

Flores-Peña, Yolanda; Aguado-Barrera, Miguel E; Cerda-Flores, Ricardo M; Cortés-Gutiérrez, Elva I; Dávila-Rodríguez, Martha I

2016-11-01

To evaluate the maternal perception of their child's weight (MPCW) and perception of unrelated children's weight. Cross-sectional. Maternal and Child Nursing Health Department at 6 Units of Family Medicine. 486 dyads (mother and child under 1 year). The following question was applied: "I think my child is", and images were provided according the child's gender. Children's weight and height were measured. A total of 20.5% of the mothers of overweight (OW) children accurately perceived this situation, while none of the mothers of obese (OB) children did (κ=0.14±0.03, Z=5.36, p=.001). By images, 63.3% of mothers of OW children and 33.3% of mothers of OB children perceived this situation (κ=0.01±0.02, Z=0.73, p=.46). Most mothers selected the image of OW child as the image of a healthy child (κ=-0.04±0.01, Z=-2.65, p=.008), the image of a child under 1 year (κ=-0.01±0.02, Z=-0.86, p=.38) and the image that they would like their child to look like (κ=0.0004±0.01, Z=0.02, p=.98). The mothers do not perceive the OW-OB of their children. Copyright © 2015 Elsevier España, S.L.U. All rights reserved.

The impact of image-size manipulation and sugar content on children's cereal consumption.

PubMed

Neyens, E; Aerts, G; Smits, T

2015-12-01

Previous studies have demonstrated that portion sizes and food energy-density influence children's eating behavior. However, the potential effects of front-of-pack image-sizes of serving suggestions and sugar content have not been tested. Using a mixed experimental design among young children, this study examines the effects of image-size manipulation and sugar content on cereal and milk consumption. Children poured and consumed significantly more cereal and drank significantly more milk when exposed to a larger sized image of serving suggestion as compared to a smaller image-size. Sugar content showed no main effects. Nevertheless, cereal consumption only differed significantly between small and large image-sizes when sugar content was low. An advantage of this study was the mundane setting in which the data were collected: a school's dining room instead of an artificial lab. Future studies should include a control condition, with children eating by themselves to reflect an even more natural context. Copyright © 2015 Elsevier Ltd. All rights reserved.

Feasibility and Use of the Mobile Food Record for Capturing Eating Occasions among Children Ages 3-10 Years in Guam.

PubMed

Aflague, Tanisha F; Boushey, Carol J; Guerrero, Rachael T Leon; Ahmad, Ziad; Kerr, Deborah A; Delp, Edward J

2015-06-02

Children's readiness to use technology supports the idea of children using mobile applications for dietary assessment. Our goal was to determine if children 3-10 years could successfully use the mobile food record (mFR) to capture a usable image pair or pairs. Children in Sample 1 were tasked to use the mFR to capture an image pair of one eating occasion while attending summer camp. For Sample 2, children were tasked to record all eating occasions for two consecutive days at two time periods that were two to four weeks apart. Trained analysts evaluated images. In Sample 1, 90% (57/63) captured one usable image pair. All children (63/63) returned the mFR undamaged. Sixty-two children reported: The mFR was easy to use (89%); willingness to use the mFR again (87%); and the fiducial marker easy to manage (94%). Children in Sample 2 used the mFR at least one day at Time 1 (59/63, 94%); Time 2 (49/63, 78%); and at both times (47/63, 75%). This latter group captured 6.21 ± 4.65 and 5.65 ± 3.26 mean (± SD) image pairs for Time 1 and Time 2, respectively. Results support the potential for children to independently record dietary intakes using the mFR.

Hepatic CT image query using Gabor features

NASA Astrophysics Data System (ADS)

Zhao, Chenguang; Cheng, Hongyan; Zhuang, Tiange

2004-07-01

A retrieval scheme for liver computerize tomography (CT) images based on Gabor texture is presented. For each hepatic CT image, we manually delineate abnormal regions within liver area. Then, a continuous Gabor transform is utilized to analyze the texture of the pathology bearing region and extract the corresponding feature vectors. For a given sample image, we compare its feature vector with those of other images. Similar images with the highest rank are retrieved. In experiments, 45 liver CT images are collected, and the effectiveness of Gabor texture for content based retrieval is verified.

Target detection method by airborne and spaceborne images fusion based on past images

NASA Astrophysics Data System (ADS)

Chen, Shanjing; Kang, Qing; Wang, Zhenggang; Shen, ZhiQiang; Pu, Huan; Han, Hao; Gu, Zhongzheng

2017-11-01

To solve the problem that remote sensing target detection method has low utilization rate of past remote sensing data on target area, and can not recognize camouflage target accurately, a target detection method by airborne and spaceborne images fusion based on past images is proposed in this paper. The target area's past of space remote sensing image is taken as background. The airborne and spaceborne remote sensing data is fused and target feature is extracted by the means of airborne and spaceborne images registration, target change feature extraction, background noise suppression and artificial target feature extraction based on real-time aerial optical remote sensing image. Finally, the support vector machine is used to detect and recognize the target on feature fusion data. The experimental results have established that the proposed method combines the target area change feature of airborne and spaceborne remote sensing images with target detection algorithm, and obtains fine detection and recognition effect on camouflage and non-camouflage targets.

Quality evaluation of no-reference MR images using multidirectional filters and image statistics.

PubMed

Jang, Jinseong; Bang, Kihun; Jang, Hanbyol; Hwang, Dosik

2018-09-01

This study aimed to develop a fully automatic, no-reference image-quality assessment (IQA) method for MR images. New quality-aware features were obtained by applying multidirectional filters to MR images and examining the feature statistics. A histogram of these features was then fitted to a generalized Gaussian distribution function for which the shape parameters yielded different values depending on the type of distortion in the MR image. Standard feature statistics were established through a training process based on high-quality MR images without distortion. Subsequently, the feature statistics of a test MR image were calculated and compared with the standards. The quality score was calculated as the difference between the shape parameters of the test image and the undistorted standard images. The proposed IQA method showed a >0.99 correlation with the conventional full-reference assessment methods; accordingly, this proposed method yielded the best performance among no-reference IQA methods for images containing six types of synthetic, MR-specific distortions. In addition, for authentically distorted images, the proposed method yielded the highest correlation with subjective assessments by human observers, thus demonstrating its superior performance over other no-reference IQAs. Our proposed IQA was designed to consider MR-specific features and outperformed other no-reference IQAs designed mainly for photographic images. Magn Reson Med 80:914-924, 2018. © 2018 International Society for Magnetic Resonance in Medicine. © 2018 International Society for Magnetic Resonance in Medicine.

Does Anxiety Modify the Risk for, or Severity of, Conduct Problems Among Children With Co-Occurring ADHD: Categorical and Dimensional and Analyses.

PubMed

Danforth, Jeffrey S; Doerfler, Leonard A; Connor, Daniel F

2017-08-01

The goal was to examine whether anxiety modifies the risk for, or severity of, conduct problems in children with ADHD. Assessment included both categorical and dimensional measures of ADHD, anxiety, and conduct problems. Analyses compared conduct problems between children with ADHD features alone versus children with co-occurring ADHD and anxiety features. When assessed by dimensional rating scales, results showed that compared with children with ADHD alone, those children with ADHD co-occurring with anxiety are at risk for more intense conduct problems. When assessment included a Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV) diagnosis via the Schedule for Affective Disorders and Schizophrenia for School Age Children-Epidemiologic Version (K-SADS), results showed that compared with children with ADHD alone, those children with ADHD co-occurring with anxiety neither had more intense conduct problems nor were they more likely to be diagnosed with oppositional defiant disorder or conduct disorder. Different methodological measures of ADHD, anxiety, and conduct problem features influenced the outcome of the analyses.

Histogram of gradient and binarized statistical image features of wavelet subband-based palmprint features extraction

NASA Astrophysics Data System (ADS)

Attallah, Bilal; Serir, Amina; Chahir, Youssef; Boudjelal, Abdelwahhab

2017-11-01

Palmprint recognition systems are dependent on feature extraction. A method of feature extraction using higher discrimination information was developed to characterize palmprint images. In this method, two individual feature extraction techniques are applied to a discrete wavelet transform of a palmprint image, and their outputs are fused. The two techniques used in the fusion are the histogram of gradient and the binarized statistical image features. They are then evaluated using an extreme learning machine classifier before selecting a feature based on principal component analysis. Three palmprint databases, the Hong Kong Polytechnic University (PolyU) Multispectral Palmprint Database, Hong Kong PolyU Palmprint Database II, and the Delhi Touchless (IIDT) Palmprint Database, are used in this study. The study shows that our method effectively identifies and verifies palmprints and outperforms other methods based on feature extraction.

Reproducibility and Prognosis of Quantitative Features Extracted from CT Images12

PubMed Central

Balagurunathan, Yoganand; Gu, Yuhua; Wang, Hua; Kumar, Virendra; Grove, Olya; Hawkins, Sam; Kim, Jongphil; Goldgof, Dmitry B; Hall, Lawrence O; Gatenby, Robert A; Gillies, Robert J

2014-01-01

We study the reproducibility of quantitative imaging features that are used to describe tumor shape, size, and texture from computed tomography (CT) scans of non-small cell lung cancer (NSCLC). CT images are dependent on various scanning factors. We focus on characterizing image features that are reproducible in the presence of variations due to patient factors and segmentation methods. Thirty-two NSCLC nonenhanced lung CT scans were obtained from the Reference Image Database to Evaluate Response data set. The tumors were segmented using both manual (radiologist expert) and ensemble (software-automated) methods. A set of features (219 three-dimensional and 110 two-dimensional) was computed, and quantitative image features were statistically filtered to identify a subset of reproducible and nonredundant features. The variability in the repeated experiment was measured by the test-retest concordance correlation coefficient (CCCTreT). The natural range in the features, normalized to variance, was measured by the dynamic range (DR). In this study, there were 29 features across segmentation methods found with CCCTreT and DR ≥ 0.9 and R2Bet ≥ 0.95. These reproducible features were tested for predicting radiologist prognostic score; some texture features (run-length and Laws kernels) had an area under the curve of 0.9. The representative features were tested for their prognostic capabilities using an independent NSCLC data set (59 lung adenocarcinomas), where one of the texture features, run-length gray-level nonuniformity, was statistically significant in separating the samples into survival groups (P ≤ .046). PMID:24772210

Image fusion using sparse overcomplete feature dictionaries

DOEpatents

Brumby, Steven P.; Bettencourt, Luis; Kenyon, Garrett T.; Chartrand, Rick; Wohlberg, Brendt

2015-10-06

Approaches for deciding what individuals in a population of visual system "neurons" are looking for using sparse overcomplete feature dictionaries are provided. A sparse overcomplete feature dictionary may be learned for an image dataset and a local sparse representation of the image dataset may be built using the learned feature dictionary. A local maximum pooling operation may be applied on the local sparse representation to produce a translation-tolerant representation of the image dataset. An object may then be classified and/or clustered within the translation-tolerant representation of the image dataset using a supervised classification algorithm and/or an unsupervised clustering algorithm.

Maternal employment and Mexican school-age children overweight in 2012: the importance of households features.

PubMed

Espinosa, Alejandro Martínez

2018-01-01

International evidence regarding the relationship between maternal employment and school-age children overweight and obesity shows divergent results. In Mexico, this relationship has not been confirmed by national data sets analysis. Consequently, the objective of this article was to evaluate the role of the mothers' participation in labor force related to excess body weight in Mexican school-age children (aged 5-11 years). A cross-sectional study was conducted on a sample of 17,418 individuals from the National Health and Nutrition Survey 2012, applying binomial logistic regression models. After controlling for individual, maternal and contextual features, the mothers' participation in labor force was associated with children body composition. However, when the household features (living arrangements, household ethnicity, size, food security and socioeconomic status) were incorporated, maternal employment was no longer statically significant. Household features are crucial factors for understanding the overweight and obesity prevalence levels in Mexican school-age children, despite the mother having a paid job. Copyright: © 2018 Permanyer.

Self-recognition in retarded children.

PubMed

Hill, S D; Tomlin, C

1981-03-01

This study was designed to investigate the relationship between cognitive and affective development. Young preverbal retarded children watched TV images of themselves with faces marked or unmarked and of a peer whose face was marked. We used the objective technique of increased mark-directed responses as evidence of self-recognition and rated the children's reactions as they watched these images. The emergence of self-recognition was closely tied to the maturity of the children's general responsiveness to their reflections. The Down's syndrome children made a broad range of responses, including the curiosity and self-conscious behaviors characteristic of normal children during the second year of life, and all except one of these children showed evidence that they recognized their images. In contrast, the range of behaviors displayed by multihandicapped children was greatly restricted and similar to children in the first year of life. Less than half of these children showed an emergence of self-recognition.

Visual search for features and conjunctions in development.

PubMed

Lobaugh, N J; Cole, S; Rovet, J F

1998-12-01

Visual search performance was examined in three groups of children 7 to 12 years of age and in young adults. Colour and orientation feature searches and a conjunction search were conducted. Reaction time (RT) showed expected improvements in processing speed with age. Comparisons of RT's on target-present and target-absent trials were consistent with parallel search on the two feature conditions and with serial search in the conjunction condition. The RT results indicated searches for feature and conjunctions were treated similarly for children and adults. However, the youngest children missed more targets at the largest array sizes, most strikingly in conjunction search. Based on an analysis of speed/accuracy trade-offs, we suggest that low target-distractor discriminability leads to an undersampling of array elements, and is responsible for the high number of misses in the youngest children.

From Scribbles to Scrabble: Preschool Children’s Developing Knowledge of Written Language

PubMed Central

Puranik, Cynthia S.; Lonigan, Christopher J.

2011-01-01

The purpose of this study was to concurrently examine the development of written language across several writing tasks and to investigate how writing features develop in preschool children. Emergent written language knowledge of 372 preschoolers was assessed using numerous writing tasks. The findings from this study indicate that children possess a great deal of writing knowledge before beginning school. Children appear to progress along a continuum from scribbling to conventional spelling, and this progression is linear and task dependent. There was clear evidence to support the claim that universal writing features develop before language-specific features. Children as young as 3 years possess knowledge regarding universal and language-specific writing features. There is substantial developmental continuity in literacy skills from the preschool period into early elementary grades. Implications of these findings on writing development are discussed. PMID:22448101

HoDOr: histogram of differential orientations for rigid landmark tracking in medical images

NASA Astrophysics Data System (ADS)

Tiwari, Abhishek; Patwardhan, Kedar Anil

2018-03-01

Feature extraction plays a pivotal role in pattern recognition and matching. An ideal feature should be invariant to image transformations such as translation, rotation, scaling, etc. In this work, we present a novel rotation-invariant feature, which is based on Histogram of Oriented Gradients (HOG). We compare performance of the proposed approach with the HOG feature on 2D phantom data, as well as 3D medical imaging data. We have used traditional histogram comparison measures such as Bhattacharyya distance and Normalized Correlation Coefficient (NCC) to assess efficacy of the proposed approach under effects of image rotation. In our experiments, the proposed feature performs 40%, 20%, and 28% better than the HOG feature on phantom (2D), Computed Tomography (CT-3D), and Ultrasound (US-3D) data for image matching, and landmark tracking tasks respectively.

A similarity measure method combining location feature for mammogram retrieval.

PubMed

Wang, Zhiqiong; Xin, Junchang; Huang, Yukun; Li, Chen; Xu, Ling; Li, Yang; Zhang, Hao; Gu, Huizi; Qian, Wei

2018-05-28

Breast cancer, the most common malignancy among women, has a high mortality rate in clinical practice. Early detection, diagnosis and treatment can reduce the mortalities of breast cancer greatly. The method of mammogram retrieval can help doctors to find the early breast lesions effectively and determine a reasonable feature set for image similarity measure. This will improve the accuracy effectively for mammogram retrieval. This paper proposes a similarity measure method combining location feature for mammogram retrieval. Firstly, the images are pre-processed, the regions of interest are detected and the lesions are segmented in order to get the center point and radius of the lesions. Then, the method, namely Coherent Point Drift, is used for image registration with the pre-defined standard image. The center point and radius of the lesions after registration are obtained and the standard location feature of the image is constructed. This standard location feature can help figure out the location similarity between the image pair from the query image to each dataset image in the database. Next, the content feature of the image is extracted, including the Histogram of Oriented Gradients, the Edge Direction Histogram, the Local Binary Pattern and the Gray Level Histogram, and the image pair content similarity can be calculated using the Earth Mover's Distance. Finally, the location similarity and content similarity are fused to form the image fusion similarity, and the specified number of the most similar images can be returned according to it. In the experiment, 440 mammograms, which are from Chinese women in Northeast China, are used as the database. When fusing 40% lesion location feature similarity and 60% content feature similarity, the results have obvious advantages. At this time, precision is 0.83, recall is 0.76, comprehensive indicator is 0.79, satisfaction is 96.0%, mean is 4.2 and variance is 17.7. The results show that the precision and recall of this method have obvious advantage, compared with the content-based image retrieval.

Many local pattern texture features: which is better for image-based multilabel human protein subcellular localization classification?

PubMed

Yang, Fan; Xu, Ying-Ying; Shen, Hong-Bin

2014-01-01

Human protein subcellular location prediction can provide critical knowledge for understanding a protein's function. Since significant progress has been made on digital microscopy, automated image-based protein subcellular location classification is urgently needed. In this paper, we aim to investigate more representative image features that can be effectively used for dealing with the multilabel subcellular image samples. We prepared a large multilabel immunohistochemistry (IHC) image benchmark from the Human Protein Atlas database and tested the performance of different local texture features, including completed local binary pattern, local tetra pattern, and the standard local binary pattern feature. According to our experimental results from binary relevance multilabel machine learning models, the completed local binary pattern, and local tetra pattern are more discriminative for describing IHC images when compared to the traditional local binary pattern descriptor. The combination of these two novel local pattern features and the conventional global texture features is also studied. The enhanced performance of final binary relevance classification model trained on the combined feature space demonstrates that different features are complementary to each other and thus capable of improving the accuracy of classification.

Is the spatial distribution of brain lesions associated with closed-head injury predictive of subsequent development of attention-deficit/hyperactivity disorder? Analysis with brain-image database

NASA Technical Reports Server (NTRS)

Herskovits, E. H.; Megalooikonomou, V.; Davatzikos, C.; Chen, A.; Bryan, R. N.; Gerring, J. P.

1999-01-01

PURPOSE: To determine whether there is an association between the spatial distribution of lesions detected at magnetic resonance (MR) imaging of the brain in children after closed-head injury and the development of secondary attention-deficit/hyperactivity disorder (ADHD). MATERIALS AND METHODS: Data obtained from 76 children without prior history of ADHD were analyzed. MR images were obtained 3 months after closed-head injury. After manual delineation of lesions, images were registered to the Talairach coordinate system. For each subject, registered images and secondary ADHD status were integrated into a brain-image database, which contains depiction (visualization) and statistical analysis software. Using this database, we assessed visually the spatial distributions of lesions and performed statistical analysis of image and clinical variables. RESULTS: Of the 76 children, 15 developed secondary ADHD. Depiction of the data suggested that children who developed secondary ADHD had more lesions in the right putamen than children who did not develop secondary ADHD; this impression was confirmed statistically. After Bonferroni correction, we could not demonstrate significant differences between secondary ADHD status and lesion burdens for the right caudate nucleus or the right globus pallidus. CONCLUSION: Closed-head injury-induced lesions in the right putamen in children are associated with subsequent development of secondary ADHD. Depiction software is useful in guiding statistical analysis of image data.

Image Mosaic Method Based on SIFT Features of Line Segment

PubMed Central

Zhu, Jun; Ren, Mingwu

2014-01-01

This paper proposes a novel image mosaic method based on SIFT (Scale Invariant Feature Transform) feature of line segment, aiming to resolve incident scaling, rotation, changes in lighting condition, and so on between two images in the panoramic image mosaic process. This method firstly uses Harris corner detection operator to detect key points. Secondly, it constructs directed line segments, describes them with SIFT feature, and matches those directed segments to acquire rough point matching. Finally, Ransac method is used to eliminate wrong pairs in order to accomplish image mosaic. The results from experiment based on four pairs of images show that our method has strong robustness for resolution, lighting, rotation, and scaling. PMID:24511326

Automatic Extraction of Planetary Image Features

NASA Technical Reports Server (NTRS)

Troglio, G.; LeMoigne, J.; Moser, G.; Serpico, S. B.; Benediktsson, J. A.

2009-01-01

With the launch of several Lunar missions such as the Lunar Reconnaissance Orbiter (LRO) and Chandrayaan-1, a large amount of Lunar images will be acquired and will need to be analyzed. Although many automatic feature extraction methods have been proposed and utilized for Earth remote sensing images, these methods are not always applicable to Lunar data that often present low contrast and uneven illumination characteristics. In this paper, we propose a new method for the extraction of Lunar features (that can be generalized to other planetary images), based on the combination of several image processing techniques, a watershed segmentation and the generalized Hough Transform. This feature extraction has many applications, among which image registration.

Computer-aided Classification of Mammographic Masses Using Visually Sensitive Image Features

PubMed Central

Wang, Yunzhi; Aghaei, Faranak; Zarafshani, Ali; Qiu, Yuchen; Qian, Wei; Zheng, Bin

2017-01-01

Purpose To develop a new computer-aided diagnosis (CAD) scheme that computes visually sensitive image features routinely used by radiologists to develop a machine learning classifier and distinguish between the malignant and benign breast masses detected from digital mammograms. Methods An image dataset including 301 breast masses was retrospectively selected. From each segmented mass region, we computed image features that mimic five categories of visually sensitive features routinely used by radiologists in reading mammograms. We then selected five optimal features in the five feature categories and applied logistic regression models for classification. A new CAD interface was also designed to show lesion segmentation, computed feature values and classification score. Results Areas under ROC curves (AUC) were 0.786±0.026 and 0.758±0.027 when to classify mass regions depicting on two view images, respectively. By fusing classification scores computed from two regions, AUC increased to 0.806±0.025. Conclusion This study demonstrated a new approach to develop CAD scheme based on 5 visually sensitive image features. Combining with a “visual aid” interface, CAD results may be much more easily explainable to the observers and increase their confidence to consider CAD generated classification results than using other conventional CAD approaches, which involve many complicated and visually insensitive texture features. PMID:27911353

Effective Moment Feature Vectors for Protein Domain Structures

PubMed Central

Shi, Jian-Yu; Yiu, Siu-Ming; Zhang, Yan-Ning; Chin, Francis Yuk-Lun

2013-01-01

Imaging processing techniques have been shown to be useful in studying protein domain structures. The idea is to represent the pairwise distances of any two residues of the structure in a 2D distance matrix (DM). Features and/or submatrices are extracted from this DM to represent a domain. Existing approaches, however, may involve a large number of features (100–400) or complicated mathematical operations. Finding fewer but more effective features is always desirable. In this paper, based on some key observations on DMs, we are able to decompose a DM image into four basic binary images, each representing the structural characteristics of a fundamental secondary structure element (SSE) or a motif in the domain. Using the concept of moments in image processing, we further derive 45 structural features based on the four binary images. Together with 4 features extracted from the basic images, we represent the structure of a domain using 49 features. We show that our feature vectors can represent domain structures effectively in terms of the following. (1) We show a higher accuracy for domain classification. (2) We show a clear and consistent distribution of domains using our proposed structural vector space. (3) We are able to cluster the domains according to our moment features and demonstrate a relationship between structural variation and functional diversity. PMID:24391828

An improved feature extraction algorithm based on KAZE for multi-spectral image

NASA Astrophysics Data System (ADS)

Yang, Jianping; Li, Jun

2018-02-01

Multi-spectral image contains abundant spectral information, which is widely used in all fields like resource exploration, meteorological observation and modern military. Image preprocessing, such as image feature extraction and matching, is indispensable while dealing with multi-spectral remote sensing image. Although the feature matching algorithm based on linear scale such as SIFT and SURF performs strong on robustness, the local accuracy cannot be guaranteed. Therefore, this paper proposes an improved KAZE algorithm, which is based on nonlinear scale, to raise the number of feature and to enhance the matching rate by using the adjusted-cosine vector. The experiment result shows that the number of feature and the matching rate of the improved KAZE are remarkably than the original KAZE algorithm.

Identification of important image features for pork and turkey ham classification using colour and wavelet texture features and genetic selection.

PubMed

Jackman, Patrick; Sun, Da-Wen; Allen, Paul; Valous, Nektarios A; Mendoza, Fernando; Ward, Paddy

2010-04-01

A method to discriminate between various grades of pork and turkey ham was developed using colour and wavelet texture features. Image analysis methods originally developed for predicting the palatability of beef were applied to rapidly identify the ham grade. With high quality digital images of 50-94 slices per ham it was possible to identify the greyscale that best expressed the differences between the various ham grades. The best 10 discriminating image features were then found with a genetic algorithm. Using the best 10 image features, simple linear discriminant analysis models produced 100% correct classifications for both pork and turkey on both calibration and validation sets. 2009 Elsevier Ltd. All rights reserved.

[Several mechanisms of visual gnosis disorders in local brain lesions].

PubMed

Meerson, Ia A

1981-01-01

The object of the studies were peculiarities of recognizing visual images by patients with local cerebral lesions under conditions of incomplete sets of the image features, disjunction of the latter, distortion of their spatial arrangement, and unusual spatial orientation of the image as a whole. It was found that elimination of even one essential feature sharply hampered the recognition of the image both by healthy individuals (control), and patients with extraoccipital lesions, whereas elimination of several nonessential features only slowed down the process. In distinction from this the difficulties of the recognition of incomplete images by patients with occipital lesions were directly proportional to the number of the eliminated features irrespective of the latters' significance, i.e. these patients were unable to evaluate the hierarchy of the features. The recognition process in these patients were followed the way of scanning individual features. The reaccumulation and summation. The recognition of the fragmental, spatially distorted and unusually oriented images was found to be affected selectively in patients with parietal lobe affections. The patients with occipital lesions recognized such images practically as good as the ordinary ones.

A Study for Texture Feature Extraction of High-Resolution Satellite Images Based on a Direction Measure and Gray Level Co-Occurrence Matrix Fusion Algorithm

PubMed Central

Zhang, Xin; Cui, Jintian; Wang, Weisheng; Lin, Chao

2017-01-01

To address the problem of image texture feature extraction, a direction measure statistic that is based on the directionality of image texture is constructed, and a new method of texture feature extraction, which is based on the direction measure and a gray level co-occurrence matrix (GLCM) fusion algorithm, is proposed in this paper. This method applies the GLCM to extract the texture feature value of an image and integrates the weight factor that is introduced by the direction measure to obtain the final texture feature of an image. A set of classification experiments for the high-resolution remote sensing images were performed by using support vector machine (SVM) classifier with the direction measure and gray level co-occurrence matrix fusion algorithm. Both qualitative and quantitative approaches were applied to assess the classification results. The experimental results demonstrated that texture feature extraction based on the fusion algorithm achieved a better image recognition, and the accuracy of classification based on this method has been significantly improved. PMID:28640181

Near infrared and visible face recognition based on decision fusion of LBP and DCT features

NASA Astrophysics Data System (ADS)

Xie, Zhihua; Zhang, Shuai; Liu, Guodong; Xiong, Jinquan

2018-03-01

Visible face recognition systems, being vulnerable to illumination, expression, and pose, can not achieve robust performance in unconstrained situations. Meanwhile, near infrared face images, being light- independent, can avoid or limit the drawbacks of face recognition in visible light, but its main challenges are low resolution and signal noise ratio (SNR). Therefore, near infrared and visible fusion face recognition has become an important direction in the field of unconstrained face recognition research. In order to extract the discriminative complementary features between near infrared and visible images, in this paper, we proposed a novel near infrared and visible face fusion recognition algorithm based on DCT and LBP features. Firstly, the effective features in near-infrared face image are extracted by the low frequency part of DCT coefficients and the partition histograms of LBP operator. Secondly, the LBP features of visible-light face image are extracted to compensate for the lacking detail features of the near-infrared face image. Then, the LBP features of visible-light face image, the DCT and LBP features of near-infrared face image are sent to each classifier for labeling. Finally, decision level fusion strategy is used to obtain the final recognition result. The visible and near infrared face recognition is tested on HITSZ Lab2 visible and near infrared face database. The experiment results show that the proposed method extracts the complementary features of near-infrared and visible face images and improves the robustness of unconstrained face recognition. Especially for the circumstance of small training samples, the recognition rate of proposed method can reach 96.13%, which has improved significantly than 92.75 % of the method based on statistical feature fusion.

Seeing White: Children of Color and the Disney Fairy Tale Princess

ERIC Educational Resources Information Center

Hurley, Dorothy L.

2005-01-01

The children's self-image is affected by the ways in which they see themselves in texts both verbal and visual which plays an important role in building self-image and the belief-system of the children. The development of critical literacy skills in children and teachers and the importance of exposing the children to transcultural literature are…

A Probabilistic Feature Map-Based Localization System Using a Monocular Camera.

PubMed

Kim, Hyungjin; Lee, Donghwa; Oh, Taekjun; Choi, Hyun-Taek; Myung, Hyun

2015-08-31

Image-based localization is one of the most widely researched localization techniques in the robotics and computer vision communities. As enormous image data sets are provided through the Internet, many studies on estimating a location with a pre-built image-based 3D map have been conducted. Most research groups use numerous image data sets that contain sufficient features. In contrast, this paper focuses on image-based localization in the case of insufficient images and features. A more accurate localization method is proposed based on a probabilistic map using 3D-to-2D matching correspondences between a map and a query image. The probabilistic feature map is generated in advance by probabilistic modeling of the sensor system as well as the uncertainties of camera poses. Using the conventional PnP algorithm, an initial camera pose is estimated on the probabilistic feature map. The proposed algorithm is optimized from the initial pose by minimizing Mahalanobis distance errors between features from the query image and the map to improve accuracy. To verify that the localization accuracy is improved, the proposed algorithm is compared with the conventional algorithm in a simulation and realenvironments.

A Probabilistic Feature Map-Based Localization System Using a Monocular Camera

PubMed Central

Kim, Hyungjin; Lee, Donghwa; Oh, Taekjun; Choi, Hyun-Taek; Myung, Hyun

2015-01-01

Image-based localization is one of the most widely researched localization techniques in the robotics and computer vision communities. As enormous image data sets are provided through the Internet, many studies on estimating a location with a pre-built image-based 3D map have been conducted. Most research groups use numerous image data sets that contain sufficient features. In contrast, this paper focuses on image-based localization in the case of insufficient images and features. A more accurate localization method is proposed based on a probabilistic map using 3D-to-2D matching correspondences between a map and a query image. The probabilistic feature map is generated in advance by probabilistic modeling of the sensor system as well as the uncertainties of camera poses. Using the conventional PnP algorithm, an initial camera pose is estimated on the probabilistic feature map. The proposed algorithm is optimized from the initial pose by minimizing Mahalanobis distance errors between features from the query image and the map to improve accuracy. To verify that the localization accuracy is improved, the proposed algorithm is compared with the conventional algorithm in a simulation and realenvironments. PMID:26404284

Thin Cloud Detection Method by Linear Combination Model of Cloud Image

NASA Astrophysics Data System (ADS)

Liu, L.; Li, J.; Wang, Y.; Xiao, Y.; Zhang, W.; Zhang, S.

2018-04-01

The existing cloud detection methods in photogrammetry often extract the image features from remote sensing images directly, and then use them to classify images into cloud or other things. But when the cloud is thin and small, these methods will be inaccurate. In this paper, a linear combination model of cloud images is proposed, by using this model, the underlying surface information of remote sensing images can be removed. So the cloud detection result can become more accurate. Firstly, the automatic cloud detection program in this paper uses the linear combination model to split the cloud information and surface information in the transparent cloud images, then uses different image features to recognize the cloud parts. In consideration of the computational efficiency, AdaBoost Classifier was introduced to combine the different features to establish a cloud classifier. AdaBoost Classifier can select the most effective features from many normal features, so the calculation time is largely reduced. Finally, we selected a cloud detection method based on tree structure and a multiple feature detection method using SVM classifier to compare with the proposed method, the experimental data shows that the proposed cloud detection program in this paper has high accuracy and fast calculation speed.

Attention-based image similarity measure with application to content-based information retrieval

NASA Astrophysics Data System (ADS)

Stentiford, Fred W. M.

2003-01-01

Whilst storage and capture technologies are able to cope with huge numbers of images, image retrieval is in danger of rendering many repositories valueless because of the difficulty of access. This paper proposes a similarity measure that imposes only very weak assumptions on the nature of the features used in the recognition process. This approach does not make use of a pre-defined set of feature measurements which are extracted from a query image and used to match those from database images, but instead generates features on a trial and error basis during the calculation of the similarity measure. This has the significant advantage that features that determine similarity can match whatever image property is important in a particular region whether it be a shape, a texture, a colour or a combination of all three. It means that effort is expended searching for the best feature for the region rather than expecting that a fixed feature set will perform optimally over the whole area of an image and over every image in a database. The similarity measure is evaluated on a problem of distinguishing similar shapes in sets of black and white symbols.

The Role of Canonical Orientations in Children's Drawing of Interpersonal Relationships: Aspects of Graphic Feature Marking.

ERIC Educational Resources Information Center

Ives, William; Houseworth, Marguerite

Aspects of children's early representational drawing ability may provide evidence for feature marking in non-linguistic symbol systems. To test this assumption children in kindergarten, second, and fourth grade were asked to draw a set of referent objects in three conditions: a nominal or standard condition with no implied relationship ("two…

Poverty Is Not a Human Characteristic: A Retrospective Study of Comprehending and Educating Impoverished Children

ERIC Educational Resources Information Center

Holmlund, Kerstin

2012-01-01

This article describes and compares the differences between a feature-oriented understanding and a relational understanding of a child's behavior and the different ways of educating children which these two empirical and theoretical perspectives offer. The feature-oriented perspective focuses on the nature and character of impoverished children as…

Children's Social Categories and the Salience of Race.

ERIC Educational Resources Information Center

Vora, Parul; England, Eileen M.

Research has shown that children use physical features to distinguish among people, and that race can be distinguished by certain features such as skin color and the shape of eyes, nose, and lips. However, L. Hirschfeld (1993, 1994) has argued that children must have the concept of race before they form the race social category and that other…

An Inner Face Advantage in Children's Recognition of Familiar Peers

ERIC Educational Resources Information Center

Ge, Liezhong; Anzures, Gizelle; Wang, Zhe; Kelly, David J.; Pascalis, Olivier; Quinn, Paul C.; Slater, Alan M.; Yang, Zhiliang; Lee, Kang

2008-01-01

Children's recognition of familiar own-age peers was investigated. Chinese children (4-, 8-, and 14-year-olds) were asked to identify their classmates from photographs showing the entire face, the internal facial features only, the external facial features only, or the eyes, nose, or mouth only. Participants from all age groups were familiar with…

Real-space post-processing correction of thermal drift and piezoelectric actuator nonlinearities in scanning tunneling microscope images.

PubMed

Yothers, Mitchell P; Browder, Aaron E; Bumm, Lloyd A

2017-01-01

We have developed a real-space method to correct distortion due to thermal drift and piezoelectric actuator nonlinearities on scanning tunneling microscope images using Matlab. The method uses the known structures typically present in high-resolution atomic and molecularly resolved images as an internal standard. Each image feature (atom or molecule) is first identified in the image. The locations of each feature's nearest neighbors are used to measure the local distortion at that location. The local distortion map across the image is simultaneously fit to our distortion model, which includes thermal drift in addition to piezoelectric actuator hysteresis and creep. The image coordinates of the features and image pixels are corrected using an inverse transform from the distortion model. We call this technique the thermal-drift, hysteresis, and creep transform. Performing the correction in real space allows defects, domain boundaries, and step edges to be excluded with a spatial mask. Additional real-space image analyses are now possible with these corrected images. Using graphite(0001) as a model system, we show lattice fitting to the corrected image, averaged unit cell images, and symmetry-averaged unit cell images. Statistical analysis of the distribution of the image features around their best-fit lattice sites measures the aggregate noise in the image, which can be expressed as feature confidence ellipsoids.

Real-space post-processing correction of thermal drift and piezoelectric actuator nonlinearities in scanning tunneling microscope images

NASA Astrophysics Data System (ADS)

Yothers, Mitchell P.; Browder, Aaron E.; Bumm, Lloyd A.

2017-01-01

We have developed a real-space method to correct distortion due to thermal drift and piezoelectric actuator nonlinearities on scanning tunneling microscope images using Matlab. The method uses the known structures typically present in high-resolution atomic and molecularly resolved images as an internal standard. Each image feature (atom or molecule) is first identified in the image. The locations of each feature's nearest neighbors are used to measure the local distortion at that location. The local distortion map across the image is simultaneously fit to our distortion model, which includes thermal drift in addition to piezoelectric actuator hysteresis and creep. The image coordinates of the features and image pixels are corrected using an inverse transform from the distortion model. We call this technique the thermal-drift, hysteresis, and creep transform. Performing the correction in real space allows defects, domain boundaries, and step edges to be excluded with a spatial mask. Additional real-space image analyses are now possible with these corrected images. Using graphite(0001) as a model system, we show lattice fitting to the corrected image, averaged unit cell images, and symmetry-averaged unit cell images. Statistical analysis of the distribution of the image features around their best-fit lattice sites measures the aggregate noise in the image, which can be expressed as feature confidence ellipsoids.

Image Recommendation Algorithm Using Feature-Based Collaborative Filtering

NASA Astrophysics Data System (ADS)

Kim, Deok-Hwan

As the multimedia contents market continues its rapid expansion, the amount of image contents used in mobile phone services, digital libraries, and catalog service is increasing remarkably. In spite of this rapid growth, users experience high levels of frustration when searching for the desired image. Even though new images are profitable to the service providers, traditional collaborative filtering methods cannot recommend them. To solve this problem, in this paper, we propose feature-based collaborative filtering (FBCF) method to reflect the user's most recent preference by representing his purchase sequence in the visual feature space. The proposed approach represents the images that have been purchased in the past as the feature clusters in the multi-dimensional feature space and then selects neighbors by using an inter-cluster distance function between their feature clusters. Various experiments using real image data demonstrate that the proposed approach provides a higher quality recommendation and better performance than do typical collaborative filtering and content-based filtering techniques.

The ship edge feature detection based on high and low threshold for remote sensing image

NASA Astrophysics Data System (ADS)

Li, Xuan; Li, Shengyang

2018-05-01

In this paper, a method based on high and low threshold is proposed to detect the ship edge feature due to the low accuracy rate caused by the noise. Analyze the relationship between human vision system and the target features, and to determine the ship target by detecting the edge feature. Firstly, using the second-order differential method to enhance the quality of image; Secondly, to improvement the edge operator, we introduction of high and low threshold contrast to enhancement image edge and non-edge points, and the edge as the foreground image, non-edge as a background image using image segmentation to achieve edge detection, and remove the false edges; Finally, the edge features are described based on the result of edge features detection, and determine the ship target. The experimental results show that the proposed method can effectively reduce the number of false edges in edge detection, and has the high accuracy of remote sensing ship edge detection.

Optic Nerve Head Development in Healthy Infants and Children Using Handheld Spectral-Domain Optical Coherence Tomography.

PubMed

Patel, Aarti; Purohit, Ravi; Lee, Helena; Sheth, Viral; Maconachie, Gail; Papageorgiou, Eleni; McLean, Rebecca J; Gottlob, Irene; Proudlock, Frank A

2016-10-01

To determine feasibility of optic nerve head (ONH) imaging and to characterize ONH development in full-term infants without sedation using handheld spectral-domain optical coherence tomography (SD OCT). Prospective cross-sectional study. Three hundred fifty-two children aged between 1 day and 13 years. All participants were imaged using handheld SD OCT without sedation during a single scan session. The percentage of successful scans was calculated. Interexaminer reproducibility and differences between right and left eyes were assessed using intraclass correlation coefficients (ICCs). Images were analyzed using ImageJ software. The developmental trajectories over time for ONH parameters were calculated using fractional polynomial modelling. Disc and cup diameter (expressed as distance in micrometers and visual angle in degrees), cup depth, Bruch's membrane opening-minimum rim width (BMO-MRW), retinal thickness, and retinal nerve fiber layer (RNFL; 1700 μm and 6° from the disc center). On average, 70% of participants were imaged successfully. Interexaminer reliability was excellent (ICC, >0.89) for diametric and retinal thickness parameters. Right and left eyes were similar for diametric measurements (ICC, >0.79), but more variable for nasal BMO-MRW, RNFL, and retinal thickness. The mean disc and cup diameter increase by 30% and 40%, respectively, between birth and 13 years of age when expressed as a distance measure, but remained constant (at 5°-5.5° and 2°, respectively) when expressed as a visual angle with reference to the eye nodal point. The peripapillary temporal RNFL demonstrated a marked initial decrease of nearly 35% between birth and approximately 18 months of age. This was followed by a slow increase up to 12 years of age when measured at 1700 μm from the disc center, although there was little change when measured at 6° from the disc center. We demonstrated feasibility of handheld SD OCT imaging of the ONH in full-term infants and children without anaesthesia or sedation. This is the first in vivo handheld SD OCT study to describe the development of ONH parameters during the critical early years of visual maturation. Our results provide a normative database for use in routine practice and further studies of ONH pathologic features. Copyright © 2016 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Measurement of food-related approach-avoidance biases: Larger biases when food stimuli are task relevant.

PubMed

Lender, Anja; Meule, Adrian; Rinck, Mike; Brockmeyer, Timo; Blechert, Jens

2018-06-01

Strong implicit responses to food have evolved to avoid energy depletion but contribute to overeating in today's affluent environments. The Approach-Avoidance Task (AAT) supposedly assesses implicit biases in response to food stimuli: Participants push pictures on a monitor "away" or pull them "near" with a joystick that controls a corresponding image zoom. One version of the task couples movement direction with image content-independent features, for example, pulling blue-framed images and pushing green-framed images regardless of content ('irrelevant feature version'). However, participants might selectively attend to this feature and ignore image content and, thus, such a task setup might underestimate existing biases. The present study tested this attention account by comparing two irrelevant feature versions of the task with either a more peripheral (image frame color: green vs. blue) or central (small circle vs. cross overlaid over the image content) image feature as response instruction to a 'relevant feature version', in which participants responded to the image content, thus making it impossible to ignore that content. Images of chocolate-containing foods and of objects were used, and several trait and state measures were acquired to validate the obtained biases. Results revealed a robust approach bias towards food only in the relevant feature condition. Interestingly, a positive correlation with state chocolate craving during the task was found when all three conditions were combined, indicative of criterion validity of all three versions. However, no correlations were found with trait chocolate craving. Results provide a strong case for the relevant feature version of the AAT for bias measurement. They also point to several methodological avenues for future research around selective attention in the irrelevant versions and task validity regarding trait vs. state variables. Copyright © 2018 Elsevier Ltd. All rights reserved.

A Novel Image Recuperation Approach for Diagnosing and Ranking Retinopathy Disease Level Using Diabetic Fundus Image

PubMed Central

2015-01-01

Retinal fundus images are widely used in diagnosing and providing treatment for several eye diseases. Prior works using retinal fundus images detected the presence of exudation with the aid of publicly available dataset using extensive segmentation process. Though it was proved to be computationally efficient, it failed to create a diabetic retinopathy feature selection system for transparently diagnosing the disease state. Also the diagnosis of diseases did not employ machine learning methods to categorize candidate fundus images into true positive and true negative ratio. Several candidate fundus images did not include more detailed feature selection technique for diabetic retinopathy. To apply machine learning methods and classify the candidate fundus images on the basis of sliding window a method called, Diabetic Fundus Image Recuperation (DFIR) is designed in this paper. The initial phase of DFIR method select the feature of optic cup in digital retinal fundus images based on Sliding Window Approach. With this, the disease state for diabetic retinopathy is assessed. The feature selection in DFIR method uses collection of sliding windows to obtain the features based on the histogram value. The histogram based feature selection with the aid of Group Sparsity Non-overlapping function provides more detailed information of features. Using Support Vector Model in the second phase, the DFIR method based on Spiral Basis Function effectively ranks the diabetic retinopathy diseases. The ranking of disease level for each candidate set provides a much promising result for developing practically automated diabetic retinopathy diagnosis system. Experimental work on digital fundus images using the DFIR method performs research on the factors such as sensitivity, specificity rate, ranking efficiency and feature selection time. PMID:25974230

Fourier domain image fusion for differential X-ray phase-contrast breast imaging.

PubMed

Coello, Eduardo; Sperl, Jonathan I; Bequé, Dirk; Benz, Tobias; Scherer, Kai; Herzen, Julia; Sztrókay-Gaul, Anikó; Hellerhoff, Karin; Pfeiffer, Franz; Cozzini, Cristina; Grandl, Susanne

2017-04-01

X-Ray Phase-Contrast (XPC) imaging is a novel technology with a great potential for applications in clinical practice, with breast imaging being of special interest. This work introduces an intuitive methodology to combine and visualize relevant diagnostic features, present in the X-ray attenuation, phase shift and scattering information retrieved in XPC imaging, using a Fourier domain fusion algorithm. The method allows to present complementary information from the three acquired signals in one single image, minimizing the noise component and maintaining visual similarity to a conventional X-ray image, but with noticeable enhancement in diagnostic features, details and resolution. Radiologists experienced in mammography applied the image fusion method to XPC measurements of mastectomy samples and evaluated the feature content of each input and the fused image. This assessment validated that the combination of all the relevant diagnostic features, contained in the XPC images, was present in the fused image as well. Copyright © 2017 Elsevier B.V. All rights reserved.

Accuracy and variability of texture-based radiomics features of lung lesions across CT imaging conditions

NASA Astrophysics Data System (ADS)

Zheng, Yuese; Solomon, Justin; Choudhury, Kingshuk; Marin, Daniele; Samei, Ehsan

2017-03-01

Texture analysis for lung lesions is sensitive to changing imaging conditions but these effects are not well understood, in part, due to a lack of ground-truth phantoms with realistic textures. The purpose of this study was to explore the accuracy and variability of texture features across imaging conditions by comparing imaged texture features to voxel-based 3D printed textured lesions for which the true values are known. The seven features of interest were based on the Grey Level Co-Occurrence Matrix (GLCM). The lesion phantoms were designed with three shapes (spherical, lobulated, and spiculated), two textures (homogenous and heterogeneous), and two sizes (diameter < 1.5 cm and 1.5 cm < diameter < 3 cm), resulting in 24 lesions (with a second replica of each). The lesions were inserted into an anthropomorphic thorax phantom (Multipurpose Chest Phantom N1, Kyoto Kagaku) and imaged using a commercial CT system (GE Revolution) at three CTDI levels (0.67, 1.42, and 5.80 mGy), three reconstruction algorithms (FBP, IR-2, IR-4), four reconstruction kernel types (standard, soft, edge), and two slice thicknesses (0.6 mm and 5 mm). Another repeat scan was performed. Texture features from these images were extracted and compared to the ground truth feature values by percent relative error. The variability across imaging conditions was calculated by standard deviation across a certain imaging condition for all heterogeneous lesions. The results indicated that the acquisition method has a significant influence on the accuracy and variability of extracted features and as such, feature quantities are highly susceptible to imaging parameter choices. The most influential parameters were slice thickness and reconstruction kernels. Thin slice thickness and edge reconstruction kernel overall produced more accurate and more repeatable results. Some features (e.g., Contrast) were more accurately quantified under conditions that render higher spatial frequencies (e.g., thinner slice thickness and sharp kernels), while others (e.g., Homogeneity) showed more accurate quantification under conditions that render smoother images (e.g., higher dose and smoother kernels). Care should be exercised is relating texture features between cases of varied acquisition protocols, with need to cross calibration dependent on the feature of interest.

Population differences in dysmorphic features among children with fetal alcohol spectrum disorders.

PubMed

May, Philip A; Gossage, J Phillip; Smith, Matthew; Tabachnick, Barbara G; Robinson, Luther K; Manning, Melanie; Cecanti, Mauro; Jones, Kenneth Lyons; Khaole, Nathaniel; Buckley, David; Kalberg, Wendy O; Trujillo, Phyllis M; Hoyme, H Eugene

2010-05-01

To examine the variation in significant dysmorphic features in children from 3 different populations with the most dysmorphic forms of fetal alcohol spectrum disorders, fetal alcohol syndrome (FAS), and partial fetal alcohol syndrome (PFAS). Advanced multiple regression techniques are used to determine the discriminating physical features in the diagnosis of FAS and PFAS among children from Northern Plains Indian communities, South Africa, and Italy. Within the range of physical features used to identify children with fetal alcohol spectrum disorders, specifically FAS and PFAS, there is some significant variation in salient diagnostic features from one population to the next. Intraclass correlations in diagnostic features between these 3 populations is 0.20, indicating that about 20% of the variability in dysmorphology core features is associated with location and, therefore, specific racial/ethnic population. The highly significant diagnostic indicators present in each population are identified for the full samples of FAS, PFAS, and normals and also among children with FAS only. A multilevel model for these populations combined indicates that these variables predict dysmorphology unambiguously: small palpebral fissures, narrow vermillion, smooth philtrum, flat nasal bridge, and fifth finger clinodactyly. Long philtrum varies substantially as a predictor in the 3 populations. Predictors not significantly related to fetal alcohol spectrum disorders dysmorphology across the 3 populations are centile of height (except in Italy) strabismus, interpupilary distance, intercanthal distance, and heart murmurs. The dysmorphology associated with FAS and PFAS vary across populations, yet a particular array of common features occurs in each population, which permits a consistent diagnosis across populations.

Socializing Young Readers: A Content Analysis of Body Size Images in Caldecott Medal Winners

ERIC Educational Resources Information Center

Wedwick, Linda; Latham, Nancy

2013-01-01

Many studies have examined gender issues in children's literature, but a review of the literature reveals that few studies have examined the instances of fatness in the images. Studying the fat representation in the images of children's literature is important because exposure to a variety of body types may slow the rate of children's body…

Reproducibility of radiomics for deciphering tumor phenotype with imaging

NASA Astrophysics Data System (ADS)

Zhao, Binsheng; Tan, Yongqiang; Tsai, Wei-Yann; Qi, Jing; Xie, Chuanmiao; Lu, Lin; Schwartz, Lawrence H.

2016-03-01

Radiomics (radiogenomics) characterizes tumor phenotypes based on quantitative image features derived from routine radiologic imaging to improve cancer diagnosis, prognosis, prediction and response to therapy. Although radiomic features must be reproducible to qualify as biomarkers for clinical care, little is known about how routine imaging acquisition techniques/parameters affect reproducibility. To begin to fill this knowledge gap, we assessed the reproducibility of a comprehensive, commonly-used set of radiomic features using a unique, same-day repeat computed tomography data set from lung cancer patients. Each scan was reconstructed at 6 imaging settings, varying slice thicknesses (1.25 mm, 2.5 mm and 5 mm) and reconstruction algorithms (sharp, smooth). Reproducibility was assessed using the repeat scans reconstructed at identical imaging setting (6 settings in total). In separate analyses, we explored differences in radiomic features due to different imaging parameters by assessing the agreement of these radiomic features extracted from the repeat scans reconstructed at the same slice thickness but different algorithms (3 settings in total). Our data suggest that radiomic features are reproducible over a wide range of imaging settings. However, smooth and sharp reconstruction algorithms should not be used interchangeably. These findings will raise awareness of the importance of properly setting imaging acquisition parameters in radiomics/radiogenomics research.

Laser interference effect evaluation method based on character of laser-spot and image feature

NASA Astrophysics Data System (ADS)

Tang, Jianfeng; Luo, Xiaolin; Wu, Lingxia

2016-10-01

Evaluating the laser interference effect to CCD objectively and accurately has great research value. Starting from the change of the image's feature before and after interference, meanwhile, considering the influence of the laser-spot distribution character on the masking degree of the image feature information, a laser interference effect evaluation method based on character of laser-spot and image feature was proposed. It reflected the laser-spot distribution character using the distance between the center of the laser-spot and center of the target. It reflected the change of the global image feature using the changes of image's sparse coefficient matrix, which was obtained by the SSIM-inspired orthogonal matching pursuit (OMP) sparse coding algorithm. What's more, the assessment method reflected the change of the local image feature using the changes of the image's edge sharpness, which could be obtained by the change of the image's gradient magnitude. Taken together, the laser interference effect can be evaluated accurately. In terms of the laser interference experiment results, the proposed method shows good rationality and feasibility under the disturbing condition of different laser powers, and it can also overcome the inaccuracy caused by the change of the laser-spot position, realizing the evaluation of the laser interference effect objectively and accurately.

Interpersonal and Affective Features of Psychopathy in Children and Adolescents: Advancing a Developmental Perspective--Introduction to Special Section

ERIC Educational Resources Information Center

Pardini, Dustin A.; Loeber, Rolf

2007-01-01

The interpersonal (e.g., manipulative, deceitful) and affective (e.g., callous, unemotional) features associated with adult psychopathy have been identified in children and adolescents. Although early research suggests that these features have clinical utility in identifying a particularly severe and recalcitrant form of antisocial behavior with…

Ecological Features of Preschools and the Social Engagement of Children with Autism

ERIC Educational Resources Information Center

Reszka, Stephanie S.; Odom, Samuel L.; Hume, Kara A.

2012-01-01

One way to support the social engagement of children with autism spectrum disorders (ASD) is by identifying features of natural environments that increase the likelihood of social interaction. This descriptive study was an examination of the (a) social engagement of 68 preschoolers with ASD in classrooms, (b) ecological features of classrooms that…

Motion tracking and electromyography assist the removal of mirror hand contributions to fNIRS images acquired during a finger tapping task performed by children with cerebral palsy

NASA Astrophysics Data System (ADS)

Hervey, Nathan; Khan, Bilal; Shagman, Laura; Tian, Fenghua; Delgado, Mauricio R.; Tulchin-Francis, Kirsten; Shierk, Angela; Smith, Linsley; Reid, Dahlia; Clegg, Nancy J.; Liu, Hanli; MacFarlane, Duncan; Alexandrakis, George

2013-03-01

Functional neurological imaging has been shown to be valuable in evaluating brain plasticity in children with cerebral palsy (CP). In recent studies it has been demonstrated that functional near-infrared spectroscopy (fNIRS) is a viable and sensitive method for imaging motor cortex activities in children with CP. However, during unilateral finger tapping tasks children with CP often exhibit mirror motions (unintended motions in the non-tapping hand), and current fNIRS image formation techniques do not account for this. Therefore, the resulting fNIRS images contain activation from intended and unintended motions. In this study, cortical activity was mapped with fNIRS on four children with CP and five controls during a finger tapping task. Finger motion and arm muscle activation were concurrently measured using motion tracking cameras and electromyography (EMG). Subject-specific regressors were created from motion capture and EMG data and used in a general linear model (GLM) analysis in an attempt to create fNIRS images representative of different motions. The analysis provided an fNIRS image representing activation due to motion and muscle activity for each hand. This method could prove to be valuable in monitoring brain plasticity in children with CP by providing more consistent images between measurements. Additionally, muscle effort versus cortical effort was compared between control and CP subjects. More cortical effort was required to produce similar muscle effort in children with CP. It is possible this metric could be a valuable diagnostic tool in determining response to treatment.

TU-A-12A-07: CT-Based Biomarkers to Characterize Lung Lesion: Effects of CT Dose, Slice Thickness and Reconstruction Algorithm Based Upon a Phantom Study

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

Zhao, B; Tan, Y; Tsai, W

2014-06-15

Purpose: Radiogenomics promises the ability to study cancer tumor genotype from the phenotype obtained through radiographic imaging. However, little attention has been paid to the sensitivity of image features, the image-based biomarkers, to imaging acquisition techniques. This study explores the impact of CT dose, slice thickness and reconstruction algorithm on measuring image features using a thorax phantom. Methods: Twentyfour phantom lesions of known volume (1 and 2mm), shape (spherical, elliptical, lobular and spicular) and density (-630, -10 and +100 HU) were scanned on a GE VCT at four doses (25, 50, 100, and 200 mAs). For each scan, six imagemore » series were reconstructed at three slice thicknesses of 5, 2.5 and 1.25mm with continuous intervals, using the lung and standard reconstruction algorithms. The lesions were segmented with an in-house 3D algorithm. Fifty (50) image features representing lesion size, shape, edge, and density distribution/texture were computed. Regression method was employed to analyze the effect of CT dose, slice of thickness and reconstruction algorithm on these features adjusting 3 confounding factors (size, density and shape of phantom lesions). Results: The coefficients of CT dose, slice thickness and reconstruction algorithm are presented in Table 1 in the supplementary material. No significant difference was found between the image features calculated on low dose CT scans (25mAs and 50mAs). About 50% texture features were found statistically different between low doses and high doses (100 and 200mAs). Significant differences were found for almost all features when calculated on 1.25mm, 2.5mm, and 5mm slice thickness images. Reconstruction algorithms significantly affected all density-based image features, but not morphological features. Conclusions: There is a great need to standardize the CT imaging protocols for radiogenomics study because CT dose, slice thickness and reconstruction algorithm impact quantitative image features to various degrees as our study has shown.« less

Designing augmentative and alternative communication applications: the results of focus groups with speech-language pathologists and parents of children with autism spectrum disorder.

PubMed

Boster, Jamie B; McCarthy, John W

2018-05-01

The purpose of this study was to gain insight from speech-language pathologists (SLPs) and parents of children with autism spectrum disorder (ASD) regarding appealing features of augmentative and alternative communication (AAC) applications. Two separate 1-hour focus groups were conducted with 8 SLPs and 5 parents of children with ASD to identify appealing design features of AAC Apps, their benefits and potential concerns. Participants were shown novel interface designs for communication mode, play mode and incentive systems. Participants responded to poll questions and provided benefits and drawbacks of the features as part of structured discussion. SLPs and parents identified a range of appealing features in communication mode (customization, animation and colour-coding) as well as in play mode (games and videos). SLPs preferred interfaces that supported motor planning and instruction while parents preferred those features such as character assistants that would appeal to their child. Overall SLPs and parents agreed on features for future AAC Apps. SLPs and parents have valuable input in regards to future AAC app design informed by their experiences with children with ASD. Both groups are key stakeholders in the design process and should be included in future design and research endeavors. Implications for Rehabilitation AAC applications for the iPad are often designed based on previous devices without consideration of new features. Ensuring the design of new interfaces are appealing and beneficial for children with ASD can potentially further support their communication. This study demonstrates how key stakeholders in AAC including speech language pathologists and parents can provide information to support the development of future AAC interface designs. Key stakeholders may be an untapped resource in the development of future AAC interfaces for children with ASD.

Control groups in paediatric epilepsy research: do first-degree cousins show familial effects?

PubMed

Hanson, Melissa; Morrison, Blaise; Jones, Jana E; Jackson, Daren C; Almane, Dace; Seidenberg, Michael; Zhao, Qianqian; Rathouz, Paul J; Hermann, Bruce P

2017-03-01

To determine whether first-degree cousins of children with idiopathic focal and genetic generalized epilepsies show any association across measures of cognition, behaviour, and brain structure. The presence/absence of associations addresses the question of whether and to what extent first-degree cousins may serve as unbiased controls in research addressing the cognitive, psychiatric, and neuroimaging features of paediatric epilepsies. Participants were children (aged 8-18) with epilepsy who had at least one first-degree cousin control enrolled in the study (n=37) and all enrolled cousin controls (n=100). Participants underwent neuropsychological assessment and brain imaging (cortical, subcortical, and cerebellar volumes), and parents completed the Child Behaviour Checklist (CBCL). Data (based on 42 outcome measures) from cousin controls were regressed on the corresponding epilepsy cognitive, behavioural, and imaging measures in a linear mixed model and case/control correlations were examined. Of the 42 uncorrected correlations involving cognitive, behavioural, and neuroimaging measures, only two were significant (p<0.05). The median correlation was 0.06. A test for whether the distribution of p values deviated from the null distribution under no association was not significant (p>0.25). Similar results held for the cognition/behaviour and brain imaging measures separately. Given the lack of association between cases and first-degree cousin performances on measures of cognition, behaviour, and neuroimaging, the results suggest a non-significant genetic influence on control group performance. First-degree cousins appear to be unbiased controls for cognitive, behavioural, and neuroimaging research in paediatric epilepsy.

Single-image-based Rain Detection and Removal via CNN

NASA Astrophysics Data System (ADS)

Chen, Tianyi; Fu, Chengzhou

2018-04-01

The quality of the image is degraded by rain streaks, which have negative impact when we extract image features for many visual tasks, such as feature extraction for classification and recognition, tracking, surveillance and autonomous navigation. Hence, it is necessary to detect and remove rain streaks from single images, which is a challenging problem since we have no spatial-temporal information of rain streaks compared to the dynamic video stream. Inspired by the priori that the rain streaks have almost the same feature, such as the direction or the thickness, although they are in different types of real-world images. The paper aims at proposing an effective convolutional neural network (CNN) to detect and remove rain streaks from single image. Two models of synthesized rainy image, linear additive composite model (LACM model) and screen blend model (SCM model), are considered in this paper. The main idea is that it is easier for our CNN network to find the mapping between the rainy image and rain streaks than between the rainy image and clean image. The reason is that rain streaks have fixed features, but clean images have various features. The experiments show that the designed CNN network outperforms state-of-the-art approaches on both synthesized and real-world images, which indicates the effectiveness of our proposed framework.

Research on simulated infrared image utility evaluation using deep representation

NASA Astrophysics Data System (ADS)

Zhang, Ruiheng; Mu, Chengpo; Yang, Yu; Xu, Lixin

2018-01-01

Infrared (IR) image simulation is an important data source for various target recognition systems. However, whether simulated IR images could be used as training data for classifiers depends on the features of fidelity and authenticity of simulated IR images. For evaluation of IR image features, a deep-representation-based algorithm is proposed. Being different from conventional methods, which usually adopt a priori knowledge or manually designed feature, the proposed method can extract essential features and quantitatively evaluate the utility of simulated IR images. First, for data preparation, we employ our IR image simulation system to generate large amounts of IR images. Then, we present the evaluation model of simulated IR image, for which an end-to-end IR feature extraction and target detection model based on deep convolutional neural network is designed. At last, the experiments illustrate that our proposed method outperforms other verification algorithms in evaluating simulated IR images. Cross-validation, variable proportion mixed data validation, and simulation process contrast experiments are carried out to evaluate the utility and objectivity of the images generated by our simulation system. The optimum mixing ratio between simulated and real data is 0.2≤γ≤0.3, which is an effective data augmentation method for real IR images.

[Callous and unemotional--do children have psychopathic features?].

PubMed

Laajasalo, Taina; Saukkonen, Suvi; Aronen, Eeva

2014-01-01

The essence of psychopathic personality disorder is considered to consist of emotional deviations, the most central ones of which being the lack of feelings of guilt and empathy along with impoverishment of experiencing emotions. The interest in the occurrence of these callous-unemotional features in children and adolescents has increased over the past few years. According to the most recent studies, parental interventions promoting a positive, warm, and attentive parenting and interaction style are effective in the treatment of children having a conduct disorder accompanied by callous-unemotional features.

Dynamic feature analysis of vector-based images for neuropsychological testing

NASA Astrophysics Data System (ADS)

Smith, Stephen L.; Cervantes, Basilio R.

1998-07-01

The dynamic properties of human motor activities, such as those observed in the course of drawing simple geometric shapes, are considerably more complex and often more informative than the goal to be achieved; in this case a static line drawing. This paper demonstrates how these dynamic properties may be used to provide a means of assessing a patient's visuo-spatial ability -- an important component of neuropsychological testing. The work described here provides a quantitative assessment of visuo-spatial ability, whilst preserving the conventional test environment. Results will be presented for a clinical population of long-term haemodialysis patients and test population comprises three groups of children (1) 7-8 years, (2) 9-10 years and (3) 11-12 years, all of which have no known neurological dysfunction. Ten new dynamic measurements extracted from patient responses in conjunction with one static feature deduced from earlier work describe a patient's visuo-spatial ability in a quantitative manner with sensitivity not previously attainable. The dynamic feature measurements in isolation provide a unique means of tracking a patient's approach to motor activities and could prove useful in monitoring a child' visuo-motor development.

Line fitting based feature extraction for object recognition

NASA Astrophysics Data System (ADS)

Li, Bing

2014-06-01

Image feature extraction plays a significant role in image based pattern applications. In this paper, we propose a new approach to generate hierarchical features. This new approach applies line fitting to adaptively divide regions based upon the amount of information and creates line fitting features for each subsequent region. It overcomes the feature wasting drawback of the wavelet based approach and demonstrates high performance in real applications. For gray scale images, we propose a diffusion equation approach to map information-rich pixels (pixels near edges and ridge pixels) into high values, and pixels in homogeneous regions into small values near zero that form energy map images. After the energy map images are generated, we propose a line fitting approach to divide regions recursively and create features for each region simultaneously. This new feature extraction approach is similar to wavelet based hierarchical feature extraction in which high layer features represent global characteristics and low layer features represent local characteristics. However, the new approach uses line fitting to adaptively focus on information-rich regions so that we avoid the feature waste problems of the wavelet approach in homogeneous regions. Finally, the experiments for handwriting word recognition show that the new method provides higher performance than the regular handwriting word recognition approach.

Building Facade Modeling Under Line Feature Constraint Based on Close-Range Images

NASA Astrophysics Data System (ADS)

Liang, Y.; Sheng, Y. H.

2018-04-01

To solve existing problems in modeling facade of building merely with point feature based on close-range images , a new method for modeling building facade under line feature constraint is proposed in this paper. Firstly, Camera parameters and sparse spatial point clouds data were restored using the SFM , and 3D dense point clouds were generated with MVS; Secondly, the line features were detected based on the gradient direction , those detected line features were fit considering directions and lengths , then line features were matched under multiple types of constraints and extracted from multi-image sequence. At last, final facade mesh of a building was triangulated with point cloud and line features. The experiment shows that this method can effectively reconstruct the geometric facade of buildings using the advantages of combining point and line features of the close - range image sequence, especially in restoring the contour information of the facade of buildings.

Vehicle license plate recognition based on geometry restraints and multi-feature decision

NASA Astrophysics Data System (ADS)

Wu, Jianwei; Wang, Zongyue

2005-10-01

Vehicle license plate (VLP) recognition is of great importance to many traffic applications. Though researchers have paid much attention to VLP recognition there has not been a fully operational VLP recognition system yet for many reasons. This paper discusses a valid and practical method for vehicle license plate recognition based on geometry restraints and multi-feature decision including statistical and structural features. In general, the VLP recognition includes the following steps: the location of VLP, character segmentation, and character recognition. This paper discusses the three steps in detail. The characters of VLP are always declining caused by many factors, which makes it more difficult to recognize the characters of VLP, therefore geometry restraints such as the general ratio of length and width, the adjacent edges being perpendicular are used for incline correction. Image Moment has been proved to be invariant to translation, rotation and scaling therefore image moment is used as one feature for character recognition. Stroke is the basic element for writing and hence taking it as a feature is helpful to character recognition. Finally we take the image moment, the strokes and the numbers of each stroke for each character image and some other structural features and statistical features as the multi-feature to match each character image with sample character images so that each character image can be recognized by BP neural net. The proposed method combines statistical and structural features for VLP recognition, and the result shows its validity and efficiency.

Prediction of troponin-T degradation using color image texture features in 10d aged beef longissimus steaks.

PubMed

Sun, X; Chen, K J; Berg, E P; Newman, D J; Schwartz, C A; Keller, W L; Maddock Carlin, K R

2014-02-01

The objective was to use digital color image texture features to predict troponin-T degradation in beef. Image texture features, including 88 gray level co-occurrence texture features, 81 two-dimension fast Fourier transformation texture features, and 48 Gabor wavelet filter texture features, were extracted from color images of beef strip steaks (longissimus dorsi, n = 102) aged for 10d obtained using a digital camera and additional lighting. Steaks were designated degraded or not-degraded based on troponin-T degradation determined on d 3 and d 10 postmortem by immunoblotting. Statistical analysis (STEPWISE regression model) and artificial neural network (support vector machine model, SVM) methods were designed to classify protein degradation. The d 3 and d 10 STEPWISE models were 94% and 86% accurate, respectively, while the d 3 and d 10 SVM models were 63% and 71%, respectively, in predicting protein degradation in aged meat. STEPWISE and SVM models based on image texture features show potential to predict troponin-T degradation in meat. © 2013.

Development of Embodied Word Meanings: Sensorimotor Effects in Children's Lexical Processing.

PubMed

Inkster, Michelle; Wellsby, Michele; Lloyd, Ellen; Pexman, Penny M

2016-01-01

Previous research showed an effect of words' rated body-object interaction (BOI) in children's visual word naming performance, but only in children 8 years of age or older (Wellsby and Pexman, 2014a). In that study, however, BOI was established using adult ratings. Here we collected ratings from a group of parents for children's BOI experience (child-BOI). We examined effects of words' child-BOI and also words' imageability on children's responses in an auditory word naming task, which is suited to the lexical processing skills of younger children. We tested a group of 54 children aged 6-7 years and a comparison group of 25 adults. Results showed significant effects of both imageability and child-BOI on children's auditory naming latencies. These results provide evidence that children younger than 8 years of age have richer semantic representations for high imageability and high child-BOI words, consistent with an embodied account of word meaning.

Character feature integration of Chinese calligraphy and font

NASA Astrophysics Data System (ADS)

Shi, Cao; Xiao, Jianguo; Jia, Wenhua; Xu, Canhui

2013-01-01

A framework is proposed in this paper to effectively generate a new hybrid character type by means of integrating local contour feature of Chinese calligraphy with structural feature of font in computer system. To explore traditional art manifestation of calligraphy, multi-directional spatial filter is applied for local contour feature extraction. Then the contour of character image is divided into sub-images. The sub-images in the identical position from various characters are estimated by Gaussian distribution. According to its probability distribution, the dilation operator and erosion operator are designed to adjust the boundary of font image. And then new Chinese character images are generated which possess both contour feature of artistical calligraphy and elaborate structural feature of font. Experimental results demonstrate the new characters are visually acceptable, and the proposed framework is an effective and efficient strategy to automatically generate the new hybrid character of calligraphy and font.

Texture feature extraction based on a uniformity estimation method for local brightness and structure in chest CT images.

PubMed

Peng, Shao-Hu; Kim, Deok-Hwan; Lee, Seok-Lyong; Lim, Myung-Kwan

2010-01-01

Texture feature is one of most important feature analysis methods in the computer-aided diagnosis (CAD) systems for disease diagnosis. In this paper, we propose a Uniformity Estimation Method (UEM) for local brightness and structure to detect the pathological change in the chest CT images. Based on the characteristics of the chest CT images, we extract texture features by proposing an extension of rotation invariant LBP (ELBP(riu4)) and the gradient orientation difference so as to represent a uniform pattern of the brightness and structure in the image. The utilization of the ELBP(riu4) and the gradient orientation difference allows us to extract rotation invariant texture features in multiple directions. Beyond this, we propose to employ the integral image technique to speed up the texture feature computation of the spatial gray level dependent method (SGLDM). Copyright © 2010 Elsevier Ltd. All rights reserved.

Image Quality Assessment of High-Resolution Satellite Images with Mtf-Based Fuzzy Comprehensive Evaluation Method

NASA Astrophysics Data System (ADS)

Wu, Z.; Luo, Z.; Zhang, Y.; Guo, F.; He, L.

2018-04-01

A Modulation Transfer Function (MTF)-based fuzzy comprehensive evaluation method was proposed in this paper for the purpose of evaluating high-resolution satellite image quality. To establish the factor set, two MTF features and seven radiant features were extracted from the knife-edge region of image patch, which included Nyquist, MTF0.5, entropy, peak signal to noise ratio (PSNR), average difference, edge intensity, average gradient, contrast and ground spatial distance (GSD). After analyzing the statistical distribution of above features, a fuzzy evaluation threshold table and fuzzy evaluation membership functions was established. The experiments for comprehensive quality assessment of different natural and artificial objects was done with GF2 image patches. The results showed that the calibration field image has the highest quality scores. The water image has closest image quality to the calibration field, quality of building image is a little poor than water image, but much higher than farmland image. In order to test the influence of different features on quality evaluation, the experiment with different weights were tested on GF2 and SPOT7 images. The results showed that different weights correspond different evaluating effectiveness. In the case of setting up the weights of edge features and GSD, the image quality of GF2 is better than SPOT7. However, when setting MTF and PSNR as main factor, the image quality of SPOT7 is better than GF2.

A novel biomedical image indexing and retrieval system via deep preference learning.

PubMed

Pang, Shuchao; Orgun, Mehmet A; Yu, Zhezhou

2018-05-01

The traditional biomedical image retrieval methods as well as content-based image retrieval (CBIR) methods originally designed for non-biomedical images either only consider using pixel and low-level features to describe an image or use deep features to describe images but still leave a lot of room for improving both accuracy and efficiency. In this work, we propose a new approach, which exploits deep learning technology to extract the high-level and compact features from biomedical images. The deep feature extraction process leverages multiple hidden layers to capture substantial feature structures of high-resolution images and represent them at different levels of abstraction, leading to an improved performance for indexing and retrieval of biomedical images. We exploit the current popular and multi-layered deep neural networks, namely, stacked denoising autoencoders (SDAE) and convolutional neural networks (CNN) to represent the discriminative features of biomedical images by transferring the feature representations and parameters of pre-trained deep neural networks from another domain. Moreover, in order to index all the images for finding the similarly referenced images, we also introduce preference learning technology to train and learn a kind of a preference model for the query image, which can output the similarity ranking list of images from a biomedical image database. To the best of our knowledge, this paper introduces preference learning technology for the first time into biomedical image retrieval. We evaluate the performance of two powerful algorithms based on our proposed system and compare them with those of popular biomedical image indexing approaches and existing regular image retrieval methods with detailed experiments over several well-known public biomedical image databases. Based on different criteria for the evaluation of retrieval performance, experimental results demonstrate that our proposed algorithms outperform the state-of-the-art techniques in indexing biomedical images. We propose a novel and automated indexing system based on deep preference learning to characterize biomedical images for developing computer aided diagnosis (CAD) systems in healthcare. Our proposed system shows an outstanding indexing ability and high efficiency for biomedical image retrieval applications and it can be used to collect and annotate the high-resolution images in a biomedical database for further biomedical image research and applications. Copyright © 2018 Elsevier B.V. All rights reserved.

The Power of Imageability: How the Acquisition of Inflected Forms Is Facilitated in Highly Imageable Verbs and Nouns in Czech Children

ERIC Educational Resources Information Center

Smolík, Filip; Kríž, Adam

2015-01-01

Imageability is the ability of words to elicit mental sensory images of their referents. Recent research has suggested that imageability facilitates the processing and acquisition of inflected word forms. The present study examined whether inflected word forms are acquired earlier in highly imageable words in Czech children. Parents of 317…

Texture Analysis and Cartographic Feature Extraction.

DTIC Science & Technology

1985-01-01

Investigations into using various image descriptors as well as developing interactive feature extraction software on the Digital Image Analysis Laboratory...system. Originator-supplied keywords: Ad-Hoc image descriptor; Bayes classifier; Bhattachryya distance; Clustering; Digital Image Analysis Laboratory

New breast cancer prognostic factors identified by computer-aided image analysis of HE stained histopathology images

PubMed Central

Chen, Jia-Mei; Qu, Ai-Ping; Wang, Lin-Wei; Yuan, Jing-Ping; Yang, Fang; Xiang, Qing-Ming; Maskey, Ninu; Yang, Gui-Fang; Liu, Juan; Li, Yan

2015-01-01

Computer-aided image analysis (CAI) can help objectively quantify morphologic features of hematoxylin-eosin (HE) histopathology images and provide potentially useful prognostic information on breast cancer. We performed a CAI workflow on 1,150 HE images from 230 patients with invasive ductal carcinoma (IDC) of the breast. We used a pixel-wise support vector machine classifier for tumor nests (TNs)-stroma segmentation, and a marker-controlled watershed algorithm for nuclei segmentation. 730 morphologic parameters were extracted after segmentation, and 12 parameters identified by Kaplan-Meier analysis were significantly associated with 8-year disease free survival (P < 0.05 for all). Moreover, four image features including TNs feature (HR 1.327, 95%CI [1.001 - 1.759], P = 0.049), TNs cell nuclei feature (HR 0.729, 95%CI [0.537 - 0.989], P = 0.042), TNs cell density (HR 1.625, 95%CI [1.177 - 2.244], P = 0.003), and stromal cell structure feature (HR 1.596, 95%CI [1.142 - 2.229], P = 0.006) were identified by multivariate Cox proportional hazards model to be new independent prognostic factors. The results indicated that CAI can assist the pathologist in extracting prognostic information from HE histopathology images for IDC. The TNs feature, TNs cell nuclei feature, TNs cell density, and stromal cell structure feature could be new prognostic factors. PMID:26022540

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

Galavis, P; Friedman, K; Chandarana, H

Purpose: Radiomics involves the extraction of texture features from different imaging modalities with the purpose of developing models to predict patient treatment outcomes. The purpose of this study is to investigate texture feature reproducibility across [18F]FDG PET/CT and [18F]FDG PET/MR imaging in patients with primary malignancies. Methods: Twenty five prospective patients with solid tumors underwent clinical [18F]FDG PET/CT scan followed by [18F]FDG PET/MR scans. In all patients the lesions were identified using nuclear medicine reports. The images were co-registered and segmented using an in-house auto-segmentation method. Fifty features, based on the intensity histogram, second and high order matrices, were extractedmore » from the segmented regions from both image data sets. One-way random-effects ANOVA model of the intra-class correlation coefficient (ICC) was used to establish texture feature correlations between both data sets. Results: Fifty features were classified based on their ICC values, which were found in the range from 0.1 to 0.86, in three categories: high, intermediate, and low. Ten features extracted from second and high-order matrices showed large ICC ≥ 0.70. Seventeen features presented intermediate 0.5 ≤ ICC ≤ 0.65 and the remaining twenty three presented low ICC ≤ 0.45. Conclusion: Features with large ICC values could be reliable candidates for quantification as they lead to similar results from both imaging modalities. Features with small ICC indicates a lack of correlation. Therefore, the use of these features as a quantitative measure will lead to different assessments of the same lesion depending on the imaging modality from where they are extracted. This study shows the importance of the need for further investigation and standardization of features across multiple imaging modalities.« less

Noise Gating Solar Images

NASA Astrophysics Data System (ADS)

DeForest, Craig; Seaton, Daniel B.; Darnell, John A.

2017-08-01

I present and demonstrate a new, general purpose post-processing technique, "3D noise gating", that can reduce image noise by an order of magnitude or more without effective loss of spatial or temporal resolution in typical solar applications.Nearly all scientific images are, ultimately, limited by noise. Noise can be direct Poisson "shot noise" from photon counting effects, or introduced by other means such as detector read noise. Noise is typically represented as a random variable (perhaps with location- or image-dependent characteristics) that is sampled once per pixel or once per resolution element of an image sequence. Noise limits many aspects of image analysis, including photometry, spatiotemporal resolution, feature identification, morphology extraction, and background modeling and separation.Identifying and separating noise from image signal is difficult. The common practice of blurring in space and/or time works because most image "signal" is concentrated in the low Fourier components of an image, while noise is evenly distributed. Blurring in space and/or time attenuates the high spatial and temporal frequencies, reducing noise at the expense of also attenuating image detail. Noise-gating exploits the same property -- "coherence" -- that we use to identify features in images, to separate image features from noise.Processing image sequences through 3-D noise gating results in spectacular (more than 10x) improvements in signal-to-noise ratio, while not blurring bright, resolved features in either space or time. This improves most types of image analysis, including feature identification, time sequence extraction, absolute and relative photometry (including differential emission measure analysis), feature tracking, computer vision, correlation tracking, background modeling, cross-scale analysis, visual display/presentation, and image compression.I will introduce noise gating, describe the method, and show examples from several instruments (including SDO/AIA , SDO/HMI, STEREO/SECCHI, and GOES-R/SUVI) that explore the benefits and limits of the technique.