A method to investigate the effect of shoe-hole size on surface marker movement when describing in-shoe joint kinematics using a multi-segment foot model.

PubMed

Bishop, Chris; Arnold, John B; Fraysse, Francois; Thewlis, Dominic

2015-01-01

To investigate in-shoe foot kinematics, holes are often cut in the shoe upper to allow markers to be placed on the skin surface. However, there is currently a lack of understanding as to what is an appropriate size. This study aimed to demonstrate a method to assess whether different diameter holes were large enough to allow free motion of marker wands mounted on the skin surface during walking using a multi-segment foot model. Eighteen participants underwent an analysis of foot kinematics whilst walking barefoot and wearing shoes with different size holes (15 mm, 20mm and 25 mm). The analysis was conducted in two parts; firstly the trajectory of the individual skin-mounted markers were analysed in a 2D ellipse to investigate total displacement of each marker during stance. Secondly, a geometrical analysis was conducted to assess cluster deformation of the hindfoot and midfoot-forefoot segments. Where movement of the markers in the 15 and 20mm conditions were restricted, the marker movement in the 25 mm condition did not exceed the radius at any anatomical location. Despite significant differences in the isotropy index of the medial and lateral calcaneus markers between the 25 mm and barefoot conditions, the differences were due to the effect of footwear on the foot and not a result of the marker wands hitting the shoe upper. In conclusion, the method proposed and results can be used to increase confidence in the representativeness of joint kinematics with respect to in-shoe multi-segment foot motion during walking. Crown Copyright © 2014. Published by Elsevier B.V. All rights reserved.

A comparison of subtalar joint motion during anticipated medial cutting turns and level walking using a multi-segment foot model.

PubMed

Jenkyn, T R; Shultz, R; Giffin, J R; Birmingham, T B

2010-02-01

The weight-bearing in-vivo kinematics and kinetics of the talocrural joint, subtalar joint and joints of the foot were quantified using optical motion analysis. Twelve healthy subjects were studied during level walking and anticipated medial turns at self-selected pace. A multi-segment model of the foot using skin-mounted marker triads tracked four foot segments: the hindfoot, midfoot, lateral and medial forefoot. The lower leg and thigh were also tracked. Motion between each of the segments could occur in three degrees of rotational freedom, but only six inter-segmental motions were reported in this study: (1) talocrural dorsi-plantar-flexion, (2) subtalar inversion-eversion, (3) frontal plane hindfoot motion, (4) transverse plane hindfoot motion, (5) forefoot supination-pronation twisting and (6) the height-to-length ratio of the medial longitudinal arch. The motion at the subtalar joint during stance phase of walking (eversion then inversion) was reversed during a turning task (inversion then eversion). The external subtalar joint moment was also changed from a moderate eversion moment during walking to a larger inversion moment during the turn. The kinematics of the talocrural joint and the joints of the foot were similar between these two tasks. During a medial turn, the subtalar joint may act to maintain the motions in the foot and talocrural joint that occur during level walking. This is occurring despite the conspicuously different trajectory of the centre of mass of the body. This may allow the foot complex to maintain its function of energy absorption followed by energy return during stance phase that is best suited to level walking. Copyright 2009 Elsevier B.V. All rights reserved.

Radiographic-directed local coordinate systems critical in kinematic analysis of walking in diabetes-related medial column foot deformity.

PubMed

Hastings, Mary K; Woodburn, James; Mueller, Michael J; Strube, Michael J; Johnson, Jeffrey E; Beckert, Krista S; Stein, Michelle L; Sinacore, David R

2014-01-01

Diabetic foot deformity onset and progression maybe associated with abnormal foot and ankle motion. The modified Oxford multi-segmental foot model allows kinematic assessment of inter-segmental foot motion. However, there are insufficient anatomical landmarks to accurately representation the alignment of the hindfoot and forefoot segments during model construction. This is most notable for the sagittal plane which is referenced parallel to the floor, allowing comparison of inter-segmental excursion but not capturing important sagittal hind-to-forefoot deformity associated with diabetic foot disease and can potentially underestimate true kinematic differences. The purpose of the study was to compare walking kinematics using local coordinate systems derived from the modified Oxford model and the radiographic directed model which incorporated individual calcaneal and 1st metatarsal declination pitch angles for the hindfoot and forefoot. We studied twelve participants in each of the following groups: (1) diabetes mellitus, peripheral neuropathy and medial column foot deformity (DMPN+), (2) DMPN without medial column deformity (DMPN-) and (3) age- and weight-match controls. The modified Oxford model coordinate system did not identify differences between groups in the initial, peak, final, or excursion hindfoot relative to shank or forefoot relative to hindfoot dorsiflexion/plantarflexion during walking. The radiographic coordinate system identified the DMPN+ group to have an initial, peak and final position of the forefoot relative to hindfoot that was more dorsiflexed (lower arch phenotype) than the DMPN- group (p<.05). Use of radiographic alignment in kinematic modeling of those with foot deformity reveals segmental motion occurring upon alignment indicative of a lower arch. Copyright © 2014 Elsevier B.V. All rights reserved.

Multi-segment foot kinematics after total ankle replacement and ankle arthrodesis during relatively long-distance gait.

PubMed

Rouhani, H; Favre, J; Aminian, K; Crevoisier, X

2012-07-01

This study aimed to investigate the influence of ankle osteoarthritis (AOA) treatments, i.e., ankle arthrodesis (AA) and total ankle replacement (TAR), on the kinematics of multi-segment foot and ankle complex during relatively long-distance gait. Forty-five subjects in four groups (AOA, AA, TAR, and control) were equipped with a wearable system consisting of inertial sensors installed on the tibia, calcaneus, and medial metatarsals. The subjects walked 50-m twice while the system measured the kinematic parameters of their multi-segment foot: the range of motion of joints between tibia, calcaneus, and medial metatarsals in three anatomical planes, and the peaks of angular velocity of these segments in the sagittal plane. These parameters were then compared among the four groups. It was observed that the range of motion and peak of angular velocities generally improved after TAR and were similar to the control subjects. However, unlike AOA and TAR, AA imposed impairments in the range of motion in the coronal plane for both the tibia-calcaneus and tibia-metatarsals joints. In general, the kinematic parameters showed significant correlation with established clinical scales (FFI and AOFAS), which shows their convergent validity. Based on the kinematic parameters of multi-segment foot during 50-m gait, this study showed significant improvements in foot mobility after TAR, but several significant impairments remained after AA. Copyright © 2012 Elsevier B.V. All rights reserved.

Foot posture is associated with kinematics of the foot during gait: A comparison of normal, planus and cavus feet.

PubMed

Buldt, Andrew K; Levinger, Pazit; Murley, George S; Menz, Hylton B; Nester, Christopher J; Landorf, Karl B

2015-06-01

Variations in foot posture are associated with the development of some lower limb injuries. However, the mechanisms underlying this relationship are unclear. The objective of this study was to compare foot kinematics between normal, pes cavus and pes planus foot posture groups using a multi-segment foot model. Ninety-seven healthy adults, aged 18-47 were classified as either normal (n=37), pes cavus (n=30) or pes planus (n=30) based on normative data for the Foot Posture Index, Arch Index and normalised navicular height. A five segment foot model was used to measure tri-planar motion of the rearfoot, midfoot, medial forefoot, lateral forefoot and hallux during barefoot walking at a self-selected speed. Angle at heel contact, peak angle, time to peak angle and range of motion was measured for each segment. One way ANOVAs with post-hoc analyses of mean differences were used to compare foot posture groups. The pes cavus group demonstrated a distinctive pattern of motion compared to the normal and pes planus foot posture groups. Effect sizes of significant mean differences were large and comparable to similar studies. Three key differences in overall foot function were observed between the groups: (i) altered frontal and transverse plane angles of the rearfoot in the pes cavus foot; (ii) Less midfoot motion in the pes cavus foot during initial contact and midstance; and (iii) reduced midfoot frontal plane ROM in the pes planus foot during pre-swing. These findings indicate that foot posture does influence motion of the foot. Copyright © 2015 Elsevier B.V. All rights reserved.

Inter-segmental motions of the foot: differences between younger and older healthy adult females.

PubMed

Lee, Dong Yeon; Seo, Sang Gyo; Kim, Eo Jin; Lee, Doo Jae; Bae, Kee Jeong; Lee, Kyoung Min; Choi, In Ho

2017-01-01

Although accumulative evidence exists that support the applicability of multi-segmental foot models (MFMs) in evaluating foot motion in various pathologic conditions, little is known of the effect of aging on inter-segmental foot motion. The objective of this study was to evaluate differences in inter-segmental motion of the foot between older and younger adult healthy females during gait using a MFM with 15-marker set. One hundred symptom-free females, who had no radiographic evidence of osteoarthritis, were evaluated using MFM with 15-marker set. They were divided into young ( n  = 50, 20-35 years old) and old ( n  = 50, 60-69 years old) groups. Coefficients of multiple correlations were evaluated to assess the similarity of kinematic curve. Inter-segmental angles (hindfoot, forefoot, and hallux) were calculated at each gait phase. To evaluate the effect of gait speed on intersegmental foot motion, subgroup analysis was performed according to the similar speed of walking. Kinematic curves showed good or excellent similarity in most parameters. Range of motion in the sagittal ( p  < 0.001) and transverse ( p  = 0.001) plane of the hallux, and sagittal ( p  = 0.023) plane of the forefoot was lower in older females. The dorsiflexion ( p  = 0.001) of the hallux at terminal stance and pre-swing phases was significantly lower in older females. When we compared young and older females with similar speed, these differences remained. Although the overall kinematic pattern was similar between young and older females, reduced range of inter-segmental motion was observed in the older group. Our results suggest that age-related changes need to be considered in studies evaluating inter-segmental motion of the foot.

A clinically applicable six-segmented foot model.

PubMed

De Mits, Sophie; Segers, Veerle; Woodburn, Jim; Elewaut, Dirk; De Clercq, Dirk; Roosen, Philip

2012-04-01

We describe a multi-segmented foot model comprising lower leg, rearfoot, midfoot, lateral forefoot, medial forefoot, and hallux for routine use in a clinical setting. The Ghent Foot Model describes the kinematic patterns of functional units of the foot, especially the midfoot, to investigate patient populations where midfoot deformation or dysfunction is an important feature, for example, rheumatoid arthritis patients. Data were obtained from surface markers by a 6 camera motion capture system at 500 Hz. Ten healthy subjects walked barefoot along a 12 m walkway at self-selected speed. Joint angles (rearfoot to shank, midfoot to rearfoot, lateral and medial forefoot to midfoot, and hallux to medial forefoot) in the sagittal, frontal, and transverse plane are reported according to anatomically based reference frames. These angles were calculated and reported during the foot rollover phases in stance, detected by synchronized plantar pressure measurements. Repeated measurements of each subject revealed low intra-subject variability, varying between 0.7° and 2.3° for the minimum values, between 0.5° and 2.1° for the maximum values, and between 0.8° and 5.8° for the ROM. The described movement patterns were repeatable and consistent with biomechanical and clinical knowledge. As such, the Ghent Foot model permits intersegment, in vivo motion measurement of the foot, which is crucial for both clinical and research applications. Copyright © 2011 Orthopaedic Research Society.

Reliability study of tibialis posterior and selected leg muscle EMG and multi-segment foot kinematics in rheumatoid arthritis associated pes planovalgus

PubMed Central

Barn, Ruth; Rafferty, Daniel; Turner, Deborah E.; Woodburn, James

2012-01-01

Objective To determine within- and between-day reliability characteristics of electromyographic (EMG) activity patterns of selected lower leg muscles and kinematic variables in patients with rheumatoid arthritis (RA) and pes planovalgus. Methods Five patients with RA underwent gait analysis barefoot and shod on two occasions 1 week apart. Fine-wire (tibialis posterior [TP]) and surface EMG for selected muscles and 3D kinematics using a multi-segmented foot model was undertaken barefoot and shod. Reliability of pre-determined variables including EMG activity patterns and inter-segment kinematics were analysed using coefficients of multiple correlation, intraclass correlation coefficients (ICC) and the standard error of the measurement (SEM). Results Muscle activation patterns within- and between-day ranged from fair-to-good to excellent in both conditions. Discrete temporal and amplitude variables were highly variable across all muscle groups in both conditions but particularly poor for TP and peroneus longus. SEMs ranged from 1% to 9% of stance and 4% to 27% of maximum voluntary contraction; in most cases the 95% confidence interval crossed zero. Excellent within-day reliability was found for the inter-segment kinematics in both conditions. Between-day reliability ranged from fair-to-good to excellent for kinematic variables and all ICCs were excellent; the SEM ranged from 0.60° to 1.99°. Conclusion Multi-segmented foot kinematics can be reliably measured in RA patients with pes planovalgus. Serial measurement of discrete variables for TP and other selected leg muscles via EMG is not supported from the findings in this cohort of RA patients. Caution should be exercised when EMG measurements are considered to study disease progression or intervention effects. PMID:22721819

Multi-segment foot kinematics and ground reaction forces during gait of individuals with plantar fasciitis.

PubMed

Chang, Ryan; Rodrigues, Pedro A; Van Emmerik, Richard E A; Hamill, Joseph

2014-08-22

Clinically, plantar fasciitis (PF) is believed to be a result and/or prolonged by overpronation and excessive loading, but there is little biomechanical data to support this assertion. The purpose of this study was to determine the differences between healthy individuals and those with PF in (1) rearfoot motion, (2) medial forefoot motion, (3) first metatarsal phalangeal joint (FMPJ) motion, and (4) ground reaction forces (GRF). We recruited healthy (n=22) and chronic PF individuals (n=22, symptomatic over three months) of similar age, height, weight, and foot shape (p>0.05). Retro-reflective skin markers were fixed according to a multi-segment foot and shank model. Ground reaction forces and three dimensional kinematics of the shank, rearfoot, medial forefoot, and hallux segment were captured as individuals walked at 1.35 ms(-1). Despite similarities in foot anthropometrics, when compared to healthy individuals, individuals with PF exhibited significantly (p<0.05) (1) greater total rearfoot eversion, (2) greater forefoot plantar flexion at initial contact, (3) greater total sagittal plane forefoot motion, (4) greater maximum FMPJ dorsiflexion, and (5) decreased vertical GRF during propulsion. These data suggest that compared to healthy individuals, individuals with PF exhibit significant differences in foot kinematics and kinetics. Consistent with the theoretical injury mechanisms of PF, we found these individuals to have greater total rearfoot eversion and peak FMPJ dorsiflexion, which may put undue loads on the plantar fascia. Meanwhile, increased medial forefoot plantar flexion at initial contact and decreased propulsive GRF are suggestive of compensatory responses, perhaps to manage pain. Copyright © 2014 Elsevier Ltd. All rights reserved.

Differences in foot kinematics between young and older adults during walking.

PubMed

Arnold, John B; Mackintosh, Shylie; Jones, Sara; Thewlis, Dominic

2014-02-01

Our understanding of age-related changes to foot function during walking has mainly been based on plantar pressure measurements, with little information on differences in foot kinematics between young and older adults. The purpose of this study was to investigate the differences in foot kinematics between young and older adults during walking using a multi-segment foot model. Joint kinematics of the foot and ankle for 20 young (mean age 23.2 years, standard deviation (SD) 3.0) and 20 older adults (mean age 73.2 years, SD 5.1) were quantified during walking with a 12 camera Vicon motion analysis system using a five segment kinematic model. Differences in kinematics were compared between older adults and young adults (preferred and slow walking speeds) using Student's t-tests or if indicated, Mann-Whitney U tests. Effect sizes (Cohen's d) for the differences were also computed. The older adults had a less plantarflexed calcaneus at toe-off (-9.6° vs. -16.1°, d = 1.0, p = <0.001), a smaller sagittal plane range of motion (ROM) of the midfoot (11.9° vs. 14.8°, d = 1.3, p = <0.001) and smaller coronal plane ROM of the metatarsus (3.2° vs. 4.3°, d = 1.1, p = 0.006) compared to the young adults. Walking speed did not influence these differences, as they remained present when groups walked at comparable speeds. The findings of this study indicate that independent of walking speed, older adults exhibit significant differences in foot kinematics compared to younger adults, characterised by less propulsion and reduced mobility of multiple foot segments. Copyright © 2013 Elsevier B.V. All rights reserved.

Multi-segment foot landing kinematics in subjects with chronic ankle instability.

PubMed

De Ridder, Roel; Willems, Tine; Vanrenterghem, Jos; Robinson, Mark A; Palmans, Tanneke; Roosen, Philip

2015-07-01

Chronic ankle instability has been associated with altered joint kinematics at the ankle, knee and hip. However, no studies have investigated possible kinematic deviations at more distal segments of the foot. The purpose of this study was to evaluate if subjects with ankle instability and copers show altered foot and ankle kinematics and altered kinetics during a landing task when compared to controls. Ninety-six subjects (38 subjects with chronic ankle instability, 28 copers and 30 controls) performed a vertical drop and side jump task. Foot kinematics were obtained using the Ghent Foot Model and a single-segment foot model. Group differences were evaluated using statistical parametric mapping and analysis of variance. Subjects with ankle instability had a more inverted midfoot position in relation to the rearfoot when compared to controls during the side jump. They also had a greater midfoot inversion/eversion range of motion than copers during the vertical drop. Copers exhibited less plantar flexion/dorsiflexion range of motion in the lateral and medial forefoot. Furthermore, the ankle instability and coper group exhibited less ankle plantar flexion at touchdown. Additionally, the ankle instability group demonstrated a decreased plantar flexion/dorsiflexion range of motion at the ankle compared to the control group. Analysis of ground reaction forces showed a higher vertical peak and loading rate during the vertical drop in subjects with ankle instability. Subjects with chronic ankle instability displayed an altered, stiffer kinematic landing strategy and related alterations in landing kinetics, which might predispose them for episodes of giving way and actual ankle sprains. Copyright © 2015 Elsevier Ltd. All rights reserved.

Ankle and Midfoot Power During Walking and Stair Ascent in Healthy Adults.

PubMed

DiLiberto, Frank E; Nawoczenski, Deborah A; Houck, Jeff

2018-02-27

Ankle power dominates forward propulsion of gait, but midfoot power generation is also important for successful push off. However, it is unclear if midfoot power generation increases or stays the same in response to propulsive activities that induce larger external loads and require greater ankle power. The purpose of this study was to examine ankle and midfoot power in healthy adults during progressively more demanding functional tasks. Multi-segment foot motion (tibia, calcaneus, forefoot) and ground reaction forces were recorded as participants (N=12) walked, ascended a standard step, and ascended a high step. Ankle and midfoot positive peak power and total power, and the proportion of midfoot to ankle total power were calculated. One-way repeated measures ANOVAs were conducted to evaluate differences across tasks. Main effects were found for ankle and midfoot peak and total powers (all p < .001), but not for the proportion of midfoot to ankle total power (p = .331). Ankle and midfoot power significantly increased across each task. Midfoot power increased in proportion to ankle power and in congruence to the external load of a task. Study findings may serve to inform multi-segment foot modeling applications and internal mechanistic theories of normal and pathological foot function.

Foot function is well preserved in children and adolescents with juvenile idiopathic arthritis who are optimally managed

PubMed Central

Hendry, Gordon J.; Rafferty, Danny; Barn, Ruth; Gardner-Medwin, Janet; Turner, Debbie E.; Woodburn, James

2013-01-01

Purpose The objective of this study was to compare disease activity, impairments, disability, foot function and gait characteristics between a well described cohort of juvenile idiopathic arthritis (JIA) patients and normal healthy controls using a 7-segment foot model and three-dimensional gait analysis. Methods Fourteen patients with JIA (mean (standard deviation) age of 12.4 years (3.2)) and a history of foot disease and 10 healthy children (mean (standard deviation) age of 12.5 years (3.4)) underwent three-dimensional gait analysis and plantar pressure analysis to measure biomechanical foot function. Localised disease impact and foot-specific disease activity were determined using the juvenile arthritis foot disability index, rear- and forefoot deformity scores, and clinical and musculoskeletal ultrasound examinations respectively. Mean differences between groups with associated 95% confidence intervals were calculated using the t distribution. Results Mild-to-moderate foot impairments and disability but low levels of disease activity were detected in the JIA group. In comparison with healthy subjects, minor trends towards increased midfoot dorsiflexion and reduced lateral forefoot abduction within a 3–5° range were observed in patients with JIA. The magnitude and timing of remaining kinematic, kinetic and plantar pressure distribution variables during the stance phase were similar for both groups. Conclusion In children and adolescents with JIA, foot function as determined by a multi-segment foot model did not differ from that of normal age- and gender-matched subjects despite moderate foot impairments and disability scores. These findings may indicate that tight control of active foot disease may prevent joint destruction and associated structural and functional impairments. PMID:23142184

Multiple linear regression approach for the analysis of the relationships between joints mobility and regional pressure-based parameters in the normal-arched foot.

PubMed

Caravaggi, Paolo; Leardini, Alberto; Giacomozzi, Claudia

2016-10-03

Plantar load can be considered as a measure of the foot ability to transmit forces at the foot/ground, or foot/footwear interface during ambulatory activities via the lower limb kinematic chain. While morphological and functional measures have been shown to be correlated with plantar load, no exhaustive data are currently available on the possible relationships between range of motion of foot joints and plantar load regional parameters. Joints' kinematics from a validated multi-segmental foot model were recorded together with plantar pressure parameters in 21 normal-arched healthy subjects during three barefoot walking trials. Plantar pressure maps were divided into six anatomically-based regions of interest associated to corresponding foot segments. A stepwise multiple regression analysis was performed to determine the relationships between pressure-based parameters, joints range of motion and normalized walking speed (speed/subject height). Sagittal- and frontal-plane joint motion were those most correlated to plantar load. Foot joints' range of motion and normalized walking speed explained between 6% and 43% of the model variance (adjusted R 2 ) for pressure-based parameters. In general, those joints' presenting lower mobility during stance were associated to lower vertical force at forefoot and to larger mean and peak pressure at hindfoot and forefoot. Normalized walking speed was always positively correlated to mean and peak pressure at hindfoot and forefoot. While a large variance in plantar pressure data is still not accounted for by the present models, this study provides statistical corroboration of the close relationship between joint mobility and plantar pressure during stance in the normal healthy foot. Copyright © 2016 Elsevier Ltd. All rights reserved.

Frontal plane multi-segment foot kinematics in high- and low-arched females during dynamic loading tasks.

PubMed

Powell, Douglas W; Long, Benjamin; Milner, Clare E; Zhang, Songning

2011-02-01

The functions of the medial longitudinal arch have been the focus of much research in recent years. Several studies have shown kinematic differences between high- and low-arched runners. No literature currently compares the inter-segmental foot motion of high- and low-arched recreational athletes. The purpose of this study was to examine inter-segmental foot motion in the frontal plane during dynamic loading activities in high- and low-arched female athletes. Inter-segmental foot motions were examined in 10 high- and 10 low-arched female recreational athletes. Subjects performed five barefooted trials in each of the following randomized movements: walking, running, downward stepping and landing. Three-dimensional kinematic data were recorded. High-arched athletes had smaller peak ankle eversion angles in walking, running and downward stepping than low-arched athletes. At the rear-midfoot joint high-arched athletes reached peak eversion later in walking and downward stepping than the low-arched athletes. The high-arched athletes had smaller peak mid-forefoot eversion angles in walking, running and downward stepping than the low-arched athletes. The current findings show that differences in foot kinematics between the high- and low-arched athletes were in position and not range of motion within the foot. Copyright © 2010 Elsevier B.V. All rights reserved.

The Glasgow-Maastricht foot model, evaluation of a 26 segment kinematic model of the foot.

PubMed

Oosterwaal, Michiel; Carbes, Sylvain; Telfer, Scott; Woodburn, James; Tørholm, Søren; Al-Munajjed, Amir A; van Rhijn, Lodewijk; Meijer, Kenneth

2016-01-01

Accurately measuring of intrinsic foot kinematics using skin mounted markers is difficult, limited in part by the physical dimensions of the foot. Existing kinematic foot models solve this problem by combining multiple bones into idealized rigid segments. This study presents a novel foot model that allows the motion of the 26 bones to be individually estimated via a combination of partial joint constraints and coupling the motion of separate joints using kinematic rhythms. Segmented CT data from one healthy subject was used to create a template Glasgow-Maastricht foot model (GM-model). Following this, the template was scaled to produce subject-specific models for five additional healthy participants using a surface scan of the foot and ankle. Forty-three skin mounted markers, mainly positioned around the foot and ankle, were used to capture the stance phase of the right foot of the six healthy participants during walking. The GM-model was then applied to calculate the intrinsic foot kinematics. Distinct motion patterns where found for all joints. The variability in outcome depended on the location of the joint, with reasonable results for sagittal plane motions and poor results for transverse plane motions. The results of the GM-model were comparable with existing literature, including bone pin studies, with respect to the range of motion, motion pattern and timing of the motion in the studied joints. This novel model is the most complete kinematic model to date. Further evaluation of the model is warranted.

Gait kinematics of subjects with ankle instability using a multisegmented foot model.

PubMed

De Ridder, Roel; Willems, Tine; Vanrenterghem, Jos; Robinson, Mark; Pataky, Todd; Roosen, Philip

2013-11-01

Many patients who sustain an acute lateral ankle sprain develop chronic ankle instability (CAI). Altered ankle kinematics have been reported to play a role in the underlying mechanisms of CAI. In previous studies, however, the foot was modeled as one rigid segment, ignoring the complexity of the ankle and foot anatomy and kinematics. The purpose of this study was to evaluate stance phase kinematics of subjects with CAI, copers, and controls during walking and running using both a rigid and a multisegmented foot model. Foot and ankle kinematics of 77 subjects (29 subjects with self-reported CAI, 24 copers, and 24 controls) were measured during barefoot walking and running using a rigid foot model and a six-segment Ghent Foot Model. Data were collected on a 20-m-long instrumented runway embedded with a force plate and a six-camera optoelectronic system. Groups were compared using statistical parametric mapping. Both the CAI and the coper group showed similar differences during midstance and late stance compared with the control group (P < 0.05). The rigid foot segment showed a more everted position during walking compared with the control group. Based on the Ghent Foot Model, the rear foot also showed a more everted position during running. The medial forefoot showed a more inverted position for both running and walking compared with the control group. Our study revealed significant midstance and late stance differences in rigid foot, rear foot, and medial forefoot kinematics The multisegmented foot model demonstrated intricate behavior of the foot that is not detectable with rigid foot modeling. Further research using these models is necessary to expand knowledge of foot kinematics in subjects with CAI.

Reliability of a Seven-Segment Foot Model with Medial and Lateral Midfoot and Forefoot Segments During Walking Gait.

PubMed

Cobb, Stephen C; Joshi, Mukta N; Pomeroy, Robin L

2016-12-01

In-vitro and invasive in-vivo studies have reported relatively independent motion in the medial and lateral forefoot segments during gait. However, most current surface-based models have not defined medial and lateral forefoot or midfoot segments. The purpose of the current study was to determine the reliability of a 7-segment foot model that includes medial and lateral midfoot and forefoot segments during walking gait. Three-dimensional positions of marker clusters located on the leg and 6 foot segments were tracked as 10 participants completed 5 walking trials. To examine the reliability of the foot model, coefficients of multiple correlation (CMC) were calculated across the trials for each participant. Three-dimensional stance time series and range of motion (ROM) during stance were also calculated for each functional articulation. CMCs for all of the functional articulations were ≥ 0.80. Overall, the rearfoot complex (leg-calcaneus segments) was the most reliable articulation and the medial midfoot complex (calcaneus-navicular segments) was the least reliable. With respect to ROM, reliability was greatest for plantarflexion/dorsiflexion and least for abduction/adduction. Further, the stance ROM and time-series patterns results between the current study and previous invasive in-vivo studies that have assessed actual bone motion were generally consistent.

Manipulating the fidelity of lower extremity visual feedback to identify obstacle negotiation strategies in immersive virtual reality.

PubMed

Kim, Aram; Zhou, Zixuan; Kretch, Kari S; Finley, James M

2017-07-01

The ability to successfully navigate obstacles in our environment requires integration of visual information about the environment with estimates of our body's state. Previous studies have used partial occlusion of the visual field to explore how information about the body and impending obstacles are integrated to mediate a successful clearance strategy. However, because these manipulations often remove information about both the body and obstacle, it remains to be seen how information about the lower extremities alone is utilized during obstacle crossing. Here, we used an immersive virtual reality (VR) interface to explore how visual feedback of the lower extremities influences obstacle crossing performance. Participants wore a head-mounted display while walking on treadmill and were instructed to step over obstacles in a virtual corridor in four different feedback trials. The trials involved: (1) No visual feedback of the lower extremities, (2) an endpoint-only model, (3) a link-segment model, and (4) a volumetric multi-segment model. We found that the volumetric model improved success rate, placed their trailing foot before crossing and leading foot after crossing more consistently, and placed their leading foot closer to the obstacle after crossing compared to no model. This knowledge is critical for the design of obstacle negotiation tasks in immersive virtual environments as it may provide information about the fidelity necessary to reproduce ecologically valid practice environments.

Foot structure is significantly associated to subtalar joint kinetics and mechanical energetics.

PubMed

Maharaj, Jayishni N; Cresswell, Andrew G; Lichtwark, Glen A

2017-10-01

Foot structure has been implicated as a risk factor of numerous overuse injuries, however, the mechanism linking foot structure and the development of soft-tissue overuse injuries are not well understood. The aim of this study was to identify factors that could predict foot function during walking. A total of eleven variables (including measures of foot structure, anthropometry and spatiotemporal gait characteristics) were investigated for their predictive ability on identifying kinematic, kinetic and energetic components of the foot. Three-dimensional motion capture and force data were collected at preferred walking speed on an instrumented treadmill. Mechanical measures were subsequently assessed using a custom multi-segment foot model in Opensim. Factors with significant univariate associations were entered into multiple linear regression models to identify a group of factors independently associated with the mechanical measures. Although no model could be created for any of the kinematic measures analysed, approximately 46% and 37% of the variance in the kinetic and energetic measures were associated with three or two factors respectively. Arch-height ratio, foot length and step width were associated with peak subtalar joint (STJ) moment, while greater STJ negative work was correlated to a low arch-height ratio and greater foot mobility. The models presented in this study suggest that the soft-tissue structures of a flat-arched, mobile foot are at a greater risk of injury as they have greater requirements to absorb energy and generate larger forces. However, as these associations are only moderate, other measures may also have an influence. Copyright © 2017. Published by Elsevier B.V.

Estimation of stature from the foot and its segments in a sub-adult female population of North India

PubMed Central

2011-01-01

Background Establishing personal identity is one of the main concerns in forensic investigations. Estimation of stature forms a basic domain of the investigation process in unknown and co-mingled human remains in forensic anthropology case work. The objective of the present study was to set up standards for estimation of stature from the foot and its segments in a sub-adult female population. Methods The sample for the study constituted 149 young females from the Northern part of India. The participants were aged between 13 and 18 years. Besides stature, seven anthropometric measurements that included length of the foot from each toe (T1, T2, T3, T4, and T5 respectively), foot breadth at ball (BBAL) and foot breadth at heel (BHEL) were measured on both feet in each participant using standard methods and techniques. Results The results indicated that statistically significant differences (p < 0.05) between left and right feet occur in both the foot breadth measurements (BBAL and BHEL). Foot length measurements (T1 to T5 lengths) did not show any statistically significant bilateral asymmetry. The correlation between stature and all the foot measurements was found to be positive and statistically significant (p-value < 0.001). Linear regression models and multiple regression models were derived for estimation of stature from the measurements of the foot. The present study indicates that anthropometric measurements of foot and its segments are valuable in the estimation of stature. Foot length measurements estimate stature with greater accuracy when compared to foot breadth measurements. Conclusions The present study concluded that foot measurements have a strong relationship with stature in the sub-adult female population of North India. Hence, the stature of an individual can be successfully estimated from the foot and its segments using different regression models derived in the study. The regression models derived in the study may be applied successfully for the estimation of stature in sub-adult females, whenever foot remains are brought for forensic examination. Stepwise multiple regression models tend to estimate stature more accurately than linear regression models in female sub-adults. PMID:22104433

Estimation of stature from the foot and its segments in a sub-adult female population of North India.

PubMed

Krishan, Kewal; Kanchan, Tanuj; Passi, Neelam

2011-11-21

Establishing personal identity is one of the main concerns in forensic investigations. Estimation of stature forms a basic domain of the investigation process in unknown and co-mingled human remains in forensic anthropology case work. The objective of the present study was to set up standards for estimation of stature from the foot and its segments in a sub-adult female population. The sample for the study constituted 149 young females from the Northern part of India. The participants were aged between 13 and 18 years. Besides stature, seven anthropometric measurements that included length of the foot from each toe (T1, T2, T3, T4, and T5 respectively), foot breadth at ball (BBAL) and foot breadth at heel (BHEL) were measured on both feet in each participant using standard methods and techniques. The results indicated that statistically significant differences (p < 0.05) between left and right feet occur in both the foot breadth measurements (BBAL and BHEL). Foot length measurements (T1 to T5 lengths) did not show any statistically significant bilateral asymmetry. The correlation between stature and all the foot measurements was found to be positive and statistically significant (p-value < 0.001). Linear regression models and multiple regression models were derived for estimation of stature from the measurements of the foot. The present study indicates that anthropometric measurements of foot and its segments are valuable in the estimation of stature. Foot length measurements estimate stature with greater accuracy when compared to foot breadth measurements. The present study concluded that foot measurements have a strong relationship with stature in the sub-adult female population of North India. Hence, the stature of an individual can be successfully estimated from the foot and its segments using different regression models derived in the study. The regression models derived in the study may be applied successfully for the estimation of stature in sub-adult females, whenever foot remains are brought for forensic examination. Stepwise multiple regression models tend to estimate stature more accurately than linear regression models in female sub-adults.

Automatic segmentation of thermal images of diabetic-at-risk feet using the snakes algorithm

NASA Astrophysics Data System (ADS)

Etehadtavakol, Mahnaz; Ng, E. Y. K.; Kaabouch, Naima

2017-11-01

Diabetes is a disease with multi-systemic problems. It is a leading cause of death, medical costs, and loss of productivity. Foot ulcers are one generally known problem of uncontrolled diabetes that can lead to amputation signs of foot ulcers are not always obvious. Sometimes, symptoms won't even show up until ulcer is infected. Hence, identification of pre-ulceration of the plantar surface of the foot in diabetics is beneficial. Thermography has the potential to identify regions of the plantar with no evidence of ulcer but yet risk. Thermography is a technique that is safe, easy, non-invasive, with no contact, and repeatable. In this study, 59 thermographic images of the plantar foot of patients with diabetic neuropathy are implemented using the snakes algorithm to separate two feet from background automatically and separating the right foot from the left on each image. The snakes algorithm both separates the right and left foot into segmented different clusters according to their temperatures. The hottest regions will have the highest risk of ulceration for each foot. This algorithm also worked perfectly for all the current images.

The reliability, accuracy and minimal detectable difference of a multi-segment kinematic model of the foot-shoe complex.

PubMed

Bishop, Chris; Paul, Gunther; Thewlis, Dominic

2013-04-01

Kinematic models are commonly used to quantify foot and ankle kinematics, yet no marker sets or models have been proven reliable or accurate when wearing shoes. Further, the minimal detectable difference of a developed model is often not reported. We present a kinematic model that is reliable, accurate and sensitive to describe the kinematics of the foot-shoe complex and lower leg during walking gait. In order to achieve this, a new marker set was established, consisting of 25 markers applied on the shoe and skin surface, which informed a four segment kinematic model of the foot-shoe complex and lower leg. Three independent experiments were conducted to determine the reliability, accuracy and minimal detectable difference of the marker set and model. Inter-rater reliability of marker placement on the shoe was proven to be good to excellent (ICC=0.75-0.98) indicating that markers could be applied reliably between raters. Intra-rater reliability was better for the experienced rater (ICC=0.68-0.99) than the inexperienced rater (ICC=0.38-0.97). The accuracy of marker placement along each axis was <6.7 mm for all markers studied. Minimal detectable difference (MDD90) thresholds were defined for each joint; tibiocalcaneal joint--MDD90=2.17-9.36°, tarsometatarsal joint--MDD90=1.03-9.29° and the metatarsophalangeal joint--MDD90=1.75-9.12°. These thresholds proposed are specific for the description of shod motion, and can be used in future research designed at comparing between different footwear. Copyright © 2012 Elsevier B.V. All rights reserved.

Estimation of foot joint kinetics in three and four segment foot models using an existing proportionality scheme: Application in paediatric barefoot walking.

PubMed

Deschamps, Kevin; Eerdekens, Maarten; Desmet, Dirk; Matricali, Giovanni Arnoldo; Wuite, Sander; Staes, Filip

2017-08-16

Recent studies which estimated foot segment kinetic patterns were found to have inconclusive data on one hand, and did not dissociate the kinetics of the chopart and lisfranc joint. The current study aimed therefore at reproducing independent, recently published three-segment foot kinetic data (Study 1) and in a second stage expand the estimation towards a four-segment model (Study 2). Concerning the reproducibility study, two recently published three segment foot models (Bruening et al., 2014; Saraswat et al., 2014) were reproduced and kinetic parameters were incorporated in order to calculate joint moments and powers of paediatric cohorts during gait. Ground reaction forces were measured with an integrated force/pressure plate measurement set-up and a recently published proportionality scheme was applied to determine subarea total ground reaction forces. Regarding Study 2, moments and powers were estimated with respect to the Instituto Ortopedico Rizzoli four-segment model. The proportionality scheme was expanded in this study and the impact of joint centre location on kinetic data was evaluated. Findings related to Study 1 showed in general good agreement with the kinetic data published by Bruening et al. (2014). Contrarily, the peak ankle, midfoot and hallux powers published by Saraswat et al. (2014) are disputed. Findings of Study 2 revealed that the chopart joint encompasses both power absorption and generation, whereas the Lisfranc joint mainly contributes to power generation. The results highlights the necessity for further studies in the field of foot kinetic models and provides a first estimation of the kinetic behaviour of the Lisfranc joint. Copyright © 2017 Elsevier Ltd. All rights reserved.

Lower leg and foot contributions to turnout in female pre-professional dancers: A 3D kinematic analysis.

PubMed

Carter, Sarah L; Duncan, Rebekha; Weidemann, Andries L; Hopper, Luke S

2018-03-02

Turnout is a central element of classical ballet which involves sustained external rotation of the lower limbs during dance movements. Lower leg and foot compensation mechanisms which are often used to increase turnout have been attributed to the high incidence of lower limb injury in dancers. Evaluation of dancers' leg posture is needed to provide insight into the lower limb kinematic strategies used to achieve turnout. The primary purpose of this study was to use 3D kinematic analyses to determine the lower leg and foot compensations that are incorporated by female university dancers to accentuate their turnout. Active and passive external tibiofemoral rotation (TFR) was also measured. A moderate-strong negative relationship was observed between hip external rotation (HER) and foot abduction in the three first position conditions. A moderate negative relationship was found between passive TFR and foot abduction in all first position conditions. Our findings suggest dancers are more likely to pronate, than rotate the knee to compensate for limited HER. Dancers with a limited capacity to pronate may force additional rotation via the knee. Ongoing research would benefit from more in-depth analyses of the foot/ankle complex using a multi-segment foot model.

A system for the analysis of foot and ankle kinematics during gait.

PubMed

Kidder, S M; Abuzzahab, F S; Harris, G F; Johnson, J E

1996-03-01

A five-camera Vicon (Oxford Metrics, Oxford, England) motion analysis system was used to acquire foot and ankle motion data. Static resolution and accuracy were computed as 0.86 +/- 0.13 mm and 98.9%, while dynamic resolution and accuracy were 0.1 +/- 0.89 and 99.4% (sagittal plane). Spectral analysis revealed high frequency noise and the need for a filter (6 Hz Butterworth low-pass) as used in similar clinical situations. A four-segment rigid body model of the foot and ankle was developed. The four rigid body foot model segments were 1) tibia and fibula, 2) calcaneus, talus, and navicular, 3) cuneiforms, cuboid, and metatarsals, and 4) hallux. The Euler method for describing relative foot and ankle segment orientation was utilized in order to maintain accuracy and ease of clinical application. Kinematic data from a single test subject are presented.

Correlation between static radiographic measurements and intersegmental angular measurements during gait using a multisegment foot model.

PubMed

Lee, Dong Yeon; Seo, Sang Gyo; Kim, Eo Jin; Kim, Sung Ju; Lee, Kyoung Min; Farber, Daniel C; Chung, Chin Youb; Choi, In Ho

2015-01-01

Radiographic examination is a widely used evaluation method in the orthopedic clinic. However, conventional radiography alone does not reflect the dynamic changes between foot and ankle segments during gait. Multiple 3-dimensional multisegment foot models (3D MFMs) have been introduced to evaluate intersegmental motion of the foot. In this study, we evaluated the correlation between static radiographic indices and intersegmental foot motion indices. One hundred twenty-five females were tested. Static radiographs of full-leg and anteroposterior (AP) and lateral foot views were performed. For hindfoot evaluation, we measured the AP tibiotalar angle (TiTA), talar tilt (TT), calcaneal pitch, lateral tibiocalcaneal angle, and lateral talcocalcaneal angle. For the midfoot segment, naviculocuboid overlap and talonavicular coverage angle were calculated. AP and lateral talo-first metatarsal angles and metatarsal stacking angle (MSA) were measured to assess the forefoot. Hallux valgus angle (HVA) and hallux interphalangeal angle were measured. In gait analysis by 3D MFM, intersegmental angle (ISA) measurements of each segment (hallux, forefoot, hindfoot, arch) were recorded. ISAs at midstance phase were most highly correlated with radiography. Significant correlations were observed between ISA measurements using MFM and static radiographic measurements in the same segment. In the hindfoot, coronal plane ISA was correlated with AP TiTA (P < .001) and TT (P = .018). In the hallux, HVA was strongly correlated with transverse ISA of the hallux (P < .001). The segmental foot motion indices at midstance phase during gait measured by 3D MFM gait analysis were correlated with the conventional radiographic indices. The observed correlation between MFM measurements at midstance phase during gait and static radiographic measurements supports the fundamental basis for the use of MFM in analysis of dynamic motion of foot segment during gait. © The Author(s) 2014.

Quantifying skin motion artifact error of the hindfoot and forefoot marker clusters with the optical tracking of a multi-segment foot model using single-plane fluoroscopy.

PubMed

Shultz, R; Kedgley, A E; Jenkyn, T R

2011-05-01

The trajectories of skin-mounted markers tracked with optical motion capture are assumed to be an adequate representation of the underlying bone motions. However, it is well known that soft tissue artifact (STA) exists between marker and bone. This study quantifies the STA associated with the hindfoot and midfoot marker clusters of a multi-segment foot model. To quantify STA of the hindfoot and midfoot marker clusters with respect to the calcaneus and navicular respectively, fluoroscopic images were collected on 27 subjects during four quasi-static positions, (1) quiet standing (non-weight bearing), (2) at heel strike (weight-bearing), (3) at midstance (weight-bearing) and (4) at toe-off (weight-bearing). The translation and rotation components of STA were calculated in the sagittal plane. Translational STA at the calcaneus varied from 5.9±7.3mm at heel-strike to 12.1±0.3mm at toe-off. For the navicular the translational STA ranged from 7.6±7.6mm at heel strike to 16.4±16.7mm at toe-off. Rotational STA was relatively smaller for both bones at all foot positions. For the calcaneus they varied between 0.1±2.2° at heel-strike to 0.2±0.6° at toe-off. For the navicular, the rotational STA ranged from 0.6±0.9° at heel-strike to 0.7±0.7° at toe-off. The largest translational STA found in this study (16mm for the navicular) was smaller than those reported in the literature for the thigh and the lower leg, but was larger than the STA of individual spherical markers affixed to the foot. The largest errors occurred at toe-off position for all subjects for both the hindfoot and midfoot clusters. Future studies are recommended to quantify true three-dimensional STA of the entire foot during gait. Copyright © 2011. Published by Elsevier B.V.

A comparison of foot kinematics in people with normal- and flat-arched feet using the Oxford Foot Model.

PubMed

Levinger, Pazit; Murley, George S; Barton, Christian J; Cotchett, Matthew P; McSweeney, Simone R; Menz, Hylton B

2010-10-01

Foot posture is thought to influence predisposition to overuse injuries of the lower limb. Although the mechanisms underlying this proposed relationship are unclear, it is thought that altered foot kinematics may play a role. Therefore, this study was designed to investigate differences in foot motion between people with normal- and flat-arched feet using the Oxford Foot Model (OFM). Foot posture in 19 participants was documented as normal-arched (n=10) or flat-arched (n=9) using a foot screening protocol incorporating measurements from weightbearing antero-posterior and lateral foot radiographs. Differences between the groups in triplanar motion of the tibia, rearfoot and forefoot during walking were evaluated using a three-dimensional motion analysis system incorporating a multi-segment foot model (OFM). Participants with flat-arched feet demonstrated greater peak forefoot plantar-flexion (-13.7° ± 5.6° vs -6.5° ± 3.7°; p=0.004), forefoot abduction (-12.9° ± 6.9° vs -1.8° ± 6.3°; p=0.002), and rearfoot internal rotation (10.6° ± 7.5° vs -0.2°± 9.9°; p=0.018) compared to those with normal-arched feet. Additionally, participants with flat-arched feet demonstrated decreased peak forefoot adduction (-7.0° ± 9.2° vs 5.6° ± 7.3°; p=0.004) and a trend towards increased rearfoot eversion (-5.8° ± 4.4° vs -2.5° ± 2.6°; p=0.06). These findings support the notion that flat-arched feet have altered motion associated with greater pronation during gait; factors that may increase the risk of overuse injury. Copyright © 2010 Elsevier B.V. All rights reserved.

Repeatability of the Oxford Foot Model in children with foot deformity.

PubMed

McCahill, Jennifer; Stebbins, Julie; Koning, Bart; Harlaar, Jaap; Theologis, Tim

2018-03-01

The Oxford Foot Model (OFM) is a multi-segment, kinematic model developed to assess foot motion. It has previously been assessed for repeatability in healthy populations. To determine the OFM's reliability for detecting foot deformity, it is important to know repeatability in pathological conditions. The aim of the study was to assess the repeatability of the OFM in children with foot deformity. Intra-tester repeatability was assessed for 45 children (15 typically developing, 15 hemiplegic, 15 clubfoot). Inter-tester repeatability was assessed in the clubfoot population. The mean absolute differences between testers (clubfoot) and sessions (clubfoot and hemiplegic) were calculated for each of 15 clinically relevant, kinematic variables and compared to typically developing children. Children with clubfoot showed a mean difference between visits of 2.9° and a mean difference between raters of 3.6° Mean absolute differences were within one degree for the intra and inter-rater reliability in 12/15 variables. Hindfoot rotation, forefoot/tibia abduction and forefoot supination were the most variable between testers. Overall the clubfoot data were less variable than the typically developing population. Children with hemiplegia demonstrated slightly higher differences between sessions (mean 4.1°), with the most reliable data in the sagittal plane, and largest differences in the transverse plane. The OFM was designed to measure different types of foot deformity. The results of this study show that it provides repeatable results in children with foot deformity. To be distinguished from measurement artifact, changes in foot kinematics as a result of intervention or natural progression over time must be greater than the repeatability reported here. Copyright © 2018 Elsevier B.V. All rights reserved.

Segmentation and determination of joint space width in foot radiographs

NASA Astrophysics Data System (ADS)

Schenk, O.; de Muinck Keizer, D. M.; Bernelot Moens, H. J.; Slump, C. H.

2016-03-01

Joint damage in rheumatoid arthritis is frequently assessed using radiographs of hands and feet. Evaluation includes measurements of the joint space width (JSW) and detection of erosions. Current visual scoring methods are timeconsuming and subject to inter- and intra-observer variability. Automated measurement methods avoid these limitations and have been fairly successful in hand radiographs. This contribution aims at foot radiographs. Starting from an earlier proposed automated segmentation method we have developed a novel model based image analysis algorithm for JSW measurements. This method uses active appearance and active shape models to identify individual bones. The model compiles ten submodels, each representing a specific bone of the foot (metatarsals 1-5, proximal phalanges 1-5). We have performed segmentation experiments using 24 foot radiographs, randomly selected from a large database from the rheumatology department of a local hospital: 10 for training and 14 for testing. Segmentation was considered successful if the joint locations are correctly determined. Segmentation was successful in only 14%. To improve results a step-by-step analysis will be performed. We performed JSW measurements on 14 randomly selected radiographs. JSW was successfully measured in 75%, mean and standard deviation are 2.30+/-0.36mm. This is a first step towards automated determination of progression of RA and therapy response in feet using radiographs.

A multi-segment foot model based on anatomically registered technical coordinate systems: method repeatability and sensitivity in pediatric planovalgus feet.

PubMed

Saraswat, Prabhav; MacWilliams, Bruce A; Davis, Roy B; D'Astous, Jacques L

2013-01-01

Several multisegment foot models have been proposed and some have been used to study foot pathologies. These models have been tested and validated on typically developed populations; however application of such models to feet with significant deformities presents an additional set of challenges. For the first time, in this study, a multisegment foot model is tested for repeatability in a population of children with symptomatic abnormal feet. The results from this population are compared to the same metrics collected from an age matched (8-14 years) typically developing population. The modified Shriners Hospitals for Children, Greenville (mSHCG) foot model was applied to ten typically developing children and eleven children with planovalgus feet by two clinicians. Five subjects in each group were retested by both clinicians after 4-6 weeks. Both intra-clinician and inter-clinician repeatability were evaluated using static and dynamic measures. A plaster mold method was used to quantify variability arising from marker placement error. Dynamic variability was measured by examining trial differences from the same subjects when multiple clinicians carried out the data collection multiple times. For hindfoot and forefoot angles, static and dynamic variability in both groups was found to be less than 4° and 6° respectively. The mSHCG model strategy of minimal reliance on anatomical markers for dynamic measures and inherent flexibility enabled by separate anatomical and technical coordinate systems resulted in a model equally repeatable in typically developing and planovalgus populations. Copyright © 2012 Elsevier B.V. All rights reserved.

Computational wing optimization and comparisons with experiment for a semi-span wing model

NASA Technical Reports Server (NTRS)

Waggoner, E. G.; Haney, H. P.; Ballhaus, W. F.

1978-01-01

A computational wing optimization procedure was developed and verified by an experimental investigation of a semi-span variable camber wing model in the NASA Ames Research Center 14 foot transonic wind tunnel. The Bailey-Ballhaus transonic potential flow analysis and Woodward-Carmichael linear theory codes were linked to Vanderplaats constrained minimization routine to optimize model configurations at several subsonic and transonic design points. The 35 deg swept wing is characterized by multi-segmented leading and trailing edge flaps whose hinge lines are swept relative to the leading and trailing edges of the wing. By varying deflection angles of the flap segments, camber and twist distribution can be optimized for different design conditions. Results indicate that numerical optimization can be both an effective and efficient design tool. The optimized configurations had as good or better lift to drag ratios at the design points as the best designs previously tested during an extensive parametric study.

Differences in neutral foot positions when measured barefoot compared to in shoes with varying stiffnesses.

PubMed

Shultz, R; Birmingham, T B; Jenkyn, T R

2011-12-01

This study examined the absolute differences in neutral positions of the joints of the foot with different footwear. This addresses the question of whether separate static trials should be collected for each footwear condition to establish neutral positions. A multi-segment kinematic foot model and optical motion analysis system measured four inter-segmental joints of the foot: (1) hindfoot-to-midfoot in the frontal plane, (2) forefoot-to-midfoot in the frontal plane, (3) hallux-to-forefoot in the sagittal plane, and (4) the height-to-length ratio of the medial longitudinal arch. Barefoot was compared to three shoe condition using Nike Free trainers of varying longitudinal torsional stiffness in ten male volunteers. There was high variability both within subjects and shoe conditions. Shoes in general tended to raise the medial longitudinal arch and dorsiflex the hallux compared to barefoot condition. For the hallux, a minimum important difference of 5° or more was found between shoe conditions and the barefoot condition for majority of the subjects in all three shoe conditions (90% for control, 60% for least stiff, 50% for most stiff). This was less for the frontal plane inter-segmental joints of the foot where 50% of the subjects experience a change above 5° for at least one of the conditions. The choice of using condition-specific neutral trials versus a single common neutral trials should be considered carefully. A single common trial allows for differences in absolute joint angles to be compared between footwear conditions. This can be important clinically to determine whether a joint is approaching its end-of-range and therefore at risk of injury. Several condition-specific neutral trials allows for subtleties in kinematic waveforms to be better compared between conditions, since absolute shifts in joint angles due to changing neutral position are removed and the waveforms are better aligned. Copyright © 2011. Published by Elsevier Ltd.

Development of a Subject-Specific Foot-Ground Contact Model for Walking.

PubMed

Jackson, Jennifer N; Hass, Chris J; Fregly, Benjamin J

2016-09-01

Computational walking simulations could facilitate the development of improved treatments for clinical conditions affecting walking ability. Since an effective treatment is likely to change a patient's foot-ground contact pattern and timing, such simulations should ideally utilize deformable foot-ground contact models tailored to the patient's foot anatomy and footwear. However, no study has reported a deformable modeling approach that can reproduce all six ground reaction quantities (expressed as three reaction force components, two center of pressure (CoP) coordinates, and a free reaction moment) for an individual subject during walking. This study proposes such an approach for use in predictive optimizations of walking. To minimize complexity, we modeled each foot as two rigid segments-a hindfoot (HF) segment and a forefoot (FF) segment-connected by a pin joint representing the toes flexion-extension axis. Ground reaction forces (GRFs) and moments acting on each segment were generated by a grid of linear springs with nonlinear damping and Coulomb friction spread across the bottom of each segment. The stiffness and damping of each spring and common friction parameter values for all springs were calibrated for both feet simultaneously via a novel three-stage optimization process that used motion capture and ground reaction data collected from a single walking trial. The sequential three-stage process involved matching (1) the vertical force component, (2) all three force components, and finally (3) all six ground reaction quantities. The calibrated model was tested using four additional walking trials excluded from calibration. With only small changes in input kinematics, the calibrated model reproduced all six ground reaction quantities closely (root mean square (RMS) errors less than 13 N for all three forces, 25 mm for anterior-posterior (AP) CoP, 8 mm for medial-lateral (ML) CoP, and 2 N·m for the free moment) for both feet in all walking trials. The largest errors in AP CoP occurred at the beginning and end of stance phase when the vertical ground reaction force (vGRF) was small. Subject-specific deformable foot-ground contact models created using this approach should enable changes in foot-ground contact pattern to be predicted accurately by gait optimization studies, which may lead to improvements in personalized rehabilitation medicine.

Computer aided diagnosis of diabetic peripheral neuropathy

NASA Astrophysics Data System (ADS)

Chekh, Viktor; Soliz, Peter; McGrew, Elizabeth; Barriga, Simon; Burge, Mark; Luan, Shuang

2014-03-01

Diabetic peripheral neuropathy (DPN) refers to the nerve damage that can occur in diabetes patients. It most often affects the extremities, such as the feet, and can lead to peripheral vascular disease, deformity, infection, ulceration, and even amputation. The key to managing diabetic foot is prevention and early detection. Unfortunately, current existing diagnostic techniques are mostly based on patient sensations and exhibit significant inter- and intra-observer differences. We have developed a computer aided diagnostic (CAD) system for diabetic peripheral neuropathy. The thermal response of the feet of diabetic patients following cold stimulus is captured using an infrared camera. The plantar foot in the images from a thermal video are segmented and registered for tracking points or specific regions. The temperature recovery of each point on the plantar foot is extracted using our bio-thermal model and analyzed. The regions that exhibit abnormal ability to recover are automatically identified to aid the physicians to recognize problematic areas. The key to our CAD system is the segmentation of infrared video. The main challenges for segmenting infrared video compared to normal digital video are (1) as the foot warms up, it also warms up the surrounding, creating an ever changing contrast; and (2) there may be significant motion during imaging. To overcome this, a hybrid segmentation algorithm was developed based on a number of techniques such as continuous max-flow, model based segmentation, shape preservation, convex hull, and temperature normalization. Verifications of the automatic segmentation and registration using manual segmentation and markers show good agreement.

Anatomical masking of pressure footprints based on the Oxford Foot Model: validation and clinical relevance.

PubMed

Giacomozzi, Claudia; Stebbins, Julie A

2017-03-01

Plantar pressure analysis is widely used in the assessment of foot function. In order to assess regional loading, a mask is applied to the footprint to sub-divide it into regions of interest (ROIs). The most common masking method is based on geometric features of the footprint (GM). Footprint masking based on anatomical landmarks of the foot has been implemented more recently, and involves the integration of a 3D motion capture system, plantar pressure measurement device, and a multi-segment foot model. However, thorough validation of anatomical masking (AM) using pathological footprints has not yet been presented. In the present study, an AM method based on the Oxford Foot Model (OFM) was compared to an equivalent GM. Pressure footprints from 20 young healthy subjects (HG) and 20 patients with clubfoot (CF) were anatomically divided into 5 ROIs using a subset of the OFM markers. The same foot regions were also identified by using a standard GM method. Comparisons of intra-subject coefficient of variation (CV) showed that the OFM-based AM was at least as reliable as the GM for all investigated pressure parameters in all foot regions. Clinical relevance of AM was investigated by comparing footprints from HG and CF groups. Contact time, maximum force, force-time integral and contact area proved to be sensitive parameters that were able to distinguish HG and CF groups, using both AM and GM methods However, the AM method revealed statistically significant differences between groups in 75% of measured variables, compared to 62% using a standard GM method, indicating that the AM method is more sensitive for revealing differences between groups. Copyright © 2017 Elsevier B.V. All rights reserved.

Foot segmental motion and coupling in stage II and III tibialis posterior tendon dysfunction.

PubMed

Van de Velde, Maarten; Matricali, Giovanni Arnoldo; Wuite, Sander; Roels, Charlotte; Staes, Filip; Deschamps, Kevin

2017-06-01

Classification systems developed in the field of posterior tibialis tendon dysfunction omit to include dynamic measurements. Since this may negatively affect the selection of the most appropriate treatment modality, studies on foot kinematics are highly recommended. Previous research characterised the foot kinematics in patients with posterior tibialis tendon dysfunction. However, none of the studies analysed foot segmental motion synchrony during stance phase, nor compared the kinematic behaviour of the foot in presence of different posterior tibialis tendon dysfunction stages. Therefore, we aimed at comparing foot segmental motion and coupling in patients with posterior tibialis tendon dysfunction grade 2 and 3 to those of asymptomatic subjects. Foot segmental motion of 11 patients suffering from posterior tibialis tendon dysfunction stage 2, 4 patients with posterior tibialis tendon dysfunction stage 3 and 15 asymptomatic subjects was objectively quantified with the Rizzoli foot model using an instrumented walkway and a 3D passive motion capture system. Dependent variables were the range of motion occurring at the different inter-segment angles during subphases of stance and swing phase as well as the cross-correlation coefficient between a number of segments. Significant differences in range of motion were predominantly found during the forefoot push off phase and swing phase. In general, both patient cohorts demonstrated a reduced range of motion compared to the control group. This hypomobility occurred predominantly in the rearfoot and midfoot (p<0.01). Significant differences between both posterior tibialis tendon dysfunction patient cohorts were not revealed. Cross-correlation coefficients highlighted a loss of joint coupling between rearfoot and tibia as well as between rearfoot and forefoot in both posterior tibialis tendon dysfunction groups. The current evidence reveals considerable mechanical alterations in the foot which should be considered in the decision making process since it may help explaining the success and failure of certain conservative and surgical interventions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Modeling and analysis of passive dynamic bipedal walking with segmented feet and compliant joints

NASA Astrophysics Data System (ADS)

Huang, Yan; Wang, Qi-Ning; Gao, Yue; Xie, Guang-Ming

2012-10-01

Passive dynamic walking has been developed as a possible explanation for the efficiency of the human gait. This paper presents a passive dynamic walking model with segmented feet, which makes the bipedal walking gait more close to natural human-like gait. The proposed model extends the simplest walking model with the addition of flat feet and torsional spring based compliance on ankle joints and toe joints, to achieve stable walking on a slope driven by gravity. The push-off phase includes foot rotations around the toe joint and around the toe tip, which shows a great resemblance to human normal walking. This paper investigates the effects of the segmented foot structure on bipedal walking in simulations. The model achieves satisfactory walking results on even or uneven slopes.

The effect of age and speed on foot and ankle kinematics assessed using a 4-segment foot model.

PubMed

van Hoeve, Sander; Leenstra, Bernard; Willems, Paul; Poeze, Martijn; Meijer, Kenneth

2017-09-01

The effects of age and speed on foot and ankle kinematics in gait studies using foot models are not fully understood, whereas this can have significant influence. We analyzed these variables with the 4-segment Oxford foot model. Twenty-one healthy subjects (aged 20-65 years) were recruited for gait analysis. The effect of speed on foot and ankle kinematics was assessed by comparing results during slow walking and fast walking. To assess the effect of age, a group of 13 healthy young adults (aged 20-24 years) were compared with a group of 8 older adults (aged 53-65 years). Also, the interaction between age and speed was analyzed. Regarding speed, there was a significant difference between forefoot/hindfoot motion in the sagittal plane (flexion/extension) during both loading- and push-off phase (P = .004, P < .001). Between hindfoot/tibia, there was a significant difference for all parameters except for motion in the sagittal plane (flexion/extension) during push-off phase (P = .5). Age did not significantly influence kinematics. There was no interaction between age and speed. Our analysis found that speed significantly influenced the kinematic outcome parameters. This was more pronounced in the ankle joint. In contrast, no significant differences were found between younger and older healthy subjects.

Hierarchical information fusion for global displacement estimation in microsensor motion capture.

PubMed

Meng, Xiaoli; Zhang, Zhi-Qiang; Wu, Jian-Kang; Wong, Wai-Choong

2013-07-01

This paper presents a novel hierarchical information fusion algorithm to obtain human global displacement for different gait patterns, including walking, running, and hopping based on seven body-worn inertial and magnetic measurement units. In the first-level sensor fusion, the orientation for each segment is achieved by a complementary Kalman filter (CKF) which compensates for the orientation error of the inertial navigation system solution through its error state vector. For each foot segment, the displacement is also estimated by the CKF, and zero velocity update is included for the drift reduction in foot displacement estimation. Based on the segment orientations and left/right foot locations, two global displacement estimates can be acquired from left/right lower limb separately using a linked biomechanical model. In the second-level geometric fusion, another Kalman filter is deployed to compensate for the difference between the two estimates from the sensor fusion and get more accurate overall global displacement estimation. The updated global displacement will be transmitted to left/right foot based on the human lower biomechanical model to restrict the drifts in both feet displacements. The experimental results have shown that our proposed method can accurately estimate human locomotion for the three different gait patterns with regard to the optical motion tracker.

GC-ASM: Synergistic Integration of Graph-Cut and Active Shape Model Strategies for Medical Image Segmentation

PubMed Central

Chen, Xinjian; Udupa, Jayaram K.; Alavi, Abass; Torigian, Drew A.

2013-01-01

Image segmentation methods may be classified into two categories: purely image based and model based. Each of these two classes has its own advantages and disadvantages. In this paper, we propose a novel synergistic combination of the image based graph-cut (GC) method with the model based ASM method to arrive at the GC-ASM method for medical image segmentation. A multi-object GC cost function is proposed which effectively integrates the ASM shape information into the GC framework. The proposed method consists of two phases: model building and segmentation. In the model building phase, the ASM model is built and the parameters of the GC are estimated. The segmentation phase consists of two main steps: initialization (recognition) and delineation. For initialization, an automatic method is proposed which estimates the pose (translation, orientation, and scale) of the model, and obtains a rough segmentation result which also provides the shape information for the GC method. For delineation, an iterative GC-ASM algorithm is proposed which performs finer delineation based on the initialization results. The proposed methods are implemented to operate on 2D images and evaluated on clinical chest CT, abdominal CT, and foot MRI data sets. The results show the following: (a) An overall delineation accuracy of TPVF > 96%, FPVF < 0.6% can be achieved via GC-ASM for different objects, modalities, and body regions. (b) GC-ASM improves over ASM in its accuracy and precision to search region. (c) GC-ASM requires far fewer landmarks (about 1/3 of ASM) than ASM. (d) GC-ASM achieves full automation in the segmentation step compared to GC which requires seed specification and improves on the accuracy of GC. (e) One disadvantage of GC-ASM is its increased computational expense owing to the iterative nature of the algorithm. PMID:23585712

GC-ASM: Synergistic Integration of Graph-Cut and Active Shape Model Strategies for Medical Image Segmentation.

PubMed

Chen, Xinjian; Udupa, Jayaram K; Alavi, Abass; Torigian, Drew A

2013-05-01

Image segmentation methods may be classified into two categories: purely image based and model based. Each of these two classes has its own advantages and disadvantages. In this paper, we propose a novel synergistic combination of the image based graph-cut (GC) method with the model based ASM method to arrive at the GC-ASM method for medical image segmentation. A multi-object GC cost function is proposed which effectively integrates the ASM shape information into the GC framework. The proposed method consists of two phases: model building and segmentation. In the model building phase, the ASM model is built and the parameters of the GC are estimated. The segmentation phase consists of two main steps: initialization (recognition) and delineation. For initialization, an automatic method is proposed which estimates the pose (translation, orientation, and scale) of the model, and obtains a rough segmentation result which also provides the shape information for the GC method. For delineation, an iterative GC-ASM algorithm is proposed which performs finer delineation based on the initialization results. The proposed methods are implemented to operate on 2D images and evaluated on clinical chest CT, abdominal CT, and foot MRI data sets. The results show the following: (a) An overall delineation accuracy of TPVF > 96%, FPVF < 0.6% can be achieved via GC-ASM for different objects, modalities, and body regions. (b) GC-ASM improves over ASM in its accuracy and precision to search region. (c) GC-ASM requires far fewer landmarks (about 1/3 of ASM) than ASM. (d) GC-ASM achieves full automation in the segmentation step compared to GC which requires seed specification and improves on the accuracy of GC. (e) One disadvantage of GC-ASM is its increased computational expense owing to the iterative nature of the algorithm.

The effect of age and speed on foot and ankle kinematics assessed using a 4-segment foot model

PubMed Central

van Hoeve, Sander; Leenstra, Bernard; Willems, Paul; Poeze, Martijn; Meijer, Kenneth

2017-01-01

Abstract Background: The effects of age and speed on foot and ankle kinematics in gait studies using foot models are not fully understood, whereas this can have significant influence. We analyzed these variables with the 4-segment Oxford foot model. Methods: Twenty-one healthy subjects (aged 20–65 years) were recruited for gait analysis. The effect of speed on foot and ankle kinematics was assessed by comparing results during slow walking and fast walking. To assess the effect of age, a group of 13 healthy young adults (aged 20–24 years) were compared with a group of 8 older adults (aged 53–65 years). Also, the interaction between age and speed was analyzed. Results: Regarding speed, there was a significant difference between forefoot/hindfoot motion in the sagittal plane (flexion/extension) during both loading- and push-off phase (P = .004, P < .001). Between hindfoot/tibia, there was a significant difference for all parameters except for motion in the sagittal plane (flexion/extension) during push-off phase (P = .5). Age did not significantly influence kinematics. There was no interaction between age and speed. Conclusion: Our analysis found that speed significantly influenced the kinematic outcome parameters. This was more pronounced in the ankle joint. In contrast, no significant differences were found between younger and older healthy subjects. PMID:28858109

The effects of klapskate hinge position on push-off performance: a simulation study.

PubMed

Houdijk, Han; Bobbert, Maarten F; De Koning, Jos J; De Groot, Gert

2003-12-01

The introduction of the klapskate in speed skating confronts skaters with the question of how to adjust the position of the hinge in order to maximize performance. The purpose of this study was to reveal the constraint that klapskate hinge position imposes on push-off performance in speed skating. For this purpose, a model of the musculoskeletal system was designed to simulate a simplified, two-dimensional skating push off. To capture the essence of a skating push off, this model performed a one-leg vertical jump, from a frictionless surface, while keeping its trunk horizontally. In this model, klapskate hinge position was varied by varying the length of the foot segment between 115 and 300 mm. With each foot length, an optimal control solution was found that resulted in the maximal amount of vertical kinetic and potential energy of the body's center of mass at take off (Weff). Foot length was shown to considerably affect push-off performance. Maximal Weff was obtained with a foot length of 185 mm and decreased by approximately 25% at either foot length of 115 mm and 300 mm. The reason for this decrease was that foot length affected the onset and control of foot rotation. This resulted in a distortion of the pattern of leg segment rotations and affected muscle work (Wmus) and the efficacy ratio (Weff/Wmus) of the entire leg system. Despite its simplicity, the model very well described and explained the effects of klapskate hinge position on push off performance that have been observed in speed-skating experiments. The simplicity of the model, however, does not allow quantitative analyses of optimal klapskate hinge position for speed-skating practice.

Does excessive flatfoot deformity affect function? A comparison between symptomatic and asymptomatic flatfeet using the Oxford Foot Model.

PubMed

Hösl, Matthias; Böhm, Harald; Multerer, Christel; Döderlein, Leonhard

2014-01-01

Treatment of asymptomatic flexible flatfeet is a subject of great controversy. The purpose of this study was to examine foot function during walking in symptomatic (SFF) and asymptomatic (ASFF) flexible flatfeet. Thirty-five paediatric and juvenile patients with idiopathic flexible flatfeet were recruited from an orthopaedic outpatient department (14 SFF and 21 ASFF). Eleven age-matched participants with typically developing feet served as controls (TDF). To study foot function, 3D multi-segment foot kinematics and ankle joint kinetics were captured during barefoot gait analysis. Overall, alterations in foot kinematics in flatfeet were pronounced but differences between SFF and ASFF were not observed. Largest discriminatory effects between flatfeet and TDF were noticed in reduced hindfoot dorsiflexion as well as in increased forefoot supination and abduction. Upon clinical examination, restrictions in passive dorsiflexion in ASFF and SFF were significant. During gait, the hindfoot in flatfeet (both ASFF and SFF) was more everted, but less flexible. In sagittal plane, limited hindfoot dorsiflexion of ASFF and SFF was compensated for by increased forefoot mobility and a hypermobile hallux. Concerning ankle kinetics, SFF lacked positive joint energy for propulsion while ASFF needed to absorb more negative ankle joint energy during loading response. This may risk fatigue and overuse syndrome of anterior shank muscles in ASFF. Hence, despite a lack of symptoms flatfoot deformity in ASFF affected function. Yet, contrary to what was expected, SFF did not show greater deviations in 3D foot kinematics than ASFF. Symptoms may rather depend on tissue wear and subjective pain thresholds. Copyright © 2013. Published by Elsevier B.V.

Development of a Subject-Specific Foot-Ground Contact Model for Walking

PubMed Central

Jackson, Jennifer N.; Hass, Chris J.; Fregly, Benjamin J.

2016-01-01

Computational walking simulations could facilitate the development of improved treatments for clinical conditions affecting walking ability. Since an effective treatment is likely to change a patient's foot-ground contact pattern and timing, such simulations should ideally utilize deformable foot-ground contact models tailored to the patient's foot anatomy and footwear. However, no study has reported a deformable modeling approach that can reproduce all six ground reaction quantities (expressed as three reaction force components, two center of pressure (CoP) coordinates, and a free reaction moment) for an individual subject during walking. This study proposes such an approach for use in predictive optimizations of walking. To minimize complexity, we modeled each foot as two rigid segments—a hindfoot (HF) segment and a forefoot (FF) segment—connected by a pin joint representing the toes flexion–extension axis. Ground reaction forces (GRFs) and moments acting on each segment were generated by a grid of linear springs with nonlinear damping and Coulomb friction spread across the bottom of each segment. The stiffness and damping of each spring and common friction parameter values for all springs were calibrated for both feet simultaneously via a novel three-stage optimization process that used motion capture and ground reaction data collected from a single walking trial. The sequential three-stage process involved matching (1) the vertical force component, (2) all three force components, and finally (3) all six ground reaction quantities. The calibrated model was tested using four additional walking trials excluded from calibration. With only small changes in input kinematics, the calibrated model reproduced all six ground reaction quantities closely (root mean square (RMS) errors less than 13 N for all three forces, 25 mm for anterior–posterior (AP) CoP, 8 mm for medial–lateral (ML) CoP, and 2 N·m for the free moment) for both feet in all walking trials. The largest errors in AP CoP occurred at the beginning and end of stance phase when the vertical ground reaction force (vGRF) was small. Subject-specific deformable foot-ground contact models created using this approach should enable changes in foot-ground contact pattern to be predicted accurately by gait optimization studies, which may lead to improvements in personalized rehabilitation medicine. PMID:27379886

Clinical workflow for personalized foot pressure ulcer prevention.

PubMed

Bucki, M; Luboz, V; Perrier, A; Champion, E; Diot, B; Vuillerme, N; Payan, Y

2016-09-01

Foot pressure ulcers are a common complication of diabetes because of patient's lack of sensitivity due to neuropathy. Deep pressure ulcers appear internally when pressures applied on the foot create high internal strains nearby bony structures. Monitoring tissue strains in persons with diabetes is therefore important for an efficient prevention. We propose to use personalized biomechanical foot models to assess strains within the foot and to determine the risk of ulcer formation. Our workflow generates a foot model adapted to a patient's morphology by deforming an atlas model to conform it to the contours of segmented medical images of the patient's foot. Our biomechanical model is composed of rigid bodies for the bones, joined by ligaments and muscles, and a finite element mesh representing the soft tissues. Using our registration algorithm to conform three datasets, three new patient models were created. After applying a pressure load below these foot models, the Von Mises equivalent strains and "cluster volumes" (i.e. volumes of contiguous elements with strains above a given threshold) were measured within eight functionally meaningful foot regions. The results show the variability of both location and strain values among the three considered patients. This study also confirms that the anatomy of the foot has an influence on the risk of pressure ulcer. Copyright © 2016. Published by Elsevier Ltd.

Multi-object model-based multi-atlas segmentation for rodent brains using dense discrete correspondences

NASA Astrophysics Data System (ADS)

Lee, Joohwi; Kim, Sun Hyung; Styner, Martin

2016-03-01

The delineation of rodent brain structures is challenging due to low-contrast multiple cortical and subcortical organs that are closely interfacing to each other. Atlas-based segmentation has been widely employed due to its ability to delineate multiple organs at the same time via image registration. The use of multiple atlases and subsequent label fusion techniques has further improved the robustness and accuracy of atlas-based segmentation. However, the accuracy of atlas-based segmentation is still prone to registration errors; for example, the segmentation of in vivo MR images can be less accurate and robust against image artifacts than the segmentation of post mortem images. In order to improve the accuracy and robustness of atlas-based segmentation, we propose a multi-object, model-based, multi-atlas segmentation method. We first establish spatial correspondences across atlases using a set of dense pseudo-landmark particles. We build a multi-object point distribution model using those particles in order to capture inter- and intra- subject variation among brain structures. The segmentation is obtained by fitting the model into a subject image, followed by label fusion process. Our result shows that the proposed method resulted in greater accuracy than comparable segmentation methods, including a widely used ANTs registration tool.

Foot and ankle kinematics in patients with posterior tibial tendon dysfunction.

PubMed

Ness, Mary Ellen; Long, Jason; Marks, Richard; Harris, Gerald

2008-02-01

The purpose of this study is to provide a quantitative characterization of gait in patients with posterior tibial tendon dysfunction (PTTD), including temporal-spatial and kinematic parameters, and to compare these results to those of a Normal population. Our hypothesis was that segmental foot kinematics were significantly different in multiple segments across multiple planes. A 15 camera motion analysis system and weight-bearing radiographs were employed to evaluate 3D foot and ankle motion in a population of 34 patients with PTTD (30 females, 4 males) and 25 normal subjects (12 females, 13 males). The four-segment Milwaukee Foot Model (MFM) with radiographic indexing was used to analyze foot and ankle motion and provided kinematic data in the sagittal, coronal and transverse planes as well as temporal-spatial information. The temporal-spatial parameters revealed statistically significant deviations in all four metrics for the PTTD population. Stride length, cadence and walking speed were all significantly diminished, while stance duration was significantly prolonged (p<0.0125). Significant kinematic differences were noted between the groups (p<0.002), including: (1) diminished dorsiflexion and increased eversion of the hindfoot; (2) decreased plantarflexion of the forefoot, as well as abduction shift and loss of the varus thrust in the forefoot; and (3) decreased range of motion (ROM) with diminished dorsiflexion of the hallux. The study provides an impetus for improved orthotic and bracing designs to aid in the care of distal foot segments during the treatment of PTTD. It also provides the basis for future evaluation of surgical efficacy. The course of this investigation may ultimately lead to improved treatment planning methods, including orthotic and operative interventions.

Challenging the foundations of the clinical model of foot function: further evidence that the root model assessments fail to appropriately classify foot function.

PubMed

Jarvis, Hannah L; Nester, Christopher J; Bowden, Peter D; Jones, Richard K

2017-01-01

The Root model of normal and abnormal foot function remains the basis for clinical foot orthotic practice globally. Our aim was to investigate the relationship between foot deformities and kinematic compensations that are the foundations of the model. A convenience sample of 140 were screened and 100 symptom free participants aged 18-45 years were invited to participate. The static biomechanical assessment described by the Root model was used to identify five foot deformities. A 6 segment foot model was used to measure foot kinematics during gait. Statistical tests compared foot kinematics between feet with and without foot deformities and correlated the degree of deformity with any compensatory motions. None of the deformities proposed by the Root model were associated with distinct differences in foot kinematics during gait when compared to those without deformities or each other. Static and dynamic parameters were not correlated. Taken as part of a wider body of evidence, the results of this study have profound implications for clinical foot health practice. We believe that the assessment protocol advocated by the Root model is no longer a suitable basis for professional practice. We recommend that clinicians stop using sub-talar neutral position during clinical assessments and stop assessing the non-weight bearing range of ankle dorsiflexion, first ray position and forefoot alignments and movement as a means of defining the associated foot deformities. The results question the relevance of the Root assessments in the prescription of foot orthoses.

Segment Fixed Priority Scheduling for Self Suspending Real Time Tasks

DTIC Science & Technology

2016-08-11

Segment-Fixed Priority Scheduling for Self-Suspending Real -Time Tasks Junsung Kim, Department of Electrical and Computer Engineering, Carnegie...4 2.1 Application of a Multi-Segment Self-Suspending Real -Time Task Model ............................. 5 3 Fixed Priority Scheduling...1 Figure 2: A multi-segment self-suspending real -time task model

Subject-specific finite element modelling of the human foot complex during walking: sensitivity analysis of material properties, boundary and loading conditions.

PubMed

Akrami, Mohammad; Qian, Zhihui; Zou, Zhemin; Howard, David; Nester, Chris J; Ren, Lei

2018-04-01

The objective of this study was to develop and validate a subject-specific framework for modelling the human foot. This was achieved by integrating medical image-based finite element modelling, individualised multi-body musculoskeletal modelling and 3D gait measurements. A 3D ankle-foot finite element model comprising all major foot structures was constructed based on MRI of one individual. A multi-body musculoskeletal model and 3D gait measurements for the same subject were used to define loading and boundary conditions. Sensitivity analyses were used to investigate the effects of key modelling parameters on model predictions. Prediction errors of average and peak plantar pressures were below 10% in all ten plantar regions at five key gait events with only one exception (lateral heel, in early stance, error of 14.44%). The sensitivity analyses results suggest that predictions of peak plantar pressures are moderately sensitive to material properties, ground reaction forces and muscle forces, and significantly sensitive to foot orientation. The maximum region-specific percentage change ratios (peak stress percentage change over parameter percentage change) were 1.935-2.258 for ground reaction forces, 1.528-2.727 for plantar flexor muscles and 4.84-11.37 for foot orientations. This strongly suggests that loading and boundary conditions need to be very carefully defined based on personalised measurement data.

Multi-atlas learner fusion: An efficient segmentation approach for large-scale data.

PubMed

Asman, Andrew J; Huo, Yuankai; Plassard, Andrew J; Landman, Bennett A

2015-12-01

We propose multi-atlas learner fusion (MLF), a framework for rapidly and accurately replicating the highly accurate, yet computationally expensive, multi-atlas segmentation framework based on fusing local learners. In the largest whole-brain multi-atlas study yet reported, multi-atlas segmentations are estimated for a training set of 3464 MR brain images. Using these multi-atlas estimates we (1) estimate a low-dimensional representation for selecting locally appropriate example images, and (2) build AdaBoost learners that map a weak initial segmentation to the multi-atlas segmentation result. Thus, to segment a new target image we project the image into the low-dimensional space, construct a weak initial segmentation, and fuse the trained, locally selected, learners. The MLF framework cuts the runtime on a modern computer from 36 h down to 3-8 min - a 270× speedup - by completely bypassing the need for deformable atlas-target registrations. Additionally, we (1) describe a technique for optimizing the weak initial segmentation and the AdaBoost learning parameters, (2) quantify the ability to replicate the multi-atlas result with mean accuracies approaching the multi-atlas intra-subject reproducibility on a testing set of 380 images, (3) demonstrate significant increases in the reproducibility of intra-subject segmentations when compared to a state-of-the-art multi-atlas framework on a separate reproducibility dataset, (4) show that under the MLF framework the large-scale data model significantly improve the segmentation over the small-scale model under the MLF framework, and (5) indicate that the MLF framework has comparable performance as state-of-the-art multi-atlas segmentation algorithms without using non-local information. Copyright © 2015 Elsevier B.V. All rights reserved.

Energy neutral: the human foot and ankle subsections combine to produce near zero net mechanical work during walking.

PubMed

Takahashi, Kota Z; Worster, Kate; Bruening, Dustin A

2017-11-13

The human foot and ankle system is equipped with structures that can produce mechanical work through elastic (e.g., Achilles tendon, plantar fascia) or viscoelastic (e.g., heel pad) mechanisms, or by active muscle contractions. Yet, quantifying the work distribution among various subsections of the foot and ankle can be difficult, in large part due to a lack of objective methods for partitioning the forces acting underneath the stance foot. In this study, we deconstructed the mechanical work production during barefoot walking in a segment-by-segment manner (hallux, forefoot, hindfoot, and shank). This was accomplished by isolating the forces acting within each foot segment through controlling the placement of the participants' foot as it contacted a ground-mounted force platform. Combined with an analysis that incorporated non-rigid mechanics, we quantified the total work production distal to each of the four isolated segments. We found that various subsections within the foot and ankle showed disparate work distribution, particularly within structures distal to the hindfoot. When accounting for all sources of positive and negative work distal to the shank (i.e., ankle joint and all foot structures), these structures resembled an energy-neutral system that produced net mechanical work close to zero (-0.012 ± 0.054 J/kg).

Three-dimensional data-tracking dynamic optimization simulations of human locomotion generated by direct collocation.

PubMed

Lin, Yi-Chung; Pandy, Marcus G

2017-07-05

The aim of this study was to perform full-body three-dimensional (3D) dynamic optimization simulations of human locomotion by driving a neuromusculoskeletal model toward in vivo measurements of body-segmental kinematics and ground reaction forces. Gait data were recorded from 5 healthy participants who walked at their preferred speeds and ran at 2m/s. Participant-specific data-tracking dynamic optimization solutions were generated for one stride cycle using direct collocation in tandem with an OpenSim-MATLAB interface. The body was represented as a 12-segment, 21-degree-of-freedom skeleton actuated by 66 muscle-tendon units. Foot-ground interaction was simulated using six contact spheres under each foot. The dynamic optimization problem was to find the set of muscle excitations needed to reproduce 3D measurements of body-segmental motions and ground reaction forces while minimizing the time integral of muscle activations squared. Direct collocation took on average 2.7±1.0h and 2.2±1.6h of CPU time, respectively, to solve the optimization problems for walking and running. Model-computed kinematics and foot-ground forces were in good agreement with corresponding experimental data while the calculated muscle excitation patterns were consistent with measured EMG activity. The results demonstrate the feasibility of implementing direct collocation on a detailed neuromusculoskeletal model with foot-ground contact to accurately and efficiently generate 3D data-tracking dynamic optimization simulations of human locomotion. The proposed method offers a viable tool for creating feasible initial guesses needed to perform predictive simulations of movement using dynamic optimization theory. The source code for implementing the model and computational algorithm may be downloaded at http://simtk.org/home/datatracking. Copyright © 2017 Elsevier Ltd. All rights reserved.

Integrated multi-choice goal programming and multi-segment goal programming for supplier selection considering imperfect-quality and price-quantity discounts in a multiple sourcing environment

NASA Astrophysics Data System (ADS)

Chang, Ching-Ter; Chen, Huang-Mu; Zhuang, Zheng-Yun

2014-05-01

Supplier selection (SS) is a multi-criteria and multi-objective problem, in which multi-segment (e.g. imperfect-quality discount (IQD) and price-quantity discount (PQD)) and multi-aspiration level problems may be significantly important; however, little attention had been given to dealing with both of them simultaneously in the past. This study proposes a model for integrating multi-choice goal programming and multi-segment goal programming to solve the above-mentioned problems by providing the following main contributions: (1) it allows decision-makers to set multiple aspiration levels on the right-hand side of each goal to suit real-world situations, (2) the PQD and IQD conditions are considered in the proposed model simultaneously and (3) the proposed model can solve a SS problem with n suppliers where each supplier offers m IQD with r PQD intervals, where only ? extra binary variables are required. The usefulness of the proposed model is explained using a real case. The results indicate that the proposed model not only can deal with a SS problem with multi-segment and multi-aspiration levels, but also can help the decision-maker to find the appropriate order quantities for each supplier by considering cost, quality and delivery.

Integrated kinematics-kinetics-plantar pressure data analysis: a useful tool for characterizing diabetic foot biomechanics.

PubMed

Sawacha, Zimi; Guarneri, Gabriella; Cristoferi, Giuseppe; Guiotto, Annamaria; Avogaro, Angelo; Cobelli, Claudio

2012-05-01

The fundamental cause of lower-extremity complications in diabetes is chronic hyperglycemia leading to diabetic foot ulcer pathology. While the relationship between abnormal plantar pressure distribution and plantar ulcers has been widely investigated, little is known about the role of shear stress. Moreover, the mutual relationship among plantar pressure, shear stress, and abnormal kinematics in the etiology of diabetic foot has not been established. This lack of knowledge is determined by the lack of commercially available instruments which allow such a complex analysis. This study aims to develop a method for the simultaneous assessment of kinematics, kinetics, and plantar pressure on foot subareas of diabetic subjects by means of combining three commercial systems. Data were collected during gait on 24 patients (12 controls and 12 diabetic neuropathics) with a motion capture system synchronized with two force plates and two baropodometric systems. A four segment three-dimensional foot kinematics model was adopted for the subsegment angles estimation together with a three segment model for the plantar sub-area definition during gait. The neuropathic group exhibited significantly excessive plantar pressure, ground reaction forces on each direction, and a reduced loading surface on the midfoot subsegment (p<0.04). Furthermore the same subsegment displayed excessive dorsiflexion, external rotation, and eversion (p<0.05). Initial results showed that this methodology may enable a more appropriate characterization of patients at risk of foot ulcerations, and help planning prevention programs. Copyright © 2011 Elsevier B.V. All rights reserved.

A comparative study on dynamic stiffness in typical finite element model and multi-body model of C6-C7 cervical spine segment.

PubMed

Wang, Yawei; Wang, Lizhen; Du, Chengfei; Mo, Zhongjun; Fan, Yubo

2016-06-01

In contrast to numerous researches on static or quasi-static stiffness of cervical spine segments, very few investigations on their dynamic stiffness were published. Currently, scale factors and estimated coefficients were usually used in multi-body models for including viscoelastic properties and damping effects, meanwhile viscoelastic properties of some tissues were unavailable for establishing finite element models. Because dynamic stiffness of cervical spine segments in these models were difficult to validate because of lacking in experimental data, we tried to gain some insights on current modeling methods through studying dynamic stiffness differences between these models. A finite element model and a multi-body model of C6-C7 segment were developed through using available material data and typical modeling technologies. These two models were validated with quasi-static response data of the C6-C7 cervical spine segment. Dynamic stiffness differences were investigated through controlling motions of C6 vertebrae at different rates and then comparing their reaction forces or moments. Validation results showed that both the finite element model and the multi-body model could generate reasonable responses under quasi-static loads, but the finite element segment model exhibited more nonlinear characters. Dynamic response investigations indicated that dynamic stiffness of this finite element model might be underestimated because of the absence of dynamic stiffen effect and damping effects of annulus fibrous, while representation of these effects also need to be improved in current multi-body model. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Simultaneous segmentation of the bone and cartilage surfaces of a knee joint in 3D

NASA Astrophysics Data System (ADS)

Yin, Y.; Zhang, X.; Anderson, D. D.; Brown, T. D.; Hofwegen, C. Van; Sonka, M.

2009-02-01

We present a novel framework for the simultaneous segmentation of multiple interacting surfaces belonging to multiple mutually interacting objects. The method is a non-trivial extension of our previously reported optimal multi-surface segmentation. Considering an example application of knee-cartilage segmentation, the framework consists of the following main steps: 1) Shape model construction: Building a mean shape for each bone of the joint (femur, tibia, patella) from interactively segmented volumetric datasets. Using the resulting mean-shape model - identification of cartilage, non-cartilage, and transition areas on the mean-shape bone model surfaces. 2) Presegmentation: Employment of iterative optimal surface detection method to achieve approximate segmentation of individual bone surfaces. 3) Cross-object surface mapping: Detection of inter-bone equidistant separating sheets to help identify corresponding vertex pairs for all interacting surfaces. 4) Multi-object, multi-surface graph construction and final segmentation: Construction of a single multi-bone, multi-surface graph so that two surfaces (bone and cartilage) with zero and non-zero intervening distances can be detected for each bone of the joint, according to whether or not cartilage can be locally absent or present on the bone. To define inter-object relationships, corresponding vertex pairs identified using the separating sheets were interlinked in the graph. The graph optimization algorithm acted on the entire multiobject, multi-surface graph to yield a globally optimal solution. The segmentation framework was tested on 16 MR-DESS knee-joint datasets from the Osteoarthritis Initiative database. The average signed surface positioning error for the 6 detected surfaces ranged from 0.00 to 0.12 mm. When independently initialized, the signed reproducibility error of bone and cartilage segmentation ranged from 0.00 to 0.26 mm. The results showed that this framework provides robust, accurate, and reproducible segmentation of the knee joint bone and cartilage surfaces of the femur, tibia, and patella. As a general segmentation tool, the developed framework can be applied to a broad range of multi-object segmentation problems.

[The functional sport shoe parameter "torsion" within running shoe research--a literature review].

PubMed

Michel, F I; Kälin, X; Metzger, A; Westphal, K; Schweizer, F; Campe, S; Segesser, B

2009-12-01

Within the sport shoe area torsion is described as the twisting and decoupling of the rear-, mid- and forefoot along the longitudinal axis of the foot. Studies have shown that running shoes restrict the torsion of the foot and thus they increase the pronation of the foot. Based on the findings, it is recommended to design running shoes, which allow the natural freedom of movement of the foot. The market introduction of the first torsion concept through adidas(R) took place in 1989. Independently of the first market introduction, only one epidemiological study was conducted in the running shoe area. The study should investigate the occurrence of Achilles tendon problems of the athletes running in the new "adidas Torsion(R) shoes". However, further studies quantifying the optimal region of torsionability concerning the reduction of injury incidence are still missing. Newer studies reveal that the criterion torsion only plays a secondary roll regarding the buying decision. Moreover, athletes are not able to perceive torsionability as a discrete functional parameter. It is to register, that several workgroups are dealing intensively with the detailed analysis of the foot movement based on kinematic multi-segment-models. However, scientific as well as popular scientific contributions display that the original idea of the torsion concept is still not completely understood. Hence, the "inverse" characteristic is postulated. The present literature review leads to the deduction that the functional characteristics of the torsion concept are not fully implemented within the running shoe area. This implies the necessity of scientific studies, which investigate the relevance of a functional torsion concept regarding injury prevention based on basic and applied research. Besides, biomechanical studies should analyse systematically the mechanism and the effects of torsion relevant technologies and systems.

Subtalar neutral position as an offset for a kinematic model of the foot during walking.

PubMed

Houck, Jeff R; Tome, Josh M; Nawoczenski, Deborah A

2008-07-01

The lack of a common reference position when defining foot postures may underestimate the ability to differentiate foot function in subjects with pathology. The effect of using the subtalar neutral (STN) position as an offset for both rearfoot and forefoot through comparison of the kinematic walking patterns of subjects classified as normal (n=7) and abnormally pronated (n=14) foot postures was completed. An Optotrak Motion Analysis System (Northern Digital, Inc.) integrated with Motion Monitor Software (Innovative Sports, Inc.) was used to track three-dimensional movement of the leg, rearfoot and first metatarsal segments. Intrarater reliability of positioning the foot into STN using clinical guidelines was determined for a single rater for 21 subjects. Walking data were subsequently compared before and after an offset was applied to the rearfoot and first metatarsal segments. Repeated measures of foot positioning found the STN position to be highly repeatable (intraclass correlation coefficients>0.9), with peak errors ranging from 1.9 degrees to 4.3 degrees . Utilizing STN as the offset resulted in a significant increase in rearfoot eversion (p=0.019) during early stance, and greater first metatarsal dorsiflexion (p<0.007) across stance in the pronated foot groups that was not observed prior to applying the offset. When applied to subjects with differing foot postures, the selection of a common reference position that is both clinically appropriate and reliable may distinguish kinematic patterns during walking that are consistent with theories of abnormal pronation.

A Multi-Objective Decision Making Approach for Solving the Image Segmentation Fusion Problem.

PubMed

Khelifi, Lazhar; Mignotte, Max

2017-08-01

Image segmentation fusion is defined as the set of methods which aim at merging several image segmentations, in a manner that takes full advantage of the complementarity of each one. Previous relevant researches in this field have been impeded by the difficulty in identifying an appropriate single segmentation fusion criterion, providing the best possible, i.e., the more informative, result of fusion. In this paper, we propose a new model of image segmentation fusion based on multi-objective optimization which can mitigate this problem, to obtain a final improved result of segmentation. Our fusion framework incorporates the dominance concept in order to efficiently combine and optimize two complementary segmentation criteria, namely, the global consistency error and the F-measure (precision-recall) criterion. To this end, we present a hierarchical and efficient way to optimize the multi-objective consensus energy function related to this fusion model, which exploits a simple and deterministic iterative relaxation strategy combining the different image segments. This step is followed by a decision making task based on the so-called "technique for order performance by similarity to ideal solution". Results obtained on two publicly available databases with manual ground truth segmentations clearly show that our multi-objective energy-based model gives better results than the classical mono-objective one.

A three-dimensional model to assess the effect of ankle joint axis misalignments in ankle-foot orthoses.

PubMed

Fatone, Stefania; Johnson, William Brett; Tucker, Kerice

2016-04-01

Misalignment of an articulated ankle-foot orthosis joint axis with the anatomic joint axis may lead to discomfort, alterations in gait, and tissue damage. Theoretical, two-dimensional models describe the consequences of misalignments, but cannot capture the three-dimensional behavior of ankle-foot orthosis use. The purpose of this project was to develop a model to describe the effects of ankle-foot orthosis ankle joint misalignment in three dimensions. Computational simulation. Three-dimensional scans of a leg and ankle-foot orthosis were incorporated into a link segment model where the ankle-foot orthosis joint axis could be misaligned with the anatomic ankle joint axis. The leg/ankle-foot orthosis interface was modeled as a network of nodes connected by springs to estimate interface pressure. Motion between the leg and ankle-foot orthosis was calculated as the ankle joint moved through a gait cycle. While the three-dimensional model corroborated predictions of the previously published two-dimensional model that misalignments in the anterior -posterior direction would result in greater relative motion compared to misalignments in the proximal -distal direction, it provided greater insight showing that misalignments have asymmetrical effects. The three-dimensional model has been incorporated into a freely available computer program to assist others in understanding the consequences of joint misalignments. Models and simulations can be used to gain insight into functioning of systems of interest. We have developed a three-dimensional model to assess the effect of ankle joint axis misalignments in ankle-foot orthoses. The model has been incorporated into a freely available computer program to assist understanding of trainees and others interested in orthotics. © The International Society for Prosthetics and Orthotics 2014.

Foot trajectory approximation using the pendulum model of walking.

PubMed

Fang, Juan; Vuckovic, Aleksandra; Galen, Sujay; Conway, Bernard A; Hunt, Kenneth J

2014-01-01

Generating a natural foot trajectory is an important objective in robotic systems for rehabilitation of walking. Human walking has pendular properties, so the pendulum model of walking has been used in bipedal robots which produce rhythmic gait patterns. Whether natural foot trajectories can be produced by the pendulum model needs to be addressed as a first step towards applying the pendulum concept in gait orthosis design. This study investigated circle approximation of the foot trajectories, with focus on the geometry of the pendulum model of walking. Three able-bodied subjects walked overground at various speeds, and foot trajectories relative to the hip were analysed. Four circle approximation approaches were developed, and best-fit circle algorithms were derived to fit the trajectories of the ankle, heel and toe. The study confirmed that the ankle and heel trajectories during stance and the toe trajectory in both the stance and the swing phases during walking at various speeds could be well modelled by a rigid pendulum. All the pendulum models were centred around the hip with pendular lengths approximately equal to the segment distances from the hip. This observation provides a new approach for using the pendulum model of walking in gait orthosis design.

Multi-object segmentation using coupled nonparametric shape and relative pose priors

NASA Astrophysics Data System (ADS)

Uzunbas, Mustafa Gökhan; Soldea, Octavian; Çetin, Müjdat; Ünal, Gözde; Erçil, Aytül; Unay, Devrim; Ekin, Ahmet; Firat, Zeynep

2009-02-01

We present a new method for multi-object segmentation in a maximum a posteriori estimation framework. Our method is motivated by the observation that neighboring or coupling objects in images generate configurations and co-dependencies which could potentially aid in segmentation if properly exploited. Our approach employs coupled shape and inter-shape pose priors that are computed using training images in a nonparametric multi-variate kernel density estimation framework. The coupled shape prior is obtained by estimating the joint shape distribution of multiple objects and the inter-shape pose priors are modeled via standard moments. Based on such statistical models, we formulate an optimization problem for segmentation, which we solve by an algorithm based on active contours. Our technique provides significant improvements in the segmentation of weakly contrasted objects in a number of applications. In particular for medical image analysis, we use our method to extract brain Basal Ganglia structures, which are members of a complex multi-object system posing a challenging segmentation problem. We also apply our technique to the problem of handwritten character segmentation. Finally, we use our method to segment cars in urban scenes.

An adaptive multi-feature segmentation model for infrared image

NASA Astrophysics Data System (ADS)

Zhang, Tingting; Han, Jin; Zhang, Yi; Bai, Lianfa

2016-04-01

Active contour models (ACM) have been extensively applied to image segmentation, conventional region-based active contour models only utilize global or local single feature information to minimize the energy functional to drive the contour evolution. Considering the limitations of original ACMs, an adaptive multi-feature segmentation model is proposed to handle infrared images with blurred boundaries and low contrast. In the proposed model, several essential local statistic features are introduced to construct a multi-feature signed pressure function (MFSPF). In addition, we draw upon the adaptive weight coefficient to modify the level set formulation, which is formed by integrating MFSPF with local statistic features and signed pressure function with global information. Experimental results demonstrate that the proposed method can make up for the inadequacy of the original method and get desirable results in segmenting infrared images.

Reliability and minimal detectable difference in multisegment foot kinematics during shod walking and running.

PubMed

Milner, Clare E; Brindle, Richard A

2016-01-01

There has been increased interest recently in measuring kinematics within the foot during gait. While several multisegment foot models have appeared in the literature, the Oxford foot model has been used frequently for both walking and running. Several studies have reported the reliability for the Oxford foot model, but most studies to date have reported reliability for barefoot walking. The purpose of this study was to determine between-day (intra-rater) and within-session (inter-trial) reliability of the modified Oxford foot model during shod walking and running and calculate minimum detectable difference for common variables of interest. Healthy adult male runners participated. Participants ran and walked in the gait laboratory for five trials of each. Three-dimensional gait analysis was conducted and foot and ankle joint angle time series data were calculated. Participants returned for a second gait analysis at least 5 days later. Intraclass correlation coefficients and minimum detectable difference were determined for walking and for running, to indicate both within-session and between-day reliability. Overall, relative variables were more reliable than absolute variables, and within-session reliability was greater than between-day reliability. Between-day intraclass correlation coefficients were comparable to those reported previously for adults walking barefoot. It is an extension in the use of the Oxford foot model to incorporate wearing a shoe while maintaining marker placement directly on the skin for each segment. These reliability data for walking and running will aid in the determination of meaningful differences in studies which use this model during shod gait. Copyright © 2015 Elsevier B.V. All rights reserved.

Hierarchical combinatorial deep learning architecture for pancreas segmentation of medical computed tomography cancer images.

PubMed

Fu, Min; Wu, Wenming; Hong, Xiafei; Liu, Qiuhua; Jiang, Jialin; Ou, Yaobin; Zhao, Yupei; Gong, Xinqi

2018-04-24

Efficient computational recognition and segmentation of target organ from medical images are foundational in diagnosis and treatment, especially about pancreas cancer. In practice, the diversity in appearance of pancreas and organs in abdomen, makes detailed texture information of objects important in segmentation algorithm. According to our observations, however, the structures of previous networks, such as the Richer Feature Convolutional Network (RCF), are too coarse to segment the object (pancreas) accurately, especially the edge. In this paper, we extend the RCF, proposed to the field of edge detection, for the challenging pancreas segmentation, and put forward a novel pancreas segmentation network. By employing multi-layer up-sampling structure replacing the simple up-sampling operation in all stages, the proposed network fully considers the multi-scale detailed contexture information of object (pancreas) to perform per-pixel segmentation. Additionally, using the CT scans, we supply and train our network, thus get an effective pipeline. Working with our pipeline with multi-layer up-sampling model, we achieve better performance than RCF in the task of single object (pancreas) segmentation. Besides, combining with multi scale input, we achieve the 76.36% DSC (Dice Similarity Coefficient) value in testing data. The results of our experiments show that our advanced model works better than previous networks in our dataset. On the other words, it has better ability in catching detailed contexture information. Therefore, our new single object segmentation model has practical meaning in computational automatic diagnosis.

Estimates of Median Flows for Streams on the 1999 Kansas Surface Water Register

USGS Publications Warehouse

Perry, Charles A.; Wolock, David M.; Artman, Joshua C.

2004-01-01

The Kansas State Legislature, by enacting Kansas Statute KSA 82a?2001 et. seq., mandated the criteria for determining which Kansas stream segments would be subject to classification by the State. One criterion for the selection as a classified stream segment is based on the statistic of median flow being equal to or greater than 1 cubic foot per second. As specified by KSA 82a?2001 et. seq., median flows were determined from U.S. Geological Survey streamflow-gaging-station data by using the most-recent 10 years of gaged data (KSA) for each streamflow-gaging station. Median flows also were determined by using gaged data from the entire period of record (all-available hydrology, AAH). Least-squares multiple regression techniques were used, along with Tobit analyses, to develop equations for estimating median flows for uncontrolled stream segments. The drainage area of the gaging stations on uncontrolled stream segments used in the regression analyses ranged from 2.06 to 12,004 square miles. A logarithmic transformation of the data was needed to develop the best linear relation for computing median flows. In the regression analyses, the significant climatic and basin characteristics, in order of importance, were drainage area, mean annual precipitation, mean basin permeability, and mean basin slope. Tobit analyses of KSA data yielded a model standard error of prediction of 0.285 logarithmic units, and the best equations using Tobit analyses of AAH data had a model standard error of prediction of 0.250 logarithmic units. These regression equations and an interpolation procedure were used to compute median flows for the uncontrolled stream segments on the 1999 Kansas Surface Water Register. Measured median flows from gaging stations were incorporated into the regression-estimated median flows along the stream segments where available. The segments that were uncontrolled were interpolated using gaged data weighted according to the drainage area and the bias between the regression-estimated and gaged flow information. On controlled segments of Kansas streams, the median flow information was interpolated between gaging stations using only gaged data weighted by drainage area. Of the 2,232 total stream segments on the Kansas Surface Water Register, 34.5 percent of the segments had an estimated median streamflow of less than 1 cubic foot per second when the KSA analysis was used. When the AAH analysis was used, 36.2 percent of the segments had an estimated median streamflow of less than 1 cubic foot per second. This report supercedes U.S. Geological Survey Water-Resources Investigations Report 02?4292.

A sea-land segmentation algorithm based on multi-feature fusion for a large-field remote sensing image

NASA Astrophysics Data System (ADS)

Li, Jing; Xie, Weixin; Pei, Jihong

2018-03-01

Sea-land segmentation is one of the key technologies of sea target detection in remote sensing images. At present, the existing algorithms have the problems of low accuracy, low universality and poor automatic performance. This paper puts forward a sea-land segmentation algorithm based on multi-feature fusion for a large-field remote sensing image removing island. Firstly, the coastline data is extracted and all of land area is labeled by using the geographic information in large-field remote sensing image. Secondly, three features (local entropy, local texture and local gradient mean) is extracted in the sea-land border area, and the three features combine a 3D feature vector. And then the MultiGaussian model is adopted to describe 3D feature vectors of sea background in the edge of the coastline. Based on this multi-gaussian sea background model, the sea pixels and land pixels near coastline are classified more precise. Finally, the coarse segmentation result and the fine segmentation result are fused to obtain the accurate sea-land segmentation. Comparing and analyzing the experimental results by subjective vision, it shows that the proposed method has high segmentation accuracy, wide applicability and strong anti-disturbance ability.

3D finite element model of the diabetic neuropathic foot: a gait analysis driven approach.

PubMed

Guiotto, Annamaria; Sawacha, Zimi; Guarneri, Gabriella; Avogaro, Angelo; Cobelli, Claudio

2014-09-22

Diabetic foot is an invalidating complication of diabetes that can lead to foot ulcers. Three-dimensional (3D) finite element analysis (FEA) allows characterizing the loads developed in the different anatomical structures of the foot in dynamic conditions. The aim of this study was to develop a subject specific 3D foot FE model (FEM) of a diabetic neuropathic (DNS) and a healthy (HS) subject, whose subject specificity can be found in term of foot geometry and boundary conditions. Kinematics, kinetics and plantar pressure (PP) data were extracted from the gait analysis trials of the two subjects with this purpose. The FEM were developed segmenting bones, cartilage and skin from MRI and drawing a horizontal plate as ground support. Materials properties were adopted from previous literature. FE simulations were run with the kinematics and kinetics data of four different phases of the stance phase of gait (heel strike, loading response, midstance and push off). FEMs were then driven by group gait data of 10 neuropathic and 10 healthy subjects. Model validation focused on agreement between FEM-simulated and experimental PP. The peak values and the total distribution of the pressures were compared for this purpose. Results showed that the models were less robust when driven from group data and underestimated the PP in each foot subarea. In particular in the case of the neuropathic subject's model the mean errors between experimental and simulated data were around the 20% of the peak values. This knowledge is crucial in understanding the aetiology of diabetic foot. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Dynamic Finite Element Analysis of Human Foot Complex in the Sagittal Plane during Level Walking

PubMed Central

Qian, Zhihui; Ren, Lei; Ding, Yun; Hutchinson, John R.; Ren, Luquan

2013-01-01

The objective of this study is to develop a computational framework for investigating the dynamic behavior and the internal loading conditions of the human foot complex during locomotion. A subject-specific dynamic finite element model in the sagittal plane was constructed based on anatomical structures segmented from medical CT scan images. Three-dimensional gait measurements were conducted to support and validate the model. Ankle joint forces and moment derived from gait measurements were used to drive the model. Explicit finite element simulations were conducted, covering the entire stance phase from heel-strike impact to toe-off. The predicted ground reaction forces, center of pressure, foot bone motions and plantar surface pressure showed reasonably good agreement with the gait measurement data over most of the stance phase. The prediction discrepancies can be explained by the assumptions and limitations of the model. Our analysis showed that a dynamic FE simulation can improve the prediction accuracy in the peak plantar pressures at some parts of the foot complex by 10%–33% compared to a quasi-static FE simulation. However, to simplify the costly explicit FE simulation, the proposed model is confined only to the sagittal plane and has a simplified representation of foot structure. The dynamic finite element foot model proposed in this study would provide a useful tool for future extension to a fully muscle-driven dynamic three-dimensional model with detailed representation of all major anatomical structures, in order to investigate the structural dynamics of the human foot musculoskeletal system during normal or even pathological functioning. PMID:24244500

A dynamic finite element analysis of human foot complex in the sagittal plane during level walking.

PubMed

Qian, Zhihui; Ren, Lei; Ding, Yun; Hutchinson, John R; Ren, Luquan

2013-01-01

The objective of this study is to develop a computational framework for investigating the dynamic behavior and the internal loading conditions of the human foot complex during locomotion. A subject-specific dynamic finite element model in the sagittal plane was constructed based on anatomical structures segmented from medical CT scan images. Three-dimensional gait measurements were conducted to support and validate the model. Ankle joint forces and moment derived from gait measurements were used to drive the model. Explicit finite element simulations were conducted, covering the entire stance phase from heel-strike impact to toe-off. The predicted ground reaction forces, center of pressure, foot bone motions and plantar surface pressure showed reasonably good agreement with the gait measurement data over most of the stance phase. The prediction discrepancies can be explained by the assumptions and limitations of the model. Our analysis showed that a dynamic FE simulation can improve the prediction accuracy in the peak plantar pressures at some parts of the foot complex by 10%-33% compared to a quasi-static FE simulation. However, to simplify the costly explicit FE simulation, the proposed model is confined only to the sagittal plane and has a simplified representation of foot structure. The dynamic finite element foot model proposed in this study would provide a useful tool for future extension to a fully muscle-driven dynamic three-dimensional model with detailed representation of all major anatomical structures, in order to investigate the structural dynamics of the human foot musculoskeletal system during normal or even pathological functioning.

Automatic abdominal multi-organ segmentation using deep convolutional neural network and time-implicit level sets.

PubMed

Hu, Peijun; Wu, Fa; Peng, Jialin; Bao, Yuanyuan; Chen, Feng; Kong, Dexing

2017-03-01

Multi-organ segmentation from CT images is an essential step for computer-aided diagnosis and surgery planning. However, manual delineation of the organs by radiologists is tedious, time-consuming and poorly reproducible. Therefore, we propose a fully automatic method for the segmentation of multiple organs from three-dimensional abdominal CT images. The proposed method employs deep fully convolutional neural networks (CNNs) for organ detection and segmentation, which is further refined by a time-implicit multi-phase evolution method. Firstly, a 3D CNN is trained to automatically localize and delineate the organs of interest with a probability prediction map. The learned probability map provides both subject-specific spatial priors and initialization for subsequent fine segmentation. Then, for the refinement of the multi-organ segmentation, image intensity models, probability priors as well as a disjoint region constraint are incorporated into an unified energy functional. Finally, a novel time-implicit multi-phase level-set algorithm is utilized to efficiently optimize the proposed energy functional model. Our method has been evaluated on 140 abdominal CT scans for the segmentation of four organs (liver, spleen and both kidneys). With respect to the ground truth, average Dice overlap ratios for the liver, spleen and both kidneys are 96.0, 94.2 and 95.4%, respectively, and average symmetric surface distance is less than 1.3 mm for all the segmented organs. The computation time for a CT volume is 125 s in average. The achieved accuracy compares well to state-of-the-art methods with much higher efficiency. A fully automatic method for multi-organ segmentation from abdominal CT images was developed and evaluated. The results demonstrated its potential in clinical usage with high effectiveness, robustness and efficiency.

Optimal Body Size and Limb Length Ratios Associated with 100-m Personal-Best Swim Speeds.

PubMed

Nevill, Alan M; Oxford, Samuel W; Duncan, Michael J

2015-08-01

This study aims to identify optimal body size and limb segment length ratios associated with 100-m personal-best (PB) swim speeds in children and adolescents. Fifty national-standard youth swimmers (21 males and 29 females age 11-16 yr; mean ± SD age, 13.5 ± 1.5 yr) participated in the study. Anthropometry comprised stature; body mass; skinfolds; maturity offset; upper arm, lower arm, and hand lengths; and upper leg, lower leg, and foot lengths. Swimming performance was taken as the PB time recorded in competition for the 100-m freestyle swim. To identify the optimal body size and body composition components associated with 100-m PB swim speeds (having controlled for age and maturity offset), we adopted a multiplicative allometric log-linear regression model, which was refined using backward elimination. Lean body mass was the singularly most important whole-body characteristic. Stature and body mass did not contribute to the model, suggesting that the advantage of longer levers was limb-specific rather than a general whole-body advantage. The allometric model also identified that having greater limb segment length ratios [i.e., arm ratio = (low arm)/(upper arm); foot-to-leg ratio = (foot)/(lower leg)] was key to PB swim speeds. It is only by adopting multiplicative allometric models that the above mentioned ratios could have been derived. The advantage of having a greater lower arm is clear; however, having a shorter upper arm (achieved by adopting a closer elbow angle technique or by possessing a naturally endowed shorter upper arm), at the same time, is a new insight into swimming performance. A greater foot-to-lower-leg ratio suggests that a combination of larger feet and shorter lower leg length may also benefit PB swim speeds.

An anatomically based protocol for the description of foot segment kinematics during gait.

PubMed

Leardini, A; Benedetti, M G; Catani, F; Simoncini, L; Giannini, S

1999-10-01

To design a technique for the in vivo description of ankle and other foot joint rotations to be applied in routine functional evaluation using non-invasive stereophotogrammetry. Position and orientation of tibia/fibula, calcaneus, mid-foot, 1st metatarsal and hallux segments were tracked during the stance phase of walking in nine asymptomatic subjects. Rigid clusters of reflective markers were used for foot segment pose estimation. Anatomical landmark calibration was applied for the reconstruction of anatomical landmarks. Previous studies have analysed only a limited number of joints or have proposed invasive techniques. Anatomical landmark trajectories were reconstructed in the laboratory frame using data from the anatomical calibration procedure. Anatomical co-ordinate frames were defined using the obtained landmark trajectories. Joint co-ordinate systems were used to calculate corresponding joint rotations in all three anatomical planes. The patterns of the joint rotations were highly repeatable within subjects. Consistent patterns between subjects were also exhibited at most of the joints. The method proposed enables a detailed description of ankle and other foot joint rotations on an anatomical base. Joint rotations can therefore be expressed in the well-established terminology necessary for their clinical interpretation. Functional evaluation of patients affected by foot diseases has recently called for more detailed and non-invasive protocols for the description of foot joint rotations during gait. The proposed method can help clinicians to distinguish between normal and pathological pattern of foot joint rotations, and to quantitatively assess the restoration of normal function after treatment.

TU-AB-202-11: Tumor Segmentation by Fusion of Multi-Tracer PET Images Using Copula Based Statistical Methods

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

Lapuyade-Lahorgue, J; Ruan, S; Li, H

Purpose: Multi-tracer PET imaging is getting more attention in radiotherapy by providing additional tumor volume information such as glucose and oxygenation. However, automatic PET-based tumor segmentation is still a very challenging problem. We propose a statistical fusion approach to joint segment the sub-area of tumors from the two tracers FDG and FMISO PET images. Methods: Non-standardized Gamma distributions are convenient to model intensity distributions in PET. As a serious correlation exists in multi-tracer PET images, we proposed a new fusion method based on copula which is capable to represent dependency between different tracers. The Hidden Markov Field (HMF) model ismore » used to represent spatial relationship between PET image voxels and statistical dynamics of intensities for each modality. Real PET images of five patients with FDG and FMISO are used to evaluate quantitatively and qualitatively our method. A comparison between individual and multi-tracer segmentations was conducted to show advantages of the proposed fusion method. Results: The segmentation results show that fusion with Gaussian copula can receive high Dice coefficient of 0.84 compared to that of 0.54 and 0.3 of monomodal segmentation results based on individual segmentation of FDG and FMISO PET images. In addition, high correlation coefficients (0.75 to 0.91) for the Gaussian copula for all five testing patients indicates the dependency between tumor regions in the multi-tracer PET images. Conclusion: This study shows that using multi-tracer PET imaging can efficiently improve the segmentation of tumor region where hypoxia and glucidic consumption are present at the same time. Introduction of copulas for modeling the dependency between two tracers can simultaneously take into account information from both tracers and deal with two pathological phenomena. Future work will be to consider other families of copula such as spherical and archimedian copulas, and to eliminate partial volume effect by considering dependency between neighboring voxels.« less

Stature estimation from the lengths of the growing foot-a study on North Indian adolescents.

PubMed

Krishan, Kewal; Kanchan, Tanuj; Passi, Neelam; DiMaggio, John A

2012-12-01

Stature estimation is considered as one of the basic parameters of the investigation process in unknown and commingled human remains in medico-legal case work. Race, age and sex are the other parameters which help in this process. Stature estimation is of the utmost importance as it completes the biological profile of a person along with the other three parameters of identification. The present research is intended to formulate standards for stature estimation from foot dimensions in adolescent males from North India and study the pattern of foot growth during the growing years. 154 male adolescents from the Northern part of India were included in the study. Besides stature, five anthropometric measurements that included the length of the foot from each toe (T1, T2, T3, T4, and T5 respectively) to pternion were measured on each foot. The data was analyzed statistically using Student's t-test, Pearson's correlation, linear and multiple regression analysis for estimation of stature and growth of foot during ages 13-18 years. Correlation coefficients between stature and all the foot measurements were found to be highly significant and positively correlated. Linear regression models and multiple regression models (with age as a co-variable) were derived for estimation of stature from the different measurements of the foot. Multiple regression models (with age as a co-variable) estimate stature with greater accuracy than the regression models for 13-18 years age group. The study shows the growth pattern of feet in North Indian adolescents and indicates that anthropometric measurements of the foot and its segments are valuable in estimation of stature in growing individuals of that population. Copyright © 2012 Elsevier Ltd. All rights reserved.

Automatic 3D kidney segmentation based on shape constrained GC-OAAM

NASA Astrophysics Data System (ADS)

Chen, Xinjian; Summers, Ronald M.; Yao, Jianhua

2011-03-01

The kidney can be classified into three main tissue types: renal cortex, renal medulla and renal pelvis (or collecting system). Dysfunction of different renal tissue types may cause different kidney diseases. Therefore, accurate and efficient segmentation of kidney into different tissue types plays a very important role in clinical research. In this paper, we propose an automatic 3D kidney segmentation method which segments the kidney into the three different tissue types: renal cortex, medulla and pelvis. The proposed method synergistically combines active appearance model (AAM), live wire (LW) and graph cut (GC) methods, GC-OAAM for short. Our method consists of two main steps. First, a pseudo 3D segmentation method is employed for kidney initialization in which the segmentation is performed slice-by-slice via a multi-object oriented active appearance model (OAAM) method. An improved iterative model refinement algorithm is proposed for the AAM optimization, which synergistically combines the AAM and LW method. Multi-object strategy is applied to help the object initialization. The 3D model constraints are applied to the initialization result. Second, the object shape information generated from the initialization step is integrated into the GC cost computation. A multi-label GC method is used to segment the kidney into cortex, medulla and pelvis. The proposed method was tested on 19 clinical arterial phase CT data sets. The preliminary results showed the feasibility and efficiency of the proposed method.

Image Segmentation Method Using Fuzzy C Mean Clustering Based on Multi-Objective Optimization

NASA Astrophysics Data System (ADS)

Chen, Jinlin; Yang, Chunzhi; Xu, Guangkui; Ning, Li

2018-04-01

Image segmentation is not only one of the hottest topics in digital image processing, but also an important part of computer vision applications. As one kind of image segmentation algorithms, fuzzy C-means clustering is an effective and concise segmentation algorithm. However, the drawback of FCM is that it is sensitive to image noise. To solve the problem, this paper designs a novel fuzzy C-mean clustering algorithm based on multi-objective optimization. We add a parameter λ to the fuzzy distance measurement formula to improve the multi-objective optimization. The parameter λ can adjust the weights of the pixel local information. In the algorithm, the local correlation of neighboring pixels is added to the improved multi-objective mathematical model to optimize the clustering cent. Two different experimental results show that the novel fuzzy C-means approach has an efficient performance and computational time while segmenting images by different type of noises.

Changes in foot and shank coupling due to alterations in foot strike pattern during running.

PubMed

Pohl, Michael B; Buckley, John G

2008-03-01

Determining if and how the kinematic relationship between adjacent body segments changes when an individual's gait pattern is experimentally manipulated can yield insight into the robustness of the kinematic coupling across the associated joint(s). The aim of this study was to assess the effects on the kinematic coupling between the forefoot, rearfoot and shank during ground contact of running with alteration in foot strike pattern. Twelve subjects ran over-ground using three different foot strike patterns (heel strike, forefoot strike, toe running). Kinematic data were collected of the forefoot, rearfoot and shank, which were modelled as rigid segments. Coupling at the ankle-complex and midfoot joints was assessed using cross-correlation and vector coding techniques. In general good coupling was found between rearfoot frontal plane motion and transverse plane shank rotation regardless of foot strike pattern. Forefoot motion was also strongly coupled with rearfoot frontal plane motion. Subtle differences were noted in the amount of rearfoot eversion transferred into shank internal rotation in the first 10-15% of stance during heel strike running compared to forefoot and toe running, and this was accompanied by small alterations in forefoot kinematics. These findings indicate that during ground contact in running there is strong coupling between the rearfoot and shank via the action of the joints in the ankle-complex. In addition, there was good coupling of both sagittal and transverse plane forefoot with rearfoot frontal plane motion via the action of the midfoot joints.

Conditioning a segmented stem profile model for two diameter measurements

Treesearch

Raymond L. Czaplewski; Joe P. Mcclure

1988-01-01

The stem profile model of Max and Burkhart (1976) is conditioned for dbh and a second upper stem measurement. This model was applied to a loblolly pine data set using diameter outside bark at 5.3m (i.e., height of 17.3 foot Girard form class) as the second upper stem measurement, and then compared to the original, unconditioned model. Variance of residuals was reduced...

Effect of kinesiotaping, non-elastic taping and bracing on segmental foot kinematics during drop landing in healthy subjects and subjects with chronic ankle instability.

PubMed

Kuni, B; Mussler, J; Kalkum, E; Schmitt, H; Wolf, S I

2016-09-01

To evaluate the effects of kinesiotape, non-elastic tape, and soft brace on segmental foot kinematics during drop landing in subjects with chronic ankle instability and healthy subjects. Controlled study with repeated measurements. Three-dimensional motion analysis laboratory. Twenty participants with chronic ankle instability and 20 healthy subjects. The subjects performed drop landings with 17 retroreflective markers on the foot and lower leg in four conditions: barefoot, with kinesiotape, with non-elastic tape and with a soft brace. Ranges of motion of foot segments using a foot measurement method. In participants with chronic ankle instability, midfoot movement in the frontal plane (inclination of the medial arch) was reduced significantly by non-elastic taping, but kinesiotaping and bracing had no effect. In healthy subjects, both non-elastic taping and bracing reduced that movement. In both groups, non-elastic taping and bracing reduced rearfoot excursion in inversion/eversion significantly, which indicates a stabilisation effect. No such effect was found with kinesiotaping. All three methods reduced maximum plantar flexion significantly. Non-elastic taping stabilised the midfoot best in patients with chronic ankle instability, while kinesiotaping did not influence foot kinematics other than to stabilise the rearfoot in the sagittal plane. ClinicalTrials.gov NCT01810471. Copyright © 2015 Chartered Society of Physiotherapy. Published by Elsevier Ltd. All rights reserved.

Statistical label fusion with hierarchical performance models

PubMed Central

Asman, Andrew J.; Dagley, Alexander S.; Landman, Bennett A.

2014-01-01

Label fusion is a critical step in many image segmentation frameworks (e.g., multi-atlas segmentation) as it provides a mechanism for generalizing a collection of labeled examples into a single estimate of the underlying segmentation. In the multi-label case, typical label fusion algorithms treat all labels equally – fully neglecting the known, yet complex, anatomical relationships exhibited in the data. To address this problem, we propose a generalized statistical fusion framework using hierarchical models of rater performance. Building on the seminal work in statistical fusion, we reformulate the traditional rater performance model from a multi-tiered hierarchical perspective. This new approach provides a natural framework for leveraging known anatomical relationships and accurately modeling the types of errors that raters (or atlases) make within a hierarchically consistent formulation. Herein, we describe several contributions. First, we derive a theoretical advancement to the statistical fusion framework that enables the simultaneous estimation of multiple (hierarchical) performance models within the statistical fusion context. Second, we demonstrate that the proposed hierarchical formulation is highly amenable to the state-of-the-art advancements that have been made to the statistical fusion framework. Lastly, in an empirical whole-brain segmentation task we demonstrate substantial qualitative and significant quantitative improvement in overall segmentation accuracy. PMID:24817809

Development of a finite element model of female foot for high-heeled shoe design.

PubMed

Yu, Jia; Cheung, Jason Tak-Man; Fan, Yubo; Zhang, Yan; Leung, Aaron Kam-Lun; Zhang, Ming

2008-01-01

Wearing high-heeled shoes may produce deleterious effects on the musculoskeletal system while elevation of the shoe heel with arch insole insert is used as a treatment strategy for plantar fasciitis. Due to limitations of the experimental approaches, direct measurements of internal stress/strain of the foot are impossible or invasive. This study aims at developing a finite element model for evaluating the biomechanical effects of high-heeled support on the ankle-foot complex. A 3D anatomically detailed FE model of the female foot and ankle together with a high-heeled support was developed and used to investigate the plantar contact pressure and internal loading responses of the bony and soft tissue structures of the foot with varying heel heights during simulated balanced standing. In the balanced standing position with high-heeled support, a pronounced increase in von Mises stress at the first metatarsophalangeal (MTP) joint was predicted. The strain on plantar fascia decreased compared to the flat horizontal support and valgus deformity of the hallux was not significant. The increased stress in forefoot especially at the first MTP segment during prolonged high-heeled standing may contribute to progressive hallux valgus (HV) deformity. However, the reduced tensile strain in the plantar fascia with heel elevation may help relieve plantar fasciitis related pain and inflammation.

Method of Grassland Information Extraction Based on Multi-Level Segmentation and Cart Model

NASA Astrophysics Data System (ADS)

Qiao, Y.; Chen, T.; He, J.; Wen, Q.; Liu, F.; Wang, Z.

2018-04-01

It is difficult to extract grassland accurately by traditional classification methods, such as supervised method based on pixels or objects. This paper proposed a new method combing the multi-level segmentation with CART (classification and regression tree) model. The multi-level segmentation which combined the multi-resolution segmentation and the spectral difference segmentation could avoid the over and insufficient segmentation seen in the single segmentation mode. The CART model was established based on the spectral characteristics and texture feature which were excavated from training sample data. Xilinhaote City in Inner Mongolia Autonomous Region was chosen as the typical study area and the proposed method was verified by using visual interpretation results as approximate truth value. Meanwhile, the comparison with the nearest neighbor supervised classification method was obtained. The experimental results showed that the total precision of classification and the Kappa coefficient of the proposed method was 95 % and 0.9, respectively. However, the total precision of classification and the Kappa coefficient of the nearest neighbor supervised classification method was 80 % and 0.56, respectively. The result suggested that the accuracy of classification proposed in this paper was higher than the nearest neighbor supervised classification method. The experiment certificated that the proposed method was an effective extraction method of grassland information, which could enhance the boundary of grassland classification and avoid the restriction of grassland distribution scale. This method was also applicable to the extraction of grassland information in other regions with complicated spatial features, which could avoid the interference of woodland, arable land and water body effectively.

2. View looking Northeast. The masonry section of the viaduct, ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

2. View looking Northeast. The masonry section of the viaduct, west of the river, was 1,382 feet long and consisted of eight segmental arches of 83 foot span and two segmental arches of 97.5 foot span plus intervening sections of retaining wall. Eight of the Masonry arches, made of Berea Sandstone, still stand - Superior Avenue Viaduct, Cleveland East & West side, Cuyahoga Valley Vicinity, Cleveland, Cuyahoga County, OH

Corpus callosum segmentation using deep neural networks with prior information from multi-atlas images

NASA Astrophysics Data System (ADS)

Park, Gilsoon; Hong, Jinwoo; Lee, Jong-Min

2018-03-01

In human brain, Corpus Callosum (CC) is the largest white matter structure, connecting between right and left hemispheres. Structural features such as shape and size of CC in midsagittal plane are of great significance for analyzing various neurological diseases, for example Alzheimer's disease, autism and epilepsy. For quantitative and qualitative studies of CC in brain MR images, robust segmentation of CC is important. In this paper, we present a novel method for CC segmentation. Our approach is based on deep neural networks and the prior information generated from multi-atlas images. Deep neural networks have recently shown good performance in various image processing field. Convolutional neural networks (CNN) have shown outstanding performance for classification and segmentation in medical image fields. We used convolutional neural networks for CC segmentation. Multi-atlas based segmentation model have been widely used in medical image segmentation because atlas has powerful information about the target structure we want to segment, consisting of MR images and corresponding manual segmentation of the target structure. We combined the prior information, such as location and intensity distribution of target structure (i.e. CC), made from multi-atlas images in CNN training process for more improving training. The CNN with prior information showed better segmentation performance than without.

Development of gait segmentation methods for wearable foot pressure sensors.

PubMed

Crea, S; De Rossi, S M M; Donati, M; Reberšek, P; Novak, D; Vitiello, N; Lenzi, T; Podobnik, J; Munih, M; Carrozza, M C

2012-01-01

We present an automated segmentation method based on the analysis of plantar pressure signals recorded from two synchronized wireless foot insoles. Given the strict limits on computational power and power consumption typical of wearable electronic components, our aim is to investigate the capability of a Hidden Markov Model machine-learning method, to detect gait phases with different levels of complexity in the processing of the wearable pressure sensors signals. Therefore three different datasets are developed: raw voltage values, calibrated sensor signals and a calibrated estimation of total ground reaction force and position of the plantar center of pressure. The method is tested on a pool of 5 healthy subjects, through a leave-one-out cross validation. The results show high classification performances achieved using estimated biomechanical variables, being on average the 96%. Calibrated signals and raw voltage values show higher delays and dispersions in phase transition detection, suggesting a lower reliability for online applications.

Multi-scales region segmentation for ROI separation in digital mammograms

NASA Astrophysics Data System (ADS)

Zhang, Dapeng; Zhang, Di; Li, Yue; Wang, Wei

2017-02-01

Mammography is currently the most effective imaging modality used by radiologists for the screening of breast cancer. Segmentation is one of the key steps in the process of developing anatomical models for calculation of safe medical dose of radiation. This paper explores the potential of the statistical region merging segmentation technique for Breast segmentation in digital mammograms. First, the mammograms are pre-processing for regions enhancement, then the enhanced images are segmented using SRM with multi scales, finally these segmentations are combined for region of interest (ROI) separation and edge detection. The proposed algorithm uses multi-scales region segmentation in order to: separate breast region from background region, region edge detection and ROIs separation. The experiments are performed using a data set of mammograms from different patients, demonstrating the validity of the proposed criterion. Results show that, the statistical region merging segmentation algorithm actually can work on the segmentation of medical image and more accurate than another methods. And the outcome shows that the technique has a great potential to become a method of choice for segmentation of mammograms.

Active Contours Driven by Multi-Feature Gaussian Distribution Fitting Energy with Application to Vessel Segmentation.

PubMed

Wang, Lei; Zhang, Huimao; He, Kan; Chang, Yan; Yang, Xiaodong

2015-01-01

Active contour models are of great importance for image segmentation and can extract smooth and closed boundary contours of the desired objects with promising results. However, they cannot work well in the presence of intensity inhomogeneity. Hence, a novel region-based active contour model is proposed by taking image intensities and 'vesselness values' from local phase-based vesselness enhancement into account simultaneously to define a novel multi-feature Gaussian distribution fitting energy in this paper. This energy is then incorporated into a level set formulation with a regularization term for accurate segmentations. Experimental results based on publicly available STructured Analysis of the Retina (STARE) demonstrate our model is more accurate than some existing typical methods and can successfully segment most small vessels with varying width.

Can we predict body height from segmental bone length measurements? A study of 3,647 children.

PubMed

Cheng, J C; Leung, S S; Chiu, B S; Tse, P W; Lee, C W; Chan, A K; Xia, G; Leung, A K; Xu, Y Y

1998-01-01

It is well known that significant differences exist in the anthropometric data of different races and ethnic groups. This is a cross-sectional study on segmental bone length based on 3,647 Chinese children of equal sex distribution aged 3-18 years. The measurements included standing height, weight, arm span, foot length, and segmental bone length of the humerus, radius, ulna, and tibia. A normality growth chart of all the measured parameters was constructed. Statistical analysis of the results showed a very high linear correlation of height with arm span, foot length, and segmental bone lengths with a correlation coefficient of 0.96-0.99 for both sexes. No differences were found between the right and left side of all the segmental bone lengths. These Chinese children were found to have a proportional limb segmental length relative to the trunk.

Numerical simulation of the plantar pressure distribution in the diabetic foot during the push-off stance.

PubMed

Actis, Ricardo L; Ventura, Liliana B; Smith, Kirk E; Commean, Paul K; Lott, Donovan J; Pilgram, Thomas K; Mueller, Michael J

2006-08-01

The primary objective of conservative care for the diabetic foot is to protect the foot from excessive pressures. Pressure reduction and redistribution may be achieved by designing and fabricating orthotic devices based on foot structure, tissue mechanics, and external loads on the diabetic foot. The purpose of this paper is to describe the process used for the development of patient-specific mathematical models of the second and third rays of the foot, their solution by the finite element method, and their sensitivity to model parameters and assumptions. We hypothesized that the least complex model to capture the pressure distribution in the region of the metatarsal heads would include the bony structure segmented as toe, metatarsal and support, with cartilage between the bones, plantar fascia and soft tissue. To check the hypothesis, several models were constructed with different levels of details. The process of numerical simulation is comprised of three constituent parts: model definition, numerical solution and prediction. In this paper the main considerations relating model selection and computation of approximate solutions by the finite element method are considered. The fit of forefoot plantar pressures estimated using the FEA models and those explicitly tested were good as evidenced by high Pearson correlations (r=0.70-0.98) and small bias and dispersion. We concluded that incorporating bone support, metatarsal and toes with linear material properties, tendon and fascia with linear material properties, soft tissue with nonlinear material properties, is sufficient for the determination of the pressure distribution in the metatarsal head region in the push-off position, both barefoot and with shoe and total contact insert. Patient-specific examples are presented.

Conditional, Time-Dependent Probabilities for Segmented Type-A Faults in the WGCEP UCERF 2

USGS Publications Warehouse

Field, Edward H.; Gupta, Vipin

2008-01-01

This appendix presents elastic-rebound-theory (ERT) motivated time-dependent probabilities, conditioned on the date of last earthquake, for the segmented type-A fault models of the 2007 Working Group on California Earthquake Probabilities (WGCEP). These probabilities are included as one option in the WGCEP?s Uniform California Earthquake Rupture Forecast 2 (UCERF 2), with the other options being time-independent Poisson probabilities and an ?Empirical? model based on observed seismicity rate changes. A more general discussion of the pros and cons of all methods for computing time-dependent probabilities, as well as the justification of those chosen for UCERF 2, are given in the main body of this report (and the 'Empirical' model is also discussed in Appendix M). What this appendix addresses is the computation of conditional, time-dependent probabilities when both single- and multi-segment ruptures are included in the model. Computing conditional probabilities is relatively straightforward when a fault is assumed to obey strict segmentation in the sense that no multi-segment ruptures occur (e.g., WGCEP (1988, 1990) or see Field (2007) for a review of all previous WGCEPs; from here we assume basic familiarity with conditional probability calculations). However, and as we?ll see below, the calculation is not straightforward when multi-segment ruptures are included, in essence because we are attempting to apply a point-process model to a non point process. The next section gives a review and evaluation of the single- and multi-segment rupture probability-calculation methods used in the most recent statewide forecast for California (WGCEP UCERF 1; Petersen et al., 2007). We then present results for the methodology adopted here for UCERF 2. We finish with a discussion of issues and possible alternative approaches that could be explored and perhaps applied in the future. A fault-by-fault comparison of UCERF 2 probabilities with those of previous studies is given in the main part of this report.

Metatarsal Shape and Foot Type: A Geometric Morphometric Analysis.

PubMed

Telfer, Scott; Kindig, Matthew W; Sangeorzan, Bruce J; Ledoux, William R

2017-03-01

Planus and cavus foot types have been associated with an increased risk of pain and disability. Improving our understanding of the geometric differences between bones in different foot types may provide insights into injury risk profiles and have implications for the design of musculoskeletal and finite-element models. In this study, we performed a geometric morphometric analysis on the geometry of metatarsal bones from 65 feet, segmented from computed tomography (CT) scans. These were categorized into four foot types: pes cavus, neutrally aligned, asymptomatic pes planus, and symptomatic pes planus. Generalized procrustes analysis (GPA) followed by permutation tests was used to determine significant shape differences associated with foot type and sex, and principal component analysis was used to find the modes of variation for each metatarsal. Significant shape differences were found between foot types for all the metatarsals (p < 0.01), most notably in the case of the second metatarsal which showed significant pairwise differences across all the foot types. Analysis of the principal components of variation showed pes cavus bones to have reduced cross-sectional areas in the sagittal and frontal planes. The first (p = 0.02) and fourth metatarsals (p = 0.003) were found to have significant sex-based differences, with first metatarsals from females shown to have reduced width, and fourth metatarsals from females shown to have reduced frontal and sagittal plane cross-sectional areas. Overall, these findings suggest that metatarsal bones have distinct morphological characteristics that are associated with foot type and sex, with implications for our understanding of anatomy and numerical modeling of the foot.

Sequence and onset of whole-body coordination when turning in response to a visual trigger: comparing people with Parkinson's disease and healthy adults.

PubMed

Ashburn, A; Kampshoff, C; Burnett, M; Stack, E; Pickering, R M; Verheyden, G

2014-01-01

Turning round is a routine everyday activity that can often lead to instability. The purpose of this study was to investigate abnormalities of turning among people with Parkinson's disease (PwPD) through the measurement of sequence of body segments and latency response. Participants were asked to turn 180° and whole-body movements were recorded using CODAmotion and Visio Fast eye tracking equipment. Thirty-one independently mobile PwPD and 15 age-matched healthy controls participated in the study. We found that contrary to common belief, the head preceded movement of all other body segments (eyes, shoulders, pelvis, first and second foot). We also found interaction between group and body segment (P=0.005), indicating that overall, PwPD took longer to move from head to second foot than age-matched healthy controls. For PwPD only, interactions were found between disease severity and body segment (P<0.0001), between age group and body segment (P<0.0001) and between gender and body segments (P<0.0001). For each interaction, longer time periods were noted between moving the first foot after the pelvis, and moving the second foot after the first, and this was noted for PwPD in Hoehn and Yahr stage III-IV (in comparison to Hoehn and Yahr stage I-II); for PwPD who were under 70 years (in comparison with 70 years or over); and for ladies (in comparison with men). Our results indicate that in PwPD and healthy elderly, turning-on-the-spot might not follow the top-to-bottom approach we know from previous research. Copyright © 2013. Published by Elsevier B.V.

A tool for multi-scale modelling of the renal nephron

PubMed Central

Nickerson, David P.; Terkildsen, Jonna R.; Hamilton, Kirk L.; Hunter, Peter J.

2011-01-01

We present the development of a tool, which provides users with the ability to visualize and interact with a comprehensive description of a multi-scale model of the renal nephron. A one-dimensional anatomical model of the nephron has been created and is used for visualization and modelling of tubule transport in various nephron anatomical segments. Mathematical models of nephron segments are embedded in the one-dimensional model. At the cellular level, these segment models use models encoded in CellML to describe cellular and subcellular transport kinetics. A web-based presentation environment has been developed that allows the user to visualize and navigate through the multi-scale nephron model, including simulation results, at the different spatial scales encompassed by the model description. The Zinc extension to Firefox is used to provide an interactive three-dimensional view of the tubule model and the native Firefox rendering of scalable vector graphics is used to present schematic diagrams for cellular and subcellular scale models. The model viewer is embedded in a web page that dynamically presents content based on user input. For example, when viewing the whole nephron model, the user might be presented with information on the various embedded segment models as they select them in the three-dimensional model view. Alternatively, the user chooses to focus the model viewer on a cellular model located in a particular nephron segment in order to view the various membrane transport proteins. Selecting a specific protein may then present the user with a description of the mathematical model governing the behaviour of that protein—including the mathematical model itself and various simulation experiments used to validate the model against the literature. PMID:22670210

Novel active contour model based on multi-variate local Gaussian distribution for local segmentation of MR brain images

NASA Astrophysics Data System (ADS)

Zheng, Qiang; Li, Honglun; Fan, Baode; Wu, Shuanhu; Xu, Jindong

2017-12-01

Active contour model (ACM) has been one of the most widely utilized methods in magnetic resonance (MR) brain image segmentation because of its ability of capturing topology changes. However, most of the existing ACMs only consider single-slice information in MR brain image data, i.e., the information used in ACMs based segmentation method is extracted only from one slice of MR brain image, which cannot take full advantage of the adjacent slice images' information, and cannot satisfy the local segmentation of MR brain images. In this paper, a novel ACM is proposed to solve the problem discussed above, which is based on multi-variate local Gaussian distribution and combines the adjacent slice images' information in MR brain image data to satisfy segmentation. The segmentation is finally achieved through maximizing the likelihood estimation. Experiments demonstrate the advantages of the proposed ACM over the single-slice ACM in local segmentation of MR brain image series.

Vertical ground reaction forces in patients after calcaneal trauma surgery.

PubMed

van Hoeve, S; Verbruggen, J; Willems, P; Meijer, K; Poeze, M

2017-10-01

Vertical ground reaction forces (VGRFs) are altered in patients after foot trauma. It is not known if this correlates with ankle kinematics. The aim of this study was to analyze VGRFs in patients after calcaneal trauma and correlate them to patient-reported outcome measures (PROMs), radiographic findings and kinematic analysis, using a multi-segment foot model. In addition, we determined the predictive value of VGRFs to identify patients with altered foot kinematics. Thirteen patients (13 feet) with displaced intra-articular calcaneal fractures, were included an average of two years after trauma surgery. PROMs, radiographic findings on postoperative computed tomography scans, gait analysis using the Oxford foot model and VGRFs were analysed during gait. Results were compared with those of 11 healthy subjects (20 feet). Speed was equal in both groups, with healthy subjects walking at self-selected slow speed (0.94±0.18m/s) and patients after surgery walking at self-selected normal speed (0.94±0.29m/s). ROC curves were used to determine the predictive value. Patients after calcaneal surgery showed a lower minimum force during midstance (p=0.004) and a lower maximum force during toe-off (p=0.011). This parameter correlated significantly with the range of motion in the sagittal plane during the push-off phase (r 0.523, p=0.002), as well as with PROMs and with postoperative residual step-off (r 0.423, p=0.016). Combining these two parameters yielded a cut-off value of 193% (p<0.001), area under the curve 0.93 (95%confidence interval 0.84-1.00). Patients after calcaneal fracture showed lower minimum force during midstance and lower maximum force during toe-off compared to healthy subjects. This lower maximum force during push-off correlated significantly with PROMs, range of motion in the sagittal plane during push-off and radiographic postoperative residual step-off in the posterior facet of the calcaneal bone. VGRFs are a valuable screening tool for identifying patients with altered gait patterns. Copyright © 2017 Elsevier B.V. All rights reserved.

Global Kalman filter approaches to estimate absolute angles of lower limb segments.

PubMed

Nogueira, Samuel L; Lambrecht, Stefan; Inoue, Roberto S; Bortole, Magdo; Montagnoli, Arlindo N; Moreno, Juan C; Rocon, Eduardo; Terra, Marco H; Siqueira, Adriano A G; Pons, Jose L

2017-05-16

In this paper we propose the use of global Kalman filters (KFs) to estimate absolute angles of lower limb segments. Standard approaches adopt KFs to improve the performance of inertial sensors based on individual link configurations. In consequence, for a multi-body system like a lower limb exoskeleton, the inertial measurements of one link (e.g., the shank) are not taken into account in other link angle estimations (e.g., foot). Global KF approaches, on the other hand, correlate the collective contribution of all signals from lower limb segments observed in the state-space model through the filtering process. We present a novel global KF (matricial global KF) relying only on inertial sensor data, and validate both this KF and a previously presented global KF (Markov Jump Linear Systems, MJLS-based KF), which fuses data from inertial sensors and encoders from an exoskeleton. We furthermore compare both methods to the commonly used local KF. The results indicate that the global KFs performed significantly better than the local KF, with an average root mean square error (RMSE) of respectively 0.942° for the MJLS-based KF, 1.167° for the matrical global KF, and 1.202° for the local KFs. Including the data from the exoskeleton encoders also resulted in a significant increase in performance. The results indicate that the current practice of using KFs based on local models is suboptimal. Both the presented KF based on inertial sensor data, as well our previously presented global approach fusing inertial sensor data with data from exoskeleton encoders, were superior to local KFs. We therefore recommend to use global KFs for gait analysis and exoskeleton control.

A discriminative model-constrained graph cuts approach to fully automated pediatric brain tumor segmentation in 3-D MRI.

PubMed

Wels, Michael; Carneiro, Gustavo; Aplas, Alexander; Huber, Martin; Hornegger, Joachim; Comaniciu, Dorin

2008-01-01

In this paper we present a fully automated approach to the segmentation of pediatric brain tumors in multi-spectral 3-D magnetic resonance images. It is a top-down segmentation approach based on a Markov random field (MRF) model that combines probabilistic boosting trees (PBT) and lower-level segmentation via graph cuts. The PBT algorithm provides a strong discriminative observation model that classifies tumor appearance while a spatial prior takes into account the pair-wise homogeneity in terms of classification labels and multi-spectral voxel intensities. The discriminative model relies not only on observed local intensities but also on surrounding context for detecting candidate regions for pathology. A mathematically sound formulation for integrating the two approaches into a unified statistical framework is given. The proposed method is applied to the challenging task of detection and delineation of pediatric brain tumors. This segmentation task is characterized by a high non-uniformity of both the pathology and the surrounding non-pathologic brain tissue. A quantitative evaluation illustrates the robustness of the proposed method. Despite dealing with more complicated cases of pediatric brain tumors the results obtained are mostly better than those reported for current state-of-the-art approaches to 3-D MR brain tumor segmentation in adult patients. The entire processing of one multi-spectral data set does not require any user interaction, and takes less time than previously proposed methods.

Automatic Cell Segmentation in Fluorescence Images of Confluent Cell Monolayers Using Multi-object Geometric Deformable Model.

PubMed

Yang, Zhen; Bogovic, John A; Carass, Aaron; Ye, Mao; Searson, Peter C; Prince, Jerry L

2013-03-13

With the rapid development of microscopy for cell imaging, there is a strong and growing demand for image analysis software to quantitatively study cell morphology. Automatic cell segmentation is an important step in image analysis. Despite substantial progress, there is still a need to improve the accuracy, efficiency, and adaptability to different cell morphologies. In this paper, we propose a fully automatic method for segmenting cells in fluorescence images of confluent cell monolayers. This method addresses several challenges through a combination of ideas. 1) It realizes a fully automatic segmentation process by first detecting the cell nuclei as initial seeds and then using a multi-object geometric deformable model (MGDM) for final segmentation. 2) To deal with different defects in the fluorescence images, the cell junctions are enhanced by applying an order-statistic filter and principal curvature based image operator. 3) The final segmentation using MGDM promotes robust and accurate segmentation results, and guarantees no overlaps and gaps between neighboring cells. The automatic segmentation results are compared with manually delineated cells, and the average Dice coefficient over all distinguishable cells is 0.88.

Adaptive surrogate model based multi-objective transfer trajectory optimization between different libration points

NASA Astrophysics Data System (ADS)

Peng, Haijun; Wang, Wei

2016-10-01

An adaptive surrogate model-based multi-objective optimization strategy that combines the benefits of invariant manifolds and low-thrust control toward developing a low-computational-cost transfer trajectory between libration orbits around the L1 and L2 libration points in the Sun-Earth system has been proposed in this paper. A new structure for a multi-objective transfer trajectory optimization model that divides the transfer trajectory into several segments and gives the dominations for invariant manifolds and low-thrust control in different segments has been established. To reduce the computational cost of multi-objective transfer trajectory optimization, a mixed sampling strategy-based adaptive surrogate model has been proposed. Numerical simulations show that the results obtained from the adaptive surrogate-based multi-objective optimization are in agreement with the results obtained using direct multi-objective optimization methods, and the computational workload of the adaptive surrogate-based multi-objective optimization is only approximately 10% of that of direct multi-objective optimization. Furthermore, the generating efficiency of the Pareto points of the adaptive surrogate-based multi-objective optimization is approximately 8 times that of the direct multi-objective optimization. Therefore, the proposed adaptive surrogate-based multi-objective optimization provides obvious advantages over direct multi-objective optimization methods.

Modeling and stress analyses of a normal foot-ankle and a prosthetic foot-ankle complex.

PubMed

Ozen, Mustafa; Sayman, Onur; Havitcioglu, Hasan

2013-01-01

Total ankle replacement (TAR) is a relatively new concept and is becoming more popular for treatment of ankle arthritis and fractures. Because of the high costs and difficulties of experimental studies, the developments of TAR prostheses are progressing very slowly. For this reason, the medical imaging techniques such as CT, and MR have become more and more useful. The finite element method (FEM) is a widely used technique to estimate the mechanical behaviors of materials and structures in engineering applications. FEM has also been increasingly applied to biomechanical analyses of human bones, tissues and organs, thanks to the development of both the computing capabilities and the medical imaging techniques. 3-D finite element models of the human foot and ankle from reconstruction of MR and CT images have been investigated by some authors. In this study, data of geometries (used in modeling) of a normal and a prosthetic foot and ankle were obtained from a 3D reconstruction of CT images. The segmentation software, MIMICS was used to generate the 3D images of the bony structures, soft tissues and components of prosthesis of normal and prosthetic ankle-foot complex. Except the spaces between the adjacent surface of the phalanges fused, metatarsals, cuneiforms, cuboid, navicular, talus and calcaneus bones, soft tissues and components of prosthesis were independently developed to form foot and ankle complex. SOLIDWORKS program was used to form the boundary surfaces of all model components and then the solid models were obtained from these boundary surfaces. Finite element analyses software, ABAQUS was used to perform the numerical stress analyses of these models for balanced standing position. Plantar pressure and von Mises stress distributions of the normal and prosthetic ankles were compared with each other. There was a peak pressure increase at the 4th metatarsal, first metatarsal and talus bones and a decrease at the intermediate cuneiform and calcaneus bones, in prosthetic ankle-foot complex compared to normal one. The predicted plantar pressures and von Misses stress distributions for a normal foot were consistent with other FE models given in the literature. The present study is aimed to open new approaches for the development of ankle prosthesis.

Joint kinematics estimation using a multi-body kinematics optimisation and an extended Kalman filter, and embedding a soft tissue artefact model.

PubMed

Bonnet, Vincent; Richard, Vincent; Camomilla, Valentina; Venture, Gentiane; Cappozzo, Aurelio; Dumas, Raphaël

2017-09-06

To reduce the impact of the soft tissue artefact (STA) on the estimate of skeletal movement using stereophotogrammetric and skin-marker data, multi-body kinematics optimisation (MKO) and extended Kalman filters (EKF) have been proposed. This paper assessed the feasibility and efficiency of these methods when they embed a mathematical model of the STA and simultaneously estimate the ankle, knee and hip joint kinematics and the model parameters. A STA model was used that provides an estimate of the STA affecting the marker-cluster located on a body segment as a function of the kinematics of the adjacent joints. The MKO and the EKF were implemented with and without the STA model. To assess these methods, intra-cortical pin and skin markers located on the thigh, shank, and foot of three subjects and tracked during the stance phase of running were used. Embedding the STA model in MKO and EKF reduced the average RMS of marker tracking from 12.6 to 1.6mm and from 4.3 to 1.9mm, respectively, showing that a STA model trial-specific calibration is feasible. Nevertheless, with the STA model embedded in MKO, the RMS difference between the estimated and the reference joint kinematics determined from the pin markers slightly increased (from 2.0 to 2.1deg) On the contrary, when the STA model was embedded in the EKF, this RMS difference was slightly reduced (from 2.0 to 1.7deg) thus showing a better potentiality of this method to attenuate STA effects and improve the accuracy of joint kinematics estimate. Copyright © 2017 Elsevier Ltd. All rights reserved.

Analysis of joint force and torque for the human and non-human ape foot during bipedal walking with implications for the evolution of the foot.

PubMed

Wang, Weijie; Abboud, Rami J; Günther, Michael M; Crompton, Robin H

2014-08-01

The feet of apes have a different morphology from those of humans. Until now, it has merely been assumed that the morphology seen in humans must be adaptive for habitual bipedal walking, as the habitual use of bipedal walking is generally regarded as one of the most clear-cut differences between humans and apes. This study asks simply whether human skeletal proportions do actually enhance foot performance during human-like bipedalism, by examining the influence of foot proportions on force, torque and work in the foot joints during simulated bipedal walking. Skeletons of the common chimpanzee, orangutan, gorilla and human were represented by multi-rigid-body models, where the components of the foot make external contact via finite element surfaces. The models were driven by identical joint motion functions collected from experiments on human walking. Simulated contact forces between the ground and the foot were found to be reasonably comparable with measurements made during human walking using pressure- and force-platforms. Joint force, torque and work in the foot were then predicted. Within the limitations of our model, the results show that during simulated human-like bipedal walking, (1) the human and non-human ape (NHA) feet carry similar joint forces, although the distributions of the forces differ; (2) the NHA foot incurs larger joint torques than does the human foot, although the human foot has higher values in the first tarso-metatarsal and metatarso-phalangeal joints, whereas the NHA foot incurs higher values in the lateral digits; and (3) total work in the metatarso-phalangeal joints is lower in the human foot than in the NHA foot. The results indicate that human foot proportions are indeed well suited to performance in normal human walking. © 2014 Anatomical Society.

Analysis of joint force and torque for the human and non-human ape foot during bipedal walking with implications for the evolution of the foot

PubMed Central

Wang, Weijie; Abboud, Rami J; Günther, Michael M; Crompton, Robin H

2014-01-01

The feet of apes have a different morphology from those of humans. Until now, it has merely been assumed that the morphology seen in humans must be adaptive for habitual bipedal walking, as the habitual use of bipedal walking is generally regarded as one of the most clear-cut differences between humans and apes. This study asks simply whether human skeletal proportions do actually enhance foot performance during human-like bipedalism, by examining the influence of foot proportions on force, torque and work in the foot joints during simulated bipedal walking. Skeletons of the common chimpanzee, orangutan, gorilla and human were represented by multi-rigid-body models, where the components of the foot make external contact via finite element surfaces. The models were driven by identical joint motion functions collected from experiments on human walking. Simulated contact forces between the ground and the foot were found to be reasonably comparable with measurements made during human walking using pressure- and force-platforms. Joint force, torque and work in the foot were then predicted. Within the limitations of our model, the results show that during simulated human-like bipedal walking, (1) the human and non-human ape (NHA) feet carry similar joint forces, although the distributions of the forces differ; (2) the NHA foot incurs larger joint torques than does the human foot, although the human foot has higher values in the first tarso-metatarsal and metatarso-phalangeal joints, whereas the NHA foot incurs higher values in the lateral digits; and (3) total work in the metatarso-phalangeal joints is lower in the human foot than in the NHA foot. The results indicate that human foot proportions are indeed well suited to performance in normal human walking. PMID:24925580

Multi-atlas label fusion using hybrid of discriminative and generative classifiers for segmentation of cardiac MR images.

PubMed

Sedai, Suman; Garnavi, Rahil; Roy, Pallab; Xi Liang

2015-08-01

Multi-atlas segmentation first registers each atlas image to the target image and transfers the label of atlas image to the coordinate system of the target image. The transferred labels are then combined, using a label fusion algorithm. In this paper, we propose a novel label fusion method which aggregates discriminative learning and generative modeling for segmentation of cardiac MR images. First, a probabilistic Random Forest classifier is trained as a discriminative model to obtain the prior probability of a label at the given voxel of the target image. Then, a probability distribution of image patches is modeled using Gaussian Mixture Model for each label, providing the likelihood of the voxel belonging to the label. The final label posterior is obtained by combining the classification score and the likelihood score under Bayesian rule. Comparative study performed on MICCAI 2013 SATA Segmentation Challenge demonstrates that our proposed hybrid label fusion algorithm is accurate than other five state-of-the-art label fusion methods. The proposed method obtains dice similarity coefficient of 0.94 and 0.92 in segmenting epicardium and endocardium respectively. Moreover, our label fusion method achieves more accurate segmentation results compared to four other label fusion methods.

Accurate Segmentation of CT Male Pelvic Organs via Regression-based Deformable Models and Multi-task Random Forests

PubMed Central

Gao, Yaozong; Shao, Yeqin; Lian, Jun; Wang, Andrew Z.; Chen, Ronald C.

2016-01-01

Segmenting male pelvic organs from CT images is a prerequisite for prostate cancer radiotherapy. The efficacy of radiation treatment highly depends on segmentation accuracy. However, accurate segmentation of male pelvic organs is challenging due to low tissue contrast of CT images, as well as large variations of shape and appearance of the pelvic organs. Among existing segmentation methods, deformable models are the most popular, as shape prior can be easily incorporated to regularize the segmentation. Nonetheless, the sensitivity to initialization often limits their performance, especially for segmenting organs with large shape variations. In this paper, we propose a novel approach to guide deformable models, thus making them robust against arbitrary initializations. Specifically, we learn a displacement regressor, which predicts 3D displacement from any image voxel to the target organ boundary based on the local patch appearance. This regressor provides a nonlocal external force for each vertex of deformable model, thus overcoming the initialization problem suffered by the traditional deformable models. To learn a reliable displacement regressor, two strategies are particularly proposed. 1) A multi-task random forest is proposed to learn the displacement regressor jointly with the organ classifier; 2) an auto-context model is used to iteratively enforce structural information during voxel-wise prediction. Extensive experiments on 313 planning CT scans of 313 patients show that our method achieves better results than alternative classification or regression based methods, and also several other existing methods in CT pelvic organ segmentation. PMID:26800531

Comparison of foot muscle morphology and foot kinematics between recreational runners with normal feet and with asymptomatic over-pronated feet.

PubMed

Zhang, Xianyi; Aeles, Jeroen; Vanwanseele, Benedicte

2017-05-01

Over-pronated feet are common in adults and are associated with lower limb injuries. Studying the foot muscle morphology and foot kinematic patterns is important for understanding the mechanism of over-pronation related injuries. The aim of this study is to compare the foot muscle morphology and foot inter-segmental kinematics between recreational runners with normal feet and those with asymptomatic over-pronated feet. A total of 26 recreational runners (17 had normal feet and 9 had over-pronated feet) participated in this study and their foot type was assessed using the 6-item Foot Posture Index. Selected foot muscles were scanned using an ultrasound device and the scanned images were processed to measure the thickness and cross-sectional area of the muscles. Muscles of interest include abductor hallucis, abductor digiti minimi, flexor digitorum brevis and longus, tibialis anterior and peroneus muscles. Foot kinematic data during walking was collected using a 3D motion capture system incorporating the Oxford Foot Model. The results show that individuals with over-pronated feet have larger size of abductor hallucis, flexor digitorum brevis and longus and smaller abductor digiti minimi than controls. Higher rearfoot peak eversion and forefoot peak supination during walking were observed in individuals with over-pronated feet. However, during gait the forefoot peak abduction was comparable. These findings indicate that in active asymptomatic individuals with over-pronated feet, the foot muscle morphology is adapted to increase control of the foot motion. The morphological characteristics of the foot muscles in asymptomatic individuals with over-pronated feet may affect their foot kinematics and benefit prevention from injuries. Copyright © 2017 Elsevier B.V. All rights reserved.

Foot and Ankle Kinematics During Descent From Varying Step Heights.

PubMed

Gerstle, Emily E; O'Connor, Kristian; Keenan, Kevin G; Cobb, Stephen C

2017-12-01

In the general population, one-third of incidences during step negotiation occur during the transition to level walking. Furthermore, falls during curb negotiation are a common cause of injury in older adults. Distal foot kinematics may be an important factor in determining injury risk associated with transition step negotiation. The purpose of this study was to identify foot and ankle kinematics of uninjured individuals during descent from varying step heights. A 7-segment foot model was used to quantify kinematics as participants walked on a level walkway, stepped down a single step (heights: 5 cm, 15 cm, 25 cm), and continued walking. As step height increased, landing strategy transitioned from the rearfoot to the forefoot, and the rearfoot, lateral and medial midfoot, and medial forefoot became more plantar flexed. During weight acceptance, sagittal plane range of motion of the rearfoot, lateral midfoot, and medial and lateral forefoot increased as step height increased. The changes in landing strategy and distal foot function suggest a less stable ankle position at initial contact and increased demand on the distal foot at initial contact and through the weight acceptance phase of transition step negotiation as step height increases.

Multifractal modeling, segmentation, prediction, and statistical validation of posterior fossa tumors

NASA Astrophysics Data System (ADS)

Islam, Atiq; Iftekharuddin, Khan M.; Ogg, Robert J.; Laningham, Fred H.; Sivakumar, Bhuvaneswari

2008-03-01

In this paper, we characterize the tumor texture in pediatric brain magnetic resonance images (MRIs) and exploit these features for automatic segmentation of posterior fossa (PF) tumors. We focus on PF tumor because of the prevalence of such tumor in pediatric patients. Due to varying appearance in MRI, we propose to model the tumor texture with a multi-fractal process, such as a multi-fractional Brownian motion (mBm). In mBm, the time-varying Holder exponent provides flexibility in modeling irregular tumor texture. We develop a detailed mathematical framework for mBm in two-dimension and propose a novel algorithm to estimate the multi-fractal structure of tissue texture in brain MRI based on wavelet coefficients. This wavelet based multi-fractal feature along with MR image intensity and a regular fractal feature obtained using our existing piecewise-triangular-prism-surface-area (PTPSA) method, are fused in segmenting PF tumor and non-tumor regions in brain T1, T2, and FLAIR MR images respectively. We also demonstrate a non-patient-specific automated tumor prediction scheme based on these image features. We experimentally show the tumor discriminating power of our novel multi-fractal texture along with intensity and fractal features in automated tumor segmentation and statistical prediction. To evaluate the performance of our tumor prediction scheme, we obtain ROCs and demonstrate how sharply the curves reach the specificity of 1.0 sacrificing minimal sensitivity. Experimental results show the effectiveness of our proposed techniques in automatic detection of PF tumors in pediatric MRIs.

Crk1/2-dependent signaling is necessary for podocyte foot process spreading in mouse models of glomerular disease

PubMed Central

George, Britta; Verma, Rakesh; Soofi, Abdulsalam A.; Garg, Puneet; Zhang, Jidong; Park, Tae-Ju; Giardino, Laura; Ryzhova, Larisa; Johnstone, Duncan B.; Wong, Hetty; Nihalani, Deepak; Salant, David J.; Hanks, Steven K.; Curran, Tom; Rastaldi, Maria Pia; Holzman, Lawrence B.

2012-01-01

The morphology of healthy podocyte foot processes is necessary for maintaining the characteristics of the kidney filtration barrier. In most forms of glomerular disease, abnormal filter barrier function results when podocytes undergo foot process spreading and retraction by remodeling their cytoskeletal architecture and intercellular junctions during a process known as effacement. The cell adhesion protein nephrin is necessary for establishing the morphology of the kidney podocyte in development by transducing from the specialized podocyte intercellular junction phosphorylation-mediated signals that regulate cytoskeletal dynamics. The present studies extend our understanding of nephrin function by showing that nephrin activation in cultured podocytes induced actin dynamics necessary for lamellipodial protrusion. This process required a PI3K-, Cas-, and Crk1/2-dependent signaling mechanism distinct from the previously described nephrin-Nck1/2 pathway necessary for assembly and polymerization of actin filaments. Our present findings also support the hypothesis that mechanisms governing lamellipodial protrusion in culture are similar to those used in vivo during foot process effacement in a subset of glomerular diseases. In mice, podocyte-specific deletion of Crk1/2 prevented foot process effacement in one model of podocyte injury and attenuated foot process effacement and associated proteinuria in a delayed fashion in a second model. In humans, focal adhesion kinase and Cas phosphorylation — markers of focal adhesion complex–mediated Crk-dependent signaling — was induced in minimal change disease and membranous nephropathy, but not focal segmental glomerulosclerosis. Together, these observations suggest that activation of a Cas-Crk1/2–dependent complex is necessary for foot process effacement observed in distinct subsets of human glomerular diseases. PMID:22251701

Optical Design of Segmented Hexagon Array Solar Mirror

NASA Technical Reports Server (NTRS)

Huegele, Vince

2000-01-01

A segmented array of mirrors was designed for a solar concentrator test stand at MSFC for firing solar thermal propulsion engines. The 144 mirrors each have a spherical surface to approximate a parabolic concentrator when combined into the entire 18-foot diameter array. The mirror segments are aluminum hexagons that had the surface diamond turned and quartz coated. The array focuses sunlight reflected from a heliostat to a 4 inch diameter spot containing 10 kw of power at the 15-foot focal point. The derivation of the surface figure for the respective mirror elements is shown. The alignment process of the array is discussed and test results of the system's performance is given.

Repeatability of a 3D multi-segment foot model during anterior and lateral step down tests.

PubMed

Lucareli, Paulo Roberto Garcia; Contani, Luciane Beatriz Grohs; Lima, Bruna; Rabelo, Nayra Deise dos Anjos; Ferreira, Cintia Lopes; Lima, Fernanda Pulpio Silva; Correa, João Carlos Ferrari; Politti, Fabiano

2016-01-01

The aim of the present study was to analyse the reproducibility of the Oxford Foot Model (OFM) when used with healthy adults during two clinical tests, i.e., the Anterior Step Down Test (SDA) and the Lateral Step Down Test (SDL). Five healthy participants (one male and four females, 10 limbs in total) with a mean age of 22.2 (19-30) years were assessed in four sessions of tests conducted at intervals of one week. Two independent examiners performed two of the sessions of each of the tests. For each session (intra-day), nine repetitions of each clinical test (SDA and SDL) were performed. After an interval of three hours, the data were collected again. The tests were conducted again after an interval of one week using the same experimental conditions. The intra- and inter-session repeatabilities of the ranges of motion of the feet were determined according to the standard error of measurement (SEM) for each examiner and for the differences between the examiners. The repeatabilities of the results were high for both of the conducted tests. The SEM results were as follows: 0.47-1.94° for the intra-examiner assessment (SDA), 0.55-2.01° for the inter-examiner comparison (SDA), 0.44-2.43° for the intra-examiner assessment (SDL), and 0.54-1.89° for the inter-examiner comparison (SDL). The OFM model was shown to be reproducible in terms of assessing the range of motion of healthy adults during functional tests (SDA and SDL). Copyright © 2015 Elsevier B.V. All rights reserved.

Medical Image Segmentation by Combining Graph Cut and Oriented Active Appearance Models

PubMed Central

Chen, Xinjian; Udupa, Jayaram K.; Bağcı, Ulaş; Zhuge, Ying; Yao, Jianhua

2017-01-01

In this paper, we propose a novel 3D segmentation method based on the effective combination of the active appearance model (AAM), live wire (LW), and graph cut (GC). The proposed method consists of three main parts: model building, initialization, and segmentation. In the model building part, we construct the AAM and train the LW cost function and GC parameters. In the initialization part, a novel algorithm is proposed for improving the conventional AAM matching method, which effectively combines the AAM and LW method, resulting in Oriented AAM (OAAM). A multi-object strategy is utilized to help in object initialization. We employ a pseudo-3D initialization strategy, and segment the organs slice by slice via multi-object OAAM method. For the segmentation part, a 3D shape constrained GC method is proposed. The object shape generated from the initialization step is integrated into the GC cost computation, and an iterative GC-OAAM method is used for object delineation. The proposed method was tested in segmenting the liver, kidneys, and spleen on a clinical CT dataset and also tested on the MICCAI 2007 grand challenge for liver segmentation training dataset. The results show the following: (a) An overall segmentation accuracy of true positive volume fraction (TPVF) > 94.3%, false positive volume fraction (FPVF) < 0.2% can be achieved. (b) The initialization performance can be improved by combining AAM and LW. (c) The multi-object strategy greatly facilitates the initialization. (d) Compared to the traditional 3D AAM method, the pseudo 3D OAAM method achieves comparable performance while running 12 times faster. (e) The performance of proposed method is comparable to the state of the art liver segmentation algorithm. The executable version of 3D shape constrained GC with user interface can be downloaded from website http://xinjianchen.wordpress.com/research/. PMID:22311862

Shape characteristics of the foot arch: dynamics in the pregnancy period.

PubMed

Jelen, Karel; Tetkova, Zuzana; Halounova, Lena; Pavelka, Karel; Koudelka, Tomas; Ruzicka, Pavel

2005-12-01

The aim is data detection and finding some load consequences generated by various mechanical or physiological changes in the interaction of the end segment of the body--the foot--and the environment. Shape instability of the foot caused by e.g. loading of the foot by long-term frequency loads--walking, by extreme loads--sport, by hormonal changes--pregnancy, by aging, by pathologies, etc. The footprint surface was numerically described in 3D by means of stereo-photo-gram-metrical method--DMR digital relief model. Density of discrete points--250-400 per one print. Detailed DMR was constructed by means of triangular web including contour picture with the use of Atlas program. The specified generated web is characterized by triangles with a cca 1 mm side in the number of up to 4,500 elements per one footprint model. The results enable us to deduce shape characteristics of DMR--the shape of the interactive boundary of the foot--the rest surface, to solve foot arch straining, to solve issues of discomfort and distribution of the pressure at the boundary of the foot--the rest surface, the shoe, etc. The gained findings can be interpreted in the field of prevention, therapy, orthopedics, podology, and enable us to come up with recommendations for the orthopedic practice and industrial use in the footwear production, etc. THE MAIN FINDINGS: The difference between volume reductions of the space under the foot arch characterizes the level of "fall" of the arch. This criterion is independent of the foot size, and is in 3D. Shape characteristics of footprints in pregnant women and in the period after childbirth were calculated on the basis of the defined criterion. The results of the group of four women tested in three periods suggest that there is no clear tendency towards the foot arch falling/increasing of the foot arch "fall" during the pregnancy period.

Ares I-X Launch Vehicle Modal Test Measurements and Data Quality Assessments

NASA Technical Reports Server (NTRS)

Templeton, Justin D.; Buehrle, Ralph D.; Gaspar, James L.; Parks, Russell A.; Lazor, Daniel R.

2010-01-01

The Ares I-X modal test program consisted of three modal tests conducted at the Vehicle Assembly Building at NASA s Kennedy Space Center. The first test was performed on the 71-foot 53,000-pound top segment of the Ares I-X launch vehicle known as Super Stack 5 and the second test was performed on the 66-foot 146,000- pound middle segment known as Super Stack 1. For these tests, two 250 lb-peak electro-dynamic shakers were used to excite bending and shell modes with the test articles resting on the floor. The third modal test was performed on the 327-foot 1,800,000-pound Ares I-X launch vehicle mounted to the Mobile Launcher Platform. The excitation for this test consisted of four 1000+ lb-peak hydraulic shakers arranged to excite the vehicle s cantilevered bending modes. Because the frequencies of interest for these modal tests ranged from 0.02 to 30 Hz, high sensitivity capacitive accelerometers were used. Excitation techniques included impact, burst random, pure random, and force controlled sine sweep. This paper provides the test details for the companion papers covering the Ares I-X finite element model calibration process. Topics to be discussed include test setups, procedures, measurements, data quality assessments, and consistency of modal parameter estimates.

3D Measurement of Anatomical Cross-sections of Foot while Walking

NASA Astrophysics Data System (ADS)

Kimura, Makoto; Mochimaru, Masaaki; Kanade, Takeo

Recently, techniques for measuring and modeling of human body are taking attention, because human models are useful for ergonomic design in manufacturing. We aim to measure accurate shape of human foot that will be useful for the design of shoes. For such purpose, shape measurement of foot in motion is obviously important, because foot shape in the shoe is deformed while walking or running. In this paper, we propose a method to measure anatomical cross-sections of foot while walking. No one had ever measured dynamic shape of anatomical cross-sections, though they are very basic and popular in the field of biomechanics. Our proposed method is based on multi-view stereo method. The target cross-sections are painted in individual colors (red, green, yellow and blue), and the proposed method utilizes the characteristic of target shape in the camera captured images. Several nonlinear conditions are introduced in the process to find the consistent correspondence in all images. Our desired accuracy is less than 1mm error, which is similar to the existing 3D scanners for static foot measurement. In our experiments, the proposed method achieved the desired accuracy.

3D automatic anatomy segmentation based on iterative graph-cut-ASM.

PubMed

Chen, Xinjian; Bagci, Ulas

2011-08-01

This paper studies the feasibility of developing an automatic anatomy segmentation (AAS) system in clinical radiology and demonstrates its operation on clinical 3D images. The AAS system, the authors are developing consists of two main parts: object recognition and object delineation. As for recognition, a hierarchical 3D scale-based multiobject method is used for the multiobject recognition task, which incorporates intensity weighted ball-scale (b-scale) information into the active shape model (ASM). For object delineation, an iterative graph-cut-ASM (IGCASM) algorithm is proposed, which effectively combines the rich statistical shape information embodied in ASM with the globally optimal delineation capability of the GC method. The presented IGCASM algorithm is a 3D generalization of the 2D GC-ASM method that they proposed previously in Chen et al. [Proc. SPIE, 7259, 72590C1-72590C-8 (2009)]. The proposed methods are tested on two datasets comprised of images obtained from 20 patients (10 male and 10 female) of clinical abdominal CT scans, and 11 foot magnetic resonance imaging (MRI) scans. The test is for four organs (liver, left and right kidneys, and spleen) segmentation, five foot bones (calcaneus, tibia, cuboid, talus, and navicular). The recognition and delineation accuracies were evaluated separately. The recognition accuracy was evaluated in terms of translation, rotation, and scale (size) error. The delineation accuracy was evaluated in terms of true and false positive volume fractions (TPVF, FPVF). The efficiency of the delineation method was also evaluated on an Intel Pentium IV PC with a 3.4 GHZ CPU machine. The recognition accuracies in terms of translation, rotation, and scale error over all organs are about 8 mm, 10 degrees and 0.03, and over all foot bones are about 3.5709 mm, 0.35 degrees and 0.025, respectively. The accuracy of delineation over all organs for all subjects as expressed in TPVF and FPVF is 93.01% and 0.22%, and all foot bones for all subjects are 93.75% and 0.28%, respectively. While the delineations for the four organs can be accomplished quite rapidly with average of 78 s, the delineations for the five foot bones can be accomplished with average of 70 s. The experimental results showed the feasibility and efficacy of the proposed automatic anatomy segmentation system: (a) the incorporation of shape priors into the GC framework is feasible in 3D as demonstrated previously for 2D images; (b) our results in 3D confirm the accuracy behavior observed in 2D. The hybrid strategy IGCASM seems to be more robust and accurate than ASM and GC individually; and (c) delineations within body regions and foot bones of clinical importance can be accomplished quite rapidly within 1.5 min.

Sagittal plane kinematics of passive dorsiflexion of the foot in adolescent athletes.

PubMed

Gatt, Alfred; Chockalingam, Nachiappan; Falzon, Owen

2013-01-01

Although assessment of passive maximum foot dorsiflexion angle is performed routinely, there is a paucity of information regarding adolescents' foot and foot segment motion during this procedure. There are currently no trials investigating the kinematics of the adolescent foot during passive foot dorsiflexion. A six-camera optoelectronic motion capture system was used to collect kinematic data using the Oxford Foot Model. Eight female amateur gymnasts 11 to 16 years old (mean age, 13.2 years; mean height, 1.5 m) participated in the study. A dorsiflexing force was applied to the forefoot until reaching maximum resistance with the foot placed in the neutral, pronated, and supinated positions in random order. The maximum foot dorsiflexion angle and the range of movement of the forefoot to hindfoot, tibia to forefoot, and tibia to hindfoot angles were computed. Mean ± SD maximum foot dorsiflexion angles were 36.3° ± 7.2° for pronated, 36.9° ± 4.0° for neutral, and 33.0° ± 4.9° for supinated postures. One-way repeated-measures analysis of variance results were nonsignificant among the 3 groups (P = .70), as were the forefoot to tibia angle and hindfoot to tibia angle variations (P = .091 and P = .188, respectively). Forefoot to hindfoot angle increased with the application of force, indicating that in adolescents, the forefoot does not lock at any particular posture as portrayed by the traditional Rootian paradigm. Participants had very flexible foot dorsiflexion, unlike those in another study assessing adolescent athletes. This finding, together with nonsignificant statistical results, implies that foot dorsiflexion measurement may be performed at any foot posture without notably affecting results.

Deep Convolutional Neural Networks for Multi-Modality Isointense Infant Brain Image Segmentation

PubMed Central

Zhang, Wenlu; Li, Rongjian; Deng, Houtao; Wang, Li; Lin, Weili; Ji, Shuiwang; Shen, Dinggang

2015-01-01

The segmentation of infant brain tissue images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) plays an important role in studying early brain development in health and disease. In the isointense stage (approximately 6–8 months of age), WM and GM exhibit similar levels of intensity in both T1 and T2 MR images, making the tissue segmentation very challenging. Only a small number of existing methods have been designed for tissue segmentation in this isointense stage; however, they only used a single T1 or T2 images, or the combination of T1 and T2 images. In this paper, we propose to use deep convolutional neural networks (CNNs) for segmenting isointense stage brain tissues using multi-modality MR images. CNNs are a type of deep models in which trainable filters and local neighborhood pooling operations are applied alternatingly on the raw input images, resulting in a hierarchy of increasingly complex features. Specifically, we used multimodality information from T1, T2, and fractional anisotropy (FA) images as inputs and then generated the segmentation maps as outputs. The multiple intermediate layers applied convolution, pooling, normalization, and other operations to capture the highly nonlinear mappings between inputs and outputs. We compared the performance of our approach with that of the commonly used segmentation methods on a set of manually segmented isointense stage brain images. Results showed that our proposed model significantly outperformed prior methods on infant brain tissue segmentation. In addition, our results indicated that integration of multi-modality images led to significant performance improvement. PMID:25562829

Primitive-path statistics of entangled polymers: mapping multi-chain simulations onto single-chain mean-field models

NASA Astrophysics Data System (ADS)

Steenbakkers, Rudi J. A.; Tzoumanekas, Christos; Li, Ying; Liu, Wing Kam; Kröger, Martin; Schieber, Jay D.

2014-01-01

We present a method to map the full equilibrium distribution of the primitive-path (PP) length, obtained from multi-chain simulations of polymer melts, onto a single-chain mean-field ‘target’ model. Most previous works used the Doi-Edwards tube model as a target. However, the average number of monomers per PP segment, obtained from multi-chain PP networks, has consistently shown a discrepancy of a factor of two with respect to tube-model estimates. Part of the problem is that the tube model neglects fluctuations in the lengths of PP segments, the number of entanglements per chain and the distribution of monomers among PP segments, while all these fluctuations are observed in multi-chain simulations. Here we use a recently proposed slip-link model, which includes fluctuations in all these variables as well as in the spatial positions of the entanglements. This turns out to be essential to obtain qualitative and quantitative agreement with the equilibrium PP-length distribution obtained from multi-chain simulations. By fitting this distribution, we are able to determine two of the three parameters of the model, which govern its equilibrium properties. This mapping is executed for four different linear polymers and for different molecular weights. The two parameters are found to depend on chemistry, but not on molecular weight. The model predicts a constant plateau modulus minus a correction inversely proportional to molecular weight. The value for well-entangled chains, with the parameters determined ab initio, lies in the range of experimental data for the materials investigated.

A database of aerothermal measurements in hypersonic flow for CFD validation

NASA Technical Reports Server (NTRS)

Holden, M. S.; Moselle, J. R.

1992-01-01

This paper presents an experimental database selected and compiled from aerothermal measurements obtained on basic model configurations on which fundamental flow phenomena could be most easily examined. The experimental studies were conducted in hypersonic flows in 48-inch, 96-inch, and 6-foot shock tunnels. A special computer program was constructed to provide easy access to the measurements in the database as well as the means to plot the measurements and compare them with imported data. The database contains tabulations of model configurations, freestream conditions, and measurements of heat transfer, pressure, and skin friction for each of the studies selected for inclusion. The first segment contains measurements in laminar flow emphasizing shock-wave boundary-layer interaction. In the second segment, measurements in transitional flows over flat plates and cones are given. The third segment comprises measurements in regions of shock-wave/turbulent-boundary-layer interactions. Studies of the effects of surface roughness of nosetips and conical afterbodies are presented in the fourth segment of the database. Detailed measurements in regions of shock/shock boundary layer interaction are contained in the fifth segment. Measurements in regions of wall jet and transpiration cooling are presented in the final two segments.

100. DAM ROLLER GATES GEAR SEGMENTS & TRACK ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

100. DAM - ROLLER GATES - GEAR SEGMENTS & TRACK EXTENSIONS (ML-8-47/16-FS) June 1935 - Upper Mississippi River 9-Foot Channel, Lock & Dam No. 8, On Mississippi River near Houston County, MN, Genoa, Vernon County, WI

Multi-Nozzle Base Flow Model in the 10- by 10-Foot Supersonic Wind Tunnel

NASA Image and Video Library

1964-02-21

Researchers check the setup of a multi-nozzle base flow model in the 10- by 10-Foot Supersonic Wind Tunnel at the National Aeronautics and Space Administration (NASA) Lewis Research Center. NASA researchers were struggling to understand the complex flow phenomena resulting from the use of multiple rocket engines. Robert Wasko and Theodore Cover of the Advanced Development and Evaluation Division’s analysis and operations sections conducted a set of tests in the 10- by 10 tunnel to further understand the flow issues. The Lewis researchers studied four and five-nozzle configurations in the 10- by 10 at simulated altitudes from 60,000 to 200,000 feet. The nozzles were gimbaled during some of the test runs to simulate steering. The flow field for the four-nozzle clusters was surveyed in the center and the lateral areas between the nozzles, whereas the five-nozzle cluster was surveyed in the lateral area only.

Discriminative confidence estimation for probabilistic multi-atlas label fusion.

PubMed

Benkarim, Oualid M; Piella, Gemma; González Ballester, Miguel Angel; Sanroma, Gerard

2017-12-01

Quantitative neuroimaging analyses often rely on the accurate segmentation of anatomical brain structures. In contrast to manual segmentation, automatic methods offer reproducible outputs and provide scalability to study large databases. Among existing approaches, multi-atlas segmentation has recently shown to yield state-of-the-art performance in automatic segmentation of brain images. It consists in propagating the labelmaps from a set of atlases to the anatomy of a target image using image registration, and then fusing these multiple warped labelmaps into a consensus segmentation on the target image. Accurately estimating the contribution of each atlas labelmap to the final segmentation is a critical step for the success of multi-atlas segmentation. Common approaches to label fusion either rely on local patch similarity, probabilistic statistical frameworks or a combination of both. In this work, we propose a probabilistic label fusion framework based on atlas label confidences computed at each voxel of the structure of interest. Maximum likelihood atlas confidences are estimated using a supervised approach, explicitly modeling the relationship between local image appearances and segmentation errors produced by each of the atlases. We evaluate different spatial pooling strategies for modeling local segmentation errors. We also present a novel type of label-dependent appearance features based on atlas labelmaps that are used during confidence estimation to increase the accuracy of our label fusion. Our approach is evaluated on the segmentation of seven subcortical brain structures from the MICCAI 2013 SATA Challenge dataset and the hippocampi from the ADNI dataset. Overall, our results indicate that the proposed label fusion framework achieves superior performance to state-of-the-art approaches in the majority of the evaluated brain structures and shows more robustness to registration errors. Copyright © 2017 Elsevier B.V. All rights reserved.

Modeling the relaxation of internal DNA segments during genome mapping in nanochannels.

PubMed

Jain, Aashish; Sheats, Julian; Reifenberger, Jeffrey G; Cao, Han; Dorfman, Kevin D

2016-09-01

We have developed a multi-scale model describing the dynamics of internal segments of DNA in nanochannels used for genome mapping. In addition to the channel geometry, the model takes as its inputs the DNA properties in free solution (persistence length, effective width, molecular weight, and segmental hydrodynamic radius) and buffer properties (temperature and viscosity). Using pruned-enriched Rosenbluth simulations of a discrete wormlike chain model with circa 10 base pair resolution and a numerical solution for the hydrodynamic interactions in confinement, we convert these experimentally available inputs into the necessary parameters for a one-dimensional, Rouse-like model of the confined chain. The resulting coarse-grained model resolves the DNA at a length scale of approximately 6 kilobase pairs in the absence of any global hairpin folds, and is readily studied using a normal-mode analysis or Brownian dynamics simulations. The Rouse-like model successfully reproduces both the trends and order of magnitude of the relaxation time of the distance between labeled segments of DNA obtained in experiments. The model also provides insights that are not readily accessible from experiments, such as the role of the molecular weight of the DNA and location of the labeled segments that impact the statistical models used to construct genome maps from data acquired in nanochannels. The multi-scale approach used here, while focused towards a technologically relevant scenario, is readily adapted to other channel sizes and polymers.

The pathogenesis of Foot-and-Mouth Disease in pigs

USDA-ARS?s Scientific Manuscript database

The greatest segment of foot-and-mouth disease (FMD) clinical research has been dedicated to elucidating pathogenesis and enhancing vaccine protection in cattle with less efforts invested in studies that are specific to pigs. However, accumulated evidence from FMD outbreaks and experimental invest...

Do Online Learning Patterns Exhibit Regional and Demographic Differences?

ERIC Educational Resources Information Center

Hsieh, Tsui-Chuan; Yang, Chyan

2012-01-01

This paper used a multi-level latent class model to evaluate whether online learning patterns exhibit regional differences and demographics. This study discovered that the Internet learning pattern consists of five segments, and the region of Taiwan is divided into two segments and further found that both the user and the regional segments are…

Evaluating habitat for black-footed ferrets: Revision of an existing model

USGS Publications Warehouse

Biggins, Dean E.; Lockhart, J. Michael; Godbey, Jerry L.

2006-01-01

Black-footed ferrets (Mustela nigripes) are highly dependent on prairie dogs (Cynomys spp.) as prey, and prairie dog colonies are the only known habitats that sustain black-footed ferret populations. An existing model used extensively for evaluating black-footed ferret reintroduction habitat defined complexes by interconnecting colonies with 7-km line segments. Although the 7-km complex remains a useful construct, we propose additional, smaller-scale evaluations that consider 1.5-km subcomplexes. The original model estimated the carrying capacity of complexes based on energy requirements of ferrets and density estimates of their prairie dog prey. Recent data have supported earlier contentions of intraspecific competition and intrasexual territorial behavior in ferrets. We suggest a revised model that retains the fixed linear relationship of the existing model when prairie dog densities are <18/ha and uses a curvilinear relationship that reflects increasing effects of ferret territoriality when there are 18–42 prairie dogs per hectare. We discuss possible effects of colony size and shape, interacting with territoriality, as justification for the exclusion of territorial influences if a prairie dog colony supports only a single female ferret. We also present data to support continued use of active prairie dog burrow densities as indices suitable for broad-scale estimates of prairie dog density. Calculation of percent of complexes that are occupied by prairie dog colonies was recommended as part of the original habitat evaluation process. That attribute has been largely ignored, resulting in rating anomalies.

Multi-stage learning for robust lung segmentation in challenging CT volumes.

PubMed

Sofka, Michal; Wetzl, Jens; Birkbeck, Neil; Zhang, Jingdan; Kohlberger, Timo; Kaftan, Jens; Declerck, Jérôme; Zhou, S Kevin

2011-01-01

Simple algorithms for segmenting healthy lung parenchyma in CT are unable to deal with high density tissue common in pulmonary diseases. To overcome this problem, we propose a multi-stage learning-based approach that combines anatomical information to predict an initialization of a statistical shape model of the lungs. The initialization first detects the carina of the trachea, and uses this to detect a set of automatically selected stable landmarks on regions near the lung (e.g., ribs, spine). These landmarks are used to align the shape model, which is then refined through boundary detection to obtain fine-grained segmentation. Robustness is obtained through hierarchical use of discriminative classifiers that are trained on a range of manually annotated data of diseased and healthy lungs. We demonstrate fast detection (35s per volume on average) and segmentation of 2 mm accuracy on challenging data.

Planar covariance of upper and lower limb elevation angles during hand-foot crawling in healthy young adults.

PubMed

MacLellan, M J; Catavitello, G; Ivanenko, Y P; Lacquaniti, F

2017-11-01

Habitual quadrupeds have been shown to display a planar covariance of segment elevation angle waveforms in the fore and hind limbs during many forms of locomotion. The purpose of the current study was to determine if humans generate similar patterns in the upper and lower limbs during hand-foot crawling. Nine healthy young adults performed hand-foot crawling on a treadmill at speeds of 1, 2, and 3 km/h. A principal component analysis (PCA) was applied to the segment elevation angle waveforms for the upper (upper arm, lower arm, and hand) and lower (thigh, shank, and foot) limbs separately. The planarity of the elevation angle waveforms was determined using the sum of the variance explained by the first two PCs and the orientation of the covariance plane was quantified using the direction cosines of the eigenvector orthogonal to the plane, projected upon each of the segmental semi-axes. Results showed that planarity of segment elevation angles was maintained in the upper and lower limbs (explained variance >97%), although a slight decrease was present in the upper limb when crawling at 3 km/h. The orientation of the covariance plane was highly limb-specific, consistent with animal studies and possibly related to the functional neural control differences between the upper and lower limbs. These results may suggest that the motor patterns stored in the central nervous system for quadrupedal locomotion may be retained through evolution and may still be exploited when humans perform such tasks.

Biomechanical study of tarsometatarsal joint fusion using finite element analysis.

PubMed

Wang, Yan; Li, Zengyong; Zhang, Ming

2014-11-01

Complications of surgeries in foot and ankle bring patients with severe sufferings. Sufficient understanding of the internal biomechanical information such as stress distribution, contact pressure, and deformation is critical to estimate the effectiveness of surgical treatments and avoid complications. Foot and ankle is an intricate and synergetic system, and localized intervention may alter the functions to the adjacent components. The aim of this study was to estimate biomechanical effects of the TMT joint fusion using comprehensive finite element (FE) analysis. A foot and ankle model consists of 28 bones, 72 ligaments, and plantar fascia with soft tissues embracing all the segments. Kinematic information and ground reaction force during gait were obtained from motion analysis. Three gait instants namely the first peak, second peak and mid-stance were simulated in a normal foot and a foot with TMT joint fusion. It was found that contact pressure on plantar foot increased by 0.42%, 19% and 37%, respectively after TMT fusion compared with normal foot walking. Navico-cuneiform and fifth meta-cuboid joints sustained 27% and 40% increase in contact pressure at second peak, implying potential risk of joint problems such as arthritis. Von Mises stress in the second metatarsal bone increased by 22% at midstance, making it susceptible to stress fracture. This study provides biomechanical information for understanding the possible consequences of TMT joint fusion. Copyright © 2014 IPEM. Published by Elsevier Ltd. All rights reserved.

Comparison of Multisegmental Foot and Ankle Motion Between Total Ankle Replacement and Ankle Arthrodesis in Adults.

PubMed

Seo, Sang Gyo; Kim, Eo Jin; Lee, Doo Jae; Bae, Kee Jeong; Lee, Kyoung Min; Lee, Dong Yeon

2017-09-01

Total ankle replacement (TAR) and ankle arthrodesis (AA) are usually performed for severe ankle arthritis. We compared postoperative foot segmental motion during gait in patients treated with TAR and AA. Gait analysis was performed in 17 and 7 patients undergoing TAR and AA, respectively. Subjects were evaluated using a 3-dimensional multisegmental foot model with 15 markers. Temporal gait parameters were calculated. The maximum and minimum values and the differences in hallux, forefoot, hindfoot, and arch in 3 planes (sagittal, coronal, transverse) were compared between the 2 groups. One hundred healthy adults were evaluated as a control. Gait speed was faster in the TAR ( P = .028). On analysis of foot and ankle segmental motion, the range of hindfoot sagittal motion was significantly greater in the TAR (15.1 vs 10.2 degrees in AA; P = .004). The main component of motion increase was hindfoot dorsiflexion (12.3 and 8.6 degrees). The range of forefoot sagittal motion was greater in the TAR (9.3 vs 5.8 degrees in AA; P = .004). Maximum ankle power in the TAR (1.16) was significantly higher than 0.32 in AA; P = .008). However, the range of hindfoot and forefoot sagittal motion was decreased in both TAR and AA compared with the control group ( P = .000). Although biomechanical results of TAR and AA were not similar to those in the normal controls, joint motions in the TAR more closely matched normal values. Treatment decision making should involve considerations of the effect of surgery on the adjacent joints. Level III, case-control study.

Dual Segment Glocal Model Based Capacitive Level Sensor (CLS) for Adhesive Material and Level Detection

NASA Astrophysics Data System (ADS)

Khan, F. A.; Yousaf, A.; Reindl, L. M.

2018-04-01

This paper presents a multi segment capacitive level monitoring sensor based on distributed E-fields approach Glocal. This approach has an advantage to analyze build-up problem by the local E-fields as well the fluid level monitoring by the global E-fields. The multi segment capacitive approach presented within this work addresses the main problem of unwanted parasitic capacitance generated from Copper (Cu) strips by applying active shielding concept. Polyvinyl chloride (PVC) is used for isolation and parafilm is used for creating artificial build-up on a CLS.

Multi-scale image segmentation method with visual saliency constraints and its application

NASA Astrophysics Data System (ADS)

Chen, Yan; Yu, Jie; Sun, Kaimin

2018-03-01

Object-based image analysis method has many advantages over pixel-based methods, so it is one of the current research hotspots. It is very important to get the image objects by multi-scale image segmentation in order to carry out object-based image analysis. The current popular image segmentation methods mainly share the bottom-up segmentation principle, which is simple to realize and the object boundaries obtained are accurate. However, the macro statistical characteristics of the image areas are difficult to be taken into account, and fragmented segmentation (or over-segmentation) results are difficult to avoid. In addition, when it comes to information extraction, target recognition and other applications, image targets are not equally important, i.e., some specific targets or target groups with particular features worth more attention than the others. To avoid the problem of over-segmentation and highlight the targets of interest, this paper proposes a multi-scale image segmentation method with visually saliency graph constraints. Visual saliency theory and the typical feature extraction method are adopted to obtain the visual saliency information, especially the macroscopic information to be analyzed. The visual saliency information is used as a distribution map of homogeneity weight, where each pixel is given a weight. This weight acts as one of the merging constraints in the multi- scale image segmentation. As a result, pixels that macroscopically belong to the same object but are locally different can be more likely assigned to one same object. In addition, due to the constraint of visual saliency model, the constraint ability over local-macroscopic characteristics can be well controlled during the segmentation process based on different objects. These controls will improve the completeness of visually saliency areas in the segmentation results while diluting the controlling effect for non- saliency background areas. Experiments show that this method works better for texture image segmentation than traditional multi-scale image segmentation methods, and can enable us to give priority control to the saliency objects of interest. This method has been used in image quality evaluation, scattered residential area extraction, sparse forest extraction and other applications to verify its validation. All applications showed good results.

A mathematical analysis to address the 6 degree-of-freedom segmental power imbalance.

PubMed

Ebrahimi, Anahid; Collins, John D; Kepple, Thomas M; Takahashi, Kota Z; Higginson, Jill S; Stanhope, Steven J

2018-01-03

Segmental power is used in human movement analyses to indicate the source and net rate of energy transfer between the rigid bodies of biomechanical models. Segmental power calculations are performed using segment endpoint dynamics (kinetic method). A theoretically equivalent method is to measure the rate of change in a segment's mechanical energy state (kinematic method). However, these two methods have not produced experimentally equivalent results for segments proximal to the foot, with the difference in methods deemed the "power imbalance." In a 6 degree-of-freedom model, segments move independently, resulting in relative segment endpoint displacement and non-equivalent segment endpoint velocities at a joint. In the kinetic method, a segment's distal end translational velocity may be defined either at the anatomical end of the segment or at the location of the joint center (defined here as the proximal end of the adjacent distal segment). Our mathematical derivations revealed the power imbalance between the kinetic method using the anatomical definition and the kinematic method can be explained by power due to relative segment endpoint displacement. In this study, we tested this analytical prediction through experimental gait data from nine healthy subjects walking at a typical speed. The average absolute segmental power imbalance was reduced from 0.023 to 0.046 W/kg using the anatomical definition to ≤0.001 W/kg using the joint center definition in the kinetic method (95.56-98.39% reduction). Power due to relative segment endpoint displacement in segmental power analyses is substantial and should be considered in analyzing energetic flow into and between segments. Copyright © 2017 Elsevier Ltd. All rights reserved.

A vessel segmentation method for multi-modality angiographic images based on multi-scale filtering and statistical models.

PubMed

Lu, Pei; Xia, Jun; Li, Zhicheng; Xiong, Jing; Yang, Jian; Zhou, Shoujun; Wang, Lei; Chen, Mingyang; Wang, Cheng

2016-11-08

Accurate segmentation of blood vessels plays an important role in the computer-aided diagnosis and interventional treatment of vascular diseases. The statistical method is an important component of effective vessel segmentation; however, several limitations discourage the segmentation effect, i.e., dependence of the image modality, uneven contrast media, bias field, and overlapping intensity distribution of the object and background. In addition, the mixture models of the statistical methods are constructed relaying on the characteristics of the image histograms. Thus, it is a challenging issue for the traditional methods to be available in vessel segmentation from multi-modality angiographic images. To overcome these limitations, a flexible segmentation method with a fixed mixture model has been proposed for various angiography modalities. Our method mainly consists of three parts. Firstly, multi-scale filtering algorithm was used on the original images to enhance vessels and suppress noises. As a result, the filtered data achieved a new statistical characteristic. Secondly, a mixture model formed by three probabilistic distributions (two Exponential distributions and one Gaussian distribution) was built to fit the histogram curve of the filtered data, where the expectation maximization (EM) algorithm was used for parameters estimation. Finally, three-dimensional (3D) Markov random field (MRF) were employed to improve the accuracy of pixel-wise classification and posterior probability estimation. To quantitatively evaluate the performance of the proposed method, two phantoms simulating blood vessels with different tubular structures and noises have been devised. Meanwhile, four clinical angiographic data sets from different human organs have been used to qualitatively validate the method. To further test the performance, comparison tests between the proposed method and the traditional ones have been conducted on two different brain magnetic resonance angiography (MRA) data sets. The results of the phantoms were satisfying, e.g., the noise was greatly suppressed, the percentages of the misclassified voxels, i.e., the segmentation error ratios, were no more than 0.3%, and the Dice similarity coefficients (DSCs) were above 94%. According to the opinions of clinical vascular specialists, the vessels in various data sets were extracted with high accuracy since complete vessel trees were extracted while lesser non-vessels and background were falsely classified as vessel. In the comparison experiments, the proposed method showed its superiority in accuracy and robustness for extracting vascular structures from multi-modality angiographic images with complicated background noises. The experimental results demonstrated that our proposed method was available for various angiographic data. The main reason was that the constructed mixture probability model could unitarily classify vessel object from the multi-scale filtered data of various angiography images. The advantages of the proposed method lie in the following aspects: firstly, it can extract the vessels with poor angiography quality, since the multi-scale filtering algorithm can improve the vessel intensity in the circumstance such as uneven contrast media and bias field; secondly, it performed well for extracting the vessels in multi-modality angiographic images despite various signal-noises; and thirdly, it was implemented with better accuracy, and robustness than the traditional methods. Generally, these traits declare that the proposed method would have significant clinical application.

Notochord segmentation may lay down the pathway for the development of the vertebral bodies in the Atlantic salmon.

PubMed

Grotmol, Sindre; Kryvi, Harald; Nordvik, Kari; Totland, Geir K

2003-12-01

This study indicates that the development of the vertebrae in the Atlantic salmon requires the orchestration of two sources of metameric patterning, derived from the notochord and the somite rows, respectively. Before segmentation of the salmon notochord, chordoblasts exhibit a well-defined cell axis that is uniformly aligned with the cranio-caudal axis. The morphology of these cells is characterised by a foot-like basal projection that rests on the notochordal sheath. Notochordal segments are initially formed within the chordoblast layer by metameric change in the axial orientation of groups of chordoblasts. This process results in the formation of circular bands of chordoblasts, with feet perpendicular to the cranio-caudal axis, the original chordoblast orientation. Each vertebra is defined by two such chordoblast bands, at the cranial and caudal borders, respectively. Formation of the chordoblast segments closely precedes formation of the chordacentra, which form as calcified rings within the adjacent notochordal sheath. Sclerotomal osteoblasts then differentiate on the surface of the chordacentra, using them as foundations for further vertebral growth. Thus, the morphogenesis of the rudiments of the vertebral bodies is initiated by a generation of segments within the chordoblast layer. This dual segmentation model for salmon, in which the segmental patterns of the neural and haemal arches are somite-derived, while the vertebral segments seem to be notochord-derived, contrasts with current models for avians and mammals.

The influence of foot hyperpronation on pelvic biomechanics during stance phase of the gait: A biomechanical simulation study.

PubMed

Yazdani, Farzaneh; Razeghi, Mohsen; Karimi, Mohammad Taghi; Raeisi Shahraki, Hadi; Salimi Bani, Milad

2018-05-01

Despite the theoretical link between foot hyperpronation and biomechanical dysfunction of the pelvis, the literature lacks evidence that confirms this assumption in truly hyperpronated feet subjects during gait. Changes in the kinematic pattern of the pelvic segment were assessed in 15 persons with hyperpronated feet and compared to a control group of 15 persons with normally aligned feet during the stance phase of gait based on biomechanical musculoskeletal simulation. Kinematic and kinetic data were collected while participants walked at a comfortable self-selected speed. A generic OpenSim musculoskeletal model with 23 degrees of freedom and 92 muscles was scaled for each participant. OpenSim inverse kinematic analysis was applied to calculate segment angles in the sagittal, frontal and horizontal planes. Principal component analysis was employed as a data reduction technique, as well as a computational tool to obtain principal component scores. Independent-sample t-test was used to detect group differences. The difference between groups in scores for the first principal component in the sagittal plane was statistically significant (p = 0.01; effect size = 1.06), but differences between principal component scores in the frontal and horizontal planes were not significant. The hyperpronation group had greater anterior pelvic tilt during 20%-80% of the stance phase. In conclusion, in persons with hyperpronation we studied the role of the pelvic segment was mainly to maintain postural balance in the sagittal plane by increasing anterior pelvic inclination. Since anterior pelvic tilt may be associated with low back symptoms, the evaluation of foot posture should be considered in assessing the patients with low back and pelvic dysfunction.

KSC-04PD-2561

NASA Technical Reports Server (NTRS)

2004-01-01

KENNEDY SPACE CENTER, FLA. In a Vehicle Assembly Building (VAB) high bay, workers monitor the movement of a Solid Rocket Booster (SRB) aft center segment as it is lowered toward an aft segment already secured to a Mobile Launch Platform. These segments are part of the right SRB for the Space Shuttle Return to Flight mission, STS-114. Two SRBs are stacked on a Mobile Launch Platform for each Shuttle flight and later joined by an External Tank. The twin 149-foot tall, 12-foot diameter SRBs provide the main propulsion system during launch. They operate in parallel with the Space Shuttle main engines for the first two minutes of flight and jettison away from the orbiter with help from the Booster Separation Motors, about 26.3 nautical miles above the Earths surface.

KSC-04PD-2562

NASA Technical Reports Server (NTRS)

2004-01-01

KENNEDY SPACE CENTER, FLA. In a Vehicle Assembly Building (VAB) high bay, workers check the alignment of a Solid Rocket Booster (SRB) aft center segment as it is lowered toward an aft segment already secured to a Mobile Launch Platform. These segments are part of the right SRB for the Space Shuttle Return to Flight mission, STS-114. Two SRBs are stacked on a Mobile Launch Platform for each Shuttle flight and later joined by an External Tank. The twin 149-foot tall, 12-foot diameter SRBs provide the main propulsion system during launch. They operate in parallel with the Space Shuttle main engines for the first two minutes of flight and jettison away from the orbiter with help from the Booster Separation Motors, about 26.3 nautical miles above the Earths surface.

KSC-04PD-2565

NASA Technical Reports Server (NTRS)

2004-01-01

KENNEDY SPACE CENTER, FLA. In a Vehicle Assembly Building (VAB) high bay, workers check the alignment of a Solid Rocket Booster (SRB) aft center segment which has been lowered onto an aft segment already secured to a Mobile Launch Platform. These segments are part of the right SRB for the Space Shuttle Return to Flight mission, STS-114. Two SRBs are stacked on a Mobile Launch Platform for each Shuttle flight and later joined by an External Tank. The twin 149-foot tall, 12-foot diameter SRBs provide the main propulsion system during launch. They operate in parallel with the Space Shuttle main engines for the first two minutes of flight and jettison away from the orbiter with help from the Booster Separation Motors, about 26.3 nautical miles above the Earths surface.

Low voltage electrophoresis chip with multi-segments synchronized scanning

NASA Astrophysics Data System (ADS)

Gu, Wenwen; Wen, Zhiyu; Xu, Yi

2017-03-01

For low voltage electrophoresis chip, there is always a problem that the samples are truncated and peaks are broadened, as well as longer time for separation. In this paper, a low voltage electrophoresis separation model was established, and the separation conditions were discussed. A new driving mode was proposed for applying low voltage, which was called multi-segments synchronized scanning. By using this driving mode, the reversed electric field that existed between the multi-segments can enrich samples and shorten the sample zone. The low voltage electrophoresis experiments using multi-segments synchronized scanning were carried out by home-made silicon-PDMS-based chip. The fluorescein isothiocyanate (FITC) labeled lysine and phenylalanine mixed samples with the concentration of 10-4 mol/L were successfully separated under the optimal conditions of 10 mmol/L borax buffer (pH = 10.0), 200 V/cm separation electric field and electrode switch time of 2.5 s. The separation was completed with a resolution of 2.0, and the peak time for lysine and phenylalanine was 4 min and 6 min, respectively.

Multi-atlas segmentation for abdominal organs with Gaussian mixture models

NASA Astrophysics Data System (ADS)

Burke, Ryan P.; Xu, Zhoubing; Lee, Christopher P.; Baucom, Rebeccah B.; Poulose, Benjamin K.; Abramson, Richard G.; Landman, Bennett A.

2015-03-01

Abdominal organ segmentation with clinically acquired computed tomography (CT) is drawing increasing interest in the medical imaging community. Gaussian mixture models (GMM) have been extensively used through medical segmentation, most notably in the brain for cerebrospinal fluid / gray matter / white matter differentiation. Because abdominal CT exhibit strong localized intensity characteristics, GMM have recently been incorporated in multi-stage abdominal segmentation algorithms. In the context of variable abdominal anatomy and rich algorithms, it is difficult to assess the marginal contribution of GMM. Herein, we characterize the efficacy of an a posteriori framework that integrates GMM of organ-wise intensity likelihood with spatial priors from multiple target-specific registered labels. In our study, we first manually labeled 100 CT images. Then, we assigned 40 images to use as training data for constructing target-specific spatial priors and intensity likelihoods. The remaining 60 images were evaluated as test targets for segmenting 12 abdominal organs. The overlap between the true and the automatic segmentations was measured by Dice similarity coefficient (DSC). A median improvement of 145% was achieved by integrating the GMM intensity likelihood against the specific spatial prior. The proposed framework opens the opportunities for abdominal organ segmentation by efficiently using both the spatial and appearance information from the atlases, and creates a benchmark for large-scale automatic abdominal segmentation.

Conjunctive Management of Multi-Aquifer System for Saltwater Intrusion Mitigation

NASA Astrophysics Data System (ADS)

Tsai, F. T. C.; Pham, H. V.

2015-12-01

Due to excessive groundwater withdrawals, many water wells in Baton Rouge, Louisiana experience undesirable chloride concentration because of saltwater intrusion. The study goal is to develop a conjunctive management framework that takes advantage of the Baton Rouge multi-aquifer system to mitigate saltwater intrusion. The conjunctive management framework utilizes several hydraulic control techniques to mitigate saltwater encroachment. These hydraulic control approaches include pumping well relocation, freshwater injection, saltwater scavenging, and their combinations. Specific objectives of the study are: (1) constructing scientific geologic architectures of the "800-foot" sand, the "1,000-foot" sand, the "1,200-foot" sand, the "1,500-foot" sand, the "1,700-foot" sand, and the "2,000-foot" sand, (2) developing scientific saltwater intrusion models for these sands. (3) using connector wells to draw native groundwater from one sand and inject to another sand to create hydraulic barriers to halt saltwater intrusion, (4) using scavenger wells or well couples to impede saltwater intrusion progress and reduce chloride concentration in pumping wells, and (5) reducing cones of depression by relocating and dispersing pumping wells to different sands. The study utilizes optimization techniques and newest LSU high performance computing (HPC) facilities to derive solutions. The conjunctive management framework serves as a scientific tool to assist policy makers to solve the urgent saltwater encroachment issue in the Baton Rouge area. The research results will help water companies as well as industries in East Baton Rouge Parish and neighboring parishes by reducing their saltwater intrusion threats, which in turn would sustain Capital Area economic development.

Effects of knee sleeves on coordination of lower-limb segments in healthy adults during level walking and one-leg hopping

PubMed Central

Chang, Yunhee; Jeong, Bora; Kang, Sungjae; Ryu, Jeicheong; Kim, Gyoosuk

2017-01-01

The evaluation of multisegment coordination is important in gaining a better understanding of the gait and physical activities in humans. Therefore, this study aims to verify whether the use of knee sleeves affects the coordination of lower-limb segments during level walking and one-leg hopping. Eleven healthy male adults participated in this study. They were asked to walk 10 m on a level ground and perform one-leg hops with and without a knee sleeve. The segment angles and the response velocities of the thigh, shank, and foot were measured and calculated by using a motion analysis system. The phases between the segment angle and the velocity were then calculated. Moreover, the continuous relative phase (CRP) was calculated as the phase of the distal segment subtracted from the phase of the proximal segment and denoted as CRPTS (thigh–shank), CRPSF (shank–foot), and CRPTF (thigh–foot). The root mean square (RMS) values were used to evaluate the in-phase or out-of-phase states, while the standard deviation (SD) values were utilized to evaluate the variability in the stance and swing phases during level walking and in the preflight, flight, and landing phases during one-leg hopping. The walking velocity and the flight time improved when the knee sleeve was worn (p < 0.05). The segment angles of the thigh and shank also changed when the knee sleeve was worn during level walking and one-leg hopping. The RMS values of CRPTS and CRPSF in the stance phase and the RMS values of CRPSF in the preflight and landing phases changed (p < 0.05 in all cases). Moreover, the SD values of CRPTS in the landing phase and the SD values of CRPSF in the preflight and landing phases increased (p < 0.05 in all cases). These results indicated that wearing a knee sleeve caused changes in segment kinematics and coordination. PMID:28533981

Balancing the Role of Priors in Multi-Observer Segmentation Evaluation

PubMed Central

Huang, Xiaolei; Wang, Wei; Lopresti, Daniel; Long, Rodney; Antani, Sameer; Xue, Zhiyun; Thoma, George

2009-01-01

Comparison of a group of multiple observer segmentations is known to be a challenging problem. A good segmentation evaluation method would allow different segmentations not only to be compared, but to be combined to generate a “true” segmentation with higher consensus. Numerous multi-observer segmentation evaluation approaches have been proposed in the literature, and STAPLE in particular probabilistically estimates the true segmentation by optimal combination of observed segmentations and a prior model of the truth. An Expectation–Maximization (EM) algorithm, STAPLE’S convergence to the desired local minima depends on good initializations for the truth prior and the observer-performance prior. However, accurate modeling of the initial truth prior is nontrivial. Moreover, among the two priors, the truth prior always dominates so that in certain scenarios when meaningful observer-performance priors are available, STAPLE can not take advantage of that information. In this paper, we propose a Bayesian decision formulation of the problem that permits the two types of prior knowledge to be integrated in a complementary manner in four cases with differing application purposes: (1) with known truth prior; (2) with observer prior; (3) with neither truth prior nor observer prior; and (4) with both truth prior and observer prior. The third and fourth cases are not discussed (or effectively ignored) by STAPLE, and in our research we propose a new method to combine multiple-observer segmentations based on the maximum a posterior (MAP) principle, which respects the observer prior regardless of the availability of the truth prior. Based on the four scenarios, we have developed a web-based software application that implements the flexible segmentation evaluation framework for digitized uterine cervix images. Experiment results show that our framework has flexibility in effectively integrating different priors for multi-observer segmentation evaluation and it also generates results comparing favorably to those by the STAPLE algorithm and the Majority Vote Rule. PMID:20523759

Segmentation and pulse shape discrimination techniques for rejecting background in germanium detectors

NASA Technical Reports Server (NTRS)

Roth, J.; Primbsch, J. H.; Lin, R. P.

1984-01-01

The possibility of rejecting the internal beta-decay background in coaxial germanium detectors by distinguishing between the multi-site energy losses characteristic of photons and the single-site energy losses of electrons in the range 0.2 - 2 MeV is examined. The photon transport was modeled with a Monte Carlo routine. Background rejection by both multiple segmentation and pulse shape discrimination techniques is investigated. The efficiency of a six 1 cm-thick segment coaxial detector operating in coincidence mode alone is compared to that of a two-segment (1 cm and 5 cm) detector employing both front-rear coincidence and PSD in the rear segment to isolate photon events. Both techniques can provide at least 95 percent rejection of single-site events while accepting at least 80 percent of the multi-site events above 500 keV.

Improved segmentation of cerebellar structures in children

PubMed Central

Narayanan, Priya Lakshmi; Boonazier, Natalie; Warton, Christopher; Molteno, Christopher D; Joseph, Jesuchristopher; Jacobson, Joseph L; Jacobson, Sandra W; Zöllei, Lilla; Meintjes, Ernesta M

2016-01-01

Background Consistent localization of cerebellar cortex in a standard coordinate system is important for functional studies and detection of anatomical alterations in studies of morphometry. To date, no pediatric cerebellar atlas is available. New method The probabilistic Cape Town Pediatric Cerebellar Atlas (CAPCA18) was constructed in the age-appropriate National Institute of Health Pediatric Database asymmetric template space using manual tracings of 16 cerebellar compartments in 18 healthy children (9–13 years) from Cape Town, South Africa. The individual atlases of the training subjects were also used to implement multi atlas label fusion using multi atlas majority voting (MAMV) and multi atlas generative model (MAGM) approaches. Segmentation accuracy in 14 test subjects was compared for each method to ‘gold standard’ manual tracings. Results Spatial overlap between manual tracings and CAPCA18 automated segmentation was 73% or higher for all lobules in both hemispheres, except VIIb and X. Automated segmentation using MAGM yielded the best segmentation accuracy over all lobules (mean Dice Similarity Coefficient 0.76; range 0.55–0.91). Comparison with existing methods In all lobules, spatial overlap of CAPCA18 segmentations with manual tracings was similar or higher than those obtained with SUIT (spatially unbiased infra-tentorial template), providing additional evidence of the benefits of an age appropriate atlas. MAGM segmentation accuracy was comparable to values reported recently by Park et al. (2014) in adults (across all lobules mean DSC = 0.73, range 0.40–0.89). Conclusions CAPCA18 and the associated multi atlases of the training subjects yield improved segmentation of cerebellar structures in children. PMID:26743973

3D automatic anatomy segmentation based on iterative graph-cut-ASM

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

Chen, Xinjian; Bagci, Ulas; Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Building 10 Room 1C515, Bethesda, Maryland 20892-1182

2011-08-15

Purpose: This paper studies the feasibility of developing an automatic anatomy segmentation (AAS) system in clinical radiology and demonstrates its operation on clinical 3D images. Methods: The AAS system, the authors are developing consists of two main parts: object recognition and object delineation. As for recognition, a hierarchical 3D scale-based multiobject method is used for the multiobject recognition task, which incorporates intensity weighted ball-scale (b-scale) information into the active shape model (ASM). For object delineation, an iterative graph-cut-ASM (IGCASM) algorithm is proposed, which effectively combines the rich statistical shape information embodied in ASM with the globally optimal delineation capability ofmore » the GC method. The presented IGCASM algorithm is a 3D generalization of the 2D GC-ASM method that they proposed previously in Chen et al.[Proc. SPIE, 7259, 72590C1-72590C-8 (2009)]. The proposed methods are tested on two datasets comprised of images obtained from 20 patients (10 male and 10 female) of clinical abdominal CT scans, and 11 foot magnetic resonance imaging (MRI) scans. The test is for four organs (liver, left and right kidneys, and spleen) segmentation, five foot bones (calcaneus, tibia, cuboid, talus, and navicular). The recognition and delineation accuracies were evaluated separately. The recognition accuracy was evaluated in terms of translation, rotation, and scale (size) error. The delineation accuracy was evaluated in terms of true and false positive volume fractions (TPVF, FPVF). The efficiency of the delineation method was also evaluated on an Intel Pentium IV PC with a 3.4 GHZ CPU machine. Results: The recognition accuracies in terms of translation, rotation, and scale error over all organs are about 8 mm, 10 deg. and 0.03, and over all foot bones are about 3.5709 mm, 0.35 deg. and 0.025, respectively. The accuracy of delineation over all organs for all subjects as expressed in TPVF and FPVF is 93.01% and 0.22%, and all foot bones for all subjects are 93.75% and 0.28%, respectively. While the delineations for the four organs can be accomplished quite rapidly with average of 78 s, the delineations for the five foot bones can be accomplished with average of 70 s. Conclusions: The experimental results showed the feasibility and efficacy of the proposed automatic anatomy segmentation system: (a) the incorporation of shape priors into the GC framework is feasible in 3D as demonstrated previously for 2D images; (b) our results in 3D confirm the accuracy behavior observed in 2D. The hybrid strategy IGCASM seems to be more robust and accurate than ASM and GC individually; and (c) delineations within body regions and foot bones of clinical importance can be accomplished quite rapidly within 1.5 min.« less

3D automatic anatomy segmentation based on iterative graph-cut-ASM

PubMed Central

Chen, Xinjian; Bagci, Ulas

2011-01-01

Purpose: This paper studies the feasibility of developing an automatic anatomy segmentation (AAS) system in clinical radiology and demonstrates its operation on clinical 3D images.Methods: The AAS system, the authors are developing consists of two main parts: object recognition and object delineation. As for recognition, a hierarchical 3D scale-based multiobject method is used for the multiobject recognition task, which incorporates intensity weighted ball-scale (b-scale) information into the active shape model (ASM). For object delineation, an iterative graph-cut-ASM (IGCASM) algorithm is proposed, which effectively combines the rich statistical shape information embodied in ASM with the globally optimal delineation capability of the GC method. The presented IGCASM algorithm is a 3D generalization of the 2D GC-ASM method that they proposed previously in Chen et al. [Proc. SPIE, 7259, 72590C1–72590C-8 (2009)]. The proposed methods are tested on two datasets comprised of images obtained from 20 patients (10 male and 10 female) of clinical abdominal CT scans, and 11 foot magnetic resonance imaging (MRI) scans. The test is for four organs (liver, left and right kidneys, and spleen) segmentation, five foot bones (calcaneus, tibia, cuboid, talus, and navicular). The recognition and delineation accuracies were evaluated separately. The recognition accuracy was evaluated in terms of translation, rotation, and scale (size) error. The delineation accuracy was evaluated in terms of true and false positive volume fractions (TPVF, FPVF). The efficiency of the delineation method was also evaluated on an Intel Pentium IV PC with a 3.4 GHZ CPU machine.Results: The recognition accuracies in terms of translation, rotation, and scale error over all organs are about 8 mm, 10° and 0.03, and over all foot bones are about 3.5709 mm, 0.35° and 0.025, respectively. The accuracy of delineation over all organs for all subjects as expressed in TPVF and FPVF is 93.01% and 0.22%, and all foot bones for all subjects are 93.75% and 0.28%, respectively. While the delineations for the four organs can be accomplished quite rapidly with average of 78 s, the delineations for the five foot bones can be accomplished with average of 70 s.Conclusions: The experimental results showed the feasibility and efficacy of the proposed automatic anatomy segmentation system: (a) the incorporation of shape priors into the GC framework is feasible in 3D as demonstrated previously for 2D images; (b) our results in 3D confirm the accuracy behavior observed in 2D. The hybrid strategy IGCASM seems to be more robust and accurate than ASM and GC individually; and (c) delineations within body regions and foot bones of clinical importance can be accomplished quite rapidly within 1.5 min. PMID:21928634

Genetic evaluation and selection response for growth in meat-type quail through random regression models using B-spline functions and Legendre polynomials.

PubMed

Mota, L F M; Martins, P G M A; Littiere, T O; Abreu, L R A; Silva, M A; Bonafé, C M

2018-04-01

The objective was to estimate (co)variance functions using random regression models (RRM) with Legendre polynomials, B-spline function and multi-trait models aimed at evaluating genetic parameters of growth traits in meat-type quail. A database containing the complete pedigree information of 7000 meat-type quail was utilized. The models included the fixed effects of contemporary group and generation. Direct additive genetic and permanent environmental effects, considered as random, were modeled using B-spline functions considering quadratic and cubic polynomials for each individual segment, and Legendre polynomials for age. Residual variances were grouped in four age classes. Direct additive genetic and permanent environmental effects were modeled using 2 to 4 segments and were modeled by Legendre polynomial with orders of fit ranging from 2 to 4. The model with quadratic B-spline adjustment, using four segments for direct additive genetic and permanent environmental effects, was the most appropriate and parsimonious to describe the covariance structure of the data. The RRM using Legendre polynomials presented an underestimation of the residual variance. Lesser heritability estimates were observed for multi-trait models in comparison with RRM for the evaluated ages. In general, the genetic correlations between measures of BW from hatching to 35 days of age decreased as the range between the evaluated ages increased. Genetic trend for BW was positive and significant along the selection generations. The genetic response to selection for BW in the evaluated ages presented greater values for RRM compared with multi-trait models. In summary, RRM using B-spline functions with four residual variance classes and segments were the best fit for genetic evaluation of growth traits in meat-type quail. In conclusion, RRM should be considered in genetic evaluation of breeding programs.

Fully Convolutional Neural Networks Improve Abdominal Organ Segmentation.

PubMed

Bobo, Meg F; Bao, Shunxing; Huo, Yuankai; Yao, Yuang; Virostko, Jack; Plassard, Andrew J; Lyu, Ilwoo; Assad, Albert; Abramson, Richard G; Hilmes, Melissa A; Landman, Bennett A

2018-03-01

Abdominal image segmentation is a challenging, yet important clinical problem. Variations in body size, position, and relative organ positions greatly complicate the segmentation process. Historically, multi-atlas methods have achieved leading results across imaging modalities and anatomical targets. However, deep learning is rapidly overtaking classical approaches for image segmentation. Recently, Zhou et al. showed that fully convolutional networks produce excellent results in abdominal organ segmentation of computed tomography (CT) scans. Yet, deep learning approaches have not been applied to whole abdomen magnetic resonance imaging (MRI) segmentation. Herein, we evaluate the applicability of an existing fully convolutional neural network (FCNN) designed for CT imaging to segment abdominal organs on T2 weighted (T2w) MRI's with two examples. In the primary example, we compare a classical multi-atlas approach with FCNN on forty-five T2w MRI's acquired from splenomegaly patients with five organs labeled (liver, spleen, left kidney, right kidney, and stomach). Thirty-six images were used for training while nine were used for testing. The FCNN resulted in a Dice similarity coefficient (DSC) of 0.930 in spleens, 0.730 in left kidneys, 0.780 in right kidneys, 0.913 in livers, and 0.556 in stomachs. The performance measures for livers, spleens, right kidneys, and stomachs were significantly better than multi-atlas (p < 0.05, Wilcoxon rank-sum test). In a secondary example, we compare the multi-atlas approach with FCNN on 138 distinct T2w MRI's with manually labeled pancreases (one label). On the pancreas dataset, the FCNN resulted in a median DSC of 0.691 in pancreases versus 0.287 for multi-atlas. The results are highly promising given relatively limited training data and without specific training of the FCNN model and illustrate the potential of deep learning approaches to transcend imaging modalities.

Fully convolutional neural networks improve abdominal organ segmentation

NASA Astrophysics Data System (ADS)

Bobo, Meg F.; Bao, Shunxing; Huo, Yuankai; Yao, Yuang; Virostko, Jack; Plassard, Andrew J.; Lyu, Ilwoo; Assad, Albert; Abramson, Richard G.; Hilmes, Melissa A.; Landman, Bennett A.

2018-03-01

Abdominal image segmentation is a challenging, yet important clinical problem. Variations in body size, position, and relative organ positions greatly complicate the segmentation process. Historically, multi-atlas methods have achieved leading results across imaging modalities and anatomical targets. However, deep learning is rapidly overtaking classical approaches for image segmentation. Recently, Zhou et al. showed that fully convolutional networks produce excellent results in abdominal organ segmentation of computed tomography (CT) scans. Yet, deep learning approaches have not been applied to whole abdomen magnetic resonance imaging (MRI) segmentation. Herein, we evaluate the applicability of an existing fully convolutional neural network (FCNN) designed for CT imaging to segment abdominal organs on T2 weighted (T2w) MRI's with two examples. In the primary example, we compare a classical multi-atlas approach with FCNN on forty-five T2w MRI's acquired from splenomegaly patients with five organs labeled (liver, spleen, left kidney, right kidney, and stomach). Thirty-six images were used for training while nine were used for testing. The FCNN resulted in a Dice similarity coefficient (DSC) of 0.930 in spleens, 0.730 in left kidneys, 0.780 in right kidneys, 0.913 in livers, and 0.556 in stomachs. The performance measures for livers, spleens, right kidneys, and stomachs were significantly better than multi-atlas (p < 0.05, Wilcoxon rank-sum test). In a secondary example, we compare the multi-atlas approach with FCNN on 138 distinct T2w MRI's with manually labeled pancreases (one label). On the pancreas dataset, the FCNN resulted in a median DSC of 0.691 in pancreases versus 0.287 for multi-atlas. The results are highly promising given relatively limited training data and without specific training of the FCNN model and illustrate the potential of deep learning approaches to transcend imaging modalities. 1

Locally adaptive MR intensity models and MRF-based segmentation of multiple sclerosis lesions

NASA Astrophysics Data System (ADS)

Galimzianova, Alfiia; Lesjak, Žiga; Likar, Boštjan; Pernuš, Franjo; Špiclin, Žiga

2015-03-01

Neuroimaging biomarkers are an important paraclinical tool used to characterize a number of neurological diseases, however, their extraction requires accurate and reliable segmentation of normal and pathological brain structures. For MR images of healthy brains the intensity models of normal-appearing brain tissue (NABT) in combination with Markov random field (MRF) models are known to give reliable and smooth NABT segmentation. However, the presence of pathology, MR intensity bias and natural tissue-dependent intensity variability altogether represent difficult challenges for a reliable estimation of NABT intensity model based on MR images. In this paper, we propose a novel method for segmentation of normal and pathological structures in brain MR images of multiple sclerosis (MS) patients that is based on locally-adaptive NABT model, a robust method for the estimation of model parameters and a MRF-based segmentation framework. Experiments on multi-sequence brain MR images of 27 MS patients show that, compared to whole-brain model and compared to the widely used Expectation-Maximization Segmentation (EMS) method, the locally-adaptive NABT model increases the accuracy of MS lesion segmentation.

Whole abdominal wall segmentation using augmented active shape models (AASM) with multi-atlas label fusion and level set

NASA Astrophysics Data System (ADS)

Xu, Zhoubing; Baucom, Rebeccah B.; Abramson, Richard G.; Poulose, Benjamin K.; Landman, Bennett A.

2016-03-01

The abdominal wall is an important structure differentiating subcutaneous and visceral compartments and intimately involved with maintaining abdominal structure. Segmentation of the whole abdominal wall on routinely acquired computed tomography (CT) scans remains challenging due to variations and complexities of the wall and surrounding tissues. In this study, we propose a slice-wise augmented active shape model (AASM) approach to robustly segment both the outer and inner surfaces of the abdominal wall. Multi-atlas label fusion (MALF) and level set (LS) techniques are integrated into the traditional ASM framework. The AASM approach globally optimizes the landmark updates in the presence of complicated underlying local anatomical contexts. The proposed approach was validated on 184 axial slices of 20 CT scans. The Hausdorff distance against the manual segmentation was significantly reduced using proposed approach compared to that using ASM, MALF, and LS individually. Our segmentation of the whole abdominal wall enables the subcutaneous and visceral fat measurement, with high correlation to the measurement derived from manual segmentation. This study presents the first generic algorithm that combines ASM, MALF, and LS, and demonstrates practical application for automatically capturing visceral and subcutaneous fat volumes.

Multi-channel NIRS of the primary motor cortex to discriminate hand from foot activity

NASA Astrophysics Data System (ADS)

Koenraadt, K. L. M.; Duysens, J.; Smeenk, M.; Keijsers, N. L. W.

2012-08-01

The poor spatial resolution of near-infrared spectroscopy (NIRS) makes it difficult to distinguish two closely located cortical areas from each other. Here, a combination of multi-channel NIRS and a centre of gravity (CoG) approach (widely accepted in the field of transcranial magnetic stimulation; TMS) was used to discriminate between closely located cortical areas activated during hand and foot movements. Similarly, the possibility of separating the more anteriorly represented discrete movements from rhythmic movements was studied. Thirteen healthy right-handed subjects performed rhythmic or discrete (‘task’) hand or foot (‘extremity’) tapping. Hemodynamic responses were measured using an 8-channel NIRS setup. For oxyhemoglobin (OHb) and deoxyhemoglobin (HHb), a CoG was determined for each condition using the mean hemodynamic responses and the coordinates of the channels. Significant hemodynamic responses were found for hand and foot movements. Based on the HHb responses, the NIRS-CoG of hand movements was located 0.6 cm more laterally compared to the NIRS-CoG of foot movements. For OHb responses no difference in NIRS-CoG was found for ‘extremity’ nor for ‘task’. This is the first NIRS study showing hemodynamic responses for isolated foot movements. Furthermore, HHb responses have the potential to be used in multi-channel NIRS experiments requiring differential activation of motor cortex areas linked to either hand or foot movements.

Asymmetric interjoint feedback contributes to postural control of redundant multi-link systems

NASA Astrophysics Data System (ADS)

Bunderson, Nathan E.; Ting, Lena H.; Burkholder, Thomas J.

2007-09-01

Maintaining the postural configuration of a limb such as an arm or leg is a fundamental neural control task that involves the coordination of multiple linked body segments. Biological systems are known to use a complex network of inter- and intra-joint feedback mechanisms arising from muscles, spinal reflexes and higher neuronal structures to stabilize the limbs. While previous work has shown that a small amount of asymmetric heterogenic feedback contributes to the behavior of these systems, a satisfactory functional explanation for this non-conservative feedback structure has not been put forth. We hypothesized that an asymmetric multi-joint control strategy would confer both an energetic and stability advantage in maintaining endpoint position of a kinematically redundant system. We tested this hypothesis by using optimal control models incorporating symmetric versus asymmetric feedback with the goal of maintaining the endpoint location of a kinematically redundant, planar limb. Asymmetric feedback improved endpoint control performance of the limb by 16%, reduced energetic cost by 21% and increased interjoint coordination by 40% compared to the symmetric feedback system. The overall effect of the asymmetry was that proximal joint motion resulted in greater torque generation at distal joints than vice versa. The asymmetric organization is consistent with heterogenic stretch reflex gains measured experimentally. We conclude that asymmetric feedback has a functionally relevant role in coordinating redundant degrees of freedom to maintain the position of the hand or foot.

Asymmetric interjoint feedback contributes to postural control of redundant multi-link systems

PubMed Central

Bunderson, Nathan E.; Ting, Lena H.; Burkholder, Thomas J.

2008-01-01

Maintaining the postural configuration of a limb such as an arm or leg is a fundamental neural control task that involves the coordination of multiple linked body segments. Biological systems are known to use a complex network of inter- and intra-joint feedback mechanisms arising from muscles, spinal reflexes, and higher neuronal structures to stabilize the limbs. While previous work has shown that a small amount of asymmetric heterogenic feedback contributes to the behavior of these systems, a satisfactory functional explanation for this nonconservative feedback structure has not been put forth. We hypothesized that an asymmetric multi-joint control strategy would confer both an energetic and stability advantage in maintaining endpoint position of a kinematically redundant system. We tested this hypothesis by using optimal control models incorporating symmetric versus asymmetric feedback with the goal of maintaining the endpoint location of a kinematically redundant, planar limb. Asymmetric feedback improved endpoint control performance of the limb by 16%, reduced energetic cost by 21% and increased interjoint coordination by 40% compared to the symmetric feedback system. The overall effect of the asymmetry was that proximal joint motion resulted in greater torque generation at distal joints than vice versa. The asymmetric organization is consistent with heterogenic stretch reflex gains measured experimentally. We conclude that asymmetric feedback has a functionally relevant role in coordinating redundant degrees of freedom to maintain the position of the hand or foot. PMID:17873426

A multi-directional and multi-scale roughness filter to detect lineament segments on digital elevation models - analyzing spatial objects in R

NASA Astrophysics Data System (ADS)

Baumann, Sebastian; Robl, Jörg; Wendt, Lorenz; Willingshofer, Ernst; Hilberg, Sylke

2016-04-01

Automated lineament analysis on remotely sensed data requires two general process steps: The identification of neighboring pixels showing high contrast and the conversion of these domains into lines. The target output is the lineaments' position, extent and orientation. We developed a lineament extraction tool programmed in R using digital elevation models as input data to generate morphological lineaments defined as follows: A morphological lineament represents a zone of high relief roughness, whose length significantly exceeds the width. As relief roughness any deviation from a flat plane, defined by a roughness threshold, is considered. In our novel approach a multi-directional and multi-scale roughness filter uses moving windows of different neighborhood sizes to identify threshold limited rough domains on digital elevation models. Surface roughness is calculated as the vertical elevation difference between the center cell and the different orientated straight lines connecting two edge cells of a neighborhood, divided by the horizontal distance of the edge cells. Thus multiple roughness values depending on the neighborhood sizes and orientations of the edge connecting lines are generated for each cell and their maximum and minimum values are extracted. Thereby negative signs of the roughness parameter represent concave relief structures as valleys, positive signs convex relief structures as ridges. A threshold defines domains of high relief roughness. These domains are thinned to a representative point pattern by a 3x3 neighborhood filter, highlighting maximum and minimum roughness peaks, and representing the center points of lineament segments. The orientation and extent of the lineament segments are calculated within the roughness domains, generating a straight line segment in the direction of least roughness differences. We tested our algorithm on digital elevation models of multiple sources and scales and compared the results visually with shaded relief map of these digital elevation models. The lineament segments trace the relief structure to a great extent and the calculated roughness parameter represents the physical geometry of the digital elevation model. Modifying the threshold for the surface roughness value highlights different distinct relief structures. Also the neighborhood size at which lineament segments are detected correspond with the width of the surface structure and may be a useful additional parameter for further analysis. The discrimination of concave and convex relief structures perfectly matches with valleys and ridges of the surface.

Seismic Hazard Analysis on a Complex, Interconnected Fault Network

NASA Astrophysics Data System (ADS)

Page, M. T.; Field, E. H.; Milner, K. R.

2017-12-01

In California, seismic hazard models have evolved from simple, segmented prescriptive models to much more complex representations of multi-fault and multi-segment earthquakes on an interconnected fault network. During the development of the 3rd Uniform California Earthquake Rupture Forecast (UCERF3), the prevalence of multi-fault ruptures in the modeling was controversial. Yet recent earthquakes, for example, the Kaikora earthquake - as well as new research on the potential of multi-fault ruptures (e.g., Nissen et al., 2016; Sahakian et al. 2017) - have validated this approach. For large crustal earthquakes, multi-fault ruptures may be the norm rather than the exception. As datasets improve and we can view the rupture process at a finer scale, the interconnected, fractal nature of faults is revealed even by individual earthquakes. What is the proper way to model earthquakes on a fractal fault network? We show multiple lines of evidence that connectivity even in modern models such as UCERF3 may be underestimated, although clustering in UCERF3 mitigates some modeling simplifications. We need a methodology that can be applied equally well where the fault network is well-mapped and where it is not - an extendable methodology that allows us to "fill in" gaps in the fault network and in our knowledge.

Segmentation of pelvic structures for planning CT using a geometrical shape model tuned by a multi-scale edge detector

PubMed Central

Martínez, Fabio; Romero, Eduardo; Dréan, Gaël; Simon, Antoine; Haigron, Pascal; De Crevoisier, Renaud; Acosta, Oscar

2014-01-01

Accurate segmentation of the prostate and organs at risk in computed tomography (CT) images is a crucial step for radiotherapy (RT) planning. Manual segmentation, as performed nowadays, is a time consuming process and prone to errors due to the a high intra- and inter-expert variability. This paper introduces a new automatic method for prostate, rectum and bladder segmentation in planning CT using a geometrical shape model under a Bayesian framework. A set of prior organ shapes are first built by applying Principal Component Analysis (PCA) to a population of manually delineated CT images. Then, for a given individual, the most similar shape is obtained by mapping a set of multi-scale edge observations to the space of organs with a customized likelihood function. Finally, the selected shape is locally deformed to adjust the edges of each organ. Experiments were performed with real data from a population of 116 patients treated for prostate cancer. The data set was split in training and test groups, with 30 and 86 patients, respectively. Results show that the method produces competitive segmentations w.r.t standard methods (Averaged Dice = 0.91 for prostate, 0.94 for bladder, 0.89 for Rectum) and outperforms the majority-vote multi-atlas approaches (using rigid registration, free-form deformation (FFD) and the demons algorithm) PMID:24594798

Automatic Structural Parcellation of Mouse Brain MRI Using Multi-Atlas Label Fusion

PubMed Central

Ma, Da; Cardoso, Manuel J.; Modat, Marc; Powell, Nick; Wells, Jack; Holmes, Holly; Wiseman, Frances; Tybulewicz, Victor; Fisher, Elizabeth; Lythgoe, Mark F.; Ourselin, Sébastien

2014-01-01

Multi-atlas segmentation propagation has evolved quickly in recent years, becoming a state-of-the-art methodology for automatic parcellation of structural images. However, few studies have applied these methods to preclinical research. In this study, we present a fully automatic framework for mouse brain MRI structural parcellation using multi-atlas segmentation propagation. The framework adopts the similarity and truth estimation for propagated segmentations (STEPS) algorithm, which utilises a locally normalised cross correlation similarity metric for atlas selection and an extended simultaneous truth and performance level estimation (STAPLE) framework for multi-label fusion. The segmentation accuracy of the multi-atlas framework was evaluated using publicly available mouse brain atlas databases with pre-segmented manually labelled anatomical structures as the gold standard, and optimised parameters were obtained for the STEPS algorithm in the label fusion to achieve the best segmentation accuracy. We showed that our multi-atlas framework resulted in significantly higher segmentation accuracy compared to single-atlas based segmentation, as well as to the original STAPLE framework. PMID:24475148

Example based lesion segmentation

NASA Astrophysics Data System (ADS)

Roy, Snehashis; He, Qing; Carass, Aaron; Jog, Amod; Cuzzocreo, Jennifer L.; Reich, Daniel S.; Prince, Jerry; Pham, Dzung

2014-03-01

Automatic and accurate detection of white matter lesions is a significant step toward understanding the progression of many diseases, like Alzheimer's disease or multiple sclerosis. Multi-modal MR images are often used to segment T2 white matter lesions that can represent regions of demyelination or ischemia. Some automated lesion segmentation methods describe the lesion intensities using generative models, and then classify the lesions with some combination of heuristics and cost minimization. In contrast, we propose a patch-based method, in which lesions are found using examples from an atlas containing multi-modal MR images and corresponding manual delineations of lesions. Patches from subject MR images are matched to patches from the atlas and lesion memberships are found based on patch similarity weights. We experiment on 43 subjects with MS, whose scans show various levels of lesion-load. We demonstrate significant improvement in Dice coefficient and total lesion volume compared to a state of the art model-based lesion segmentation method, indicating more accurate delineation of lesions.

Combining multi-atlas segmentation with brain surface estimation

NASA Astrophysics Data System (ADS)

Huo, Yuankai; Carass, Aaron; Resnick, Susan M.; Pham, Dzung L.; Prince, Jerry L.; Landman, Bennett A.

2016-03-01

Whole brain segmentation (with comprehensive cortical and subcortical labels) and cortical surface reconstruction are two essential techniques for investigating the human brain. The two tasks are typically conducted independently, however, which leads to spatial inconsistencies and hinders further integrated cortical analyses. To obtain self-consistent whole brain segmentations and surfaces, FreeSurfer segregates the subcortical and cortical segmentations before and after the cortical surface reconstruction. However, this "segmentation to surface to parcellation" strategy has shown limitation in various situations. In this work, we propose a novel "multi-atlas segmentation to surface" method called Multi-atlas CRUISE (MaCRUISE), which achieves self-consistent whole brain segmentations and cortical surfaces by combining multi-atlas segmentation with the cortical reconstruction method CRUISE. To our knowledge, this is the first work that achieves the reliability of state-of-the-art multi-atlas segmentation and labeling methods together with accurate and consistent cortical surface reconstruction. Compared with previous methods, MaCRUISE has three features: (1) MaCRUISE obtains 132 cortical/subcortical labels simultaneously from a single multi-atlas segmentation before reconstructing volume consistent surfaces; (2) Fuzzy tissue memberships are combined with multi-atlas segmentations to address partial volume effects; (3) MaCRUISE reconstructs topologically consistent cortical surfaces by using the sulci locations from multi-atlas segmentation. Two data sets, one consisting of five subjects with expertly traced landmarks and the other consisting of 100 volumes from elderly subjects are used for validation. Compared with CRUISE, MaCRUISE achieves self-consistent whole brain segmentation and cortical reconstruction without compromising on surface accuracy. MaCRUISE is comparably accurate to FreeSurfer while achieving greater robustness across an elderly population.

Combining Multi-atlas Segmentation with Brain Surface Estimation.

PubMed

Huo, Yuankai; Carass, Aaron; Resnick, Susan M; Pham, Dzung L; Prince, Jerry L; Landman, Bennett A

2016-02-27

Whole brain segmentation (with comprehensive cortical and subcortical labels) and cortical surface reconstruction are two essential techniques for investigating the human brain. The two tasks are typically conducted independently, however, which leads to spatial inconsistencies and hinders further integrated cortical analyses. To obtain self-consistent whole brain segmentations and surfaces, FreeSurfer segregates the subcortical and cortical segmentations before and after the cortical surface reconstruction. However, this "segmentation to surface to parcellation" strategy has shown limitations in various situations. In this work, we propose a novel "multi-atlas segmentation to surface" method called Multi-atlas CRUISE (MaCRUISE), which achieves self-consistent whole brain segmentations and cortical surfaces by combining multi-atlas segmentation with the cortical reconstruction method CRUISE. To our knowledge, this is the first work that achieves the reliability of state-of-the-art multi-atlas segmentation and labeling methods together with accurate and consistent cortical surface reconstruction. Compared with previous methods, MaCRUISE has three features: (1) MaCRUISE obtains 132 cortical/subcortical labels simultaneously from a single multi-atlas segmentation before reconstructing volume consistent surfaces; (2) Fuzzy tissue memberships are combined with multi-atlas segmentations to address partial volume effects; (3) MaCRUISE reconstructs topologically consistent cortical surfaces by using the sulci locations from multi-atlas segmentation. Two data sets, one consisting of five subjects with expertly traced landmarks and the other consisting of 100 volumes from elderly subjects are used for validation. Compared with CRUISE, MaCRUISE achieves self-consistent whole brain segmentation and cortical reconstruction without compromising on surface accuracy. MaCRUISE is comparably accurate to FreeSurfer while achieving greater robustness across an elderly population.

Ischemic stroke lesion segmentation in multi-spectral MR images with support vector machine classifiers

NASA Astrophysics Data System (ADS)

Maier, Oskar; Wilms, Matthias; von der Gablentz, Janina; Krämer, Ulrike; Handels, Heinz

2014-03-01

Automatic segmentation of ischemic stroke lesions in magnetic resonance (MR) images is important in clinical practice and for neuroscientific trials. The key problem is to detect largely inhomogeneous regions of varying sizes, shapes and locations. We present a stroke lesion segmentation method based on local features extracted from multi-spectral MR data that are selected to model a human observer's discrimination criteria. A support vector machine classifier is trained on expert-segmented examples and then used to classify formerly unseen images. Leave-one-out cross validation on eight datasets with lesions of varying appearances is performed, showing our method to compare favourably with other published approaches in terms of accuracy and robustness. Furthermore, we compare a number of feature selectors and closely examine each feature's and MR sequence's contribution.

Biomechanical Characteristics and Determinants of Instep Soccer Kick

PubMed Central

Kellis, Eleftherios; Katis, Athanasios

2007-01-01

Good kicking technique is an important aspect of a soccer player. Therefore, understanding the biomechanics of soccer kicking is particularly important for guiding and monitoring the training process. The purpose of this review was to examine latest research findings on biomechanics of soccer kick performance and identify weaknesses of present research which deserve further attention in the future. Being a multiarticular movement, soccer kick is characterised by a proximal-to-distal motion of the lower limb segments of the kicking leg. Angular velocity is maximized first by the thigh, then by the shank and finally by the foot. This is accomplished by segmental and joint movements in multiple planes. During backswing, the thigh decelerates mainly due to a motion-dependent moment from the shank and, to a lesser extent, by activation of hip muscles. In turn, forward acceleration of the shank is accomplished through knee extensor moment as well as a motion-dependent moment from the thigh. The final speed, path and spin of the ball largely depend on the quality of foot-ball contact. Powerful kicks are achieved through a high foot velocity and coefficient of restitution. Preliminary data indicate that accurate kicks are achieved through slower kicking motion and ball speed values. Key pointsSoccer kick is achieved through segmental and joint rotations in multiple planes and via the proximal-to-distal sequence of segmental angular velocities until ball impact. The quality of ball - foot impact and the mechanical behavior of the foot are also important determinants of the final speed, path and spin of the ball.Ball speed values during the maximum instep kick range from 18 to 35 msec-1 depending on various factors, such as skill level, age, approach angle and limb dominance.The main bulk of biomechanics research examined the biomechanics of powerful kicks, mostly under laboratory conditions. A powerful kick is characterized by the achievement of maximal ball speed. However, maximal ball speed does not guarantee a successful kick: in each case, the ball must reach the target. As already explained, when the player is instructed to hit the ball accurately, joint and segment velocities are lower as opposed to a fast and powerful kick performance. It is therefore apparent that future research should focus on biomechanics of fast but accurate kicking. PMID:24149324

Multi-object segmentation framework using deformable models for medical imaging analysis.

PubMed

Namías, Rafael; D'Amato, Juan Pablo; Del Fresno, Mariana; Vénere, Marcelo; Pirró, Nicola; Bellemare, Marc-Emmanuel

2016-08-01

Segmenting structures of interest in medical images is an important step in different tasks such as visualization, quantitative analysis, simulation, and image-guided surgery, among several other clinical applications. Numerous segmentation methods have been developed in the past three decades for extraction of anatomical or functional structures on medical imaging. Deformable models, which include the active contour models or snakes, are among the most popular methods for image segmentation combining several desirable features such as inherent connectivity and smoothness. Even though different approaches have been proposed and significant work has been dedicated to the improvement of such algorithms, there are still challenging research directions as the simultaneous extraction of multiple objects and the integration of individual techniques. This paper presents a novel open-source framework called deformable model array (DMA) for the segmentation of multiple and complex structures of interest in different imaging modalities. While most active contour algorithms can extract one region at a time, DMA allows integrating several deformable models to deal with multiple segmentation scenarios. Moreover, it is possible to consider any existing explicit deformable model formulation and even to incorporate new active contour methods, allowing to select a suitable combination in different conditions. The framework also introduces a control module that coordinates the cooperative evolution of the snakes and is able to solve interaction issues toward the segmentation goal. Thus, DMA can implement complex object and multi-object segmentations in both 2D and 3D using the contextual information derived from the model interaction. These are important features for several medical image analysis tasks in which different but related objects need to be simultaneously extracted. Experimental results on both computed tomography and magnetic resonance imaging show that the proposed framework has a wide range of applications especially in the presence of adjacent structures of interest or under intra-structure inhomogeneities giving excellent quantitative results.

A generative model for segmentation of tumor and organs-at-risk for radiation therapy planning of glioblastoma patients

NASA Astrophysics Data System (ADS)

Agn, Mikael; Law, Ian; Munck af Rosenschöld, Per; Van Leemput, Koen

2016-03-01

We present a fully automated generative method for simultaneous brain tumor and organs-at-risk segmentation in multi-modal magnetic resonance images. The method combines an existing whole-brain segmentation technique with a spatial tumor prior, which uses convolutional restricted Boltzmann machines to model tumor shape. The method is not tuned to any specific imaging protocol and can simultaneously segment the gross tumor volume, peritumoral edema and healthy tissue structures relevant for radiotherapy planning. We validate the method on a manually delineated clinical data set of glioblastoma patients by comparing segmentations of gross tumor volume, brainstem and hippocampus. The preliminary results demonstrate the feasibility of the method.

Leveraging unsupervised training sets for multi-scale compartmentalization in renal pathology

NASA Astrophysics Data System (ADS)

Lutnick, Brendon; Tomaszewski, John E.; Sarder, Pinaki

2017-03-01

Clinical pathology relies on manual compartmentalization and quantification of biological structures, which is time consuming and often error-prone. Application of computer vision segmentation algorithms to histopathological image analysis, in contrast, can offer fast, reproducible, and accurate quantitative analysis to aid pathologists. Algorithms tunable to different biologically relevant structures can allow accurate, precise, and reproducible estimates of disease states. In this direction, we have developed a fast, unsupervised computational method for simultaneously separating all biologically relevant structures from histopathological images in multi-scale. Segmentation is achieved by solving an energy optimization problem. Representing the image as a graph, nodes (pixels) are grouped by minimizing a Potts model Hamiltonian, adopted from theoretical physics, modeling interacting electron spins. Pixel relationships (modeled as edges) are used to update the energy of the partitioned graph. By iteratively improving the clustering, the optimal number of segments is revealed. To reduce computational time, the graph is simplified using a Cantor pairing function to intelligently reduce the number of included nodes. The classified nodes are then used to train a multiclass support vector machine to apply the segmentation over the full image. Accurate segmentations of images with as many as 106 pixels can be completed only in 5 sec, allowing for attainable multi-scale visualization. To establish clinical potential, we employed our method in renal biopsies to quantitatively visualize for the first time scale variant compartments of heterogeneous intra- and extraglomerular structures simultaneously. Implications of the utility of our method extend to fields such as oncology, genomics, and non-biological problems.

Carotid stenosis assessment with multi-detector CT angiography: comparison between manual and automatic segmentation methods.

PubMed

Zhu, Chengcheng; Patterson, Andrew J; Thomas, Owen M; Sadat, Umar; Graves, Martin J; Gillard, Jonathan H

2013-04-01

Luminal stenosis is used for selecting the optimal management strategy for patients with carotid artery disease. The aim of this study is to evaluate the reproducibility of carotid stenosis quantification using manual and automated segmentation methods using submillimeter through-plane resolution Multi-Detector CT angiography (MDCTA). 35 patients having carotid artery disease with >30 % luminal stenosis as identified by carotid duplex imaging underwent contrast enhanced MDCTA. Two experienced CT readers quantified carotid stenosis from axial source images, reconstructed maximum intensity projection (MIP) and 3D-carotid geometry which was automatically segmented by an open-source toolkit (Vascular Modelling Toolkit, VMTK) using NASCET criteria. Good agreement among the measurement using axial images, MIP and automatic segmentation was observed. Automatic segmentation methods show better inter-observer agreement between the readers (intra-class correlation coefficient (ICC): 0.99 for diameter stenosis measurement) than manual measurement of axial (ICC = 0.82) and MIP (ICC = 0.86) images. Carotid stenosis quantification using an automatic segmentation method has higher reproducibility compared with manual methods.

Deformity or dysfunction? Osteopathic manipulation of the idiopathic cavus foot: A clinical suggestion.

PubMed Central

Gidali, Adi; Harris, Valerie

2010-01-01

Observed gait abnormalities are often related to a variety of foot deformities such as the cavus foot, also known as pes cavus, cavovarus, uncompensated varus, and the high arched foot. When gait abnormalities related to cavus foot deformities produce symptoms or contribute to dysfunctional movement of the lower extremity, foot orthotics are commonly used to accommodate the deformity and optimize the function of the lower extremity. In more severe cases, surgical intervention is common. Hypomobility of the many joints of the foot and ankle may be mistaken as an idiopathic cavus foot deformity. As for any other limb segment suspected of musculoskeletal dysfunction, it is suggested that joint mobility testing and mobilization, if indicated, be attempted on the foot and ankle joints before assuming the presence of a bony cavus deformity. The purpose of this clinical suggestion is to describe the use of osteopathic manipulations of the foot and ankle in the context of an illustrative case of bilateral idiopathic cavus feet to demonstrate that apparent foot deformities may actually be joint hypomobility dysfunctions. PMID:21509155

Effects of medially posted insoles on foot and lower limb mechanics across walking and running in overpronating men.

PubMed

Kosonen, Jukka; Kulmala, Juha-Pekka; Müller, Erich; Avela, Janne

2017-03-21

Anti-pronation orthoses, like medially posted insoles (MPI), have traditionally been used to treat various of lower limb problems. Yet, we know surprisingly little about their effects on overall foot motion and lower limb mechanics across walking and running, which represent highly different loading conditions. To address this issue, multi-segment foot and lower limb mechanics was examined among 11 overpronating men with normal (NORM) and MPI insoles during walking (self-selected speed 1.70±0.19m/s vs 1.72±0.20m/s, respectively) and running (4.04±0.17m/s vs 4.10±0.13m/s, respectively). The kinematic results showed that MPI reduced the peak forefoot eversion movement in respect to both hindfoot and tibia across walking and running when compared to NORM (p<0.05-0.01). No differences were found in hindfoot eversion between conditions. The kinetic results showed no insole effects in walking, but during running MPI shifted center of pressure medially under the foot (p<0.01) leading to an increase in frontal plane moments at the hip (p<0.05) and knee (p<0.05) joints and a reduction at the ankle joint (p<0.05). These findings indicate that MPI primarily controlled the forefoot motion across walking and running. While kinetic response to MPI was more pronounced in running than walking, kinematic effects were essentially similar across both modes. This suggests that despite higher loads placed upon lower limb during running, there is no need to have a stiffer insoles to achieve similar reduction in the forefoot motion than in walking. Copyright © 2017 Elsevier Ltd. All rights reserved.

Performing label-fusion-based segmentation using multiple automatically generated templates.

PubMed

Chakravarty, M Mallar; Steadman, Patrick; van Eede, Matthijs C; Calcott, Rebecca D; Gu, Victoria; Shaw, Philip; Raznahan, Armin; Collins, D Louis; Lerch, Jason P

2013-10-01

Classically, model-based segmentation procedures match magnetic resonance imaging (MRI) volumes to an expertly labeled atlas using nonlinear registration. The accuracy of these techniques are limited due to atlas biases, misregistration, and resampling error. Multi-atlas-based approaches are used as a remedy and involve matching each subject to a number of manually labeled templates. This approach yields numerous independent segmentations that are fused using a voxel-by-voxel label-voting procedure. In this article, we demonstrate how the multi-atlas approach can be extended to work with input atlases that are unique and extremely time consuming to construct by generating a library of multiple automatically generated templates of different brains (MAGeT Brain). We demonstrate the efficacy of our method for the mouse and human using two different nonlinear registration algorithms (ANIMAL and ANTs). The input atlases consist a high-resolution mouse brain atlas and an atlas of the human basal ganglia and thalamus derived from serial histological data. MAGeT Brain segmentation improves the identification of the mouse anterior commissure (mean Dice Kappa values (κ = 0.801), but may be encountering a ceiling effect for hippocampal segmentations. Applying MAGeT Brain to human subcortical structures improves segmentation accuracy for all structures compared to regular model-based techniques (κ = 0.845, 0.752, and 0.861 for the striatum, globus pallidus, and thalamus, respectively). Experiments performed with three manually derived input templates suggest that MAGeT Brain can approach or exceed the accuracy of multi-atlas label-fusion segmentation (κ = 0.894, 0.815, and 0.895 for the striatum, globus pallidus, and thalamus, respectively). Copyright © 2012 Wiley Periodicals, Inc.

Immediate effects of a distal gait modification during stair descent in individuals with patellofemoral pain.

PubMed

Aliberti, Sandra; Mezêncio, Bruno; Amadio, Alberto Carlos; Serrão, Julio Cerca; Mochizuki, Luis

2018-05-23

Knee pain during stair managing is a common complaint among individuals with PFP and can negatively affect their activities of daily living. Gait modification programs can be used to decrease patellofemoral pain. Immediate effects of a stair descent distal gait modification session that intended to emphasize forefoot landing during stair descent are described in this study. To analyze the immediate effects of a distal gait modification session on lower extremity movements and intensity of pain in women with patellofemoral pain during stair descent. Nonrandomized controlled trial. Sixteen women with patellofemoral pain were allocated into two groups: (1) Gait Modification Group (n = 8); and 2) Control Group (n = 8). The intensity of pain (visual analog scale) and kinematics of knee, ankle, and forefoot (multi-segmental foot model) during stair descent were assessed before and after the intervention. After the gait modification session, there was an increase of forefoot eversion and ankle plantarflexion as well as a decrease of knee flexion. An immediate decrease in patellofemoral pain intensity during stair descent was also observed. The distal gait modification session changed the lower extremity kinetic chain strategy of movement, increasing foot and ankle movement contribution and decreasing knee contribution to the task. An immediate decrease in patellofemoral pain intensity during stair descent was also observed. To emphasize forefoot landing may be a useful intervention to immediately relieve pain in patients with patellofemoral pain during stair descent. Clinical studies are needed to verify the gait modification session effects in medium and long terms.

Sparse intervertebral fence composition for 3D cervical vertebra segmentation

NASA Astrophysics Data System (ADS)

Liu, Xinxin; Yang, Jian; Song, Shuang; Cong, Weijian; Jiao, Peifeng; Song, Hong; Ai, Danni; Jiang, Yurong; Wang, Yongtian

2018-06-01

Statistical shape models are capable of extracting shape prior information, and are usually utilized to assist the task of segmentation of medical images. However, such models require large training datasets in the case of multi-object structures, and it also is difficult to achieve satisfactory results for complex shapes. This study proposed a novel statistical model for cervical vertebra segmentation, called sparse intervertebral fence composition (SiFC), which can reconstruct the boundary between adjacent vertebrae by modeling intervertebral fences. The complex shape of the cervical spine is replaced by a simple intervertebral fence, which considerably reduces the difficulty of cervical segmentation. The final segmentation results are obtained by using a 3D active contour deformation model without shape constraint, which substantially enhances the recognition capability of the proposed method for objects with complex shapes. The proposed segmentation framework is tested on a dataset with CT images from 20 patients. A quantitative comparison against corresponding reference vertebral segmentation yields an overall mean absolute surface distance of 0.70 mm and a dice similarity index of 95.47% for cervical vertebral segmentation. The experimental results show that the SiFC method achieves competitive cervical vertebral segmentation performances, and completely eliminates inter-process overlap.

GLISTRboost: Combining Multimodal MRI Segmentation, Registration, and Biophysical Tumor Growth Modeling with Gradient Boosting Machines for Glioma Segmentation.

PubMed

Bakas, Spyridon; Zeng, Ke; Sotiras, Aristeidis; Rathore, Saima; Akbari, Hamed; Gaonkar, Bilwaj; Rozycki, Martin; Pati, Sarthak; Davatzikos, Christos

2016-01-01

We present an approach for segmenting low- and high-grade gliomas in multimodal magnetic resonance imaging volumes. The proposed approach is based on a hybrid generative-discriminative model. Firstly, a generative approach based on an Expectation-Maximization framework that incorporates a glioma growth model is used to segment the brain scans into tumor, as well as healthy tissue labels. Secondly, a gradient boosting multi-class classification scheme is used to refine tumor labels based on information from multiple patients. Lastly, a probabilistic Bayesian strategy is employed to further refine and finalize the tumor segmentation based on patient-specific intensity statistics from the multiple modalities. We evaluated our approach in 186 cases during the training phase of the BRAin Tumor Segmentation (BRATS) 2015 challenge and report promising results. During the testing phase, the algorithm was additionally evaluated in 53 unseen cases, achieving the best performance among the competing methods.

Fully automatic multi-atlas segmentation of CTA for partial volume correction in cardiac SPECT/CT

NASA Astrophysics Data System (ADS)

Liu, Qingyi; Mohy-ud-Din, Hassan; Boutagy, Nabil E.; Jiang, Mingyan; Ren, Silin; Stendahl, John C.; Sinusas, Albert J.; Liu, Chi

2017-05-01

Anatomical-based partial volume correction (PVC) has been shown to improve image quality and quantitative accuracy in cardiac SPECT/CT. However, this method requires manual segmentation of various organs from contrast-enhanced computed tomography angiography (CTA) data. In order to achieve fully automatic CTA segmentation for clinical translation, we investigated the most common multi-atlas segmentation methods. We also modified the multi-atlas segmentation method by introducing a novel label fusion algorithm for multiple organ segmentation to eliminate overlap and gap voxels. To evaluate our proposed automatic segmentation, eight canine 99mTc-labeled red blood cell SPECT/CT datasets that incorporated PVC were analyzed, using the leave-one-out approach. The Dice similarity coefficient of each organ was computed. Compared to the conventional label fusion method, our proposed label fusion method effectively eliminated gaps and overlaps and improved the CTA segmentation accuracy. The anatomical-based PVC of cardiac SPECT images with automatic multi-atlas segmentation provided consistent image quality and quantitative estimation of intramyocardial blood volume, as compared to those derived using manual segmentation. In conclusion, our proposed automatic multi-atlas segmentation method of CTAs is feasible, practical, and facilitates anatomical-based PVC of cardiac SPECT/CT images.

A proposed framework for consensus-based lung tumour volume auto-segmentation in 4D computed tomography imaging

NASA Astrophysics Data System (ADS)

Martin, Spencer; Brophy, Mark; Palma, David; Louie, Alexander V.; Yu, Edward; Yaremko, Brian; Ahmad, Belal; Barron, John L.; Beauchemin, Steven S.; Rodrigues, George; Gaede, Stewart

2015-02-01

This work aims to propose and validate a framework for tumour volume auto-segmentation based on ground-truth estimates derived from multi-physician input contours to expedite 4D-CT based lung tumour volume delineation. 4D-CT datasets of ten non-small cell lung cancer (NSCLC) patients were manually segmented by 6 physicians. Multi-expert ground truth (GT) estimates were constructed using the STAPLE algorithm for the gross tumour volume (GTV) on all respiratory phases. Next, using a deformable model-based method, multi-expert GT on each individual phase of the 4D-CT dataset was propagated to all other phases providing auto-segmented GTVs and motion encompassing internal gross target volumes (IGTVs) based on GT estimates (STAPLE) from each respiratory phase of the 4D-CT dataset. Accuracy assessment of auto-segmentation employed graph cuts for 3D-shape reconstruction and point-set registration-based analysis yielding volumetric and distance-based measures. STAPLE-based auto-segmented GTV accuracy ranged from (81.51  ±  1.92) to (97.27  ±  0.28)% volumetric overlap of the estimated ground truth. IGTV auto-segmentation showed significantly improved accuracies with reduced variance for all patients ranging from 90.87 to 98.57% volumetric overlap of the ground truth volume. Additional metrics supported these observations with statistical significance. Accuracy of auto-segmentation was shown to be largely independent of selection of the initial propagation phase. IGTV construction based on auto-segmented GTVs within the 4D-CT dataset provided accurate and reliable target volumes compared to manual segmentation-based GT estimates. While inter-/intra-observer effects were largely mitigated, the proposed segmentation workflow is more complex than that of current clinical practice and requires further development.

A proposed framework for consensus-based lung tumour volume auto-segmentation in 4D computed tomography imaging.

PubMed

Martin, Spencer; Brophy, Mark; Palma, David; Louie, Alexander V; Yu, Edward; Yaremko, Brian; Ahmad, Belal; Barron, John L; Beauchemin, Steven S; Rodrigues, George; Gaede, Stewart

2015-02-21

This work aims to propose and validate a framework for tumour volume auto-segmentation based on ground-truth estimates derived from multi-physician input contours to expedite 4D-CT based lung tumour volume delineation. 4D-CT datasets of ten non-small cell lung cancer (NSCLC) patients were manually segmented by 6 physicians. Multi-expert ground truth (GT) estimates were constructed using the STAPLE algorithm for the gross tumour volume (GTV) on all respiratory phases. Next, using a deformable model-based method, multi-expert GT on each individual phase of the 4D-CT dataset was propagated to all other phases providing auto-segmented GTVs and motion encompassing internal gross target volumes (IGTVs) based on GT estimates (STAPLE) from each respiratory phase of the 4D-CT dataset. Accuracy assessment of auto-segmentation employed graph cuts for 3D-shape reconstruction and point-set registration-based analysis yielding volumetric and distance-based measures. STAPLE-based auto-segmented GTV accuracy ranged from (81.51  ±  1.92) to (97.27  ±  0.28)% volumetric overlap of the estimated ground truth. IGTV auto-segmentation showed significantly improved accuracies with reduced variance for all patients ranging from 90.87 to 98.57% volumetric overlap of the ground truth volume. Additional metrics supported these observations with statistical significance. Accuracy of auto-segmentation was shown to be largely independent of selection of the initial propagation phase. IGTV construction based on auto-segmented GTVs within the 4D-CT dataset provided accurate and reliable target volumes compared to manual segmentation-based GT estimates. While inter-/intra-observer effects were largely mitigated, the proposed segmentation workflow is more complex than that of current clinical practice and requires further development.

Model-Based Segmentation of Cortical Regions of Interest for Multi-subject Analysis of fMRI Data

NASA Astrophysics Data System (ADS)

Engel, Karin; Brechmann, Andr'e.; Toennies, Klaus

The high inter-subject variability of human neuroanatomy complicates the analysis of functional imaging data across subjects. We propose a method for the correct segmentation of cortical regions of interest based on the cortical surface. First results on the segmentation of Heschl's gyrus indicate the capability of our approach for correct comparison of functional activations in relation to individual cortical patterns.

Lung lobe modeling and segmentation with individualized surface meshes

NASA Astrophysics Data System (ADS)

Blaffert, Thomas; Barschdorf, Hans; von Berg, Jens; Dries, Sebastian; Franz, Astrid; Klinder, Tobias; Lorenz, Cristian; Renisch, Steffen; Wiemker, Rafael

2008-03-01

An automated segmentation of lung lobes in thoracic CT images is of interest for various diagnostic purposes like the quantification of emphysema or the localization of tumors within the lung. Although the separating lung fissures are visible in modern multi-slice CT-scanners, their contrast in the CT-image often does not separate the lobes completely. This makes it impossible to build a reliable segmentation algorithm without additional information. Our approach uses general anatomical knowledge represented in a geometrical mesh model to construct a robust lobe segmentation, which even gives reasonable estimates of lobe volumes if fissures are not visible at all. The paper describes the generation of the lung model mesh including lobes by an average volume model, its adaptation to individual patient data using a special fissure feature image, and a performance evaluation over a test data set showing an average segmentation accuracy of 1 to 3 mm.

Modelling of subject specific based segmental dynamics of knee joint

NASA Astrophysics Data System (ADS)

Nasir, N. H. M.; Ibrahim, B. S. K. K.; Huq, M. S.; Ahmad, M. K. I.

2017-09-01

This study determines segmental dynamics parameters based on subject specific method. Five hemiplegic patients participated in the study, two men and three women. Their ages ranged from 50 to 60 years, weights from 60 to 70 kg and heights from 145 to 170 cm. Sample group included patients with different side of stroke. The parameters of the segmental dynamics resembling the knee joint functions measured via measurement of Winter and its model generated via the employment Kane's equation of motion. Inertial parameters in the form of the anthropometry can be identified and measured by employing Standard Human Dimension on the subjects who are in hemiplegia condition. The inertial parameters are the location of centre of mass (COM) at the length of the limb segment, inertia moment around the COM and masses of shank and foot to generate accurate motion equations. This investigation has also managed to dig out a few advantages of employing the table of anthropometry in movement biomechanics of Winter's and Kane's equation of motion. A general procedure is presented to yield accurate measurement of estimation for the inertial parameters for the joint of the knee of certain subjects with stroke history.

Superpixel-based segmentation of muscle fibers in multi-channel microscopy.

PubMed

Nguyen, Binh P; Heemskerk, Hans; So, Peter T C; Tucker-Kellogg, Lisa

2016-12-05

Confetti fluorescence and other multi-color genetic labelling strategies are useful for observing stem cell regeneration and for other problems of cell lineage tracing. One difficulty of such strategies is segmenting the cell boundaries, which is a very different problem from segmenting color images from the real world. This paper addresses the difficulties and presents a superpixel-based framework for segmentation of regenerated muscle fibers in mice. We propose to integrate an edge detector into a superpixel algorithm and customize the method for multi-channel images. The enhanced superpixel method outperforms the original and another advanced superpixel algorithm in terms of both boundary recall and under-segmentation error. Our framework was applied to cross-section and lateral section images of regenerated muscle fibers from confetti-fluorescent mice. Compared with "ground-truth" segmentations, our framework yielded median Dice similarity coefficients of 0.92 and higher. Our segmentation framework is flexible and provides very good segmentations of multi-color muscle fibers. We anticipate our methods will be useful for segmenting a variety of tissues in confetti fluorecent mice and in mice with similar multi-color labels.

The free moment is associated with torsion between the pelvis and the foot during gait.

PubMed

Ohkawa, Takahiro; Atomi, Tomoaki; Hasegawa, Katsuya; Atomi, Yoriko

2017-10-01

During walking, the friction between the foot and the ground surface causes a free moment (FM), which influences the torsional stress on the lower extremity. However, few studies have investigated the FM during natural walking. The main aim of this study was to examine the relationship between the FM and the absolute and relative rotation angles of the foot and pelvis. The rotation angles of foot and pelvic were measured in 18 healthy men using a motion capture system. Rotation angles were measured in absolute and relative coordinates as well as in reference to the line connecting the center of pressure (CoP) line under the right and left feet to evaluate the effects of the opposite lower limb on the FM. The absolute and relative rotation angles of the foot and pelvis were entered into forced-entry linear regression models to evaluate the influence on the FM. Only the relative angle of rotation between the foot and pelvis could explain the prediction equations significantly. In the Pearson's product-moment correlation coefficient, the rotation angles of the foot and pelvis defined using the bilateral CoP points had not significantly correlated with FM. No joint rotation movement was correlated with FM. The torsion of the entire lower extremity should be performed principally through hip internal rotation. When evaluating the FM as a torsional stress, focusing on the rotation of the entire lower extremity, rather than on one segment, is beneficial. Copyright © 2017 Elsevier B.V. All rights reserved.

Automatic segmentation of the liver using multi-planar anatomy and deformable surface model in abdominal contrast-enhanced CT images

NASA Astrophysics Data System (ADS)

Jang, Yujin; Hong, Helen; Chung, Jin Wook; Yoon, Young Ho

2012-02-01

We propose an effective technique for the extraction of liver boundary based on multi-planar anatomy and deformable surface model in abdominal contrast-enhanced CT images. Our method is composed of four main steps. First, for extracting an optimal volume circumscribing a liver, lower and side boundaries are defined by positional information of pelvis and rib. An upper boundary is defined by separating the lungs and heart from CT images. Second, for extracting an initial liver volume, optimal liver volume is smoothed by anisotropic diffusion filtering and is segmented using adaptively selected threshold value. Third, for removing neighbor organs from initial liver volume, morphological opening and connected component labeling are applied to multiple planes. Finally, for refining the liver boundaries, deformable surface model is applied to a posterior liver surface and missing left robe in previous step. Then, probability summation map is generated by calculating regional information of the segmented liver in coronal plane, which is used for restoring the inaccurate liver boundaries. Experimental results show that our segmentation method can accurately extract liver boundaries without leakage to neighbor organs in spite of various liver shape and ambiguous boundary.

Segmentation of multiple heart cavities in 3-D transesophageal ultrasound images.

PubMed

Haak, Alexander; Vegas-Sánchez-Ferrero, Gonzalo; Mulder, Harriët W; Ren, Ben; Kirişli, Hortense A; Metz, Coert; van Burken, Gerard; van Stralen, Marijn; Pluim, Josien P W; van der Steen, Antonius F W; van Walsum, Theo; Bosch, Johannes G

2015-06-01

Three-dimensional transesophageal echocardiography (TEE) is an excellent modality for real-time visualization of the heart and monitoring of interventions. To improve the usability of 3-D TEE for intervention monitoring and catheter guidance, automated segmentation is desired. However, 3-D TEE segmentation is still a challenging task due to the complex anatomy with multiple cavities, the limited TEE field of view, and typical ultrasound artifacts. We propose to segment all cavities within the TEE view with a multi-cavity active shape model (ASM) in conjunction with a tissue/blood classification based on a gamma mixture model (GMM). 3-D TEE image data of twenty patients were acquired with a Philips X7-2t matrix TEE probe. Tissue probability maps were estimated by a two-class (blood/tissue) GMM. A statistical shape model containing the left ventricle, right ventricle, left atrium, right atrium, and aorta was derived from computed tomography angiography (CTA) segmentations by principal component analysis. ASMs of the whole heart and individual cavities were generated and consecutively fitted to tissue probability maps. First, an average whole-heart model was aligned with the 3-D TEE based on three manually indicated anatomical landmarks. Second, pose and shape of the whole-heart ASM were fitted by a weighted update scheme excluding parts outside of the image sector. Third, pose and shape of ASM for individual heart cavities were initialized by the previous whole heart ASM and updated in a regularized manner to fit the tissue probability maps. The ASM segmentations were validated against manual outlines by two observers and CTA derived segmentations. Dice coefficients and point-to-surface distances were used to determine segmentation accuracy. ASM segmentations were successful in 19 of 20 cases. The median Dice coefficient for all successful segmentations versus the average observer ranged from 90% to 71% compared with an inter-observer range of 95% to 84%. The agreement against the CTA segmentations was slightly lower with a median Dice coefficient between 85% and 57%. In this work, we successfully showed the accuracy and robustness of the proposed multi-cavity segmentation scheme. This is a promising development for intraoperative procedure guidance, e.g., in cardiac electrophysiology.

Automated bone segmentation from large field of view 3D MR images of the hip joint

NASA Astrophysics Data System (ADS)

Xia, Ying; Fripp, Jurgen; Chandra, Shekhar S.; Schwarz, Raphael; Engstrom, Craig; Crozier, Stuart

2013-10-01

Accurate bone segmentation in the hip joint region from magnetic resonance (MR) images can provide quantitative data for examining pathoanatomical conditions such as femoroacetabular impingement through to varying stages of osteoarthritis to monitor bone and associated cartilage morphometry. We evaluate two state-of-the-art methods (multi-atlas and active shape model (ASM) approaches) on bilateral MR images for automatic 3D bone segmentation in the hip region (proximal femur and innominate bone). Bilateral MR images of the hip joints were acquired at 3T from 30 volunteers. Image sequences included water-excitation dual echo stead state (FOV 38.6 × 24.1 cm, matrix 576 × 360, thickness 0.61 mm) in all subjects and multi-echo data image combination (FOV 37.6 × 23.5 cm, matrix 576 × 360, thickness 0.70 mm) for a subset of eight subjects. Following manual segmentation of femoral (head-neck, proximal-shaft) and innominate (ilium+ischium+pubis) bone, automated bone segmentation proceeded via two approaches: (1) multi-atlas segmentation incorporating non-rigid registration and (2) an advanced ASM-based scheme. Mean inter- and intra-rater reliability Dice's similarity coefficients (DSC) for manual segmentation of femoral and innominate bone were (0.970, 0.963) and (0.971, 0.965). Compared with manual data, mean DSC values for femoral and innominate bone volumes using automated multi-atlas and ASM-based methods were (0.950, 0.922) and (0.946, 0.917), respectively. Both approaches delivered accurate (high DSC values) segmentation results; notably, ASM data were generated in substantially less computational time (12 min versus 10 h). Both automated algorithms provided accurate 3D bone volumetric descriptions for MR-based measures in the hip region. The highly computational efficient ASM-based approach is more likely suitable for future clinical applications such as extracting bone-cartilage interfaces for potential cartilage segmentation.

Automated bone segmentation from large field of view 3D MR images of the hip joint.

PubMed

Xia, Ying; Fripp, Jurgen; Chandra, Shekhar S; Schwarz, Raphael; Engstrom, Craig; Crozier, Stuart

2013-10-21

Accurate bone segmentation in the hip joint region from magnetic resonance (MR) images can provide quantitative data for examining pathoanatomical conditions such as femoroacetabular impingement through to varying stages of osteoarthritis to monitor bone and associated cartilage morphometry. We evaluate two state-of-the-art methods (multi-atlas and active shape model (ASM) approaches) on bilateral MR images for automatic 3D bone segmentation in the hip region (proximal femur and innominate bone). Bilateral MR images of the hip joints were acquired at 3T from 30 volunteers. Image sequences included water-excitation dual echo stead state (FOV 38.6 × 24.1 cm, matrix 576 × 360, thickness 0.61 mm) in all subjects and multi-echo data image combination (FOV 37.6 × 23.5 cm, matrix 576 × 360, thickness 0.70 mm) for a subset of eight subjects. Following manual segmentation of femoral (head-neck, proximal-shaft) and innominate (ilium+ischium+pubis) bone, automated bone segmentation proceeded via two approaches: (1) multi-atlas segmentation incorporating non-rigid registration and (2) an advanced ASM-based scheme. Mean inter- and intra-rater reliability Dice's similarity coefficients (DSC) for manual segmentation of femoral and innominate bone were (0.970, 0.963) and (0.971, 0.965). Compared with manual data, mean DSC values for femoral and innominate bone volumes using automated multi-atlas and ASM-based methods were (0.950, 0.922) and (0.946, 0.917), respectively. Both approaches delivered accurate (high DSC values) segmentation results; notably, ASM data were generated in substantially less computational time (12 min versus 10 h). Both automated algorithms provided accurate 3D bone volumetric descriptions for MR-based measures in the hip region. The highly computational efficient ASM-based approach is more likely suitable for future clinical applications such as extracting bone-cartilage interfaces for potential cartilage segmentation.

Evaluation of prostate segmentation algorithms for MRI: the PROMISE12 challenge

PubMed Central

Litjens, Geert; Toth, Robert; van de Ven, Wendy; Hoeks, Caroline; Kerkstra, Sjoerd; van Ginneken, Bram; Vincent, Graham; Guillard, Gwenael; Birbeck, Neil; Zhang, Jindang; Strand, Robin; Malmberg, Filip; Ou, Yangming; Davatzikos, Christos; Kirschner, Matthias; Jung, Florian; Yuan, Jing; Qiu, Wu; Gao, Qinquan; Edwards, Philip “Eddie”; Maan, Bianca; van der Heijden, Ferdinand; Ghose, Soumya; Mitra, Jhimli; Dowling, Jason; Barratt, Dean; Huisman, Henkjan; Madabhushi, Anant

2014-01-01

Prostate MRI image segmentation has been an area of intense research due to the increased use of MRI as a modality for the clinical workup of prostate cancer. Segmentation is useful for various tasks, e.g. to accurately localize prostate boundaries for radiotherapy or to initialize multi-modal registration algorithms. In the past, it has been difficult for research groups to evaluate prostate segmentation algorithms on multi-center, multi-vendor and multi-protocol data. Especially because we are dealing with MR images, image appearance, resolution and the presence of artifacts are affected by differences in scanners and/or protocols, which in turn can have a large influence on algorithm accuracy. The Prostate MR Image Segmentation (PROMISE12) challenge was setup to allow a fair and meaningful comparison of segmentation methods on the basis of performance and robustness. In this work we will discuss the initial results of the online PROMISE12 challenge, and the results obtained in the live challenge workshop hosted by the MICCAI2012 conference. In the challenge, 100 prostate MR cases from 4 different centers were included, with differences in scanner manufacturer, field strength and protocol. A total of 11 teams from academic research groups and industry participated. Algorithms showed a wide variety in methods and implementation, including active appearance models, atlas registration and level sets. Evaluation was performed using boundary and volume based metrics which were combined into a single score relating the metrics to human expert performance. The winners of the challenge where the algorithms by teams Imorphics and ScrAutoProstate, with scores of 85.72 and 84.29 overall. Both algorithms where significantly better than all other algorithms in the challenge (p < 0.05) and had an efficient implementation with a run time of 8 minutes and 3 second per case respectively. Overall, active appearance model based approaches seemed to outperform other approaches like multi-atlas registration, both on accuracy and computation time. Although average algorithm performance was good to excellent and the Imorphics algorithm outperformed the second observer on average, we showed that algorithm combination might lead to further improvement, indicating that optimal performance for prostate segmentation is not yet obtained. All results are available online at http://promise12.grand-challenge.org/. PMID:24418598

Multi-functional foot use during running in the zebra-tailed lizard (Callisaurus draconoides).

PubMed

Li, Chen; Hsieh, S Tonia; Goldman, Daniel I

2012-09-15

A diversity of animals that run on solid, level, flat, non-slip surfaces appear to bounce on their legs; elastic elements in the limbs can store and return energy during each step. The mechanics and energetics of running in natural terrain, particularly on surfaces that can yield and flow under stress, is less understood. The zebra-tailed lizard (Callisaurus draconoides), a small desert generalist with a large, elongate, tendinous hind foot, runs rapidly across a variety of natural substrates. We use high-speed video to obtain detailed three-dimensional running kinematics on solid and granular surfaces to reveal how leg, foot and substrate mechanics contribute to its high locomotor performance. Running at ~10 body lengths s(-1) (~1 m s(-1)), the center of mass oscillates like a spring-mass system on both substrates, with only 15% reduction in stride length on the granular surface. On the solid surface, a strut-spring model of the hind limb reveals that the hind foot saves ~40% of the mechanical work needed per step, significant for the lizard's small size. On the granular surface, a penetration force model and hypothesized subsurface foot rotation indicates that the hind foot paddles through fluidized granular medium, and that the energy lost per step during irreversible deformation of the substrate does not differ from the reduction in the mechanical energy of the center of mass. The upper hind leg muscles must perform three times as much mechanical work on the granular surface as on the solid surface to compensate for the greater energy lost within the foot and to the substrate.

Fast automated segmentation of multiple objects via spatially weighted shape learning

NASA Astrophysics Data System (ADS)

Chandra, Shekhar S.; Dowling, Jason A.; Greer, Peter B.; Martin, Jarad; Wratten, Chris; Pichler, Peter; Fripp, Jurgen; Crozier, Stuart

2016-11-01

Active shape models (ASMs) have proved successful in automatic segmentation by using shape and appearance priors in a number of areas such as prostate segmentation, where accurate contouring is important in treatment planning for prostate cancer. The ASM approach however, is heavily reliant on a good initialisation for achieving high segmentation quality. This initialisation often requires algorithms with high computational complexity, such as three dimensional (3D) image registration. In this work, we present a fast, self-initialised ASM approach that simultaneously fits multiple objects hierarchically controlled by spatially weighted shape learning. Prominent objects are targeted initially and spatial weights are progressively adjusted so that the next (more difficult, less visible) object is simultaneously initialised using a series of weighted shape models. The scheme was validated and compared to a multi-atlas approach on 3D magnetic resonance (MR) images of 38 cancer patients and had the same (mean, median, inter-rater) Dice’s similarity coefficients of (0.79, 0.81, 0.85), while having no registration error and a computational time of 12-15 min, nearly an order of magnitude faster than the multi-atlas approach.

Fast automated segmentation of multiple objects via spatially weighted shape learning.

PubMed

Chandra, Shekhar S; Dowling, Jason A; Greer, Peter B; Martin, Jarad; Wratten, Chris; Pichler, Peter; Fripp, Jurgen; Crozier, Stuart

2016-11-21

Active shape models (ASMs) have proved successful in automatic segmentation by using shape and appearance priors in a number of areas such as prostate segmentation, where accurate contouring is important in treatment planning for prostate cancer. The ASM approach however, is heavily reliant on a good initialisation for achieving high segmentation quality. This initialisation often requires algorithms with high computational complexity, such as three dimensional (3D) image registration. In this work, we present a fast, self-initialised ASM approach that simultaneously fits multiple objects hierarchically controlled by spatially weighted shape learning. Prominent objects are targeted initially and spatial weights are progressively adjusted so that the next (more difficult, less visible) object is simultaneously initialised using a series of weighted shape models. The scheme was validated and compared to a multi-atlas approach on 3D magnetic resonance (MR) images of 38 cancer patients and had the same (mean, median, inter-rater) Dice's similarity coefficients of (0.79, 0.81, 0.85), while having no registration error and a computational time of 12-15 min, nearly an order of magnitude faster than the multi-atlas approach.

Use of multi-opening burrow systems by black-footed ferrets

USGS Publications Warehouse

Biggins, Dean E.

2012-01-01

Multi-opening burrow systems constructed by prairie dogs (Cynomys) ostensibly provide escape routes when prairie dogs are pursued by predators capable of entering the burrows, such as black-footed ferrets (Mustela nigripes), or by predators that can rapidly dig into the tunnels, such as American badgers (Taxidea taxus). Because badgers also prey on ferrets, ferrets might similarly benefit from multi-opening burrow systems. Using an air blower, white-tailed prairie dog (Cynomys leucurus) burrow openings were tested for connectivity on plots occupied by black-footed ferrets and on randomly selected plots in Wyoming. Significantly more connected openings were found on ferret-occupied plots than on random plots. Connected openings might be due to modifications by ferrets in response to plugging by prairie dogs, due to selection by ferrets for complex systems with multiple openings that are already unobstructed, or simply due to ferrets lingering at kill sites that were multi-opening systems selected by their prairie dog prey.

Pre-impact lower extremity posture and brake pedal force predict foot and ankle forces during an automobile collision.

PubMed

Hardin, E C; Su, A; van den Bogert, A J

2004-12-01

The purpose of this study was to determine how a driver's foot and ankle forces during a frontal vehicle collision depend on initial lower extremity posture and brake pedal force. A 2D musculoskeletal model with seven segments and six right-side muscle groups was used. A simulation of a three-second braking task found 3647 sets of muscle activation levels that resulted in stable braking postures with realistic pedal force. These activation patterns were then used in impact simulations where vehicle deceleration was applied and driver movements and foot and ankle forces were simulated. Peak rearfoot ground reaction force (F(RF)), peak Achilles tendon force (FAT), peak calcaneal force (F(CF)) and peak ankle joint force (F(AJ)) were calculated. Peak forces during the impact simulation were 476 +/- 687 N (F(RF)), 2934 +/- 944 N (F(CF)) and 2449 +/- 918 N (F(AJ)). Many simulations resulted in force levels that could cause fractures. Multivariate quadratic regression determined that the pre-impact brake pedal force (PF), knee angle (KA) and heel distance (HD) explained 72% of the variance in peak FRF, 62% in peak F(CF) and 73% in peak F(AJ). Foot and ankle forces during a collision depend on initial posture and pedal force. Braking postures with increased knee flexion, while keeping the seat position fixed, are associated with higher foot and ankle forces during a collision.

Surface-region context in optimal multi-object graph-based segmentation: robust delineation of pulmonary tumors.

PubMed

Song, Qi; Chen, Mingqing; Bai, Junjie; Sonka, Milan; Wu, Xiaodong

2011-01-01

Multi-object segmentation with mutual interaction is a challenging task in medical image analysis. We report a novel solution to a segmentation problem, in which target objects of arbitrary shape mutually interact with terrain-like surfaces, which widely exists in the medical imaging field. The approach incorporates context information used during simultaneous segmentation of multiple objects. The object-surface interaction information is encoded by adding weighted inter-graph arcs to our graph model. A globally optimal solution is achieved by solving a single maximum flow problem in a low-order polynomial time. The performance of the method was evaluated in robust delineation of lung tumors in megavoltage cone-beam CT images in comparison with an expert-defined independent standard. The evaluation showed that our method generated highly accurate tumor segmentations. Compared with the conventional graph-cut method, our new approach provided significantly better results (p < 0.001). The Dice coefficient obtained by the conventional graph-cut approach (0.76 +/- 0.10) was improved to 0.84 +/- 0.05 when employing our new method for pulmonary tumor segmentation.

A fuzzy feature fusion method for auto-segmentation of gliomas with multi-modality diffusion and perfusion magnetic resonance images in radiotherapy.

PubMed

Guo, Lu; Wang, Ping; Sun, Ranran; Yang, Chengwen; Zhang, Ning; Guo, Yu; Feng, Yuanming

2018-02-19

The diffusion and perfusion magnetic resonance (MR) images can provide functional information about tumour and enable more sensitive detection of the tumour extent. We aimed to develop a fuzzy feature fusion method for auto-segmentation of gliomas in radiotherapy planning using multi-parametric functional MR images including apparent diffusion coefficient (ADC), fractional anisotropy (FA) and relative cerebral blood volume (rCBV). For each functional modality, one histogram-based fuzzy model was created to transform image volume into a fuzzy feature space. Based on the fuzzy fusion result of the three fuzzy feature spaces, regions with high possibility belonging to tumour were generated automatically. The auto-segmentations of tumour in structural MR images were added in final auto-segmented gross tumour volume (GTV). For evaluation, one radiation oncologist delineated GTVs for nine patients with all modalities. Comparisons between manually delineated and auto-segmented GTVs showed that, the mean volume difference was 8.69% (±5.62%); the mean Dice's similarity coefficient (DSC) was 0.88 (±0.02); the mean sensitivity and specificity of auto-segmentation was 0.87 (±0.04) and 0.98 (±0.01) respectively. High accuracy and efficiency can be achieved with the new method, which shows potential of utilizing functional multi-parametric MR images for target definition in precision radiation treatment planning for patients with gliomas.

Self-correcting multi-atlas segmentation

NASA Astrophysics Data System (ADS)

Gao, Yi; Wilford, Andrew; Guo, Liang

2016-03-01

In multi-atlas segmentation, one typically registers several atlases to the new image, and their respective segmented label images are transformed and fused to form the final segmentation. After each registration, the quality of the registration is reflected by the single global value: the final registration cost. Ideally, if the quality of the registration can be evaluated at each point, independent of the registration process, which also provides a direction in which the deformation can further be improved, the overall segmentation performance can be improved. We propose such a self-correcting multi-atlas segmentation method. The method is applied on hippocampus segmentation from brain images and statistically significantly improvement is observed.

Multi-scale image segmentation and numerical modeling in carbonate rocks

NASA Astrophysics Data System (ADS)

Alves, G. C.; Vanorio, T.

2016-12-01

Numerical methods based on computational simulations can be an important tool in estimating physical properties of rocks. These can complement experimental results, especially when time constraints and sample availability are a problem. However, computational models created at different scales can yield conflicting results with respect to the physical laboratory. This problem is exacerbated in carbonate rocks due to their heterogeneity at all scales. We developed a multi-scale approach performing segmentation of the rock images and numerical modeling across several scales, accounting for those heterogeneities. As a first step, we measured the porosity and the elastic properties of a group of carbonate samples with varying micrite content. Then, samples were imaged by Scanning Electron Microscope (SEM) as well as optical microscope at different magnifications. We applied three different image segmentation techniques to create numerical models from the SEM images and performed numerical simulations of the elastic wave-equation. Our results show that a multi-scale approach can efficiently account for micro-porosities in tight micrite-supported samples, yielding acoustic velocities comparable to those obtained experimentally. Nevertheless, in high-porosity samples characterized by larger grain/micrite ratio, results show that SEM scale images tend to overestimate velocities, mostly due to their inability to capture macro- and/or intragranular- porosity. This suggests that, for high-porosity carbonate samples, optical microscope images would be more suited for numerical simulations.

An Automatic Assessment System of Diabetic Foot Ulcers Based on Wound Area Determination, Color Segmentation, and Healing Score Evaluation.

PubMed

Wang, Lei; Pedersen, Peder C; Strong, Diane M; Tulu, Bengisu; Agu, Emmanuel; Ignotz, Ron; He, Qian

2015-08-07

For individuals with type 2 diabetes, foot ulcers represent a significant health issue. The aim of this study is to design and evaluate a wound assessment system to help wound clinics assess patients with foot ulcers in a way that complements their current visual examination and manual measurements of their foot ulcers. The physical components of the system consist of an image capture box, a smartphone for wound image capture and a laptop for analyzing the wound image. The wound image assessment algorithms calculate the overall wound area, color segmented wound areas, and a healing score, to provide a quantitative assessment of the wound healing status both for a single wound image and comparisons of subsequent images to an initial wound image. The system was evaluated by assessing foot ulcers for 12 patients in the Wound Clinic at University of Massachusetts Medical School. As performance measures, the Matthews correlation coefficient (MCC) value for the wound area determination algorithm tested on 32 foot ulcer images was .68. The clinical validity of our healing score algorithm relative to the experienced clinicians was measured by Krippendorff's alpha coefficient (KAC) and ranged from .42 to .81. Our system provides a promising real-time method for wound assessment based on image analysis. Clinical comparisons indicate that the optimized mean-shift-based algorithm is well suited for wound area determination. Clinical evaluation of our healing score algorithm shows its potential to provide clinicians with a quantitative method for evaluating wound healing status. © 2015 Diabetes Technology Society.

Spinal motor outputs during step-to-step transitions of diverse human gaits.

PubMed

La Scaleia, Valentina; Ivanenko, Yuri P; Zelik, Karl E; Lacquaniti, Francesco

2014-01-01

Aspects of human motor control can be inferred from the coordination of muscles during movement. For instance, by combining multimuscle electromyographic (EMG) recordings with human neuroanatomy, it is possible to estimate alpha-motoneuron (MN) pool activations along the spinal cord. It has previously been shown that the spinal motor output fluctuates with the body's center-of-mass motion, with bursts of activity around foot-strike and foot lift-off during walking. However, it is not known whether these MN bursts are generalizable to other ambulation tasks, nor is it clear if the spatial locus of the activity (along the rostrocaudal axis of the spinal cord) is fixed or variable. Here we sought to address these questions by investigating the spatiotemporal characteristics of the spinal motor output during various tasks: walking forward, backward, tiptoe and uphill. We reconstructed spinal maps from 26 leg muscle EMGs, including some intrinsic foot muscles. We discovered that the various walking tasks shared qualitative similarities in their temporal spinal activation profiles, exhibiting peaks around foot-strike and foot-lift. However, we also observed differences in the segmental level and intensity of spinal activations, particularly following foot-strike. For example, forward level-ground walking exhibited a mean motor output roughly 2 times lower than the other gaits. Finally, we found that the reconstruction of the spinal motor output from multimuscle EMG recordings was relatively insensitive to the subset of muscles analyzed. In summary, our results suggested temporal similarities, but spatial differences in the segmental spinal motor outputs during the step-to-step transitions of disparate walking behaviors.

Morphometrics and inertial properties in the body segments of chimpanzees (Pan troglodytes)

PubMed Central

Schoonaert, Kirsten; D’Août, Kristiaan; Aerts, Peter

2007-01-01

Inertial characteristics and dimensions of the body and body segments form an integral part of a biomechanical analysis of motion. In primate studies, however, segment inertial parameters of non-human hominoids are scarce and often obtained using varying techniques. Therefore, the principal aim of this study was to expand the existing chimpanzee inertial property data set using a non-invasive measuring technique. We also considered age- and sex-related differences within our sample. By means of a geometric model based on Crompton et al. (1996); Am J Phys Anthropol 99, 547–570) we generated inertial properties using external segment length and diameter measurements of 53 anaesthetized chimpanzees (Pan troglodytes). We report absolute inertial parameters for immature and mature subjects and for males and females separately. Proportional data were computed to allow the comparison between age classes and sex classes. In addition, we calculated whole limb inertial properties and we discuss their potential biomechanical consequences. We found no significant differences between the age classes in the proportional data except for hand and foot measures where juveniles exhibit relatively longer and heavier distal segments than adults. Furthermore, most sex-related differences can be directly attributed to the higher absolute segment masses in male chimpanzees resulting in higher moments of inertia. Additionally, males tend to have longer upper limbs than females. However, regarding proportional data we discuss the general inertial properties of the chimpanzee. The described segment inertial parameters of males and females, and of the two age classes, represent a valuable data set ready for use in a range of biomechanical locomotor models. These models offer great potential for improving our understanding of early hominin locomotor patterns. PMID:17451529

Calcaneocuboid joint subluxation after calcaneal lengthening for planovalgus foot deformity in children with cerebral palsy.

PubMed

Adams, Samuel B; Simpson, Andrew W; Pugh, Linda I; Stasikelis, Peter J

2009-03-01

Calcaneal lengthening is a common procedure for the treatment of symptomatic planovalgus deformity in children with cerebral palsy. Stabilization of the calcaneocuboid joint to prevent subluxation at the time of lengthening has been described. The purpose of this study was to evaluate the magnitude of calcaneocuboid joint subluxation and associated degenerative changes in patients with cerebral palsy who underwent calcaneal lengthening for planovalgus foot deformity with and without stabilization of the calcaneocuboid joint. We conducted a retrospective review of children with cerebral palsy who underwent lateral column lengthening through the calcaneus. For the purposes of statistical analysis, the feet were divided into 2 groups: stabilized (those that received Steinmann pin stabilization at the time of lengthening) and nonstabilized (those feet that did not receive Steinmann pin stabilization). Initial, intraoperative, and most recent follow-up radiographs were reviewed for segmental foot analysis of planovalgus deformity, calcaneocuboid joint subluxation, and osteoarthritic changes. A minimum of 3-year follow-up was required. Sixty-one feet were included in this study; 28 feet in the stabilized group and 33 in the nonstabilized group. Radiographic assessment of segmental foot analysis demonstrated significant improvement with regard to planovalgus deformity (P<0.05, 5 measurements). Calcaneocuboid joint subluxation occurred in 24 feet in the stabilized group and 29 feet in the nonstabilized group (P=0.5269). At final follow-up, the magnitude of subluxation was not significantly different between the groups (P=0.076). There was no difference in the incidence of osteoarthritic changes at the calcaneocuboid joint between the groups (P=0.2856). Lateral column lengthening through the calcaneus, for planovalgus foot deformity, significantly improved the segmental alignment of the foot with respect to radiographic assessment. Stabilization of the calcaneocuboid joint at the time of lateral column lengthening through the calcaneus did not significantly reduce the incidence or magnitude of subluxation when compared with nonstabilized lengthening. In addition, stabilization did not have an effect on the development of radiographic osteoarthritic changes at the calcaneocuboid joint. Level III, retrospective comparative study.

A Bayesian Approach for Image Segmentation with Shape Priors

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

Chang, Hang; Yang, Qing; Parvin, Bahram

2008-06-20

Color and texture have been widely used in image segmentation; however, their performance is often hindered by scene ambiguities, overlapping objects, or missingparts. In this paper, we propose an interactive image segmentation approach with shape prior models within a Bayesian framework. Interactive features, through mouse strokes, reduce ambiguities, and the incorporation of shape priors enhances quality of the segmentation where color and/or texture are not solely adequate. The novelties of our approach are in (i) formulating the segmentation problem in a well-de?ned Bayesian framework with multiple shape priors, (ii) ef?ciently estimating parameters of the Bayesian model, and (iii) multi-object segmentationmore » through user-speci?ed priors. We demonstrate the effectiveness of our method on a set of natural and synthetic images.« less

Segmentation of knee cartilage by using a hierarchical active shape model based on multi-resolution transforms in magnetic resonance images

NASA Astrophysics Data System (ADS)

León, Madeleine; Escalante-Ramirez, Boris

2013-11-01

Knee osteoarthritis (OA) is characterized by the morphological degeneration of cartilage. Efficient segmentation of cartilage is important for cartilage damage diagnosis and to support therapeutic responses. We present a method for knee cartilage segmentation in magnetic resonance images (MRI). Our method incorporates the Hermite Transform to obtain a hierarchical decomposition of contours which describe knee cartilage shapes. Then, we compute a statistical model of the contour of interest from a set of training images. Thereby, our Hierarchical Active Shape Model (HASM) captures a large range of shape variability even from a small group of training samples, improving segmentation accuracy. The method was trained with a training set of 16- MRI of knee and tested with leave-one-out method.

Semantic Image Segmentation with Contextual Hierarchical Models.

PubMed

Seyedhosseini, Mojtaba; Tasdizen, Tolga

2016-05-01

Semantic segmentation is the problem of assigning an object label to each pixel. It unifies the image segmentation and object recognition problems. The importance of using contextual information in semantic segmentation frameworks has been widely realized in the field. We propose a contextual framework, called contextual hierarchical model (CHM), which learns contextual information in a hierarchical framework for semantic segmentation. At each level of the hierarchy, a classifier is trained based on downsampled input images and outputs of previous levels. Our model then incorporates the resulting multi-resolution contextual information into a classifier to segment the input image at original resolution. This training strategy allows for optimization of a joint posterior probability at multiple resolutions through the hierarchy. Contextual hierarchical model is purely based on the input image patches and does not make use of any fragments or shape examples. Hence, it is applicable to a variety of problems such as object segmentation and edge detection. We demonstrate that CHM performs at par with state-of-the-art on Stanford background and Weizmann horse datasets. It also outperforms state-of-the-art edge detection methods on NYU depth dataset and achieves state-of-the-art on Berkeley segmentation dataset (BSDS 500).

Intelligent multi-spectral IR image segmentation

NASA Astrophysics Data System (ADS)

Lu, Thomas; Luong, Andrew; Heim, Stephen; Patel, Maharshi; Chen, Kang; Chao, Tien-Hsin; Chow, Edward; Torres, Gilbert

2017-05-01

This article presents a neural network based multi-spectral image segmentation method. A neural network is trained on the selected features of both the objects and background in the longwave (LW) Infrared (IR) images. Multiple iterations of training are performed until the accuracy of the segmentation reaches satisfactory level. The segmentation boundary of the LW image is used to segment the midwave (MW) and shortwave (SW) IR images. A second neural network detects the local discontinuities and refines the accuracy of the local boundaries. This article compares the neural network based segmentation method to the Wavelet-threshold and Grab-Cut methods. Test results have shown increased accuracy and robustness of this segmentation scheme for multi-spectral IR images.

A tree canopy height delineation method based on Morphological Reconstruction—Open Crown Decomposition

NASA Astrophysics Data System (ADS)

Liu, Q.; Jing, L.; Li, Y.; Tang, Y.; Li, H.; Lin, Q.

2016-04-01

For the purpose of forest management, high resolution LIDAR and optical remote sensing imageries are used for treetop detection, tree crown delineation, and classification. The purpose of this study is to develop a self-adjusted dominant scales calculation method and a new crown horizontal cutting method of tree canopy height model (CHM) to detect and delineate tree crowns from LIDAR, under the hypothesis that a treetop is radiometric or altitudinal maximum and tree crowns consist of multi-scale branches. The major concept of the method is to develop an automatic selecting strategy of feature scale on CHM, and a multi-scale morphological reconstruction-open crown decomposition (MRCD) to get morphological multi-scale features of CHM by: cutting CHM from treetop to the ground; analysing and refining the dominant multiple scales with differential horizontal profiles to get treetops; segmenting LiDAR CHM using watershed a segmentation approach marked with MRCD treetops. This method has solved the problems of false detection of CHM side-surface extracted by the traditional morphological opening canopy segment (MOCS) method. The novel MRCD delineates more accurate and quantitative multi-scale features of CHM, and enables more accurate detection and segmentation of treetops and crown. Besides, the MRCD method can also be extended to high optical remote sensing tree crown extraction. In an experiment on aerial LiDAR CHM of a forest of multi-scale tree crowns, the proposed method yielded high-quality tree crown maps.

Multi-atlas segmentation enables robust multi-contrast MRI spleen segmentation for splenomegaly

NASA Astrophysics Data System (ADS)

Huo, Yuankai; Liu, Jiaqi; Xu, Zhoubing; Harrigan, Robert L.; Assad, Albert; Abramson, Richard G.; Landman, Bennett A.

2017-02-01

Non-invasive spleen volume estimation is essential in detecting splenomegaly. Magnetic resonance imaging (MRI) has been used to facilitate splenomegaly diagnosis in vivo. However, achieving accurate spleen volume estimation from MR images is challenging given the great inter-subject variance of human abdomens and wide variety of clinical images/modalities. Multi-atlas segmentation has been shown to be a promising approach to handle heterogeneous data and difficult anatomical scenarios. In this paper, we propose to use multi-atlas segmentation frameworks for MRI spleen segmentation for splenomegaly. To the best of our knowledge, this is the first work that integrates multi-atlas segmentation for splenomegaly as seen on MRI. To address the particular concerns of spleen MRI, automated and novel semi-automated atlas selection approaches are introduced. The automated approach interactively selects a subset of atlases using selective and iterative method for performance level estimation (SIMPLE) approach. To further control the outliers, semi-automated craniocaudal length based SIMPLE atlas selection (L-SIMPLE) is proposed to introduce a spatial prior in a fashion to guide the iterative atlas selection. A dataset from a clinical trial containing 55 MRI volumes (28 T1 weighted and 27 T2 weighted) was used to evaluate different methods. Both automated and semi-automated methods achieved median DSC > 0.9. The outliers were alleviated by the L-SIMPLE (≍1 min manual efforts per scan), which achieved 0.9713 Pearson correlation compared with the manual segmentation. The results demonstrated that the multi-atlas segmentation is able to achieve accurate spleen segmentation from the multi-contrast splenomegaly MRI scans.

Multi-atlas Segmentation Enables Robust Multi-contrast MRI Spleen Segmentation for Splenomegaly.

PubMed

Huo, Yuankai; Liu, Jiaqi; Xu, Zhoubing; Harrigan, Robert L; Assad, Albert; Abramson, Richard G; Landman, Bennett A

2017-02-11

Non-invasive spleen volume estimation is essential in detecting splenomegaly. Magnetic resonance imaging (MRI) has been used to facilitate splenomegaly diagnosis in vivo. However, achieving accurate spleen volume estimation from MR images is challenging given the great inter-subject variance of human abdomens and wide variety of clinical images/modalities. Multi-atlas segmentation has been shown to be a promising approach to handle heterogeneous data and difficult anatomical scenarios. In this paper, we propose to use multi-atlas segmentation frameworks for MRI spleen segmentation for splenomegaly. To the best of our knowledge, this is the first work that integrates multi-atlas segmentation for splenomegaly as seen on MRI. To address the particular concerns of spleen MRI, automated and novel semi-automated atlas selection approaches are introduced. The automated approach interactively selects a subset of atlases using selective and iterative method for performance level estimation (SIMPLE) approach. To further control the outliers, semi-automated craniocaudal length based SIMPLE atlas selection (L-SIMPLE) is proposed to introduce a spatial prior in a fashion to guide the iterative atlas selection. A dataset from a clinical trial containing 55 MRI volumes (28 T1 weighted and 27 T2 weighted) was used to evaluate different methods. Both automated and semi-automated methods achieved median DSC > 0.9. The outliers were alleviated by the L-SIMPLE (≈1 min manual efforts per scan), which achieved 0.9713 Pearson correlation compared with the manual segmentation. The results demonstrated that the multi-atlas segmentation is able to achieve accurate spleen segmentation from the multi-contrast splenomegaly MRI scans.

A Real Time System for Multi-Sensor Image Analysis through Pyramidal Segmentation

DTIC Science & Technology

1992-01-30

A Real Time Syte for M~ulti- sensor Image Analysis S. E I0 through Pyramidal Segmentation/ / c •) L. Rudin, S. Osher, G. Koepfler, J.9. Morel 7. ytu...experiments with reconnaissance photography, multi- sensor satellite imagery, medical CT and MRI multi-band data have shown a great practi- cal potential...C ,SF _/ -- / WSM iS-I-0-d41-40450 $tltwt, kw" I (nor.- . Z-97- A real-time system for multi- sensor image analysis through pyramidal segmentation

Saturn Apollo Program

NASA Image and Video Library

1966-09-15

This vintage photograph shows the 138-foot long first stage of the Saturn V being lowered to the ground following a successful static test firing at Marshall Space flight Center's S-1C test stand. The firing provided NASA engineers information on the booster's systems. The towering 363-foot Saturn V was a multi-stage, multi-engine launch vehicle standing taller than the Statue of Liberty. Altogether, the Saturn V engines produced as much power as 85 Hoover Dams.

Multi-Atlas Based Segmentation of Brainstem Nuclei from MR Images by Deep Hyper-Graph Learning.

PubMed

Dong, Pei; Guo, Yangrong; Gao, Yue; Liang, Peipeng; Shi, Yonghong; Wang, Qian; Shen, Dinggang; Wu, Guorong

2016-10-01

Accurate segmentation of brainstem nuclei (red nucleus and substantia nigra) is very important in various neuroimaging applications such as deep brain stimulation and the investigation of imaging biomarkers for Parkinson's disease (PD). Due to iron deposition during aging, image contrast in the brainstem is very low in Magnetic Resonance (MR) images. Hence, the ambiguity of patch-wise similarity makes the recently successful multi-atlas patch-based label fusion methods have difficulty to perform as competitive as segmenting cortical and sub-cortical regions from MR images. To address this challenge, we propose a novel multi-atlas brainstem nuclei segmentation method using deep hyper-graph learning. Specifically, we achieve this goal in three-fold. First , we employ hyper-graph to combine the advantage of maintaining spatial coherence from graph-based segmentation approaches and the benefit of harnessing population priors from multi-atlas based framework. Second , besides using low-level image appearance, we also extract high-level context features to measure the complex patch-wise relationship. Since the context features are calculated on a tentatively estimated label probability map, we eventually turn our hyper-graph learning based label propagation into a deep and self-refining model. Third , since anatomical labels on some voxels (usually located in uniform regions) can be identified much more reliably than other voxels (usually located at the boundary between two regions), we allow these reliable voxels to propagate their labels to the nearby difficult-to-label voxels. Such hierarchical strategy makes our proposed label fusion method deep and dynamic. We evaluate our proposed label fusion method in segmenting substantia nigra (SN) and red nucleus (RN) from 3.0 T MR images, where our proposed method achieves significant improvement over the state-of-the-art label fusion methods.

Efficient 3D multi-region prostate MRI segmentation using dual optimization.

PubMed

Qiu, Wu; Yuan, Jing; Ukwatta, Eranga; Sun, Yue; Rajchl, Martin; Fenster, Aaron

2013-01-01

Efficient and accurate extraction of the prostate, in particular its clinically meaningful sub-regions from 3D MR images, is of great interest in image-guided prostate interventions and diagnosis of prostate cancer. In this work, we propose a novel multi-region segmentation approach to simultaneously locating the boundaries of the prostate and its two major sub-regions: the central gland and the peripheral zone. The proposed method utilizes the prior knowledge of the spatial region consistency and employs a customized prostate appearance model to simultaneously segment multiple clinically meaningful regions. We solve the resulted challenging combinatorial optimization problem by means of convex relaxation, for which we introduce a novel spatially continuous flow-maximization model and demonstrate its duality to the investigated convex relaxed optimization problem with the region consistency constraint. Moreover, the proposed continuous max-flow model naturally leads to a new and efficient continuous max-flow based algorithm, which enjoys great advantages in numerics and can be readily implemented on GPUs. Experiments using 15 T2-weighted 3D prostate MR images, by inter- and intra-operator variability, demonstrate the promising performance of the proposed approach.

Multivariable Parametric Cost Model for Ground Optical: Telescope Assembly

NASA Technical Reports Server (NTRS)

Stahl, H. Philip; Rowell, Ginger Holmes; Reese, Gayle; Byberg, Alicia

2004-01-01

A parametric cost model for ground-based telescopes is developed using multi-variable statistical analysis of both engineering and performance parameters. While diameter continues to be the dominant cost driver, diffraction limited wavelength is found to be a secondary driver. Other parameters such as radius of curvature were examined. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e. multi-telescope phased-array systems). Additionally, single variable models based on aperture diameter were derived.

Midtarsal locking, the windlass mechanism, and running strike pattern: A kinematic and kinetic assessment.

PubMed

Bruening, Dustin A; Pohl, Michael B; Takahashi, Kota Z; Barrios, Joaquin A

2018-05-17

Changes in running strike pattern affect ankle and knee mechanics, but little is known about the influence of strike pattern on the joints distal to the ankle. The purpose of this study was to explore the effects of forefoot strike (FFS) and rearfoot strike (RFS) running patterns on foot kinematics and kinetics, from the perspectives of the midtarsal locking theory and the windlass mechanism. Per the midtarsal locking theory, we hypothesized that the ankle would be more inverted in early stance when using a FFS, resulting in decreased midtarsal joint excursions and increased dynamic stiffness. Associated with a more engaged windlass mechanism, we hypothesized that a FFS would elicit increased metatarsophalangeal joint excursions and negative work in late stance. Eighteen healthy female runners ran overground with both FFS and RFS patterns. Instrumented motion capture and a validated multi-segment foot model were used to analyze midtarsal and metatarsophalangeal joint kinematics and kinetics. During early stance in FFS the ankle was more inverted, with concurrently decreased midtarsal eversion (p < 0.001) and abduction excursions (p = 0.003) but increased dorsiflexion excursion (p = 0.005). Dynamic midtarsal stiffness did not differ (p = 0.761). During late stance in FFS, metatarsophalangeal extension was increased (p = 0.009), with concurrently increased negative work (p < 0.001). In addition, there was simultaneously increased midtarsal positive work (p < 0.001), suggesting enhanced power transfer in FFS. Clear evidence for the presence of midtarsal locking was not observed in either strike pattern during running. However, the windlass mechanism appeared to be engaged to a greater extent during FFS. Copyright © 2018 Elsevier Ltd. All rights reserved.

Adjustments to de Leva-anthropometric regression data for the changes in body proportions in elderly humans.

PubMed

Ho Hoang, Khai-Long; Mombaur, Katja

2015-10-15

Dynamic modeling of the human body is an important tool to investigate the fundamentals of the biomechanics of human movement. To model the human body in terms of a multi-body system, it is necessary to know the anthropometric parameters of the body segments. For young healthy subjects, several data sets exist that are widely used in the research community, e.g. the tables provided by de Leva. None such comprehensive anthropometric parameter sets exist for elderly people. It is, however, well known that body proportions change significantly during aging, e.g. due to degenerative effects in the spine, such that parameters for young people cannot be used for realistically simulating the dynamics of elderly people. In this study, regression equations are derived from the inertial parameters, center of mass positions, and body segment lengths provided by de Leva to be adjustable to the changes in proportion of the body parts of male and female humans due to aging. Additional adjustments are made to the reference points of the parameters for the upper body segments as they are chosen in a more practicable way in the context of creating a multi-body model in a chain structure with the pelvis representing the most proximal segment. Copyright © 2015 Elsevier Ltd. All rights reserved.

Towards an Auditory Account of Speech Rhythm: Application of a Model of the Auditory "Primal Sketch" to Two Multi-Language Corpora

ERIC Educational Resources Information Center

Lee, Christopher S.; Todd, Neil P. McAngus

2004-01-01

The world's languages display important differences in their rhythmic organization; most particularly, different languages seem to privilege different phonological units (mora, syllable, or stress foot) as their basic rhythmic unit. There is now considerable evidence that such differences have important consequences for crucial aspects of language…

A model to identify high crash road segments with the dynamic segmentation method.

PubMed

Boroujerdian, Amin Mirza; Saffarzadeh, Mahmoud; Yousefi, Hassan; Ghassemian, Hassan

2014-12-01

Currently, high social and economic costs in addition to physical and mental consequences put road safety among most important issues. This paper aims at presenting a novel approach, capable of identifying the location as well as the length of high crash road segments. It focuses on the location of accidents occurred along the road and their effective regions. In other words, due to applicability and budget limitations in improving safety of road segments, it is not possible to recognize all high crash road segments. Therefore, it is of utmost importance to identify high crash road segments and their real length to be able to prioritize the safety improvement in roads. In this paper, after evaluating deficiencies of the current road segmentation models, different kinds of errors caused by these methods are addressed. One of the main deficiencies of these models is that they can not identify the length of high crash road segments. In this paper, identifying the length of high crash road segments (corresponding to the arrangement of accidents along the road) is achieved by converting accident data to the road response signal of through traffic with a dynamic model based on the wavelet theory. The significant advantage of the presented method is multi-scale segmentation. In other words, this model identifies high crash road segments with different lengths and also it can recognize small segments within long segments. Applying the presented model into a real case for identifying 10-20 percent of high crash road segment showed an improvement of 25-38 percent in relative to the existing methods. Copyright © 2014 Elsevier Ltd. All rights reserved.

Anthropometric and biomechanical characteristics on body segments of Koreans.

PubMed

Park, S J; Kim, C B; Park, S C

1999-05-01

This paper documents the physical measurements of the Korean population in order to construct a data base for ergonomic design. The dimension, volume, density, mass, and center of mass of Koreans whose ages range from 7 to 49 were investigated. Sixty-five male subjects and sixty-nine female subjects participated. Eight body segments (head with neck, trunk, thigh, shank, foot, upper arm, forearm and hand) were directly measured with a Martin-type anthropometer, and the immersion method was adopted to measure the volume of body segments. After this, densities were computed by the density equations in Drillis and Contini (1966). The reaction board method was employed for the measurement of the center of mass. Obtained data were compared with the results in the literature. The results in this paper showed different features on body segment parameters comparing with the results in the literature. The constructed data base can be applied to statistical guideline for product design, workspace design, design of clothing and tools, furniture design and construction of biomechanical models for Korean. Also, they can be extended to the application areas for Mongolian.

Joint moments and contact forces in the foot during walking.

PubMed

Kim, Yongcheol; Lee, Kyoung Min; Koo, Seungbum

2018-06-06

The net force and moment of a joint have been widely used to understand joint disease in the foot. Meanwhile, it does not reflect the physiological forces on muscles and contact surfaces. The objective of the study is to estimate active moments by muscles, passive moments by connective tissues and joint contact forces in the foot joints during walking. Joint kinematics and external forces of ten healthy subjects (all males, 24.7 ± 1.2 years) were acquired during walking. The data were entered into the five-segment musculoskeletal foot model to calculate muscle forces and joint contact forces of the foot joints using an inverse dynamics-based optimization. Joint reaction forces and active, passive and net moments of each joint were calculated from muscle and ligament forces. The maximum joint reaction forces were 8.72, 4.31, 2.65, and 3.41 body weight (BW) for the ankle, Chopart's, Lisfranc and metatarsophalangeal joints, respectively. Active and passive moments along with net moments were also obtained. The maximum net moments were 8.6, 8.4, 5.4 and 0.8%BW∙HT, respectively. While the trend of net moment was very similar between the four joints, the magnitudes and directions of the active and passive moments varied between joints. The active and passive moments during walking could reveal the roles of muscles and ligaments in each of the foot joints, which was not obvious in the net moment. This method may help narrow down the source of joint problems if applied to clinical studies. Copyright © 2018 Elsevier Ltd. All rights reserved.

Fusion set selection with surrogate metric in multi-atlas based image segmentation

NASA Astrophysics Data System (ADS)

Zhao, Tingting; Ruan, Dan

2016-02-01

Multi-atlas based image segmentation sees unprecedented opportunities but also demanding challenges in the big data era. Relevant atlas selection before label fusion plays a crucial role in reducing potential performance loss from heterogeneous data quality and high computation cost from extensive data. This paper starts with investigating the image similarity metric (termed ‘surrogate’), an alternative to the inaccessible geometric agreement metric (termed ‘oracle’) in atlas relevance assessment, and probes into the problem of how to select the ‘most-relevant’ atlases and how many such atlases to incorporate. We propose an inference model to relate the surrogates and the oracle geometric agreement metrics. Based on this model, we quantify the behavior of the surrogates in mimicking oracle metrics for atlas relevance ordering. Finally, analytical insights on the choice of fusion set size are presented from a probabilistic perspective, with the integrated goal of including the most relevant atlases and excluding the irrelevant ones. Empirical evidence and performance assessment are provided based on prostate and corpus callosum segmentation.

Shape priors for segmentation of the cervix region within uterine cervix images

NASA Astrophysics Data System (ADS)

Lotenberg, Shelly; Gordon, Shiri; Greenspan, Hayit

2008-03-01

The work focuses on a unique medical repository of digital Uterine Cervix images ("Cervigrams") collected by the National Cancer Institute (NCI), National Institute of Health, in longitudinal multi-year studies. NCI together with the National Library of Medicine is developing a unique web-based database of the digitized cervix images to study the evolution of lesions related to cervical cancer. Tools are needed for the automated analysis of the cervigram content to support the cancer research. In recent works, a multi-stage automated system for segmenting and labeling regions of medical and anatomical interest within the cervigrams was developed. The current paper concentrates on incorporating prior-shape information in the cervix region segmentation task. In accordance with the fact that human experts mark the cervix region as circular or elliptical, two shape models (and corresponding methods) are suggested. The shape models are embedded within an active contour framework that relies on image features. Experiments indicate that incorporation of the prior shape information augments previous results.

Change Detection of Remote Sensing Images by Dt-Cwt and Mrf

NASA Astrophysics Data System (ADS)

Ouyang, S.; Fan, K.; Wang, H.; Wang, Z.

2017-05-01

Aiming at the significant loss of high frequency information during reducing noise and the pixel independence in change detection of multi-scale remote sensing image, an unsupervised algorithm is proposed based on the combination between Dual-tree Complex Wavelet Transform (DT-CWT) and Markov random Field (MRF) model. This method first performs multi-scale decomposition for the difference image by the DT-CWT and extracts the change characteristics in high-frequency regions by using a MRF-based segmentation algorithm. Then our method estimates the final maximum a posterior (MAP) according to the segmentation algorithm of iterative condition model (ICM) based on fuzzy c-means(FCM) after reconstructing the high-frequency and low-frequency sub-bands of each layer respectively. Finally, the method fuses the above segmentation results of each layer by using the fusion rule proposed to obtain the mask of the final change detection result. The results of experiment prove that the method proposed is of a higher precision and of predominant robustness properties.

Residual Shuffling Convolutional Neural Networks for Deep Semantic Image Segmentation Using Multi-Modal Data

NASA Astrophysics Data System (ADS)

Chen, K.; Weinmann, M.; Gao, X.; Yan, M.; Hinz, S.; Jutzi, B.; Weinmann, M.

2018-05-01

In this paper, we address the deep semantic segmentation of aerial imagery based on multi-modal data. Given multi-modal data composed of true orthophotos and the corresponding Digital Surface Models (DSMs), we extract a variety of hand-crafted radiometric and geometric features which are provided separately and in different combinations as input to a modern deep learning framework. The latter is represented by a Residual Shuffling Convolutional Neural Network (RSCNN) combining the characteristics of a Residual Network with the advantages of atrous convolution and a shuffling operator to achieve a dense semantic labeling. Via performance evaluation on a benchmark dataset, we analyze the value of different feature sets for the semantic segmentation task. The derived results reveal that the use of radiometric features yields better classification results than the use of geometric features for the considered dataset. Furthermore, the consideration of data on both modalities leads to an improvement of the classification results. However, the derived results also indicate that the use of all defined features is less favorable than the use of selected features. Consequently, data representations derived via feature extraction and feature selection techniques still provide a gain if used as the basis for deep semantic segmentation.

Jansen-MIDAS: A multi-level photomicrograph segmentation software based on isotropic undecimated wavelets.

PubMed

de Siqueira, Alexandre Fioravante; Cabrera, Flávio Camargo; Nakasuga, Wagner Massayuki; Pagamisse, Aylton; Job, Aldo Eloizo

2018-01-01

Image segmentation, the process of separating the elements within a picture, is frequently used for obtaining information from photomicrographs. Segmentation methods should be used with reservations, since incorrect results can mislead when interpreting regions of interest (ROI). This decreases the success rate of extra procedures. Multi-Level Starlet Segmentation (MLSS) and Multi-Level Starlet Optimal Segmentation (MLSOS) were developed to be an alternative for general segmentation tools. These methods gave rise to Jansen-MIDAS, an open-source software. A scientist can use it to obtain several segmentations of hers/his photomicrographs. It is a reliable alternative to process different types of photomicrographs: previous versions of Jansen-MIDAS were used to segment ROI in photomicrographs of two different materials, with an accuracy superior to 89%. © 2017 Wiley Periodicals, Inc.

A User''s Guide to the Zwikker-Kosten Transmission Line Code (ZKTL)

NASA Technical Reports Server (NTRS)

Kelly, J. J.; Abu-Khajeel, H.

1997-01-01

This user's guide documents updates to the Zwikker-Kosten Transmission Line Code (ZKTL). This code was developed for analyzing new liner concepts developed to provide increased sound absorption. Contiguous arrays of multi-degree-of-freedom (MDOF) liner elements serve as the model for these liner configurations, and Zwikker and Kosten's theory of sound propagation in channels is used to predict the surface impedance. Transmission matrices for the various liner elements incorporate both analytical and semi-empirical methods. This allows standard matrix techniques to be employed in the code to systematically calculate the composite impedance due to the individual liner elements. The ZKTL code consists of four independent subroutines: 1. Single channel impedance calculation - linear version (SCIC) 2. Single channel impedance calculation - nonlinear version (SCICNL) 3. Multi-channel, multi-segment, multi-layer impedance calculation - linear version (MCMSML) 4. Multi-channel, multi-segment, multi-layer impedance calculation - nonlinear version (MCMSMLNL) Detailed examples, comments, and explanations for each liner impedance computation module are included. Also contained in the guide are depictions of the interactive execution, input files and output files.

Are Physics-Based Simulators Ready for Prime Time? Comparisons of RSQSim with UCERF3 and Observations.

NASA Astrophysics Data System (ADS)

Milner, K. R.; Shaw, B. E.; Gilchrist, J. J.; Jordan, T. H.

2017-12-01

Probabilistic seismic hazard analysis (PSHA) is typically performed by combining an earthquake rupture forecast (ERF) with a set of empirical ground motion prediction equations (GMPEs). ERFs have typically relied on observed fault slip rates and scaling relationships to estimate the rate of large earthquakes on pre-defined fault segments, either ignoring or relying on expert opinion to set the rates of multi-fault or multi-segment ruptures. Version 3 of the Uniform California Earthquake Rupture Forecast (UCERF3) is a significant step forward, replacing expert opinion and fault segmentation with an inversion approach that matches observations better than prior models while incorporating multi-fault ruptures. UCERF3 is a statistical model, however, and doesn't incorporate the physics of earthquake nucleation, rupture propagation, and stress transfer. We examine the feasibility of replacing UCERF3, or components therein, with physics-based rupture simulators such as the Rate-State Earthquake Simulator (RSQSim), developed by Dieterich & Richards-Dinger (2010). RSQSim simulations on the UCERF3 fault system produce catalogs of seismicity that match long term rates on major faults, and produce remarkable agreement with UCERF3 when carried through to PSHA calculations. Averaged over a representative set of sites, the RSQSim-UCERF3 hazard-curve differences are comparable to the small differences between UCERF3 and its predecessor, UCERF2. The hazard-curve agreement between the empirical and physics-based models provides substantial support for the PSHA methodology. RSQSim catalogs include many complex multi-fault ruptures, which we compare with the UCERF3 rupture-plausibility metrics as well as recent observations. Complications in generating physically plausible kinematic descriptions of multi-fault ruptures have thus far prevented us from using UCERF3 in the CyberShake physics-based PSHA platform, which replaces GMPEs with deterministic ground motion simulations. RSQSim produces full slip/time histories that can be directly implemented as sources in CyberShake, without relying on the conditional hypocenter and slip distributions needed for the UCERF models. We also compare RSQSim with time-dependent PSHA calculations based on multi-fault renewal models.

Cell Motility Dynamics: A Novel Segmentation Algorithm to Quantify Multi-Cellular Bright Field Microscopy Images

PubMed Central

Zaritsky, Assaf; Natan, Sari; Horev, Judith; Hecht, Inbal; Wolf, Lior; Ben-Jacob, Eshel; Tsarfaty, Ilan

2011-01-01

Confocal microscopy analysis of fluorescence and morphology is becoming the standard tool in cell biology and molecular imaging. Accurate quantification algorithms are required to enhance the understanding of different biological phenomena. We present a novel approach based on image-segmentation of multi-cellular regions in bright field images demonstrating enhanced quantitative analyses and better understanding of cell motility. We present MultiCellSeg, a segmentation algorithm to separate between multi-cellular and background regions for bright field images, which is based on classification of local patches within an image: a cascade of Support Vector Machines (SVMs) is applied using basic image features. Post processing includes additional classification and graph-cut segmentation to reclassify erroneous regions and refine the segmentation. This approach leads to a parameter-free and robust algorithm. Comparison to an alternative algorithm on wound healing assay images demonstrates its superiority. The proposed approach was used to evaluate common cell migration models such as wound healing and scatter assay. It was applied to quantify the acceleration effect of Hepatocyte growth factor/scatter factor (HGF/SF) on healing rate in a time lapse confocal microscopy wound healing assay and demonstrated that the healing rate is linear in both treated and untreated cells, and that HGF/SF accelerates the healing rate by approximately two-fold. A novel fully automated, accurate, zero-parameters method to classify and score scatter-assay images was developed and demonstrated that multi-cellular texture is an excellent descriptor to measure HGF/SF-induced cell scattering. We show that exploitation of textural information from differential interference contrast (DIC) images on the multi-cellular level can prove beneficial for the analyses of wound healing and scatter assays. The proposed approach is generic and can be used alone or alongside traditional fluorescence single-cell processing to perform objective, accurate quantitative analyses for various biological applications. PMID:22096600

Cell motility dynamics: a novel segmentation algorithm to quantify multi-cellular bright field microscopy images.

PubMed

Zaritsky, Assaf; Natan, Sari; Horev, Judith; Hecht, Inbal; Wolf, Lior; Ben-Jacob, Eshel; Tsarfaty, Ilan

2011-01-01

Confocal microscopy analysis of fluorescence and morphology is becoming the standard tool in cell biology and molecular imaging. Accurate quantification algorithms are required to enhance the understanding of different biological phenomena. We present a novel approach based on image-segmentation of multi-cellular regions in bright field images demonstrating enhanced quantitative analyses and better understanding of cell motility. We present MultiCellSeg, a segmentation algorithm to separate between multi-cellular and background regions for bright field images, which is based on classification of local patches within an image: a cascade of Support Vector Machines (SVMs) is applied using basic image features. Post processing includes additional classification and graph-cut segmentation to reclassify erroneous regions and refine the segmentation. This approach leads to a parameter-free and robust algorithm. Comparison to an alternative algorithm on wound healing assay images demonstrates its superiority. The proposed approach was used to evaluate common cell migration models such as wound healing and scatter assay. It was applied to quantify the acceleration effect of Hepatocyte growth factor/scatter factor (HGF/SF) on healing rate in a time lapse confocal microscopy wound healing assay and demonstrated that the healing rate is linear in both treated and untreated cells, and that HGF/SF accelerates the healing rate by approximately two-fold. A novel fully automated, accurate, zero-parameters method to classify and score scatter-assay images was developed and demonstrated that multi-cellular texture is an excellent descriptor to measure HGF/SF-induced cell scattering. We show that exploitation of textural information from differential interference contrast (DIC) images on the multi-cellular level can prove beneficial for the analyses of wound healing and scatter assays. The proposed approach is generic and can be used alone or alongside traditional fluorescence single-cell processing to perform objective, accurate quantitative analyses for various biological applications.

Positioning the endoscope in laparoscopic surgery by foot: Influential factors on surgeons' performance in virtual trainer.

PubMed

Abdi, Elahe; Bouri, Mohamed; Burdet, Etienne; Himidan, Sharifa; Bleuler, Hannes

2017-07-01

We have investigated how surgeons can use the foot to position a laparoscopic endoscope, a task that normally requires an extra assistant. Surgeons need to train in order to exploit the possibilities offered by this new technique and safely manipulate the endoscope together with the hands movements. A realistic abdominal cavity has been developed as training simulator to investigate this multi-arm manipulation. In this virtual environment, the surgeon's biological hands are modelled as laparoscopic graspers while the viewpoint is controlled by the dominant foot. 23 surgeons and medical students performed single-handed and bimanual manipulation in this environment. The results show that residents had superior performance compared to both medical students and more experienced surgeons, suggesting that residency is an ideal period for this training. Performing the single-handed task improves the performance in the bimanual task, whereas the converse was not true.

[A simulation study with finite element model on the unequal loss of peripheral vision caused by acceleration].

PubMed

Geng, Xiaoqi; Liu, Xiaoyu; Liu, Songyang; Xu, Yan; Zhao, Xianliang; Wang, Jie; Fan, Yubo

2017-04-01

An unequal loss of peripheral vision may happen with high sustaining multi-axis acceleration, leading to a great potential flight safety hazard. In the present research, finite element method was used to study the mechanism of unequal loss of peripheral vision. Firstly, a 3D geometric model of skull was developed based on the adult computer tomography (CT) images. The model of double eyes was created by mirroring with the previous right eye model. Then, the double-eye model was matched to the skull model, and fat was filled between eyeballs and skull. Acceleration loads of head-to-foot (G z ), right-to-left (G y ), chest-to-back (G x ) and multi-axis directions were applied to the current model to simulate dynamic response of retina by explicit dynamics solution. The results showed that the relative strain of double eyes was 25.7% under multi-axis acceleration load. Moreover, the strain distributions showed a significant difference among acceleration loaded in different directions. It indicated that a finite element model of double eyes was an effective means to study the mechanism of an unequal loss of peripheral vision at sustaining high multi-axis acceleration.

Development of a finite element/multi-body model of a newborn infant for restraint analysis and design.

PubMed

Bondy, Matthew; Altenhof, William; Chen, Xilin; Snowdon, Anne; Vrkljan, Brenda

2014-01-01

A finite element/multi-body model of a newborn infant has been developed by researchers at the University of Windsor. The geometry of this model is derived from a Nita newborn hospital training mannequin. It consists of 17 parts: eight upper and lower limb segments, the torso, head, and a seven-segment neck with seven translational and eight rotational joints. Anthropometry is consistent with hospital growth charts, measurements requested from health professionals and data from the open literature. The biomechanical properties of the model (i.e. joint stiffnesses) are implementations of data identified in the open literature. The model has been validated with respect to studies of the biomechanics of shaken baby syndrome, infant falls and the Q0 anthropomorphic testing device. A significant conclusion of this study is that the kinetics of the Q0 neck is not biofidelic. This model is currently used in an analysis of airway patency for infants in modern automotive child restraints.

Multi-scale Fracture Patterns Associated with a Complex Anticline Structure: Insights from Field Outcrop Analogues of the Jebel Hafit Pericline, Al Ain-UAE

NASA Astrophysics Data System (ADS)

Kokkalas, S.; Jones, R. R.; Long, J. J.; Zampos, M.; Wilkinson, M. W.; Gilment, S.

2017-12-01

The formation of folds and their associated fracture patterns plays an important role in controlling the migration and concentration of fluids within the upper crust. Prediction of fracture patterns from various fold shapes and kinematics still remains poorly understood in terms of spatial and temporal distribution of fracture sets. Thus, a more detailed field-based multi scale approach is required to better constrain 3D models of fold-fracture relationships, which are critical for reservoir characterization studies. In order to generate reservoir-scale fracture models representative fracture properties across a wider range of scales are needed. For this reason we applied modern geospatial technologies, including terrestrial LiDAR, photogrammetry and satellite images in the asymmetric, east verging, four-way closure Jebel Hafit anticline, in the eastern part of the United Arab Emirates. The excellent surface outcrops allowed the rapid acquisition of extensive areas of fracture data from both limbs and fold hinge area of the anticline, even from large areas of steep exposure that are practically inaccessible on foot. The digital outcrops provide longer 1D transects, and 2D or 3D surface datasets and give more robust data, particularly for fracture heights, lengths, spacing, clustering, termination and connectivity. The fracture patterns across the folded structure are more complex than those predicted from conceptual models and geomechanical fracture modeling. Mechanical layering, pre-existing structures and sedimentation during fold growth seem to exert a critical influence in the development of fracture systems within Jebel Hafit anticline and directly affect fracture orientations, spacing/intensity, segmentation and connectivity. Seismic and borehole data provide additional constraints on the sub-surface fold geometry and existence of large-scale thrusting in the core of the anticline. The complexity of the relationship between fold geometry and fracture intensity is presented and the implications for prediction of fracture networks in naturally fractured reservoirs are discussed.

Climbing robot. [caterpillar design

NASA Technical Reports Server (NTRS)

Kerley, James J. (Inventor); May, Edward L. (Inventor); Ecklund, Wayne D. (Inventor)

1993-01-01

A mobile robot for traversing any surface consisting of a number of interconnected segments, each interconnected segment having an upper 'U' frame member, a lower 'U' frame member, a compliant joint between the upper 'U' frame member and the lower 'U' frame member, a number of linear actuators between the two frame members acting to provide relative displacement between the frame members, a foot attached to the lower 'U' frame member for adherence of the segment to the surface, an inter-segment attachment attached to the upper 'U' frame member for interconnecting the segments, a power source connected to the linear actuator, and a computer/controller for independently controlling each linear actuator in each interconnected segment such that the mobile robot moves in a caterpillar like fashion.

The Atlantic Richfield Company Black Thunder mine haul road dust study. [Wyoming

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

Maxwell, D.R.; Hormel, T.R.; Ives, J.A.

An examination of the effectiveness of various haul road dust control measures was performed at ARCO's Black Thunder Mine near Wright, Wyoming by evaluating both visible observations and quantitative measurements of particle concentrations. In order to evaluate dust control effectiveness both a 300 foot (91.5 meter) and 175 foot (53.4 meter) section of the main coal haul road was selected for testing. The test sections were separated by a 200 foot (61 meter) buffer zone. Each test section was relatively straight and away from interferences from other mine sources. The five haul road treatment test sequences evaluated for control measuremore » effectiveness were: an untreated road segment; water treatment two times per hour; water treatment four times per hour; previously chemically treated segment of haul road (ARCO 2400 dust suppressant); and testing after application of Coherex (10% dilution). By comparing uncontrolled situations with various controlled situations, an estimate of the control efficiency of the dust control measures was determined. Based upon the results of the study a fugitive dust control scheme was selected considering control effectiveness, economics and operational efficiency.« less

Selecting exposure measures in crash rate prediction for two-lane highway segments.

PubMed

Qin, Xiao; Ivan, John N; Ravishanker, Nalini

2004-03-01

A critical part of any risk assessment is identifying how to represent exposure to the risk involved. Recent research shows that the relationship between crash count and traffic volume is non-linear; consequently, a simple crash rate computed as the ratio of crash count to volume is not proper for comparing the safety of sites with different traffic volumes. To solve this problem, we describe a new approach for relating traffic volume and crash incidence. Specifically, we disaggregate crashes into four types: (1) single-vehicle, (2) multi-vehicle same direction, (3) multi-vehicle opposite direction, and (4) multi-vehicle intersecting, and define candidate exposure measures for each that we hypothesize will be linear with respect to each crash type. This paper describes initial investigation using crash and physical characteristics data for highway segments in Michigan from the Highway Safety Information System (HSIS). We use zero-inflated-Poisson (ZIP) modeling to estimate models for predicting counts for each of the above crash types as a function of the daily volume, segment length, speed limit and roadway width. We found that the relationship between crashes and the daily volume (AADT) is non-linear and varies by crash type, and is significantly different from the relationship between crashes and segment length for all crash types. Our research will provide information to improve accuracy of crash predictions and, thus, facilitate more meaningful comparison of the safety record of seemingly similar highway locations.

Joint Labeling Of Multiple Regions of Interest (Rois) By Enhanced Auto Context Models.

PubMed

Kim, Minjeong; Wu, Guorong; Guo, Yanrong; Shen, Dinggang

2015-04-01

Accurate segmentation of a set of regions of interest (ROIs) in the brain images is a key step in many neuroscience studies. Due to the complexity of image patterns, many learning-based segmentation methods have been proposed, including auto context model (ACM) that can capture high-level contextual information for guiding segmentation. However, since current ACM can only handle one ROI at a time, neighboring ROIs have to be labeled separately with different ACMs that are trained independently without communicating each other. To address this, we enhance the current single-ROI learning ACM to multi-ROI learning ACM for joint labeling of multiple neighboring ROIs (called e ACM). First, we extend current independently-trained single-ROI ACMs to a set of jointly-trained cross-ROI ACMs, by simultaneous training of ACMs for all spatially-connected ROIs to let them to share their respective intermediate outputs for coordinated labeling of each image point. Then, the context features in each ACM can capture the cross-ROI dependence information from the outputs of other ACMs that are designed for neighboring ROIs. Second, we upgrade the output labeling map of each ACM with the multi-scale representation, thus both local and global context information can be effectively used to increase the robustness in characterizing geometric relationship among neighboring ROIs. Third, we integrate ACM into a multi-atlases segmentation paradigm, for encompassing high variations among subjects. Experiments on LONI LPBA40 dataset show much better performance by our e ACM, compared to the conventional ACM.

Ground-Based Telescope Parametric Cost Model

NASA Technical Reports Server (NTRS)

Stahl, H. Philip; Rowell, Ginger Holmes

2004-01-01

A parametric cost model for ground-based telescopes is developed using multi-variable statistical analysis, The model includes both engineering and performance parameters. While diameter continues to be the dominant cost driver, other significant factors include primary mirror radius of curvature and diffraction limited wavelength. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e.. multi-telescope phased-array systems). Additionally, single variable models based on aperture diameter are derived. This analysis indicates that recent mirror technology advances have indeed reduced the historical telescope cost curve.

The quality of visual information about the lower extremities influences visuomotor coordination during virtual obstacle negotiation.

PubMed

Kim, Aram; Kretch, Kari S; Zhou, Zixuan; Finley, James M

2018-05-09

Successful negotiation of obstacles during walking relies on the integration of visual information about the environment with ongoing locomotor commands. When information about the body and environment are removed through occlusion of the lower visual field, individuals increase downward head pitch angle, reduce foot placement precision, and increase safety margins during crossing. However, whether these effects are mediated by loss of visual information about the lower extremities, the obstacle, or both remains to be seen. Here, we used a fully immersive, virtual obstacle negotiation task to investigate how visual information about the lower extremities is integrated with information about the environment to facilitate skillful obstacle negotiation. Participants stepped over virtual obstacles while walking on a treadmill with one of three types of visual feedback about the lower extremities: no feedback, end-point feedback, or a link-segment model. We found that absence of visual information about the lower extremities led to an increase in the variability of leading foot placement after crossing. The presence of a visual representation of the lower extremities promoted greater downward head pitch angle during the approach to and subsequent crossing of an obstacle. In addition, having greater downward head pitch was associated with closer placement of the trailing foot to the obstacle, further placement of the leading foot after the obstacle, and higher trailing foot clearance. These results demonstrate that the fidelity of visual information about the lower extremities influences both feed-forward and feedback aspects of visuomotor coordination during obstacle negotiation.

Multi-Step Time Series Forecasting with an Ensemble of Varied Length Mixture Models.

PubMed

Ouyang, Yicun; Yin, Hujun

2018-05-01

Many real-world problems require modeling and forecasting of time series, such as weather temperature, electricity demand, stock prices and foreign exchange (FX) rates. Often, the tasks involve predicting over a long-term period, e.g. several weeks or months. Most existing time series models are inheritably for one-step prediction, that is, predicting one time point ahead. Multi-step or long-term prediction is difficult and challenging due to the lack of information and uncertainty or error accumulation. The main existing approaches, iterative and independent, either use one-step model recursively or treat the multi-step task as an independent model. They generally perform poorly in practical applications. In this paper, as an extension of the self-organizing mixture autoregressive (AR) model, the varied length mixture (VLM) models are proposed to model and forecast time series over multi-steps. The key idea is to preserve the dependencies between the time points within the prediction horizon. Training data are segmented to various lengths corresponding to various forecasting horizons, and the VLM models are trained in a self-organizing fashion on these segments to capture these dependencies in its component AR models of various predicting horizons. The VLM models form a probabilistic mixture of these varied length models. A combination of short and long VLM models and an ensemble of them are proposed to further enhance the prediction performance. The effectiveness of the proposed methods and their marked improvements over the existing methods are demonstrated through a number of experiments on synthetic data, real-world FX rates and weather temperatures.

Sea-land segmentation for infrared remote sensing images based on superpixels and multi-scale features

NASA Astrophysics Data System (ADS)

Lei, Sen; Zou, Zhengxia; Liu, Dunge; Xia, Zhenghuan; Shi, Zhenwei

2018-06-01

Sea-land segmentation is a key step for the information processing of ocean remote sensing images. Traditional sea-land segmentation algorithms ignore the local similarity prior of sea and land, and thus fail in complex scenarios. In this paper, we propose a new sea-land segmentation method for infrared remote sensing images to tackle the problem based on superpixels and multi-scale features. Considering the connectivity and local similarity of sea or land, we interpret the sea-land segmentation task in view of superpixels rather than pixels, where similar pixels are clustered and the local similarity are explored. Moreover, the multi-scale features are elaborately designed, comprising of gray histogram and multi-scale total variation. Experimental results on infrared bands of Landsat-8 satellite images demonstrate that the proposed method can obtain more accurate and more robust sea-land segmentation results than the traditional algorithms.

The relationship between allometry and preferred transition speed in human locomotion.

PubMed

Ranisavljev, Igor; Ilic, Vladimir; Soldatovic, Ivan; Stefanovic, Djordje

2014-04-01

The purpose of this study was to explore the relationships between preferred transition speed (PTS) and anthropometric characteristics, body composition and different human body proportions in males. In a sample of 59 male students, we collected anthropometric and body composition data and determined individual PTS using increment protocol. The relationships between PTS and other variables were determined using Pearson correlation, stepwise linear and hierarchical regression. Body ratios were formed as quotient of two variables whereby at least one significantly correlated to PTS. Circular and transversal (except bitrochanteric diameter) body dimensions did not correlate with PTS. Moderate correlations were found between longitudinal leg dimensions (foot, leg and thigh length) and PTS, while the highest correlation was found for lower leg length (r=.488, p<.01). Two parameters related to body composition showed weak correlation with PTS: body fat mass (r=-.250, p<.05) and amount of lean leg mass scaled to body weight (r=.309, p<.05). Segmental body proportions correlated more significantly with PTS, where thigh/lower leg length ratio showed the highest correlation (r=.521, p<.01). Prediction model with individual variables (lower leg and foot length) have explained just 31% of PTS variability, while model with body proportions showed almost 20% better prediction (R(2)=.504). These results suggests that longitudinal leg dimensions have moderate influence on PTS and that segmental body proportions significantly more explain PTS than single anthropometric variables. Copyright © 2014 Elsevier B.V. All rights reserved.

Consistent cortical reconstruction and multi-atlas brain segmentation.

PubMed

Huo, Yuankai; Plassard, Andrew J; Carass, Aaron; Resnick, Susan M; Pham, Dzung L; Prince, Jerry L; Landman, Bennett A

2016-09-01

Whole brain segmentation and cortical surface reconstruction are two essential techniques for investigating the human brain. Spatial inconsistences, which can hinder further integrated analyses of brain structure, can result due to these two tasks typically being conducted independently of each other. FreeSurfer obtains self-consistent whole brain segmentations and cortical surfaces. It starts with subcortical segmentation, then carries out cortical surface reconstruction, and ends with cortical segmentation and labeling. However, this "segmentation to surface to parcellation" strategy has shown limitations in various cohorts such as older populations with large ventricles. In this work, we propose a novel "multi-atlas segmentation to surface" method called Multi-atlas CRUISE (MaCRUISE), which achieves self-consistent whole brain segmentations and cortical surfaces by combining multi-atlas segmentation with the cortical reconstruction method CRUISE. A modification called MaCRUISE(+) is designed to perform well when white matter lesions are present. Comparing to the benchmarks CRUISE and FreeSurfer, the surface accuracy of MaCRUISE and MaCRUISE(+) is validated using two independent datasets with expertly placed cortical landmarks. A third independent dataset with expertly delineated volumetric labels is employed to compare segmentation performance. Finally, 200MR volumetric images from an older adult sample are used to assess the robustness of MaCRUISE and FreeSurfer. The advantages of MaCRUISE are: (1) MaCRUISE constructs self-consistent voxelwise segmentations and cortical surfaces, while MaCRUISE(+) is robust to white matter pathology. (2) MaCRUISE achieves more accurate whole brain segmentations than independently conducting the multi-atlas segmentation. (3) MaCRUISE is comparable in accuracy to FreeSurfer (when FreeSurfer does not exhibit global failures) while achieving greater robustness across an older adult population. MaCRUISE has been made freely available in open source. Copyright © 2016 Elsevier Inc. All rights reserved.

Multi-atlas and label fusion approach for patient-specific MRI based skull estimation.

PubMed

Torrado-Carvajal, Angel; Herraiz, Joaquin L; Hernandez-Tamames, Juan A; San Jose-Estepar, Raul; Eryaman, Yigitcan; Rozenholc, Yves; Adalsteinsson, Elfar; Wald, Lawrence L; Malpica, Norberto

2016-04-01

MRI-based skull segmentation is a useful procedure for many imaging applications. This study describes a methodology for automatic segmentation of the complete skull from a single T1-weighted volume. The skull is estimated using a multi-atlas segmentation approach. Using a whole head computed tomography (CT) scan database, the skull in a new MRI volume is detected by nonrigid image registration of the volume to every CT, and combination of the individual segmentations by label-fusion. We have compared Majority Voting, Simultaneous Truth and Performance Level Estimation (STAPLE), Shape Based Averaging (SBA), and the Selective and Iterative Method for Performance Level Estimation (SIMPLE) algorithms. The pipeline has been evaluated quantitatively using images from the Retrospective Image Registration Evaluation database (reaching an overlap of 72.46 ± 6.99%), a clinical CT-MR dataset (maximum overlap of 78.31 ± 6.97%), and a whole head CT-MRI pair (maximum overlap 78.68%). A qualitative evaluation has also been performed on MRI acquisition of volunteers. It is possible to automatically segment the complete skull from MRI data using a multi-atlas and label fusion approach. This will allow the creation of complete MRI-based tissue models that can be used in electromagnetic dosimetry applications and attenuation correction in PET/MR. © 2015 Wiley Periodicals, Inc.

Semi-automatic brain tumor segmentation by constrained MRFs using structural trajectories.

PubMed

Zhao, Liang; Wu, Wei; Corso, Jason J

2013-01-01

Quantifying volume and growth of a brain tumor is a primary prognostic measure and hence has received much attention in the medical imaging community. Most methods have sought a fully automatic segmentation, but the variability in shape and appearance of brain tumor has limited their success and further adoption in the clinic. In reaction, we present a semi-automatic brain tumor segmentation framework for multi-channel magnetic resonance (MR) images. This framework does not require prior model construction and only requires manual labels on one automatically selected slice. All other slices are labeled by an iterative multi-label Markov random field optimization with hard constraints. Structural trajectories-the medical image analog to optical flow and 3D image over-segmentation are used to capture pixel correspondences between consecutive slices for pixel labeling. We show robustness and effectiveness through an evaluation on the 2012 MICCAI BRATS Challenge Dataset; our results indicate superior performance to baselines and demonstrate the utility of the constrained MRF formulation.

A Patch-Based Approach for the Segmentation of Pathologies: Application to Glioma Labelling.

PubMed

Cordier, Nicolas; Delingette, Herve; Ayache, Nicholas

2016-04-01

In this paper, we describe a novel and generic approach to address fully-automatic segmentation of brain tumors by using multi-atlas patch-based voting techniques. In addition to avoiding the local search window assumption, the conventional patch-based framework is enhanced through several simple procedures: an improvement of the training dataset in terms of both label purity and intensity statistics, augmented features to implicitly guide the nearest-neighbor-search, multi-scale patches, invariance to cube isometries, stratification of the votes with respect to cases and labels. A probabilistic model automatically delineates regions of interest enclosing high-probability tumor volumes, which allows the algorithm to achieve highly competitive running time despite minimal processing power and resources. This method was evaluated on Multimodal Brain Tumor Image Segmentation challenge datasets. State-of-the-art results are achieved, with a limited learning stage thus restricting the risk of overfit. Moreover, segmentation smoothness does not involve any post-processing.

Hand-to-Hand Model for Bioelectrical Impedance Analysis to Estimate Fat Free Mass in a Healthy Population

PubMed Central

Lu, Hsueh-Kuan; Chiang, Li-Ming; Chen, Yu-Yawn; Chuang, Chih-Lin; Chen, Kuen-Tsann; Dwyer, Gregory B.; Hsu, Ying-Lin; Chen, Chun-Hao; Hsieh, Kuen-Chang

2016-01-01

This study aimed to establish a hand-to-hand (HH) model for bioelectrical impedance analysis (BIA) fat free mass (FFM) estimation by comparing with a standing position hand-to-foot (HF) BIA model and dual energy X-ray absorptiometry (DXA); we also verified the reliability of the newly developed model. A total of 704 healthy Chinese individuals (403 men and 301 women) participated. FFM (FFMDXA) reference variables were measured using DXA and segmental BIA. Further, regression analysis, Bland–Altman plots, and cross-validation (2/3 participants as the modeling group, 1/3 as the validation group; three turns were repeated for validation grouping) were conducted to compare tests of agreement with FFMDXA reference variables. In male participants, the hand-to-hand BIA model estimation equation was calculated as follows: FFMmHH = 0.537 h2/ZHH − 0.126 year + 0.217 weight + 18.235 (r2 = 0.919, standard estimate of error (SEE) = 2.164 kg, n = 269). The mean validated correlation coefficients and limits of agreement (LOAs) of the Bland–Altman analysis of the calculated values for FFMmHH and FFMDXA were 0.958 and −4.369–4.343 kg, respectively, for hand-to-foot BIA model measurements for men; the FFM (FFMmHF) and FFMDXA were 0.958 and −4.356–4.375 kg, respectively. The hand-to-hand BIA model estimating equation for female participants was FFMFHH = 0.615 h2/ZHH − 0.144 year + 0.132 weight + 16.507 (r2 = 0.870, SEE = 1.884 kg, n = 201); the three mean validated correlation coefficient and LOA for the hand-to-foot BIA model measurements for female participants (FFMFHH and FFMDXA) were 0.929 and −3.880–3.886 kg, respectively. The FFMHF and FFMDXA were 0.942 and −3.511–3.489 kg, respectively. The results of both hand-to-hand and hand-to-foot BIA models demonstrated similar reliability, and the hand-to-hand BIA models are practical for assessing FFM. PMID:27775642

Hand-to-Hand Model for Bioelectrical Impedance Analysis to Estimate Fat Free Mass in a Healthy Population.

PubMed

Lu, Hsueh-Kuan; Chiang, Li-Ming; Chen, Yu-Yawn; Chuang, Chih-Lin; Chen, Kuen-Tsann; Dwyer, Gregory B; Hsu, Ying-Lin; Chen, Chun-Hao; Hsieh, Kuen-Chang

2016-10-21

This study aimed to establish a hand-to-hand (HH) model for bioelectrical impedance analysis (BIA) fat free mass (FFM) estimation by comparing with a standing position hand-to-foot (HF) BIA model and dual energy X-ray absorptiometry (DXA); we also verified the reliability of the newly developed model. A total of 704 healthy Chinese individuals (403 men and 301 women) participated. FFM (FFM DXA ) reference variables were measured using DXA and segmental BIA. Further, regression analysis, Bland-Altman plots, and cross-validation (2/3 participants as the modeling group, 1/3 as the validation group; three turns were repeated for validation grouping) were conducted to compare tests of agreement with FFM DXA reference variables. In male participants, the hand-to-hand BIA model estimation equation was calculated as follows: FFM m HH = 0.537 h²/Z HH - 0.126 year + 0.217 weight + 18.235 ( r ² = 0.919, standard estimate of error (SEE) = 2.164 kg, n = 269). The mean validated correlation coefficients and limits of agreement (LOAs) of the Bland-Altman analysis of the calculated values for FFM m HH and FFM DXA were 0.958 and -4.369-4.343 kg, respectively, for hand-to-foot BIA model measurements for men; the FFM (FFM m HF ) and FFM DXA were 0.958 and -4.356-4.375 kg, respectively. The hand-to-hand BIA model estimating equation for female participants was FFM F HH = 0.615 h²/Z HH - 0.144 year + 0.132 weight + 16.507 ( r ² = 0.870, SEE = 1.884 kg, n = 201); the three mean validated correlation coefficient and LOA for the hand-to-foot BIA model measurements for female participants (FFM F HH and FFM DXA ) were 0.929 and -3.880-3.886 kg, respectively. The FFM HF and FFM DXA were 0.942 and -3.511-3.489 kg, respectively. The results of both hand-to-hand and hand-to-foot BIA models demonstrated similar reliability, and the hand-to-hand BIA models are practical for assessing FFM.

Saturn V First Stage Lowered to the Ground After Static Test

NASA Technical Reports Server (NTRS)

1966-01-01

This vintage photograph shows the 138-foot long first stage of the Saturn V being lowered to the ground following a successful static test firing at Marshall Space flight Center's S-1C test stand. The firing provided NASA engineers information on the booster's systems. The towering 363-foot Saturn V was a multi-stage, multi-engine launch vehicle standing taller than the Statue of Liberty. Altogether, the Saturn V engines produced as much power as 85 Hoover Dams.

Saturn Apollo Program

NASA Image and Video Library

1970-01-22

This Saturn V S-II (second) stage is being lifted into position for a test at the Vehicle Assembly Building at the Kennedy Space Center. When the Saturn V booster stage (S-IC) burned out and dropped away, power for the Saturn was provided by the 82-foot-long and 33-foot-diameter S-II stage. Developed by the Space Division of North American Aviation under the direction of the Marshall Space Flight Center, the stage utilized five J-2 engines, each producing 200,000 pounds of thrust. The engines used liquid oxygen and liquid hydrogen as propellants. The towering 363-foot Saturn V was a multi-stage, multi-engine launch vehicle standing taller than the Statue of Liberty. Altogether, the Saturn V engines produced as much power as 85 Hoover Dams.

Contribution of calcaneal and leg segment rotations to ankle joint dorsiflexion in a weight-bearing task.

PubMed

Chizewski, Michael G; Chiu, Loren Z F

2012-05-01

Joint angle is the relative rotation between two segments where one is a reference and assumed to be non-moving. However, rotation of the reference segment will influence the system's spatial orientation and joint angle. The purpose of this investigation was to determine the contribution of leg and calcaneal rotations to ankle rotation in a weight-bearing task. Forty-eight individuals performed partial squats recorded using a 3D motion capture system. Markers on the calcaneus and leg were used to model leg and calcaneal segment, and ankle joint rotations. Multiple linear regression was used to determine the contribution of leg and calcaneal segment rotations to ankle joint dorsiflexion. Regression models for left (R(2)=0.97) and right (R(2)=0.97) ankle dorsiflexion were significant. Sagittal plane leg rotation had a positive influence (left: β=1.411; right: β=1.418) while sagittal plane calcaneal rotation had a negative influence (left: β=-0.573; right: β=-0.650) on ankle dorsiflexion. Sagittal plane rotations of the leg and calcaneus were positively correlated (left: r=0.84, P<0.001; right: r=0.80, P<0.001). During a partial squat, the calcaneus rotates forward. Simultaneous forward calcaneal rotation with ankle dorsiflexion reduces total ankle dorsiflexion angle. Rear foot posture is reoriented during a partial squat, allowing greater leg rotation in the sagittal plane. Segment rotations may provide greater insight into movement mechanics that cannot be explained via joint rotations alone. Copyright © 2012 Elsevier B.V. All rights reserved.

Optimal compliant-surface jumping: a multi-segment model of springboard standing jumps.

PubMed

Cheng, Kuangyou B; Hubbard, Mont

2005-09-01

A multi-segment model is used to investigate optimal compliant-surface jumping strategies and is applied to springboard standing jumps. The human model has four segments representing the feet, shanks, thighs, and trunk-head-arms. A rigid bar with a rotational spring on one end and a point mass on the other end (the tip) models the springboard. Board tip mass, length, and stiffness are functions of the fulcrum setting. Body segments and board tip are connected by frictionless hinge joints and are driven by joint torque actuators at the ankle, knee, and hip. One constant (maximum isometric torque) and three variable functions (of instantaneous joint angle, angular velocity, and activation level) determine each joint torque. Movement from a nearly straight motionless initial posture to jump takeoff is simulated. The objective is to find joint torque activation patterns during board contact so that jump height can be maximized. Minimum and maximum joint angles, rates of change of normalized activation levels, and contact duration are constrained. Optimal springboard jumping simulations can reasonably predict jumper vertical velocity and jump height. Qualitatively similar joint torque activation patterns are found over different fulcrum settings. Different from rigid-surface jumping where maximal activation is maintained until takeoff, joint activation decreases near takeoff in compliant-surface jumping. The fulcrum-height relations in experimental data were predicted by the models. However, lack of practice at non-preferred fulcrum settings might have caused less jump height than the models' prediction. Larger fulcrum numbers are beneficial for taller/heavier jumpers because they need more time to extend joints.

A general model for estimating lower extremity inertial properties of individuals with transtibial amputation.

PubMed

Ferris, Abbie E; Smith, Jeremy D; Heise, Gary D; Hinrichs, Richard N; Martin, Philip E

2017-03-21

Lower extremity joint moment magnitudes during swing are dependent on the inertial properties of the prosthesis and residual limb of individuals with transtibial amputation (TTA). Often, intact limb inertial properties (INTACT) are used for prosthetic limb values in an inverse dynamics model even though these values overestimate the amputated limb's inertial properties. The purpose of this study was to use subject-specific (SPECIFIC) measures of prosthesis inertial properties to generate a general model (GENERAL) for estimating TTA prosthesis inertial properties. Subject-specific mass, center of mass, and moment of inertia were determined for the shank and foot segments of the prosthesis (n=11) using an oscillation technique and reaction board. The GENERAL model was derived from the means of the SPECIFIC model. Mass and segment lengths are required GENERAL model inputs. Comparisons of segment inertial properties and joint moments during walking were made using three inertial models (unique sample; n=9): (1) SPECIFIC, (2) GENERAL, and (3) INTACT. Prosthetic shank inertial properties were significantly smaller with the SPECIFIC and GENERAL model than the INTACT model, but the SPECIFIC and GENERAL model did not statistically differ. Peak knee and hip joint moments during swing were significantly smaller for the SPECIFIC and GENERAL model compared with the INTACT model and were not significantly different between SPECIFIC and GENERAL models. When subject-specific measures are unavailable, using the GENERAL model produces a better estimate of prosthetic side inertial properties resulting in more accurate joint moment measurements for individuals with TTA than the INTACT model. Copyright © 2017 Elsevier Ltd. All rights reserved.

Infants and young children modeling method for numerical dosimetry studies: application to plane wave exposure

NASA Astrophysics Data System (ADS)

Dahdouh, S.; Varsier, N.; Nunez Ochoa, M. A.; Wiart, J.; Peyman, A.; Bloch, I.

2016-02-01

Numerical dosimetry studies require the development of accurate numerical 3D models of the human body. This paper proposes a novel method for building 3D heterogeneous young children models combining results obtained from a semi-automatic multi-organ segmentation algorithm and an anatomy deformation method. The data consist of 3D magnetic resonance images, which are first segmented to obtain a set of initial tissues. A deformation procedure guided by the segmentation results is then developed in order to obtain five young children models ranging from the age of 5 to 37 months. By constraining the deformation of an older child model toward a younger one using segmentation results, we assure the anatomical realism of the models. Using the proposed framework, five models, containing thirteen tissues, are built. Three of these models are used in a prospective dosimetry study to analyze young child exposure to radiofrequency electromagnetic fields. The results lean to show the existence of a relationship between age and whole body exposure. The results also highlight the necessity to specifically study and develop measurements of child tissues dielectric properties.

A Foot-Arch Parameter Measurement System Using a RGB-D Camera.

PubMed

Chun, Sungkuk; Kong, Sejin; Mun, Kyung-Ryoul; Kim, Jinwook

2017-08-04

The conventional method of measuring foot-arch parameters is highly dependent on the measurer's skill level, so accurate measurements are difficult to obtain. To solve this problem, we propose an autonomous geometric foot-arch analysis platform that is capable of capturing the sole of the foot and yields three foot-arch parameters: arch index (AI), arch width (AW) and arch height (AH). The proposed system captures 3D geometric and color data on the plantar surface of the foot in a static standing pose using a commercial RGB-D camera. It detects the region of the foot surface in contact with the footplate by applying the clustering and Markov random field (MRF)-based image segmentation methods. The system computes the foot-arch parameters by analyzing the 2/3D shape of the contact region. Validation experiments were carried out to assess the accuracy and repeatability of the system. The average errors for AI, AW, and AH estimation on 99 data collected from 11 subjects during 3 days were -0.17%, 0.95 mm, and 0.52 mm, respectively. Reliability and statistical analysis on the estimated foot-arch parameters, the robustness to the change of weights used in the MRF, the processing time were also performed to show the feasibility of the system.

A Foot-Arch Parameter Measurement System Using a RGB-D Camera

PubMed Central

Kong, Sejin; Mun, Kyung-Ryoul; Kim, Jinwook

2017-01-01

The conventional method of measuring foot-arch parameters is highly dependent on the measurer’s skill level, so accurate measurements are difficult to obtain. To solve this problem, we propose an autonomous geometric foot-arch analysis platform that is capable of capturing the sole of the foot and yields three foot-arch parameters: arch index (AI), arch width (AW) and arch height (AH). The proposed system captures 3D geometric and color data on the plantar surface of the foot in a static standing pose using a commercial RGB-D camera. It detects the region of the foot surface in contact with the footplate by applying the clustering and Markov random field (MRF)-based image segmentation methods. The system computes the foot-arch parameters by analyzing the 2/3D shape of the contact region. Validation experiments were carried out to assess the accuracy and repeatability of the system. The average errors for AI, AW, and AH estimation on 99 data collected from 11 subjects during 3 days were −0.17%, 0.95 mm, and 0.52 mm, respectively. Reliability and statistical analysis on the estimated foot-arch parameters, the robustness to the change of weights used in the MRF, the processing time were also performed to show the feasibility of the system. PMID:28777349

Non-driving intersegmental knee moments in cycling computed using a model that includes three-dimensional kinematics of the shank/foot and the effect of simplifying assumptions.

PubMed

Gregersen, Colin S; Hull, M L

2003-06-01

Assessing the importance of non-driving intersegmental knee moments (i.e. varus/valgus and internal/external axial moments) on over-use knee injuries in cycling requires the use of a three-dimensional (3-D) model to compute these loads. The objectives of this study were: (1) to develop a complete, 3-D model of the lower limb to calculate the 3-D knee loads during pedaling for a sample of the competitive cycling population, and (2) to examine the effects of simplifying assumptions on the calculations of the non-driving knee moments. The non-driving knee moments were computed using a complete 3-D model that allowed three rotational degrees of freedom at the knee joint, included the 3-D inertial loads of the shank/foot, and computed knee loads in a shank-fixed coordinate system. All input data, which included the 3-D segment kinematics and the six pedal load components, were collected from the right limb of 15 competitive cyclists while pedaling at 225 W and 90 rpm. On average, the peak varus and internal axial moments of 7.8 and 1.5 N m respectively occurred during the power stroke whereas the peak valgus and external axial moments of 8.1 and 2.5 N m respectively occurred during the recovery stroke. However, the non-driving knee moments were highly variable between subjects; the coefficients of variability in the peak values ranged from 38.7% to 72.6%. When it was assumed that the inertial loads of the shank/foot for motion out of the sagittal plane were zero, the root-mean-squared difference (RMSD) in the non-driving knee moments relative to those for the complete model was 12% of the peak varus/valgus moment and 25% of the peak axial moment. When it was also assumed that the knee joint was revolute with the flexion/extension axis perpendicular to the sagittal plane, the RMSD increased to 24% of the peak varus/valgus moment and 204% of the peak axial moment. Thus, the 3-D orientation of the shank segment has a major affect on the computation of the non-driving knee moments, while the inertial contributions to these loads for motions out of the sagittal plane are less important.

Multi-plug insole design to reduce peak plantar pressure on the diabetic foot during walking

PubMed Central

Actis, Ricardo L.; Ventura, Liliana B.; Lott, Donovan J.; Smith, Kirk E.; Commean, Paul K.; Hastings, Mary K.; Mueller, Michael J.

2009-01-01

There is evidence that appropriate footwear is an important factor in the prevention of foot pain in otherwise healthy people or foot ulcers in people with diabetes and peripheral neuropathy. A standard care for reducing forefoot plantar pressure is the utilization of orthotic devices such as total contact inserts (TCI) with therapeutic footwear. Most neuropathic ulcers occur under the metatarsal heads, and foot deformity combined with high localized plantar pressure, appear to be the most significant factors contributing to these ulcers. In this study, patient-specific finite element models of the second ray of the foot were developed to study the influence of TCI design on peak plantar pressure (PPP) under the metatarsal heads. A typical full contact insert was modified based on the results of finite element analyses, by inserting 4 mm diameter cylindrical plugs of softer material in the regions of high pressure. Validation of the numerical model was addressed by comparing the numerical results obtained by the finite element method with measured pressure distribution in the region of the metatarsal heads for a shoe and TCI condition. Two subjects, one with a history of forefoot pain and one with diabetes and peripheral neuropathy, were tested in the laboratory while wearing therapeutic shoes and customized inserts. The study showed that customized inserts with softer plugs distributed throughout the regions of high plantar pressure reduced the PPP over that of the TCI alone. This supports the outcome as predicted by the numerical model, without causing edge effects as reported by other investigators using different plug designs, and provides a greater degree of flexibility for customizing orthotic devices than current practice allows. PMID:18266017

Multi-plug insole design to reduce peak plantar pressure on the diabetic foot during walking.

PubMed

Actis, Ricardo L; Ventura, Liliana B; Lott, Donovan J; Smith, Kirk E; Commean, Paul K; Hastings, Mary K; Mueller, Michael J

2008-04-01

There is evidence that appropriate footwear is an important factor in the prevention of foot pain in otherwise healthy people or foot ulcers in people with diabetes and peripheral neuropathy. A standard care for reducing forefoot plantar pressure is the utilization of orthotic devices such as total contact inserts (TCI) with therapeutic footwear. Most neuropathic ulcers occur under the metatarsal heads, and foot deformity combined with high localized plantar pressure, appear to be the most significant factors contributing to these ulcers. In this study, patient-specific finite element models of the second ray of the foot were developed to study the influence of TCI design on peak plantar pressure (PPP) under the metatarsal heads. A typical full contact insert was modified based on the results of finite element analyses, by inserting 4 mm diameter cylindrical plugs of softer material in the regions of high pressure. Validation of the numerical model was addressed by comparing the numerical results obtained by the finite element method with measured pressure distribution in the region of the metatarsal heads for a shoe and TCI condition. Two subjects, one with a history of forefoot pain and one with diabetes and peripheral neuropathy, were tested in the laboratory while wearing therapeutic shoes and customized inserts. The study showed that customized inserts with softer plugs distributed throughout the regions of high plantar pressure reduced the PPP over that of the TCI alone. This supports the outcome as predicted by the numerical model, without causing edge effects as reported by other investigators using different plug designs, and provides a greater degree of flexibility for customizing orthotic devices than current practice allows.

Local SIMPLE multi-atlas-based segmentation applied to lung lobe detection on chest CT

NASA Astrophysics Data System (ADS)

Agarwal, M.; Hendriks, E. A.; Stoel, B. C.; Bakker, M. E.; Reiber, J. H. C.; Staring, M.

2012-02-01

For multi atlas-based segmentation approaches, a segmentation fusion scheme which considers local performance measures may be more accurate than a method which uses a global performance measure. We improve upon an existing segmentation fusion method called SIMPLE and extend it to be localized and suitable for multi-labeled segmentations. We demonstrate the algorithm performance on 23 CT scans of COPD patients using a leave-one- out experiment. Our algorithm performs significantly better (p < 0.01) than majority voting, STAPLE, and SIMPLE, with a median overlap of the fissure of 0.45, 0.48, 0.55 and 0.6 for majority voting, STAPLE, SIMPLE, and the proposed algorithm, respectively.

Earthquake cycle modeling of multi-segmented faults: dynamic rupture and ground motion simulation of the 1992 Mw 7.3 Landers earthquake.

NASA Astrophysics Data System (ADS)

Petukhin, A.; Galvez, P.; Somerville, P.; Ampuero, J. P.

2017-12-01

We perform earthquake cycle simulations to study the characteristics of source scaling relations and strong ground motions and in multi-segmented fault ruptures. For earthquake cycle modeling, a quasi-dynamic solver (QDYN, Luo et al, 2016) is used to nucleate events and the fully dynamic solver (SPECFEM3D, Galvez et al., 2014, 2016) is used to simulate earthquake ruptures. The Mw 7.3 Landers earthquake has been chosen as a target earthquake to validate our methodology. The SCEC fault geometry for the three-segmented Landers rupture is included and extended at both ends to a total length of 200 km. We followed the 2-D spatial correlated Dc distributions based on Hillers et. al. (2007) that associates Dc distribution with different degrees of fault maturity. The fault maturity is related to the variability of Dc on a microscopic scale. Large variations of Dc represents immature faults and lower variations of Dc represents mature faults. Moreover we impose a taper (a-b) at the fault edges and limit the fault depth to 15 km. Using these settings, earthquake cycle simulations are performed to nucleate seismic events on different sections of the fault, and dynamic rupture modeling is used to propagate the ruptures. The fault segmentation brings complexity into the rupture process. For instance, the change of strike between fault segments enhances strong variations of stress. In fact, Oglesby and Mai (2012) show the normal stress varies from positive (clamping) to negative (unclamping) between fault segments, which leads to favorable or unfavorable conditions for rupture growth. To replicate these complexities and the effect of fault segmentation in the rupture process, we perform earthquake cycles with dynamic rupture modeling and generate events similar to the Mw 7.3 Landers earthquake. We extract the asperities of these events and analyze the scaling relations between rupture area, average slip and combined area of asperities versus moment magnitude. Finally, the simulated ground motions will be validated by comparison of simulated response spectra with recorded response spectra and with response spectra from ground motion prediction models. This research is sponsored by the Japan Nuclear Regulation Authority.

The Second Stage of a Saturn V Ready For Test

NASA Technical Reports Server (NTRS)

1970-01-01

This Saturn V S-II (second) stage is being lifted into position for a test at the Vehicle Assembly Building at the Kennedy Space Center. When the Saturn V booster stage (S-IC) burned out and dropped away, power for the Saturn was provided by the 82-foot-long and 33-foot-diameter S-II stage. Developed by the Space Division of North American Aviation under the direction of the Marshall Space Flight Center, the stage utilized five J-2 engines, each producing 200,000 pounds of thrust. The engines used liquid oxygen and liquid hydrogen as propellants. The towering 363-foot Saturn V was a multi-stage, multi-engine launch vehicle standing taller than the Statue of Liberty. Altogether, the Saturn V engines produced as much power as 85 Hoover Dams.

Joint multi-object registration and segmentation of left and right cardiac ventricles in 4D cine MRI

NASA Astrophysics Data System (ADS)

Ehrhardt, Jan; Kepp, Timo; Schmidt-Richberg, Alexander; Handels, Heinz

2014-03-01

The diagnosis of cardiac function based on cine MRI requires the segmentation of cardiac structures in the images, but the problem of automatic cardiac segmentation is still open, due to the imaging characteristics of cardiac MR images and the anatomical variability of the heart. In this paper, we present a variational framework for joint segmentation and registration of multiple structures of the heart. To enable the simultaneous segmentation and registration of multiple objects, a shape prior term is introduced into a region competition approach for multi-object level set segmentation. The proposed algorithm is applied for simultaneous segmentation of the myocardium as well as the left and right ventricular blood pool in short axis cine MRI images. Two experiments are performed: first, intra-patient 4D segmentation with a given initial segmentation for one time-point in a 4D sequence, and second, a multi-atlas segmentation strategy is applied to unseen patient data. Evaluation of segmentation accuracy is done by overlap coefficients and surface distances. An evaluation based on clinical 4D cine MRI images of 25 patients shows the benefit of the combined approach compared to sole registration and sole segmentation.

Estimating the concentration of gold nanoparticles incorporated on natural rubber membranes using multi-level starlet optimal segmentation

NASA Astrophysics Data System (ADS)

de Siqueira, A. F.; Cabrera, F. C.; Pagamisse, A.; Job, A. E.

2014-12-01

This study consolidates multi-level starlet segmentation (MLSS) and multi-level starlet optimal segmentation (MLSOS) techniques for photomicrograph segmentation, based on starlet wavelet detail levels to separate areas of interest in an input image. Several segmentation levels can be obtained using MLSS; after that, Matthews correlation coefficient is used to choose an optimal segmentation level, giving rise to MLSOS. In this paper, MLSOS is employed to estimate the concentration of gold nanoparticles with diameter around 47 nm, reduced on natural rubber membranes. These samples were used for the construction of SERS/SERRS substrates and in the study of the influence of natural rubber membranes with incorporated gold nanoparticles on the physiology of Leishmania braziliensis. Precision, recall, and accuracy are used to evaluate the segmentation performance, and MLSOS presents an accuracy greater than 88 % for this application.

Bayesian segmentation of atrium wall using globally-optimal graph cuts on 3D meshes.

PubMed

Veni, Gopalkrishna; Fu, Zhisong; Awate, Suyash P; Whitaker, Ross T

2013-01-01

Efficient segmentation of the left atrium (LA) wall from delayed enhancement MRI is challenging due to inconsistent contrast, combined with noise, and high variation in atrial shape and size. We present a surface-detection method that is capable of extracting the atrial wall by computing an optimal a-posteriori estimate. This estimation is done on a set of nested meshes, constructed from an ensemble of segmented training images, and graph cuts on an associated multi-column, proper-ordered graph. The graph/mesh is a part of a template/model that has an associated set of learned intensity features. When this mesh is overlaid onto a test image, it produces a set of costs which lead to an optimal segmentation. The 3D mesh has an associated weighted, directed multi-column graph with edges that encode smoothness and inter-surface penalties. Unlike previous graph-cut methods that impose hard constraints on the surface properties, the proposed method follows from a Bayesian formulation resulting in soft penalties on spatial variation of the cuts through the mesh. The novelty of this method also lies in the construction of proper-ordered graphs on complex shapes for choosing among distinct classes of base shapes for automatic LA segmentation. We evaluate the proposed segmentation framework on simulated and clinical cardiac MRI.

A multi-scale segmentation approach to filling gaps in Landsat ETM+ SLC-off images

USGS Publications Warehouse

Maxwell, S.K.; Schmidt, Gail L.; Storey, James C.

2007-01-01

On 31 May 2003, the Landsat Enhanced Thematic Plus (ETM+) Scan Line Corrector (SLC) failed, causing the scanning pattern to exhibit wedge-shaped scan-to-scan gaps. We developed a method that uses coincident spectral data to fill the image gaps. This method uses a multi-scale segment model, derived from a previous Landsat SLC-on image (image acquired prior to the SLC failure), to guide the spectral interpolation across the gaps in SLC-off images (images acquired after the SLC failure). This paper describes the process used to generate the segment model, provides details of the gap-fill algorithm used in deriving the segment-based gap-fill product, and presents the results of the gap-fill process applied to grassland, cropland, and forest landscapes. Our results indicate this product will be useful for a wide variety of applications, including regional-scale studies, general land cover mapping (e.g. forest, urban, and grass), crop-specific mapping and monitoring, and visual assessments. Applications that need to be cautious when using pixels in the gap areas include any applications that require per-pixel accuracy, such as urban characterization or impervious surface mapping, applications that use texture to characterize landscape features, and applications that require accurate measurements of small or narrow landscape features such as roads, farmsteads, and riparian areas.

Design and Experimental Validation of a Simple Controller for a Multi-Segment Magnetic Crawler Robot

DTIC Science & Technology

2015-04-01

Ave, Cambridge, MA USA 02139; bSpace and Naval Warfare (SPAWAR) Systems Center Pacific, San Diego, CA USA 92152 ABSTRACT A novel, multi-segmented...high-level, autonomous control computer. A low-level, embedded microcomputer handles the commands to the driving motors. This paper presents the...to be demonstrated.14 The Unmanned Systems Group at SPAWAR Systems Center Pacific has developed a multi-segment magnetic crawler robot (MSMR

Label fusion based brain MR image segmentation via a latent selective model

NASA Astrophysics Data System (ADS)

Liu, Gang; Guo, Xiantang; Zhu, Kai; Liao, Hengxu

2018-04-01

Multi-atlas segmentation is an effective approach and increasingly popular for automatically labeling objects of interest in medical images. Recently, segmentation methods based on generative models and patch-based techniques have become the two principal branches of label fusion. However, these generative models and patch-based techniques are only loosely related, and the requirement for higher accuracy, faster segmentation, and robustness is always a great challenge. In this paper, we propose novel algorithm that combines the two branches using global weighted fusion strategy based on a patch latent selective model to perform segmentation of specific anatomical structures for human brain magnetic resonance (MR) images. In establishing this probabilistic model of label fusion between the target patch and patch dictionary, we explored the Kronecker delta function in the label prior, which is more suitable than other models, and designed a latent selective model as a membership prior to determine from which training patch the intensity and label of the target patch are generated at each spatial location. Because the image background is an equally important factor for segmentation, it is analyzed in label fusion procedure and we regard it as an isolated label to keep the same privilege between the background and the regions of interest. During label fusion with the global weighted fusion scheme, we use Bayesian inference and expectation maximization algorithm to estimate the labels of the target scan to produce the segmentation map. Experimental results indicate that the proposed algorithm is more accurate and robust than the other segmentation methods.

Deep convolutional neural network and 3D deformable approach for tissue segmentation in musculoskeletal magnetic resonance imaging.

PubMed

Liu, Fang; Zhou, Zhaoye; Jang, Hyungseok; Samsonov, Alexey; Zhao, Gengyan; Kijowski, Richard

2018-04-01

To describe and evaluate a new fully automated musculoskeletal tissue segmentation method using deep convolutional neural network (CNN) and three-dimensional (3D) simplex deformable modeling to improve the accuracy and efficiency of cartilage and bone segmentation within the knee joint. A fully automated segmentation pipeline was built by combining a semantic segmentation CNN and 3D simplex deformable modeling. A CNN technique called SegNet was applied as the core of the segmentation method to perform high resolution pixel-wise multi-class tissue classification. The 3D simplex deformable modeling refined the output from SegNet to preserve the overall shape and maintain a desirable smooth surface for musculoskeletal structure. The fully automated segmentation method was tested using a publicly available knee image data set to compare with currently used state-of-the-art segmentation methods. The fully automated method was also evaluated on two different data sets, which include morphological and quantitative MR images with different tissue contrasts. The proposed fully automated segmentation method provided good segmentation performance with segmentation accuracy superior to most of state-of-the-art methods in the publicly available knee image data set. The method also demonstrated versatile segmentation performance on both morphological and quantitative musculoskeletal MR images with different tissue contrasts and spatial resolutions. The study demonstrates that the combined CNN and 3D deformable modeling approach is useful for performing rapid and accurate cartilage and bone segmentation within the knee joint. The CNN has promising potential applications in musculoskeletal imaging. Magn Reson Med 79:2379-2391, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Random walks based multi-image segmentation: Quasiconvexity results and GPU-based solutions

PubMed Central

Collins, Maxwell D.; Xu, Jia; Grady, Leo; Singh, Vikas

2012-01-01

We recast the Cosegmentation problem using Random Walker (RW) segmentation as the core segmentation algorithm, rather than the traditional MRF approach adopted in the literature so far. Our formulation is similar to previous approaches in the sense that it also permits Cosegmentation constraints (which impose consistency between the extracted objects from ≥ 2 images) using a nonparametric model. However, several previous nonparametric cosegmentation methods have the serious limitation that they require adding one auxiliary node (or variable) for every pair of pixels that are similar (which effectively limits such methods to describing only those objects that have high entropy appearance models). In contrast, our proposed model completely eliminates this restrictive dependence –the resulting improvements are quite significant. Our model further allows an optimization scheme exploiting quasiconvexity for model-based segmentation with no dependence on the scale of the segmented foreground. Finally, we show that the optimization can be expressed in terms of linear algebra operations on sparse matrices which are easily mapped to GPU architecture. We provide a highly specialized CUDA library for Cosegmentation exploiting this special structure, and report experimental results showing these advantages. PMID:25278742

3D multi-scale FCN with random modality voxel dropout learning for Intervertebral Disc Localization and Segmentation from Multi-modality MR Images.

PubMed

Li, Xiaomeng; Dou, Qi; Chen, Hao; Fu, Chi-Wing; Qi, Xiaojuan; Belavý, Daniel L; Armbrecht, Gabriele; Felsenberg, Dieter; Zheng, Guoyan; Heng, Pheng-Ann

2018-04-01

Intervertebral discs (IVDs) are small joints that lie between adjacent vertebrae. The localization and segmentation of IVDs are important for spine disease diagnosis and measurement quantification. However, manual annotation is time-consuming and error-prone with limited reproducibility, particularly for volumetric data. In this work, our goal is to develop an automatic and accurate method based on fully convolutional networks (FCN) for the localization and segmentation of IVDs from multi-modality 3D MR data. Compared with single modality data, multi-modality MR images provide complementary contextual information, which contributes to better recognition performance. However, how to effectively integrate such multi-modality information to generate accurate segmentation results remains to be further explored. In this paper, we present a novel multi-scale and modality dropout learning framework to locate and segment IVDs from four-modality MR images. First, we design a 3D multi-scale context fully convolutional network, which processes the input data in multiple scales of context and then merges the high-level features to enhance the representation capability of the network for handling the scale variation of anatomical structures. Second, to harness the complementary information from different modalities, we present a random modality voxel dropout strategy which alleviates the co-adaption issue and increases the discriminative capability of the network. Our method achieved the 1st place in the MICCAI challenge on automatic localization and segmentation of IVDs from multi-modality MR images, with a mean segmentation Dice coefficient of 91.2% and a mean localization error of 0.62 mm. We further conduct extensive experiments on the extended dataset to validate our method. We demonstrate that the proposed modality dropout strategy with multi-modality images as contextual information improved the segmentation accuracy significantly. Furthermore, experiments conducted on extended data collected from two different time points demonstrate the efficacy of our method on tracking the morphological changes in a longitudinal study. Copyright © 2018 Elsevier B.V. All rights reserved.

A portable system for foot biomechanical analysis during gait.

PubMed

Samson, William; Sanchez, Stéphane; Salvia, Patrick; Jan, Serge Van Sint; Feipel, Véronique

2014-07-01

Modeling the foot is challenging due to its complex structure compared to most other body segments. To analyze the biomechanics of the foot, portable devices have been designed to allow measurement of temporal, spatial, and pedobarographic parameters. The goal of this study was to design and evaluate a portable system for kinematic and dynamic analysis of the foot during gait. This device consisted of a force plate synchronized with four cameras and integrated into a walkway. The complete system can be packaged for transportation. First, the measurement system was assessed using reference objects to evaluate accuracy and precision. Second, nine healthy participants were assessed during gait trials using both the portable and Vicon systems (coupled with a force plate). The ankle and metatarsophalangeal (MP) joint angles and moments were computed, as well as the ground reaction force (GRF). The intra- and inter-subject variability was analyzed for both systems, as well as the inter-system variation. The accuracy and precision were, respectively 0.4 mm and 0.4 mm for linear values and 0.5° and 0.6° for angular values. The variability of the portable and Vicon systems were similar (i.e., the inter-system variability never exceeded 2.1°, 0.081 Nmkg(-1) and 0.267 Nkg(-1) for the angles, moments and GRF, respectively). The inter-system differences were less than the inter-subject variability and similar to the intra-subject variability. Consequently, the portable system was considered satisfactory for biomechanical analysis of the foot, outside of a motion analysis laboratory. Copyright © 2014 Elsevier B.V. All rights reserved.

LINKS: learning-based multi-source IntegratioN frameworK for Segmentation of infant brain images.

PubMed

Wang, Li; Gao, Yaozong; Shi, Feng; Li, Gang; Gilmore, John H; Lin, Weili; Shen, Dinggang

2015-03-01

Segmentation of infant brain MR images is challenging due to insufficient image quality, severe partial volume effect, and ongoing maturation and myelination processes. In the first year of life, the image contrast between white and gray matters of the infant brain undergoes dramatic changes. In particular, the image contrast is inverted around 6-8months of age, and the white and gray matter tissues are isointense in both T1- and T2-weighted MR images and thus exhibit the extremely low tissue contrast, which poses significant challenges for automated segmentation. Most previous studies used multi-atlas label fusion strategy, which has the limitation of equally treating the different available image modalities and is often computationally expensive. To cope with these limitations, in this paper, we propose a novel learning-based multi-source integration framework for segmentation of infant brain images. Specifically, we employ the random forest technique to effectively integrate features from multi-source images together for tissue segmentation. Here, the multi-source images include initially only the multi-modality (T1, T2 and FA) images and later also the iteratively estimated and refined tissue probability maps of gray matter, white matter, and cerebrospinal fluid. Experimental results on 119 infants show that the proposed method achieves better performance than other state-of-the-art automated segmentation methods. Further validation was performed on the MICCAI grand challenge and the proposed method was ranked top among all competing methods. Moreover, to alleviate the possible anatomical errors, our method can also be combined with an anatomically-constrained multi-atlas labeling approach for further improving the segmentation accuracy. Copyright © 2014 Elsevier Inc. All rights reserved.

LINKS: Learning-based multi-source IntegratioN frameworK for Segmentation of infant brain images

PubMed Central

Wang, Li; Gao, Yaozong; Shi, Feng; Li, Gang; Gilmore, John H.; Lin, Weili; Shen, Dinggang

2014-01-01

Segmentation of infant brain MR images is challenging due to insufficient image quality, severe partial volume effect, and ongoing maturation and myelination processes. In the first year of life, the image contrast between white and gray matters of the infant brain undergoes dramatic changes. In particular, the image contrast is inverted around 6-8 months of age, and the white and gray matter tissues are isointense in both T1- and T2-weighted MR images and thus exhibit the extremely low tissue contrast, which poses significant challenges for automated segmentation. Most previous studies used multi-atlas label fusion strategy, which has the limitation of equally treating the different available image modalities and is often computationally expensive. To cope with these limitations, in this paper, we propose a novel learning-based multi-source integration framework for segmentation of infant brain images. Specifically, we employ the random forest technique to effectively integrate features from multi-source images together for tissue segmentation. Here, the multi-source images include initially only the multi-modality (T1, T2 and FA) images and later also the iteratively estimated and refined tissue probability maps of gray matter, white matter, and cerebrospinal fluid. Experimental results on 119 infants show that the proposed method achieves better performance than other state-of-the-art automated segmentation methods. Further validation was performed on the MICCAI grand challenge and the proposed method was ranked top among all competing methods. Moreover, to alleviate the possible anatomical errors, our method can also be combined with an anatomically-constrained multi-atlas labeling approach for further improving the segmentation accuracy. PMID:25541188

Two-stage atlas subset selection in multi-atlas based image segmentation.

PubMed

Zhao, Tingting; Ruan, Dan

2015-06-01

Fast growing access to large databases and cloud stored data presents a unique opportunity for multi-atlas based image segmentation and also presents challenges in heterogeneous atlas quality and computation burden. This work aims to develop a novel two-stage method tailored to the special needs in the face of large atlas collection with varied quality, so that high-accuracy segmentation can be achieved with low computational cost. An atlas subset selection scheme is proposed to substitute a significant portion of the computationally expensive full-fledged registration in the conventional scheme with a low-cost alternative. More specifically, the authors introduce a two-stage atlas subset selection method. In the first stage, an augmented subset is obtained based on a low-cost registration configuration and a preliminary relevance metric; in the second stage, the subset is further narrowed down to a fusion set of desired size, based on full-fledged registration and a refined relevance metric. An inference model is developed to characterize the relationship between the preliminary and refined relevance metrics, and a proper augmented subset size is derived to ensure that the desired atlases survive the preliminary selection with high probability. The performance of the proposed scheme has been assessed with cross validation based on two clinical datasets consisting of manually segmented prostate and brain magnetic resonance images, respectively. The proposed scheme demonstrates comparable end-to-end segmentation performance as the conventional single-stage selection method, but with significant computation reduction. Compared with the alternative computation reduction method, their scheme improves the mean and medium Dice similarity coefficient value from (0.74, 0.78) to (0.83, 0.85) and from (0.82, 0.84) to (0.95, 0.95) for prostate and corpus callosum segmentation, respectively, with statistical significance. The authors have developed a novel two-stage atlas subset selection scheme for multi-atlas based segmentation. It achieves good segmentation accuracy with significantly reduced computation cost, making it a suitable configuration in the presence of extensive heterogeneous atlases.

A universal approach to determine footfall timings from kinematics of a single foot marker in hoofed animals

PubMed Central

Clayton, Hilary M.

2015-01-01

The study of animal movement commonly requires the segmentation of continuous data streams into individual strides. The use of forceplates and foot-mounted accelerometers readily allows the detection of the foot-on and foot-off events that define a stride. However, when relying on optical methods such as motion capture, there is lack of validated robust, universally applicable stride event detection methods. To date, no method has been validated for movement on a circle, while algorithms are commonly specific to front/hind limbs or gait. In this study, we aimed to develop and validate kinematic stride segmentation methods applicable to movement on straight line and circle at walk and trot, which exclusively rely on a single, dorsal hoof marker. The advantage of such marker placement is the robustness to marker loss and occlusion. Eight horses walked and trotted on a straight line and in a circle over an array of multiple forceplates. Kinetic events were detected based on the vertical force profile and used as the reference values. Kinematic events were detected based on displacement, velocity or acceleration signals of the dorsal hoof marker depending on the algorithm using (i) defined thresholds associated with derived movement signals and (ii) specific events in the derived movement signals. Method comparison was performed by calculating limits of agreement, accuracy, between-horse precision and within-horse precision based on differences between kinetic and kinematic event. In addition, we examined the effect of force thresholds ranging from 50 to 150 N on the timings of kinetic events. The two approaches resulted in very good and comparable performance: of the 3,074 processed footfall events, 95% of individual foot on and foot off events differed by no more than 26 ms from the kinetic event, with average accuracy between −11 and 10 ms and average within- and between horse precision ≤8 ms. While the event-based method may be less likely to suffer from scaling effects, on soft ground the threshold-based method may prove more valuable. While we found that use of velocity thresholds for foot on detection results in biased event estimates for the foot on the inside of the circle at trot, adjusting thresholds for this condition negated the effect. For the final four algorithms, we found no noteworthy bias between conditions or between front- and hind-foot timings. Different force thresholds in the range of 50 to 150 N had the greatest systematic effect on foot-off estimates in the hind limbs (up to on average 16 ms per condition), being greater than the effect on foot-on estimates or foot-off estimates in the forelimbs (up to on average ±7 ms per condition). PMID:26157641

Relaxation dynamics of internal segments of DNA chains in nanochannels

NASA Astrophysics Data System (ADS)

Jain, Aashish; Muralidhar, Abhiram; Dorfman, Kevin; Dorfman Group Team

We will present relaxation dynamics of internal segments of a DNA chain confined in nanochannel. The results have direct application in genome mapping technology, where long DNA molecules containing sequence-specific fluorescent probes are passed through an array of nanochannels to linearize them, and then the distances between these probes (the so-called ``DNA barcode'') are measured. The relaxation dynamics of internal segments set the experimental error due to dynamic fluctuations. We developed a multi-scale simulation algorithm, combining a Pruned-Enriched Rosenbluth Method (PERM) simulation of a discrete wormlike chain model with hard spheres with Brownian dynamics (BD) simulations of a bead-spring chain. Realistic parameters such as the bead friction coefficient and spring force law parameters are obtained from PERM simulations and then mapped onto the bead-spring model. The BD simulations are carried out to obtain the extension autocorrelation functions of various segments, which furnish their relaxation times. Interestingly, we find that (i) corner segments relax faster than the center segments and (ii) relaxation times of corner segments do not depend on the contour length of DNA chain, whereas the relaxation times of center segments increase linearly with DNA chain size.

Multi-Atlas Segmentation using Partially Annotated Data: Methods and Annotation Strategies.

PubMed

Koch, Lisa M; Rajchl, Martin; Bai, Wenjia; Baumgartner, Christian F; Tong, Tong; Passerat-Palmbach, Jonathan; Aljabar, Paul; Rueckert, Daniel

2017-08-22

Multi-atlas segmentation is a widely used tool in medical image analysis, providing robust and accurate results by learning from annotated atlas datasets. However, the availability of fully annotated atlas images for training is limited due to the time required for the labelling task. Segmentation methods requiring only a proportion of each atlas image to be labelled could therefore reduce the workload on expert raters tasked with annotating atlas images. To address this issue, we first re-examine the labelling problem common in many existing approaches and formulate its solution in terms of a Markov Random Field energy minimisation problem on a graph connecting atlases and the target image. This provides a unifying framework for multi-atlas segmentation. We then show how modifications in the graph configuration of the proposed framework enable the use of partially annotated atlas images and investigate different partial annotation strategies. The proposed method was evaluated on two Magnetic Resonance Imaging (MRI) datasets for hippocampal and cardiac segmentation. Experiments were performed aimed at (1) recreating existing segmentation techniques with the proposed framework and (2) demonstrating the potential of employing sparsely annotated atlas data for multi-atlas segmentation.

Foot roll-over evaluation based on 3D dynamic foot scan.

PubMed

Samson, William; Van Hamme, Angèle; Sanchez, Stéphane; Chèze, Laurence; Van Sint Jan, Serge; Feipel, Véronique

2014-01-01

Foot roll-over is commonly analyzed to evaluate gait pathologies. The current study utilized a dynamic foot scanner (DFS) to analyze foot roll-over. The right feet of ten healthy subjects were assessed during gait trials with a DFS system integrated into a walkway. A foot sole picture was computed by vertically projecting points from the 3D foot shape which were lower than a threshold height of 15 mm. A 'height' value of these projected points was determined; corresponding to the initial vertical coordinates prior to projection. Similar to pedobarographic analysis, the foot sole picture was segmented into anatomical regions of interest (ROIs) to process mean height (average of height data by ROI) and projected surface (area of the projected foot sole by ROI). Results showed that these variables evolved differently to plantar pressure data previously reported in the literature, mainly due to the specificity of each physical quantity (millimeters vs Pascals). Compared to plantar pressure data arising from surface contact by the foot, the current method takes into account the whole plantar aspect of the foot, including the parts that do not make contact with the support surface. The current approach using height data could contribute to a better understanding of specific aspects of foot motion during walking, such as plantar arch height and the windlass mechanism. Results of this study show the underlying method is reliable. Further investigation is required to validate the DFS measurements within a clinical context, prior to implementation into clinical practice. Copyright © 2013 Elsevier B.V. All rights reserved.

Automatic multi-organ segmentation using learning-based segmentation and level set optimization.

PubMed

Kohlberger, Timo; Sofka, Michal; Zhang, Jingdan; Birkbeck, Neil; Wetzl, Jens; Kaftan, Jens; Declerck, Jérôme; Zhou, S Kevin

2011-01-01

We present a novel generic segmentation system for the fully automatic multi-organ segmentation from CT medical images. Thereby we combine the advantages of learning-based approaches on point cloud-based shape representation, such a speed, robustness, point correspondences, with those of PDE-optimization-based level set approaches, such as high accuracy and the straightforward prevention of segment overlaps. In a benchmark on 10-100 annotated datasets for the liver, the lungs, and the kidneys we show that the proposed system yields segmentation accuracies of 1.17-2.89 mm average surface errors. Thereby the level set segmentation (which is initialized by the learning-based segmentations) contributes with an 20%-40% increase in accuracy.

Joint Multi-Leaf Segmentation, Alignment, and Tracking for Fluorescence Plant Videos.

PubMed

Yin, Xi; Liu, Xiaoming; Chen, Jin; Kramer, David M

2018-06-01

This paper proposes a novel framework for fluorescence plant video processing. The plant research community is interested in the leaf-level photosynthetic analysis within a plant. A prerequisite for such analysis is to segment all leaves, estimate their structures, and track them over time. We identify this as a joint multi-leaf segmentation, alignment, and tracking problem. First, leaf segmentation and alignment are applied on the last frame of a plant video to find a number of well-aligned leaf candidates. Second, leaf tracking is applied on the remaining frames with leaf candidate transformation from the previous frame. We form two optimization problems with shared terms in their objective functions for leaf alignment and tracking respectively. A quantitative evaluation framework is formulated to evaluate the performance of our algorithm with four metrics. Two models are learned to predict the alignment accuracy and detect tracking failure respectively in order to provide guidance for subsequent plant biology analysis. The limitation of our algorithm is also studied. Experimental results show the effectiveness, efficiency, and robustness of the proposed method.

Automated brain tumor segmentation using spatial accuracy-weighted hidden Markov Random Field.

PubMed

Nie, Jingxin; Xue, Zhong; Liu, Tianming; Young, Geoffrey S; Setayesh, Kian; Guo, Lei; Wong, Stephen T C

2009-09-01

A variety of algorithms have been proposed for brain tumor segmentation from multi-channel sequences, however, most of them require isotropic or pseudo-isotropic resolution of the MR images. Although co-registration and interpolation of low-resolution sequences, such as T2-weighted images, onto the space of the high-resolution image, such as T1-weighted image, can be performed prior to the segmentation, the results are usually limited by partial volume effects due to interpolation of low-resolution images. To improve the quality of tumor segmentation in clinical applications where low-resolution sequences are commonly used together with high-resolution images, we propose the algorithm based on Spatial accuracy-weighted Hidden Markov random field and Expectation maximization (SHE) approach for both automated tumor and enhanced-tumor segmentation. SHE incorporates the spatial interpolation accuracy of low-resolution images into the optimization procedure of the Hidden Markov Random Field (HMRF) to segment tumor using multi-channel MR images with different resolutions, e.g., high-resolution T1-weighted and low-resolution T2-weighted images. In experiments, we evaluated this algorithm using a set of simulated multi-channel brain MR images with known ground-truth tissue segmentation and also applied it to a dataset of MR images obtained during clinical trials of brain tumor chemotherapy. The results show that more accurate tumor segmentation results can be obtained by comparing with conventional multi-channel segmentation algorithms.

Collaborative Response and Recovery from a Foot-and-Mouth Disease Animal Health Emergency: Supporting Decision Making in a Complex Environment with Multiple Stakeholders

DTIC Science & Technology

2013-12-01

RESPONSE AND RECOVERY FROM A FOOT-AND- MOUTH DISEASE ANIMAL HEALTH EMERGENCY: SUPPORTING DECISION MAKING IN A COMPLEX ENVIRONMENT WITH MULTIPLE...Thesis 4. TITLE AND SUBTITLE COLLABORATIVE RESPONSE AND RECOVERY FROM A FOOT-AND- MOUTH DISEASE ANIMAL HEALTH EMERGENCY: SUPPORTING DECISION MAKING...200 words ) This thesis recommends ways to support decision makers who must operate within the multi-stakeholder complex situation of response and

3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study.

PubMed

Dolz, Jose; Desrosiers, Christian; Ben Ayed, Ismail

2018-04-15

This study investigates a 3D and fully convolutional neural network (CNN) for subcortical brain structure segmentation in MRI. 3D CNN architectures have been generally avoided due to their computational and memory requirements during inference. We address the problem via small kernels, allowing deeper architectures. We further model both local and global context by embedding intermediate-layer outputs in the final prediction, which encourages consistency between features extracted at different scales and embeds fine-grained information directly in the segmentation process. Our model is efficiently trained end-to-end on a graphics processing unit (GPU), in a single stage, exploiting the dense inference capabilities of fully CNNs. We performed comprehensive experiments over two publicly available datasets. First, we demonstrate a state-of-the-art performance on the ISBR dataset. Then, we report a large-scale multi-site evaluation over 1112 unregistered subject datasets acquired from 17 different sites (ABIDE dataset), with ages ranging from 7 to 64 years, showing that our method is robust to various acquisition protocols, demographics and clinical factors. Our method yielded segmentations that are highly consistent with a standard atlas-based approach, while running in a fraction of the time needed by atlas-based methods and avoiding registration/normalization steps. This makes it convenient for massive multi-site neuroanatomical imaging studies. To the best of our knowledge, our work is the first to study subcortical structure segmentation on such large-scale and heterogeneous data. Copyright © 2017 Elsevier Inc. All rights reserved.

a Fast Segmentation Algorithm for C-V Model Based on Exponential Image Sequence Generation

NASA Astrophysics Data System (ADS)

Hu, J.; Lu, L.; Xu, J.; Zhang, J.

2017-09-01

For the island coastline segmentation, a fast segmentation algorithm for C-V model method based on exponential image sequence generation is proposed in this paper. The exponential multi-scale C-V model with level set inheritance and boundary inheritance is developed. The main research contributions are as follows: 1) the problems of the "holes" and "gaps" are solved when extraction coastline through the small scale shrinkage, low-pass filtering and area sorting of region. 2) the initial value of SDF (Signal Distance Function) and the level set are given by Otsu segmentation based on the difference of reflection SAR on land and sea, which are finely close to the coastline. 3) the computational complexity of continuous transition are successfully reduced between the different scales by the SDF and of level set inheritance. Experiment results show that the method accelerates the acquisition of initial level set formation, shortens the time of the extraction of coastline, at the same time, removes the non-coastline body part and improves the identification precision of the main body coastline, which automates the process of coastline segmentation.

Plasmon-enhanced versatile optical nonlinearities in a Au-Ag-Au multi-segmental hybrid structure.

PubMed

Yao, Lin-Hua; Zhang, Jun-Pei; Dai, Hong-Wei; Wang, Ming-Shan; Zhang, Lu-Man; Wang, Xia; Han, Jun-Bo

2018-06-27

A Au-Ag-Au multi-segmental hybrid structure has been synthesized by using an electrodeposition method based on an anodic aluminum oxide (AAO) membrane. The third-order optical nonlinearities, second harmonic generation (SHG) and photoluminescence (PL) properties containing ultrafast supercontinuum generation and plasmon mediated thermal emission have been investigated. Significant optical enhancements have been obtained near surface plasmon resonance wavelength in all the abovementioned nonlinear processes. Comparative studies between the Au-Ag-Au multi-segmental hybrid structure and the corresponding single-component Au and Ag hybrid structures demonstrate that the Au-Ag-Au multi-segmental hybrid structure has much larger optical nonlinearities than its counterparts. These results demonstrate that the Au-Ag-Au hybrid structure is a promising candidate for applications in plasmonic devices and enhancement substrates.

Segmentation and object-oriented classification of wetlands in a karst Florida landscape using multi-season Landsat-7 ETM+ Imagery

EPA Science Inventory

Segmentation and object-oriented processing of single-season and multi-season Landsat-7 ETM+ data was utilized for the classification of wetlands in a 1560 km2 study area of north central Florida. This segmentation and object-oriented classification outperformed the traditional ...

Binary Programming Models of Spatial Pattern Recognition: Applications in Remote Sensing Image Analysis

DTIC Science & Technology

1991-12-01

9 2.6.1 Multi-Shape Detection. .. .. .. .. .. .. ...... 9 Page 2.6.2 Line Segment Extraction and Re-Combination.. 9 2.6.3 Planimetric Feature... Extraction ............... 10 2.6.4 Line Segment Extraction From Statistical Texture Analysis .............................. 11 2.6.5 Edge Following as Graph...image after image, could benefit clue to the fact that major spatial characteristics of subregions could be extracted , and minor spatial changes could be

From the diabetic foot ulcer and beyond: how do foot infections spread in patients with diabetes?

PubMed Central

Aragón-Sánchez, Javier; Lázaro-Martínez, Jose Luis; Pulido-Duque, Juan; Maynar, Manuel

2012-01-01

A diabetic foot infection is usually the result of a pre-existing foot ulceration and is the leading cause of lower extremity amputation in patients with diabetes. It is widely accepted that diabetic foot infections may be challenging to treat for several reasons. The devastating effects of hyperglycemia on host defense, ischemia, multi-drug resistant bacteria and spreading of infection through the foot may complicate the course of diabetic foot infections. Understanding the ways in which infections spread through the diabetic foot is a pivotal factor in order to decide the best approach for the patient's treatment. The ways in which infections spread can be explained by the anatomical division of the foot into compartments, the tendons included in the compartments, the initial location of the point of entry of the infection and the type of infection that the patient has. The aim of this paper is to further comment on the existed and proposed anatomical principles of the spread of infection through the foot in patients with diabetes. PMID:23050067

Simulation of brain tumors in MR images for evaluation of segmentation efficacy.

PubMed

Prastawa, Marcel; Bullitt, Elizabeth; Gerig, Guido

2009-04-01

Obtaining validation data and comparison metrics for segmentation of magnetic resonance images (MRI) are difficult tasks due to the lack of reliable ground truth. This problem is even more evident for images presenting pathology, which can both alter tissue appearance through infiltration and cause geometric distortions. Systems for generating synthetic images with user-defined degradation by noise and intensity inhomogeneity offer the possibility for testing and comparison of segmentation methods. Such systems do not yet offer simulation of sufficiently realistic looking pathology. This paper presents a system that combines physical and statistical modeling to generate synthetic multi-modal 3D brain MRI with tumor and edema, along with the underlying anatomical ground truth, Main emphasis is placed on simulation of the major effects known for tumor MRI, such as contrast enhancement, local distortion of healthy tissue, infiltrating edema adjacent to tumors, destruction and deformation of fiber tracts, and multi-modal MRI contrast of healthy tissue and pathology. The new method synthesizes pathology in multi-modal MRI and diffusion tensor imaging (DTI) by simulating mass effect, warping and destruction of white matter fibers, and infiltration of brain tissues by tumor cells. We generate synthetic contrast enhanced MR images by simulating the accumulation of contrast agent within the brain. The appearance of the the brain tissue and tumor in MRI is simulated by synthesizing texture images from real MR images. The proposed method is able to generate synthetic ground truth and synthesized MR images with tumor and edema that exhibit comparable segmentation challenges to real tumor MRI. Such image data sets will find use in segmentation reliability studies, comparison and validation of different segmentation methods, training and teaching, or even in evaluating standards for tumor size like the RECIST criteria (response evaluation criteria in solid tumors).

Subject-specific body segment parameter estimation using 3D photogrammetry with multiple cameras

PubMed Central

Morris, Mark; Sellers, William I.

2015-01-01

Inertial properties of body segments, such as mass, centre of mass or moments of inertia, are important parameters when studying movements of the human body. However, these quantities are not directly measurable. Current approaches include using regression models which have limited accuracy: geometric models with lengthy measuring procedures or acquiring and post-processing MRI scans of participants. We propose a geometric methodology based on 3D photogrammetry using multiple cameras to provide subject-specific body segment parameters while minimizing the interaction time with the participants. A low-cost body scanner was built using multiple cameras and 3D point cloud data generated using structure from motion photogrammetric reconstruction algorithms. The point cloud was manually separated into body segments, and convex hulling applied to each segment to produce the required geometric outlines. The accuracy of the method can be adjusted by choosing the number of subdivisions of the body segments. The body segment parameters of six participants (four male and two female) are presented using the proposed method. The multi-camera photogrammetric approach is expected to be particularly suited for studies including populations for which regression models are not available in literature and where other geometric techniques or MRI scanning are not applicable due to time or ethical constraints. PMID:25780778

Subject-specific body segment parameter estimation using 3D photogrammetry with multiple cameras.

PubMed

Peyer, Kathrin E; Morris, Mark; Sellers, William I

2015-01-01

Inertial properties of body segments, such as mass, centre of mass or moments of inertia, are important parameters when studying movements of the human body. However, these quantities are not directly measurable. Current approaches include using regression models which have limited accuracy: geometric models with lengthy measuring procedures or acquiring and post-processing MRI scans of participants. We propose a geometric methodology based on 3D photogrammetry using multiple cameras to provide subject-specific body segment parameters while minimizing the interaction time with the participants. A low-cost body scanner was built using multiple cameras and 3D point cloud data generated using structure from motion photogrammetric reconstruction algorithms. The point cloud was manually separated into body segments, and convex hulling applied to each segment to produce the required geometric outlines. The accuracy of the method can be adjusted by choosing the number of subdivisions of the body segments. The body segment parameters of six participants (four male and two female) are presented using the proposed method. The multi-camera photogrammetric approach is expected to be particularly suited for studies including populations for which regression models are not available in literature and where other geometric techniques or MRI scanning are not applicable due to time or ethical constraints.

Post processing for offline Chinese handwritten character string recognition

NASA Astrophysics Data System (ADS)

Wang, YanWei; Ding, XiaoQing; Liu, ChangSong

2012-01-01

Offline Chinese handwritten character string recognition is one of the most important research fields in pattern recognition. Due to the free writing style, large variability in character shapes and different geometric characteristics, Chinese handwritten character string recognition is a challenging problem to deal with. However, among the current methods over-segmentation and merging method which integrates geometric information, character recognition information and contextual information, shows a promising result. It is found experimentally that a large part of errors are segmentation error and mainly occur around non-Chinese characters. In a Chinese character string, there are not only wide characters namely Chinese characters, but also narrow characters like digits and letters of the alphabet. The segmentation error is mainly caused by uniform geometric model imposed on all segmented candidate characters. To solve this problem, post processing is employed to improve recognition accuracy of narrow characters. On one hand, multi-geometric models are established for wide characters and narrow characters respectively. Under multi-geometric models narrow characters are not prone to be merged. On the other hand, top rank recognition results of candidate paths are integrated to boost final recognition of narrow characters. The post processing method is investigated on two datasets, in total 1405 handwritten address strings. The wide character recognition accuracy has been improved lightly and narrow character recognition accuracy has been increased up by 10.41% and 10.03% respectively. It indicates that the post processing method is effective to improve recognition accuracy of narrow characters.

Design of Experiments for Model Calibration of Multi-Physics Systems with Targeted Events of Interest

DTIC Science & Technology

2017-03-01

discrete set of specimen and instrumentation locations available to be studied in a high -speed tunnel, such as the 8-foot HTT, under the desired...Benjamin P. Smarslok Hypersonic Sciences Branch High Speed Systems Division Diane Villanueva Universal Technology Corporation MARCH 2017...and is available to the general public, including foreign nationals. Copies may be obtained from the Defense Technical Information Center (DTIC

Multi-fractal texture features for brain tumor and edema segmentation

NASA Astrophysics Data System (ADS)

Reza, S.; Iftekharuddin, K. M.

2014-03-01

In this work, we propose a fully automatic brain tumor and edema segmentation technique in brain magnetic resonance (MR) images. Different brain tissues are characterized using the novel texture features such as piece-wise triangular prism surface area (PTPSA), multi-fractional Brownian motion (mBm) and Gabor-like textons, along with regular intensity and intensity difference features. Classical Random Forest (RF) classifier is used to formulate the segmentation task as classification of these features in multi-modal MRIs. The segmentation performance is compared with other state-of-art works using a publicly available dataset known as Brain Tumor Segmentation (BRATS) 2012 [1]. Quantitative evaluation is done using the online evaluation tool from Kitware/MIDAS website [2]. The results show that our segmentation performance is more consistent and, on the average, outperforms other state-of-the art works in both training and challenge cases in the BRATS competition.

Multi-atlas segmentation of subcortical brain structures via the AutoSeg software pipeline

PubMed Central

Wang, Jiahui; Vachet, Clement; Rumple, Ashley; Gouttard, Sylvain; Ouziel, Clémentine; Perrot, Emilie; Du, Guangwei; Huang, Xuemei; Gerig, Guido; Styner, Martin

2014-01-01

Automated segmenting and labeling of individual brain anatomical regions, in MRI are challenging, due to the issue of individual structural variability. Although atlas-based segmentation has shown its potential for both tissue and structure segmentation, due to the inherent natural variability as well as disease-related changes in MR appearance, a single atlas image is often inappropriate to represent the full population of datasets processed in a given neuroimaging study. As an alternative for the case of single atlas segmentation, the use of multiple atlases alongside label fusion techniques has been introduced using a set of individual “atlases” that encompasses the expected variability in the studied population. In our study, we proposed a multi-atlas segmentation scheme with a novel graph-based atlas selection technique. We first paired and co-registered all atlases and the subject MR scans. A directed graph with edge weights based on intensity and shape similarity between all MR scans is then computed. The set of neighboring templates is selected via clustering of the graph. Finally, weighted majority voting is employed to create the final segmentation over the selected atlases. This multi-atlas segmentation scheme is used to extend a single-atlas-based segmentation toolkit entitled AutoSeg, which is an open-source, extensible C++ based software pipeline employing BatchMake for its pipeline scripting, developed at the Neuro Image Research and Analysis Laboratories of the University of North Carolina at Chapel Hill. AutoSeg performs N4 intensity inhomogeneity correction, rigid registration to a common template space, automated brain tissue classification based skull-stripping, and the multi-atlas segmentation. The multi-atlas-based AutoSeg has been evaluated on subcortical structure segmentation with a testing dataset of 20 adult brain MRI scans and 15 atlas MRI scans. The AutoSeg achieved mean Dice coefficients of 81.73% for the subcortical structures. PMID:24567717

SegAN: Adversarial Network with Multi-scale L1 Loss for Medical Image Segmentation.

PubMed

Xue, Yuan; Xu, Tao; Zhang, Han; Long, L Rodney; Huang, Xiaolei

2018-05-03

Inspired by classic Generative Adversarial Networks (GANs), we propose a novel end-to-end adversarial neural network, called SegAN, for the task of medical image segmentation. Since image segmentation requires dense, pixel-level labeling, the single scalar real/fake output of a classic GAN's discriminator may be ineffective in producing stable and sufficient gradient feedback to the networks. Instead, we use a fully convolutional neural network as the segmentor to generate segmentation label maps, and propose a novel adversarial critic network with a multi-scale L 1 loss function to force the critic and segmentor to learn both global and local features that capture long- and short-range spatial relationships between pixels. In our SegAN framework, the segmentor and critic networks are trained in an alternating fashion in a min-max game: The critic is trained by maximizing a multi-scale loss function, while the segmentor is trained with only gradients passed along by the critic, with the aim to minimize the multi-scale loss function. We show that such a SegAN framework is more effective and stable for the segmentation task, and it leads to better performance than the state-of-the-art U-net segmentation method. We tested our SegAN method using datasets from the MICCAI BRATS brain tumor segmentation challenge. Extensive experimental results demonstrate the effectiveness of the proposed SegAN with multi-scale loss: on BRATS 2013 SegAN gives performance comparable to the state-of-the-art for whole tumor and tumor core segmentation while achieves better precision and sensitivity for Gd-enhance tumor core segmentation; on BRATS 2015 SegAN achieves better performance than the state-of-the-art in both dice score and precision.

Connective Tissue Reflex Massage for Type 2 Diabetic Patients with Peripheral Arterial Disease: Randomized Controlled Trial

PubMed Central

Castro-Sánchez, Adelaida María; Moreno-Lorenzo, Carmen; Matarán-Peñarrocha, Guillermo A.; Feriche-Fernández-Castanys, Belen; Granados-Gámez, Genoveva; Quesada-Rubio, José Manuel

2011-01-01

The objective of this study was to evaluate the efficacy of connective tissue massage to improve blood circulation and intermittent claudication symptoms in type 2 diabetic patients. A randomized, placebo-controlled trial was undertaken. Ninety-eight type 2 diabetes patients with stage I or II-a peripheral arterial disease (PAD) (Leriche-Fontaine classification) were randomly assigned to a massage group or to a placebo group treated using disconnected magnetotherapy equipment. Peripheral arterial circulation was determined by measuring differential segmental arterial pressure, heart rate, skin temperature, oxygen saturation and skin blood flow. Measurements were taken before and at 30 min, 6 months and 1 year after the 15-week treatment. After the 15-week program, the groups differed (P < .05) in differential segmental arterial pressure in right lower limb (lower one-third of thigh, upper and lower one-third of leg) and left lower limb (lower one-third of thigh and upper and lower one-third of leg). A significant difference (P < .05) was also observed in skin blood flow in digits 1 and 4 of right foot and digits 2, 4 and 5 of left foot. ANOVA results were significant (P < .05) for right and left foot oxygen saturation but not for heart rate and temperature. At 6 months and 1 year, the groups differed in differential segmental arterial pressure in upper third of left and right legs. Connective tissue massage improves blood circulation in the lower limbs of type 2 diabetic patients at stage I or II-a and may be useful to slow the progression of PAD. PMID:19933770

Spectroscopy of Multilayered Biological Tissues for Diabetes Care

NASA Astrophysics Data System (ADS)

Yudovsky, Dmitry

Neurological and vascular complications of diabetes mellitus are known to cause foot ulceration in diabetic patients. Present clinical screening techniques enable the diabetes care provider to triage treatment by identifying diabetic patients at risk of foot ulceration. However, these techniques cannot effectively identify specific areas of the foot at risk of ulceration. This study aims to develop non-invasive optical techniques for accurate assessment of tissue health and viability with spatial resolution on the order of 1 mm². The thesis can be divided into three parts: (1) the use of hyperspectral tissue oximetry to detect microcirculatory changes prior to ulcer formation, (2) development of a two-layer tissue spectroscopy algorithm and its application to detection of callus formation or epidermal degradation prior to ulceration, and (3) multi-layered tissue fluorescence modeling for identification of bacterial growth in existing diabetic foot wounds. The first part of the dissertation describes a clinical study in which hyperspectral tissue oximetry was performed on multiple diabetic subjects at risk of ulceration. Tissue oxyhemoglobin and deoxyhemoglobin concentrations were estimated using the Modified Beer-Lambert law. Then, an ulcer prediction algorithm was developed based on retrospective analysis of oxyhemoglobin and deoxyhemoglobin concentrations in sites that were known to ulcerate. The ulcer prediction algorithm exhibited a large sensitivity but low specificity of 95 and 80%, respectively. The second part of the dissertation revisited the hyperspectral data presented in part one with a new and novel two-layer tissue spectroscopy algorithm. This algorithm was able to detect not only oxyhemoglobin and deoxyhemoglobin concentrations, but also the thickness of the epidermis, and the tissue's scattering coefficient. Specifically, change in epidermal thickness provided insight into the formation of diabetic foot ulcers over time. Indeed, callus formation or the thickening of the epidermis which preempts ulcer formation was detectable prior to ulceration. This added dimension of information increased the specificity of the ulcer prediction algorithm by 7% without reducing the sensitivity. Finally, the third part of the dissertation describes the feasibility of detecting bacteria in open ulcers. First, a semi-empirical model of multi-layered tissue fluorescence was developed. Then, an inverse method was developed and applied to simulated fluorescence emission spectra of diabetic foot wounds infected with Staphylococcus aureus and stained with indocyanine green dye (ICG). The inverse method was able to detect the blood volume fraction, oxygen saturation, and the intrinsic fluorescence spectrum of the ICG dye from simulated fluorescence emission spectra.

Identification of foot and mouth disease risk areas using a multi-criteria analysis approach

PubMed Central

Silva, Gustavo Sousa e; Weber, Eliseu José; Hasenack, Heinrich; Groff, Fernando Henrique Sautter; Todeschini, Bernardo; Borba, Mauro Riegert; Medeiros, Antonio Augusto Rosa; Leotti, Vanessa Bielefeldt; Canal, Cláudio Wageck; Corbellini, Luis Gustavo

2017-01-01

Foot and mouth disease (FMD) is a highly infectious disease that affects cloven-hoofed livestock and wildlife. FMD has been a problem for decades, which has led to various measures to control, eradicate and prevent FMD by National Veterinary Services worldwide. Currently, the identification of areas that are at risk of FMD virus incursion and spread is a priority for FMD target surveillance after FMD is eradicated from a given country or region. In our study, a knowledge-driven spatial model was built to identify risk areas for FMD occurrence and to evaluate FMD surveillance performance in Rio Grande do Sul state, Brazil. For this purpose, multi-criteria decision analysis was used as a tool to seek multiple and conflicting criteria to determine a preferred course of action. Thirteen South American experts analyzed 18 variables associated with FMD introduction and dissemination pathways in Rio Grande do Sul. As a result, FMD higher risk areas were identified at international borders and in the central region of the state. The final model was expressed as a raster surface. The predictive ability of the model assessed by comparing, for each cell of the raster surface, the computed model risk scores with a binary variable representing the presence or absence of an FMD outbreak in that cell during the period 1985 to 2015. Current FMD surveillance performance was assessed, and recommendations were made to improve surveillance activities in critical areas. PMID:28552973

Multi-channel MRI segmentation of eye structures and tumors using patient-specific features

PubMed Central

Ciller, Carlos; De Zanet, Sandro; Kamnitsas, Konstantinos; Maeder, Philippe; Glocker, Ben; Munier, Francis L.; Rueckert, Daniel; Thiran, Jean-Philippe

2017-01-01

Retinoblastoma and uveal melanoma are fast spreading eye tumors usually diagnosed by using 2D Fundus Image Photography (Fundus) and 2D Ultrasound (US). Diagnosis and treatment planning of such diseases often require additional complementary imaging to confirm the tumor extend via 3D Magnetic Resonance Imaging (MRI). In this context, having automatic segmentations to estimate the size and the distribution of the pathological tissue would be advantageous towards tumor characterization. Until now, the alternative has been the manual delineation of eye structures, a rather time consuming and error-prone task, to be conducted in multiple MRI sequences simultaneously. This situation, and the lack of tools for accurate eye MRI analysis, reduces the interest in MRI beyond the qualitative evaluation of the optic nerve invasion and the confirmation of recurrent malignancies below calcified tumors. In this manuscript, we propose a new framework for the automatic segmentation of eye structures and ocular tumors in multi-sequence MRI. Our key contribution is the introduction of a pathological eye model from which Eye Patient-Specific Features (EPSF) can be computed. These features combine intensity and shape information of pathological tissue while embedded in healthy structures of the eye. We assess our work on a dataset of pathological patient eyes by computing the Dice Similarity Coefficient (DSC) of the sclera, the cornea, the vitreous humor, the lens and the tumor. In addition, we quantitatively show the superior performance of our pathological eye model as compared to the segmentation obtained by using a healthy model (over 4% DSC) and demonstrate the relevance of our EPSF, which improve the final segmentation regardless of the classifier employed. PMID:28350816

Fully convolutional networks with double-label for esophageal cancer image segmentation by self-transfer learning

NASA Astrophysics Data System (ADS)

Xue, Di-Xiu; Zhang, Rong; Zhao, Yuan-Yuan; Xu, Jian-Ming; Wang, Ya-Lei

2017-07-01

Cancer recognition is the prerequisite to determine appropriate treatment. This paper focuses on the semantic segmentation task of microvascular morphological types on narrowband images to aid clinical examination of esophageal cancer. The most challenge for semantic segmentation is incomplete-labeling. Our key insight is to build fully convolutional networks (FCNs) with double-label to make pixel-wise predictions. The roi-label indicating ROIs (region of interest) is introduced as extra constraint to guild feature learning. Trained end-to-end, the FCN model with two target jointly optimizes both segmentation of sem-label (semantic label) and segmentation of roi-label within the framework of self-transfer learning based on multi-task learning theory. The learning representation ability of shared convolutional networks for sem-label is improved with support of roi-label via achieving a better understanding of information outside the ROIs. Our best FCN model gives satisfactory segmentation result with mean IU up to 77.8% (pixel accuracy > 90%). The results show that the proposed approach is able to assist clinical diagnosis to a certain extent.

Abdominal multi-organ segmentation from CT images using conditional shape–location and unsupervised intensity priors

PubMed Central

Linguraru, Marius George; Hori, Masatoshi; Summers, Ronald M; Tomiyama, Noriyuki

2015-01-01

This paper addresses the automated segmentation of multiple organs in upper abdominal computed tomography (CT) data. The aim of our study is to develop methods to effectively construct the conditional priors and use their prediction power for more accurate segmentation as well as easy adaptation to various imaging conditions in CT images, as observed in clinical practice. We propose a general framework of multi-organ segmentation which effectively incorporates interrelations among multiple organs and easily adapts to various imaging conditions without the need for supervised intensity information. The features of the framework are as follows: (1) A method for modeling conditional shape and location (shape–location) priors, which we call prediction-based priors, is developed to derive accurate priors specific to each subject, which enables the estimation of intensity priors without the need for supervised intensity information. (2) Organ correlation graph is introduced, which defines how the conditional priors are constructed and segmentation processes of multiple organs are executed. In our framework, predictor organs, whose segmentation is sufficiently accurate by using conventional single-organ segmentation methods, are pre-segmented, and the remaining organs are hierarchically segmented using conditional shape–location priors. The proposed framework was evaluated through the segmentation of eight abdominal organs (liver, spleen, left and right kidneys, pancreas, gallbladder, aorta, and inferior vena cava) from 134 CT data from 86 patients obtained under six imaging conditions at two hospitals. The experimental results show the effectiveness of the proposed prediction-based priors and the applicability to various imaging conditions without the need for supervised intensity information. Average Dice coefficients for the liver, spleen, and kidneys were more than 92%, and were around 73% and 67% for the pancreas and gallbladder, respectively. PMID:26277022

Abdominal multi-organ segmentation from CT images using conditional shape-location and unsupervised intensity priors.

PubMed

Okada, Toshiyuki; Linguraru, Marius George; Hori, Masatoshi; Summers, Ronald M; Tomiyama, Noriyuki; Sato, Yoshinobu

2015-12-01

This paper addresses the automated segmentation of multiple organs in upper abdominal computed tomography (CT) data. The aim of our study is to develop methods to effectively construct the conditional priors and use their prediction power for more accurate segmentation as well as easy adaptation to various imaging conditions in CT images, as observed in clinical practice. We propose a general framework of multi-organ segmentation which effectively incorporates interrelations among multiple organs and easily adapts to various imaging conditions without the need for supervised intensity information. The features of the framework are as follows: (1) A method for modeling conditional shape and location (shape-location) priors, which we call prediction-based priors, is developed to derive accurate priors specific to each subject, which enables the estimation of intensity priors without the need for supervised intensity information. (2) Organ correlation graph is introduced, which defines how the conditional priors are constructed and segmentation processes of multiple organs are executed. In our framework, predictor organs, whose segmentation is sufficiently accurate by using conventional single-organ segmentation methods, are pre-segmented, and the remaining organs are hierarchically segmented using conditional shape-location priors. The proposed framework was evaluated through the segmentation of eight abdominal organs (liver, spleen, left and right kidneys, pancreas, gallbladder, aorta, and inferior vena cava) from 134 CT data from 86 patients obtained under six imaging conditions at two hospitals. The experimental results show the effectiveness of the proposed prediction-based priors and the applicability to various imaging conditions without the need for supervised intensity information. Average Dice coefficients for the liver, spleen, and kidneys were more than 92%, and were around 73% and 67% for the pancreas and gallbladder, respectively. Copyright © 2015 Elsevier B.V. All rights reserved.

Design and Fabrication of High Gain Multi-element Multi-segment Quarter-sector Cylindrical Dielectric Resonator Antenna

NASA Astrophysics Data System (ADS)

Ranjan, Pinku; Gangwar, Ravi Kumar

2017-12-01

A novel design and analysis of quarter cylindrical dielectric resonator antenna (q-CDRA) with multi-element and multi-segment (MEMS) approach has been presented. The MEMS q-CDRA has been designed by splitting four identical quarters from a solid cylinder and then multi-segmentation approach has been utilized to design q-CDRA. The proposed antenna has been designed for enhancement in bandwidth as well as for high gain. For bandwidth enhancement, multi-segmentation method has been explained for the selection of dielectric constant of materials. The performance of the proposed MEMS q-CDRA has been demonstrated with design guideline of MEMS approach. To validate the antenna performance, three segments q-CDRA has been fabricated and analyzed practically. The simulated results have been in good agreement with measured one. The MEMS q-CDRA has wide impedance bandwidth (|S11|≤-10 dB) of 133.8 % with monopole-like radiation pattern. The proposed MEMS q-CDRA has been operating at TM01δ mode with the measured gain of 6.65 dBi and minimum gain of 4.5 dBi in entire operating frequency band (5.1-13.7 GHz). The proposed MEMS q-CDRA may find appropriate applications in WiMAX and WLAN band.

Fusion-based multi-target tracking and localization for intelligent surveillance systems

NASA Astrophysics Data System (ADS)

Rababaah, Haroun; Shirkhodaie, Amir

2008-04-01

In this paper, we have presented two approaches addressing visual target tracking and localization in complex urban environment. The two techniques presented in this paper are: fusion-based multi-target visual tracking, and multi-target localization via camera calibration. For multi-target tracking, the data fusion concepts of hypothesis generation/evaluation/selection, target-to-target registration, and association are employed. An association matrix is implemented using RGB histograms for associated tracking of multi-targets of interests. Motion segmentation of targets of interest (TOI) from the background was achieved by a Gaussian Mixture Model. Foreground segmentation, on other hand, was achieved by the Connected Components Analysis (CCA) technique. The tracking of individual targets was estimated by fusing two sources of information, the centroid with the spatial gating, and the RGB histogram association matrix. The localization problem is addressed through an effective camera calibration technique using edge modeling for grid mapping (EMGM). A two-stage image pixel to world coordinates mapping technique is introduced that performs coarse and fine location estimation of moving TOIs. In coarse estimation, an approximate neighborhood of the target position is estimated based on nearest 4-neighbor method, and in fine estimation, we use Euclidean interpolation to localize the position within the estimated four neighbors. Both techniques were tested and shown reliable results for tracking and localization of Targets of interests in complex urban environment.

A new method to approximate load-displacement relationships of spinal motion segments for patient-specific multi-body models of scoliotic spine.

PubMed

Jalalian, Athena; Tay, Francis E H; Arastehfar, Soheil; Liu, Gabriel

2017-06-01

Load-displacement relationships of spinal motion segments are crucial factors in characterizing the stiffness of scoliotic spine models to mimic the spine responses to loads. Although nonlinear approach to approximation of the relationships can be superior to linear ones, little mention has been made to deriving personalized nonlinear load-displacement relationships in previous studies. A method is developed for nonlinear approximation of load-displacement relationships of spinal motion segments to assist characterizing in vivo the stiffness of spine models. We propose approximation by tangent functions and focus on rotational displacements in lateral direction. The tangent functions are characterized using lateral bending test. A multi-body model was characterized to 18 patients and utilized to simulate four spine positions; right bending, left bending, neutral, and traction. The same was done using linear functions to assess the performance of the proposed tangent function in comparison with the linear function. Root-mean-square error (RMSE) of the displacements estimated by the tangent functions was 44 % smaller than the linear functions. This shows the ability of our tangent function in approximation of the relationships for a range of infinitesimal to large displacements involved in the spine movement to the four positions. In addition, the models based on the tangent functions yielded 67, 55, and 39 % smaller RMSEs of Ferguson angles, locations of vertebrae, and orientations of vertebrae, respectively, implying better estimates of spine responses to loads. Overall, it can be concluded that our method for approximating load-displacement relationships of spinal motion segments can offer good estimates of scoliotic spine stiffness.

Spatiotemporal Segmentation and Modeling of the Mitral Valve in Real-Time 3D Echocardiographic Images.

PubMed

Pouch, Alison M; Aly, Ahmed H; Lai, Eric K; Yushkevich, Natalie; Stoffers, Rutger H; Gorman, Joseph H; Cheung, Albert T; Gorman, Joseph H; Gorman, Robert C; Yushkevich, Paul A

2017-09-01

Transesophageal echocardiography is the primary imaging modality for preoperative assessment of mitral valves with ischemic mitral regurgitation (IMR). While there are well known echocardiographic insights into the 3D morphology of mitral valves with IMR, such as annular dilation and leaflet tethering, less is understood about how quantification of valve dynamics can inform surgical treatment of IMR or predict short-term recurrence of the disease. As a step towards filling this knowledge gap, we present a novel framework for 4D segmentation and geometric modeling of the mitral valve in real-time 3D echocardiography (rt-3DE). The framework integrates multi-atlas label fusion and template-based medial modeling to generate quantitatively descriptive models of valve dynamics. The novelty of this work is that temporal consistency in the rt-3DE segmentations is enforced during both the segmentation and modeling stages with the use of groupwise label fusion and Kalman filtering. The algorithm is evaluated on rt-3DE data series from 10 patients: five with normal mitral valve morphology and five with severe IMR. In these 10 data series that total 207 individual 3DE images, each 3DE segmentation is validated against manual tracing and temporal consistency between segmentations is demonstrated. The ultimate goal is to generate accurate and consistent representations of valve dynamics that can both visually and quantitatively provide insight into normal and pathological valve function.

46 CFR 69.207 - Measurements.

Code of Federal Regulations, 2010 CFR

2010-10-01

... dimensions must be expressed in feet and inches to the nearest half inch or in feet and tenths of a foot to the nearest .05 of a foot. (b) For a multi-hull vessel, each hull must be measured separately for..., breadth, and depth. (c) The Coast Guard may verify dimensions of vessels measured under this subpart. ...

46 CFR 69.207 - Measurements.

Code of Federal Regulations, 2011 CFR

2011-10-01

... dimensions must be expressed in feet and inches to the nearest half inch or in feet and tenths of a foot to the nearest .05 of a foot. (b) For a multi-hull vessel, each hull must be measured separately for..., breadth, and depth. (c) The Coast Guard may verify dimensions of vessels measured under this subpart. ...

Final analysis and design of a thermal protection system for 8-foot HTST combustor

NASA Technical Reports Server (NTRS)

Moskowitz, S.

1973-01-01

The cylindrical shell combustor with T-bar supports in the 8-foot HTST at the NASA-Langley Research Center encountered vibratory fatigue cracking over a period of 50-250 tunnel tests within a limited range of the required operating envelope. A preliminary design study provided several suitable thermal protection system designs for the combustor, one of which was a two-pass regenerative type air-cooled omega-shaped segment liner. A final design layout of the omega segment liner was prepared and analyzed for steady-state and transient conditions. The design of a support system for the fuel spray bar assembly was also included. Detail drawings suitable for fabrication purposes were also prepared. Liner design problems defined during the preliminary study included (1) the ingress of gas into the attachment bulb section of the omega segment, (2) the large thermal gradient along the leg of the omega bulb attachment section and, (3) the local peak metal temperature at the radius between the liner ID and the leg of the bulb attachment. These were resolved during the final design task. Analyses of the final design of the omega segment liner indicated that all design goals were met and the design provided the capability of operating over the required test envelope with a life expectancy substantially above the goal of 1500 cycles.

Biomechanical basis of choosing the rational mass and its distribution throughout the lower limb prosthesis segments.

PubMed

Farber, B S; Moreinis, I Sh

1995-11-01

A solution for finding a rational distribution of mass in lower limb prostheses has been considered based on the formal premise favoring the identification of the movements of a prosthetic and an intact leg. For the purpose of simplicity, and analysis has been carried out for only the swing phase, the data about the properties of moving segments being determined without integrating differential equations of motion. At the formation of equations of motion, an assumption that body segments are absolutely rigid and have constant moments of inertia and locations of the center of mass was taken into consideration. Based on independent proportions formed of combinations of the coefficients of equations of motion, a system of three equations has been formulated and solved in relation to the mass values sought: a static radius and a radius of inertia of the prosthesis complex link "shin + foot + footwear." From the six unknowns included in the equations, three values are chosen as mean values determined empirically. The solution of obtained equations results in the following conclusions: the parameters of the mass distribution in a "shin + foot + footwear" complex link depend on the amputation level and the patient's mass. These data, reported in appropriate tables, may be used in prosthetics practice. Recommendations have also been presented with regard to a prosthesic mass relative to the age of the person with amputation and a method of a balancing of prostheses aimed at the achievement of a rational distribution of masses. The analysis of obtained equations has also allowed us to make recommendations about the artificial foot mass. It has been concluded that a reasonable desire to reduce the mass of the prosthetic segments is not an end in itself, but is only the means of a rational distribution by means of balancing. It has been proved that rational prosthetic fitting results in decreased energy costs and overloads are decreased and a normalized gait.

Kinematics of the field hockey penalty corner push-in.

PubMed

Kerr, Rebecca; Ness, Kevin

2006-01-01

The aims of the study were to determine those variables that significantly affect push-in execution and thereby formulate coaching recommendations specific to the push-in. Two 50 Hz video cameras recorded transverse and longitudinal views of push-in trials performed by eight experienced and nine inexperienced male push-in performers. Video footage was digitized for data analysis of ball speed, stance width, drag distance, drag time, drag speed, centre of massy displacement and segment and stick displacements and velocities. Experienced push-in performers demonstrated a significantly greater (p < 0.05) stance width, a significantly greater distance between the ball and the front foot at the start of the push-in and a significantly faster ball speed than inexperienced performers. In addition, the experienced performers showed a significant positive correlation between ball speed and playing experience and tended to adopt a combination of simultaneous and sequential segment rotation to achieve accuracy and fast ball speed. The study yielded the following coaching recommendations for enhanced push-in performance: maximize drag distance by maximizing front foot-ball distance at the start of the push-in; use a combination of simultaneous and sequential segment rotations to optimise both accuracy and ball speed and maximize drag speed.

Cooperativity and modularity in protein folding

PubMed Central

Sasai, Masaki; Chikenji, George; Terada, Tomoki P.

2016-01-01

A simple statistical mechanical model proposed by Wako and Saitô has explained the aspects of protein folding surprisingly well. This model was systematically applied to multiple proteins by Muñoz and Eaton and has since been referred to as the Wako-Saitô-Muñoz-Eaton (WSME) model. The success of the WSME model in explaining the folding of many proteins has verified the hypothesis that the folding is dominated by native interactions, which makes the energy landscape globally biased toward native conformation. Using the WSME and other related models, Saitô emphasized the importance of the hierarchical pathway in protein folding; folding starts with the creation of contiguous segments having a native-like configuration and proceeds as growth and coalescence of these segments. The Φ-values calculated for barnase with the WSME model suggested that segments contributing to the folding nucleus are similar to the structural modules defined by the pattern of native atomic contacts. The WSME model was extended to explain folding of multi-domain proteins having a complex topology, which opened the way to comprehensively understanding the folding process of multi-domain proteins. The WSME model was also extended to describe allosteric transitions, indicating that the allosteric structural movement does not occur as a deterministic sequential change between two conformations but as a stochastic diffusive motion over the dynamically changing energy landscape. Statistical mechanical viewpoint on folding, as highlighted by the WSME model, has been renovated in the context of modern methods and ideas, and will continue to provide insights on equilibrium and dynamical features of proteins. PMID:28409080

Multi-atlas-based segmentation of the parotid glands of MR images in patients following head-and-neck cancer radiotherapy

NASA Astrophysics Data System (ADS)

Cheng, Guanghui; Yang, Xiaofeng; Wu, Ning; Xu, Zhijian; Zhao, Hongfu; Wang, Yuefeng; Liu, Tian

2013-02-01

Xerostomia (dry mouth), resulting from radiation damage to the parotid glands, is one of the most common and distressing side effects of head-and-neck cancer radiotherapy. Recent MRI studies have demonstrated that the volume reduction of parotid glands is an important indicator for radiation damage and xerostomia. In the clinic, parotid-volume evaluation is exclusively based on physicians' manual contours. However, manual contouring is time-consuming and prone to inter-observer and intra-observer variability. Here, we report a fully automated multi-atlas-based registration method for parotid-gland delineation in 3D head-and-neck MR images. The multi-atlas segmentation utilizes a hybrid deformable image registration to map the target subject to multiple patients' images, applies the transformation to the corresponding segmented parotid glands, and subsequently uses the multiple patient-specific pairs (head-and-neck MR image and transformed parotid-gland mask) to train support vector machine (SVM) to reach consensus to segment the parotid gland of the target subject. This segmentation algorithm was tested with head-and-neck MRIs of 5 patients following radiotherapy for the nasopharyngeal cancer. The average parotid-gland volume overlapped 85% between the automatic segmentations and the physicians' manual contours. In conclusion, we have demonstrated the feasibility of an automatic multi-atlas based segmentation algorithm to segment parotid glands in head-and-neck MR images.

Modeling the Sedimentary Infill of Lakes in the East African Rift: A Case Study of Multiple versus Single Rift Basin Segments

NASA Astrophysics Data System (ADS)

Zhang, C.; Scholz, C. A.

2016-12-01

The sedimentary basins in the East African Rift are considered excellent modern examples for investigating sedimentary infilling and evolution of extensional systems. Some lakes in the western branch of the rift have formed within single-segment systems, and include Lake Albert and Lake Edward. The largest and oldest lakes developed within multi-segment systems, and these include Lake Tanganyika and Lake Malawi. This research aims to explore processes of erosion and sedimentary infilling of the catchment area in single-segment rift (SSR) and multi-segment rift (MSR) systems. We consider different conditions of regional precipitation and evaporation, and assess the resulting facies architecture through forward modeling, using state-of-the-art commercial basin modeling software. Dionisos is a three-dimensional numerical stratigraphic forward modeling software program, which simulates basin-scale sediment transport based on empirical water- and gravity-driven diffusion equations. It was classically used to quantify the sedimentary architecture and basin infilling of both marine siliciclastic and carbonate environments. However, we apply this approach to continental rift basin environments. In this research, two scenarios are developed, one for a MSR and the other for a SSR. The modeled systems simulate the ratio of drainage area and lake surface area observed in modern Lake Tanganyika and Lake Albert, which are examples of MSRs and SSRs, respectively. The main parameters, such as maximum subsidence rate, water- and gravity-driven diffusion coefficients, rainfall, and evaporation, are approximated using these real-world examples. The results of 5 million year model runs with 50,000 year time steps show that MSRs are characterized by a deep water lake with relatively modest sediment accumulation, while the SSRs are characterized by a nearly overfilled lake with shallow water depths and thick sediment accumulation. The preliminary modeling results conform to the features of sedimentary infills revealed by seismic reflection data acquired in Lake Tanganyika and Lake Albert. Future models will refine the parameters of rainfall and evaporation in these two scenarios to better evaluate detailed basin facies architecture.

Adolescent accessory navicular.

PubMed

Leonard, Zachary C; Fortin, Paul T

2010-06-01

Accessory tarsal navicular is a common anomaly in the human foot. It should be in the differential of medial foot pain. A proper history and physical, along with imaging modalities, can lead to the diagnosis. Often, classification of the ossicle and amount of morbidity guide treatment. Nonsurgical measures can provide relief. A variety of surgical procedures have been used with good results. Our preferred method is excision for small ossicles and segmental fusion after removal of the synchondrosis for large ossicles. In addition, pes planovalgus deformities need to be addressed concomitantly. Copyright 2010 Elsevier Inc. All rights reserved.

Foot-mounted inertial measurement unit for activity classification.

PubMed

Ghobadi, Mostafa; Esfahani, Ehsan T

2014-01-01

This paper proposes a classification technique for daily base activity recognition for human monitoring during physical therapy in home. The proposed method estimates the foot motion using single inertial measurement unit, then segments the motion into steps classify them by template-matching as walking, stairs up or stairs down steps. The results show a high accuracy of activity recognition. Unlike previous works which are limited to activity recognition, the proposed approach is more qualitative by providing similarity index of any activity to its desired template which can be used to assess subjects improvement.

Tumor propagation model using generalized hidden Markov model

NASA Astrophysics Data System (ADS)

Park, Sun Young; Sargent, Dustin

2017-02-01

Tumor tracking and progression analysis using medical images is a crucial task for physicians to provide accurate and efficient treatment plans, and monitor treatment response. Tumor progression is tracked by manual measurement of tumor growth performed by radiologists. Several methods have been proposed to automate these measurements with segmentation, but many current algorithms are confounded by attached organs and vessels. To address this problem, we present a new generalized tumor propagation model considering time-series prior images and local anatomical features using a Hierarchical Hidden Markov model (HMM) for tumor tracking. First, we apply the multi-atlas segmentation technique to identify organs/sub-organs using pre-labeled atlases. Second, we apply a semi-automatic direct 3D segmentation method to label the initial boundary between the lesion and neighboring structures. Third, we detect vessels in the ROI surrounding the lesion. Finally, we apply the propagation model with the labeled organs and vessels to accurately segment and measure the target lesion. The algorithm has been designed in a general way to be applicable to various body parts and modalities. In this paper, we evaluate the proposed algorithm on lung and lung nodule segmentation and tracking. We report the algorithm's performance by comparing the longest diameter and nodule volumes using the FDA lung Phantom data and a clinical dataset.

Engineering of multi-segmented light tunnel and flattop focus with designed axial lengths and gaps

NASA Astrophysics Data System (ADS)

Yu, Yanzhong; Huang, Han; Zhou, Mianmian; Zhan, Qiwen

2018-01-01

Based on the radiation pattern from a sectional-uniform line source antenna, a three-dimensional (3D) focus engineering technique for the creation of multi-segmented light tunnel and flattop focus with designed axial lengths and gaps is proposed. Under a 4Pi focusing system, the fields radiated from sectional-uniform magnetic and electromagnetic current line source antennas are employed to generate multi-segmented optical tube and flattop focus, respectively. Numerical results demonstrate that the produced light tube and flattop focus remain homogeneous along the optical axis; and their lengths of the nth segment and the nth gap between consecutive segments can be easily adjusted and only depend on the sizes of the nth section and the nth blanking between adjacent sectional antennas. The optical tube is a pure azimuthally polarized field but for the flattop focus the longitudinal polarization is dominant on the optical axis. To obtain the required pupil plane illumination for constructing the above focal field with prescribed characteristics, the inverse problem of the antenna radiation field is solved. These peculiar focusing fields might find potential applications in multi-particle acceleration, multi-particle trapping and manipulation.

Quasiclassical Eilenberger theory of the topological proximity effect in a superconducting nanowire

NASA Astrophysics Data System (ADS)

Stanev, Valentin; Galitski, Victor

2014-05-01

We use the quasiclassical Eilenberger theory to study the topological superconducting proximity effects between a segment of a nanowire with a p-wave order parameter and a metallic segment. This model faithfully represents key qualitative features of an experimental setup, where only a part of a nanowire is in immediate contact with a bulk superconductor, inducing topological superconductivity. It is shown that the Eilenberger equations represent a viable alternative to the Bogoliubov-de Gennes theory of the topological superconducting heterostructures and provide a much simpler quantitative description of some observables. For our setup, we obtain exact analytical solutions for the quasiclassical Green's functions and the density of states as a function of position and energy. The correlations induced by the boundary involve terms associated with both p-wave and odd-frequency pairing, which are intertwined and contribute to observables on an equal footing. We recover the signatures of the standard Majorana mode near the end of the superconducting segment, but find no such localized mode induced in the metallic segment. Instead, the zero-bias feature is spread out across the entire metallic part in accordance with the previous works. In shorter wires, the Majorana mode and delocalized peak split up away from zero energy. For long metallic segments, nontopological Andreev bound states appear and eventually merge together, giving rise to a gapless superconductor.

Automatic detection of diabetic foot complications with infrared thermography by asymmetric analysis

NASA Astrophysics Data System (ADS)

Liu, Chanjuan; van Netten, Jaap J.; van Baal, Jeff G.; Bus, Sicco A.; van der Heijden, Ferdi

2015-02-01

Early identification of diabetic foot complications and their precursors is essential in preventing their devastating consequences, such as foot infection and amputation. Frequent, automatic risk assessment by an intelligent telemedicine system might be feasible and cost effective. Infrared thermography is a promising modality for such a system. The temperature differences between corresponding areas on contralateral feet are the clinically significant parameters. This asymmetric analysis is hindered by (1) foot segmentation errors, especially when the foot temperature and the ambient temperature are comparable, and by (2) different shapes and sizes between contralateral feet due to deformities or minor amputations. To circumvent the first problem, we used a color image and a thermal image acquired synchronously. Foot regions, detected in the color image, were rigidly registered to the thermal image. This resulted in 97.8%±1.1% sensitivity and 98.4%±0.5% specificity over 76 high-risk diabetic patients with manual annotation as a reference. Nonrigid landmark-based registration with B-splines solved the second problem. Corresponding points in the two feet could be found regardless of the shapes and sizes of the feet. With that, the temperature difference of the left and right feet could be obtained.

Detection of diabetic foot hyperthermia by using a regionalization method, based on the plantar angiosomes, on infrared images.

PubMed

Liu, Y; Polo, A; Zequera, M; Harba, R; Canals, R; Vilcahuaman, L; Bello, Y

2016-08-01

Prevention of serious diabetic foot complication like ulceration or infection is an important issue. As the development of thermal graphic technologies, foot temperature-guided avoidance therapy has been recommended. Doctors from Hospital National Dos de Mayo are studying on the risk of the diabetic foot passing from Grade 0 to Grade 1 in the Wagner Scale. This risk to develop ulcers is related to the temperature difference of corresponding area between left and right foot. Generally speaking, the diabetic foot with greater mean temperature difference has more potential to develop ulcers; especially, area whose temperature difference of more than 2.2°C is where doctors and patients must pay much attention to potential problems like ulceration or infection. A system in Visual Studio was developed taking the thermal images as input and producing image with absolute mean temperature difference of 7different regions or four plantar angiosomes as output. The program process contained essential medical image processing issues such as segmentation, location and regionalization, in which adapted algorithms were implemented. From a database of 85 patients provided only 60 were used due to the quality of acquisition.

Breeding value accuracy estimates for growth traits using random regression and multi-trait models in Nelore cattle.

PubMed

Boligon, A A; Baldi, F; Mercadante, M E Z; Lobo, R B; Pereira, R J; Albuquerque, L G

2011-06-28

We quantified the potential increase in accuracy of expected breeding value for weights of Nelore cattle, from birth to mature age, using multi-trait and random regression models on Legendre polynomials and B-spline functions. A total of 87,712 weight records from 8144 females were used, recorded every three months from birth to mature age from the Nelore Brazil Program. For random regression analyses, all female weight records from birth to eight years of age (data set I) were considered. From this general data set, a subset was created (data set II), which included only nine weight records: at birth, weaning, 365 and 550 days of age, and 2, 3, 4, 5, and 6 years of age. Data set II was analyzed using random regression and multi-trait models. The model of analysis included the contemporary group as fixed effects and age of dam as a linear and quadratic covariable. In the random regression analyses, average growth trends were modeled using a cubic regression on orthogonal polynomials of age. Residual variances were modeled by a step function with five classes. Legendre polynomials of fourth and sixth order were utilized to model the direct genetic and animal permanent environmental effects, respectively, while third-order Legendre polynomials were considered for maternal genetic and maternal permanent environmental effects. Quadratic polynomials were applied to model all random effects in random regression models on B-spline functions. Direct genetic and animal permanent environmental effects were modeled using three segments or five coefficients, and genetic maternal and maternal permanent environmental effects were modeled with one segment or three coefficients in the random regression models on B-spline functions. For both data sets (I and II), animals ranked differently according to expected breeding value obtained by random regression or multi-trait models. With random regression models, the highest gains in accuracy were obtained at ages with a low number of weight records. The results indicate that random regression models provide more accurate expected breeding values than the traditionally finite multi-trait models. Thus, higher genetic responses are expected for beef cattle growth traits by replacing a multi-trait model with random regression models for genetic evaluation. B-spline functions could be applied as an alternative to Legendre polynomials to model covariance functions for weights from birth to mature age.

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

Chang, J; Gu, X; Lu, W

Purpose: A novel distance-dose weighting method for label fusion was developed to increase segmentation accuracy in dosimetrically important regions for prostate radiation therapy. Methods: Label fusion as implemented in the original SIMPLE (OS) for multi-atlas segmentation relies iteratively on the majority vote to generate an estimated ground truth and DICE similarity measure to screen candidates. The proposed distance-dose weighting puts more values on dosimetrically important regions when calculating similarity measure. Specifically, we introduced distance-to-dose error (DDE), which converts distance to dosimetric importance, in performance evaluation. The DDE calculates an estimated DE error derived from surface distance differences between the candidatemore » and estimated ground truth label by multiplying a regression coefficient. To determine the coefficient at each simulation point on the rectum, we fitted DE error with respect to simulated voxel shift. The DEs were calculated by the multi-OAR geometry-dosimetry training model previously developed in our research group. Results: For both the OS and the distance-dose weighted SIMPLE (WS) results, the evaluation metrics for twenty patients were calculated using the ground truth segmentation. The mean difference of DICE, Hausdorff distance, and mean absolute distance (MAD) between OS and WS have shown 0, 0.10, and 0.11, respectively. In partial MAD of WS which calculates MAD within a certain PTV expansion voxel distance, the lower MADs were observed at the closer distances from 1 to 8 than those of OS. The DE results showed that the segmentation from WS produced more accurate results than OS. The mean DE error of V75, V70, V65, and V60 were decreased by 1.16%, 1.17%, 1.14%, and 1.12%, respectively. Conclusion: We have demonstrated that the method can increase the segmentation accuracy in rectum regions adjacent to PTV. As a result, segmentation using WS have shown improved dosimetric accuracy than OS. The WS will provide dosimetrically important label selection strategy in multi-atlas segmentation. CPRIT grant RP150485.« less

A multi-object statistical atlas adaptive for deformable registration errors in anomalous medical image segmentation

NASA Astrophysics Data System (ADS)

Botter Martins, Samuel; Vallin Spina, Thiago; Yasuda, Clarissa; Falcão, Alexandre X.

2017-02-01

Statistical Atlases have played an important role towards automated medical image segmentation. However, a challenge has been to make the atlas more adaptable to possible errors in deformable registration of anomalous images, given that the body structures of interest for segmentation might present significant differences in shape and texture. Recently, deformable registration errors have been accounted by a method that locally translates the statistical atlas over the test image, after registration, and evaluates candidate objects from a delineation algorithm in order to choose the best one as final segmentation. In this paper, we improve its delineation algorithm and extend the model to be a multi-object statistical atlas, built from control images and adaptable to anomalous images, by incorporating a texture classifier. In order to provide a first proof of concept, we instantiate the new method for segmenting, object-by-object and all objects simultaneously, the left and right brain hemispheres, and the cerebellum, without the brainstem, and evaluate it on MRT1-images of epilepsy patients before and after brain surgery, which removed portions of the temporal lobe. The results show efficiency gain with statistically significant higher accuracy, using the mean Average Symmetric Surface Distance, with respect to the original approach.

The whole mesh deformation model: a fast image segmentation method suitable for effective parallelization

NASA Astrophysics Data System (ADS)

Lenkiewicz, Przemyslaw; Pereira, Manuela; Freire, Mário M.; Fernandes, José

2013-12-01

In this article, we propose a novel image segmentation method called the whole mesh deformation (WMD) model, which aims at addressing the problems of modern medical imaging. Such problems have raised from the combination of several factors: (1) significant growth of medical image volumes sizes due to increasing capabilities of medical acquisition devices; (2) the will to increase the complexity of image processing algorithms in order to explore new functionality; (3) change in processor development and turn towards multi processing units instead of growing bus speeds and the number of operations per second of a single processing unit. Our solution is based on the concept of deformable models and is characterized by a very effective and precise segmentation capability. The proposed WMD model uses a volumetric mesh instead of a contour or a surface to represent the segmented shapes of interest, which allows exploiting more information in the image and obtaining results in shorter times, independently of image contents. The model also offers a good ability for topology changes and allows effective parallelization of workflow, which makes it a very good choice for large datasets. We present a precise model description, followed by experiments on artificial images and real medical data.

Ultrafast exciton migration in an HJ-aggregate: Potential surfaces and quantum dynamics

NASA Astrophysics Data System (ADS)

Binder, Robert; Polkehn, Matthias; Ma, Tianji; Burghardt, Irene

2017-01-01

Quantum dynamical and electronic structure calculations are combined to investigate the mechanism of exciton migration in an oligothiophene HJ aggregate, i.e., a combination of oligomer chains (J-type aggregates) and stacked aggregates of such chains (H-type aggregates). To this end, a Frenkel exciton model is parametrized by a recently introduced procedure [Binder et al., J. Chem. Phys. 141, 014101 (2014)] which uses oligomer excited-state calculations to perform an exact, point-wise mapping of coupled potential energy surfaces to an effective Frenkel model. Based upon this parametrization, the Multi-Layer Multi-Configuration Time-Dependent Hartree (ML-MCTDH) method is employed to investigate ultrafast dynamics of exciton transfer in a small, asymmetric HJ aggregate model composed of 30 sites and 30 active modes. For a partially delocalized initial condition, it is shown that a torsional defect confines the trapped initial exciton, and planarization induces an ultrafast resonant transition between an HJ-aggregated segment and a covalently bound "dangling chain" end. This model is a minimal realization of experimentally investigated mixed systems exhibiting ultrafast exciton transfer between aggregated, highly planarized chains and neighboring disordered segments.

Optimizing Likelihood Models for Particle Trajectory Segmentation in Multi-State Systems.

PubMed

Young, Dylan Christopher; Scrimgeour, Jan

2018-06-19

Particle tracking offers significant insight into the molecular mechanics that govern the behav- ior of living cells. The analysis of molecular trajectories that transition between different motive states, such as diffusive, driven and tethered modes, is of considerable importance, with even single trajectories containing significant amounts of information about a molecule's environment and its interactions with cellular structures. Hidden Markov models (HMM) have been widely adopted to perform the segmentation of such complex tracks. In this paper, we show that extensive analysis of hidden Markov model outputs using data derived from multi-state Brownian dynamics simulations can be used both for the optimization of the likelihood models used to describe the states of the system and for characterization of the technique's failure mechanisms. This analysis was made pos- sible by the implementation of parallelized adaptive direct search algorithm on a Nvidia graphics processing unit. This approach provides critical information for the visualization of HMM failure and successful design of particle tracking experiments where trajectories contain multiple mobile states. © 2018 IOP Publishing Ltd.

International Space Station (ISS)

NASA Image and Video Library

2000-07-01

The 45-foot, port-side (P1) truss segment flight article for the International Space Station is being transported to the Redstone Airfield, Marshall Space Flight Center. The truss will be loaded aboard NASA's Super Guppy cargo plane for shipment to the Kennedy Space Center.

Region-based multi-step optic disk and cup segmentation from color fundus image

NASA Astrophysics Data System (ADS)

Xiao, Di; Lock, Jane; Manresa, Javier Moreno; Vignarajan, Janardhan; Tay-Kearney, Mei-Ling; Kanagasingam, Yogesan

2013-02-01

Retinal optic cup-disk-ratio (CDR) is a one of important indicators of glaucomatous neuropathy. In this paper, we propose a novel multi-step 4-quadrant thresholding method for optic disk segmentation and a multi-step temporal-nasal segmenting method for optic cup segmentation based on blood vessel inpainted HSL lightness images and green images. The performance of the proposed methods was evaluated on a group of color fundus images and compared with the manual outlining results from two experts. Dice scores of detected disk and cup regions between the auto and manual results were computed and compared. Vertical CDRs were also compared among the three results. The preliminary experiment has demonstrated the robustness of the method for automatic optic disk and cup segmentation and its potential value for clinical application.

Automatic CT Brain Image Segmentation Using Two Level Multiresolution Mixture Model of EM

NASA Astrophysics Data System (ADS)

Jiji, G. Wiselin; Dehmeshki, Jamshid

2014-04-01

Tissue classification in computed tomography (CT) brain images is an important issue in the analysis of several brain dementias. A combination of different approaches for the segmentation of brain images is presented in this paper. A multi resolution algorithm is proposed along with scaled versions using Gaussian filter and wavelet analysis that extends expectation maximization (EM) algorithm. It is found that it is less sensitive to noise and got more accurate image segmentation than traditional EM. Moreover the algorithm has been applied on 20 sets of CT of the human brain and compared with other works. The segmentation results show the advantages of the proposed work have achieved more promising results and the results have been tested with Doctors.

Segmentation of white rat sperm image

NASA Astrophysics Data System (ADS)

Bai, Weiguo; Liu, Jianguo; Chen, Guoyuan

2011-11-01

The segmentation of sperm image exerts a profound influence in the analysis of sperm morphology, which plays a significant role in the research of animals' infertility and reproduction. To overcome the microscope image's properties of low contrast and highly polluted noise, and to get better segmentation results of sperm image, this paper presents a multi-scale gradient operator combined with a multi-structuring element for the micro-spermatozoa image of white rat, as the multi-scale gradient operator can smooth the noise of an image, while the multi-structuring element can retain more shape details of the sperms. Then, we use the Otsu method to segment the modified gradient image whose gray scale processed is strong in sperms and weak in the background, converting it into a binary sperm image. As the obtained binary image owns impurities that are not similar with sperms in the shape, we choose a form factor to filter those objects whose form factor value is larger than the select critical value, and retain those objects whose not. And then, we can get the final binary image of the segmented sperms. The experiment shows this method's great advantage in the segmentation of the micro-spermatozoa image.

Numerical Predictions of Sonic Boom Signatures for a Straight Line Segmented Leading Edge Model

NASA Technical Reports Server (NTRS)

Elmiligui, Alaa A.; Wilcox, Floyd J.; Cliff, Susan; Thomas, Scott

2012-01-01

A sonic boom wind tunnel test was conducted on a straight-line segmented leading edge (SLSLE) model in the NASA Langley 4- by 4- Foot Unitary Plan Wind Tunnel (UPWT). The purpose of the test was to determine whether accurate sonic boom measurements could be obtained while continuously moving the SLSLE model past a conical pressure probe. Sonic boom signatures were also obtained using the conventional move-pause data acquisition method for comparison. The continuous data acquisition approach allows for accurate signatures approximately 15 times faster than a move-pause technique. These successful results provide an incentive for future testing with greatly increased efficiency using the continuous model translation technique with the single probe to measure sonic boom signatures. Two widely used NASA codes, USM3D (Navier-Stokes) and CART3D-AERO (Euler, adjoint-based adaptive mesh), were used to compute off-body sonic boom pressure signatures of the SLSLE model at several different altitudes below the model at Mach 2.0. The computed pressure signatures compared well with wind tunnel data. The effect of the different altitude for signature extraction was evaluated by extrapolating the near field signatures to the ground and comparing pressure signatures and sonic boom loudness levels.

A double-inverted pendulum model for studying the adaptability of postural control to frequency during human stepping in place.

PubMed

Breniere, Y; Ribreau, C

1998-10-01

In order to analyze the influence of gravity and body characteristics on the control of center of mass (CM) oscillations in stepping in place, equations of motion in oscillating systems were developed using a double-inverted pendulum model which accounts for both the head-arms-trunk (HAT) segment and the two-legged system. The principal goal of this work is to propose an equivalent model which makes use of the usual anthropometric data for the human body, in order to study the ability of postural control to adapt to the step frequency in this particular paradigm of human gait. This model allows the computation of CM-to-CP amplitude ratios, when the center of foot pressure (CP) oscillates, as a parametric function of the stepping in place frequency, whose parameters are gravity and major body characteristics. Motion analysis from a force plate was used to test the model by comparing experimental and simulated values of variations of the CM-to-CP amplitude ratio in the frontal plane versus the frequency. With data from the literature, the model is used to calculate the intersegmental torque which stabilizes the HAT when the Leg segment is subjected to a harmonic torque with an imposed frequency.

Estimation of vertical slip rate in an active fault-propagation fold from the analysis of a progressive unconformity at the NE segment of the Carrascoy Fault (SE Iberia)

NASA Astrophysics Data System (ADS)

Martin-Banda, Raquel; Insua-Arevalo, Juan Miguel; Garcia-Mayordomo, Julian

2017-04-01

Many studies have dealt with the calculation of fault-propagation fold growth rates considering a variety of kinematics models, from limb rotation to hinge migration models. In most cases, the different geometrical and numeric growth models are based on horizontal pre-growth strata architecture and a constant known slip rate. Here, we present the estimation of the vertical slip rate of the NE Segment of the Carrascoy Fault (SE Iberian Peninsula) from the geometrical modeling of a progressive unconformity developed on alluvial fan sediments with a high depositional slope. The NE Segment of the Carrascoy Fault is a left-lateral strike slip fault with reverse component belonging to the Eastern Betic Shear Zone, a major structure that accommodates most of the convergence between Iberian and Nubian tectonics plates in Southern Spain. The proximity of this major fault to the city of Murcia encourages the importance of carrying out paleosismological studies in order to determinate the Quaternary slip rate of the fault, a key geological parameter for seismic hazard calculations. This segment is formed by a narrow fault zone that articulates abruptly the northern edge of the Carrascoy Range with the Guadalentin Depression through high slope, short alluvial fans Upper-Middle Pleistocene in age. An outcrop in a quarry at the foot of this front reveals a progressive unconformity developed on these alluvial fan deposits, showing the important reverse component of the fault. The architecture of this unconformity is marked by well-developed calcretes on the top some of the alluvial deposits. We have determined the age of several of these calcretes by the Uranium-series disequilibrium dating method. The results obtained are consistent with recent published studies on the SW segment of the Carrascoy Fault that together with offset canals observed at a few locations suggest a net slip rate close to 1 m/ka.

Unsupervised Segmentation of Head Tissues from Multi-modal MR Images for EEG Source Localization.

PubMed

Mahmood, Qaiser; Chodorowski, Artur; Mehnert, Andrew; Gellermann, Johanna; Persson, Mikael

2015-08-01

In this paper, we present and evaluate an automatic unsupervised segmentation method, hierarchical segmentation approach (HSA)-Bayesian-based adaptive mean shift (BAMS), for use in the construction of a patient-specific head conductivity model for electroencephalography (EEG) source localization. It is based on a HSA and BAMS for segmenting the tissues from multi-modal magnetic resonance (MR) head images. The evaluation of the proposed method was done both directly in terms of segmentation accuracy and indirectly in terms of source localization accuracy. The direct evaluation was performed relative to a commonly used reference method brain extraction tool (BET)-FMRIB's automated segmentation tool (FAST) and four variants of the HSA using both synthetic data and real data from ten subjects. The synthetic data includes multiple realizations of four different noise levels and several realizations of typical noise with a 20% bias field level. The Dice index and Hausdorff distance were used to measure the segmentation accuracy. The indirect evaluation was performed relative to the reference method BET-FAST using synthetic two-dimensional (2D) multimodal magnetic resonance (MR) data with 3% noise and synthetic EEG (generated for a prescribed source). The source localization accuracy was determined in terms of localization error and relative error of potential. The experimental results demonstrate the efficacy of HSA-BAMS, its robustness to noise and the bias field, and that it provides better segmentation accuracy than the reference method and variants of the HSA. They also show that it leads to a more accurate localization accuracy than the commonly used reference method and suggest that it has potential as a surrogate for expert manual segmentation for the EEG source localization problem.

Multi-scale Gaussian representation and outline-learning based cell image segmentation.

PubMed

Farhan, Muhammad; Ruusuvuori, Pekka; Emmenlauer, Mario; Rämö, Pauli; Dehio, Christoph; Yli-Harja, Olli

2013-01-01

High-throughput genome-wide screening to study gene-specific functions, e.g. for drug discovery, demands fast automated image analysis methods to assist in unraveling the full potential of such studies. Image segmentation is typically at the forefront of such analysis as the performance of the subsequent steps, for example, cell classification, cell tracking etc., often relies on the results of segmentation. We present a cell cytoplasm segmentation framework which first separates cell cytoplasm from image background using novel approach of image enhancement and coefficient of variation of multi-scale Gaussian scale-space representation. A novel outline-learning based classification method is developed using regularized logistic regression with embedded feature selection which classifies image pixels as outline/non-outline to give cytoplasm outlines. Refinement of the detected outlines to separate cells from each other is performed in a post-processing step where the nuclei segmentation is used as contextual information. We evaluate the proposed segmentation methodology using two challenging test cases, presenting images with completely different characteristics, with cells of varying size, shape, texture and degrees of overlap. The feature selection and classification framework for outline detection produces very simple sparse models which use only a small subset of the large, generic feature set, that is, only 7 and 5 features for the two cases. Quantitative comparison of the results for the two test cases against state-of-the-art methods show that our methodology outperforms them with an increase of 4-9% in segmentation accuracy with maximum accuracy of 93%. Finally, the results obtained for diverse datasets demonstrate that our framework not only produces accurate segmentation but also generalizes well to different segmentation tasks.

Multi-scale Gaussian representation and outline-learning based cell image segmentation

PubMed Central

2013-01-01

Background High-throughput genome-wide screening to study gene-specific functions, e.g. for drug discovery, demands fast automated image analysis methods to assist in unraveling the full potential of such studies. Image segmentation is typically at the forefront of such analysis as the performance of the subsequent steps, for example, cell classification, cell tracking etc., often relies on the results of segmentation. Methods We present a cell cytoplasm segmentation framework which first separates cell cytoplasm from image background using novel approach of image enhancement and coefficient of variation of multi-scale Gaussian scale-space representation. A novel outline-learning based classification method is developed using regularized logistic regression with embedded feature selection which classifies image pixels as outline/non-outline to give cytoplasm outlines. Refinement of the detected outlines to separate cells from each other is performed in a post-processing step where the nuclei segmentation is used as contextual information. Results and conclusions We evaluate the proposed segmentation methodology using two challenging test cases, presenting images with completely different characteristics, with cells of varying size, shape, texture and degrees of overlap. The feature selection and classification framework for outline detection produces very simple sparse models which use only a small subset of the large, generic feature set, that is, only 7 and 5 features for the two cases. Quantitative comparison of the results for the two test cases against state-of-the-art methods show that our methodology outperforms them with an increase of 4-9% in segmentation accuracy with maximum accuracy of 93%. Finally, the results obtained for diverse datasets demonstrate that our framework not only produces accurate segmentation but also generalizes well to different segmentation tasks. PMID:24267488

Estimation of Coriolis Force and Torque Acting on Ares-1

NASA Technical Reports Server (NTRS)

Mackey, Ryan M.; Kulikov, Igor K.; Smelyanskiy, Vadim; Luchinsky, Dmitry; Orr, Jeb

2011-01-01

A document describes work on the origin of Coriolis force and estimating Coriolis force and torque applied to the Ares-1 vehicle during its ascent, based on an internal ballistics model for a multi-segmented solid rocket booster (SRB).

Determination of Ankle and Metatarsophalangeal Stiffness During Walking and Jogging.

PubMed

Mager, Fabian; Richards, Jim; Hennies, Malika; Dötzel, Eugen; Chohan, Ambreen; Mbuli, Alex; Capanni, Felix

2018-05-29

Forefoot stiffness has been shown to influence joint biomechanics. However, little or no data exists on metatarsophalangeal stiffness. Twenty-four healthy rearfoot strike runners were recruited from a staff and student population at the University of Central Lancashire. Five repetitions of shod, self-selected speed level walking and jogging were performed. Kinetic and kinematic data were collected using retro-reflective markers placed on the lower limb and foot, to create a three-segment foot model using the Calibrated Anatomical System Technique. Ankle and metatarsophalangeal moments and angles were calculated. Stiffness values were calculated using a linear best fit line of moment versus of angle plots. Paired t-tests were used to compare values between walking and jogging conditions. Significant differences were seen in ankle range of motion (ROM), but not in metatarsophalangeal ROM. Maximum moments were significantly greater in the ankle during jogging, but these were not significantly different at the metatarsophalangeal joint. Average ankle joint stiffness exhibited significantly lower stiffness when walking compared to jogging. However, the metatarsophalangeal joint exhibited significantly greater stiffness when walking compared to jogging. A greater understanding of forefoot stiffness may inform the development of footwear, prosthetic feet and orthotic devices, such as ankle-foot orthoses for walking and sporting activities.

FERMT2 links cortical actin structures, plasma membrane tension and focal adhesion function to stabilize podocyte morphology.

PubMed

Yasuda-Yamahara, M; Rogg, M; Frimmel, J; Trachte, P; Helmstaedter, M; Schroder, P; Schiffer, M; Schell, C; Huber, T B

2018-01-11

Simplification and retraction of podocyte protrusions, generally termed as foot process effacement, is a uniform pathological pattern observed in the majority of glomerular disease, including focal segmental glomerulosclerosis. However, it is still incompletely understood how the interaction of cortical actin structures, actomyosin contractility and focal adhesions, is being orchestrated to control foot process morphology in health and disease. By uncovering the functional role of fermitin family member 2 (FERMT2 or kindlin-2) in podocytes, we provide now evidence, how cell-extracellular matrix (ECM) interactions modulate membrane tension and actomyosin contractility. A genetic modeling approach was applied by deleting FERMT2 in a set of in vivo systems as well as in CRISPR/Cas9 modified human podocytes. Loss of FERMT2 results in altered cortical actin composition, cell cortex destabilization associated with plasma membrane blebbing and a remodeling of focal adhesions. We further show that FERMT2 knockout podocytes have high levels of RhoA activation and concomitantly increased actomyosin contractility. Inhibition of actomyosin tension reverses the membrane blebbing phenotype. Thus, our findings establish a direct link between cell-matrix adhesions, cortical actin structures and plasma membrane tension allowing to better explain cell morphological changes in foot process effacement. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

How do bendy straws bend? A study of re-configurability of multi-stable corrugated shells

NASA Astrophysics Data System (ADS)

Bende, Nakul; Selden, Sarah; Evans, Arthur; Santangelo, Christian; Hayward, Ryan

Shape programmable systems have evolved to allow for reconfiguration of structures through a variety of mechanisms including swelling, stress-relaxation, and thermal expansion. Particularly, there has been a recent interest in systems that exhibit bi-stability or multi-stability to achieve transformation between two or more pre-programmed states. Here, we study the ubiquitous architecture of corrugated shells, such as drinking straws or bellows, which has been well known for centuries. Some of these structures exhibit almost continuous stability amongst a wide range of reconfigurable shapes, but the underlying mechanisms are not well understood. To understand multi-stability in `bendy-straw' structures, we study the unit bi-conical segment using experiments and finite element modeling to elucidate the key geometrical and mechanical factors responsible for its multi-stability. The simple transformations of a unit segment - a change in length or angle can impart complex re-configurability of a structure containing many of these units. The fundamental understanding provided of this simple multi-stable building block could yield improvements in shape re-configurability for a wide array of applications such as corrugated medical tubing, robotics, and deployable structures. NSF EFRI ODISSEI-1240441.

Research on segmentation based on multi-atlas in brain MR image

NASA Astrophysics Data System (ADS)

Qian, Yuejing

2018-03-01

Accurate segmentation of specific tissues in brain MR image can be effectively achieved with the multi-atlas-based segmentation method, and the accuracy mainly depends on the image registration accuracy and fusion scheme. This paper proposes an automatic segmentation method based on the multi-atlas for brain MR image. Firstly, to improve the registration accuracy in the area to be segmented, we employ a target-oriented image registration method for the refinement. Then In the label fusion, we proposed a new algorithm to detect the abnormal sparse patch and simultaneously abandon the corresponding abnormal sparse coefficients, this method is made based on the remaining sparse coefficients combined with the multipoint label estimator strategy. The performance of the proposed method was compared with those of the nonlocal patch-based label fusion method (Nonlocal-PBM), the sparse patch-based label fusion method (Sparse-PBM) and majority voting method (MV). Based on our experimental results, the proposed method is efficient in the brain MR images segmentation compared with MV, Nonlocal-PBM, and Sparse-PBM methods.

NORTHERLY STRETCH OF MILLBURY PORTION, GENERAL VIEW SHOWING TOWPATH BERM ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

NORTHERLY STRETCH OF MILLBURY PORTION, GENERAL VIEW SHOWING TOWPATH BERM (CENTER/RIGHT) AND CANAL PRISM (LEFT); VIEW TO SOUTH FROM FOOT OF THE "TOWN-LINE DUMP" - Blackstone Canal Worcester-Millbury Segment, Eastern bank of Blackstone River, Millbury, Worcester County, MA

Brain tumor detection and segmentation in a CRF (conditional random fields) framework with pixel-pairwise affinity and superpixel-level features.

PubMed

Wu, Wei; Chen, Albert Y C; Zhao, Liang; Corso, Jason J

2014-03-01

Detection and segmentation of a brain tumor such as glioblastoma multiforme (GBM) in magnetic resonance (MR) images are often challenging due to its intrinsically heterogeneous signal characteristics. A robust segmentation method for brain tumor MRI scans was developed and tested. Simple thresholds and statistical methods are unable to adequately segment the various elements of the GBM, such as local contrast enhancement, necrosis, and edema. Most voxel-based methods cannot achieve satisfactory results in larger data sets, and the methods based on generative or discriminative models have intrinsic limitations during application, such as small sample set learning and transfer. A new method was developed to overcome these challenges. Multimodal MR images are segmented into superpixels using algorithms to alleviate the sampling issue and to improve the sample representativeness. Next, features were extracted from the superpixels using multi-level Gabor wavelet filters. Based on the features, a support vector machine (SVM) model and an affinity metric model for tumors were trained to overcome the limitations of previous generative models. Based on the output of the SVM and spatial affinity models, conditional random fields theory was applied to segment the tumor in a maximum a posteriori fashion given the smoothness prior defined by our affinity model. Finally, labeling noise was removed using "structural knowledge" such as the symmetrical and continuous characteristics of the tumor in spatial domain. The system was evaluated with 20 GBM cases and the BraTS challenge data set. Dice coefficients were computed, and the results were highly consistent with those reported by Zikic et al. (MICCAI 2012, Lecture notes in computer science. vol 7512, pp 369-376, 2012). A brain tumor segmentation method using model-aware affinity demonstrates comparable performance with other state-of-the art algorithms.

Multi-atlas based segmentation using probabilistic label fusion with adaptive weighting of image similarity measures.

PubMed

Sjöberg, C; Ahnesjö, A

2013-06-01

Label fusion multi-atlas approaches for image segmentation can give better segmentation results than single atlas methods. We present a multi-atlas label fusion strategy based on probabilistic weighting of distance maps. Relationships between image similarities and segmentation similarities are estimated in a learning phase and used to derive fusion weights that are proportional to the probability for each atlas to improve the segmentation result. The method was tested using a leave-one-out strategy on a database of 21 pre-segmented prostate patients for different image registrations combined with different image similarity scorings. The probabilistic weighting yields results that are equal or better compared to both fusion with equal weights and results using the STAPLE algorithm. Results from the experiments demonstrate that label fusion by weighted distance maps is feasible, and that probabilistic weighted fusion improves segmentation quality more the stronger the individual atlas segmentation quality depends on the corresponding registered image similarity. The regions used for evaluation of the image similarity measures were found to be more important than the choice of similarity measure. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

A real-time computational model for estimating kinematics of ankle ligaments.

PubMed

Zhang, Mingming; Davies, T Claire; Zhang, Yanxin; Xie, Sheng Quan

2016-01-01

An accurate assessment of ankle ligament kinematics is crucial in understanding the injury mechanisms and can help to improve the treatment of an injured ankle, especially when used in conjunction with robot-assisted therapy. A number of computational models have been developed and validated for assessing the kinematics of ankle ligaments. However, few of them can do real-time assessment to allow for an input into robotic rehabilitation programs. An ankle computational model was proposed and validated to quantify the kinematics of ankle ligaments as the foot moves in real-time. This model consists of three bone segments with three rotational degrees of freedom (DOFs) and 12 ankle ligaments. This model uses inputs for three position variables that can be measured from sensors in many ankle robotic devices that detect postures within the foot-ankle environment and outputs the kinematics of ankle ligaments. Validation of this model in terms of ligament length and strain was conducted by comparing it with published data on cadaver anatomy and magnetic resonance imaging. The model based on ligament lengths and strains is in concurrence with those from the published studies but is sensitive to ligament attachment positions. This ankle computational model has the potential to be used in robot-assisted therapy for real-time assessment of ligament kinematics. The results provide information regarding the quantification of kinematics associated with ankle ligaments related to the disability level and can be used for optimizing the robotic training trajectory.

TH-CD-207B-06: Swank Factor of Segmented Scintillators in Multi-Slice CT Detectors: Pulse Height Spectra and Light Escape

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

Howansky, A; Peng, B; Lubinsky, A

Purpose: Pulse height spectra (PHS) have been used to determine the Swank factor of a scintillator by measuring fluctuations in its light output per x-ray interaction. The Swank factor and x-ray quantum efficiency of a scintillator define the upper limit to its imaging performance, i.e. DQE(0). The Swank factor below the K-edge is dominated by optical properties, i.e. variations in light escape efficiency from different depths of interaction, denoted e(z). These variations can be optimized to improve tradeoffs in x-ray absorption, light yield, and spatial resolution. This work develops a quantitative model for interpreting measured PHS, and estimating e(z) onmore » an absolute scale. The method is used to investigate segmented ceramic GOS scintillators used in multi-slice CT detectors. Methods: PHS of a ceramic GOS plate (1 mm thickness) and segmented GOS array (1.4 mm thick) were measured at 46 keV. Signal and noise propagation through x-ray conversion gain, light escape, detection by a photomultiplier tube and dynode amplification were modeled using a cascade of stochastic gain stages. PHS were calculated with these expressions and compared to measurements. Light escape parameters were varied until modeled PHS agreed with measurements. The resulting estimates of e(z) were used to calculate PHS without measurement noise to determine the inherent Swank factor. Results: The variation in e(z) was 67.2–89.7% in the plate and 40.2–70.8% in the segmented sample, corresponding to conversion gains of 28.6–38.1 keV{sup −1} and 17.1–30.1 keV{sup −1}, respectively. The inherent Swank factors of the plate and segmented sample were 0.99 and 0.95, respectively. Conclusion: The high light escape efficiency in the ceramic GOS samples yields high Swank factors and DQE(0) in CT applications. The PHS model allows the intrinsic optical properties of scintillators to be deduced from PHS measurements, thus it provides new insights for evaluating the imaging performance of segmented ceramic GOS scintillators.« less

Segmentation of risk structures for otologic surgery using the Probabilistic Active Shape Model (PASM)

NASA Astrophysics Data System (ADS)

Becker, Meike; Kirschner, Matthias; Sakas, Georgios

2014-03-01

Our research project investigates a multi-port approach for minimally-invasive otologic surgery. For planning such a surgery, an accurate segmentation of the risk structures is crucial. However, the segmentation of these risk structures is a challenging task: The anatomical structures are very small and some have a complex shape, low contrast and vary both in shape and appearance. Therefore, prior knowledge is needed which is why we apply model-based approaches. In the present work, we use the Probabilistic Active Shape Model (PASM), which is a more flexible and specific variant of the Active Shape Model (ASM), to segment the following risk structures: cochlea, semicircular canals, facial nerve, chorda tympani, ossicles, internal auditory canal, external auditory canal and internal carotid artery. For the evaluation we trained and tested the algorithm on 42 computed tomography data sets using leave-one-out tests. Visual assessment of the results shows in general a good agreement of manual and algorithmic segmentations. Further, we achieve a good Average Symmetric Surface Distance while the maximum error is comparatively large due to low contrast at start and end points. Last, we compare the PASM to the standard ASM and show that the PASM leads to a higher accuracy.

An Approach for Reducing the Error Rate in Automated Lung Segmentation

PubMed Central

Gill, Gurman; Beichel, Reinhard R.

2016-01-01

Robust lung segmentation is challenging, especially when tens of thousands of lung CT scans need to be processed, as required by large multi-center studies. The goal of this work was to develop and assess a method for the fusion of segmentation results from two different methods to generate lung segmentations that have a lower failure rate than individual input segmentations. As basis for the fusion approach, lung segmentations generated with a region growing and model-based approach were utilized. The fusion result was generated by comparing input segmentations and selectively combining them using a trained classification system. The method was evaluated on a diverse set of 204 CT scans of normal and diseased lungs. The fusion approach resulted in a Dice coefficient of 0.9855 ± 0.0106 and showed a statistically significant improvement compared to both input segmentation methods. In addition, the failure rate at different segmentation accuracy levels was assessed. For example, when requiring that lung segmentations must have a Dice coefficient of better than 0.97, the fusion approach had a failure rate of 6.13%. In contrast, the failure rate for region growing and model-based methods was 18.14% and 15.69%, respectively. Therefore, the proposed method improves the quality of the lung segmentations, which is important for subsequent quantitative analysis of lungs. Also, to enable a comparison with other methods, results on the LOLA11 challenge test set are reported. PMID:27447897

Two-stage atlas subset selection in multi-atlas based image segmentation

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

Zhao, Tingting, E-mail: tingtingzhao@mednet.ucla.edu; Ruan, Dan, E-mail: druan@mednet.ucla.edu

2015-06-15

Purpose: Fast growing access to large databases and cloud stored data presents a unique opportunity for multi-atlas based image segmentation and also presents challenges in heterogeneous atlas quality and computation burden. This work aims to develop a novel two-stage method tailored to the special needs in the face of large atlas collection with varied quality, so that high-accuracy segmentation can be achieved with low computational cost. Methods: An atlas subset selection scheme is proposed to substitute a significant portion of the computationally expensive full-fledged registration in the conventional scheme with a low-cost alternative. More specifically, the authors introduce a two-stagemore » atlas subset selection method. In the first stage, an augmented subset is obtained based on a low-cost registration configuration and a preliminary relevance metric; in the second stage, the subset is further narrowed down to a fusion set of desired size, based on full-fledged registration and a refined relevance metric. An inference model is developed to characterize the relationship between the preliminary and refined relevance metrics, and a proper augmented subset size is derived to ensure that the desired atlases survive the preliminary selection with high probability. Results: The performance of the proposed scheme has been assessed with cross validation based on two clinical datasets consisting of manually segmented prostate and brain magnetic resonance images, respectively. The proposed scheme demonstrates comparable end-to-end segmentation performance as the conventional single-stage selection method, but with significant computation reduction. Compared with the alternative computation reduction method, their scheme improves the mean and medium Dice similarity coefficient value from (0.74, 0.78) to (0.83, 0.85) and from (0.82, 0.84) to (0.95, 0.95) for prostate and corpus callosum segmentation, respectively, with statistical significance. Conclusions: The authors have developed a novel two-stage atlas subset selection scheme for multi-atlas based segmentation. It achieves good segmentation accuracy with significantly reduced computation cost, making it a suitable configuration in the presence of extensive heterogeneous atlases.« less

Activity recognition using Video Event Segmentation with Text (VEST)

NASA Astrophysics Data System (ADS)

Holloway, Hillary; Jones, Eric K.; Kaluzniacki, Andrew; Blasch, Erik; Tierno, Jorge

2014-06-01

Multi-Intelligence (multi-INT) data includes video, text, and signals that require analysis by operators. Analysis methods include information fusion approaches such as filtering, correlation, and association. In this paper, we discuss the Video Event Segmentation with Text (VEST) method, which provides event boundaries of an activity to compile related message and video clips for future interest. VEST infers meaningful activities by clustering multiple streams of time-sequenced multi-INT intelligence data and derived fusion products. We discuss exemplar results that segment raw full-motion video (FMV) data by using extracted commentary message timestamps, FMV metadata, and user-defined queries.

Open-source software platform for medical image segmentation applications

NASA Astrophysics Data System (ADS)

Namías, R.; D'Amato, J. P.; del Fresno, M.

2017-11-01

Segmenting 2D and 3D images is a crucial and challenging problem in medical image analysis. Although several image segmentation algorithms have been proposed for different applications, no universal method currently exists. Moreover, their use is usually limited when detection of complex and multiple adjacent objects of interest is needed. In addition, the continually increasing volumes of medical imaging scans require more efficient segmentation software design and highly usable applications. In this context, we present an extension of our previous segmentation framework which allows the combination of existing explicit deformable models in an efficient and transparent way, handling simultaneously different segmentation strategies and interacting with a graphic user interface (GUI). We present the object-oriented design and the general architecture which consist of two layers: the GUI at the top layer, and the processing core filters at the bottom layer. We apply the framework for segmenting different real-case medical image scenarios on public available datasets including bladder and prostate segmentation from 2D MRI, and heart segmentation in 3D CT. Our experiments on these concrete problems show that this framework facilitates complex and multi-object segmentation goals while providing a fast prototyping open-source segmentation tool.

Modeling of the interaction between grip force and vibration transmissibility of a finger.

PubMed

Wu, John Z; Welcome, Daniel E; McDowell, Thomas W; Xu, Xueyan S; Dong, Ren G

2017-07-01

It is known that the vibration characteristics of the fingers and hand and the level of grip action interacts when operating a power tool. In the current study, we developed a hybrid finger model to simulate the vibrations of the hand-finger system when gripping a vibrating handle covered with soft materials. The hybrid finger model combines the characteristics of conventional finite element (FE) models, multi-body musculoskeletal models, and lumped mass models. The distal, middle, and proximal finger segments were constructed using FE models, the finger segments were connected via three flexible joint linkages (i.e., distal interphalangeal joint (DIP), proximal interphalangeal joint (PIP), and metacarpophalangeal (MCP) joint), and the MCP joint was connected to the ground and handle via lumped parameter elements. The effects of the active muscle forces were accounted for via the joint moments. The bone, nail, and hard connective tissues were assumed to be linearly elastic whereas the soft tissues, which include the skin and subcutaneous tissues, were considered as hyperelastic and viscoelastic. The general trends of the model predictions agree well with the previous experimental measurements in that the resonant frequency increased from proximal to the middle and to the distal finger segments for the same grip force, that the resonant frequency tends to increase with increasing grip force for the same finger segment, especially for the distal segment, and that the magnitude of vibration transmissibility tends to increase with increasing grip force, especially for the proximal segment. The advantage of the proposed model over the traditional vibration models is that it can predict the local vibration behavior of the finger to a tissue level, while taking into account the effects of the active musculoskeletal force, the effects of the contact conditions on vibrations, the global vibration characteristics. Published by Elsevier Ltd.

Segmentation of Image Ensembles via Latent Atlases

PubMed Central

Van Leemput, Koen; Menze, Bjoern H.; Wells, William M.; Golland, Polina

2010-01-01

Spatial priors, such as probabilistic atlases, play an important role in MRI segmentation. However, the availability of comprehensive, reliable and suitable manual segmentations for atlas construction is limited. We therefore propose a method for joint segmentation of corresponding regions of interest in a collection of aligned images that does not require labeled training data. Instead, a latent atlas, initialized by at most a single manual segmentation, is inferred from the evolving segmentations of the ensemble. The algorithm is based on probabilistic principles but is solved using partial differential equations (PDEs) and energy minimization criteria. We evaluate the method on two datasets, segmenting subcortical and cortical structures in a multi-subject study and extracting brain tumors in a single-subject multi-modal longitudinal experiment. We compare the segmentation results to manual segmentations, when those exist, and to the results of a state-of-the-art atlas-based segmentation method. The quality of the results supports the latent atlas as a promising alternative when existing atlases are not compatible with the images to be segmented. PMID:20580305

Multi-atlas segmentation of the cartilage in knee MR images with sequential volume- and bone-mask-based registrations

NASA Astrophysics Data System (ADS)

Lee, Han Sang; Kim, Hyeun A.; Kim, Hyeonjin; Hong, Helen; Yoon, Young Cheol; Kim, Junmo

2016-03-01

In spite of its clinical importance in diagnosis of osteoarthritis, segmentation of cartilage in knee MRI remains a challenging task due to its shape variability and low contrast with surrounding soft tissues and synovial fluid. In this paper, we propose a multi-atlas segmentation of cartilage in knee MRI with sequential atlas registrations and locallyweighted voting (LWV). First, bone is segmented by sequential volume- and object-based registrations and LWV. Second, to overcome the shape variability of cartilage, cartilage is segmented by bone-mask-based registration and LWV. In experiments, the proposed method improved the bone segmentation by reducing misclassified bone region, and enhanced the cartilage segmentation by preventing cartilage leakage into surrounding similar intensity region, with the help of sequential registrations and LWV.

A 3D Freehand Ultrasound System for Multi-view Reconstructions from Sparse 2D Scanning Planes

PubMed Central

2011-01-01

Background A significant limitation of existing 3D ultrasound systems comes from the fact that the majority of them work with fixed acquisition geometries. As a result, the users have very limited control over the geometry of the 2D scanning planes. Methods We present a low-cost and flexible ultrasound imaging system that integrates several image processing components to allow for 3D reconstructions from limited numbers of 2D image planes and multiple acoustic views. Our approach is based on a 3D freehand ultrasound system that allows users to control the 2D acquisition imaging using conventional 2D probes. For reliable performance, we develop new methods for image segmentation and robust multi-view registration. We first present a new hybrid geometric level-set approach that provides reliable segmentation performance with relatively simple initializations and minimum edge leakage. Optimization of the segmentation model parameters and its effect on performance is carefully discussed. Second, using the segmented images, a new coarse to fine automatic multi-view registration method is introduced. The approach uses a 3D Hotelling transform to initialize an optimization search. Then, the fine scale feature-based registration is performed using a robust, non-linear least squares algorithm. The robustness of the multi-view registration system allows for accurate 3D reconstructions from sparse 2D image planes. Results Volume measurements from multi-view 3D reconstructions are found to be consistently and significantly more accurate than measurements from single view reconstructions. The volume error of multi-view reconstruction is measured to be less than 5% of the true volume. We show that volume reconstruction accuracy is a function of the total number of 2D image planes and the number of views for calibrated phantom. In clinical in-vivo cardiac experiments, we show that volume estimates of the left ventricle from multi-view reconstructions are found to be in better agreement with clinical measures than measures from single view reconstructions. Conclusions Multi-view 3D reconstruction from sparse 2D freehand B-mode images leads to more accurate volume quantification compared to single view systems. The flexibility and low-cost of the proposed system allow for fine control of the image acquisition planes for optimal 3D reconstructions from multiple views. PMID:21251284

A 3D freehand ultrasound system for multi-view reconstructions from sparse 2D scanning planes.

PubMed

Yu, Honggang; Pattichis, Marios S; Agurto, Carla; Beth Goens, M

2011-01-20

A significant limitation of existing 3D ultrasound systems comes from the fact that the majority of them work with fixed acquisition geometries. As a result, the users have very limited control over the geometry of the 2D scanning planes. We present a low-cost and flexible ultrasound imaging system that integrates several image processing components to allow for 3D reconstructions from limited numbers of 2D image planes and multiple acoustic views. Our approach is based on a 3D freehand ultrasound system that allows users to control the 2D acquisition imaging using conventional 2D probes.For reliable performance, we develop new methods for image segmentation and robust multi-view registration. We first present a new hybrid geometric level-set approach that provides reliable segmentation performance with relatively simple initializations and minimum edge leakage. Optimization of the segmentation model parameters and its effect on performance is carefully discussed. Second, using the segmented images, a new coarse to fine automatic multi-view registration method is introduced. The approach uses a 3D Hotelling transform to initialize an optimization search. Then, the fine scale feature-based registration is performed using a robust, non-linear least squares algorithm. The robustness of the multi-view registration system allows for accurate 3D reconstructions from sparse 2D image planes. Volume measurements from multi-view 3D reconstructions are found to be consistently and significantly more accurate than measurements from single view reconstructions. The volume error of multi-view reconstruction is measured to be less than 5% of the true volume. We show that volume reconstruction accuracy is a function of the total number of 2D image planes and the number of views for calibrated phantom. In clinical in-vivo cardiac experiments, we show that volume estimates of the left ventricle from multi-view reconstructions are found to be in better agreement with clinical measures than measures from single view reconstructions. Multi-view 3D reconstruction from sparse 2D freehand B-mode images leads to more accurate volume quantification compared to single view systems. The flexibility and low-cost of the proposed system allow for fine control of the image acquisition planes for optimal 3D reconstructions from multiple views.

Initiatives (Part 1): Keystone; Cycle Time Puzzle, A Full-Scale Challenge; Foot to Foot, Face to Face; Change Management; Multi-Element Team Challenge.

ERIC Educational Resources Information Center

Schoel, Jim; Butler, Steve; Murray, Mark; Gass, Mike; Carrick, Moe

2001-01-01

Presents five group problem-solving initiatives for use in adventure and experiential settings, focusing on conflict resolution, corporate workplace issues, or adjustment to change. Includes target group, group size, time and space needs, activity level, overview, goals, props, instructions, and suggestions for framing and debriefing the…

76 FR 14959 - Fall Creek Hydro, LLC; Notice of Application Tendered for Filing With the Commission and...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-18

... facilities: (1) An intake structure located on the face of the Corps dam and installed directly above one of the existing intake structures; (2) two 8-foot-diameter by 110-foot-long steel penstocks that would..., among other things, Eicher fish screens, steel pipes, multi-level release ports, open channels, a fish...

[Foot stress simulator for biomechanical in vitro studies of lower leg segments].

PubMed

Rosenbaum, D; Schmitt, H; Bertsch, C; Bauer, G; Claes, L

1996-05-01

In this paper we describe a foot-loading simulator that permits in vitro studies on human lower leg and foot specimens. The specimens are fixed in a jig and loaded axially with the aid of a pneumatic cylinder. The resulting transfer of forces through the ankle joint complex and Chopart's articulation (line) can be demonstrated on a pressure-sensitive film. Plantar pressure measurements obtained in patients or normal subjects can be used to ensure the comparability of in vivo and in vitro measurements. The supporting platform can be tilted in such a manner as to provide a range of foot positions up to 20 degrees in plantar- or dorsiflexion, eversion or inversion. The system is used for investigating the effects on the intra-articular pressures and plantar pressure patterns of physiological muscle activity and pathological conditions following fracture of the calcaneum or damage to the lateral ligament. By way of an example, the effects of muscle forces on plantar pressure distribution are presented.

KSC-07pp1466

NASA Image and Video Library

2007-06-08

KENNEDY SPACE CENTER, FLA. -- Smoke and steam billow across Launch Pad 39A as Space Shuttle Atlantis, trailing columns of fire from the solid rocket boosters, hurtles into the sky on mission STS-117 to the International Space Station. At left is the fixed service structure with the 80-foot-tall lightning mast on top. At right is the 290-foot-high water tower that supplies the water for sound suppression. Liftoff was on-time at 7:38:04 p.m. EDT. The shuttle is delivering a new segment to the starboard side of the International Space Station's backbone, known as the truss. Three spacewalks are planned to install the S3/S4 truss segment, deploy a set of solar arrays and prepare them for operation. STS-117 is the 118th space shuttle flight, the 21st flight to the station, the 28th flight for Atlantis and the first of four flights planned for 2007. Photo credit: NASA/Tony Gray & Don Kight

Integrated modeling analysis of a novel hexapod and its application in active surface

NASA Astrophysics Data System (ADS)

Yang, Dehua; Zago, Lorenzo; Li, Hui; Lambert, Gregory; Zhou, Guohua; Li, Guoping

2011-09-01

This paper presents the concept and integrated modeling analysis of a novel mechanism, a 3-CPS/RPPS hexapod, for supporting segmented reflectors for radio telescopes and eventually segmented mirrors of optical telescopes. The concept comprises a novel type of hexapod with an original organization of actuators hence degrees of freedom, based on a swaying arm based design concept. Afterwards, with specially designed connecting joints between panels/segments, an iso-static master-slave active surface concept can be achieved for any triangular and/or hexagonal panel/segment pattern. The integrated modeling comprises all the multifold sizing and performance aspects which must be evaluated concurrently in order to optimize and validate the design and the configuration. In particular, comprehensive investigation of kinematic behavior, dynamic analysis, wave-front error and sensitivity analysis are carried out, where, frequently used tools like MATLAB/SimMechanics, CALFEM and ANSYS are used. Especially, we introduce the finite element method as a competent approach for analyses of the multi-degree of freedom mechanism. Some experimental verifications already performed validating single aspects of the integrated concept are also presented with the results obtained.

A method for automatic grain segmentation of multi-angle cross-polarized microscopic images of sandstone

NASA Astrophysics Data System (ADS)

Jiang, Feng; Gu, Qing; Hao, Huizhen; Li, Na; Wang, Bingqian; Hu, Xiumian

2018-06-01

Automatic grain segmentation of sandstone is to partition mineral grains into separate regions in the thin section, which is the first step for computer aided mineral identification and sandstone classification. The sandstone microscopic images contain a large number of mixed mineral grains where differences among adjacent grains, i.e., quartz, feldspar and lithic grains, are usually ambiguous, which make grain segmentation difficult. In this paper, we take advantage of multi-angle cross-polarized microscopic images and propose a method for grain segmentation with high accuracy. The method consists of two stages, in the first stage, we enhance the SLIC (Simple Linear Iterative Clustering) algorithm, named MSLIC, to make use of multi-angle images and segment the images as boundary adherent superpixels. In the second stage, we propose the region merging technique which combines the coarse merging and fine merging algorithms. The coarse merging merges the adjacent superpixels with less evident boundaries, and the fine merging merges the ambiguous superpixels using the spatial enhanced fuzzy clustering. Experiments are designed on 9 sets of multi-angle cross-polarized images taken from the three major types of sandstones. The results demonstrate both the effectiveness and potential of the proposed method, comparing to the available segmentation methods.

Nephrin is necessary for podocyte recovery following injury in an adult mature glomerulus.

PubMed

Verma, Rakesh; Venkatareddy, Madhusudan; Kalinowski, Anne; Li, Theodore; Kukla, Joanna; Mollin, Ashomathi; Cara-Fuentes, Gabriel; Patel, Sanjeevkumar R; Garg, Puneet

2018-01-01

Nephrin (Nphs1) is an adhesion protein that is expressed at the podocyte intercellular junction in the glomerulus. Nphs1 mutations in humans or deletion in animal genetic models results in a developmental failure of foot process formation. A number of studies have shown decrease in expression of nephrin in various proteinuric kidney diseases as well as in animal models of glomerular disease. Decrease in nephrin expression has been suggested to precede podocyte loss and linked to the progression of kidney disease. Whether the decrease in expression of nephrin is related to loss of podocytes or lead to podocyte detachment is unclear. To answer this central question we generated an inducible model of nephrin deletion (Nphs1Tam-Cre) in order to lower nephrin expression in healthy adult mice. Following tamoxifen-induction there was a 75% decrease in nephrin expression by 14 days. The Nphs1Tam-Cre mice had normal foot process ultrastructure and intact filtration barriers up to 4-6 weeks post-induction. Despite the loss of nephrin expression, the podocyte number and density remained unchanged during the initial period. Unexpectedly, nephrin expression, albeit at low levels persisted at the slit diaphragm up to 16-20 weeks post-tamoxifen induction. The mice became progressively proteinuric with glomerular hypertrophy and scarring reminiscent of focal and segmental glomerulosclerosis at 20 weeks. Four week-old Nphs1 knockout mice subjected to protamine sulfate model of podocyte injury demonstrated failure to recover from foot process effacement following heparin sulfate. Similarly, Nphs1 knockout mice failed to recover following nephrotoxic serum (NTS) with persistence of proteinuria and foot process effacement. Our results suggest that as in development, nephrin is necessary for maintenance of a healthy glomerular filter. In contrast to the developmental phenotype, lowering nephrin expression in a mature glomerulus resulted in a slowly progressive disease that histologically resembles FSGS a disease linked closely with podocyte depletion. Podocytes with low levels of nephrin expression are both susceptible and unable to recover following perturbation. Our results suggest that decreased nephrin expression independent of podocyte loss occurring as an early event in proteinuric kidney diseases might play a role in disease progression.

Source model and Coulomb stress change of 2017 Mw 6.5 Philippine (Ormoc) Earthquake revealed by SAR interferometry

NASA Astrophysics Data System (ADS)

Tsai, M. C.; Hu, J. C.; Yang, Y. H.; Hashimoto, M.; Aurelio, M.; Su, Z.; Escudero, J. A.

2017-12-01

Multi-sight and high spatial resolution interferometric SAR data enhances our ability for mapping detailed coseismic deformation to estimate fault rupture model and to infer the Coulomb stress change associated with a big earthquake. Here, we use multi-sight coseismic interferograms acquired by ALOS-2 and Sentinel-1A satellites to estimate the fault geometry and slip distribution on the fault plane of the 2017 Mw 6.5 Ormoc Earthquake in Leyte island of Philippine. The best fitting model predicts that the coseismic rupture occurs along a fault plane with strike of 325.8º and dip of 78.5ºE. This model infers that the rupture of 2017 Ormoc earthquake is dominated by left-lateral slip with minor dip-slip motion, consistent with the left-lateral strike-slip Philippine fault system. The fault tip has propagated to the ground surface, and the predicted coseismic slip on the surface is about 1 m located at 6.5 km Northeast of Kananga city. Significant slip is concentrated on the fault patches at depth of 0-8 km and an along-strike distance of 20 km with varying slip magnitude from 0.3 m to 2.3 m along the southwest segment of this seismogenic fault. Two minor coseismic fault patches are predicted underneath of the Tononan geothermal field and the creeping segment of the northwest portion of this seismogenic fault. This implies that the high geothermal gradient underneath of the Tongonan geothermal filed could prevent heated rock mass from the coseismic failure. The seismic moment release of our preferred fault model is 7.78×1018 Nm, equivalent to Mw 6.6 event. The Coulomb failure stress (CFS) calculated by the preferred fault model predicts significant positive CFS change on the northwest segment of the Philippine fault in Leyte Island which has coseismic slip deficit and is absent from aftershocks. Consequently, this segment should be considered to have increasing of risk for future seismic hazard.

Modelling foot height and foot shape-related dimensions.

PubMed

Xiong, Shuping; Goonetilleke, Ravindra S; Witana, Channa P; Lee Au, Emily Yim

2008-08-01

The application of foot anthropometry to design good-fitting footwear has been difficult due to the lack of generalised models. This study seeks to model foot dimensions so that the characteristic shapes of feet, especially in the midfoot region, can be understood. Fifty Hong Kong Chinese adults (26 males and 24 females) participated in this study. Their foot lengths, foot widths, ball girths and foot heights were measured and then evaluated using mathematical models. The results showed that there were no significant allometry (p > 0.05) effects of foot length on ball girth and foot width. Foot height showed no direct relationship with foot length. However, a normalisation with respect to foot length and foot height resulted in a significant relationship for both males and females with R(2) greater than 0.97. Due to the lack of a direct relationship between foot height and foot length, the current practice of grading shoes with a constant increase in height or proportionate scaling in response to foot length is less than ideal. The results when validated with other populations can be a significant way forward in the design of footwear that has an improved fit in the height dimension.

Automatic detection of diabetic foot complications with infrared thermography by asymmetric analysis.

PubMed

Liu, Chanjuan; van Netten, Jaap J; van Baal, Jeff G; Bus, Sicco A; van der Heijden, Ferdi

2015-02-01

Early identification of diabetic foot complications and their precursors is essential in preventing their devastating consequences, such as foot infection and amputation. Frequent, automatic risk assessment by an intelligent telemedicine system might be feasible and cost effective. Infrared thermography is a promising modality for such a system. The temperature differences between corresponding areas on contralateral feet are the clinically significant parameters. This asymmetric analysis is hindered by (1) foot segmentation errors, especially when the foot temperature and the ambient temperature are comparable, and by (2) different shapes and sizes between contralateral feet due to deformities or minor amputations. To circumvent the first problem, we used a color image and a thermal image acquired synchronously. Foot regions, detected in the color image, were rigidly registered to the thermal image. This resulted in 97.8% ± 1.1% sensitivity and 98.4% ± 0.5% specificity over 76 high-risk diabetic patients with manual annotation as a reference. Nonrigid landmark-based registration with B-splines solved the second problem. Corresponding points in the two feet could be found regardless of the shapes and sizes of the feet. With that, the temperature difference of the left and right feet could be obtained. © 2015 Society of Photo-Optical Instrumentation Engineers (SPIE)

Glucose-independent segmental phase angles from multi-frequency bioimpedance analysis to discriminate diabetes mellitus.

PubMed

Jun, Min-Ho; Kim, Soochan; Ku, Boncho; Cho, JungHee; Kim, Kahye; Yoo, Ho-Ryong; Kim, Jaeuk U

2018-01-12

We investigated segmental phase angles (PAs) in the four limbs using a multi-frequency bioimpedance analysis (MF-BIA) technique for noninvasively diagnosing diabetes mellitus. We conducted a meal tolerance test (MTT) for 45 diabetic and 45 control subjects stratified by age, sex and body mass index (BMI). HbA1c and the waist-to-hip-circumference ratio (WHR) were measured before meal intake, and we measured the glucose levels and MF-BIA PAs 5 times for 2 hours after meal intake. We employed a t-test to examine the statistical significance and the area under the curve (AUC) of the receiver operating characteristics (ROC) to test the classification accuracy using segmental PAs at 5, 50, and 250 kHz. Segmental PAs were independent of the HbA1c or glucose levels, or their changes caused by the MTT. However, the segmental PAs were good indicators for noninvasively screening diabetes In particular, leg PAs in females and arm PAs in males showed best classification accuracy (AUC = 0.827 for males, AUC = 0.845 for females). Lastly, we introduced the PA at maximum reactance (PAmax), which is independent of measurement frequencies and can be obtained from any MF-BIA device using a Cole-Cole model, thus showing potential as a useful biomarker for diabetes.

Efficient patient modeling for visuo-haptic VR simulation using a generic patient atlas.

PubMed

Mastmeyer, Andre; Fortmeier, Dirk; Handels, Heinz

2016-08-01

This work presents a new time-saving virtual patient modeling system by way of example for an existing visuo-haptic training and planning virtual reality (VR) system for percutaneous transhepatic cholangio-drainage (PTCD). Our modeling process is based on a generic patient atlas to start with. It is defined by organ-specific optimized models, method modules and parameters, i.e. mainly individual segmentation masks, transfer functions to fill the gaps between the masks and intensity image data. In this contribution, we show how generic patient atlases can be generalized to new patient data. The methodology consists of patient-specific, locally-adaptive transfer functions and dedicated modeling methods such as multi-atlas segmentation, vessel filtering and spline-modeling. Our full image volume segmentation algorithm yields median DICE coefficients of 0.98, 0.93, 0.82, 0.74, 0.51 and 0.48 regarding soft-tissue, liver, bone, skin, blood and bile vessels for ten test patients and three selected reference patients. Compared to standard slice-wise manual contouring time saving is remarkable. Our segmentation process shows out efficiency and robustness for upper abdominal puncture simulation systems. This marks a significant step toward establishing patient-specific training and hands-on planning systems in a clinical environment. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Modeling and Density Estimation of an Urban Freeway Network Based on Dynamic Graph Hybrid Automata

PubMed Central

Chen, Yangzhou; Guo, Yuqi; Wang, Ying

2017-01-01

In this paper, in order to describe complex network systems, we firstly propose a general modeling framework by combining a dynamic graph with hybrid automata and thus name it Dynamic Graph Hybrid Automata (DGHA). Then we apply this framework to model traffic flow over an urban freeway network by embedding the Cell Transmission Model (CTM) into the DGHA. With a modeling procedure, we adopt a dual digraph of road network structure to describe the road topology, use linear hybrid automata to describe multi-modes of dynamic densities in road segments and transform the nonlinear expressions of the transmitted traffic flow between two road segments into piecewise linear functions in terms of multi-mode switchings. This modeling procedure is modularized and rule-based, and thus is easily-extensible with the help of a combination algorithm for the dynamics of traffic flow. It can describe the dynamics of traffic flow over an urban freeway network with arbitrary topology structures and sizes. Next we analyze mode types and number in the model of the whole freeway network, and deduce a Piecewise Affine Linear System (PWALS) model. Furthermore, based on the PWALS model, a multi-mode switched state observer is designed to estimate the traffic densities of the freeway network, where a set of observer gain matrices are computed by using the Lyapunov function approach. As an example, we utilize the PWALS model and the corresponding switched state observer to traffic flow over Beijing third ring road. In order to clearly interpret the principle of the proposed method and avoid computational complexity, we adopt a simplified version of Beijing third ring road. Practical application for a large-scale road network will be implemented by decentralized modeling approach and distributed observer designing in the future research. PMID:28353664

Modeling and Density Estimation of an Urban Freeway Network Based on Dynamic Graph Hybrid Automata.

PubMed

Chen, Yangzhou; Guo, Yuqi; Wang, Ying

2017-03-29

In this paper, in order to describe complex network systems, we firstly propose a general modeling framework by combining a dynamic graph with hybrid automata and thus name it Dynamic Graph Hybrid Automata (DGHA). Then we apply this framework to model traffic flow over an urban freeway network by embedding the Cell Transmission Model (CTM) into the DGHA. With a modeling procedure, we adopt a dual digraph of road network structure to describe the road topology, use linear hybrid automata to describe multi-modes of dynamic densities in road segments and transform the nonlinear expressions of the transmitted traffic flow between two road segments into piecewise linear functions in terms of multi-mode switchings. This modeling procedure is modularized and rule-based, and thus is easily-extensible with the help of a combination algorithm for the dynamics of traffic flow. It can describe the dynamics of traffic flow over an urban freeway network with arbitrary topology structures and sizes. Next we analyze mode types and number in the model of the whole freeway network, and deduce a Piecewise Affine Linear System (PWALS) model. Furthermore, based on the PWALS model, a multi-mode switched state observer is designed to estimate the traffic densities of the freeway network, where a set of observer gain matrices are computed by using the Lyapunov function approach. As an example, we utilize the PWALS model and the corresponding switched state observer to traffic flow over Beijing third ring road. In order to clearly interpret the principle of the proposed method and avoid computational complexity, we adopt a simplified version of Beijing third ring road. Practical application for a large-scale road network will be implemented by decentralized modeling approach and distributed observer designing in the future research.

Foot shape modeling.

PubMed

Luximon, Ameersing; Goonetilleke, Ravindra S

2004-01-01

This study is an attempt to show how a "standard" foot can be parameterized using foot length, foot width, foot height, and a measure of foot curvature so that foot shape can be predicted using these simple anthropometric measures. The prediction model was generated using 40 Hong Kong Chinese men, and the model was validated using a different group of 25 Hong Kong Chinese men. The results show that each individual foot shape may be predicted to a mean accuracy of 2.1 mm for the left foot and 2.4 mm for the right foot. Application of this research includes the potential design and development of custom footwear without the necessity of expensive 3-D scanning of feet.

Segmented frequency-domain fluorescence lifetime measurements: minimizing the effects of photobleaching within a multi-component system.

PubMed

Marwani, Hadi M; Lowry, Mark; Keating, Patrick; Warner, Isiah M; Cook, Robert L

2007-11-01

This study introduces a newly developed frequency segmentation and recombination method for frequency-domain fluorescence lifetime measurements to address the effects of changing fractional contributions over time and minimize the effects of photobleaching within multi-component systems. Frequency segmentation and recombination experiments were evaluated using a two component system consisting of fluorescein and rhodamine B. Comparison of experimental data collected in traditional and segmented fashion with simulated data, generated using different changing fractional contributions, demonstrated the validity of the technique. Frequency segmentation and recombination was also applied to a more complex system consisting of pyrene with Suwannee River fulvic acid reference and was shown to improve recovered lifetimes and fractional intensity contributions. It was observed that photobleaching in both systems led to errors in recovered lifetimes which can complicate the interpretation of lifetime results. Results showed clear evidence that the frequency segmentation and recombination method reduced errors resulting from a changing fractional contribution in a multi-component system, and allowed photobleaching issues to be addressed by commercially available instrumentation.

Multi-Atlas Segmentation of Biomedical Images: A Survey

PubMed Central

Iglesias, Juan Eugenio; Sabuncu, Mert R.

2015-01-01

Multi-atlas segmentation (MAS), first introduced and popularized by the pioneering work of Rohlfing, Brandt, Menzel and Maurer Jr (2004), Klein, Mensh, Ghosh, Tourville and Hirsch (2005), and Heckemann, Hajnal, Aljabar, Rueckert and Hammers (2006), is becoming one of the most widely-used and successful image segmentation techniques in biomedical applications. By manipulating and utilizing the entire dataset of “atlases” (training images that have been previously labeled, e.g., manually by an expert), rather than some model-based average representation, MAS has the flexibility to better capture anatomical variation, thus offering superior segmentation accuracy. This benefit, however, typically comes at a high computational cost. Recent advancements in computer hardware and image processing software have been instrumental in addressing this challenge and facilitated the wide adoption of MAS. Today, MAS has come a long way and the approach includes a wide array of sophisticated algorithms that employ ideas from machine learning, probabilistic modeling, optimization, and computer vision, among other fields. This paper presents a survey of published MAS algorithms and studies that have applied these methods to various biomedical problems. In writing this survey, we have three distinct aims. Our primary goal is to document how MAS was originally conceived, later evolved, and now relates to alternative methods. Second, this paper is intended to be a detailed reference of past research activity in MAS, which now spans over a decade (2003 – 2014) and entails novel methodological developments and application-specific solutions. Finally, our goal is to also present a perspective on the future of MAS, which, we believe, will be one of the dominant approaches in biomedical image segmentation. PMID:26201875

Creation of 3D Multi-Body Orthodontic Models by Using Independent Imaging Sensors

PubMed Central

Barone, Sandro; Paoli, Alessandro; Razionale, Armando Viviano

2013-01-01

In the field of dental health care, plaster models combined with 2D radiographs are widely used in clinical practice for orthodontic diagnoses. However, complex malocclusions can be better analyzed by exploiting 3D digital dental models, which allow virtual simulations and treatment planning processes. In this paper, dental data captured by independent imaging sensors are fused to create multi-body orthodontic models composed of teeth, oral soft tissues and alveolar bone structures. The methodology is based on integrating Cone-Beam Computed Tomography (CBCT) and surface structured light scanning. The optical scanner is used to reconstruct tooth crowns and soft tissues (visible surfaces) through the digitalization of both patients' mouth impressions and plaster casts. These data are also used to guide the segmentation of internal dental tissues by processing CBCT data sets. The 3D individual dental tissues obtained by the optical scanner and the CBCT sensor are fused within multi-body orthodontic models without human supervisions to identify target anatomical structures. The final multi-body models represent valuable virtual platforms to clinical diagnostic and treatment planning. PMID:23385416

Creation of 3D multi-body orthodontic models by using independent imaging sensors.

PubMed

Barone, Sandro; Paoli, Alessandro; Razionale, Armando Viviano

2013-02-05

In the field of dental health care, plaster models combined with 2D radiographs are widely used in clinical practice for orthodontic diagnoses. However, complex malocclusions can be better analyzed by exploiting 3D digital dental models, which allow virtual simulations and treatment planning processes. In this paper, dental data captured by independent imaging sensors are fused to create multi-body orthodontic models composed of teeth, oral soft tissues and alveolar bone structures. The methodology is based on integrating Cone-Beam Computed Tomography (CBCT) and surface structured light scanning. The optical scanner is used to reconstruct tooth crowns and soft tissues (visible surfaces) through the digitalization of both patients' mouth impressions and plaster casts. These data are also used to guide the segmentation of internal dental tissues by processing CBCT data sets. The 3D individual dental tissues obtained by the optical scanner and the CBCT sensor are fused within multi-body orthodontic models without human supervisions to identify target anatomical structures. The final multi-body models represent valuable virtual platforms to clinical diagnostic and treatment planning.

Oriented active shape models.

PubMed

Liu, Jiamin; Udupa, Jayaram K

2009-04-01

Active shape models (ASM) are widely employed for recognizing anatomic structures and for delineating them in medical images. In this paper, a novel strategy called oriented active shape models (OASM) is presented in an attempt to overcome the following five limitations of ASM: 1) lower delineation accuracy, 2) the requirement of a large number of landmarks, 3) sensitivity to search range, 4) sensitivity to initialization, and 5) inability to fully exploit the specific information present in the given image to be segmented. OASM effectively combines the rich statistical shape information embodied in ASM with the boundary orientedness property and the globally optimal delineation capability of the live wire methodology of boundary segmentation. The latter characteristics allow live wire to effectively separate an object boundary from other nonobject boundaries with similar properties especially when they come very close in the image domain. The approach leads to a two-level dynamic programming method, wherein the first level corresponds to boundary recognition and the second level corresponds to boundary delineation, and to an effective automatic initialization method. The method outputs a globally optimal boundary that agrees with the shape model if the recognition step is successful in bringing the model close to the boundary in the image. Extensive evaluation experiments have been conducted by utilizing 40 image (magnetic resonance and computed tomography) data sets in each of five different application areas for segmenting breast, liver, bones of the foot, and cervical vertebrae of the spine. Comparisons are made between OASM and ASM based on precision, accuracy, and efficiency of segmentation. Accuracy is assessed using both region-based false positive and false negative measures and boundary-based distance measures. The results indicate the following: 1) The accuracy of segmentation via OASM is considerably better than that of ASM; 2) The number of landmarks can be reduced by a factor of 3 in OASM over that in ASM; 3) OASM becomes largely independent of search range and initialization becomes automatic. All three benefits of OASM ensue mainly from the severe constraints brought in by the boundary-orientedness property of live wire and the globally optimal solution found by the 2-level dynamic programming algorithm.

Multi-atlas pancreas segmentation: Atlas selection based on vessel structure.

PubMed

Karasawa, Ken'ichi; Oda, Masahiro; Kitasaka, Takayuki; Misawa, Kazunari; Fujiwara, Michitaka; Chu, Chengwen; Zheng, Guoyan; Rueckert, Daniel; Mori, Kensaku

2017-07-01

Automated organ segmentation from medical images is an indispensable component for clinical applications such as computer-aided diagnosis (CAD) and computer-assisted surgery (CAS). We utilize a multi-atlas segmentation scheme, which has recently been used in different approaches in the literature to achieve more accurate and robust segmentation of anatomical structures in computed tomography (CT) volume data. Among abdominal organs, the pancreas has large inter-patient variability in its position, size and shape. Moreover, the CT intensity of the pancreas closely resembles adjacent tissues, rendering its segmentation a challenging task. Due to this, conventional intensity-based atlas selection for pancreas segmentation often fails to select atlases that are similar in pancreas position and shape to those of the unlabeled target volume. In this paper, we propose a new atlas selection strategy based on vessel structure around the pancreatic tissue and demonstrate its application to a multi-atlas pancreas segmentation. Our method utilizes vessel structure around the pancreas to select atlases with high pancreatic resemblance to the unlabeled volume. Also, we investigate two types of applications of the vessel structure information to the atlas selection. Our segmentations were evaluated on 150 abdominal contrast-enhanced CT volumes. The experimental results showed that our approach can segment the pancreas with an average Jaccard index of 66.3% and an average Dice overlap coefficient of 78.5%. Copyright © 2017 Elsevier B.V. All rights reserved.

Hemodynamic analysis of sequential graft from right coronary system to left coronary system.

PubMed

Wang, Wenxin; Mao, Boyan; Wang, Haoran; Geng, Xueying; Zhao, Xi; Zhang, Huixia; Xie, Jinsheng; Zhao, Zhou; Lian, Bo; Liu, Youjun

2016-12-28

Sequential and single grafting are two surgical procedures of coronary artery bypass grafting. However, it remains unclear if the sequential graft can be used between the right and left coronary artery system. The purpose of this paper is to clarify the possibility of right coronary artery system anastomosis to left coronary system. A patient-specific 3D model was first reconstructed based on coronary computed tomography angiography (CCTA) images. Two different grafts, the normal multi-graft (Model 1) and the novel multi-graft (Model 2), were then implemented on this patient-specific model using virtual surgery techniques. In Model 1, the single graft was anastomosed to right coronary artery (RCA) and the sequential graft was adopted to anastomose left anterior descending (LAD) and left circumflex artery (LCX). While in Model 2, the single graft was anastomosed to LAD and the sequential graft was adopted to anastomose RCA and LCX. A zero-dimensional/three-dimensional (0D/3D) coupling method was used to realize the multi-scale simulation of both the pre-operative and two post-operative models. Flow rates in the coronary artery and grafts were obtained. The hemodynamic parameters were also showed, including wall shear stress (WSS) and oscillatory shear index (OSI). The area of low WSS and OSI in Model 1 was much less than that in Model 2. Model 1 shows optimistic hemodynamic modifications which may enhance the long-term patency of grafts. The anterior segments of sequential graft have better long-term patency than the posterior segments. With rational spatial position of the heart vessels, the last anastomosis of sequential graft should be connected to the main branch.

Central focused convolutional neural networks: Developing a data-driven model for lung nodule segmentation.

PubMed

Wang, Shuo; Zhou, Mu; Liu, Zaiyi; Liu, Zhenyu; Gu, Dongsheng; Zang, Yali; Dong, Di; Gevaert, Olivier; Tian, Jie

2017-08-01

Accurate lung nodule segmentation from computed tomography (CT) images is of great importance for image-driven lung cancer analysis. However, the heterogeneity of lung nodules and the presence of similar visual characteristics between nodules and their surroundings make it difficult for robust nodule segmentation. In this study, we propose a data-driven model, termed the Central Focused Convolutional Neural Networks (CF-CNN), to segment lung nodules from heterogeneous CT images. Our approach combines two key insights: 1) the proposed model captures a diverse set of nodule-sensitive features from both 3-D and 2-D CT images simultaneously; 2) when classifying an image voxel, the effects of its neighbor voxels can vary according to their spatial locations. We describe this phenomenon by proposing a novel central pooling layer retaining much information on voxel patch center, followed by a multi-scale patch learning strategy. Moreover, we design a weighted sampling to facilitate the model training, where training samples are selected according to their degree of segmentation difficulty. The proposed method has been extensively evaluated on the public LIDC dataset including 893 nodules and an independent dataset with 74 nodules from Guangdong General Hospital (GDGH). We showed that CF-CNN achieved superior segmentation performance with average dice scores of 82.15% and 80.02% for the two datasets respectively. Moreover, we compared our results with the inter-radiologists consistency on LIDC dataset, showing a difference in average dice score of only 1.98%. Copyright © 2017. Published by Elsevier B.V.

Research Technology

NASA Image and Video Library

1998-09-16

A team of engineers at Marshall Space Flight Center (MSFC) has designed, fabricated, and tested the first solar thermal engine, a non-chemical rocket that produces lower thrust but has better thrust efficiency than the chemical combustion engines. This segmented array of mirrors is the solar concentrator test stand at MSFC for firing the thermal propulsion engines. The 144 mirrors are combined to form an 18-foot diameter array concentrator. The mirror segments are aluminum hexagons that have the reflective surface cut into it by a diamond turning machine, which is developed by MSFC Space Optics Manufacturing Technology Center.

A single-photon fluorescence and multi-photon spectroscopic study of atherosclerotic lesions

NASA Astrophysics Data System (ADS)

Smith, Michael S. D.; Ko, Alex C. T.; Ridsdale, Andrew; Schattka, Bernie; Pegoraro, Adrian; Hewko, Mark D.; Shiomi, Masashi; Stolow, Albert; Sowa, Michael G.

2009-06-01

In this study we compare the single-photon autofluorescence and multi-photon emission spectra obtained from the luminal surface of healthy segments of artery with segments where there are early atherosclerotic lesions. Arterial tissue was harvested from atherosclerosis-prone WHHL-MI rabbits (Watanabe heritable hyperlipidemic rabbit-myocardial infarction), an animal model which mimics spontaneous myocardial infarction in humans. Single photon fluorescence emission spectra of samples were acquired using a simple spectrofluorometer set-up with 400 nm excitation. Samples were also investigated using a home built multi-photon microscope based on a Ti:sapphire femto-second oscillator. The excitation wavelength was set at 800 nm with a ~100 femto-second pulse width. Epi-multi-photon spectroscopic signals were collected through a fibre-optics coupled spectrometer. While the single-photon fluorescence spectra of atherosclerotic lesions show minimal spectroscopic difference from those of healthy arterial tissue, the multi-photon spectra collected from atherosclerotic lesions show marked changes in the relative intensity of two-photon excited fluorescence (TPEF) and second-harmonic generation (SHG) signals when compared with those from healthy arterial tissue. The observed sharp increase of the relative SHG signal intensity in a plaque is in agreement with the known pathology of early lesions which have increased collagen content.

Kinematic adaptations of the hindfoot, forefoot, and hallux during cross-slope walking.

PubMed

Damavandi, Mohsen; Dixon, Philippe C; Pearsall, David J

2010-07-01

Despite cross-slope surfaces being a regular feature of our environment, little is known about segmental adaptations required to maintain both balance and forward locomotion. The purpose of this study was to determine kinematic adaptations of the foot segments in relation to transverse (cross-sloped) walking surfaces. Ten young adult males walked barefoot along an inclinable walkway (level, 0° and cross-slope, 10°). Kinematic adaptations of hindfoot with respect to tibia (HF/TB), forefoot with respect to hindfoot (FF/HF), and hallux with respect to forefoot (HX/FF) in level walking (LW), inclined walking up-slope (IWU), i.e., the foot at the higher elevation, and inclined walking down-slope (IWD), i.e., the foot at the lower elevation, were measured. Multivariate analysis of variance (MANOVA) for repeated measures was used to analyze the data. In the sagittal plane, the relative FF/HF and HX/FF plantar/dorsiflexion angles differed across conditions (p=0.024 and p=0.026, respectively). More importantly, numerous frontal plane alterations occurred. For the HF/TB angle, inversion of IWU and eversion of IWD was seen at heel-strike (p<0.001). This pattern reversed with IWU showing eversion and IWD inversion in early stance (p=0.024). For the FF/HF angle, significant differences were observed in mid-stance with IWD revealing inversion while IWU was everted (p<0.004). At toe-off, the pattern switched to eversion of IWD and inversion of IWU (p=0.032). The information obtained from this study enhances our understanding of the kinematics of the human foot in stance during level and cross-slope walking. Copyright © 2010 Elsevier B.V. All rights reserved.

Multi-atlas segmentation with joint label fusion and corrective learning—an open source implementation

PubMed Central

Wang, Hongzhi; Yushkevich, Paul A.

2013-01-01

Label fusion based multi-atlas segmentation has proven to be one of the most competitive techniques for medical image segmentation. This technique transfers segmentations from expert-labeled images, called atlases, to a novel image using deformable image registration. Errors produced by label transfer are further reduced by label fusion that combines the results produced by all atlases into a consensus solution. Among the proposed label fusion strategies, weighted voting with spatially varying weight distributions derived from atlas-target intensity similarity is a simple and highly effective label fusion technique. However, one limitation of most weighted voting methods is that the weights are computed independently for each atlas, without taking into account the fact that different atlases may produce similar label errors. To address this problem, we recently developed the joint label fusion technique and the corrective learning technique, which won the first place of the 2012 MICCAI Multi-Atlas Labeling Challenge and was one of the top performers in 2013 MICCAI Segmentation: Algorithms, Theory and Applications (SATA) challenge. To make our techniques more accessible to the scientific research community, we describe an Insight-Toolkit based open source implementation of our label fusion methods. Our implementation extends our methods to work with multi-modality imaging data and is more suitable for segmentation problems with multiple labels. We demonstrate the usage of our tools through applying them to the 2012 MICCAI Multi-Atlas Labeling Challenge brain image dataset and the 2013 SATA challenge canine leg image dataset. We report the best results on these two datasets so far. PMID:24319427

7. Detail, segmentalarched, 12/12 doublehung windows (lower sash boarded against ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

7. Detail, segmental-arched, 12/12 double-hung windows (lower sash boarded against entry), southeast elevation, Roundhouse Machine Shop Extension, Southern Pacific Railroad Carlin Shops, view to northwest (210mm lens). - Southern Pacific Railroad, Carlin Shops, Roundhouse Machine Shop Extension, Foot of Sixth Street, Carlin, Elko County, NV

Application of Modern Control Design Methodologies to a Multi-Segmented Deformable Mirror System

DTIC Science & Technology

1991-05-23

state matrices, and the state equations are X= Ax + Bu (2.3) y = Cm + Du (2.4) The only dynamics modeled are associated with the six segment phasing...relationship between the L 2 and H2 spaces, the vector H2 norm can be found from the application of Parseval’s Theorem to Equation 3.1, yielding V112...of this minimization problem can be found using Riccati equations {1]. ’With a slight abuse of notation, time domain functions and frequency domain

Automated unsupervised multi-parametric classification of adipose tissue depots in skeletal muscle

PubMed Central

Valentinitsch, Alexander; Karampinos, Dimitrios C.; Alizai, Hamza; Subburaj, Karupppasamy; Kumar, Deepak; Link, Thomas M.; Majumdar, Sharmila

2012-01-01

Purpose To introduce and validate an automated unsupervised multi-parametric method for segmentation of the subcutaneous fat and muscle regions in order to determine subcutaneous adipose tissue (SAT) and intermuscular adipose tissue (IMAT) areas based on data from a quantitative chemical shift-based water-fat separation approach. Materials and Methods Unsupervised standard k-means clustering was employed to define sets of similar features (k = 2) within the whole multi-modal image after the water-fat separation. The automated image processing chain was composed of three primary stages including tissue, muscle and bone region segmentation. The algorithm was applied on calf and thigh datasets to compute SAT and IMAT areas and was compared to a manual segmentation. Results The IMAT area using the automatic segmentation had excellent agreement with the IMAT area using the manual segmentation for all the cases in the thigh (R2: 0.96) and for cases with up to moderate IMAT area in the calf (R2: 0.92). The group with the highest grade of muscle fat infiltration in the calf had the highest error in the inner SAT contour calculation. Conclusion The proposed multi-parametric segmentation approach combined with quantitative water-fat imaging provides an accurate and reliable method for an automated calculation of the SAT and IMAT areas reducing considerably the total post-processing time. PMID:23097409

Saturn Apollo Program

NASA Image and Video Library

1964-03-03

Two technicians apply insulation to the outer surface of the S-II second stage booster for the Saturn V moon rocket. The towering 363-foot Saturn V was a multi-stage, multi-engine launch vehicle standing taller than the Statue of Liberty. Altogether, the Saturn V engines produced as much power as 85 Hoover Dams.

Saturn Apollo Program

NASA Image and Video Library

1960-01-01

A NASA technician is dwarfed by the gigantic Third Stage (S-IVB) as it rests on supports in a facility at KSC. The towering 363-foot Saturn V was a multi-stage, multi-engine launch vehicle standing taller than the Statue of Liberty. Altogether, the Saturn V engines produced as much power as 85 Hoover Dams.

Automatic liver segmentation in computed tomography using general-purpose shape modeling methods.

PubMed

Spinczyk, Dominik; Krasoń, Agata

2018-05-29

Liver segmentation in computed tomography is required in many clinical applications. The segmentation methods used can be classified according to a number of criteria. One important criterion for method selection is the shape representation of the segmented organ. The aim of the work is automatic liver segmentation using general purpose shape modeling methods. As part of the research, methods based on shape information at various levels of advancement were used. The single atlas based segmentation method was used as the simplest shape-based method. This method is derived from a single atlas using the deformable free-form deformation of the control point curves. Subsequently, the classic and modified Active Shape Model (ASM) was used, using medium body shape models. As the most advanced and main method generalized statistical shape models, Gaussian Process Morphable Models was used, which are based on multi-dimensional Gaussian distributions of the shape deformation field. Mutual information and sum os square distance were used as similarity measures. The poorest results were obtained for the single atlas method. For the ASM method in 10 analyzed cases for seven test images, the Dice coefficient was above 55[Formula: see text], of which for three of them the coefficient was over 70[Formula: see text], which placed the method in second place. The best results were obtained for the method of generalized statistical distribution of the deformation field. The DICE coefficient for this method was 88.5[Formula: see text] CONCLUSIONS: This value of 88.5 [Formula: see text] Dice coefficient can be explained by the use of general-purpose shape modeling methods with a large variance of the shape of the modeled object-the liver and limitations on the size of our training data set, which was limited to 10 cases. The obtained results in presented fully automatic method are comparable with dedicated methods for liver segmentation. In addition, the deforamtion features of the model can be modeled mathematically by using various kernel functions, which allows to segment the liver on a comparable level using a smaller learning set.

Finite element modeling of a 3D coupled foot-boot model.

PubMed

Qiu, Tian-Xia; Teo, Ee-Chon; Yan, Ya-Bo; Lei, Wei

2011-12-01

Increasingly, musculoskeletal models of the human body are used as powerful tools to study biological structures. The lower limb, and in particular the foot, is of interest because it is the primary physical interaction between the body and the environment during locomotion. The goal of this paper is to adopt the finite element (FE) modeling and analysis approaches to create a state-of-the-art 3D coupled foot-boot model for future studies on biomechanical investigation of stress injury mechanism, foot wear design and parachute landing fall simulation. In the modeling process, the foot-ankle model with lower leg was developed based on Computed Tomography (CT) images using ScanIP, Surfacer and ANSYS. Then, the boot was represented by assembling the FE models of upper, insole, midsole and outsole built based on the FE model of the foot-ankle, and finally the coupled foot-boot model was generated by putting together the models of the lower limb and boot. In this study, the FE model of foot and ankle was validated during balance standing. There was a good agreement in the overall patterns of predicted and measured plantar pressure distribution published in literature. The coupled foot-boot model will be fully validated in the subsequent works under both static and dynamic loading conditions for further studies on injuries investigation in military and sports, foot wear design and characteristics of parachute landing impact in military. Copyright © 2011 IPEM. Published by Elsevier Ltd. All rights reserved.

Ground-motion signature of dynamic ruptures on rough faults

NASA Astrophysics Data System (ADS)

Mai, P. Martin; Galis, Martin; Thingbaijam, Kiran K. S.; Vyas, Jagdish C.

2016-04-01

Natural earthquakes occur on faults characterized by large-scale segmentation and small-scale roughness. This multi-scale geometrical complexity controls the dynamic rupture process, and hence strongly affects the radiated seismic waves and near-field shaking. For a fault system with given segmentation, the question arises what are the conditions for producing large-magnitude multi-segment ruptures, as opposed to smaller single-segment events. Similarly, for variable degrees of roughness, ruptures may be arrested prematurely or may break the entire fault. In addition, fault roughness induces rupture incoherence that determines the level of high-frequency radiation. Using HPC-enabled dynamic-rupture simulations, we generate physically self-consistent rough-fault earthquake scenarios (M~6.8) and their associated near-source seismic radiation. Because these computations are too expensive to be conducted routinely for simulation-based seismic hazard assessment, we thrive to develop an effective pseudo-dynamic source characterization that produces (almost) the same ground-motion characteristics. Therefore, we examine how variable degrees of fault roughness affect rupture properties and the seismic wavefield, and develop a planar-fault kinematic source representation that emulates the observed dynamic behaviour. We propose an effective workflow for improved pseudo-dynamic source modelling that incorporates rough-fault effects and its associated high-frequency radiation in broadband ground-motion computation for simulation-based seismic hazard assessment.

Intrinsic foot muscle volume in experienced runners with and without chronic plantar fasciitis.

PubMed

Cheung, R T H; Sze, L K Y; Mok, N W; Ng, G Y F

2016-09-01

Plantar fasciitis, a common injury in runners, has been speculated to be associated with weakness of the intrinsic foot muscles. A recent study reported that atrophy of the intrinsic forefoot muscles might contribute to plantar fasciitis by destabilizing the medial longitudinal arch. However, intrinsic foot muscle volume difference between individuals with plantar fasciitis and healthy counterparts remains unknown. This study examined the relationship of intrinsic foot muscle volume and incidence of plantar fasciitis. Case-control study. 20 experienced (≥5 years) runners were recruited. Ten of them had bilateral chronic (≥2 years) plantar fasciitis while the others were healthy characteristics-matched runners. Intrinsic muscle volumes of the participants' right foot were scanned with a 1.5T magnetic resonance system and segmented using established methods. Body-mass normalized intrinsic foot muscle volumes were compared between runners with and without chronic plantar fasciitis. There was significant greater rearfoot intrinsic muscle volume in healthy runners than runners with chronic plantar fasciitis (Cohen's d=1.13; p=0.023). A similar trend was also observed in the total intrinsic foot muscle volume but it did not reach a statistical significance (Cohen's d=0.92; p=0.056). Forefoot volume was similar between runners with and without plantar fasciitis. These results suggest that atrophy of intrinsic foot muscles may be associated with symptoms of plantar fasciitis in runners. These findings may provide useful information in rehabilitation strategies of chronic plantar fasciitis. Copyright © 2015 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

A comparison of two multisegment foot models in high-and low-arched athletes.

PubMed

Powell, Douglas W; Williams, D S Blaise; Butler, Robert J

2013-01-01

Malalignment and dysfunction of the foot have been associated with an increased propensity for overuse and traumatic injury in athletes. Several multisegment foot models have been developed to investigate motions in the foot. However, it remains unknown whether the kinematics measured by different multisegment foot models are equivocal. The purpose of the present study is to examine the efficacy of two multisegment foot models in tracking aberrant foot function. Ten high-arched and ten low-arched female athletes walked and ran while ground reaction forces and three-dimensional kinematics were tracked using the Leardini and Oxford multisegment foot models. Ground reaction forces and joint angles were calculated with Visual 3D (C-Motion Inc, Germantown, MD). Repeated-measures analyses of variance were used to analyze peak eversion, time to peak eversion, and eversion excursions. The Leardini model was more sensitive to differences in peak eversion angles than the Oxford model. However, the Oxford model detected differences in eversion excursion values that the Leardini model did not detect. Although both models found differences in frontal plane motion between high- and low-arched athletes, the Leardini multisegment foot model is suggested to be more appropriate as it directly tracks frontal plane midfoot motion during dynamic motion.

Performance of Dispersed Fringe Sensor in the Presence of Segmented Mirror Aberrations: Modeling and Simulation

NASA Technical Reports Server (NTRS)

Shi, Fang; Basinger, Scott A.; Redding, David C.

2006-01-01

Dispersed Fringe Sensing (DFS) is an efficient and robust method for coarse phasing of a segmented primary mirror such as the James Webb Space Telescope (JWST). In this paper, modeling and simulations are used to study the effect of segmented mirror aberrations on the fringe image, DFS signals and DFS detection accuracy. The study has shown due to the pixilation spatial filter effect from DFS signal extraction the effect of wavefront error is reduced and DFS algorithm will be more robust against wavefront aberration by using multi-trace DFS approach. We also studied the JWST Dispersed Hartmann Sensor (DHS) performance in presence of wavefront aberrations caused by the gravity sag and we use the scaled gravity sag to explore the JWST DHS performance relationship with the level of the wavefront aberration. This also includes the effect from line-of-sight jitter.

Automatic Segmentation of Fluorescence Lifetime Microscopy Images of Cells Using Multi-Resolution Community Detection -A First Study

PubMed Central

Hu, Dandan; Sarder, Pinaki; Ronhovde, Peter; Orthaus, Sandra; Achilefu, Samuel; Nussinov, Zohar

2014-01-01

Inspired by a multi-resolution community detection (MCD) based network segmentation method, we suggest an automatic method for segmenting fluorescence lifetime (FLT) imaging microscopy (FLIM) images of cells in a first pilot investigation on two selected images. The image processing problem is framed as identifying segments with respective average FLTs against the background in FLIM images. The proposed method segments a FLIM image for a given resolution of the network defined using image pixels as the nodes and similarity between the FLTs of the pixels as the edges. In the resulting segmentation, low network resolution leads to larger segments, and high network resolution leads to smaller segments. Further, using the proposed method, the mean-square error (MSE) in estimating the FLT segments in a FLIM image was found to consistently decrease with increasing resolution of the corresponding network. The MCD method appeared to perform better than a popular spectral clustering based method in performing FLIM image segmentation. At high resolution, the spectral segmentation method introduced noisy segments in its output, and it was unable to achieve a consistent decrease in MSE with increasing resolution. PMID:24251410

SU-E-J-110: A Novel Level Set Active Contour Algorithm for Multimodality Joint Segmentation/Registration Using the Jensen-Rényi Divergence.

PubMed

Markel, D; Naqa, I El; Freeman, C; Vallières, M

2012-06-01

To present a novel joint segmentation/registration for multimodality image-guided and adaptive radiotherapy. A major challenge to this framework is the sensitivity of many segmentation or registration algorithms to noise. Presented is a level set active contour based on the Jensen-Renyi (JR) divergence to achieve improved noise robustness in a multi-modality imaging space. To present a novel joint segmentation/registration for multimodality image-guided and adaptive radiotherapy. A major challenge to this framework is the sensitivity of many segmentation or registration algorithms to noise. Presented is a level set active contour based on the Jensen-Renyi (JR) divergence to achieve improved noise robustness in a multi-modality imaging space. It was found that JR divergence when used for segmentation has an improved robustness to noise compared to using mutual information, or other entropy-based metrics. The MI metric failed at around 2/3 the noise power than the JR divergence. The JR divergence metric is useful for the task of joint segmentation/registration of multimodality images and shows improved results compared entropy based metric. The algorithm can be easily modified to incorporate non-intensity based images, which would allow applications into multi-modality and texture analysis. © 2012 American Association of Physicists in Medicine.

Exertion and body discomfort perceived symptoms associated with carpentry tasks: an on-site evaluation.

PubMed

Dimov, M; Bhattacharya, A; Lemasters, G; Atterbury, M; Greathouse, L; Ollila-Glenn, N

2000-01-01

The purpose of this study was to determine how carpenters subjectively perceived the exertion level and body discomfort associated with their daily tasks. Two psychophysical instruments were utilized. The Borg Whole Body Physical Exertion Instrument, a measure of overall physical demand, and the Body Segment instrument (modified Bishop-Corlett Scale), a measure of body discomfort, were given to 73 carpenters at the end of a shift. Carpentry specialties evaluated included ceiling, drywall, formwork, finishing work, pile driving, fixtures, welding, and scaffolding. The mean Borg's exertion score for the subjects combining all specialties was 14.4 (+/-2.51 standard deviation), a score between "somewhat hard" and "hard." The perception of whole body physical exertion appeared to be a consequence of the specific task. There was no significant correlation between whole body physical exertion perception and age or the number of years as a carpenter. The findings from the body discomfort scale for the total group indicated that the three primary discomfort frequencies by body segment were mid-to-lower back (65.8%), knees (45.2%), and the neck (28.8%). The next highest discomfort rating by body segment (back, knee, right wrist, right leg/foot, and right shoulder) for those subjects in the top three job specialties represented (drywall, ceiling, and formwork; n = 38) resulted in significantly higher ratings for back (60.5%) than right leg/foot (34.2%) and right shoulder (31.6%). All other body segment ratings were not significantly different from one another using Tukey's studentized range test.

Transforaminal Endoscopic Decompression for Foot Drop Twelve Years After Lumbar Total Disc Replacment: Technical Note.

PubMed

Telfeian, Albert E; Oyelese, Adetokunbo; Fridley, Jared; Gokaslan, Ziya L

2018-05-19

Lumbar total disc replacement (LTDR) is considered for the treatment of lumbar degenerative disc disease with the hope that by preserving motion the long-term fusion complication of adjacent segment disease can be avoided. The complications of LTDR can be divided into approach-related and long-term complications. Very little has been described about the complications and treatment for complications more than 10 years after the device has been implanted. Here we describe a tranforaminal endoscopic discectomy procedure for a patient presenting with foot drop twelve years after a L5-S1 total disc replacement. Copyright © 2018. Published by Elsevier Inc.

Multivariable Parametric Cost Model for Ground Optical Telescope Assembly

NASA Technical Reports Server (NTRS)

Stahl, H. Philip; Rowell, Ginger Holmes; Reese, Gayle; Byberg, Alicia

2005-01-01

A parametric cost model for ground-based telescopes is developed using multivariable statistical analysis of both engineering and performance parameters. While diameter continues to be the dominant cost driver, diffraction-limited wavelength is found to be a secondary driver. Other parameters such as radius of curvature are examined. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e., multi-telescope phased-array systems). Additionally, single variable models Based on aperture diameter are derived.

[Charcot foot treated by correction and arthrodesis of the hindfoot].

PubMed

Wagner, Andreas; Fuhrmann, Renée; Roth, Andreas

2005-10-01

First patient: neuropathic osteoarthropathy with severely deformed foot, plantar ulceration and recurrent purulent infections. Second patient: diabetic osteoarthropathy with pathologic fracture. First patient: 50-year-old man with hereditary sensory and motor neuropathy, plantar ulceration, equinus of the hindfoot, and extensive destruction of all bones of the foot. Recurrent infections necessitated repeated surgical interventions during the last 7 years. At the time of admission purulent infection of the foot. Healing after debridement including a resection of metatarsal bones and part of sequestrated bones of the foot. Patient was left with a severe equinus of the hindfoot. Orthopedic shoes with or without below-knee orthesis. Lengthening of the Achilles tendon and plantar alignment of the calcaneus. Arthrodesis of the hindfoot. Below-knee amputation, if necessary as a primary procedure to combat infection. Arthrodesis of the hindfoot after realignment; an amputation of the foot was refused. Two-stage procedure: treatment of infection followed by astragalectomy and tibiocalcaneal arthrodesis achieved with cancellous lag screws. Bridging of the area of resection with a segment of the fibula. Bony fusion and full load bearing in an orthopedic shoe after 3 months. Recurrence of ulcerations after 20 and 27 months due to wear of ill-fitting shoes. The accompanying purulent process forced the authors to resort to a below-knee amputation and fitting of a prosthesis. Second patient: of this patient only radiographs with a retrograde introduced intramedullary nail are shown.

Multi-Sectional Views Textural Based SVM for MS Lesion Segmentation in Multi-Channels MRIs

PubMed Central

Abdullah, Bassem A; Younis, Akmal A; John, Nigel M

2012-01-01

In this paper, a new technique is proposed for automatic segmentation of multiple sclerosis (MS) lesions from brain magnetic resonance imaging (MRI) data. The technique uses a trained support vector machine (SVM) to discriminate between the blocks in regions of MS lesions and the blocks in non-MS lesion regions mainly based on the textural features with aid of the other features. The classification is done on each of the axial, sagittal and coronal sectional brain view independently and the resultant segmentations are aggregated to provide more accurate output segmentation. The main contribution of the proposed technique described in this paper is the use of textural features to detect MS lesions in a fully automated approach that does not rely on manually delineating the MS lesions. In addition, the technique introduces the concept of the multi-sectional view segmentation to produce verified segmentation. The proposed textural-based SVM technique was evaluated using three simulated datasets and more than fifty real MRI datasets. The results were compared with state of the art methods. The obtained results indicate that the proposed method would be viable for use in clinical practice for the detection of MS lesions in MRI. PMID:22741026

Hippocampal unified multi-atlas network (HUMAN): protocol and scale validation of a novel segmentation tool.

PubMed

Amoroso, N; Errico, R; Bruno, S; Chincarini, A; Garuccio, E; Sensi, F; Tangaro, S; Tateo, A; Bellotti, R

2015-11-21

In this study we present a novel fully automated Hippocampal Unified Multi-Atlas-Networks (HUMAN) algorithm for the segmentation of the hippocampus in structural magnetic resonance imaging. In multi-atlas approaches atlas selection is of crucial importance for the accuracy of the segmentation. Here we present an optimized method based on the definition of a small peri-hippocampal region to target the atlas learning with linear and non-linear embedded manifolds. All atlases were co-registered to a data driven template resulting in a computationally efficient method that requires only one test registration. The optimal atlases identified were used to train dedicated artificial neural networks whose labels were then propagated and fused to obtain the final segmentation. To quantify data heterogeneity and protocol inherent effects, HUMAN was tested on two independent data sets provided by the Alzheimer's Disease Neuroimaging Initiative and the Open Access Series of Imaging Studies. HUMAN is accurate and achieves state-of-the-art performance (Dice[Formula: see text] and Dice[Formula: see text]). It is also a robust method that remains stable when applied to the whole hippocampus or to sub-regions (patches). HUMAN also compares favorably with a basic multi-atlas approach and a benchmark segmentation tool such as FreeSurfer.

Hippocampal unified multi-atlas network (HUMAN): protocol and scale validation of a novel segmentation tool

NASA Astrophysics Data System (ADS)

Amoroso, N.; Errico, R.; Bruno, S.; Chincarini, A.; Garuccio, E.; Sensi, F.; Tangaro, S.; Tateo, A.; Bellotti, R.; Alzheimers Disease Neuroimaging Initiative,the

2015-11-01

In this study we present a novel fully automated Hippocampal Unified Multi-Atlas-Networks (HUMAN) algorithm for the segmentation of the hippocampus in structural magnetic resonance imaging. In multi-atlas approaches atlas selection is of crucial importance for the accuracy of the segmentation. Here we present an optimized method based on the definition of a small peri-hippocampal region to target the atlas learning with linear and non-linear embedded manifolds. All atlases were co-registered to a data driven template resulting in a computationally efficient method that requires only one test registration. The optimal atlases identified were used to train dedicated artificial neural networks whose labels were then propagated and fused to obtain the final segmentation. To quantify data heterogeneity and protocol inherent effects, HUMAN was tested on two independent data sets provided by the Alzheimer’s Disease Neuroimaging Initiative and the Open Access Series of Imaging Studies. HUMAN is accurate and achieves state-of-the-art performance (Dice{{}\\text{ADNI}} =0.929+/- 0.003 and Dice{{}\\text{OASIS}} =0.869+/- 0.002 ). It is also a robust method that remains stable when applied to the whole hippocampus or to sub-regions (patches). HUMAN also compares favorably with a basic multi-atlas approach and a benchmark segmentation tool such as FreeSurfer.

Development and validation of a numerical model for cross-section optimization of a multi-part probe for soft tissue intervention.

PubMed

Frasson, L; Neubert, J; Reina, S; Oldfield, M; Davies, B L; Rodriguez Y Baena, F

2010-01-01

The popularity of minimally invasive surgical procedures is driving the development of novel, safer and more accurate surgical tools. In this context a multi-part probe for soft tissue surgery is being developed in the Mechatronics in Medicine Laboratory at Imperial College, London. This study reports an optimization procedure using finite element methods, for the identification of an interlock geometry able to limit the separation of the segments composing the multi-part probe. An optimal geometry was obtained and the corresponding three-dimensional finite element model validated experimentally. Simulation results are shown to be consistent with the physical experiments. The outcome of this study is an important step in the provision of a novel miniature steerable probe for surgery.

Segmentation of time series with long-range fractal correlations.

PubMed

Bernaola-Galván, P; Oliver, J L; Hackenberg, M; Coronado, A V; Ivanov, P Ch; Carpena, P

2012-06-01

Segmentation is a standard method of data analysis to identify change-points dividing a nonstationary time series into homogeneous segments. However, for long-range fractal correlated series, most of the segmentation techniques detect spurious change-points which are simply due to the heterogeneities induced by the correlations and not to real nonstationarities. To avoid this oversegmentation, we present a segmentation algorithm which takes as a reference for homogeneity, instead of a random i.i.d. series, a correlated series modeled by a fractional noise with the same degree of correlations as the series to be segmented. We apply our algorithm to artificial series with long-range correlations and show that it systematically detects only the change-points produced by real nonstationarities and not those created by the correlations of the signal. Further, we apply the method to the sequence of the long arm of human chromosome 21, which is known to have long-range fractal correlations. We obtain only three segments that clearly correspond to the three regions of different G + C composition revealed by means of a multi-scale wavelet plot. Similar results have been obtained when segmenting all human chromosome sequences, showing the existence of previously unknown huge compositional superstructures in the human genome.

Local variance for multi-scale analysis in geomorphometry.

PubMed

Drăguţ, Lucian; Eisank, Clemens; Strasser, Thomas

2011-07-15

Increasing availability of high resolution Digital Elevation Models (DEMs) is leading to a paradigm shift regarding scale issues in geomorphometry, prompting new solutions to cope with multi-scale analysis and detection of characteristic scales. We tested the suitability of the local variance (LV) method, originally developed for image analysis, for multi-scale analysis in geomorphometry. The method consists of: 1) up-scaling land-surface parameters derived from a DEM; 2) calculating LV as the average standard deviation (SD) within a 3 × 3 moving window for each scale level; 3) calculating the rate of change of LV (ROC-LV) from one level to another, and 4) plotting values so obtained against scale levels. We interpreted peaks in the ROC-LV graphs as markers of scale levels where cells or segments match types of pattern elements characterized by (relatively) equal degrees of homogeneity. The proposed method has been applied to LiDAR DEMs in two test areas different in terms of roughness: low relief and mountainous, respectively. For each test area, scale levels for slope gradient, plan, and profile curvatures were produced at constant increments with either resampling (cell-based) or image segmentation (object-based). Visual assessment revealed homogeneous areas that convincingly associate into patterns of land-surface parameters well differentiated across scales. We found that the LV method performed better on scale levels generated through segmentation as compared to up-scaling through resampling. The results indicate that coupling multi-scale pattern analysis with delineation of morphometric primitives is possible. This approach could be further used for developing hierarchical classifications of landform elements.

Local variance for multi-scale analysis in geomorphometry

PubMed Central

Drăguţ, Lucian; Eisank, Clemens; Strasser, Thomas

2011-01-01

Increasing availability of high resolution Digital Elevation Models (DEMs) is leading to a paradigm shift regarding scale issues in geomorphometry, prompting new solutions to cope with multi-scale analysis and detection of characteristic scales. We tested the suitability of the local variance (LV) method, originally developed for image analysis, for multi-scale analysis in geomorphometry. The method consists of: 1) up-scaling land-surface parameters derived from a DEM; 2) calculating LV as the average standard deviation (SD) within a 3 × 3 moving window for each scale level; 3) calculating the rate of change of LV (ROC-LV) from one level to another, and 4) plotting values so obtained against scale levels. We interpreted peaks in the ROC-LV graphs as markers of scale levels where cells or segments match types of pattern elements characterized by (relatively) equal degrees of homogeneity. The proposed method has been applied to LiDAR DEMs in two test areas different in terms of roughness: low relief and mountainous, respectively. For each test area, scale levels for slope gradient, plan, and profile curvatures were produced at constant increments with either resampling (cell-based) or image segmentation (object-based). Visual assessment revealed homogeneous areas that convincingly associate into patterns of land-surface parameters well differentiated across scales. We found that the LV method performed better on scale levels generated through segmentation as compared to up-scaling through resampling. The results indicate that coupling multi-scale pattern analysis with delineation of morphometric primitives is possible. This approach could be further used for developing hierarchical classifications of landform elements. PMID:21779138

Swimming like algae: biomimetic soft artificial cilia

PubMed Central

Sareh, Sina; Rossiter, Jonathan; Conn, Andrew; Drescher, Knut; Goldstein, Raymond E.

2013-01-01

Cilia are used effectively in a wide variety of biological systems from fluid transport to thrust generation. Here, we present the design and implementation of artificial cilia, based on a biomimetic planar actuator using soft-smart materials. This actuator is modelled on the cilia movement of the alga Volvox, and represents the cilium as a piecewise constant-curvature robotic actuator that enables the subsequent direct translation of natural articulation into a multi-segment ionic polymer metal composite actuator. It is demonstrated how the combination of optimal segmentation pattern and biologically derived per-segment driving signals reproduce natural ciliary motion. The amenability of the artificial cilia to scaling is also demonstrated through the comparison of the Reynolds number achieved with that of natural cilia. PMID:23097503

Interactive lesion segmentation on dynamic contrast enhanced breast MRI using a Markov model

NASA Astrophysics Data System (ADS)

Wu, Qiu; Salganicoff, Marcos; Krishnan, Arun; Fussell, Donald S.; Markey, Mia K.

2006-03-01

The purpose of this study is to develop a method for segmenting lesions on Dynamic Contrast-Enhanced (DCE) breast MRI. DCE breast MRI, in which the breast is imaged before, during, and after the administration of a contrast agent, enables a truly 3D examination of breast tissues. This functional angiogenic imaging technique provides noninvasive assessment of microcirculatory characteristics of tissues in addition to traditional anatomical structure information. Since morphological features and kinetic curves from segmented lesions are to be used for diagnosis and treatment decisions, lesion segmentation is a key pre-processing step for classification. In our study, the ROI is defined by a bounding box containing the enhancement region in the subtraction image, which is generated by subtracting the pre-contrast image from 1st post-contrast image. A maximum a posteriori (MAP) estimate of the class membership (lesion vs. non-lesion) for each voxel is obtained using the Iterative Conditional Mode (ICM) method. The prior distribution of the class membership is modeled as a multi-level logistic model, a Markov Random Field model in which the class membership of each voxel is assumed to depend upon its nearest neighbors only. The likelihood distribution is assumed to be Gaussian. The parameters of each Gaussian distribution are estimated from a dozen voxels manually selected as representative of the class. The experimental segmentation results demonstrate anatomically plausible breast tissue segmentation and the predicted class membership of voxels from the interactive segmentation algorithm agrees with the manual classifications made by inspection of the kinetic enhancement curves. The proposed method is advantageous in that it is efficient, flexible, and robust.

Multi-length-scale Material Model for SiC/SiC Ceramic-Matrix Composites (CMCs): Inclusion of In-Service Environmental Effects

NASA Astrophysics Data System (ADS)

Grujicic, M.; Galgalikar, R.; Snipes, J. S.; Ramaswami, S.

2016-01-01

In our recent work, a multi-length-scale room-temperature material model for SiC/SiC ceramic-matrix composites (CMCs) was derived and parameterized. The model was subsequently linked with a finite-element solver so that it could be used in a general room-temperature, structural/damage analysis of gas-turbine engine CMC components. Due to its multi-length-scale character, the material model enabled inclusion of the effects of fiber/tow (e.g., the volume fraction, size, and properties of the fibers; fiber-coating material/thickness; decohesion properties of the coating/matrix interfaces; etc.) and ply/lamina (e.g., the 0°/90° cross-ply versus plain-weave architectures, the extent of tow crimping in the case of the plain-weave plies, cohesive properties of the inter-ply boundaries, etc.) length-scale microstructural/architectural parameters on the mechanical response of the CMCs. One of the major limitations of the model is that it applies to the CMCs in their as-fabricated conditions (i.e., the effect of prolonged in-service environmental exposure and the associated material aging-degradation is not accounted for). In the present work, the model is upgraded to include such in-service environmental-exposure effects. To demonstrate the utility of the upgraded material model, it is used within a finite-element structural/failure analysis involving impact of a toboggan-shaped turbine shroud segment by a foreign object. The results obtained clearly revealed the effects that different aspects of the in-service environmental exposure have on the material degradation and the extent of damage suffered by the impacted CMC toboggan-shaped shroud segment.

3D printing for orthopedic applications: from high resolution cone beam CT images to life size physical models

NASA Astrophysics Data System (ADS)

Jackson, Amiee; Ray, Lawrence A.; Dangi, Shusil; Ben-Zikri, Yehuda K.; Linte, Cristian A.

2017-03-01

With increasing resolution in image acquisition, the project explores capabilities of printing toward faithfully reflecting detail and features depicted in medical images. To improve safety and efficiency of orthopedic surgery and spatial conceptualization in training and education, this project focused on generating virtual models of orthopedic anatomy from clinical quality computed tomography (CT) image datasets and manufacturing life-size physical models of the anatomy using 3D printing tools. Beginning with raw micro CT data, several image segmentation techniques including thresholding, edge recognition, and region-growing algorithms available in packages such as ITK-SNAP, MITK, or Mimics, were utilized to separate bone from surrounding soft tissue. After converting the resulting data to a standard 3D printing format, stereolithography (STL), the STL file was edited using Meshlab, Netfabb, and Meshmixer. The editing process was necessary to ensure a fully connected surface (no loose elements), positive volume with manifold geometry (geometry possible in the 3D physical world), and a single, closed shell. The resulting surface was then imported into a "slicing" software to scale and orient for printing on a Flashforge Creator Pro. In printing, relationships between orientation, print bed volume, model quality, material use and cost, and print time were considered. We generated anatomical models of the hand, elbow, knee, ankle, and foot from both low-dose high-resolution cone-beam CT images acquired using the soon to be released scanner developed by Carestream, as well as scaled models of the skeletal anatomy of the arm and leg, together with life-size models of the hand and foot.

Saturn Apollo Program

NASA Image and Video Library

1969-01-01

A close-up view of the Apollo 11 command service module ready to be mated with the spacecraft LEM adapter of the third stage. The towering 363-foot Saturn V was a multi-stage, multi-engine launch vehicle standing taller than the Statue of Liberty. Altogether, the Saturn V engines produced as much power as 85 Hoover Dams.

Third Stage (S-IVB) At KSC

NASA Technical Reports Server (NTRS)

1960-01-01

A NASA technician is dwarfed by the gigantic Third Stage (S-IVB) as it rests on supports in a facility at KSC. The towering 363-foot Saturn V was a multi-stage, multi-engine launch vehicle standing taller than the Statue of Liberty. Altogether, the Saturn V engines produced as much power as 85 Hoover Dams.

Saturn Apollo Program

NASA Image and Video Library

1968-12-20

Searchlights penetrate the darkness surrounding Apollo 8 on Pad 39-A at Kennedy Space Center. This mission was the first manned flight using the Saturn V. The towering 363-foot Saturn V was a multi-stage, multi-engine launch vehicle standing taller than the Statue of Liberty. Altogether, the Saturn V engines produced as much power as 85 Hoover Dams.

Apollo 11 Command Service Module

NASA Technical Reports Server (NTRS)

1969-01-01

A close-up view of the Apollo 11 command service module ready to be mated with the spacecraft LEM adapter of the third stage. The towering 363-foot Saturn V was a multi-stage, multi-engine launch vehicle standing taller than the Statue of Liberty. Altogether, the Saturn V engines produced as much power as 85 Hoover Dams.

Performance of U-net based pyramidal lucas-kanade registration on free-breathing multi-b-value diffusion MRI of the kidney.

PubMed

Lv, Jun; Huang, Wenjian; Zhang, Jue; Wang, Xiaoying

2018-06-01

In free-breathing multi-b-value diffusion-weighted imaging (DWI), a series of images typically requires several minutes to collect. During respiration the kidney is routinely displaced and may also undergo deformation. These respiratory motion effects generate artifacts and these are the main sources of error in the quantification of intravoxel incoherent motion (IVIM) derived parameters. This work proposes a fully automated framework that combines a kidney segmentation to improve the registration accuracy. 10 healthy subjects were recruited to participate in this experiment. For the segmentation, U-net was adopted to acquire the kidney's contour. The segmented kidney then served as a region of interest (ROI) for the registration method, known as pyramidal Lucas-Kanade. Our proposed framework confines the kidney's solution range, thus increasing the pyramidal Lucas-Kanade's accuracy. To demonstrate the feasibility of our presented framework, eight regions of interest were selected in the cortex and medulla, and data stability was estimated by comparing the normalized root-mean-square error (NRMSE) values of the fitted data from the bi-exponential intravoxel incoherent motion model pre- and post- registration. The results show that the NRMSE was significantly lower after registration both in the cortex (p < 0.05) and medulla (p < 0.01) during free-breathing measurements. In addition, expert visual scoring of the derived apparent diffusion coefficient (ADC), f, D and D* maps indicated there were significant improvements in the alignment of the kidney in the post-registered image. The proposed framework can effectively reduce the motion artifacts of misaligned multi-b-value DWIs and the inaccuracies of the ADC, f, D and D* estimations. Advances in knowledge: This study demonstrates the feasibility of our proposed fully automated framework combining U-net based segmentation and pyramidal Lucas-Kanade registration method for improving the alignment of multi-b-value diffusion-weighted MRIs and reducing the inaccuracy of parameter estimation during free-breathing.

Performance of an Artificial Multi-observer Deep Neural Network for Fully Automated Segmentation of Polycystic Kidneys.

PubMed

Kline, Timothy L; Korfiatis, Panagiotis; Edwards, Marie E; Blais, Jaime D; Czerwiec, Frank S; Harris, Peter C; King, Bernard F; Torres, Vicente E; Erickson, Bradley J

2017-08-01

Deep learning techniques are being rapidly applied to medical imaging tasks-from organ and lesion segmentation to tissue and tumor classification. These techniques are becoming the leading algorithmic approaches to solve inherently difficult image processing tasks. Currently, the most critical requirement for successful implementation lies in the need for relatively large datasets that can be used for training the deep learning networks. Based on our initial studies of MR imaging examinations of the kidneys of patients affected by polycystic kidney disease (PKD), we have generated a unique database of imaging data and corresponding reference standard segmentations of polycystic kidneys. In the study of PKD, segmentation of the kidneys is needed in order to measure total kidney volume (TKV). Automated methods to segment the kidneys and measure TKV are needed to increase measurement throughput and alleviate the inherent variability of human-derived measurements. We hypothesize that deep learning techniques can be leveraged to perform fast, accurate, reproducible, and fully automated segmentation of polycystic kidneys. Here, we describe a fully automated approach for segmenting PKD kidneys within MR images that simulates a multi-observer approach in order to create an accurate and robust method for the task of segmentation and computation of TKV for PKD patients. A total of 2000 cases were used for training and validation, and 400 cases were used for testing. The multi-observer ensemble method had mean ± SD percent volume difference of 0.68 ± 2.2% compared with the reference standard segmentations. The complete framework performs fully automated segmentation at a level comparable with interobserver variability and could be considered as a replacement for the task of segmentation of PKD kidneys by a human.

Segmentation of hepatic artery in multi-phase liver CT using directional dilation and connectivity analysis

NASA Astrophysics Data System (ADS)

Wang, Lei; Schnurr, Alena-Kathrin; Zidowitz, Stephan; Georgii, Joachim; Zhao, Yue; Razavi, Mohammad; Schwier, Michael; Hahn, Horst K.; Hansen, Christian

2016-03-01

Segmentation of hepatic arteries in multi-phase computed tomography (CT) images is indispensable in liver surgery planning. During image acquisition, the hepatic artery is enhanced by the injection of contrast agent. The enhanced signals are often not stably acquired due to non-optimal contrast timing. Other vascular structure, such as hepatic vein or portal vein, can be enhanced as well in the arterial phase, which can adversely affect the segmentation results. Furthermore, the arteries might suffer from partial volume effects due to their small diameter. To overcome these difficulties, we propose a framework for robust hepatic artery segmentation requiring a minimal amount of user interaction. First, an efficient multi-scale Hessian-based vesselness filter is applied on the artery phase CT image, aiming to enhance vessel structures with specified diameter range. Second, the vesselness response is processed using a Bayesian classifier to identify the most probable vessel structures. Considering the vesselness filter normally performs not ideally on the vessel bifurcations or the segments corrupted by noise, two vessel-reconnection techniques are proposed. The first technique uses a directional morphological operator to dilate vessel segments along their centerline directions, attempting to fill the gap between broken vascular segments. The second technique analyzes the connectivity of vessel segments and reconnects disconnected segments and branches. Finally, a 3D vessel tree is reconstructed. The algorithm has been evaluated using 18 CT images of the liver. To quantitatively measure the similarities between segmented and reference vessel trees, the skeleton coverage and mean symmetric distance are calculated to quantify the agreement between reference and segmented vessel skeletons, resulting in an average of 0:55+/-0:27 and 12:7+/-7:9 mm (mean standard deviation), respectively.

Ankle foot orthosis-footwear combination tuning: an investigation into common clinical practice in the United Kingdom.

PubMed

Eddison, Nicola; Chockalingam, Nachiappan; Osborne, Stephen

2015-04-01

Ankle foot orthoses are used to treat a wide variety of gait pathologies. Ankle foot orthosis-footwear combination tuning should be routine clinical practice when prescribing an ankle foot orthosis. Current research suggests that failure to tune ankle foot orthosis-footwear combinations can lead to immediate detrimental effect on function, and in the longer term, it may actually contribute to deterioration. The purpose of this preliminary study was to identify the current level of knowledge clinicians have in the United Kingdom regarding ankle foot orthosis-footwear combination tuning and to investigate common clinical practice regarding ankle foot orthosis-footwear combination tuning among UK orthotists. Cross-sectional survey. A prospective study employing a multi-item questionnaire was sent out to registered orthotists and uploaded on to the official website of British Association of Prosthetists and Orthotists to be accessed by their members. A total of 41 completed questionnaires were received. The results demonstrate that only 50% of participants use ankle foot orthosis-footwear combination tuning as standard clinical practice. The most prevalent factors preventing participants from carrying out ankle foot orthosis-footwear combination tuning are a lack of access to three-dimensional gait analysis equipment (37%) and a lack of time available in their clinics (27%). Although, ankle foot orthosis-footwear combination tuning has been identified as an essential aspect of the prescription of ankle foot orthoses, the results of this study show a lack of understanding of the key principles behind ankle foot orthosis-footwear combination tuning. © The International Society for Prosthetics and Orthotics 2014.

Biomechanical investigation of thoracolumbar spine in different postures during ejection using a combined finite element and multi-body approach.

PubMed

Du, Chengfei; Mo, Zhongjun; Tian, Shan; Wang, Lizhen; Fan, Jie; Liu, Songyang; Fan, Yubo

2014-11-01

The aim of this study is to investigate the dynamic response of a multi-segment model of the thoracolumbar spine and determine how the sitting posture affects the response under the impact of ejection. A nonlinear finite element model of the thoracolumbar-pelvis complex (T9-S1) was developed and validated. A multi-body dynamic model of a pilot was also constructed so an ejection seat restraint system could be incorporated into the finite element model. The distribution of trunk mass on each vertebra was also considered in the model. Dynamics analysis showed that ejection impact induced obvious axial compression and anterior flexion of the spine, which may contribute to spinal injuries. Compared with a normal posture, the relaxed posture led to an increase in stress on the cortical wall, endplate, and intradiscal pressure of 43%, 10%, 13%, respectively, and accordingly increased the risk of inducing spinal injuries. Copyright © 2014 John Wiley & Sons, Ltd.

Improvement and Extension of Shape Evaluation Criteria in Multi-Scale Image Segmentation

NASA Astrophysics Data System (ADS)

Sakamoto, M.; Honda, Y.; Kondo, A.

2016-06-01

From the last decade, the multi-scale image segmentation is getting a particular interest and practically being used for object-based image analysis. In this study, we have addressed the issues on multi-scale image segmentation, especially, in improving the performances for validity of merging and variety of derived region's shape. Firstly, we have introduced constraints on the application of spectral criterion which could suppress excessive merging between dissimilar regions. Secondly, we have extended the evaluation for smoothness criterion by modifying the definition on the extent of the object, which was brought for controlling the shape's diversity. Thirdly, we have developed new shape criterion called aspect ratio. This criterion helps to improve the reproducibility on the shape of object to be matched to the actual objectives of interest. This criterion provides constraint on the aspect ratio in the bounding box of object by keeping properties controlled with conventional shape criteria. These improvements and extensions lead to more accurate, flexible, and diverse segmentation results according to the shape characteristics of the target of interest. Furthermore, we also investigated a technique for quantitative and automatic parameterization in multi-scale image segmentation. This approach is achieved by comparing segmentation result with training area specified in advance by considering the maximization of the average area in derived objects or satisfying the evaluation index called F-measure. Thus, it has been possible to automate the parameterization that suited the objectives especially in the view point of shape's reproducibility.

Gradient-based reliability maps for ACM-based segmentation of hippocampus.

PubMed

Zarpalas, Dimitrios; Gkontra, Polyxeni; Daras, Petros; Maglaveras, Nicos

2014-04-01

Automatic segmentation of deep brain structures, such as the hippocampus (HC), in MR images has attracted considerable scientific attention due to the widespread use of MRI and to the principal role of some structures in various mental disorders. In this literature, there exists a substantial amount of work relying on deformable models incorporating prior knowledge about structures' anatomy and shape information. However, shape priors capture global shape characteristics and thus fail to model boundaries of varying properties; HC boundaries present rich, poor, and missing gradient regions. On top of that, shape prior knowledge is blended with image information in the evolution process, through global weighting of the two terms, again neglecting the spatially varying boundary properties, causing segmentation faults. An innovative method is hereby presented that aims to achieve highly accurate HC segmentation in MR images, based on the modeling of boundary properties at each anatomical location and the inclusion of appropriate image information for each of those, within an active contour model framework. Hence, blending of image information and prior knowledge is based on a local weighting map, which mixes gradient information, regional and whole brain statistical information with a multi-atlas-based spatial distribution map of the structure's labels. Experimental results on three different datasets demonstrate the efficacy and accuracy of the proposed method.

Vowel Harmony in Palestinian Arabic: A Metrical Perspective.

ERIC Educational Resources Information Center

Abu-Salim, I. M.

1987-01-01

The autosegmental rule of vowel harmony (VH) in Palestinian Arabic is shown to be constrained simultaneously by metrical and segmental boundaries. The indicative prefix bi- is no longer an exception to VH if a structure is assumed that disallows the prefix from sharing a foot with the stem, consequently blocking VH. (Author/LMO)

16. Interior, Machine Shop, Roundhouse Machine Shop Extension, Southern Pacific ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

16. Interior, Machine Shop, Roundhouse Machine Shop Extension, Southern Pacific Railroad Carlin Shops, view to south (90mm lens). Note the large segmental-arched doorway to move locomotives in and out of Machine Shop. - Southern Pacific Railroad, Carlin Shops, Roundhouse Machine Shop Extension, Foot of Sixth Street, Carlin, Elko County, NV

Space Science

NASA Image and Video Library

1999-04-20

NASA's Space Optics Manufacturing Technology Center has been working to expand our view of the universe via sophisticated new telescopes. The Optics Center's goal is to develop low-cost, advanced space optics technologies for the NASA program in the 21st century, including the long-term goal of imaging Earth-like planets in distant solar systems. A segmented array of mirrors was designed by the Space Optics Manufacturing Technology Center for the solar concentrator test stand at the Marshall Space Flight Center (MSFC) for powering solar thermal propulsion engines. Each hexagon mirror has a spherical surface to approximate a parabolic concentrator when combined into the entire 18-foot diameter array. The aluminum mirrors were polished with a diamond turning machine that creates a glass-like reflective finish on metal. The precision fabrication machinery at the Space Optics Manufacturing Technology Center at MSFC can polish specialized optical elements to a world class quality of smoothness. This image shows optics physicist, Vince Huegele, examining one of the 144-segment hexagonal mirrors of the 18-foot diameter array at the MSFC solar concentrator test stand.

Space Science

NASA Image and Video Library

1999-04-20

NASA's Space Optics Manufacturing Technology Center has been working to expand our view of the universe via sophisticated new telescopes. The Optics Center's goal is to develop low-cost, advanced space optics technologies for the NASA program in the 21st century, including the long-term goal of imaging Earth-like planets in distant solar systems. A segmented array of mirrors was designed by the Space Optics Manufacturing Technology Center for solar the concentrator test stand at the Marshall Space Flight Center (MSFC) for powering solar thermal propulsion engines. Each hexagon mirror has a spherical surface to approximate a parabolic concentrator when combined into the entire 18-foot diameter array. The aluminum mirrors were polished with a diamond turning machine, that creates a glass-like reflective finish on metal. The precision fabrication machinery at the Space Optics Manufacturing Technology Center at MSFC can polish specialized optical elements to a world class quality of smoothness. This image shows optics physicist, Vince Huegele, examining one of the 144-segment hexagonal mirrors of the 18-foot diameter array at the MSFC solar concentrator test stand.

STS-112 crew takes a group photo at the 215-foot level

NASA Technical Reports Server (NTRS)

2002-01-01

KENNEDY SPACE CENTER, FLA. - The STS-112 crew gathers for a group photo on the 215-foot level of the Fixed Service Structure. From left are Mission Specialists Fyodor Yurchikhin, Piers Sellers and David Wolf; Pilot Pamela Melroy; Commander Jeffrey Ashby; and Mission Specialist Sandra Magnus. Behind them at left is seen one of the white solid rocket boosters and the orange external tank on Space Shuttle Atlantis. Mission STS-112 is scheduled to launch no earlier than Oct. 2, between 2 and 6 p.m. EDT. STS-112 is the 15th assembly mission to the International Space Station. Atlantis will be carrying the S1 Integrated Truss Structure, the first starboard truss segment, to be attached to the central truss segment, S0, and the Crew and Equipment Translation Aid (CETA) Cart A. The CETA is the first of two human-powered carts that will ride along the ISS railway, providing mobile work platforms for future spacewalking astronauts. The 11-day mission is expected to conclude with a landing at KSC Oct. 13.

Physical activity and exercise on diabetic foot related outcomes: A systematic review.

PubMed

Matos, Monica; Mendes, Romeu; Silva, André B; Sousa, Nelson

2018-05-01

Diabetic foot is one of the most common complications of diabetes. It has the potential risk of pathologic consequences including infection, ulceration and amputation, but a growing body of evidence suggests that physical activity and exercise may improve diabetic foot outcomes. To analyze de effects of exercise and physical activity interventions on diabetic foot outcomes. A comprehensive and systematic search was conducted according to PRISMA recommendations. Only controlled clinical trials with patients with diabetes were included. Six studies, involving 418 patients with diabetes, were included. Two studies used only aerobic exercise; two studies combined aerobic, resistance and balance exercise; and two studies combined aerobic and balance exercise by Thai Chin Chuan methods. Physical activity and exercise significantly improved nerve velocity conduction, peripheral sensory function and foot peak pressure distribution. Moreover, the ulcers incidence rate per year was lower in the intervention groups, compared with the controls [0.02 vs. 0.12]. This review suggests evidence that physical activity and exercise is an effective non-pharmacological intervention to improve diabetic foot related outcomes. Combined multi-disciplinary treatments are more effective in the prevention of foot complications in patients with diabetes. Copyright © 2018 Elsevier B.V. All rights reserved.

An investigation of the dynamic relationship between navicular drop and first metatarsophalangeal joint dorsal excursion

PubMed Central

Griffin, Nicole L; Miller, Charlotte; Schmitt, Daniel; D'Août, Kristiaan

2013-01-01

The modern human foot is a complex biomechanical structure that must act both as a shock absorber and as a propulsive strut during the stance phase of gait. Understanding the ways in which foot segments interact can illuminate the mechanics of foot function in healthy and pathological humans. It has been proposed that increased values of medial longitudinal arch deformation can limit metatarsophalangeal joint excursion via tension in the plantar aponeurosis. However, this model has not been tested directly in a dynamic setting. In this study, we tested the hypothesis that during the stance phase, subtalar pronation (stretching of the plantar aponeurosis and subsequent lowering of the medial longitudinal arch) will negatively affect the amount of first metatarsophalangeal joint excursion occurring at push-off. Vertical descent of the navicular (a proxy for subtalar pronation) and first metatarsophalangeal joint dorsal excursion were measured during steady locomotion over a flat substrate on a novel sample consisting of asymptomatic adult males and females, many of whom are habitually unshod. Least-squares regression analyses indicated that, contrary to the hypothesis, navicular drop did not explain a significant amount of variation in first metatarsophalangeal joint dorsal excursion. These results suggest that, in an asymptomatic subject, the plantar aponeurosis and the associated foot bones can function effectively within the normal range of subtalar pronation that takes place during walking gait. From a clinical standpoint, this study highlights the need for investigating the in vivo kinematic relationship between subtalar pronation and metatarsophalangeal joint dorsiflexion in symptomatic populations, and also the need to explore other factors that may affect the kinematics of asymptomatic feet. PMID:23600634

A general framework to learn surrogate relevance criterion for atlas based image segmentation

NASA Astrophysics Data System (ADS)

Zhao, Tingting; Ruan, Dan

2016-09-01

Multi-atlas based image segmentation sees great opportunities in the big data era but also faces unprecedented challenges in identifying positive contributors from extensive heterogeneous data. To assess data relevance, image similarity criteria based on various image features widely serve as surrogates for the inaccessible geometric agreement criteria. This paper proposes a general framework to learn image based surrogate relevance criteria to better mimic the behaviors of segmentation based oracle geometric relevance. The validity of its general rationale is verified in the specific context of fusion set selection for image segmentation. More specifically, we first present a unified formulation for surrogate relevance criteria and model the neighborhood relationship among atlases based on the oracle relevance knowledge. Surrogates are then trained to be small for geometrically relevant neighbors and large for irrelevant remotes to the given targets. The proposed surrogate learning framework is verified in corpus callosum segmentation. The learned surrogates demonstrate superiority in inferring the underlying oracle value and selecting relevant fusion set, compared to benchmark surrogates.

Ultrasound image-based thyroid nodule automatic segmentation using convolutional neural networks.

PubMed

Ma, Jinlian; Wu, Fa; Jiang, Tian'an; Zhao, Qiyu; Kong, Dexing

2017-11-01

Delineation of thyroid nodule boundaries from ultrasound images plays an important role in calculation of clinical indices and diagnosis of thyroid diseases. However, it is challenging for accurate and automatic segmentation of thyroid nodules because of their heterogeneous appearance and components similar to the background. In this study, we employ a deep convolutional neural network (CNN) to automatically segment thyroid nodules from ultrasound images. Our CNN-based method formulates a thyroid nodule segmentation problem as a patch classification task, where the relationship among patches is ignored. Specifically, the CNN used image patches from images of normal thyroids and thyroid nodules as inputs and then generated the segmentation probability maps as outputs. A multi-view strategy is used to improve the performance of the CNN-based model. Additionally, we compared the performance of our approach with that of the commonly used segmentation methods on the same dataset. The experimental results suggest that our proposed method outperforms prior methods on thyroid nodule segmentation. Moreover, the results show that the CNN-based model is able to delineate multiple nodules in thyroid ultrasound images accurately and effectively. In detail, our CNN-based model can achieve an average of the overlap metric, dice ratio, true positive rate, false positive rate, and modified Hausdorff distance as [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text] on overall folds, respectively. Our proposed method is fully automatic without any user interaction. Quantitative results also indicate that our method is so efficient and accurate that it can be good enough to replace the time-consuming and tedious manual segmentation approach, demonstrating the potential clinical applications.

Automated coronal hole identification via multi-thermal intensity segmentation

NASA Astrophysics Data System (ADS)

Garton, Tadhg M.; Gallagher, Peter T.; Murray, Sophie A.

2018-01-01

Coronal holes (CH) are regions of open magnetic fields that appear as dark areas in the solar corona due to their low density and temperature compared to the surrounding quiet corona. To date, accurate identification and segmentation of CHs has been a difficult task due to their comparable intensity to local quiet Sun regions. Current segmentation methods typically rely on the use of single Extreme Ultra-Violet passband and magnetogram images to extract CH information. Here, the coronal hole identification via multi-thermal emission recognition algorithm (CHIMERA) is described, which analyses multi-thermal images from the atmospheric image assembly (AIA) onboard the solar dynamics observatory (SDO) to segment coronal hole boundaries by their intensity ratio across three passbands (171 Å, 193 Å, and 211 Å). The algorithm allows accurate extraction of CH boundaries and many of their properties, such as area, position, latitudinal and longitudinal width, and magnetic polarity of segmented CHs. From these properties, a clear linear relationship was identified between the duration of geomagnetic storms and coronal hole areas. CHIMERA can therefore form the basis of more accurate forecasting of the start and duration of geomagnetic storms.

Bipedal gait model for precise gait recognition and optimal triggering in foot drop stimulator: a proof of concept.

PubMed

Shaikh, Muhammad Faraz; Salcic, Zoran; Wang, Kevin I-Kai; Hu, Aiguo Patrick

2018-03-10

Electrical stimulators are often prescribed to correct foot drop walking. However, commercial foot drop stimulators trigger inappropriately under certain non-gait scenarios. Past researches addressed this limitation by defining stimulation control based on automaton of a gait cycle executed by foot drop of affected limb/foot only. Since gait is a collaborative activity of both feet, this research highlights the role of normal foot for robust gait detection and stimulation triggering. A novel bipedal gait model is proposed where gait cycle is realized as an automaton based on concurrent gait sub-phases (states) from each foot. The input for state transition is fused information from feet-worn pressure and inertial sensors. Thereafter, a bipedal gait model-based stimulation control algorithm is developed. As a feasibility study, bipedal gait model and stimulation control are evaluated in real-time simulation manner on normal and simulated foot drop gait measurements from 16 able-bodied participants with three speed variations, under inappropriate triggering scenarios and with foot drop rehabilitation exercises. Also, the stimulation control employed in commercial foot drop stimulators and single foot gait-based foot drop stimulators are compared alongside. Gait detection accuracy (98.9%) and precise triggering under all investigations prove bipedal gait model reliability. This infers that gait detection leveraging bipedal periodicity is a promising strategy to rectify prevalent stimulation triggering deficiencies in commercial foot drop stimulators. Graphical abstract Bipedal information-based gait recognition and stimulation triggering.

Analysis of role of bone compliance on mechanics of a lumbar motion segment.

PubMed

Shirazi-Adl, A

1994-11-01

A large deformation elasto-static finite element formulation is developed and used for the determination of the role of bone compliance in mechanics of a lumbar motion segment. This is done by simulating each vertebra as a deformable body with realistic material properties, as a deformable body with stiffer or softer mechanical properties, as a single rigid body, or finally as two rigid bodies attached by deformable beams. The single loadings of axial compression, flexion moment, extension moment, and axial torque are considered. The results indicate the marked effect of alteration in bone material properties on biomechanics of lumbar segments specially under larger loads. The biomechanical studies of the lumbar spine should, therefore, be performed and evaluated in the light of such dependency. A model for bony vertebrae is finally proposed that preserves both the accuracy and the cost-efficiency in nonlinear finite element analyses of spinal multi-motion segment systems.

An advanced computational bioheat transfer model for a human body with an embedded systemic circulation.

PubMed

Coccarelli, Alberto; Boileau, Etienne; Parthimos, Dimitris; Nithiarasu, Perumal

2016-10-01

In the present work, an elaborate one-dimensional thermofluid model for a human body is presented. By contrast to the existing pure conduction-/perfusion-based models, the proposed methodology couples the arterial fluid dynamics of a human body with a multi-segmental bioheat model of surrounding solid tissues. In the present configuration, arterial flow is included through a network of elastic vessels. More than a dozen solid segments are employed to represent the heat conduction in the surrounding tissues, and each segment is constituted by a multilayered circular cylinder. Such multi-layers allow flexible delineation of the geometry and incorporation of properties of different tissue types. The coupling of solid tissue and fluid models requires subdivision of the arterial circulation into large and small arteries. The heat exchange between tissues and arterial wall occurs by convection in large vessels and by perfusion in small arteries. The core region, including the heart, provides the inlet conditions for the fluid equations. In the proposed model, shivering, sweating, and perfusion changes constitute the basis of the thermoregulatory system. The equations governing flow and heat transfer in the circulatory system are solved using a locally conservative Galerkin approach, and the heat conduction in the surrounding tissues is solved using a standard implicit backward Euler method. To investigate the effectiveness of the proposed model, temperature field evolutions are monitored at different points of the arterial tree and in the surrounding tissue layers. To study the differences due to flow-induced convection effects on thermal balance, the results of the current model are compared against those of the widely used modelling methodologies. The results show that the convection significantly influences the temperature distribution of the solid tissues in the vicinity of the arteries. Thus, the inner convection has a more predominant role in the human body heat balance than previously thought. To demonstrate its capabilities, the proposed new model is used to study different scenarios, including thermoregulation inactivity and variation in surrounding atmospheric conditions.

Poly-Pattern Compressive Segmentation of ASTER Data for GIS

NASA Technical Reports Server (NTRS)

Myers, Wayne; Warner, Eric; Tutwiler, Richard

2007-01-01

Pattern-based segmentation of multi-band image data, such as ASTER, produces one-byte and two-byte approximate compressions. This is a dual segmentation consisting of nested coarser and finer level pattern mappings called poly-patterns. The coarser A-level version is structured for direct incorporation into geographic information systems in the manner of a raster map. GIs renderings of this A-level approximation are called pattern pictures which have the appearance of color enhanced images. The two-byte version consisting of thousands of B-level segments provides a capability for approximate restoration of the multi-band data in selected areas or entire scenes. Poly-patterns are especially useful for purposes of change detection and landscape analysis at multiple scales. The primary author has implemented the segmentation methodology in a public domain software suite.

Mathematical modeling and full-scale shaking table tests for multi-curve buckling restrained braces

NASA Astrophysics Data System (ADS)

Tsai, C. S.; Lin, Yungchang; Chen, Wenshin; Su, H. C.

2009-09-01

Buckling restrained braces (BRBs) have been widely applied in seismic mitigation since they were introduced in the 1970s. However, traditional BRBs have several disadvantages caused by using a steel tube to envelope the mortar to prevent the core plate from buckling, such as: complex interfaces between the materials used, uncertain precision, and time consumption during the manufacturing processes. In this study, a new device called the multi-curve buckling restrained brace (MC-BRB) is proposed to overcome these disadvantages. The new device consists of a core plate with multiple neck portions assembled to form multiple energy dissipation segments, and the enlarged segment, lateral support elements and constraining elements to prevent the BRB from buckling. The enlarged segment located in the middle of the core plate can be welded to the lateral support and constraining elements to increase buckling resistance and to prevent them from sliding during earthquakes. Component tests and a series of shaking table tests on a full-scale steel structure equipped with MC-BRBs were carried out to investigate the behavior and capability of this new BRB design for seismic mitigation. The experimental results illustrate that the MC-BRB possesses a stable mechanical behavior under cyclic loadings and provides good protection to structures during earthquakes. Also, a mathematical model has been developed to simulate the mechanical characteristics of BRBs.

A methodological framework for detecting ulcers' risk in diabetic foot subjects by combining gait analysis, a new musculoskeletal foot model and a foot finite element model.

PubMed

Scarton, Alessandra; Guiotto, Annamaria; Malaquias, Tiago; Spolaor, Fabiola; Sinigaglia, Giacomo; Cobelli, Claudio; Jonkers, Ilse; Sawacha, Zimi

2018-02-01

Diabetic foot is one of the most debilitating complications of diabetes and may lead to plantar ulcers. In the last decade, gait analysis, musculoskeletal modelling (MSM) and finite element modelling (FEM) have shown their ability to contribute to diabetic foot prevention and suggested that the origin of the plantar ulcers is in deeper tissue layers rather than on the plantar surface. Hence the aim of the current work is to develop a methodology that improves FEM-derived foot internal stresses prediction, for diabetic foot prevention applications. A 3D foot FEM was combined with MSM derived force to predict the sites of excessive internal stresses on the foot. In vivo gait analysis data, and an MRI scan of a foot from a healthy subject were acquired and used to develop a six degrees of freedom (6 DOF) foot MSM and a 3D subject-specific foot FEM. Ankle kinematics were applied as boundary conditions to the FEM together with: 1. only Ground Reaction Forces (GRFs); 2. OpenSim derived extrinsic muscles forces estimated with a standard OpenSim MSM; 3. extrinsic muscle forces derived through the (6 DOF) foot MSM; 4. intrinsic and extrinsic muscles forces derived through the 6 DOF foot MSM. For model validation purposes, simulated peak pressures were extracted and compared with those measured experimentally. The importance of foot muscles in controlling plantar pressure distribution and internal stresses is confirmed by the improved accuracy in the estimation of the peak pressures obtained with the inclusion of intrinsic and extrinsic muscle forces. Copyright © 2017 Elsevier B.V. All rights reserved.

Multi-segmental movement patterns reflect juggling complexity and skill level.

PubMed

Zago, Matteo; Pacifici, Ilaria; Lovecchio, Nicola; Galli, Manuela; Federolf, Peter Andreas; Sforza, Chiarella

2017-08-01

The juggling action of six experts and six intermediates jugglers was recorded with a motion capture system and decomposed into its fundamental components through Principal Component Analysis. The aim was to quantify trends in movement dimensionality, multi-segmental patterns and rhythmicity as a function of proficiency level and task complexity. Dimensionality was quantified in terms of Residual Variance, while the Relative Amplitude was introduced to account for individual differences in movement components. We observed that: experience-related modifications in multi-segmental actions exist, such as the progressive reduction of error-correction movements, especially in complex task condition. The systematic identification of motor patterns sensitive to the acquisition of specific experience could accelerate the learning process. Copyright © 2017 Elsevier B.V. All rights reserved.

Acoustic Modifications of the Ames 40x80 Foot Wind Tunnel and Test Techniques for High-Speed Research Model Testing

NASA Technical Reports Server (NTRS)

Soderman, Paul T.; Olson, Larry (Technical Monitor)

1995-01-01

The NFAC 40- by 80- Foot Wind Tunnel at Ames is being refurbished with a new, deep acoustic lining in the test section which will make the facility nearly anechoic over a large frequency range. The modification history, key elements, and schedule will be discussed. Design features and expected performance gains will be described. Background noise reductions will be summarized. Improvements in aeroacoustic research techniques have been developed and used recently at NFAC on several wind tunnel tests of High Speed Research models. Research on quiet inflow microphones and struts will be described. The Acoustic Survey Apparatus in the 40x80 will be illustrated. A special intensity probe was tested for source localization. Multi-channel, high speed digital data acquisition is now used for acoustics. And most important, phased microphone arrays have been developed and tested which have proven to be very powerful for source identification and increased signal-to-noise ratio. Use of these tools for the HEAT model will be illustrated. In addition, an acoustically absorbent symmetry plane was built to satisfy the HEAT semispan aerodynamic and acoustic requirements. Acoustic performance of that symmetry plane will be shown.

A kinematic model to assess spinal motion during walking.

PubMed

Konz, Regina J; Fatone, Stefania; Stine, Rebecca L; Ganju, Aruna; Gard, Steven A; Ondra, Stephen L

2006-11-15

A 3-dimensional multi-segment kinematic spine model was developed for noninvasive analysis of spinal motion during walking. Preliminary data from able-bodied ambulators were collected and analyzed using the model. Neither the spine's role during walking nor the effect of surgical spinal stabilization on gait is fully understood. Typically, gait analysis models disregard the spine entirely or regard it as a single rigid structure. Data on regional spinal movements, in conjunction with lower limb data, associated with walking are scarce. KinTrak software (Motion Analysis Corp., Santa Rosa, CA) was used to create a biomechanical model for analysis of 3-dimensional regional spinal movements. Measuring known angles from a mechanical model and comparing them to the calculated angles validated the kinematic model. Spine motion data were collected from 10 able-bodied adults walking at 5 self-selected speeds. These results were compared to data reported in the literature. The uniaxial angles measured on the mechanical model were within 5 degrees of the calculated kinematic model angles, and the coupled angles were within 2 degrees. Regional spine kinematics from able-bodied subjects calculated with this model compared well to data reported by other authors. A multi-segment kinematic spine model has been developed and validated for analysis of spinal motion during walking. By understanding the spine's role during ambulation and the cause-and-effect relationship between spine motion and lower limb motion, preoperative planning may be augmented to restore normal alignment and balance with minimal negative effects on walking.

Distributed plasticity of locomotor pattern generators in spinal cord injured patients.

PubMed

Grasso, Renato; Ivanenko, Yuri P; Zago, Myrka; Molinari, Marco; Scivoletto, Giorgio; Castellano, Vincenzo; Macellari, Velio; Lacquaniti, Francesco

2004-05-01

Recent progress with spinal cord injured (SCI) patients indicates that with training they can recover some locomotor ability. Here we addressed the question of whether locomotor responses developed with training depend on re-activation of the normal motor patterns or whether they depend on learning new motor patterns. To this end we recorded detailed kinematic and EMG data in SCI patients trained to step on a treadmill with body-weight support (BWST), and in healthy subjects. We found that all patients could be trained to step with BWST in the laboratory conditions, but they used new coordinative strategies. Patients with more severe lesions used their arms and body to assist the leg movements via the biomechanical coupling of limb and body segments. In all patients, the phase-relationship of the angular motion of the different lower limb segments was very different from the control, as was the pattern of activity of most recorded muscles. Surprisingly, however, the new motor strategies were quite effective in generating foot motion that closely matched the normal in the laboratory conditions. With training, foot motion recovered the shape, the step-by-step reproducibility, and the two-thirds power relationship between curvature and velocity that characterize normal gait. We mapped the recorded patterns of muscle activity onto the approximate rostrocaudal location of motor neuron pools in the human spinal cord. The reconstructed spatiotemporal maps of motor neuron activity in SCI patients were quite different from those of healthy subjects. At the end of training, the locomotor network reorganized at both supralesional and sublesional levels, from the cervical to the sacral cord segments. We conclude that locomotor responses in SCI patients may not be subserved by changes localized to limited regions of the spinal cord, but may depend on a plastic redistribution of activity across most of the rostrocaudal extent of the spinal cord. Distributed plasticity underlies recovery of foot kinematics by generating new patterns of muscle activity that are motor equivalents of the normal ones.

Allometric associations between body size, shape, and 100-m butterfly speed performance.

PubMed

Sammoud, Senda; Nevill, Alan M; Negra, Yassine; Bouguezzi, Raja; Chaabene, Helmi; Hachana, Younés

2018-05-01

This study aimed to estimate the optimal body size, limb-segment length, and girth or breadth ratios associated with 100-m butterfly speed performance in swimmers. One-hundred-sixty-seven swimmers as subjects (male: N.=103; female: N.=64). Anthropometric measurements comprised height, body-mass, skinfolds, arm-span, upper-limb-length, upper-arm, forearm, hand-lengths, lower-limb-length, thigh-length, leg-length, foot-length, arm-relaxed-girth, forearm-girth, wrist-girth, thigh-girth, calf-girth, ankle-girth, biacromial and biiliocristal-breadths. To estimate the optimal body size and body composition components associated with 100-m butterfly speed performance, we adopted a multiplicative allometric log-linear regression model, which was refined using backward elimination. Fat-mass was the singularly most important whole-body characteristic. Height and body-mass did not contribute to the model. The allometric model identified that having greater limb segment length-ratio (arm-ratio = [arm-span]/[forearm]) and limb girth-ratio (girth-ratio = [calf-girth]/[ankle-girth]) were key to butterfly speed performance. A greater arm-span to forearm-length ratio and a greater calf to ankle-girth-ratio suggest that a combination of larger arm-span and shorter forearm-length and the combination of larger calves and smaller ankles-girth may benefit butterfly swim speed performance. In addition having greater biacromial and biliocristal breadths is also a major advantage in butterfly swimming speed performance. Finally, the estimation of these ratios was made possible by adopting a multiplicative allometric model that was able to confirm, theoretically, that swim speeds are nearly independent of total body size. The 100-m butterfly speed performance was strongly negatively associated with fat mass and positively associated with the segment length ratio (arm-span/forearm-length) and girth ratio (calf-girth)/(ankle-girth), having controlled for the developmental changes in age.

Appearance Constrained Semi-Automatic Segmentation from DCE-MRI is Reproducible and Feasible for Breast Cancer Radiomics: A Feasibility Study.

PubMed

Veeraraghavan, Harini; Dashevsky, Brittany Z; Onishi, Natsuko; Sadinski, Meredith; Morris, Elizabeth; Deasy, Joseph O; Sutton, Elizabeth J

2018-03-19

We present a segmentation approach that combines GrowCut (GC) with cancer-specific multi-parametric Gaussian Mixture Model (GCGMM) to produce accurate and reproducible segmentations. We evaluated GCGMM using a retrospectively collected 75 invasive ductal carcinoma with ERPR+ HER2- (n = 15), triple negative (TN) (n = 9), and ER-HER2+ (n = 57) cancers with variable presentation (mass and non-mass enhancement) and background parenchymal enhancement (mild and marked). Expert delineated manual contours were used to assess the segmentation performance using Dice coefficient (DSC), mean surface distance (mSD), Hausdorff distance, and volume ratio (VR). GCGMM segmentations were significantly more accurate than GrowCut (GC) and fuzzy c-means clustering (FCM). GCGMM's segmentations and the texture features computed from those segmentations were the most reproducible compared with manual delineations and other analyzed segmentation methods. Finally, random forest (RF) classifier trained with leave-one-out cross-validation using features extracted from GCGMM segmentation resulted in the best accuracy for ER-HER2+ vs. ERPR+/TN (GCGMM 0.95, expert 0.95, GC 0.90, FCM 0.92) and for ERPR + HER2- vs. TN (GCGMM 0.92, expert 0.91, GC 0.77, FCM 0.83).

Comparison of the Kinematic Patterns of Kick Between Brazilian and Japanese Young Soccer Players

PubMed Central

Pereira Santiago, Paulo Roberto; Palucci Vieira, Luiz Henrique; Barbieri, Fabio Augusto; Moura, Felipe Arruda; Exel Santana, Juliana; de Andrade, Vitor Luiz; de Souza Bedo, Bruno Luiz; Cunha, Sergio Augusto

2016-01-01

Background Kicking performance is the most studied technical action in soccer and lower limbs kinematics is closely related to success in kicking, mainly because they are essential in imparting high velocity to the ball. Previous studies demonstrated that soccer leagues in different countries exhibit different physical demands and technical requirements during the matches. However, evidencewhether nationality has any influence in the kinematics of soccer-related skills has not yet been reported. The nationality of the players is an aspect that might be also relevant to the performance in kicking. Objectives The aim of this study was to compare the lower limbs kinematic patterns during kicking, between Brazilian and Japanese young top soccer players. Patients and Methods Seven Brazilian (GA) and seven Japanese (GB) U-17 players performed 15 side-foot kicks each, with a distance of 20 m away from the goal, aiming a target of 1 × 1 m in upper corner, constrained by a defensive wall (1.8 × 2 m). Four digital video cameras (120 Hz) recorded the performance for further 3D reconstruction of thigh, shank and foot segments of both kicking and support limbs. The selected kicking cycle was characterized by the toe-off of the kicking limb to the end of the kicking foot when it came in contact with the ball. Stereographical projection of each segment was applied to obtain the representative curves of kicking as function of time for each participant in each trial. Cluster analysis was performed to identify the mean GA and GB curves for each segment. Silhouette coefficient (SC) was calculated, in order to determine the degree of separation between the two groups’ curves. Results Comparison between the median confidence intervals of the SC showed no differences between groups as regards lower limb patterns of movements. Task accuracy was determined by the relative frequency that the ball reached the target for all attempts and no differences were found (GA: 10.48 ± 14.33%; GB: 9.52 ± 6.51%; P = 0.88). Conclusions We conclude that lower limb kinematic patterns, in support and ball contact phases, are similar in young Brazilian and Japanese soccer players during free kicks when adopting the side-foot kick style. PMID:27625761

A76-0634. 1/50 Scale Model Of The 80X120 Foot Wind Tunnel Model (Nfac) In The Test Section Of The 40X80 Foot Wind Tunnel.

NASA Image and Video Library

1996-06-27

(03/12/1976) 1/50 scale model of the 80x120 foot wind tunnel model (NFAC) in the test section of the 40x80 foot wind tunnel. Model mounted on a rotating ground board designed for this test, viewed from the west, oriented for North wind.

Development and validation of a computational model to study the effect of foot constraint on ankle injury due to external rotation.

PubMed

Wei, Feng; Hunley, Stanley C; Powell, John W; Haut, Roger C

2011-02-01

Recent studies, using two different manners of foot constraint, potted and taped, document altered failure characteristics in the human cadaver ankle under controlled external rotation of the foot. The posterior talofibular ligament (PTaFL) was commonly injured when the foot was constrained in potting material, while the frequency of deltoid ligament injury was higher for the taped foot. In this study an existing multibody computational modeling approach was validated to include the influence of foot constraint, determine the kinematics of the joint under external foot rotation, and consequently obtain strains in various ligaments. It was hypothesized that the location of ankle injury due to excessive levels of external foot rotation is a function of foot constraint. The results from this model simulation supported this hypothesis and helped to explain the mechanisms of injury in the cadaver experiments. An excessive external foot rotation might generate a PTaFL injury for a rigid foot constraint, and an anterior deltoid ligament injury for a pliant foot constraint. The computational models may be further developed and modified to simulate the human response for different shoe designs, as well as on various athletic shoe-surface interfaces, so as to provide a computational basis for optimizing athletic performance with minimal injury risk.

Integration of Sparse Multi-modality Representation and Anatomical Constraint for Isointense Infant Brain MR Image Segmentation

PubMed Central

Wang, Li; Shi, Feng; Gao, Yaozong; Li, Gang; Gilmore, John H.; Lin, Weili; Shen, Dinggang

2014-01-01

Segmentation of infant brain MR images is challenging due to poor spatial resolution, severe partial volume effect, and the ongoing maturation and myelination process. During the first year of life, the brain image contrast between white and gray matters undergoes dramatic changes. In particular, the image contrast inverses around 6–8 months of age, where the white and gray matter tissues are isointense in T1 and T2 weighted images and hence exhibit the extremely low tissue contrast, posing significant challenges for automated segmentation. In this paper, we propose a general framework that adopts sparse representation to fuse the multi-modality image information and further incorporate the anatomical constraints for brain tissue segmentation. Specifically, we first derive an initial segmentation from a library of aligned images with ground-truth segmentations by using sparse representation in a patch-based fashion for the multi-modality T1, T2 and FA images. The segmentation result is further iteratively refined by integration of the anatomical constraint. The proposed method was evaluated on 22 infant brain MR images acquired at around 6 months of age by using a leave-one-out cross-validation, as well as other 10 unseen testing subjects. Our method achieved a high accuracy for the Dice ratios that measure the volume overlap between automated and manual segmentations, i.e., 0.889±0.008 for white matter and 0.870±0.006 for gray matter. PMID:24291615

An automatic brain tumor segmentation tool.

PubMed

Diaz, Idanis; Boulanger, Pierre; Greiner, Russell; Hoehn, Bret; Rowe, Lindsay; Murtha, Albert

2013-01-01

This paper introduces an automatic brain tumor segmentation method (ABTS) for segmenting multiple components of brain tumor using four magnetic resonance image modalities. ABTS's four stages involve automatic histogram multi-thresholding and morphological operations including geodesic dilation. Our empirical results, on 16 real tumors, show that ABTS works very effectively, achieving a Dice accuracy compared to expert segmentation of 81% in segmenting edema and 85% in segmenting gross tumor volume (GTV).

Template-based automatic extraction of the joint space of foot bones from CT scan

NASA Astrophysics Data System (ADS)

Park, Eunbi; Kim, Taeho; Park, Jinah

2016-03-01

Clean bone segmentation is critical in studying the joint anatomy for measuring the spacing between the bones. However, separation of the coupled bones in CT images is sometimes difficult due to ambiguous gray values coming from the noise and the heterogeneity of bone materials as well as narrowing of the joint space. For fine reconstruction of the individual local boundaries, manual operation is a common practice where the segmentation remains to be a bottleneck. In this paper, we present an automatic method for extracting the joint space by applying graph cut on Markov random field model to the region of interest (ROI) which is identified by a template of 3D bone structures. The template includes encoded articular surface which identifies the tight region of the high-intensity bone boundaries together with the fuzzy joint area of interest. The localized shape information from the template model within the ROI effectively separates the bones nearby. By narrowing the ROI down to the region including two types of tissue, the object extraction problem was reduced to binary segmentation and solved via graph cut. Based on the shape of a joint space marked by the template, the hard constraint was set by the initial seeds which were automatically generated from thresholding and morphological operations. The performance and the robustness of the proposed method are evaluated on 12 volumes of ankle CT data, where each volume includes a set of 4 tarsal bones (calcaneus, talus, navicular and cuboid).

Quantifying coordination among the rearfoot, midfoot, and forefoot segments during running.

PubMed

Takabayashi, Tomoya; Edama, Mutsuaki; Yokoyama, Erika; Kanaya, Chiaki; Kubo, Masayoshi

2018-03-01

Because previous studies have suggested that there is a relationship between injury risk and inter-segment coordination, quantifying coordination between the segments is essential. Even though the midfoot and forefoot segments play important roles in dynamic tasks, previous studies have mostly focused on coordination between the shank and rearfoot segments. This study aimed to quantify coordination among rearfoot, midfoot, and forefoot segments during running. Eleven healthy young men ran on a treadmill. The coupling angle, representing inter-segment coordination, was calculated using a modified vector coding technique. The coupling angle was categorised into four coordination patterns. During the absorption phase, rearfoot-midfoot coordination in the frontal planes was mostly in-phase (rearfoot and midfoot eversion with similar amplitudes). The present study found that the eversion of the midfoot with respect to the rearfoot was comparable in magnitude to the eversion of the rearfoot with respect to the shank. A previous study has suggested that disruption of the coordination between the internal rotation of the shank and eversion of the rearfoot leads to running injuries such as anterior knee pain. Thus, these data might be used in the future to compare to individuals with foot deformities or running injuries.

The history of late holocene surface-faulting earthquakes on the central segments of the Wasatch fault zone, Utah

USGS Publications Warehouse

Duross, Christopher; Personius, Stephen; Olig, Susan S; Crone, Anthony J.; Hylland, Michael D.; Lund, William R; Schwartz, David P.

2017-01-01

The Wasatch fault (WFZ)—Utah’s longest and most active normal fault—forms a prominent eastern boundary to the Basin and Range Province in northern Utah. To provide paleoseismic data for a Wasatch Front regional earthquake forecast, we synthesized paleoseismic data to define the timing and displacements of late Holocene surface-faulting earthquakes on the central five segments of the WFZ. Our analysis yields revised histories of large (M ~7) surface-faulting earthquakes on the segments, as well as estimates of earthquake recurrence and vertical slip rate. We constrain the timing of four to six earthquakes on each of the central segments, which together yields a history of at least 24 surface-faulting earthquakes since ~6 ka. Using earthquake data for each segment, inter-event recurrence intervals range from about 0.6 to 2.5 kyr, and have a mean of 1.2 kyr. Mean recurrence, based on closed seismic intervals, is ~1.1–1.3 kyr per segment, and when combined with mean vertical displacements per segment of 1.7–2.6 m, yield mean vertical slip rates of 1.3–2.0 mm/yr per segment. These data refine the late Holocene behavior of the central WFZ; however, a significant source of uncertainty is whether structural complexities that define the segments of the WFZ act as hard barriers to ruptures propagating along the fault. Thus, we evaluate fault rupture models including both single-segment and multi-segment ruptures, and define 3–17-km-wide spatial uncertainties in the segment boundaries. These alternative rupture models and segment-boundary zones honor the WFZ paleoseismic data, take into account the spatial and temporal limitations of paleoseismic data, and allow for complex ruptures such as partial-segment and spillover ruptures. Our data and analyses improve our understanding of the complexities in normal-faulting earthquake behavior and provide geological inputs for regional earthquake-probability and seismic hazard assessments.

Saturn Apollo Program

NASA Image and Video Library

1965-03-01

The hydrogen-powered second stage is being lowered into place during the final phase of fabrication of the Saturn V moon rocket at North American's Seal Beach, California facility. The towering 363-foot Saturn V was a multi-stage, multi-engine launch vehicle standing taller than the Statue of Liberty. Altogether, the Saturn V engines produced as much power as 85 Hoover Dams.

Two technicians apply insulation to S-II second stage

NASA Technical Reports Server (NTRS)

1964-01-01

Two technicians apply insulation to the outer surface of the S-II second stage booster for the Saturn V moon rocket. The towering 363-foot Saturn V was a multi-stage, multi-engine launch vehicle standing taller than the Statue of Liberty. Altogether, the Saturn V engines produced as much power as 85 Hoover Dams.

Saturn Apollo Program

NASA Image and Video Library

1968-02-06

Apollo 6, the second and last of the unmarned Saturn V test flights, is slowly transported past the Vehicle Assembly Building on the way to launch pad 39-A. The towering 363-foot Saturn V was a multi-stage, multi-engine launch vehicle standing taller than the Statue of Liberty. Altogether, the Saturn V engines produced as much power as 85 Hoover Dams.

Optimal foot shape for a passive dynamic biped.

PubMed

Kwan, Maxine; Hubbard, Mont

2007-09-21

Passive walking dynamics describe the motion of a biped that is able to "walk" down a shallow slope without any actuation or control. Instead, the walker relies on gravitational and inertial effects to propel itself forward, exhibiting a gait quite similar to that of humans. These purely passive models depend on potential energy to overcome the energy lost when the foot impacts the ground. Previous research has demonstrated that energy loss at heel-strike can vary widely for a given speed, depending on the nature of the collision. The point of foot contact with the ground (relative to the hip) can have a significant effect: semi-circular (round) feet soften the impact, resulting in much smaller losses than point-foot walkers. Collisional losses are also lower if a single impulse is broken up into a series of smaller impulses that gradually redirect the velocity of the center of mass rather than a single abrupt impulse. Using this principle, a model was created where foot-strike occurs over two impulses, "heel-strike" and "toe-strike," representative of the initial impact of the heel and the following impact as the ball of the foot strikes the ground. Having two collisions with the flat-foot model did improve efficiency over the point-foot model. Representation of the flat-foot walker as a rimless wheel helped to explain the optimal flat-foot shape, driven by symmetry of the virtual spoke angles. The optimal long period foot shape of the simple passive walking model was not very representative of the human foot shape, although a reasonably anthropometric foot shape was predicted by the short period solution.

Multi-dimension feature fusion for action recognition

NASA Astrophysics Data System (ADS)

Dong, Pei; Li, Jie; Dong, Junyu; Qi, Lin

2018-04-01

Typical human actions last several seconds and exhibit characteristic spatio-temporal structure. The challenge for action recognition is to capture and fuse the multi-dimension information in video data. In order to take into account these characteristics simultaneously, we present a novel method that fuses multiple dimensional features, such as chromatic images, depth and optical flow fields. We built our model based on the multi-stream deep convolutional networks with the help of temporal segment networks and extract discriminative spatial and temporal features by fusing ConvNets towers multi-dimension, in which different feature weights are assigned in order to take full advantage of this multi-dimension information. Our architecture is trained and evaluated on the currently largest and most challenging benchmark NTU RGB-D dataset. The experiments demonstrate that the performance of our method outperforms the state-of-the-art methods.

Discriminative dictionary learning for abdominal multi-organ segmentation.

PubMed

Tong, Tong; Wolz, Robin; Wang, Zehan; Gao, Qinquan; Misawa, Kazunari; Fujiwara, Michitaka; Mori, Kensaku; Hajnal, Joseph V; Rueckert, Daniel

2015-07-01

An automated segmentation method is presented for multi-organ segmentation in abdominal CT images. Dictionary learning and sparse coding techniques are used in the proposed method to generate target specific priors for segmentation. The method simultaneously learns dictionaries which have reconstructive power and classifiers which have discriminative ability from a set of selected atlases. Based on the learnt dictionaries and classifiers, probabilistic atlases are then generated to provide priors for the segmentation of unseen target images. The final segmentation is obtained by applying a post-processing step based on a graph-cuts method. In addition, this paper proposes a voxel-wise local atlas selection strategy to deal with high inter-subject variation in abdominal CT images. The segmentation performance of the proposed method with different atlas selection strategies are also compared. Our proposed method has been evaluated on a database of 150 abdominal CT images and achieves a promising segmentation performance with Dice overlap values of 94.9%, 93.6%, 71.1%, and 92.5% for liver, kidneys, pancreas, and spleen, respectively. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

A multi-scale tensor voting approach for small retinal vessel segmentation in high resolution fundus images.

PubMed

Christodoulidis, Argyrios; Hurtut, Thomas; Tahar, Houssem Ben; Cheriet, Farida

2016-09-01

Segmenting the retinal vessels from fundus images is a prerequisite for many CAD systems for the automatic detection of diabetic retinopathy lesions. So far, research efforts have concentrated mainly on the accurate localization of the large to medium diameter vessels. However, failure to detect the smallest vessels at the segmentation step can lead to false positive lesion detection counts in a subsequent lesion analysis stage. In this study, a new hybrid method for the segmentation of the smallest vessels is proposed. Line detection and perceptual organization techniques are combined in a multi-scale scheme. Small vessels are reconstructed from the perceptual-based approach via tracking and pixel painting. The segmentation was validated in a high resolution fundus image database including healthy and diabetic subjects using pixel-based as well as perceptual-based measures. The proposed method achieves 85.06% sensitivity rate, while the original multi-scale line detection method achieves 81.06% sensitivity rate for the corresponding images (p<0.05). The improvement in the sensitivity rate for the database is 6.47% when only the smallest vessels are considered (p<0.05). For the perceptual-based measure, the proposed method improves the detection of the vasculature by 7.8% against the original multi-scale line detection method (p<0.05). Copyright © 2016 Elsevier Ltd. All rights reserved.

The evaluation of single-view and multi-view fusion 3D echocardiography using image-driven segmentation and tracking.

PubMed

Rajpoot, Kashif; Grau, Vicente; Noble, J Alison; Becher, Harald; Szmigielski, Cezary

2011-08-01

Real-time 3D echocardiography (RT3DE) promises a more objective and complete cardiac functional analysis by dynamic 3D image acquisition. Despite several efforts towards automation of left ventricle (LV) segmentation and tracking, these remain challenging research problems due to the poor-quality nature of acquired images usually containing missing anatomical information, speckle noise, and limited field-of-view (FOV). Recently, multi-view fusion 3D echocardiography has been introduced as acquiring multiple conventional single-view RT3DE images with small probe movements and fusing them together after alignment. This concept of multi-view fusion helps to improve image quality and anatomical information and extends the FOV. We now take this work further by comparing single-view and multi-view fused images in a systematic study. In order to better illustrate the differences, this work evaluates image quality and information content of single-view and multi-view fused images using image-driven LV endocardial segmentation and tracking. The image-driven methods were utilized to fully exploit image quality and anatomical information present in the image, thus purposely not including any high-level constraints like prior shape or motion knowledge in the analysis approaches. Experiments show that multi-view fused images are better suited for LV segmentation and tracking, while relatively more failures and errors were observed on single-view images. Copyright © 2011 Elsevier B.V. All rights reserved.

Prostate segmentation by feature enhancement using domain knowledge and adaptive region based operations

NASA Astrophysics Data System (ADS)

Nanayakkara, Nuwan D.; Samarabandu, Jagath; Fenster, Aaron

2006-04-01

Estimation of prostate location and volume is essential in determining a dose plan for ultrasound-guided brachytherapy, a common prostate cancer treatment. However, manual segmentation is difficult, time consuming and prone to variability. In this paper, we present a semi-automatic discrete dynamic contour (DDC) model based image segmentation algorithm, which effectively combines a multi-resolution model refinement procedure together with the domain knowledge of the image class. The segmentation begins on a low-resolution image by defining a closed DDC model by the user. This contour model is then deformed progressively towards higher resolution images. We use a combination of a domain knowledge based fuzzy inference system (FIS) and a set of adaptive region based operators to enhance the edges of interest and to govern the model refinement using a DDC model. The automatic vertex relocation process, embedded into the algorithm, relocates deviated contour points back onto the actual prostate boundary, eliminating the need of user interaction after initialization. The accuracy of the prostate boundary produced by the proposed algorithm was evaluated by comparing it with a manually outlined contour by an expert observer. We used this algorithm to segment the prostate boundary in 114 2D transrectal ultrasound (TRUS) images of six patients scheduled for brachytherapy. The mean distance between the contours produced by the proposed algorithm and the manual outlines was 2.70 ± 0.51 pixels (0.54 ± 0.10 mm). We also showed that the algorithm is insensitive to variations of the initial model and parameter values, thus increasing the accuracy and reproducibility of the resulting boundaries in the presence of noise and artefacts.

Multi-font printed Mongolian document recognition system

NASA Astrophysics Data System (ADS)

Peng, Liangrui; Liu, Changsong; Ding, Xiaoqing; Wang, Hua; Jin, Jianming

2009-01-01

Mongolian is one of the major ethnic languages in China. Large amount of Mongolian printed documents need to be digitized in digital library and various applications. Traditional Mongolian script has unique writing style and multi-font-type variations, which bring challenges to Mongolian OCR research. As traditional Mongolian script has some characteristics, for example, one character may be part of another character, we define the character set for recognition according to the segmented components, and the components are combined into characters by rule-based post-processing module. For character recognition, a method based on visual directional feature and multi-level classifiers is presented. For character segmentation, a scheme is used to find the segmentation point by analyzing the properties of projection and connected components. As Mongolian has different font-types which are categorized into two major groups, the parameter of segmentation is adjusted for each group. A font-type classification method for the two font-type group is introduced. For recognition of Mongolian text mixed with Chinese and English, language identification and relevant character recognition kernels are integrated. Experiments show that the presented methods are effective. The text recognition rate is 96.9% on the test samples from practical documents with multi-font-types and mixed scripts.

Controlling a multi-degree of freedom upper limb prosthesis using foot controls: user experience.

PubMed

Resnik, Linda; Klinger, Shana Lieberman; Etter, Katherine; Fantini, Christopher

2014-07-01

The DEKA Arm, a pre-commercial upper limb prosthesis, funded by the DARPA Revolutionizing Prosthetics Program, offers increased degrees of freedom while requiring a large number of user control inputs to operate. To address this challenge, DEKA developed prototype foot controls. Although the concept of utilizing foot controls to operate an upper limb prosthesis has been discussed for decades, only small-sized studies have been performed and no commercial product exists. The purpose of this paper is to report amputee user perspectives on using three different iterations of foot controls to operate the DEKA Arm. Qualitative data was collected from 36 subjects as part of the Department of Veterans Affairs (VA) Study to Optimize the DEKA Arm through surveys, interviews, audio memos, and videotaped sessions. Three major, interrelated themes were identified using the constant comparative method: attitudes towards foot controls, psychomotor learning and physical experience of using foot controls. Feedback about foot controls was generally positive for all iterations. The final version of foot controls was viewed most favorably. Our findings indicate that foot controls are a viable control option that can enable control of a multifunction upper limb prosthesis (the DEKA Arm). Multifunction upper limb prostheses require many user control inputs to operate. Foot controls offer additional control input options for such advanced devices, yet have had minimal study. This study found that foot controls were a viable option for controlling multifunction upper limb prostheses. Most of the 36 subjects in this study were willing to adopt foot controls to control the multiple degrees of freedom of the DEKA Arm. With training and practice, all users were able to develop the psychomotor skills needed to successfully operate food controls. Some had initial difficulty, but acclimated over time.

Velocity and rolling-moment measurements in the wake of a swept-wing model in the 40 by 80 foot wind tunnel

NASA Technical Reports Server (NTRS)

Rossow, V. J.; Corsiglia, V. R.; Schwind, R. G.; Frick, J. K. D.; Lemmer, O. J.

1975-01-01

Measurements were made in the wake of a swept wing model to study the structure of lift generated vortex wakes shed by conventional span loadings and by several span loadings designed to reduce wake velocities. Variations in the span loading on the swept wing generator were obtained by deflecting seven flap segments on each side by amounts determined by vortex lattice theory to approximate the desired span loadings. The resulting wakes were probed with a three component, hot wire probe to measure velocity, and with a wing to measure the rolling moment that would be induced on a following aircraft. The experimental techniques are described herein, and the measured velocity and rolling moments are presented, along with some comparisons with the applicable theories.

Multi-tissue and multi-scale approach for nuclei segmentation in H&E stained images.

PubMed

Salvi, Massimo; Molinari, Filippo

2018-06-20

Accurate nuclei detection and segmentation in histological images is essential for many clinical purposes. While manual annotations are time-consuming and operator-dependent, full automated segmentation remains a challenging task due to the high variability of cells intensity, size and morphology. Most of the proposed algorithms for the automated segmentation of nuclei were designed for specific organ or tissues. The aim of this study was to develop and validate a fully multiscale method, named MANA (Multiscale Adaptive Nuclei Analysis), for nuclei segmentation in different tissues and magnifications. MANA was tested on a dataset of H&E stained tissue images with more than 59,000 annotated nuclei, taken from six organs (colon, liver, bone, prostate, adrenal gland and thyroid) and three magnifications (10×, 20×, 40×). Automatic results were compared with manual segmentations and three open-source software designed for nuclei detection. For each organ, MANA obtained always an F1-score higher than 0.91, with an average F1 of 0.9305 ± 0.0161. The average computational time was about 20 s independently of the number of nuclei to be detected (anyway, higher than 1000), indicating the efficiency of the proposed technique. To the best of our knowledge, MANA is the first fully automated multi-scale and multi-tissue algorithm for nuclei detection. Overall, the robustness and versatility of MANA allowed to achieve, on different organs and magnifications, performances in line or better than those of state-of-art algorithms optimized for single tissues.

Comparison of the trunk-pelvis and lower extremities sagittal plane inter-segmental coordination and variability during walking in persons with and without chronic low back pain.

PubMed

Ebrahimi, Samaneh; Kamali, Fahimeh; Razeghi, Mohsen; Haghpanah, Seyyed Arash

2017-04-01

Inter-segmental coordination can be influenced by chronic low back pain (CLBP). The sagittal plane lower extremities inter-segmental coordination pattern and variability, in conjunction with the pelvis and trunk, were assessed in subjects with and without non-specific CLBP during free-speed walking. Kinematic data were collected from 10 non-specific CLBP and 10 non-CLBP control volunteers while the subjects were walking at their preferred speed. Sagittal plane time-normalized segmental angles and velocities were used to calculate continuous relative phase for each data point. Mean absolute relative phase (MARP) and deviation phase (DP) were derived to quantify the trunk-pelvis and bilateral pelvis-thigh, thigh-shank and shank-foot coordination pattern and variability over the stance and swing phases of gait. Mann-Whitney U test was employed to compare the means of DP and MARP values between two groups (same side comparison). Statistical analysis revealed more in-phase/less variable trunk-pelvis coordination in the CLBP group (P<0.05). CLBP group demonstrated less variable right or left pelvis-thigh coordination pattern (P<0.05). Moreover, the left thigh-shank and left shank-foot MARP values in the CLBP group, were more in-phase than left MARP values in the non-CLBP control group during the swing phase (P<0.05). In conclusion, the sagittal plane lower extremities, pelvis and trunk coordination pattern and variability could be generally affected by CLBP during walking. These changes can be possible compensatory strategies of the motor control system which can be considered in the CLBP subjects. Copyright © 2017 Elsevier B.V. All rights reserved.

Multi-camera sensor system for 3D segmentation and localization of multiple mobile robots.

PubMed

Losada, Cristina; Mazo, Manuel; Palazuelos, Sira; Pizarro, Daniel; Marrón, Marta

2010-01-01

This paper presents a method for obtaining the motion segmentation and 3D localization of multiple mobile robots in an intelligent space using a multi-camera sensor system. The set of calibrated and synchronized cameras are placed in fixed positions within the environment (intelligent space). The proposed algorithm for motion segmentation and 3D localization is based on the minimization of an objective function. This function includes information from all the cameras, and it does not rely on previous knowledge or invasive landmarks on board the robots. The proposed objective function depends on three groups of variables: the segmentation boundaries, the motion parameters and the depth. For the objective function minimization, we use a greedy iterative algorithm with three steps that, after initialization of segmentation boundaries and depth, are repeated until convergence.

Robust segmentation of trabecular bone for in vivo CT imaging using anisotropic diffusion and multi-scale morphological reconstruction

NASA Astrophysics Data System (ADS)

Chen, Cheng; Jin, Dakai; Zhang, Xiaoliu; Levy, Steven M.; Saha, Punam K.

2017-03-01

Osteoporosis is associated with an increased risk of low-trauma fractures. Segmentation of trabecular bone (TB) is essential to assess TB microstructure, which is a key determinant of bone strength and fracture risk. Here, we present a new method for TB segmentation for in vivo CT imaging. The method uses Hessian matrix-guided anisotropic diffusion to improve local separability of trabecular structures, followed by a new multi-scale morphological reconstruction algorithm for TB segmentation. High sensitivity (0.93), specificity (0.93), and accuracy (0.92) were observed for the new method based on regional manual thresholding on in vivo CT images. Mechanical tests have shown that TB segmentation using the new method improved the ability of derived TB spacing measure for predicting actual bone strength (R2=0.83).

A Study on Segmented Multiple-Step Forming of Doubly Curved Thick Plate by Reconfigurable Multi-Punch Dies

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

Ko, Young Ho; Han, Myoung Soo; Han, Jong Man

2007-05-17

Doubly curved thick plate forming in shipbuilding industries is currently performed by a thermal forming process, called as Line Heating by using gas flame torches. Due to the empirical manual work of it, the industries are eager for an alternative way to manufacture curved thick plates for ships. It was envisaged in this study to manufacture doubly curved thick plates by the multi-punch die forming. Experiments and finite element analyses were conducted to evaluate the feasibility of the reconfigurable discrete die forming to the thick plates. Single and segmented multiple step forming procedures were considered from both forming efficiency andmore » accuracy. Configuration of the multi-punch dies suitable for the segmented multiple step forming was also explored. As a result, Segmented multiple step forming with matched dies had a limited formability when the objective shapes become complicate, while a unmatched die configuration provided better possibility to manufacture large curved plates for ships.« less

Effects of Spatial Scale on Cognitive Play in Preschool Children.

ERIC Educational Resources Information Center

Delong, Alton J.; And Others

1994-01-01

Examined effects of a reduced-scale play environment on the temporal aspects of complex play behavior. Children playing with playdough in a 7 x 5 x 5-foot structure began complex play more quickly, played in longer segments, and spent slightly more time in complex play than when in full-size conditions, suggesting that scale-reduced environments…

Analysis of electricity consumption: a study in the wood products industry

Treesearch

Henry Quesada-Pineda; Jan Wiedenbeck; Brian Bond

2016-01-01

This paper evaluates the effect of industry segment, year, and US region on electricity consumption per employee, per dollar sales, and per square foot of plant area for wood products industries. Data was extracted from the Industrial Assessment Center (IAC) database and imported into MS Excel. The extracted dataset was examined for outliers and abnormalities with...