Segmental acetabular rim defects, bone loss, oversizing, and press fit cup in total hip arthroplasty evaluated with a probabilistic finite element analysis.

PubMed

Amirouche, Farid; Solitro, Giovanni F; Walia, Amit; Gonzalez, Mark; Bobko, Aimee

2017-08-01

Management of segmental rim defects and bone mineral density (BMD) loss in the elderly prior to total hip replacement is unclear within classification systems for acetabular bone loss. In this study, our objectives were (1) to understand how a reduction in BMD in the elderly affects the oversizing of a press-fit cup for primary fixation and (2) to evaluate whether the location of the segmental defect affected cup fixation. A finite element (FE) model was used to simulate and evaluate cup insertion and fixation in the context of segmental rim defects. We focused on the distribution of patients over age 70 and used BMD (estimated from CT) as a proxy for aging's implications on THR and used probabilistic FE analysis to understand how BMD loss affects oversizing of a press-fit cup. A cup oversized by 1.10 ± 0.28 mm provides sufficient fixation and lower stresses at the cup-bone interface for elderly patients. Defects in the anterior column and posterior column both required the same mean insertion force for cup seating of 84% (taken as an average of 2 anterior column and 2 posterior column defects) compared to the control configuration, which was 5% greater than the insertion force for a superior rim defect and 12% greater than the insertion force for an inferior rim defect. A defect along the superior or inferior rim had a minimal effect on cup fixation, while a defect in the columns created cup instability and increased stress at the defect location.

Robust Segmentation of Planar and Linear Features of Terrestrial Laser Scanner Point Clouds Acquired from Construction Sites.

PubMed

Maalek, Reza; Lichti, Derek D; Ruwanpura, Janaka Y

2018-03-08

Automated segmentation of planar and linear features of point clouds acquired from construction sites is essential for the automatic extraction of building construction elements such as columns, beams and slabs. However, many planar and linear segmentation methods use scene-dependent similarity thresholds that may not provide generalizable solutions for all environments. In addition, outliers exist in construction site point clouds due to data artefacts caused by moving objects, occlusions and dust. To address these concerns, a novel method for robust classification and segmentation of planar and linear features is proposed. First, coplanar and collinear points are classified through a robust principal components analysis procedure. The classified points are then grouped using a new robust clustering method, the robust complete linkage method. A robust method is also proposed to extract the points of flat-slab floors and/or ceilings independent of the aforementioned stages to improve computational efficiency. The applicability of the proposed method is evaluated in eight datasets acquired from a complex laboratory environment and two construction sites at the University of Calgary. The precision, recall, and accuracy of the segmentation at both construction sites were 96.8%, 97.7% and 95%, respectively. These results demonstrate the suitability of the proposed method for robust segmentation of planar and linear features of contaminated datasets, such as those collected from construction sites.

Robust Segmentation of Planar and Linear Features of Terrestrial Laser Scanner Point Clouds Acquired from Construction Sites

PubMed Central

Maalek, Reza; Lichti, Derek D; Ruwanpura, Janaka Y

2018-01-01

Automated segmentation of planar and linear features of point clouds acquired from construction sites is essential for the automatic extraction of building construction elements such as columns, beams and slabs. However, many planar and linear segmentation methods use scene-dependent similarity thresholds that may not provide generalizable solutions for all environments. In addition, outliers exist in construction site point clouds due to data artefacts caused by moving objects, occlusions and dust. To address these concerns, a novel method for robust classification and segmentation of planar and linear features is proposed. First, coplanar and collinear points are classified through a robust principal components analysis procedure. The classified points are then grouped using a new robust clustering method, the robust complete linkage method. A robust method is also proposed to extract the points of flat-slab floors and/or ceilings independent of the aforementioned stages to improve computational efficiency. The applicability of the proposed method is evaluated in eight datasets acquired from a complex laboratory environment and two construction sites at the University of Calgary. The precision, recall, and accuracy of the segmentation at both construction sites were 96.8%, 97.7% and 95%, respectively. These results demonstrate the suitability of the proposed method for robust segmentation of planar and linear features of contaminated datasets, such as those collected from construction sites. PMID:29518062

The Axolotl Fibula as a Model for the Induction of Regeneration across Large Segment Defects in Long Bones of the Extremities

PubMed Central

Chen, Xiaoping; Song, Fengyu; Jhamb, Deepali; Li, Jiliang; Bottino, Marco C.; Palakal, Mathew J.; Stocum, David L.

2015-01-01

We tested the ability of the axolotl (Ambystoma mexicanum) fibula to regenerate across segment defects of different size in the absence of intervention or after implant of a unique 8-braid pig small intestine submucosa (SIS) scaffold, with or without incorporated growth factor combinations or tissue protein extract. Fractures and defects of 10% and 20% of the total limb length regenerated well without any intervention, but 40% and 50% defects failed to regenerate after either simple removal of bone or implanting SIS scaffold alone. By contrast, scaffold soaked in the growth factor combination BMP-4/HGF or in protein extract of intact limb tissue promoted partial or extensive induction of cartilage and bone across 50% segment defects in 30%-33% of cases. These results show that BMP-4/HGF and intact tissue protein extract can promote the events required to induce cartilage and bone formation across a segment defect larger than critical size and that the long bones of axolotl limbs are an inexpensive model to screen soluble factors and natural and synthetic scaffolds for their efficacy in stimulating this process. PMID:26098852

An Improved Unsupervised Image Segmentation Evaluation Approach Based on - and Over-Segmentation Aware

NASA Astrophysics Data System (ADS)

Su, Tengfei

2018-04-01

In this paper, an unsupervised evaluation scheme for remote sensing image segmentation is developed. Based on a method called under- and over-segmentation aware (UOA), the new approach is improved by overcoming the defect in the part of estimating over-segmentation error. Two cases of such error-prone defect are listed, and edge strength is employed to devise a solution to this issue. Two subsets of high resolution remote sensing images were used to test the proposed algorithm, and the experimental results indicate its superior performance, which is attributed to its improved OSE detection model.

Prognostic value of myocardial ischemia and necrosis in depressed left ventricular function: a multicenter stress cardiac magnetic resonance registry.

PubMed

Husser, Oliver; Monmeneu, Jose V; Bonanad, Clara; Lopez-Lereu, Maria P; Nuñez, Julio; Bosch, Maria J; Garcia, Carlos; Sanchis, Juan; Chorro, Francisco J; Bodi, Vicente

2014-09-01

The incremental prognostic value of inducible myocardial ischemia over necrosis derived by stress cardiac magnetic resonance in depressed left ventricular function is unknown. We determined the prognostic value of necrosis and ischemia in patients with depressed left ventricular function referred for dipyridamole stress perfusion magnetic resonance. In a multicenter registry using stress magnetic resonance, the presence (≥ 2 segments) of late enhancement and perfusion defects and their association with major events (cardiac death and nonfatal infarction) was determined. In 391 patients, perfusion defect or late enhancement were present in 224 (57%) and 237 (61%). During follow-up (median, 96 weeks), 47 major events (12%) occurred: 25 cardiac deaths and 22 myocardial infarctions. Patients with major events displayed a larger extent of perfusion defects (6 segments vs 3 segments; P <.001) but not late enhancement (5 segments vs 3 segments; P =.1). Major event rate was significantly higher in the presence of perfusion defects (17% vs 5%; P =.0005) but not of late enhancement (14% vs 9%; P =.1). Patients were categorized into 4 groups: absence of perfusion defect and absence of late enhancement (n = 124), presence of late enhancement and absence of perfusion defect (n = 43), presence of perfusion defect and presence of late enhancement (n = 195), absence of late enhancement and presence of perfusion defect (n = 29). Event rate was 5%, 7%, 16%, and 24%, respectively (P for trend = .003). In a multivariate regression model, only perfusion defect (hazard ratio = 2.86; 95% confidence interval, 1.37-5.95]; P = .002) but not late enhancement (hazard ratio = 1.70; 95% confidence interval, 0.90-3.22; P =.105) predicted events. In depressed left ventricular function, the presence of inducible ischemia is the strongest predictor of major events. Copyright © 2014 Sociedad Española de Cardiología. Published by Elsevier Espana. All rights reserved.

Application of Morphological Segmentation to Leaking Defect Detection in Sewer Pipelines

PubMed Central

Su, Tung-Ching; Yang, Ming-Der

2014-01-01

As one of major underground pipelines, sewerage is an important infrastructure in any modern city. The most common problem occurring in sewerage is leaking, whose position and failure level is typically idengified through closed circuit television (CCTV) inspection in order to facilitate rehabilitation process. This paper proposes a novel method of computer vision, morphological segmentation based on edge detection (MSED), to assist inspectors in detecting pipeline defects in CCTV inspection images. In addition to MSED, other mathematical morphology-based image segmentation methods, including opening top-hat operation (OTHO) and closing bottom-hat operation (CBHO), were also applied to the defect detection in vitrified clay sewer pipelines. The CCTV inspection images of the sewer system in the 9th district, Taichung City, Taiwan were selected as the experimental materials. The segmentation results demonstrate that MSED and OTHO are useful for the detection of cracks and open joints, respectively, which are the typical leakage defects found in sewer pipelines. PMID:24841247

Segmental bone defects: from cellular and molecular pathways to the development of novel biological treatments

PubMed Central

Pneumaticos, Spyros G; Triantafyllopoulos, Georgios K; Basdra, Efthimia K; Papavassiliou, Athanasios G

2010-01-01

Abstract Several conditions in clinical orthopaedic practice can lead to the development of a diaphyseal segmental bone defect, which cannot heal without intervention. Segmental bone defects have been traditionally treated with bone grafting and/or distraction osteogenesis, methods that have many advantages, but also major drawbacks, such as limited availability, risk of disease transmission and prolonged treatment. In order to overcome such limitations, biological treatments have been developed based on specific pathways of bone physiology and healing. Bone tissue engineering is a dynamic field of research, combining osteogenic cells, osteoinductive factors, such as bone morphogenetic proteins, and scaffolds with osteoconductive and osteoinductive attributes, to produce constructs that could be used as bone graft substitutes for the treatment of segmental bone defects. Scaffolds are usually made of ceramic or polymeric biomaterials, or combinations of both in composite materials. The purpose of the present review is to discuss in detail the molecular and cellular basis for the development of bone tissue engineering constructs. PMID:20345845

Repair of tracheomalacia with inflammatory defect and mediastinitis.

PubMed

Sandu, Kishore; Monnier, Yan; Hurni, Michel; Bernath, Marc-Andre; Monnier, Philippe; Wang, Yabo; Ris, Hans-Beat

2011-01-01

We describe a novel repair of an anterior inflammatory tracheal defect with mediastinitis, which occurred after external tracheal suspension of localized intrathoracic tracheomalacia. The malacic tracheal segment of 4-cm length containing the inflammatory tracheal defect was noncircumferentially resected. A temporary endotracheal silicone stent was introduced, and the trachea was closed by a pedicled pectoralis muscle flap reinforced with an embedded rib segment. Retrieval of the stent 5 months postoperatively resulted in a re-epithelialized, persistently stable, noncollapsible tracheal segment that showed the same diameter and configuration as the nonreconstructed part of the trachea. Copyright © 2011 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

Unified framework for automated iris segmentation using distantly acquired face images.

PubMed

Tan, Chun-Wei; Kumar, Ajay

2012-09-01

Remote human identification using iris biometrics has high civilian and surveillance applications and its success requires the development of robust segmentation algorithm to automatically extract the iris region. This paper presents a new iris segmentation framework which can robustly segment the iris images acquired using near infrared or visible illumination. The proposed approach exploits multiple higher order local pixel dependencies to robustly classify the eye region pixels into iris or noniris regions. Face and eye detection modules have been incorporated in the unified framework to automatically provide the localized eye region from facial image for iris segmentation. We develop robust postprocessing operations algorithm to effectively mitigate the noisy pixels caused by the misclassification. Experimental results presented in this paper suggest significant improvement in the average segmentation errors over the previously proposed approaches, i.e., 47.5%, 34.1%, and 32.6% on UBIRIS.v2, FRGC, and CASIA.v4 at-a-distance databases, respectively. The usefulness of the proposed approach is also ascertained from recognition experiments on three different publicly available databases.

Internal Prosthetic Replacement of Skeletal Segments Lost in Combat Injuries.

DTIC Science & Technology

1973-08-31

osteo- articular bone grafts. Clin. Ortho., 87: 156, 1972. 8. Tuli, S. M.: Bridging of bone defects by massive bone grafts in tumorous conditions. Clin...fashion in its proximal one-third to "prevent distractic ,n of the fragments. The fiber metal segment was then placed in the appropriate defect and the...defect slightly oversized and also osteotomizing the fibula to delete any possible distracting forces or angulating forces. The only complication in

Automated compromised right lung segmentation method using a robust atlas-based active volume model with sparse shape composition prior in CT.

PubMed

Zhou, Jinghao; Yan, Zhennan; Lasio, Giovanni; Huang, Junzhou; Zhang, Baoshe; Sharma, Navesh; Prado, Karl; D'Souza, Warren

2015-12-01

To resolve challenges in image segmentation in oncologic patients with severely compromised lung, we propose an automated right lung segmentation framework that uses a robust, atlas-based active volume model with a sparse shape composition prior. The robust atlas is achieved by combining the atlas with the output of sparse shape composition. Thoracic computed tomography images (n=38) from patients with lung tumors were collected. The right lung in each scan was manually segmented to build a reference training dataset against which the performance of the automated segmentation method was assessed. The quantitative results of this proposed segmentation method with sparse shape composition achieved mean Dice similarity coefficient (DSC) of (0.72, 0.81) with 95% CI, mean accuracy (ACC) of (0.97, 0.98) with 95% CI, and mean relative error (RE) of (0.46, 0.74) with 95% CI. Both qualitative and quantitative comparisons suggest that this proposed method can achieve better segmentation accuracy with less variance than other atlas-based segmentation methods in the compromised lung segmentation. Published by Elsevier Ltd.

Assessment of myocardial viability by dynamic tomographic iodine 123 iodophenylpentadecanoic acid imaging: comparison with rest-redistribution thallium 201 imaging.

PubMed

Iskandrian, A S; Powers, J; Cave, V; Wasserleben, V; Cassell, D; Heo, J

1995-01-01

This study examined the ability of dynamic 123I-labeled iodophenylpentadecanoic acid (IPPA) imaging to detect myocardial viability in patients with left ventricular (LV) dysfunction caused by coronary artery disease. Serial 180-degree single-photon emission computed tomographic (SPECT) images (five sets, 8 minutes each) were obtained starting 4 minutes after injection of 2 to 6 mCi 123I at rest in 21 patients with LV dysfunction (ejection fraction [EF] 34% +/- 11%). The segmental uptake was compared with that of rest-redistribution 201Tl images (20 segments/study). The number of perfusion defects (reversible and fixed) was similar by IPPA and thallium (11 +/- 5 vs 10 +/- 5 segments/patient; difference not significant). There was agreement between IPPA and thallium for presence or absence (kappa = 0.78 +/- 0.03) and nature (reversible, mild fixed, or severe fixed) of perfusion defects (kappa = 0.54 +/- 0.04). However, there were more reversible IPPA defects than reversible thallium defects (7 +/- 4 vs 3 +/- 4 segments/patient; p = 0.001). In 14 patients the EF (by gated pool imaging) improved after coronary revascularization from 33% +/- 11% to 39% +/- 12% (p = 0.002). The number of reversible IPPA defects was greater in the seven patients who had improvement in EF than in the patients without such improvement (10 +/- 4 vs 5 +/- 4 segments/patient; p = 0.075). 123I-labeled IPPA SPECT imaging is a promising new technique for assessment of viability. Reversible defects predict recovery of LV dysfunction after coronary revascularization.

Segmentation, surface rendering, and surface simplification of 3-D skull images for the repair of a large skull defect

NASA Astrophysics Data System (ADS)

Wan, Weibing; Shi, Pengfei; Li, Shuguang

2009-10-01

Given the potential demonstrated by research into bone-tissue engineering, the use of medical image data for the rapid prototyping (RP) of scaffolds is a subject worthy of research. Computer-aided design and manufacture and medical imaging have created new possibilities for RP. Accurate and efficient design and fabrication of anatomic models is critical to these applications. We explore the application of RP computational methods to the repair of a pediatric skull defect. The focus of this study is the segmentation of the defect region seen in computerized tomography (CT) slice images of this patient's skull and the three-dimensional (3-D) surface rendering of the patient's CT-scan data. We see if our segmentation and surface rendering software can improve the generation of an implant model to fill a skull defect.

Application of the 3D slicer chest imaging platform segmentation algorithm for large lung nodule delineation

PubMed Central

Parmar, Chintan; Blezek, Daniel; Estepar, Raul San Jose; Pieper, Steve; Kim, John; Aerts, Hugo J. W. L.

2017-01-01

Purpose Accurate segmentation of lung nodules is crucial in the development of imaging biomarkers for predicting malignancy of the nodules. Manual segmentation is time consuming and affected by inter-observer variability. We evaluated the robustness and accuracy of a publically available semiautomatic segmentation algorithm that is implemented in the 3D Slicer Chest Imaging Platform (CIP) and compared it with the performance of manual segmentation. Methods CT images of 354 manually segmented nodules were downloaded from the LIDC database. Four radiologists performed the manual segmentation and assessed various nodule characteristics. The semiautomatic CIP segmentation was initialized using the centroid of the manual segmentations, thereby generating four contours for each nodule. The robustness of both segmentation methods was assessed using the region of uncertainty (δ) and Dice similarity index (DSI). The robustness of the segmentation methods was compared using the Wilcoxon-signed rank test (pWilcoxon<0.05). The Dice similarity index (DSIAgree) between the manual and CIP segmentations was computed to estimate the accuracy of the semiautomatic contours. Results The median computational time of the CIP segmentation was 10 s. The median CIP and manually segmented volumes were 477 ml and 309 ml, respectively. CIP segmentations were significantly more robust than manual segmentations (median δCIP = 14ml, median dsiCIP = 99% vs. median δmanual = 222ml, median dsimanual = 82%) with pWilcoxon~10−16. The agreement between CIP and manual segmentations had a median DSIAgree of 60%. While 13% (47/354) of the nodules did not require any manual adjustment, minor to substantial manual adjustments were needed for 87% (305/354) of the nodules. CIP segmentations were observed to perform poorly (median DSIAgree≈50%) for non-/sub-solid nodules with subtle appearances and poorly defined boundaries. Conclusion Semi-automatic CIP segmentation can potentially reduce the physician workload for 13% of nodules owing to its computational efficiency and superior stability compared to manual segmentation. Although manual adjustment is needed for many cases, CIP segmentation provides a preliminary contour for physicians as a starting point. PMID:28594880

A robust and fast active contour model for image segmentation with intensity inhomogeneity

NASA Astrophysics Data System (ADS)

Ding, Keyan; Weng, Guirong

2018-04-01

In this paper, a robust and fast active contour model is proposed for image segmentation in the presence of intensity inhomogeneity. By introducing the local image intensities fitting functions before the evolution of curve, the proposed model can effectively segment images with intensity inhomogeneity. And the computation cost is low because the fitting functions do not need to be updated in each iteration. Experiments have shown that the proposed model has a higher segmentation efficiency compared to some well-known active contour models based on local region fitting energy. In addition, the proposed model is robust to initialization, which allows the initial level set function to be a small constant function.

Non-Convex Sparse and Low-Rank Based Robust Subspace Segmentation for Data Mining.

PubMed

Cheng, Wenlong; Zhao, Mingbo; Xiong, Naixue; Chui, Kwok Tai

2017-07-15

Parsimony, including sparsity and low-rank, has shown great importance for data mining in social networks, particularly in tasks such as segmentation and recognition. Traditionally, such modeling approaches rely on an iterative algorithm that minimizes an objective function with convex l ₁-norm or nuclear norm constraints. However, the obtained results by convex optimization are usually suboptimal to solutions of original sparse or low-rank problems. In this paper, a novel robust subspace segmentation algorithm has been proposed by integrating l p -norm and Schatten p -norm constraints. Our so-obtained affinity graph can better capture local geometrical structure and the global information of the data. As a consequence, our algorithm is more generative, discriminative and robust. An efficient linearized alternating direction method is derived to realize our model. Extensive segmentation experiments are conducted on public datasets. The proposed algorithm is revealed to be more effective and robust compared to five existing algorithms.

Assessing the Robustness of Complete Bacterial Genome Segmentations

NASA Astrophysics Data System (ADS)

Devillers, Hugo; Chiapello, Hélène; Schbath, Sophie; El Karoui, Meriem

Comparison of closely related bacterial genomes has revealed the presence of highly conserved sequences forming a "backbone" that is interrupted by numerous, less conserved, DNA fragments. Segmentation of bacterial genomes into backbone and variable regions is particularly useful to investigate bacterial genome evolution. Several software tools have been designed to compare complete bacterial chromosomes and a few online databases store pre-computed genome comparisons. However, very few statistical methods are available to evaluate the reliability of these software tools and to compare the results obtained with them. To fill this gap, we have developed two local scores to measure the robustness of bacterial genome segmentations. Our method uses a simulation procedure based on random perturbations of the compared genomes. The scores presented in this paper are simple to implement and our results show that they allow to discriminate easily between robust and non-robust bacterial genome segmentations when using aligners such as MAUVE and MGA.

Optimizing Soft Tissue Management and Spacer Design in Segmental Bone Defects

DTIC Science & Technology

2016-12-01

proximal and distal bone segments. 3. Debride 10 grams of tibialis anterior and gastrocnemius muscles. 4. Place an interlocking intramedullary nail ...using a custom spacer to maintain 5-cm defect length. 5. Place a pre-molded 5 cm long x 2 cm diameter PMMA spacer around the nail in the defect. 6...tibia. 3. Open the IM surrounding the PMMA spacer using a “bomb bay door opening”. 4. Remove the spacer without damaging the membrane or nail . 5

Replacement of segmental bone defects using porous bioceramic cylinders: a biomechanical and X-ray diffraction study.

PubMed

Zhang, C; Wang, J; Feng, H; Lu, B; Song, Z; Zhang, X

2001-03-05

A porous ceramic material [hydroxyapatitetricalcium phosphate (HA-TCP)] was implanted in the femora of 30 dogs to investigate the possibility of using this material to repair segmental bone defects. A bone segment, 1.5 cm in length, was removed from the diaphysis of one femur in each dog to create the defect. Cylinders of corresponding size were inserted into the defects. The animals were divided into three groups with recovery times of 2 months, 4 months, and 6 months, respectively. The implants were harvested and subjected to biomechanic tests (bending strength) and X-ray diffraction analysis. The bending strengths of the implant construct increased gradually over time postoperatively. The values of strength for the three different time groups had significant variations (p < 0.05). The X-ray diffraction analysis indicated that the peaks of the TCP included in the cylinders decreased in intensity after implantation and tended to be similar to those of natural bone by 6 months after operation. Conversely, the peaks for the HA had fewer changes compared with preimplantation values. Based on the results of this experiment it was concluded that the porous HA-TCP ceramic cylinders have potential for repair of segmental bone defects if assisted by adequate stabilizing fixtures during the early postoperative period.

Establishment of a bilateral femoral large segmental bone defect mouse model potentially applicable to basic research in bone tissue engineering.

PubMed

Xing, Junchao; Jin, Huiyong; Hou, Tianyong; Chang, Zhengqi; Luo, Fei; Wang, Pinpin; Li, Zhiqiang; Xie, Zhao; Xu, Jianzhong

2014-12-01

To understand the cellular mechanism underlying bone defect healing in the context of tissue engineering, a reliable, reproducible, and standardized load-bearing large segmental bone defect model in small animals is indispensable. The aim of this study was to establish and evaluate a bilateral femoral defect model in mice. Donor mouse bone marrow mesenchymal stem cells (mBMSCs) were obtained from six mice (FVB/N) and incorporated into partially demineralized bone matrix scaffolds to construct tissue-engineered bones. In total, 36 GFP(+) mice were used for modeling. Titanium fixation plates with locking steel wires were attached to the femurs for stabilization, and 2-mm-long segmental bone defects were created in the bilateral femoral midshafts. The defects in the left and right femurs were transplanted with tissue-engineered bones and control scaffolds, respectively. The healing process was monitored by x-ray radiography, microcomputed tomography, and histology. The capacity of the transplanted mBMSCs to recruit host CD31(+) cells was investigated by immunofluorescence and real-time polymerase chain reaction. Postoperatively, no complication was observed, except that two mice died of unknown causes. Stable fixation of femurs and implants with full load bearing was achieved in all animals. The process of bone defect repair was significantly accelerated due to the introduction of mBMSCs. Moreover, the transplanted mBMSCs attracted more host CD31(+) endothelial progenitors into the grafts. The present study established a feasible, reproducible, and clinically relevant bilateral femoral large segmental bone defect mouse model. This model is potentially suitable for basic research in the field of bone tissue engineering. Copyright © 2014 Elsevier Inc. All rights reserved.

Correlation between spectral-domain OCT findings and visual acuity in X-linked retinoschisis.

PubMed

Yang, Hyun Seung; Lee, Jung Bok; Yoon, Young Hee; Lee, Joo Yong

2014-05-08

To investigate the tomographic characteristics of the outer retina and choroid and their relationship with visual acuity in X-linked juvenile retinoschisis (XLRS) patients using spectral-domain optical coherence tomography (SD-OCT). In this retrospective, observational, case-control study, we analyzed 20 eyes of 10 patients with XLRS using SD-OCT. The clinical and tomographic features of the outer retina, including the external limiting membrane (ELM), inner segment/outer segment (IS/OS) junction, cone cell outer segment tips (COST) line, photoreceptor outer segment (PROS) length, and choroid, were evaluated. As controls, 40 age-, sex-, and refraction-matched healthy eyes (1:2 matched) were randomly selected and imaged in parallel. The most prevalent area of abnormality in the outer retina layer of our patients was the outer plexiform layer (OPL; 60% of all affected eyes) and COST line (75% of all affected eyes). On average, the subfoveal choroid and PROS lengths were 35 μm thicker and 19 μm thinner, respectively, in XLRS patients (P = 0.084 and P < 0.001, respectively). A dominant IS/OS junction, COST line defects, and PROS length were related to patient best-corrected visual acuity (BCVA; P = 0.029, P = 0.001, and P < 0.001, respectively) by univariate analysis. Cone cell outer segment tips line defect and PROS length were the only factors related to BCVA in multivariate analysis (P = 0.028 and 0.003, respectively). Outer plexiform layer and photoreceptor microstructure defects are frequent in XLRS patients. Cone cell outer segment tips line defects and shortened PROS lengths as well as other photoreceptor microstructure defects may be closely related to poor vision in XLRS.

Flow-Through Free Fibula Osteocutaneous Flap in Reconstruction of Tibial Bone, Soft Tissue, and Main Artery Segmental Defects.

PubMed

Li, Zonghuan; Yu, Aixi; Qi, Baiwen; Pan, Zhenyu; Ding, Junhui

2017-08-01

The aim of this report was to present the use of flow-through free fibula osteocutaneous flap for the repair of complex tibial bone, soft tissue, and main artery segmental defects. Five patients with bone, soft tissue, and segmental anterior tibial artery defects were included. The lengths of injured tibial bones ranged from 4 to 7 cm. The sizes of impaired soft tissues were between 9 × 4 and 15 × 6 cm. The lengths of defect of anterior tibial artery segments ranged from 6 to 10 cm. Two patients had distal limb perfusion problems. Flow-through free fibula osteocutaneous flap was performed for all 5 patients. Patients were followed for 12 to 18 months. All wounds healed after 1-stage operation, and all flow-through flaps survived. The distal perfusion after vascular repair was normal in all patients. Superficial necrosis of flap edge was noted in 1 case. After the local debridement and partial thickness skin graft, the flap healed uneventfully, and the surgical operation did not increase injury to the donor site. Satisfactory bone union was achieved in all patients in 2 to 4 months postoperation. Enlargement of fibula graft was observed during follow-up from 12 to 18 months. The functions of adjacent joints were recovered, and all patients were able to walk normally. Flow-through free fibula osteocutaneous flap was shown to be an effective and efficient technique for repairing composite tibial bone, soft tissue, and main artery segmental defects. This 1-stage operation should be useful in clinical practice for the treatment of complex bone, soft tissue, and vessel defects.

Combining the 3D model generated from point clouds and thermography to identify the defects presented on the facades of a building

NASA Astrophysics Data System (ADS)

Huang, Yishuo; Chiang, Chih-Hung; Hsu, Keng-Tsang

2018-03-01

Defects presented on the facades of a building do have profound impacts on extending the life cycle of the building. How to identify the defects is a crucial issue; destructive and non-destructive methods are usually employed to identify the defects presented on a building. Destructive methods always cause the permanent damages for the examined objects; on the other hand, non-destructive testing (NDT) methods have been widely applied to detect those defects presented on exterior layers of a building. However, NDT methods cannot provide efficient and reliable information for identifying the defects because of the huge examination areas. Infrared thermography is often applied to quantitative energy performance measurements for building envelopes. Defects on the exterior layer of buildings may be caused by several factors: ventilation losses, conduction losses, thermal bridging, defective services, moisture condensation, moisture ingress, and structure defects. Analyzing the collected thermal images can be quite difficult when the spatial variations of surface temperature are small. In this paper the authors employ image segmentation to cluster those pixels with similar surface temperatures such that the processed thermal images can be composed of limited groups. The surface temperature distribution in each segmented group is homogenous. In doing so, the regional boundaries of the segmented regions can be identified and extracted. A terrestrial laser scanner (TLS) is widely used to collect the point clouds of a building, and those point clouds are applied to reconstruct the 3D model of the building. A mapping model is constructed such that the segmented thermal images can be projected onto the 2D image of the specified 3D building. In this paper, the administrative building in Chaoyang University campus is used as an example. The experimental results not only provide the defect information but also offer their corresponding spatial locations in the 3D model.

Photoreceptor change and visual outcome after idiopathic epiretinal membrane removal with or without additional internal limiting membrane peeling.

PubMed

Ahn, Seong Joon; Ahn, Jeeyun; Woo, Se Joon; Park, Kyu Hyung

2014-01-01

To compare the postoperative photoreceptor status and visual outcome after epiretinal membrane removal with or without additional internal limiting membrane (ILM) peeling. Medical records of 40 eyes from 37 patients undergoing epiretinal membrane removal with residual ILM peeling (additional ILM peeling group) and 69 eyes from 65 patients undergoing epiretinal membrane removal without additional ILM peeling (no additional peeling group) were reviewed. The length of defects in cone outer segment tips, inner segment/outer segment junction, and external limiting membrane line were measured using spectral domain optical coherence tomography images of the fovea before and at 1, 3, 6, and 12 months after the surgery. Cone outer segment tips and inner segment/outer segment junction line defects were most severe at postoperative 1 month and gradually restored at 12 months postoperatively. The cone outer segment tips line defect in the additional ILM peeling group was significantly greater than that in the no additional peeling group at postoperative 1 month (P = 0.006), and best-corrected visual acuity was significantly worse in the former group at the same month (P = 0.001). There was no significant difference in the defect size and best-corrected visual acuity at subsequent visits and recurrence rates between the two groups. Patients who received epiretinal membrane surgery without additional ILM peeling showed better visual and anatomical outcome than those with additional ILM peeling at postoperative 1 month. However, surgical outcomes were comparable between the two groups, thereafter. In terms of visual outcome and photoreceptor integrity, additional ILM peeling may not be an essential procedure.

7 CFR 51.1837 - Classification of defects.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Definitions § 51.1837 Classification of defects. Table I Factor Damage Serious damage Very serious damage... segments more than 1/8 inch (3.2 mm) at stem end, or the equivalent of this amount, by volume, when occurring in other portions of the fruit Affecting all segments more than 1/4 inch (6.4 mm) at stem end, or...

7 CFR 51.1837 - Classification of defects.

Code of Federal Regulations, 2013 CFR

2013-01-01

... Definitions § 51.1837 Classification of defects. Table I Factor Damage Serious damage Very serious damage... segments more than 1/8 inch (3.2 mm) at stem end, or the equivalent of this amount, by volume, when occurring in other portions of the fruit Affecting all segments more than 1/4 inch (6.4 mm) at stem end, or...

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.

A Robust and Fast Method for Sidescan Sonar Image Segmentation Using Nonlocal Despeckling and Active Contour Model.

PubMed

Huo, Guanying; Yang, Simon X; Li, Qingwu; Zhou, Yan

2017-04-01

Sidescan sonar image segmentation is a very important issue in underwater object detection and recognition. In this paper, a robust and fast method for sidescan sonar image segmentation is proposed, which deals with both speckle noise and intensity inhomogeneity that may cause considerable difficulties in image segmentation. The proposed method integrates the nonlocal means-based speckle filtering (NLMSF), coarse segmentation using k -means clustering, and fine segmentation using an improved region-scalable fitting (RSF) model. The NLMSF is used before the segmentation to effectively remove speckle noise while preserving meaningful details such as edges and fine features, which can make the segmentation easier and more accurate. After despeckling, a coarse segmentation is obtained by using k -means clustering, which can reduce the number of iterations. In the fine segmentation, to better deal with possible intensity inhomogeneity, an edge-driven constraint is combined with the RSF model, which can not only accelerate the convergence speed but also avoid trapping into local minima. The proposed method has been successfully applied to both noisy and inhomogeneous sonar images. Experimental and comparative results on real and synthetic sonar images demonstrate that the proposed method is robust against noise and intensity inhomogeneity, and is also fast and accurate.

Tool Measures Depths of Defects on a Case Tang Joint

NASA Technical Reports Server (NTRS)

Ream, M. Bryan; Montgomery, Ronald B.; Mecham, Brent A.; Keirstead, Bums W.

2005-01-01

A special-purpose tool has been developed for measuring the depths of defects on an O-ring seal surface. The surface lies in a specially shaped ringlike fitting, called a capture feature tang, located on an end of a cylindrical segment of a case that contains a solid-fuel booster rocket motor for launching a space shuttle. The capture feature tang is a part of a tang-and-clevis, O-ring joint between the case segment and a similar, adjacent cylindrical case segment. When the segments are joined, the tang makes an interference fit with the clevis and squeezes the O-ring at the side of the gap.

[Comparison of initial and delayed myocardial imaging with beta-methyl-p-[123I]-iodophenylpentadecanoic acid in acute myocardial infarction].

PubMed

Naruse, H; Yoshimura, N; Yamamoto, J; Morita, M; Fukutake, N; Ohyanagi, M; Iwasaki, T; Fukuchi, M

1994-01-01

Myocardial imaging using beta-methyl-p-[123I]-iodophenylpentadecanoic acid (BMIPP) of 15 patients with acute myocardial infarction was performed to assess "fill-in" and "washout" defects in the delayed myocardial image. The initial and delayed images were evaluated by a visual and quantitative washout rate method. Visual judgement found 8/180 (4%) segments showed "fill-in" defects, and 24/180 segments (13%) showed "washout" defects. There was no relationship between days from onset to the study and the frequency of fill-in and washout defects. The mean washout rate in the segments with "fill-in" defects was 9.0 +/- 16.6%, and that of "washout" defects was 24.9 +/- 18.1% which was significantly higher than in controls (8.7 +/- 15.4%, p < 0.05). There was no correlation between mean washout rate and total blood lipids, total cholesterol, triglyceride and HDL-cholesterol. Therefore, neither time from onset nor blood lipids level was related to changes from the initial image to the delayed image. These changes may be due to relative (false) findings due to changes in circumference, and may be based on myocardial characteristics after myocardial infarction and/or reperfusion.

Atlas-based liver segmentation and hepatic fat-fraction assessment for clinical trials.

PubMed

Yan, Zhennan; Zhang, Shaoting; Tan, Chaowei; Qin, Hongxing; Belaroussi, Boubakeur; Yu, Hui Jing; Miller, Colin; Metaxas, Dimitris N

2015-04-01

Automated assessment of hepatic fat-fraction is clinically important. A robust and precise segmentation would enable accurate, objective and consistent measurement of hepatic fat-fraction for disease quantification, therapy monitoring and drug development. However, segmenting the liver in clinical trials is a challenging task due to the variability of liver anatomy as well as the diverse sources the images were acquired from. In this paper, we propose an automated and robust framework for liver segmentation and assessment. It uses single statistical atlas registration to initialize a robust deformable model to obtain fine segmentation. Fat-fraction map is computed by using chemical shift based method in the delineated region of liver. This proposed method is validated on 14 abdominal magnetic resonance (MR) volumetric scans. The qualitative and quantitative comparisons show that our proposed method can achieve better segmentation accuracy with less variance comparing with two other atlas-based methods. Experimental results demonstrate the promises of our assessment framework. Copyright © 2014 Elsevier Ltd. All rights reserved.

AutoCellSeg: robust automatic colony forming unit (CFU)/cell analysis using adaptive image segmentation and easy-to-use post-editing techniques.

PubMed

Khan, Arif Ul Maula; Torelli, Angelo; Wolf, Ivo; Gretz, Norbert

2018-05-08

In biological assays, automated cell/colony segmentation and counting is imperative owing to huge image sets. Problems occurring due to drifting image acquisition conditions, background noise and high variation in colony features in experiments demand a user-friendly, adaptive and robust image processing/analysis method. We present AutoCellSeg (based on MATLAB) that implements a supervised automatic and robust image segmentation method. AutoCellSeg utilizes multi-thresholding aided by a feedback-based watershed algorithm taking segmentation plausibility criteria into account. It is usable in different operation modes and intuitively enables the user to select object features interactively for supervised image segmentation method. It allows the user to correct results with a graphical interface. This publicly available tool outperforms tools like OpenCFU and CellProfiler in terms of accuracy and provides many additional useful features for end-users.

Rapid surface defect detection based on singular value decomposition using steel strips as an example

NASA Astrophysics Data System (ADS)

Sun, Qianlai; Wang, Yin; Sun, Zhiyi

2018-05-01

For most surface defect detection methods based on image processing, image segmentation is a prerequisite for determining and locating the defect. In our previous work, a method based on singular value decomposition (SVD) was used to determine and approximately locate surface defects on steel strips without image segmentation. For the SVD-based method, the image to be inspected was projected onto its first left and right singular vectors respectively. If there were defects in the image, there would be sharp changes in the projections. Then the defects may be determined and located according sharp changes in the projections of each image to be inspected. This method was simple and practical but the SVD should be performed for each image to be inspected. Owing to the high time complexity of SVD itself, it did not have a significant advantage in terms of time consumption over image segmentation-based methods. Here, we present an improved SVD-based method. In the improved method, a defect-free image is considered as the reference image which is acquired under the same environment as the image to be inspected. The singular vectors of each image to be inspected are replaced by the singular vectors of the reference image, and SVD is performed only once for the reference image off-line before detecting of the defects, thus greatly reducing the time required. The improved method is more conducive to real-time defect detection. Experimental results confirm its validity.

Color image segmentation to detect defects on fresh ham

NASA Astrophysics Data System (ADS)

Marty-Mahe, Pascale; Loisel, Philippe; Brossard, Didier

2003-04-01

We present in this paper the color segmentation methods that were used to detect appearance defects on 3 dimensional shape of fresh ham. The use of color histograms turned out to be an efficient solution to characterize the healthy skin, but a special care must be taken to choose the color components because of the 3 dimensional shape of ham.

[The monorail system--bone segment transport over unreamed interlocking nails].

PubMed

Oedekoven, G; Jansen, D; Raschke, M; Claudi, B F

1996-11-01

A treatment protocol is demonstrated, consisting of an osteotomy, either proximal or distal, of the bone defect with subsequent segmental transport via an anteromedially (tibia) or laterally (femur) mounted AO external fixation over an unreamed interlocking nail (monorail system). Twenty patients were treated by this method with indications as follows: 13 had a segmental bone defect of the tibia, 3 of the femur. Three patients showed post-traumatic and postinfectious leg-length discrepancies and one was treated for hypertrophic non-union of the femur. Defect distance varied between 5 and 18.5 cm and average time for transport was 19,42 days/ cm for the tibial shaft, 15,93 days/cm for the femur. Two patients developed deep infection, which required change of treatment, removing the monorail system and application of an Ilizarov apparatus. Despite complications using the monorail system, all patients healed and no amputations were required. The monorail system can be used as an alternative to the Ilizarov method under certain criteria of patient selection; these criteria are shown by an algorithm for segmental bone defects without infection, respecting the soft-tissue status with or without neurovascular compromise.

Combination of BMP-2-releasing gelatin/β-TCP sponges with autologous bone marrow for bone regeneration of X-ray-irradiated rabbit ulnar defects.

PubMed

Yamamoto, Masaya; Hokugo, Akishige; Takahashi, Yoshitake; Nakano, Takayoshi; Hiraoka, Masahiro; Tabata, Yasuhiko

2015-07-01

The objective of this study is to evaluate the feasibility of gelatin sponges incorporating β-tricalcium phosphate (β-TCP) granules (gelatin/β-TCP sponges) to enhance bone regeneration at a segmental ulnar defect of rabbits with X-ray irradiation. After X-ray irradiation of the ulnar bone, segmental critical-sized defects of 20-mm length were created, and bone morphogenetic protein-2 (BMP-2)-releasing gelatin/β-TCP sponges with or without autologous bone marrow were applied to the defects to evaluate bone regeneration. Both gelatin/β-TCP sponges containing autologous bone marrow and BMP-2-releasing sponges enhanced bone regeneration at the ulna defect to a significantly greater extent than the empty sponges (control). However, in the X-ray-irradiated bone, the bone regeneration either by autologous bone marrow or BMP-2 was inhibited. When combined with autologous bone marrow, the BMP-2 exhibited significantly high osteoinductivity, irrespective of the X-ray irradiation. The bone mineral content at the ulna defect was similar to that of the intact bone. It is concluded that the combination of bone marrow with the BMP-2-releasing gelatin/β-TCP sponge is a promising technique to induce bone regeneration at segmental bone defects after X-ray irradiation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Reconstruction of irradiated bone segmental defects with a biomaterial associating MBCP+(R), microstructured collagen membrane and total bone marrow grafting: an experimental study in rabbits.

PubMed

Jégoux, Franck; Goyenvalle, Eric; Cognet, Ronan; Malard, Olivier; Moreau, Francoise; Daculsi, Guy; Aguado, Eric

2009-12-15

The bone tissue engineering models used today are still a long way from any oncologic application as immediate postimplantation irradiation would decrease their osteoinductive potential. The aim of this study was to reconstruct a segmental critical size defect in a weight-bearing bone irradiated after implantation. Six white New Zealand rabbits were immediately implanted with a biomaterial associating resorbable collagen membrane EZ(R) filled and micro-macroporous biphasic calcium phosphate granules (MBCP+(R)). After a daily schedule of radiation delivery, and within 4 weeks, a total autologous bone marrow (BM) graft was injected percutaneously into the center of the implant. All the animals were sacrificed at 16 weeks. Successful osseous colonization was found to have bridged the entire length of the defects. Identical distribution of bone ingrowth and residual ceramics at the different levels of the implant suggests that the BM graft plays an osteoinductive role in the center of the defect. Periosteum-like formation was observed at the periphery, with the collagen membrane most likely playing a role. This model succeeded in bridging a large segmental defect in weight-bearing bone with immediate postimplantation fractionated radiation delivery. This has significant implications for the bone tissue engineering approach to patients with cancer-related bone defects.

System and process for detecting and monitoring surface defects

NASA Technical Reports Server (NTRS)

Mueller, Mark K. (Inventor)

1994-01-01

A system and process for detecting and monitoring defects in large surfaces such as the field joints of the container segments of a space shuttle booster motor. Beams of semi-collimated light from three non-parallel fiber optic light panels are directed at a region of the surface at non-normal angles of expected incidence. A video camera gathers some portion of the light that is reflected at an angle other than the angle of expected reflectance, and generates signals which are analyzed to discern defects in the surface. The analysis may be performed by visual inspection of an image on a video monitor, or by inspection of filtered or otherwise processed images. In one alternative embodiment, successive predetermined regions of the surface are aligned with the light source before illumination, thereby permitting efficient detection of defects in a large surface. Such alignment is performed by using a line scan gauge to sense the light which passes through an aperture in the surface. In another embodiment a digital map of the surface is created, thereby permitting the maintenance of records detailing changes in the location or size of defects as the container segment is refurbished and re-used. The defect detection apparatus may also be advantageously mounted on a fixture which engages the edge of a container segment.

Mechanical evaluation of anastomotic tension and patency in arteries.

PubMed

Zhang, F; Lineaweaver, W C; Buntic, R; Walker, R

1996-02-01

This study quantified arterial anastomotic tension, evaluated subsequent patency rates, and examined the degree of tension reduction with vessel mobilization. The study was divided into two components. In part I, a mechanical analysis was undertaken to evaluate tension, based on the determination of the force required to deflect a cable (vessel) laterally, and its resulting lateral displacement. Six Sprague-Dawley rats with 12 femoral arteries were divided into two subgroups: 1) no mobilization; and 2) axial mobilization by ligation and transection of superficial epigastric and gracilis muscular branches. The tension of femoral arterial anastomoses was calculated in vessels with no segmental defect and with 1.5-, 3-, 4.5-, 6-, and 7.5-mm defects. In part II, patency was evaluated. Fifty-five rats with 110 femoral arteries were divided into two sub-groups as defined in part I: 1) no mobilization; and 2) axial mobilization by ligation and transection of superficial epigastric and gracilis muscular branches. Microvascular anastomoses were performed with no segmental defect and with 1-, 2-, 3-, 4-, 5-, 6-, 7-, 8-, 9-, and 10-mm segmental vessel defects. Patency was evaluated 24 hr postoperatively. Part I of the study revealed that anastomotic tension gradually increased along with an increase in the length of the vessel defect, from 1.9 to 11.34 g in the no-mobilization group and from 1.97 to 8.44 g in the axial-mobilization group. Comparison of tension linear regression coefficient showed a significant difference between the two groups (p < 0.05). In part II of the study, the maximum length of femoral artery defects still able to maintain 100 percent patency of anastomoses was 4 mm (tension approximately 6 g) in the no-mobilization group and 6 mm in the axial-mobilization group (tension approximately 6.48 g). Microanastomotic tension was related to the size of the vessel defect, with increasing tension leading to thrombosis. Axial mobilization significantly reduced the tension in vessels with segmental defects and decreased thrombosis rates.

Segmentation of the pectoral muscle in breast MR images using structure tensor and deformable model

NASA Astrophysics Data System (ADS)

Lee, Myungeun; Kim, Jong Hyo

2012-02-01

Recently, breast MR images have been used in wider clinical area including diagnosis, treatment planning, and treatment response evaluation, which requests quantitative analysis and breast tissue segmentation. Although several methods have been proposed for segmenting MR images, segmenting out breast tissues robustly from surrounding structures in a wide range of anatomical diversity still remains challenging. Therefore, in this paper, we propose a practical and general-purpose approach for segmenting the pectoral muscle boundary based on the structure tensor and deformable model. The segmentation work flow comprises four key steps: preprocessing, detection of the region of interest (ROI) within the breast region, segmenting the pectoral muscle and finally extracting and refining the pectoral muscle boundary. From experimental results we show that the proposed method can segment the pectoral muscle robustly in diverse patient cases. In addition, the proposed method will allow the application of the quantification research for various breast images.

Bioactive borate glass promotes the repair of radius segmental bone defects by enhancing the osteogenic differentiation of BMSCs.

PubMed

Zhang, Jieyuan; Guan, Junjie; Zhang, Changqing; Wang, Hui; Huang, Wenhai; Guo, Shangchun; Niu, Xin; Xie, Zongping; Wang, Yang

2015-11-20

Bioactive borate glass (BG) has emerged as a promising alternative for bone regeneration due to its high osteoinductivity, osteoconductivity, compressive strength, and biocompatibility. However, the role of BG in large segmental bone repair is unclear and little is known about the underlying mechanism of BG's osteoinductivity. In this study, we demonstrated that BG possessed pro-osteogenic effects in an experimental model of critical-sized radius defects. Transplanting BG to radius defects resulted in better repair of bone defects as compared to widely used β-TCP. Histological and morphological analysis indicated that BG significantly enhanced new bone formation. Furthermore, the degradation rate of the BG was faster than that of β-TCP, which matched the higher bone regeneration rate. In addition, ions from BG enhanced cell viability, ALP activity, and osteogenic-related genes expression. Mechanistically, the critical genes Smad1/5 and Dlx5 in the BMP pathway and p-Smad1/5 proteins were significantly elevated after BG transplantation, and these effects could be blocked by the BMP/Smad specific inhibitor. Taken together, our findings suggest that BG could repair large segmental bone defects through activating the BMP/Smad pathway and osteogenic differentiation in BMSCs.

Tissue Probability Map Constrained 4-D Clustering Algorithm for Increased Accuracy and Robustness in Serial MR Brain Image Segmentation

PubMed Central

Xue, Zhong; Shen, Dinggang; Li, Hai; Wong, Stephen

2010-01-01

The traditional fuzzy clustering algorithm and its extensions have been successfully applied in medical image segmentation. However, because of the variability of tissues and anatomical structures, the clustering results might be biased by the tissue population and intensity differences. For example, clustering-based algorithms tend to over-segment white matter tissues of MR brain images. To solve this problem, we introduce a tissue probability map constrained clustering algorithm and apply it to serial MR brain image segmentation, i.e., a series of 3-D MR brain images of the same subject at different time points. Using the new serial image segmentation algorithm in the framework of the CLASSIC framework, which iteratively segments the images and estimates the longitudinal deformations, we improved both accuracy and robustness for serial image computing, and at the mean time produced longitudinally consistent segmentation and stable measures. In the algorithm, the tissue probability maps consist of both the population-based and subject-specific segmentation priors. Experimental study using both simulated longitudinal MR brain data and the Alzheimer’s Disease Neuroimaging Initiative (ADNI) data confirmed that using both priors more accurate and robust segmentation results can be obtained. The proposed algorithm can be applied in longitudinal follow up studies of MR brain imaging with subtle morphological changes for neurological disorders. PMID:26566399

Software for roof defects recognition on aerial photographs

NASA Astrophysics Data System (ADS)

Yudin, D.; Naumov, A.; Dolzhenko, A.; Patrakova, E.

2018-05-01

The article presents information on software for roof defects recognition on aerial photographs, made with air drones. An areal image segmentation mechanism is described. It allows detecting roof defects – unsmoothness that causes water stagnation after rain. It is shown that HSV-transformation approach allows quick detection of stagnation areas, their size and perimeters, but is sensitive to shadows and changes of the roofing-types. Deep Fully Convolutional Network software solution eliminates this drawback. The tested data set consists of the roofing photos with defects and binary masks for them. FCN approach gave acceptable results of image segmentation in Dice metric average value. This software can be used in inspection automation of roof conditions in the production sector and housing and utilities infrastructure.

Emergence and robustness of target waves in a neuronal network

NASA Astrophysics Data System (ADS)

Xu, Ying; Jin, Wuyin; Ma, Jun

2015-08-01

Target waves in excitable media such as neuronal network can regulate the spatial distribution and orderliness as a continuous pacemaker. Three different schemes are used to develop stable target wave in the network, and the potential mechanism for emergence of target waves in the excitable media is investigated. For example, a local pacing driven by external periodical forcing can generate stable target wave in the excitable media, furthermore, heterogeneity and local feedback under self-feedback coupling are also effective to generate continuous target wave as well. To discern the difference of these target waves, a statistical synchronization factor is defined by using mean field theory and artificial defects are introduced into the network to block the target wave, thus the robustness of these target waves could be detected. However, these target waves developed from the above mentioned schemes show different robustness to the blocking from artificial defects. A regular network of Hindmarsh-Rose neurons is designed in a two-dimensional square array, target waves are induced by using three different ways, and then some artificial defects, which are associated with anatomical defects, are set in the network to detect the effect of defects blocking on the travelling waves. It confirms that the robustness of target waves to defects blocking depends on the intrinsic properties (ways to generate target wave) of target waves.

Deformable templates guided discriminative models for robust 3D brain MRI segmentation.

PubMed

Liu, Cheng-Yi; Iglesias, Juan Eugenio; Tu, Zhuowen

2013-10-01

Automatically segmenting anatomical structures from 3D brain MRI images is an important task in neuroimaging. One major challenge is to design and learn effective image models accounting for the large variability in anatomy and data acquisition protocols. A deformable template is a type of generative model that attempts to explicitly match an input image with a template (atlas), and thus, they are robust against global intensity changes. On the other hand, discriminative models combine local image features to capture complex image patterns. In this paper, we propose a robust brain image segmentation algorithm that fuses together deformable templates and informative features. It takes advantage of the adaptation capability of the generative model and the classification power of the discriminative models. The proposed algorithm achieves both robustness and efficiency, and can be used to segment brain MRI images with large anatomical variations. We perform an extensive experimental study on four datasets of T1-weighted brain MRI data from different sources (1,082 MRI scans in total) and observe consistent improvement over the state-of-the-art systems.

Washout of ⁸²Rb as a marker of impaired tissue integrity, obtained by list-mode cardiac PET/CT: relationship with perfusion/metabolism patterns of myocardial viability.

PubMed

Chien, David T; Bravo, Paco; Higuchi, Takahiro; Merrill, Jennifer; Bengel, Frank M

2011-08-01

Myocardial washout of the potassium analogue (82)Rb may indicate tissue impairment. Few studies have evaluated its usefulness for viability assessment, and controversial results were reported. We revisited this topic using list-mode positron emission tomography (PET)/CT. A total of 22 patients with chronic ischemic cardiomyopathy (ICM) and 11 control subjects with normal CT coronary angiogram were studied. Rest (82)Rb PET/CT studies were acquired in list mode and resampled to static, gated, and dynamic images. Using a 17-segment model, (82)Rb washout was determined by monoexponential fitting of myocardial time-activity curves. In ICM patients, (18)F-fluorodeoxyglucose (FDG) studies were obtained in the same session and segments were classified as normally perfused, mismatch, or matched defect. (82)Rb washout was minimal and homogeneous in control subjects. Normally perfused segments of ICM did not differ (p = 0.33). ICM patients had a left ventricular ejection fraction (LVEF) of 25 ± 12%, 25/353 mismatched, and 46/353 matched defect segments. (82)Rb washout was higher in hypoperfused vs normal segments (p < 0.05), but not different between mismatch and matched defect (p = 0.18). Intraindividual analysis in nine patients showing both FDG mismatch and matched defect confirmed absence of differences. Overall, segmental (82)Rb washout correlated inversely with (82)Rb uptake (r = -0.70; p < 0.05) and less well with FDG uptake (r = -0.31; p < 0.05). Using state-of-the-art PET/CT technology for myocardial viability assessment, (82)Rb washout does not distinguish between perfusion/metabolism patterns of hibernating myocardium and scar. Tissue integrity may be at least partially impaired in hibernation.

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.

Repair of Segmental Bone Defect Using Totally Vitalized Tissue Engineered Bone Graft by a Combined Perfusion Seeding and Culture System

PubMed Central

Feng, Ya-Fei; Li, Xiang; Hu, Yun-Yu; Wang, Zhen; Ma, Zhen-Sheng; Lei, Wei

2014-01-01

Background The basic strategy to construct tissue engineered bone graft (TEBG) is to combine osteoblastic cells with three dimensional (3D) scaffold. Based on this strategy, we proposed the “Totally Vitalized TEBG” (TV-TEBG) which was characterized by abundant and homogenously distributed cells with enhanced cell proliferation and differentiation and further investigated its biological performance in repairing segmental bone defect. Methods In this study, we constructed the TV-TEBG with the combination of customized flow perfusion seeding/culture system and β-tricalcium phosphate (β-TCP) scaffold fabricated by Rapid Prototyping (RP) technique. We systemically compared three kinds of TEBG constructed by perfusion seeding and perfusion culture (PSPC) method, static seeding and perfusion culture (SSPC) method, and static seeding and static culture (SSSC) method for their in vitro performance and bone defect healing efficacy with a rabbit model. Results Our study has demonstrated that TEBG constructed by PSPC method exhibited better biological properties with higher daily D-glucose consumption, increased cell proliferation and differentiation, and better cell distribution, indicating the successful construction of TV-TEBG. After implanted into rabbit radius defects for 12 weeks, PSPC group exerted higher X-ray score close to autograft, much greater mechanical property evidenced by the biomechanical testing and significantly higher new bone formation as shown by histological analysis compared with the other two groups, and eventually obtained favorable healing efficacy of the segmental bone defect that was the closest to autograft transplantation. Conclusion This study demonstrated the feasibility of TV-TEBG construction with combination of perfusion seeding, perfusion culture and RP technique which exerted excellent biological properties. The application of TV-TEBG may become a preferred candidate for segmental bone defect repair in orthopedic and maxillofacial fields. PMID:24728277

Automated pulmonary lobar ventilation measurements using volume-matched thoracic CT and MRI

NASA Astrophysics Data System (ADS)

Guo, F.; Svenningsen, S.; Bluemke, E.; Rajchl, M.; Yuan, J.; Fenster, A.; Parraga, G.

2015-03-01

Objectives: To develop and evaluate an automated registration and segmentation pipeline for regional lobar pulmonary structure-function measurements, using volume-matched thoracic CT and MRI in order to guide therapy. Methods: Ten subjects underwent pulmonary function tests and volume-matched 1H and 3He MRI and thoracic CT during a single 2-hr visit. CT was registered to 1H MRI using an affine method that incorporated block-matching and this was followed by a deformable step using free-form deformation. The resultant deformation field was used to deform the associated CT lobe mask that was generated using commercial software. 3He-1H image registration used the same two-step registration method and 3He ventilation was segmented using hierarchical k-means clustering. Whole lung and lobar 3He ventilation and ventilation defect percent (VDP) were generated by mapping ventilation defects to CT-defined whole lung and lobe volumes. Target CT-3He registration accuracy was evaluated using region- , surface distance- and volume-based metrics. Automated whole lung and lobar VDP was compared with semi-automated and manual results using paired t-tests. Results: The proposed pipeline yielded regional spatial agreement of 88.0+/-0.9% and surface distance error of 3.9+/-0.5 mm. Automated and manual whole lung and lobar ventilation and VDP were not significantly different and they were significantly correlated (r = 0.77, p < 0.0001). Conclusion: The proposed automated pipeline can be used to generate regional pulmonary structural-functional maps with high accuracy and robustness, providing an important tool for image-guided pulmonary interventions.

Multiclass feature selection for improved pediatric brain tumor segmentation

NASA Astrophysics Data System (ADS)

Ahmed, Shaheen; Iftekharuddin, Khan M.

2012-03-01

In our previous work, we showed that fractal-based texture features are effective in detection, segmentation and classification of posterior-fossa (PF) pediatric brain tumor in multimodality MRI. We exploited an information theoretic approach such as Kullback-Leibler Divergence (KLD) for feature selection and ranking different texture features. We further incorporated the feature selection technique with segmentation method such as Expectation Maximization (EM) for segmentation of tumor T and non tumor (NT) tissues. In this work, we extend the two class KLD technique to multiclass for effectively selecting the best features for brain tumor (T), cyst (C) and non tumor (NT). We further obtain segmentation robustness for each tissue types by computing Bay's posterior probabilities and corresponding number of pixels for each tissue segments in MRI patient images. We evaluate improved tumor segmentation robustness using different similarity metric for 5 patients in T1, T2 and FLAIR modalities.

Robust tissue-air volume segmentation of MR images based on the statistics of phase and magnitude: Its applications in the display of susceptibility-weighted imaging of the brain.

PubMed

Du, Yiping P; Jin, Zhaoyang

2009-10-01

To develop a robust algorithm for tissue-air segmentation in magnetic resonance imaging (MRI) using the statistics of phase and magnitude of the images. A multivariate measure based on the statistics of phase and magnitude was constructed for tissue-air volume segmentation. The standard deviation of first-order phase difference and the standard deviation of magnitude were calculated in a 3 x 3 x 3 kernel in the image domain. To improve differentiation accuracy, the uniformity of phase distribution in the kernel was also calculated and linear background phase introduced by field inhomogeneity was corrected. The effectiveness of the proposed volume segmentation technique was compared to a conventional approach that uses the magnitude data alone. The proposed algorithm was shown to be more effective and robust in volume segmentation in both synthetic phantom and susceptibility-weighted images of human brain. Using our proposed volume segmentation method, veins in the peripheral regions of the brain were well depicted in the minimum-intensity projection of the susceptibility-weighted images. Using the additional statistics of phase, tissue-air volume segmentation can be substantially improved compared to that using the statistics of magnitude data alone. (c) 2009 Wiley-Liss, Inc.

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.

Patterns of pulmonary perfusion scans in normal subjects

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

Wallace, J.M.; Moser, K.M.; Hartman, M.T.

1981-01-01

A vital factor conditioning the usage of the pulmonary perfusion (Q) scan in the evaluation of patients suspected of pulmonary embolism is the prevalence of abnormal Q scans in subjects free of cardiopulmonary disease. Because this prevalence has not been well defined, we performed Q scans in 80 nonsmoking subjects 18 to 29 yr of age having no known active cardiopulmonary disease. Each subject underwent a history, physical examination, electrocardiogram, spirometry, and PA chest roentgenogram, followed by a 6-view Q scan. Two subjects in whom a Q defect was suspected underwent a /sup 133/Xe equilibrium-washout ventilation (V) scan. All Qmore » scans were interpreted blindly and independently by 2 experienced readers. Seventy-nine of the 80 Q scans were read as normal. No subject demonstrated a lobar or segmental defect. One of the 80 subjects, who had a mild pectus excavatum, had a left upper lobe subsegmental defect, which was not seen on the V scan. Based on the statistical analysis of these data, no more than 3.68% of normal nonsmoking persons in this age group may have a lobar or segmental Q scan defect and no more than 6.77% may have a subsegmental defect (with 95% confidence). Therefore, our study indicated that Q scan defects, particularly lobar or segmental, are rarely present among normal nonsmokers in this age group.« less

Internal bone transport using a cannulated screw as a mounting device in the treatment of a post-infective ulnar defect.

PubMed

Tsitskaris, Konstantinos; Havard, Heledd; Bijlsma, Paulien; Hill, Robert A

2016-04-01

Bone transport techniques can be used to address the segmental bone loss occurring after debridement for infection. Secure fixation of the bone transport construct to the bone transport segment can be challenging, particularly if the bone is small and osteopenic. We report a case of a segmental ulnar bone defect in a young child treated with internal bone transport using a cannulated screw as the mounting device. We found this technique particularly useful in the treatment of bone loss secondary to infection, where previous treatment and prolonged immobilisation had led to osteopenia. This technique has not been previously reported.

Seed robustness of oriented relative fuzzy connectedness: core computation and its applications

NASA Astrophysics Data System (ADS)

Tavares, Anderson C. M.; Bejar, Hans H. C.; Miranda, Paulo A. V.

2017-02-01

In this work, we present a formal definition and an efficient algorithm to compute the cores of Oriented Relative Fuzzy Connectedness (ORFC), a recent seed-based segmentation technique. The core is a region where the seed can be moved without altering the segmentation, an important aspect for robust techniques and reduction of user effort. We show how ORFC cores can be used to build a powerful hybrid image segmentation approach. We also provide some new theoretical relations between ORFC and Oriented Image Foresting Transform (OIFT), as well as their cores. Experimental results among several methods show that the hybrid approach conserves high accuracy, avoids the shrinking problem and provides robustness to seed placement inside the desired object due to the cores properties.

Association of ST segment depression >5 min after exercise testing with severity of coronary artery disease.

PubMed

Shaikh, Ayaz Hussain; Hanif, Bashir; Siddiqui, Adeel M; Shahab, Hunaina; Qazi, Hammad Ali; Mujtaba, Iqbal

2010-04-01

To determine the association of prolonged ST segment depression after an exercise test with severity of coronary artery disease. A cross sectional study of 100 consecutive patients referred to the cardiology laboratory for stress myocardial perfusion imaging (MPI) conducted between April-August 2008. All selected patients were monitored until their ST segment depression was recovered to baseline. ST segment recovery time was categorized into less and more than 5 minutes. Subsequent gated SPECT-MPI was performed and stratified according to severity of perfusion defect. Association was determined between post exercise ST segment depression recovery time (<5 minutes and >5 minutes) and severity of perfusion defect on MPI. The mean age of the patients was 57.12 +/- 9.0 years. The results showed statistically insignificant association (p > 0.05) between ST segment recovery time of <5 minutes and >5 minutes with low, intermediate or high risk MPI. Our findings suggest that the commonly used cut-off levels used in literature for prolonged, post exercise ST segment depression (>5 minutes into recovery phase) does not correlate with severity of ischaemia based on MPI results.

A Novel Machine Vision System for the Inspection of Micro-Spray Nozzle

PubMed Central

Huang, Kuo-Yi; Ye, Yu-Ting

2015-01-01

In this study, we present an application of neural network and image processing techniques for detecting the defects of an internal micro-spray nozzle. The defect regions were segmented by Canny edge detection, a randomized algorithm for detecting circles and a circle inspection (CI) algorithm. The gray level co-occurrence matrix (GLCM) was further used to evaluate the texture features of the segmented region. These texture features (contrast, entropy, energy), color features (mean and variance of gray level) and geometric features (distance variance, mean diameter and diameter ratio) were used in the classification procedures. A back-propagation neural network classifier was employed to detect the defects of micro-spray nozzles. The methodology presented herein effectively works for detecting micro-spray nozzle defects to an accuracy of 90.71%. PMID:26131678

A Novel Machine Vision System for the Inspection of Micro-Spray Nozzle.

PubMed

Huang, Kuo-Yi; Ye, Yu-Ting

2015-06-29

In this study, we present an application of neural network and image processing techniques for detecting the defects of an internal micro-spray nozzle. The defect regions were segmented by Canny edge detection, a randomized algorithm for detecting circles and a circle inspection (CI) algorithm. The gray level co-occurrence matrix (GLCM) was further used to evaluate the texture features of the segmented region. These texture features (contrast, entropy, energy), color features (mean and variance of gray level) and geometric features (distance variance, mean diameter and diameter ratio) were used in the classification procedures. A back-propagation neural network classifier was employed to detect the defects of micro-spray nozzles. The methodology presented herein effectively works for detecting micro-spray nozzle defects to an accuracy of 90.71%.

Segmental Bone Regeneration Using a Load Bearing Biodegradable Carrier of Bone Morphogenetic Protein-2

PubMed Central

Chu, Tien-Min G.; Warden, Stuart J.; Turner, Charles H.; Stewart, Rena L.

2006-01-01

Segmental defect regeneration has been a clinical challenge. Current tissue engineering approach using porous biodegradable scaffolds to delivery osteogenic cells and growth factors demonstrated success in facilitating bone regeneration in these cases. However, due to the lack of mechanical property, the porous scaffolds were evaluated in non-load bearing area or were stabilized with stress-shielding devices (bone plate or external fixation). In this paper, we tested a scaffold that does not require a bone plate because it has sufficient biomechanical strength. The tube-shaped scaffolds were manufactured from poly(propylene) fumarate/tricalcium phosphate (PPF/TCP) composites. Dicalcium phosphate dehydrate (DCPD) were used as bone morphogenetic protein -2 (BMP-2) carrier. Twenty two scaffolds were implanted in 5 mm segmental defects in rat femurs stabilized with k-wire for 6 and 15 weeks with and without 10 μg of rhBMP-2. Bridging of the segmental defect was evaluated first radiographically and was confirmed by histology and micro- computer tomography (μ-CT) imaging. The scaffolds in the BMP group maintained the bone length throughout the duration of the study and allow for bridging. The scaffolds in the control group failed to induce bridging and collapsed at 15 weeks. Peripheral computed tomography (pQCT) showed that BMP-2 does not increase the bone mineral density in the callus. Finally, the scaffold in BMP group was found to restore the mechanical property of the rat femur after 15 weeks. Our results demonstrated that the load-bearing BMP-2 scaffold can maintain bone length and allow successfully regeneration in segmental defects. PMID:16996588

Testosterone Delivered with a Scaffold Is as Effective as Bone Morphologic Protein-2 in Promoting the Repair of Critical-Size Segmental Defect of Femoral Bone in Mice

PubMed Central

Cheng, Bi-Hua; Chu, Tien-Min G.; Chang, Chawnshang; Kang, Hong-Yo; Huang, Ko-En

2013-01-01

Loss of large bone segments due to fracture resulting from trauma or tumor removal is a common clinical problem. The goal of this study was to evaluate the use of scaffolds containing testosterone, bone morphogenetic protein-2 (BMP-2), or a combination of both for treatment of critical-size segmental bone defects in mice. A 2.5-mm wide osteotomy was created on the left femur of wildtype and androgen receptor knockout (ARKO) mice. Testosterone, BMP-2, or both were delivered locally using a scaffold that bridged the fracture. Results of X-ray imaging showed that in both wildtype and ARKO mice, BMP-2 treatment induced callus formation within 14 days after initiation of the treatment. Testosterone treatment also induced callus formation within 14 days in wildtype but not in ARKO mice. Micro-computed tomography and histological examinations revealed that testosterone treatment caused similar degrees of callus formation as BMP-2 treatment in wildtype mice, but had no such effect in ARKO mice, suggesting that the androgen receptor is required for testosterone to initiate fracture healing. These results demonstrate that testosterone is as effective as BMP-2 in promoting the healing of critical-size segmental defects and that combination therapy with testosterone and BMP-2 is superior to single therapy. Results of this study may provide a foundation to develop a cost effective and efficient therapeutic modality for treatment of bone fractures with segmental defects. PMID:23940550

Left ventricular rotation and torsion in patients with perimembranous ventricular septal defect.

PubMed

Zhuang, Yan; Yong, Yong-hong; Yao, Jing; Ji, Ling; Xu, Di

2014-03-01

Assessment of left ventricular (LV) rotation has become an important approach for quantifying LV function. In this study, we sought to analyze LV rotation and twist using speckle tracking imaging (STI) in adult patients with isolated ventricular septal defects. Using STI, the peak rotation and time to peak rotation of 6 segments in basal and apical short-axis were measured, respectively, in 32 patients with ventricular septal defect and 30 healthy subjects as controls. The global rotation of the 6 segments in basal and apical and LV twist versus time profile were drawn, the peak rotation and twist of LV were calculated. All the time to peak rotation/twist were expressed as a percentage of end-systole (end-systole = 100%). Left ventricular ejection fraction was measured by biplane Simpson method. In patients group, the peak rotation of posterior, inferior, and postsept wall in basal was higher(P ≤ 0.05) and LV twist was also higher (P ≤ 0.05) than healthy controls. There were no significant differences between 2 groups in the peak rotation of the other 9 segments and left ventricular ejection fraction. Different from the control group, the time to peak rotation of the 6 segments in basal were delayed and the global rotation of the base was delayed (P ≤ 0.05) in ventricular septal defect group. Left ventricular volume overload due to ventricular septal defect has significant effect on LV rotation and twist, and LV rotation and twist may be a new index predicting LV systolic function. © 2013, Wiley Periodicals, Inc.

Preliminary evaluation of a load-bearing BMP-2 carrier for segmental defect regeneration.

PubMed

Chu, Tien-Min G; Sargent, Peter; Warden, Stuart J; Turner, Charles H; Stewart, Rena L

2006-01-01

Large segmental defects in bones can result from tumor removal, massive trauma, congenital malformation, or non-union fractures. Such defects often are difficult to manage and require multiple-phase surgery to achieve adequate union and function. In this study, we propose a novel design of bone morphogenetic protein 2 (BMP-2) carrier for tissue engineering of segmental defect regeneration. The tube-shaped BMP-2 carrier was fabrication from a poly(propylene fumarate)/tricalcium phosphate (PPF/TCP) composite via casting technique developed in our laboratory. An in vitro evaluation showed that the compressive strength of the carrier decreased about 48% in 12 weeks while maintained a pH in the 6.8-7.4 range. In vivo study was conducted by implanting carriers loaded with 10 microg of BMP-2 in 5 mm rat femur gap model for 15 weeks. X-ray evidence of bridging was first found in the BMP group at 3 weeks. Bridging in all animals (N = 4) in the BMP group was found at 9 weeks. No x-ray evidence of bridging was found in the No BMP group (N = 3). pQCT analysis indicated that the bone mineral density of the callus in the BMP group has reached the level of native femur at 15 weeks after implantation, while the callus in the No BMP group has a bone mineral density at a lower level of 84% to the native femur. Histology analysis shows that a normal fatty bone marrow was restored and mineralized callus formed and bridged the segmental defect.

Simultaneous macula detection and optic disc boundary segmentation in retinal fundus images

NASA Astrophysics Data System (ADS)

Girard, Fantin; Kavalec, Conrad; Grenier, Sébastien; Ben Tahar, Houssem; Cheriet, Farida

2016-03-01

The optic disc (OD) and the macula are important structures in automatic diagnosis of most retinal diseases inducing vision defects such as glaucoma, diabetic or hypertensive retinopathy and age-related macular degeneration. We propose a new method to detect simultaneously the macula and the OD boundary. First, the color fundus images are processed to compute several maps highlighting the different anatomical structures such as vessels, the macula and the OD. Then, macula candidates and OD candidates are found simultaneously and independently using seed detectors identified on the corresponding maps. After selecting a set of macula/OD pairs, the top candidates are sent to the OD segmentation method. The segmentation method is based on local K-means applied to color coordinates in polar space followed by a polynomial fitting regularization step. Pair scores are updated, resulting in the final best macula/OD pair. The method was evaluated on two public image databases: ONHSD and MESSIDOR. The results show an overlapping area of 0.84 on ONHSD and 0.90 on MESSIDOR, which is better than recent state of the art methods. Our segmentation method is robust to contrast and illumination problems and outputs the exact boundary of the OD, not just a circular or elliptical model. The macula detection has an accuracy of 94%, which again outperforms other macula detection methods. This shows that combining the OD and macula detections improves the overall accuracy. The computation time for the whole process is 6.4 seconds, which is faster than other methods in the literature.

Automated cell analysis tool for a genome-wide RNAi screen with support vector machine based supervised learning

NASA Astrophysics Data System (ADS)

Remmele, Steffen; Ritzerfeld, Julia; Nickel, Walter; Hesser, Jürgen

2011-03-01

RNAi-based high-throughput microscopy screens have become an important tool in biological sciences in order to decrypt mostly unknown biological functions of human genes. However, manual analysis is impossible for such screens since the amount of image data sets can often be in the hundred thousands. Reliable automated tools are thus required to analyse the fluorescence microscopy image data sets usually containing two or more reaction channels. The herein presented image analysis tool is designed to analyse an RNAi screen investigating the intracellular trafficking and targeting of acylated Src kinases. In this specific screen, a data set consists of three reaction channels and the investigated cells can appear in different phenotypes. The main issue of the image processing task is an automatic cell segmentation which has to be robust and accurate for all different phenotypes and a successive phenotype classification. The cell segmentation is done in two steps by segmenting the cell nuclei first and then using a classifier-enhanced region growing on basis of the cell nuclei to segment the cells. The classification of the cells is realized by a support vector machine which has to be trained manually using supervised learning. Furthermore, the tool is brightness invariant allowing different staining quality and it provides a quality control that copes with typical defects during preparation and acquisition. A first version of the tool has already been successfully applied for an RNAi-screen containing three hundred thousand image data sets and the SVM extended version is designed for additional screens.

Supramolecular luminescence from oligofluorenol-based supramolecular polymer semiconductors.

PubMed

Zhang, Guang-Wei; Wang, Long; Xie, Ling-Hai; Lin, Jin-Yi; Huang, Wei

2013-11-13

Supramolecular luminescence stems from non-covalent exciton behaviors of active π-segments in supramolecular entities or aggregates via intermolecular forces. Herein, a π-conjugated oligofluorenol, containing self-complementary double hydrogen bonds, was synthesized using Suzuki coupling as a supramolecular semiconductor. Terfluorenol-based random supramolecular polymers were confirmed via concentration-dependent nuclear magnetic resonance (NMR) and dynamic light scattering (DLS). The photoluminescent spectra of the TFOH-1 solution exhibit a green emission band (g-band) at approximately ~520 nm with reversible features, as confirmed through titration experiments. Supramolecular luminescence of TFOH-1 thin films serves as robust evidence for the aggregates of g-band. Our results suggest that the presence of polyfluorene ketone defects is a sufficient condition, rather than a sufficient-necessary condition for the g-band. Supramolecular electroluminescence will push organic devices into the fields of supramolecular optoelectronics, spintronics, and mechatronics.

High-speed potato grading and quality inspection based on a color vision system

NASA Astrophysics Data System (ADS)

Noordam, Jacco C.; Otten, Gerwoud W.; Timmermans, Toine J. M.; van Zwol, Bauke H.

2000-03-01

A high-speed machine vision system for the quality inspection and grading of potatoes has been developed. The vision system grades potatoes on size, shape and external defects such as greening, mechanical damages, rhizoctonia, silver scab, common scab, cracks and growth cracks. A 3-CCD line-scan camera inspects the potatoes in flight as they pass under the camera. The use of mirrors to obtain a 360-degree view of the potato and the lack of product holders guarantee a full view of the potato. To achieve the required capacity of 12 tons/hour, 11 SHARC Digital Signal Processors perform the image processing and classification tasks. The total capacity of the system is about 50 potatoes/sec. The color segmentation procedure uses Linear Discriminant Analysis (LDA) in combination with a Mahalanobis distance classifier to classify the pixels. The procedure for the detection of misshapen potatoes uses a Fourier based shape classification technique. Features such as area, eccentricity and central moments are used to discriminate between similar colored defects. Experiments with red and yellow skin-colored potatoes have shown that the system is robust and consistent in its classification.

Combination of Heel-strike like Mechanical Loading with Deproteinized Cancellous Bone Scaffold Implantation to Repair Segmental Bone Defects in Rabbits.

PubMed

Huang, Guofeng; Liu, Guojun; Zhang, Feng; Gao, Jianting; Wang, Jiangze; Chen, Qi; Wu, Benwen; Ding, Zhenqi; Cai, Taoyi

2017-01-01

Under physiological conditions bone defects often occur at mechanical load bearing sites and bone substitutes used for regeneration should be similarly subjected to mechanical loading stress. In this study, we investigated whether a novel heel-strike like mechanical loading method can be used as a complementary therapy to promote bone regeneration following bone substitute grafting. To test this, three groups of rabbits with segmental bone defects in the tibia were implanted with bovine deproteinized cancellous bone scaffold (DCBS), with one group also receiving heel-strike like mechanical loading generated by a rap stress stimulator. From weeks 4-12 post-operation X-ray and micro-CT scanning showed that rabbits receiving combination therapy had significantly more callus at the bone defect. Moreover, bone defects in the combination group were completely replaced with new bone at week 12, while the DCBS implantation alone group healed only partially and rabbits receiving neither DCBS nor mechanical loading developed only small calluses throughout the observation period. Analysis of micro-CT scanning results demonstrated that new bone density in the combination group was significantly higher than the DCBS only group at weeks 4 and 12 ( p <0.05). H&E staining results also indicated a significantly higher percentage of new bone in the bone defect area and a lower percentage of residual scaffold in the combination group compared to the DCBS only group ( p <0.05). Thus, this heel-strike like mechanical loading method appears to accelerate bone regeneration following substitute implantation by restoring a local mechanical loading environment in segmental bone defects.

Primary versus secondary achalasia: New signs on barium esophagogram

PubMed Central

Gupta, Pankaj; Debi, Uma; Sinha, Saroj Kant; Prasad, Kaushal Kishor

2015-01-01

Aim: To investigate new signs on barium swallow that can differentiate primary from secondary achalasia. Materials and Methods: Records of 30 patients with primary achalasia and 17 patients with secondary achalasia were reviewed. Clinical, endoscopic, and manometric data was recorded. Barium esophagograms were evaluated for peristalsis and morphology of distal esophageal segment (length, symmetry, nodularity, shouldering, filling defects, and “tram-track sign”). Results: Mean age at presentation was 39 years in primary achalasia and 49 years in secondary achalasia. The mean duration of symptoms was 3.5 years in primary achalasia and 3 months in secondary achalasia. False-negative endoscopic results were noted in the first instance in five patients. In the secondary achalasia group, five patients had distal esophageal segment morphology indistinguishable from that of primary achalasia. None of the patients with primary achalasia and 35% patients with secondary achalasia had a length of the distal segment approaching combined height of two vertebral bodies. None of the patients with secondary achalasia and 34% patients with primary achalasia had maximum caliber of esophagus approaching combined height of two vertebral bodies. Tertiary contractions were noted in 90% patients with primary achalasia and 24% patients with secondary achalasia. Tram-track sign was found in 55% patients with primary achalasia. Filling defects in the distal esophageal segment were noted in 94% patients with secondary achalasia. Conclusion: Length of distal esophageal segment, tertiary contractions, tram-track sign, and filling defects in distal esophageal segment are useful esophagographic features distinguishing primary from secondary achalasia. PMID:26288525

Robust and fast-converging level set method for side-scan sonar image segmentation

NASA Astrophysics Data System (ADS)

Liu, Yan; Li, Qingwu; Huo, Guanying

2017-11-01

A robust and fast-converging level set method is proposed for side-scan sonar (SSS) image segmentation. First, the noise in each sonar image is removed using the adaptive nonlinear complex diffusion filter. Second, k-means clustering is used to obtain the initial presegmentation image from the denoised image, and then the distance maps of the initial contours are reinitialized to guarantee the accuracy of the numerical calculation used in the level set evolution. Finally, the satisfactory segmentation is achieved using a robust variational level set model, where the evolution control parameters are generated by the presegmentation. The proposed method is successfully applied to both synthetic image with speckle noise and real SSS images. Experimental results show that the proposed method needs much less iteration and therefore is much faster than the fuzzy local information c-means clustering method, the level set method using a gamma observation model, and the enhanced region-scalable fitting method. Moreover, the proposed method can usually obtain more accurate segmentation results compared with other methods.

A cascade method for TFT-LCD defect detection

NASA Astrophysics Data System (ADS)

Yi, Songsong; Wu, Xiaojun; Yu, Zhiyang; Mo, Zhuoya

2017-07-01

In this paper, we propose a novel cascade detection algorithm which focuses on point and line defects on TFT-LCD. At the first step of the algorithm, we use the gray level difference of su-bimage to segment the abnormal area. The second step is based on phase only transform (POT) which corresponds to the Discrete Fourier Transform (DFT), normalized by the magnitude. It can remove regularities like texture and noise. After that, we improve the method of setting regions of interest (ROI) with the method of edge segmentation and polar transformation. The algorithm has outstanding performance in both computation speed and accuracy. It can solve most of the defect detections including dark point, light point, dark line, etc.

On a methodology for robust segmentation of nonideal iris images.

PubMed

Schmid, Natalia A; Zuo, Jinyu

2010-06-01

Iris biometric is one of the most reliable biometrics with respect to performance. However, this reliability is a function of the ideality of the data. One of the most important steps in processing nonideal data is reliable and precise segmentation of the iris pattern from remaining background. In this paper, a segmentation methodology that aims at compensating various nonidealities contained in iris images during segmentation is proposed. The virtue of this methodology lies in its capability to reliably segment nonideal imagery that is simultaneously affected with such factors as specular reflection, blur, lighting variation, occlusion, and off-angle images. We demonstrate the robustness of our segmentation methodology by evaluating ideal and nonideal data sets, namely, the Chinese Academy of Sciences iris data version 3 interval subdirectory, the iris challenge evaluation data, the West Virginia University (WVU) data, and the WVU off-angle data. Furthermore, we compare our performance to that of our implementation of Camus and Wildes's algorithm and Masek's algorithm. We demonstrate considerable improvement in segmentation performance over the formerly mentioned algorithms.

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

PubMed

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

2018-05-01

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

Automatic cardiac LV segmentation in MRI using modified graph cuts with smoothness and interslice constraints.

PubMed

Albà, Xènia; Figueras I Ventura, Rosa M; Lekadir, Karim; Tobon-Gomez, Catalina; Hoogendoorn, Corné; Frangi, Alejandro F

2014-12-01

Magnetic resonance imaging (MRI), specifically late-enhanced MRI, is the standard clinical imaging protocol to assess cardiac viability. Segmentation of myocardial walls is a prerequisite for this assessment. Automatic and robust multisequence segmentation is required to support processing massive quantities of data. A generic rule-based framework to automatically segment the left ventricle myocardium is presented here. We use intensity information, and include shape and interslice smoothness constraints, providing robustness to subject- and study-specific changes. Our automatic initialization considers the geometrical and appearance properties of the left ventricle, as well as interslice information. The segmentation algorithm uses a decoupled, modified graph cut approach with control points, providing a good balance between flexibility and robustness. The method was evaluated on late-enhanced MRI images from a 20-patient in-house database, and on cine-MRI images from a 15-patient open access database, both using as reference manually delineated contours. Segmentation agreement, measured using the Dice coefficient, was 0.81±0.05 and 0.92±0.04 for late-enhanced MRI and cine-MRI, respectively. The method was also compared favorably to a three-dimensional Active Shape Model approach. The experimental validation with two magnetic resonance sequences demonstrates increased accuracy and versatility. © 2013 Wiley Periodicals, Inc.

Reconstruction of segmental bone defect of long bones after tumor resection by devitalized tumor-bearing bone.

PubMed

Qu, Huayi; Guo, Wei; Yang, Rongli; Li, Dasen; Tang, Shun; Yang, Yi; Dong, Sen; Zang, Jie

2015-09-24

The reconstruction of an intercalary bone defect after a tumor resection of a long bone remains a challenge to orthopedic surgeons. Though several methods have been adopted to enhance the union of long segmental allografts or retrieved segmental autografts to the host bones, still more progresses are required to achieve a better union rate. Several methods have been adopted to devitalize tumor bone for recycling usage, and the results varied. We describe our experiences of using devitalized tumor-bearing bones for the repairing of segmental defects after tumor resection. Twenty-seven eligible patients treated from February 2004 to May 2012 were included. The segmental tumor bone (mean length, 14 cm) was resected, and then devitalized in 20% sterile saline at 65 °C for 30 min after the tumor tissue was removed. The devitalized bone was implanted back into the defect by using nails or plates. Complete healing of 50 osteotomy ends was achieved at a median time of 11 months (interquartile range (IQR) 9-13 months). Major complications included bone nonunion in four bone junctions (7.4%), devitalized bone fracture in one patient (3.7%), deep infection in three patients (11.1%), and fixation failure in two patients (7.4%). The bone union rates at 1 and 2 years were 74.1 and 92.6%, respectively. The average functional score according to the Musculoskeletal Tumor Society (MSTS) 93 scoring system was 93 % (IQR 80-96.7%). Incubation in 20% sterile saline at 65 °C for 30 min is an effective method of devitalization of tumor-bearing bone. The retrieved bone graft may provide as a less expensive alternative for limb salvage. The structural bone and the preserved osteoinductivity of protein may improve bone union.

Comparison of the sensitivity and specificity of 5 image sets of dual-energy computed tomography for detecting first-pass myocardial perfusion defects compared with positron emission tomography.

PubMed

Li, Wenhuan; Zhu, Xiaolian; Li, Jing; Peng, Cheng; Chen, Nan; Qi, Zhigang; Yang, Qi; Gao, Yan; Zhao, Yang; Sun, Kai; Li, Kuncheng

2014-12-01

The sensitivity and specificity of 5 different image sets of dual-energy computed tomography (DECT) for the detection of first-pass myocardial perfusion defects have not systematically been compared using positron emission tomography (PET) as a reference standard. Forty-nine consecutive patients, with known or strongly suspected of coronary artery disease, were prospectively enrolled in our study. Cardiac DECT was performed at rest state using a second-generation 128-slice dual-source CT. The DECT data were reconstructed to iodine maps, monoenergetic images, 100 kV images, nonlinearly blended images, and linearly blended images by different postprocessing techniques. The myocardial perfusion defects on DECT images were visually assessed by 5 observers, using standard 17-segment model. Diagnostic accuracy of 5 image sets was assessed using nitrogen-13 ammonia PET as the gold standard. Discrimination was quantified using the area under the receiver operating characteristic curve (AUC), and AUCs were compared using the method of DeLong. The DECT and PET examinations were successfully completed in 30 patients and a total of 90 territories and 510 segments were analyzed. Cardiac PET revealed myocardial perfusion defects in 56 territories (62%) and 209 segments (41%). The AUC of iodine maps, monoenergetic images, 100 kV images, nonlinearly blended images, and linearly blended images were 0.986, 0.934, 0.913, 0.881, and 0.871, respectively, on a per-territory basis. These values were 0.922, 0.813, 0.779, 0.763, and 0.728, respectively, on a per-segment basis. DECT iodine maps shows high sensitivity and specificity, and is superior to other DECT image sets for the detection of myocardial perfusion defects in the first-pass myocardial perfusion.

An improved segmentation method for defects inspection on steel roller surface

NASA Astrophysics Data System (ADS)

Xu, Jirui; Li, Xuekun; Cao, Yuzhong; Shi, Depeng; Yang, Jun; Jiang, Sheng; Rong, Yiming

2018-05-01

In the field of metal rolling, the quality of the steel roller's surface is significant for the final rolling products, e.g. metal sheets or foils. Besides the dimensional accuracy and surface roughness, the optical uniformity of the roller surface is also required for high quality rolling application. The typical optical defects of rollers after finish grinding include speckles, chatter marks, feed traces, and combination of all above. Unlike surface roughness, the optical defects can hardly be characterized by the topography or scanning electrical microscope measurement. Only the inspection by bared eyes of experienced engineers appears to be the effective manner for surface optical defects examination for large steel rollers. In this paper, an on-site machine vision system is designed to add on to the roller grinding machine to capture the surface image, and then an improved optical defects segmentation algorithm is developed based on the active contour model. Finally, experiments are carried out to verify the efficacy of the improved model.

Repair of segmental bone defects in the maxilla by transport disc distraction osteogenesis: Clinical experience with a new device

PubMed Central

Boonzaier, James; Vicatos, George; Hendricks, Rushdi

2015-01-01

The bones of the maxillary complex are vital for normal oro-nasal function and facial cosmetics. Maxillary tumor excision results in large defects that commonly include segments of the alveolar and palatine processes, compromising eating, speech and facial appearance. Unlike the conventional approach to maxillary defect repair by vascularized bone grafting, transport disc distraction osteogenesis (TDDO) stimulates new bone by separating the healing callus, and stimulates growth of surrounding soft tissues as well. Bone formed in this way closely mimics the parent bone in form and internal structure, producing a superior anatomical, functional and cosmetic result. Historically, TDDO has been successfully used to close small horizontal cleft defects in the maxilla, not exceeding 25 mm. Fujioka et al. reported in 2012 that “no bone transporter corresponding to the (large) size of the oro-antral fistula is marketed. The authors report the successful treatment of 4 cases involving alveolar defects of between 25 mm and 80 mm in length. PMID:26389041

Custom-made composite scaffolds for segmental defect repair in long bones.

PubMed

Reichert, Johannes C; Wullschleger, Martin E; Cipitria, Amaia; Lienau, Jasmin; Cheng, Tan K; Schütz, Michael A; Duda, Georg N; Nöth, Ulrich; Eulert, Jochen; Hutmacher, Dietmar W

2011-08-01

Current approaches for segmental bone defect reconstruction are restricted to autografts and allografts which possess osteoconductive, osteoinductive and osteogenic properties, but face significant disadvantages. The objective of this study was to compare the regenerative potential of scaffolds with different material composition but similar mechanical properties to autologous bone graft from the iliac crest in an ovine segmental defect model. After 12 weeks, in vivo specimens were analysed by X-ray imaging, torsion testing, micro-computed tomography and histology to assess amount, strength and structure of the newly formed bone. The highest amounts of bone neoformation with highest torsional moment values were observed in the autograft group and the lowest in the medical grade polycaprolactone and tricalcium phosphate composite group. The study results suggest that scaffolds based on aliphatic polyesters and ceramics, which are considered biologically inactive materials, induce only limited new bone formation but could be an equivalent alternative to autologous bone when combined with a biologically active stimulus such as bone morphogenetic proteins.

Reconstruction of goat femur segmental defects using triphasic ceramic-coated hydroxyapatite in combination with autologous cells and platelet-rich plasma.

PubMed

Nair, Manitha B; Varma, H K; Menon, K V; Shenoy, Sachin J; John, Annie

2009-06-01

Segmental bone defects resulting from trauma or pathology represent a common and significant clinical problem. In this study, a triphasic ceramic (calcium silicate, hydroxyapatite and tricalcium phosphate)-coated hydroxyapatite (HASi) having the benefits of both HA (osteointegration, osteoconduction) and silica (degradation) was used as a bone substitute for the repair of segmental defect (2 cm) created in a goat femur model. Three experimental goat femur implant groups--(a) bare HASi, (b) osteogenic-induced goat bone marrow-derived mesenchymal stem cells cultured HASi (HASi+C) and (c) osteogenic-induced goat bone marrow-derived mesenchymal stem cells cultured HASi+platelet-rich plasma (HASi+CP)--were designed and efficacy performance in the healing of the defect was evaluated. In all the groups, the material united with host bone without any inflammation and an osseous callus formed around the implant. This reflects the osteoconductivity of HASi where the cells have migrated from the cut ends of host bone. The most observable difference between the groups appeared in the mid region of the defect. In bare HASi groups, numerous osteoblast-like cells could be seen together with a portion of material. However, in HASi+C and HASi+CP, about 60-70% of that area was occupied by woven bone, in line with material degradation. The interconnected porous nature (50-500 microm), together with the chemical composition of the HASi, facilitated the degradation of HASi, thereby opening up void spaces for cellular ingrowth and bone regeneration. The combination of HASi with cells and PRP was an added advantage that could promote the expression of many osteoinductive proteins, leading to faster bone regeneration and material degradation. Based on these results, we conclude that bare HASi can aid in bone regeneration but, with the combination of cells and PRP, the sequence of healing events are much faster in large segmental bone defects in weight-bearing areas in goats.

Robust and accurate vectorization of line drawings.

PubMed

Hilaire, Xavier; Tombre, Karl

2006-06-01

This paper presents a method for vectorizing the graphical parts of paper-based line drawings. The method consists of separating the input binary image into layers of homogeneous thickness, skeletonizing each layer, segmenting the skeleton by a method based on random sampling, and simplifying the result. The segmentation method is robust with a best bound of 50 percent noise reached for indefinitely long primitives. Accurate estimation of the recognized vector's parameters is enabled by explicitly computing their feasibility domains. Theoretical performance analysis and expression of the complexity of the segmentation method are derived. Experimental results and comparisons with other vectorization systems are also provided.

Real-time segmentation of burst suppression patterns in critical care EEG monitoring

PubMed Central

Westover, M. Brandon; Shafi, Mouhsin M.; Ching, ShiNung; Chemali, Jessica J.; Purdon, Patrick L.; Cash, Sydney S.; Brown, Emery N.

2014-01-01

Objective Develop a real-time algorithm to automatically discriminate suppressions from non-suppressions (bursts) in electroencephalograms of critically ill adult patients. Methods A real-time method for segmenting adult ICU EEG data into bursts and suppressions is presented based on thresholding local voltage variance. Results are validated against manual segmentations by two experienced human electroencephalographers. We compare inter-rater agreement between manual EEG segmentations by experts with inter-rater agreement between human vs automatic segmentations, and investigate the robustness of segmentation quality to variations in algorithm parameter settings. We further compare the results of using these segmentations as input for calculating the burst suppression probability (BSP), a continuous measure of depth-of-suppression. Results Automated segmentation was comparable to manual segmentation, i.e. algorithm-vs-human agreement was comparable to human-vs-human agreement, as judged by comparing raw EEG segmentations or the derived BSP signals. Results were robust to modest variations in algorithm parameter settings. Conclusions Our automated method satisfactorily segments burst suppression data across a wide range adult ICU EEG patterns. Performance is comparable to or exceeds that of manual segmentation by human electroencephalographers. Significance Automated segmentation of burst suppression EEG patterns is an essential component of quantitative brain activity monitoring in critically ill and anesthetized adults. The segmentations produced by our algorithm provide a basis for accurate tracking of suppression depth. PMID:23891828

Real-time segmentation of burst suppression patterns in critical care EEG monitoring.

PubMed

Brandon Westover, M; Shafi, Mouhsin M; Ching, Shinung; Chemali, Jessica J; Purdon, Patrick L; Cash, Sydney S; Brown, Emery N

2013-09-30

Develop a real-time algorithm to automatically discriminate suppressions from non-suppressions (bursts) in electroencephalograms of critically ill adult patients. A real-time method for segmenting adult ICU EEG data into bursts and suppressions is presented based on thresholding local voltage variance. Results are validated against manual segmentations by two experienced human electroencephalographers. We compare inter-rater agreement between manual EEG segmentations by experts with inter-rater agreement between human vs automatic segmentations, and investigate the robustness of segmentation quality to variations in algorithm parameter settings. We further compare the results of using these segmentations as input for calculating the burst suppression probability (BSP), a continuous measure of depth-of-suppression. Automated segmentation was comparable to manual segmentation, i.e. algorithm-vs-human agreement was comparable to human-vs-human agreement, as judged by comparing raw EEG segmentations or the derived BSP signals. Results were robust to modest variations in algorithm parameter settings. Our automated method satisfactorily segments burst suppression data across a wide range adult ICU EEG patterns. Performance is comparable to or exceeds that of manual segmentation by human electroencephalographers. Automated segmentation of burst suppression EEG patterns is an essential component of quantitative brain activity monitoring in critically ill and anesthetized adults. The segmentations produced by our algorithm provide a basis for accurate tracking of suppression depth. Copyright © 2013 Elsevier B.V. All rights reserved.

Robust Machine Learning-Based Correction on Automatic Segmentation of the Cerebellum and Brainstem.

PubMed

Wang, Jun Yi; Ngo, Michael M; Hessl, David; Hagerman, Randi J; Rivera, Susan M

2016-01-01

Automated segmentation is a useful method for studying large brain structures such as the cerebellum and brainstem. However, automated segmentation may lead to inaccuracy and/or undesirable boundary. The goal of the present study was to investigate whether SegAdapter, a machine learning-based method, is useful for automatically correcting large segmentation errors and disagreement in anatomical definition. We further assessed the robustness of the method in handling size of training set, differences in head coil usage, and amount of brain atrophy. High resolution T1-weighted images were acquired from 30 healthy controls scanned with either an 8-channel or 32-channel head coil. Ten patients, who suffered from brain atrophy because of fragile X-associated tremor/ataxia syndrome, were scanned using the 32-channel head coil. The initial segmentations of the cerebellum and brainstem were generated automatically using Freesurfer. Subsequently, Freesurfer's segmentations were both manually corrected to serve as the gold standard and automatically corrected by SegAdapter. Using only 5 scans in the training set, spatial overlap with manual segmentation in Dice coefficient improved significantly from 0.956 (for Freesurfer segmentation) to 0.978 (for SegAdapter-corrected segmentation) for the cerebellum and from 0.821 to 0.954 for the brainstem. Reducing the training set size to 2 scans only decreased the Dice coefficient ≤0.002 for the cerebellum and ≤ 0.005 for the brainstem compared to the use of training set size of 5 scans in corrective learning. The method was also robust in handling differences between the training set and the test set in head coil usage and the amount of brain atrophy, which reduced spatial overlap only by <0.01. These results suggest that the combination of automated segmentation and corrective learning provides a valuable method for accurate and efficient segmentation of the cerebellum and brainstem, particularly in large-scale neuroimaging studies, and potentially for segmenting other neural regions as well.

Robust Machine Learning-Based Correction on Automatic Segmentation of the Cerebellum and Brainstem

PubMed Central

Wang, Jun Yi; Ngo, Michael M.; Hessl, David; Hagerman, Randi J.; Rivera, Susan M.

2016-01-01

Automated segmentation is a useful method for studying large brain structures such as the cerebellum and brainstem. However, automated segmentation may lead to inaccuracy and/or undesirable boundary. The goal of the present study was to investigate whether SegAdapter, a machine learning-based method, is useful for automatically correcting large segmentation errors and disagreement in anatomical definition. We further assessed the robustness of the method in handling size of training set, differences in head coil usage, and amount of brain atrophy. High resolution T1-weighted images were acquired from 30 healthy controls scanned with either an 8-channel or 32-channel head coil. Ten patients, who suffered from brain atrophy because of fragile X-associated tremor/ataxia syndrome, were scanned using the 32-channel head coil. The initial segmentations of the cerebellum and brainstem were generated automatically using Freesurfer. Subsequently, Freesurfer’s segmentations were both manually corrected to serve as the gold standard and automatically corrected by SegAdapter. Using only 5 scans in the training set, spatial overlap with manual segmentation in Dice coefficient improved significantly from 0.956 (for Freesurfer segmentation) to 0.978 (for SegAdapter-corrected segmentation) for the cerebellum and from 0.821 to 0.954 for the brainstem. Reducing the training set size to 2 scans only decreased the Dice coefficient ≤0.002 for the cerebellum and ≤ 0.005 for the brainstem compared to the use of training set size of 5 scans in corrective learning. The method was also robust in handling differences between the training set and the test set in head coil usage and the amount of brain atrophy, which reduced spatial overlap only by <0.01. These results suggest that the combination of automated segmentation and corrective learning provides a valuable method for accurate and efficient segmentation of the cerebellum and brainstem, particularly in large-scale neuroimaging studies, and potentially for segmenting other neural regions as well. PMID:27213683

BBSome function is required for both the morphogenesis and maintenance of the photoreceptor outer segment

PubMed Central

Hsu, Ying; Kim, Gunhee; Zhang, Qihong; Datta, Poppy; Seo, Seongjin

2017-01-01

Genetic mutations disrupting the structure and function of primary cilia cause various inherited retinal diseases in humans. Bardet-Biedl syndrome (BBS) is a genetically heterogeneous, pleiotropic ciliopathy characterized by retinal degeneration, obesity, postaxial polydactyly, intellectual disability, and genital and renal abnormalities. To gain insight into the mechanisms of retinal degeneration in BBS, we developed a congenital knockout mouse of Bbs8, as well as conditional mouse models in which function of the BBSome (a protein complex that mediates ciliary trafficking) can be temporally inactivated or restored. We demonstrate that BBS mutant mice have defects in retinal outer segment morphogenesis. We further demonstrate that removal of Bbs8 in adult mice affects photoreceptor function and disrupts the structural integrity of the outer segment. Notably, using a mouse model in which a gene trap inhibiting Bbs8 gene expression can be removed by an inducible FLP recombinase, we show that when BBS8 is restored in immature retinas with malformed outer segments, outer segment extension can resume normally and malformed outer segment discs are displaced distally by normal outer segment structures. Over time, the retinas of the rescued mice become morphologically and functionally normal, indicating that there is a window of plasticity when initial retinal outer segment morphogenesis defects can be ameliorated. PMID:29049287

Preparation of porous PLA/DBM composite biomaterials and experimental research of repair rabbit radius segmental bone defect.

PubMed

Zhang, Yumin; Wang, Jianru; Wang, Jue; Niu, Xiaojun; Liu, Jianchun; Gao, Lan; Zhai, Xiaoyan; Chu, Kaibo

2015-12-01

Bone substitutes are used in wide range of orthopaedic application. An ideal bone substitute should exhibit superior osteoinductive and osteoconductive properties. Neither bio-derived materials nor synthetic materials can meet the needs of an ideal bone substitute. Preparation of composite materials is a promising way to improve properties of biomaterial. In this study, the porous poly lactic acid (PLA)/demineralized bone matrix (DBM) composite biomaterials prepared by supercritical CO2 technique were implanted to repair rabbit radius segmental bone defect. By comparing with PLA and bone autograft, the X-ray result and histological analysis showed the repair effect of PLA/DBM porous composite materials is significantly better than that of the PLA group and the blank control group, and is similar to autologous bone. The PLA/DBM can promote the healing of bone defects and can be used as a kind of ideal alternative materials to repair bone defects.

Management of segmental bony defects: the role of osteoconductive orthobiologics.

PubMed

McKee, Michael D

2006-01-01

Our knowledge about, and the availability of, orthobiologic materials has increased exponentially in the last decade. Although previously confined to the experimental or animal-model realm, several orthobiologics have been shown to be useful in a variety of clinical situations. As surgical techniques in vascular anastomosis, soft-tissue coverage, limb salvage, and fracture stabilization have improved, the size and frequency of bony defects (commensurate with the severity of the initial injury) have increased, as well. Because all methods of managing segmental bony defects have drawbacks, a need remains for a readily available, void-filling, inexpensive bone substitute. Such a bone substitute fulfills a permissive role in allowing new bone to grow into a given defect. Such potential osteoconductive materials include ceramics, calcium sulfate or calcium phosphate compounds, hydroxyapatite, deproteinized bone, corals, and recently developed polymers. Some materials that have osteoinductive properties, such as demineralized bone matrix, also display prominent osteoconductive properties.

Fast and Robust Segmentation and Classification for Change Detection in Urban Point Clouds

NASA Astrophysics Data System (ADS)

Roynard, X.; Deschaud, J.-E.; Goulette, F.

2016-06-01

Change detection is an important issue in city monitoring to analyse street furniture, road works, car parking, etc. For example, parking surveys are needed but are currently a laborious task involving sending operators in the streets to identify the changes in car locations. In this paper, we propose a method that performs a fast and robust segmentation and classification of urban point clouds, that can be used for change detection. We apply this method to detect the cars, as a particular object class, in order to perform parking surveys automatically. A recently proposed method already addresses the need for fast segmentation and classification of urban point clouds, using elevation images. The interest to work on images is that processing is much faster, proven and robust. However there may be a loss of information in complex 3D cases: for example when objects are one above the other, typically a car under a tree or a pedestrian under a balcony. In this paper we propose a method that retain the three-dimensional information while preserving fast computation times and improving segmentation and classification accuracy. It is based on fast region-growing using an octree, for the segmentation, and specific descriptors with Random-Forest for the classification. Experiments have been performed on large urban point clouds acquired by Mobile Laser Scanning. They show that the method is as fast as the state of the art, and that it gives more robust results in the complex 3D cases.

Multi-phase simultaneous segmentation of tumor in lung 4D-CT data with context information.

PubMed

Shen, Zhengwen; Wang, Huafeng; Xi, Weiwen; Deng, Xiaogang; Chen, Jin; Zhang, Yu

2017-01-01

Lung 4D computed tomography (4D-CT) plays an important role in high-precision radiotherapy because it characterizes respiratory motion, which is crucial for accurate target definition. However, the manual segmentation of a lung tumor is a heavy workload for doctors because of the large number of lung 4D-CT data slices. Meanwhile, tumor segmentation is still a notoriously challenging problem in computer-aided diagnosis. In this paper, we propose a new method based on an improved graph cut algorithm with context information constraint to find a convenient and robust approach of lung 4D-CT tumor segmentation. We combine all phases of the lung 4D-CT into a global graph, and construct a global energy function accordingly. The sub-graph is first constructed for each phase. A context cost term is enforced to achieve segmentation results in every phase by adding a context constraint between neighboring phases. A global energy function is finally constructed by combining all cost terms. The optimization is achieved by solving a max-flow/min-cut problem, which leads to simultaneous and robust segmentation of the tumor in all the lung 4D-CT phases. The effectiveness of our approach is validated through experiments on 10 different lung 4D-CT cases. The comparison with the graph cut without context constraint, the level set method and the graph cut with star shape prior demonstrates that the proposed method obtains more accurate and robust segmentation results.

A method of plane geometry primitive presentation

NASA Astrophysics Data System (ADS)

Jiao, Anbo; Luo, Haibo; Chang, Zheng; Hui, Bin

2014-11-01

Point feature and line feature are basic elements in object feature sets, and they play an important role in object matching and recognition. On one hand, point feature is sensitive to noise; on the other hand, there are usually a huge number of point features in an image, which makes it complex for matching. Line feature includes straight line segment and curve. One difficulty in straight line segment matching is the uncertainty of endpoint location, the other is straight line segment fracture problem or short straight line segments joined to form long straight line segment. While for the curve, in addition to the above problems, there is another difficulty in how to quantitatively describe the shape difference between curves. Due to the problems of point feature and line feature, the robustness and accuracy of target description will be affected; in this case, a method of plane geometry primitive presentation is proposed to describe the significant structure of an object. Firstly, two types of primitives are constructed, they are intersecting line primitive and blob primitive. Secondly, a line segment detector (LSD) is applied to detect line segment, and then intersecting line primitive is extracted. Finally, robustness and accuracy of the plane geometry primitive presentation method is studied. This method has a good ability to obtain structural information of the object, even if there is rotation or scale change of the object in the image. Experimental results verify the robustness and accuracy of this method.

Tracheal reconstruction with autogenous jejunal microsurgical transfer.

PubMed

Jones, R E; Morgan, R F; Marcella, K L; Mills, S E; Kron, I L

1986-06-01

Tracheal defects due to stricture formation, tracheomalacia, and neoplasms can present difficult reconstructive problems. Tracheal defects were surgically created in 6 dogs and primarily reconstructed with microsurgical free tissue transfer of autogenous jejunal segments. Primary healing was accomplished in all dogs without severe air leakage or infection. Bronchoscopy demonstrated no substantial secretions or tracheal narrowing. Gross pathological examination of the trachea revealed no evidence of tracheal disruption or infection. Direct measurements revealed no major tracheal narrowing. Microscopic examination demonstrated normal jejunal mucosa with a minimal amount of inflammatory change at the margins of the reconstruction at 6 weeks. Microvascular free tissue transfer of jejunal segments to correct cervical tracheal defects can readily be accomplished with excellent healing and maintenance of the tracheal lumen in dogs.

Supramolecular Luminescence from Oligofluorenol-Based Supramolecular Polymer Semiconductors

PubMed Central

Zhang, Guang-Wei; Wang, Long; Xie, Ling-Hai; Lin, Jin-Yi; Huang, Wei

2013-01-01

Supramolecular luminescence stems from non-covalent exciton behaviors of active π-segments in supramolecular entities or aggregates via intermolecular forces. Herein, a π-conjugated oligofluorenol, containing self-complementary double hydrogen bonds, was synthesized using Suzuki coupling as a supramolecular semiconductor. Terfluorenol-based random supramolecular polymers were confirmed via concentration-dependent nuclear magnetic resonance (NMR) and dynamic light scattering (DLS). The photoluminescent spectra of the TFOH-1 solution exhibit a green emission band (g-band) at approximately ~520 nm with reversible features, as confirmed through titration experiments. Supramolecular luminescence of TFOH-1 thin films serves as robust evidence for the aggregates of g-band. Our results suggest that the presence of polyfluorene ketone defects is a sufficient condition, rather than a sufficient-necessary condition for the g-band. Supramolecular electroluminescence will push organic devices into the fields of supramolecular optoelectronics, spintronics, and mechatronics. PMID:24232455

Voxel classification based airway tree segmentation

NASA Astrophysics Data System (ADS)

Lo, Pechin; de Bruijne, Marleen

2008-03-01

This paper presents a voxel classification based method for segmenting the human airway tree in volumetric computed tomography (CT) images. In contrast to standard methods that use only voxel intensities, our method uses a more complex appearance model based on a set of local image appearance features and Kth nearest neighbor (KNN) classification. The optimal set of features for classification is selected automatically from a large set of features describing the local image structure at several scales. The use of multiple features enables the appearance model to differentiate between airway tree voxels and other voxels of similar intensities in the lung, thus making the segmentation robust to pathologies such as emphysema. The classifier is trained on imperfect segmentations that can easily be obtained using region growing with a manual threshold selection. Experiments show that the proposed method results in a more robust segmentation that can grow into the smaller airway branches without leaking into emphysematous areas, and is able to segment many branches that are not present in the training set.

Automatic coronary artery segmentation based on multi-domains remapping and quantile regression in angiographies.

PubMed

Li, Zhixun; Zhang, Yingtao; Gong, Huiling; Li, Weimin; Tang, Xianglong

2016-12-01

Coronary artery disease has become the most dangerous diseases to human life. And coronary artery segmentation is the basis of computer aided diagnosis and analysis. Existing segmentation methods are difficult to handle the complex vascular texture due to the projective nature in conventional coronary angiography. Due to large amount of data and complex vascular shapes, any manual annotation has become increasingly unrealistic. A fully automatic segmentation method is necessary in clinic practice. In this work, we study a method based on reliable boundaries via multi-domains remapping and robust discrepancy correction via distance balance and quantile regression for automatic coronary artery segmentation of angiography images. The proposed method can not only segment overlapping vascular structures robustly, but also achieve good performance in low contrast regions. The effectiveness of our approach is demonstrated on a variety of coronary blood vessels compared with the existing methods. The overall segmentation performances si, fnvf, fvpf and tpvf were 95.135%, 3.733%, 6.113%, 96.268%, respectively. Copyright © 2016 Elsevier Ltd. All rights reserved.

Automated tumor volumetry using computer-aided image segmentation.

PubMed

Gaonkar, Bilwaj; Macyszyn, Luke; Bilello, Michel; Sadaghiani, Mohammed Salehi; Akbari, Hamed; Atthiah, Mark A; Ali, Zarina S; Da, Xiao; Zhan, Yiqang; O'Rourke, Donald; Grady, Sean M; Davatzikos, Christos

2015-05-01

Accurate segmentation of brain tumors, and quantification of tumor volume, is important for diagnosis, monitoring, and planning therapeutic intervention. Manual segmentation is not widely used because of time constraints. Previous efforts have mainly produced methods that are tailored to a particular type of tumor or acquisition protocol and have mostly failed to produce a method that functions on different tumor types and is robust to changes in scanning parameters, resolution, and image quality, thereby limiting their clinical value. Herein, we present a semiautomatic method for tumor segmentation that is fast, accurate, and robust to a wide variation in image quality and resolution. A semiautomatic segmentation method based on the geodesic distance transform was developed and validated by using it to segment 54 brain tumors. Glioblastomas, meningiomas, and brain metastases were segmented. Qualitative validation was based on physician ratings provided by three clinical experts. Quantitative validation was based on comparing semiautomatic and manual segmentations. Tumor segmentations obtained using manual and automatic methods were compared quantitatively using the Dice measure of overlap. Subjective evaluation was performed by having human experts rate the computerized segmentations on a 0-5 rating scale where 5 indicated perfect segmentation. The proposed method addresses a significant, unmet need in the field of neuro-oncology. Specifically, this method enables clinicians to obtain accurate and reproducible tumor volumes without the need for manual segmentation. Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.

Automated Tumor Volumetry Using Computer-Aided Image Segmentation

PubMed Central

Bilello, Michel; Sadaghiani, Mohammed Salehi; Akbari, Hamed; Atthiah, Mark A.; Ali, Zarina S.; Da, Xiao; Zhan, Yiqang; O'Rourke, Donald; Grady, Sean M.; Davatzikos, Christos

2015-01-01

Rationale and Objectives Accurate segmentation of brain tumors, and quantification of tumor volume, is important for diagnosis, monitoring, and planning therapeutic intervention. Manual segmentation is not widely used because of time constraints. Previous efforts have mainly produced methods that are tailored to a particular type of tumor or acquisition protocol and have mostly failed to produce a method that functions on different tumor types and is robust to changes in scanning parameters, resolution, and image quality, thereby limiting their clinical value. Herein, we present a semiautomatic method for tumor segmentation that is fast, accurate, and robust to a wide variation in image quality and resolution. Materials and Methods A semiautomatic segmentation method based on the geodesic distance transform was developed and validated by using it to segment 54 brain tumors. Glioblastomas, meningiomas, and brain metastases were segmented. Qualitative validation was based on physician ratings provided by three clinical experts. Quantitative validation was based on comparing semiautomatic and manual segmentations. Results Tumor segmentations obtained using manual and automatic methods were compared quantitatively using the Dice measure of overlap. Subjective evaluation was performed by having human experts rate the computerized segmentations on a 0–5 rating scale where 5 indicated perfect segmentation. Conclusions The proposed method addresses a significant, unmet need in the field of neuro-oncology. Specifically, this method enables clinicians to obtain accurate and reproducible tumor volumes without the need for manual segmentation. PMID:25770633

Defect detection in slab surface: a novel dual Charge-coupled Device imaging-based fuzzy connectedness strategy.

PubMed

Zhao, Liming; Ouyang, Qi; Chen, Dengfu; Udupa, Jayaram K; Wang, Huiqian; Zeng, Yuebin

2014-11-01

To provide an accurate surface defects inspection system and make the automation of robust image segmentation method a reality in routine production line, a general approach is presented for continuous casting slab (CC-slab) surface defects extraction and delineation. The applicability of the system is not tied to CC-slab exclusively. We combined the line array CCD (Charge-coupled Device) traditional scanning imaging (LS-imaging) and area array CCD laser three-dimensional (3D) scanning imaging (AL-imaging) strategies in designing the system. Its aim is to suppress the respective imaging system's limitations. In the system, the images acquired from the two CCD sensors are carefully aligned in space and in time by maximum mutual information-based full-fledged registration schema. Subsequently, the image information is fused from these two subsystems such as the unbroken 2D information in LS-imaging and 3D depressed information in AL-imaging. Finally, on the basis of the established dual scanning imaging system the region of interest (ROI) localization by seed specification was designed, and the delineation for ROI by iterative relative fuzzy connectedness (IRFC) algorithm was utilized to get a precise inspection result. Our method takes into account the complementary advantages in the two common machine vision (MV) systems and it performs competitively with the state-of-the-art as seen from the comparison of experimental results. For the first time, a joint imaging scanning strategy is proposed for CC-slab surface defect inspection that allows a feasible way of powerful ROI delineation strategies to be applied to the MV inspection field. Multi-ROI delineation by using IRFC in this research field may further improve the results.

Robust finger vein ROI localization based on flexible segmentation.

PubMed

Lu, Yu; Xie, Shan Juan; Yoon, Sook; Yang, Jucheng; Park, Dong Sun

2013-10-24

Finger veins have been proved to be an effective biometric for personal identification in the recent years. However, finger vein images are easily affected by influences such as image translation, orientation, scale, scattering, finger structure, complicated background, uneven illumination, and collection posture. All these factors may contribute to inaccurate region of interest (ROI) definition, and so degrade the performance of finger vein identification system. To improve this problem, in this paper, we propose a finger vein ROI localization method that has high effectiveness and robustness against the above factors. The proposed method consists of a set of steps to localize ROIs accurately, namely segmentation, orientation correction, and ROI detection. Accurate finger region segmentation and correct calculated orientation can support each other to produce higher accuracy in localizing ROIs. Extensive experiments have been performed on the finger vein image database, MMCBNU_6000, to verify the robustness of the proposed method. The proposed method shows the segmentation accuracy of 100%. Furthermore, the average processing time of the proposed method is 22 ms for an acquired image, which satisfies the criterion of a real-time finger vein identification system.

Robust Finger Vein ROI Localization Based on Flexible Segmentation

PubMed Central

Lu, Yu; Xie, Shan Juan; Yoon, Sook; Yang, Jucheng; Park, Dong Sun

2013-01-01

Finger veins have been proved to be an effective biometric for personal identification in the recent years. However, finger vein images are easily affected by influences such as image translation, orientation, scale, scattering, finger structure, complicated background, uneven illumination, and collection posture. All these factors may contribute to inaccurate region of interest (ROI) definition, and so degrade the performance of finger vein identification system. To improve this problem, in this paper, we propose a finger vein ROI localization method that has high effectiveness and robustness against the above factors. The proposed method consists of a set of steps to localize ROIs accurately, namely segmentation, orientation correction, and ROI detection. Accurate finger region segmentation and correct calculated orientation can support each other to produce higher accuracy in localizing ROIs. Extensive experiments have been performed on the finger vein image database, MMCBNU_6000, to verify the robustness of the proposed method. The proposed method shows the segmentation accuracy of 100%. Furthermore, the average processing time of the proposed method is 22 ms for an acquired image, which satisfies the criterion of a real-time finger vein identification system. PMID:24284769

"Palmar pivot flap" for resurfacing palmar lateral defects of the fingers.

PubMed

Yam, Andrew; Peng, Yeong-Pin; Pho, Robert Wan-Heng

2008-12-01

Soft tissue defects on the lateral borders of the digits are difficult to reconstruct using local or local-regional flaps. We describe a "palmar pivot flap" to resurface an adjacent defect on the palmar-lateral aspect of the digit. The surgical technique is described. This flap is an axial pattern flap based on the subcutaneous transverse branches of the digital artery. The flap is pivoted up to 90 degrees on the neurovascular bundle in its base, into an adjacent defect. The flap can be raised from either the proximal or the middle phalangeal segments. It can cover defects sited from the level of the proximal interphalangeal joint up to the fingertip. The donor defect is limited to the same digit and is covered with a full-thickness skin graft. We have used this flap on 3 patients with defects at the middle phalangeal segment, the distal interphalangeal joint, and the fingertip. All healed primarily. One patient had a mild flexion contracture of the proximal interphalangeal joint, whereas the other 2 had no complications. The patients with distal interphalangeal joint and fingertip defects had excellent sensation in the flap (2-point discrimination of 5-6 mm). The palmar pivot flap is useful for resurfacing otherwise difficult defects on the lateral borders of the digits around and distal to the proximal interphalangeal joint, including those at the fingertip. It provides sensate, glabrous skin. The donor defect is on the same digit and is well hidden, producing an aesthetic and functional reconstruction.

[Visual rehabilitation of patients with large post-traumatic defects of the anterior eye segment through iris-lens diaphragm implantation].

PubMed

Khodzhaev, N S; Sobolev, N P; Mushkova, I A; Izmaylova, S B; Karimova, A N

The diversity of methodological approaches and lack of pathogenetically reasonable tactics for patients with combined ocular injuries became the basis for the development and systematization of surgical rehabilitation stages of patients, in whom post-traumatic cataract is combined with post-traumatic aniridia and corneal scarring. to construct a visual rehabilitation approach to patients with post-traumatic defects of the anterior eye segment following optical-reconstructive surgery that involved implantation of an iris-lens diaphragm (ILD). We have analyzed 80 reconstructive cases with ILD implantation in patients with post-traumatic aniridia and corneal damage. These patients constituted the first study group (Group 1). We have also investigated 58 eyes with residual ametropy and stable visual function 1 year after ILD implantation before and after conducting a laser keratorefractive surgery. These patients were assigned to the second study group (Group 2). Rehabilitation approach to patients after anterior segment injuries that has been proposed allows to achieve high clinical and functional results and reduce the risk of intra- and postoperative complications. The proposed approach to patients after optical-reconstructive surgery with iris-lens diaphragm implantation followed by keratorefractive surgery is an effective method of visual rehabilitation of anterior eye segment post-traumatic defects.

Adjustable stiffness, external fixator for the rat femur osteotomy and segmental bone defect models.

PubMed

Glatt, Vaida; Matthys, Romano

2014-10-09

The mechanical environment around the healing of broken bone is very important as it determines the way the fracture will heal. Over the past decade there has been great clinical interest in improving bone healing by altering the mechanical environment through the fixation stability around the lesion. One constraint of preclinical animal research in this area is the lack of experimental control over the local mechanical environment within a large segmental defect as well as osteotomies as they heal. In this paper we report on the design and use of an external fixator to study the healing of large segmental bone defects or osteotomies. This device not only allows for controlled axial stiffness on the bone lesion as it heals, but it also enables the change of stiffness during the healing process in vivo. The conducted experiments have shown that the fixators were able to maintain a 5 mm femoral defect gap in rats in vivo during unrestricted cage activity for at least 8 weeks. Likewise, we observed no distortion or infections, including pin infections during the entire healing period. These results demonstrate that our newly developed external fixator was able to achieve reproducible and standardized stabilization, and the alteration of the mechanical environment of in vivo rat large bone defects and various size osteotomies. This confirms that the external fixation device is well suited for preclinical research investigations using a rat model in the field of bone regeneration and repair.

Usher syndrome type 1–associated cadherins shape the photoreceptor outer segment

PubMed Central

Parain, Karine; Aghaie, Asadollah; Picaud, Serge

2017-01-01

Usher syndrome type 1 (USH1) causes combined hearing and sight defects, but how mutations in USH1 genes lead to retinal dystrophy in patients remains elusive. The USH1 protein complex is associated with calyceal processes, which are microvilli of unknown function surrounding the base of the photoreceptor outer segment. We show that in Xenopus tropicalis, these processes are connected to the outer-segment membrane by links composed of protocadherin-15 (USH1F protein). Protocadherin-15 deficiency, obtained by a knockdown approach, leads to impaired photoreceptor function and abnormally shaped photoreceptor outer segments. Rod basal outer disks displayed excessive outgrowth, and cone outer segments were curved, with lamellae of heterogeneous sizes, defects also observed upon knockdown of Cdh23, encoding cadherin-23 (USH1D protein). The calyceal processes were virtually absent in cones and displayed markedly reduced F-actin content in rods, suggesting that protocadherin-15–containing links are essential for their development and/or maintenance. We propose that calyceal processes, together with their associated links, control the sizing of rod disks and cone lamellae throughout their daily renewal. PMID:28495838

Usher syndrome type 1-associated cadherins shape the photoreceptor outer segment.

PubMed

Schietroma, Cataldo; Parain, Karine; Estivalet, Amrit; Aghaie, Asadollah; Boutet de Monvel, Jacques; Picaud, Serge; Sahel, José-Alain; Perron, Muriel; El-Amraoui, Aziz; Petit, Christine

2017-06-05

Usher syndrome type 1 (USH1) causes combined hearing and sight defects, but how mutations in USH1 genes lead to retinal dystrophy in patients remains elusive. The USH1 protein complex is associated with calyceal processes, which are microvilli of unknown function surrounding the base of the photoreceptor outer segment. We show that in Xenopus tropicalis , these processes are connected to the outer-segment membrane by links composed of protocadherin-15 (USH1F protein). Protocadherin-15 deficiency, obtained by a knockdown approach, leads to impaired photoreceptor function and abnormally shaped photoreceptor outer segments. Rod basal outer disks displayed excessive outgrowth, and cone outer segments were curved, with lamellae of heterogeneous sizes, defects also observed upon knockdown of Cdh23 , encoding cadherin-23 (USH1D protein). The calyceal processes were virtually absent in cones and displayed markedly reduced F-actin content in rods, suggesting that protocadherin-15-containing links are essential for their development and/or maintenance. We propose that calyceal processes, together with their associated links, control the sizing of rod disks and cone lamellae throughout their daily renewal. © 2017 Schietroma et al.

Robustness of Thirty Meter Telescope primary mirror control

NASA Astrophysics Data System (ADS)

Macmynowski, Douglas G.; Thompson, Peter M.; Shelton, Chris; Roberts, Lewis C., Jr.

2010-07-01

The primary mirror control system for the Thirty Meter Telescope (TMT) maintains the alignment of the 492 segments in the presence of both quasi-static (gravity and thermal) and dynamic disturbances due to unsteady wind loads. The latter results in a desired control bandwidth of 1Hz at high spatial frequencies. The achievable bandwidth is limited by robustness to (i) uncertain telescope structural dynamics (control-structure interaction) and (ii) small perturbations in the ill-conditioned influence matrix that relates segment edge sensor response to actuator commands. Both of these effects are considered herein using models of TMT. The former is explored through multivariable sensitivity analysis on a reduced-order Zernike-basis representation of the structural dynamics. The interaction matrix ("A-matrix") uncertainty has been analyzed theoretically elsewhere, and is examined here for realistic amplitude perturbations due to segment and sensor installation errors, and gravity and thermal induced segment motion. The primary influence of A-matrix uncertainty is on the control of "focusmode"; this is the least observable mode, measurable only through the edge-sensor (gap-dependent) sensitivity to the dihedral angle between segments. Accurately estimating focus-mode will require updating the A-matrix as a function of the measured gap. A-matrix uncertainty also results in a higher gain-margin requirement for focus-mode, and hence the A-matrix and CSI robustness need to be understood simultaneously. Based on the robustness analysis, the desired 1 Hz bandwidth is achievable in the presence of uncertainty for all except the lowest spatial-frequency response patterns of the primary mirror.

Segmental liver incarceration through a recurrent incisional lumbar hernia.

PubMed

Salemis, Nikolaos S; Nisotakis, Konstantinos; Gourgiotis, Stavros; Tsohataridis, Efstathios

2007-08-01

Lumbar hernia is a rare congenital or acquired defect of the posterior abdominal wall. The acquired type is more common and occurs mainly as an incisional defect after flank surgery. Incarceration or strangulation of hernia contents is uncommon. Segmental liver incarceration through a recurrent incisional lumbar defect was diagnosed in a 58 years old woman by magnetic resonance imaging. The patient underwent an open repair of the complicated hernia. An expanded polytetraflouoroethylene (e-PTFE) mesh was fashioned as a sublay prosthesis. She had an uncomplicated postoperative course. Follow-up examinations revealed no evidence of recurrence. Although lumbar hernia rarely results in incarceration or strangulation, early repair is necessary because of the risks of complications and the increasing difficulty in repairment as it enlarges. Surgical repair is often difficult and challenging.

A Generic Deep-Learning-Based Approach for Automated Surface Inspection.

PubMed

Ren, Ruoxu; Hung, Terence; Tan, Kay Chen

2018-03-01

Automated surface inspection (ASI) is a challenging task in industry, as collecting training dataset is usually costly and related methods are highly dataset-dependent. In this paper, a generic approach that requires small training data for ASI is proposed. First, this approach builds classifier on the features of image patches, where the features are transferred from a pretrained deep learning network. Next, pixel-wise prediction is obtained by convolving the trained classifier over input image. An experiment on three public and one industrial data set is carried out. The experiment involves two tasks: 1) image classification and 2) defect segmentation. The results of proposed algorithm are compared against several best benchmarks in literature. In the classification tasks, the proposed method improves accuracy by 0.66%-25.50%. In the segmentation tasks, the proposed method reduces error escape rates by 6.00%-19.00% in three defect types and improves accuracies by 2.29%-9.86% in all seven defect types. In addition, the proposed method achieves 0.0% error escape rate in the segmentation task of industrial data.

[Implantation of an Artificial Iris in 11 Patients].

PubMed

Kniestedt, C; Eberhard, R; Fleischhauer, J

2016-04-01

Background. Iris defects are mostly acquired after injury, or may be iatrogenic after surgical excision of iris tumours or the result of collateral trauma after anterior segment surgery. They cause severe visual disability, e.g. glare, loss of contrast sensitivity, and loss of best corrected visual acuity. The foldable Koch iris prosthesis has a customised iris design and may be used to reconstruct the anterior segment in patients with partial or complete aniridia. History and Signs. We present the surgical management and clinical course of 6 patients with traumatic iris defects, together with 3 patients with partial aniridia after cataract surgery. Cataract surgery and implantation of an artificial iris were performed in 2 female patients (3 eyes) with congenital aniridia syndrome. Therapy and Outcome. No patient exhibited complications in the postoperative course, with the exception of various intraocular pressure peaks due to secondary glaucoma, that were all corrected by medication to lower topical pressure. Conclusions. In patients with major iris defects, the artificial iris allows functionally and aesthetically satisfactory reconstruction of the anterior segment. Georg Thieme Verlag KG Stuttgart · New York.

Robust optimization of the billet for isothermal local loading transitional region of a Ti-alloy rib-web component based on dual-response surface method

NASA Astrophysics Data System (ADS)

Wei, Ke; Fan, Xiaoguang; Zhan, Mei; Meng, Miao

2018-03-01

Billet optimization can greatly improve the forming quality of the transitional region in the isothermal local loading forming (ILLF) of large-scale Ti-alloy ribweb components. However, the final quality of the transitional region may be deteriorated by uncontrollable factors, such as the manufacturing tolerance of the preforming billet, fluctuation of the stroke length, and friction factor. Thus, a dual-response surface method (RSM)-based robust optimization of the billet was proposed to address the uncontrollable factors in transitional region of the ILLF. Given that the die underfilling and folding defect are two key factors that influence the forming quality of the transitional region, minimizing the mean and standard deviation of the die underfilling rate and avoiding folding defect were defined as the objective function and constraint condition in robust optimization. Then, the cross array design was constructed, a dual-RSM model was established for the mean and standard deviation of the die underfilling rate by considering the size parameters of the billet and uncontrollable factors. Subsequently, an optimum solution was derived to achieve the robust optimization of the billet. A case study on robust optimization was conducted. Good results were attained for improving the die filling and avoiding folding defect, suggesting that the robust optimization of the billet in the transitional region of the ILLF was efficient and reliable.

Automatic allograft bone selection through band registration and its application to distal femur.

PubMed

Zhang, Yu; Qiu, Lei; Li, Fengzan; Zhang, Qing; Zhang, Li; Niu, Xiaohui

2017-09-01

Clinical reports suggest that large bone defects could be effectively restored by allograft bone transplantation, where allograft bone selection acts an important role. Besides, there is a huge demand for developing the automatic allograft bone selection methods, as the automatic methods could greatly improve the management efficiency of the large bone banks. Although several automatic methods have been presented to select the most suitable allograft bone from the massive allograft bone bank, these methods still suffer from inaccuracy. In this paper, we propose an effective allograft bone selection method without using the contralateral bones. Firstly, the allograft bone is globally aligned to the recipient bone by surface registration. Then, the global alignment is further refined through band registration. The band, defined as the recipient points within the lifted and lowered cutting planes, could involve more local structure of the defected segment. Therefore, our method could achieve robust alignment and high registration accuracy of the allograft and recipient. Moreover, the existing contour method and surface method could be unified into one framework under our method by adjusting the lift and lower distances of the cutting planes. Finally, our method has been validated on the database of distal femurs. The experimental results indicate that our method outperforms the surface method and contour method.

Damage Tolerance of Large Shell Structures

NASA Technical Reports Server (NTRS)

Minnetyan, L.; Chamis, C. C.

1999-01-01

Progressive damage and fracture of large shell structures is investigated. A computer model is used for the assessment of structural response, progressive fracture resistance, and defect/damage tolerance characteristics. Critical locations of a stiffened conical shell segment are identified. Defective and defect-free computer models are simulated to evaluate structural damage/defect tolerance. Safe pressurization levels are assessed for the retention of structural integrity at the presence of damage/ defects. Damage initiation, growth, accumulation, and propagation to fracture are included in the simulations. Damage propagation and burst pressures for defective and defect-free shells are compared to evaluate damage tolerance. Design implications with regard to defect and damage tolerance of a large steel pressure vessel are examined.

Molecular dynamics simulations of fluoropolymers in the solid state

NASA Astrophysics Data System (ADS)

Holt, David Bryan

1998-10-01

Molecular mechanics and dynamics simulations have been utilized to address the behavior of helix reversal defects in fluoropolymers. The results of the simulations confirm that helix reversals do form and migrate in PTFE crystals. The most important defect structure is a helix reversal band: two helix reversals which bracker a small chain segment (typically 6-7 backbone atoms) having the opposite helical sense from the parent molecule. Small reversal bands had velocities ranging between 100 m/s (low temperature)-250 m/s (high temperature). The size of this reversal band defect is dependent upon the helical conformation and is equal to approximately half of the helical repeat unit in the low and intermediate temperature phases. In the high temperature phase where intermolecular effects are diminished, a wider distribution of reversal band sizes was observed during the simulations. A mechanism is identified by which significant reorientation of a chain segment about the molecular axis can occur when it is bracketed by two helix reversal bands. Simulations with a model containing a perfluoromethyl (PFM) group at low temperature showed that the presence of the PFM group significantly restricts chain mobility locally. However, a significant reduction in the helix reversal defect density was observed on neighboring chains as well. During simulations in which a shear deformation was applied to the models with and without a PFM group, an increase in reversal defect density was observed. However, the helix reversal density in the sheared model containing the PFM branch was less than that in the model without a PFM branch under no shear. These data implicate helix reversal defects and associated chain segment motions in the mechanical behavior of fluoropolymer materials.

Distribution path robust optimization of electric vehicle with multiple distribution centers

PubMed Central

Hao, Wei; He, Ruichun; Jia, Xiaoyan; Pan, Fuquan; Fan, Jing; Xiong, Ruiqi

2018-01-01

To identify electrical vehicle (EV) distribution paths with high robustness, insensitivity to uncertainty factors, and detailed road-by-road schemes, optimization of the distribution path problem of EV with multiple distribution centers and considering the charging facilities is necessary. With the minimum transport time as the goal, a robust optimization model of EV distribution path with adjustable robustness is established based on Bertsimas’ theory of robust discrete optimization. An enhanced three-segment genetic algorithm is also developed to solve the model, such that the optimal distribution scheme initially contains all road-by-road path data using the three-segment mixed coding and decoding method. During genetic manipulation, different interlacing and mutation operations are carried out on different chromosomes, while, during population evolution, the infeasible solution is naturally avoided. A part of the road network of Xifeng District in Qingyang City is taken as an example to test the model and the algorithm in this study, and the concrete transportation paths are utilized in the final distribution scheme. Therefore, more robust EV distribution paths with multiple distribution centers can be obtained using the robust optimization model. PMID:29518169

Thrombus formation in the interrupted segment of the aorta.

PubMed

Karavelioğlu, Yusuf; Kalçık, Macit; Yetim, Mucahit; Doğan, Tolga; Gölbaşı, Zehra

2017-06-01

Interrupted aorta is a very rare heart defect in which there is a gap between the ascending and the descending thoracic aorta. It is usually associated with other cardiac anomalies, including ventricular septal defect, ductus arteriosus, and truncus arteriosus. Severe cases present with serious complications such as hypertension, heart failure, or intracranial hemorrhage. Neurological complications are very rare form of presentation and commonly associated with intracranial aneurysms. We have reported a case of interrupted aorta who presented with transient ischemic attack due to thrombus formation in the interrupted segment of the aorta. © 2017, Wiley Periodicals, Inc.

Regional glucose utilization in infarcted and remote myocardium: its relation to coronary anatomy and perfusion.

PubMed

Fragasso, G; Chierchia, S L; Landoni, C; Lucignani, G; Rossetti, E; Sciammarella, M; Vanoli, G E; Fazio, F

1998-07-01

We studied the relationship between coronary anatomy, perfusion and metabolism in myocardial segments exhibiting transient and persistent perfusion defects on stress/rest 99Tcm-MIBI single photon emission tomography in 35 patients (31 males, 4 females, mean age 56 +/- 7 years) with a previous myocardial infarction. Quantitative coronary angiography and assessment of myocardial perfusion reserve and glucose metabolism were performed within 1 week of one another. Perfusion was assessed by SPET after the intravenous injection of 740 MBq of 99Tcm-MIBI at rest and after exercise. Regional myocardial glucose metabolism was assessed by position emission tomography at rest (200 MBq of 18F-2-deoxyglucose, FDG) after an overnight fast with no glucose loading. All 35 patients exhibited persistent perfusion defects consistent with the clinically identified infarct site, and 27 (77%) also showed various degrees of within-infarct FDG uptake; 11 patients developed exercise-induced transient perfusion defects within, or in the vicinity of, 15 infarct segments and resting FDG uptake was present in 10 of these segments (67%). Five patients also showed exercise-induced transient perfusion defects in nine segments remote from the site of infarct: resting FDG uptake was present in six of these regions (67%). Finally, nine patients had increased glucose uptake in non-infarcted regions not showing transient perfusion defects upon exercise testing and perfused by coronary arteries with only minor irregularities. Our results confirm the presence of viable tissue in a large proportion of infarct sites. Moreover, FDG uptake can be seen in regions perfused by coronary arteries showing minor irregularities, not necessarily resulting in detectable transient perfusion defects on a MIBI stress scan. Since the clinical significance of such findings is not clear, further studies should be conducted to assess the long-term evolution of perfusion, function and metabolism in non-revascularized patients of those remote areas which are apparently normally perfused, but show abnormal fasting FDG uptake after myocardial infarction. Such studies may have important implications for the management of post-infarct patients, as the preservation of coronary vasodilator reserve and myocardial metabolism in remote myocardium may be seen as an additional goal in the treatment of such patients.

Analysis of the results of replacement of large bone defects in the patients who underwent segmental bone resection for tumor

NASA Astrophysics Data System (ADS)

Anastasieva, E. A.; Voropaeva, A. A.; Sadovoy, M. A.; Kirilova, I. A.

2017-09-01

The problem of large bone defects replacement, formed after segmental bone resections, remains an actual issue of modern orthopedics. It is known that the autograft is the most acceptable material for the replacement of bone tissue; however, due to its small volume and physical properties, it has limited usage. Our goal is to analyze the results of the experiments and studies on replacement of large bone defects after resection of the bone tumor. The problem is justified by the complicated osteoconduction and osteointegration; because it is proved that the reconstruction of the microcirculatory bloodstream is difficult in the presence of damage more than 4 cm2. It was revealed that using of allograft in combination with additional components is comparable in effectiveness, including long-term period, with autograft usage. It is promising to combine plastic allogenous material, capable of reconstructing defects of various configuration intraoperatively, with the necessary chemotherapy with controlled desorption to maintain effective concentration of drug.

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.

Automated Sperm Head Detection Using Intersecting Cortical Model Optimised by Particle Swarm Optimization.

PubMed

Tan, Weng Chun; Mat Isa, Nor Ashidi

2016-01-01

In human sperm motility analysis, sperm segmentation plays an important role to determine the location of multiple sperms. To ensure an improved segmentation result, the Laplacian of Gaussian filter is implemented as a kernel in a pre-processing step before applying the image segmentation process to automatically segment and detect human spermatozoa. This study proposes an intersecting cortical model (ICM), which was derived from several visual cortex models, to segment the sperm head region. However, the proposed method suffered from parameter selection; thus, the ICM network is optimised using particle swarm optimization where feature mutual information is introduced as the new fitness function. The final results showed that the proposed method is more accurate and robust than four state-of-the-art segmentation methods. The proposed method resulted in rates of 98.14%, 98.82%, 86.46% and 99.81% in accuracy, sensitivity, specificity and precision, respectively, after testing with 1200 sperms. The proposed algorithm is expected to be implemented in analysing sperm motility because of the robustness and capability of this algorithm.

Wood industrial application for quality control using image processing

NASA Astrophysics Data System (ADS)

Ferreira, M. J. O.; Neves, J. A. C.

1994-11-01

This paper describes an application of image processing for the furniture industry. It uses an input data, images acquired directly from wood planks where defects were previously marked by an operator. A set of image processing algorithms separates and codes each defect and detects a polygonal approach of the line representing them. For such a purpose we developed a pattern classification algorithm and a new technique of segmenting defects by carving the convex hull of the binary shape representing each isolated defect.

Inorganic-organic shape memory polymers and foams for bone defect repairs

NASA Astrophysics Data System (ADS)

Zhang, Dawei

The ultimate goal of this research was to develop a "self-fitting" shape memory polymer (SMP) scaffold for the repair of craniomaxillofacial (CMF) bone defects. CMF defects may be caused by trauma, tumor removal or congenital abnormalities and represent a major class of bone defects. Their repair with autografts is limited by availability, donor site morbidity and complex surgical procedures. In addition, shaping and positioning of these rigid grafts into irregular defects is difficult. Herein, we have developed SMP scaffolds which soften at T > ˜56 °C, allowing them to conformally fit into a bone defect. Upon cooling to body temperature, the scaffold becomes rigid and mechanically locks in place. This research was comprised of four major studies. In the first study, photocrosslinkable acrylated (AcO) SMP macromers containing a poly(epsilon-caprolactone) (PCL) segment and polydimethylsiloxane (PDMS) segments were synthesized with the general formula: AcO-PCL40-block-PDMS m-block-PCL40-OAc. By varying the PDMS segment length (m), solid SMPs with highly tunable mechanical properties and excellent shape memory abilities were prepared. In the second study, porous SMP scaffolds were fabricated based on AcO-PCL 40-block-PDMS37-block-PCL 40-OAc via a revised solvent casting particulate leaching (SCPL) method. By tailoring scaffold parameters including salt fusion, macromer concentration and salt size, scaffold properties (e.g. pore features, compressive modulus and shape memory behavior) were tuned. In the third study, porous SMP scaffolds were produced from macromers with variable PDMS segment lengths (m = 0 -- 130) via an optimized SCPL method. The impact on pore features, thermal, mechanical, and shape memory properties as well as degradation rates were investigated. In the final study, a bioactive polydopamine coating was applied onto pore surfaces of the SMP scaffold prepared from PCL diacrylate. The thin coating did not affect intrinsic bulk properties of the scaffold. However, the coating significantly increased its bioactivity, giving rise to the formation of "bone-bonding" hydroxyapatite (HAp) when exposed to simulated body fluid (SBF). It was also shown that the coating largely enhanced the scaffold's capacities to support osteoblasts adhesion, proliferation and osteogenesis. Thus, the polydopamine coating should enhance the performance of the "self-fitting" SMP scaffolds for the repair of bone defects.

Superpixel guided active contour segmentation of retinal layers in OCT volumes

NASA Astrophysics Data System (ADS)

Bai, Fangliang; Gibson, Stuart J.; Marques, Manuel J.; Podoleanu, Adrian

2018-03-01

Retinal OCT image segmentation is a precursor to subsequent medical diagnosis by a clinician or machine learning algorithm. In the last decade, many algorithms have been proposed to detect retinal layer boundaries and simplify the image representation. Inspired by the recent success of superpixel methods for pre-processing natural images, we present a novel framework for segmentation of retinal layers in OCT volume data. In our framework, the region of interest (e.g. the fovea) is located using an adaptive-curve method. The cell layer boundaries are then robustly detected firstly using 1D superpixels, applied to A-scans, and then fitting active contours in B-scan images. Thereafter the 3D cell layer surfaces are efficiently segmented from the volume data. The framework was tested on healthy eye data and we show that it is capable of segmenting up to 12 layers. The experimental results imply the effectiveness of proposed method and indicate its robustness to low image resolution and intrinsic speckle noise.

Hybrid active contour model for inhomogeneous image segmentation with background estimation

NASA Astrophysics Data System (ADS)

Sun, Kaiqiong; Li, Yaqin; Zeng, Shan; Wang, Jun

2018-03-01

This paper proposes a hybrid active contour model for inhomogeneous image segmentation. The data term of the energy function in the active contour consists of a global region fitting term in a difference image and a local region fitting term in the original image. The difference image is obtained by subtracting the background from the original image. The background image is dynamically estimated from a linear filtered result of the original image on the basis of the varying curve locations during the active contour evolution process. As in existing local models, fitting the image to local region information makes the proposed model robust against an inhomogeneous background and maintains the accuracy of the segmentation result. Furthermore, fitting the difference image to the global region information makes the proposed model robust against the initial contour location, unlike existing local models. Experimental results show that the proposed model can obtain improved segmentation results compared with related methods in terms of both segmentation accuracy and initial contour sensitivity.

Special distraction osteogenesis before bone grafting for alveolar cleft defects to correct maxillary deformities in patients with bilateral cleft lips and palates: distraction osteogenesis performed separately for each bone segment.

PubMed

Mitsukawa, Nobuyuki; Saiga, Atsuomi; Morishita, Tadashi; Satoh, Kaneshige

2014-07-01

Patients with bilateral cleft lips and palates have premaxillary protrusion and characteristic jaw deformities involving three-dimensional malposition of the premaxilla and bilateral maxillary bone segments. This study examined patients with bilateral cleft lips and palates who had deviation and hypoplasia of the premaxillas and bilateral maxillary segments. Before bone grafting, the patients were treated with special distraction performed separately for each bone segment using a halo-type external device. This report describes this novel treatment method which produced good results. The subjects were five patients with severe jaw deformities due to bilateral cleft lip and palate. They were treated with maxillary Le Fort I osteotomy and subsequent distraction performed separately for each bone segment using a halo device. In three of five patients, premaxillary osteotomy was not performed, and osteotomy and distraction were performed only for the right and left lateral segments with severe hypoplasia. All patients achieved distraction close to the desired amount. The widths of the alveolar clefts were narrowed, and satisfactory occlusion and maxillary arch form were achieved. After the surgery, three of five patients underwent bone grafting for bilateral alveolar cleft defects and the bone graft survival was satisfactory. This method had many benefits, including narrowing of alveolar clefts, improvement of maxillary hypoplasia, and achievement of a good maxillary arch form. In addition, subsequent bone grafting for alveolar cleft defects was beneficial, dental prostheses were unnecessary, and frequency of surgery and surgical invasiveness were reduced. This method is a good surgical procedure that should be considered for patients with bilateral cleft lips and palates who have premaxillary protrusion and hypoplasia of the right and left lateral segments. Copyright © 2013 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.

Segmenting lung fields in serial chest radiographs using both population-based and patient-specific shape statistics.

PubMed

Shi, Y; Qi, F; Xue, Z; Chen, L; Ito, K; Matsuo, H; Shen, D

2008-04-01

This paper presents a new deformable model using both population-based and patient-specific shape statistics to segment lung fields from serial chest radiographs. There are two novelties in the proposed deformable model. First, a modified scale invariant feature transform (SIFT) local descriptor, which is more distinctive than the general intensity and gradient features, is used to characterize the image features in the vicinity of each pixel. Second, the deformable contour is constrained by both population-based and patient-specific shape statistics, and it yields more robust and accurate segmentation of lung fields for serial chest radiographs. In particular, for segmenting the initial time-point images, the population-based shape statistics is used to constrain the deformable contour; as more subsequent images of the same patient are acquired, the patient-specific shape statistics online collected from the previous segmentation results gradually takes more roles. Thus, this patient-specific shape statistics is updated each time when a new segmentation result is obtained, and it is further used to refine the segmentation results of all the available time-point images. Experimental results show that the proposed method is more robust and accurate than other active shape models in segmenting the lung fields from serial chest radiographs.

Comparison of parameter-adapted segmentation methods for fluorescence micrographs.

PubMed

Held, Christian; Palmisano, Ralf; Häberle, Lothar; Hensel, Michael; Wittenberg, Thomas

2011-11-01

Interpreting images from fluorescence microscopy is often a time-consuming task with poor reproducibility. Various image processing routines that can help investigators evaluate the images are therefore useful. The critical aspect for a reliable automatic image analysis system is a robust segmentation algorithm that can perform accurate segmentation for different cell types. In this study, several image segmentation methods were therefore compared and evaluated in order to identify the most appropriate segmentation schemes that are usable with little new parameterization and robustly with different types of fluorescence-stained cells for various biological and biomedical tasks. The study investigated, compared, and enhanced four different methods for segmentation of cultured epithelial cells. The maximum-intensity linking (MIL) method, an improved MIL, a watershed method, and an improved watershed method based on morphological reconstruction were used. Three manually annotated datasets consisting of 261, 817, and 1,333 HeLa or L929 cells were used to compare the different algorithms. The comparisons and evaluations showed that the segmentation performance of methods based on the watershed transform was significantly superior to the performance of the MIL method. The results also indicate that using morphological opening by reconstruction can improve the segmentation of cells stained with a marker that exhibits the dotted surface of cells. Copyright © 2011 International Society for Advancement of Cytometry.

In-situ tissue regeneration through SDF-1α driven cell recruitment and stiffness-mediated bone regeneration in a critical-sized segmental femoral defect.

PubMed

Cipitria, Amaia; Boettcher, Kathrin; Schoenhals, Sophia; Garske, Daniela S; Schmidt-Bleek, Katharina; Ellinghaus, Agnes; Dienelt, Anke; Peters, Anja; Mehta, Manav; Madl, Christopher M; Huebsch, Nathaniel; Mooney, David J; Duda, Georg N

2017-09-15

In-situ tissue regeneration aims to utilize the body's endogenous healing capacity through the recruitment of host stem or progenitor cells to an injury site. Stromal cell-derived factor-1α (SDF-1α) is widely discussed as a potent chemoattractant. Here we use a cell-free biomaterial-based approach to (i) deliver SDF-1α for the recruitment of endogenous bone marrow-derived stromal cells (BMSC) into a critical-sized segmental femoral defect in rats and to (ii) induce hydrogel stiffness-mediated osteogenic differentiation in-vivo. Ionically crosslinked alginate hydrogels with a stiffness optimized for osteogenic differentiation were used. Fast-degrading porogens were incorporated to impart a macroporous architecture that facilitates host cell invasion. Endogenous cell recruitment to the defect site was successfully triggered through the controlled release of SDF-1α. A trend for increased bone volume fraction (BV/TV) and a significantly higher bone mineral density (BMD) were observed for gels loaded with SDF-1α, compared to empty gels at two weeks. A trend was also observed, albeit not statistically significant, towards matrix stiffness influencing BV/TV and BMD at two weeks. However, over a six week time-frame, these effects were insufficient for bone bridging of a segmental femoral defect. While mechanical cues combined with ex-vivo cell encapsulation have been shown to have an effect in the regeneration of less demanding in-vivo models, such as cranial defects of nude rats, they are not sufficient for a SDF-1α mediated in-situ regeneration approach in segmental femoral defects of immunocompetent rats, suggesting that additional osteogenic cues may also be required. Stromal cell-derived factor-1α (SDF-1α) is a chemoattractant used to recruit host cells for tissue regeneration. The concept that matrix stiffness can direct mesenchymal stromal cell (MSC) differentiation into various lineages was described a decade ago using in-vitro experiments. Recently, alginate hydrogels with an optimized stiffness and ex-vivo encapsulated MSCs were shown to have an effect in the regeneration of skull defects of nude rats. Here, we apply this material system, loaded with SDF-1α and without encapsulated MSCs, to (i) recruit endogenous cells and (ii) induce stiffness-mediated osteogenic differentiation in-vivo, using as model system a load-bearing femoral defect in immunocompetent rats. While a cell-free approach is of great interest from a translational perspective, the current limitations are described. Copyright © 2017 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Development of a Three-Dimensional (3D) Printed Biodegradable Cage to Convert Morselized Corticocancellous Bone Chips into a Structured Cortical Bone Graft.

PubMed

Chou, Ying-Chao; Lee, Demei; Chang, Tzu-Min; Hsu, Yung-Heng; Yu, Yi-Hsun; Liu, Shih-Jung; Ueng, Steve Wen-Neng

2016-04-20

This study aimed to develop a new biodegradable polymeric cage to convert corticocancellous bone chips into a structured strut graft for treating segmental bone defects. A total of 24 adult New Zealand white rabbits underwent a left femoral segmental bone defect creation. Twelve rabbits in group A underwent three-dimensional (3D) printed cage insertion, corticocancellous chips implantation, and Kirschner-wire (K-wire) fixation, while the other 12 rabbits in group B received bone chips implantation and K-wire fixation only. All rabbits received a one-week activity assessment and the initial image study at postoperative 1 week. The final image study was repeated at postoperative 12 or 24 weeks before the rabbit scarification procedure on schedule. After the animals were sacrificed, both femurs of all the rabbits were prepared for leg length ratios and 3-point bending tests. The rabbits in group A showed an increase of activities during the first week postoperatively and decreased anterior cortical disruptions in the postoperative image assessments. Additionally, higher leg length ratios and 3-point bending strengths demonstrated improved final bony ingrowths within the bone defects for rabbits in group A. In conclusion, through this bone graft converting technique, orthopedic surgeons can treat segmental bone defects by using bone chips but with imitate characters of structured cortical bone graft.

Development of a Three-Dimensional (3D) Printed Biodegradable Cage to Convert Morselized Corticocancellous Bone Chips into a Structured Cortical Bone Graft

PubMed Central

Chou, Ying-Chao; Lee, Demei; Chang, Tzu-Min; Hsu, Yung-Heng; Yu, Yi-Hsun; Liu, Shih-Jung; Ueng, Steve Wen-Neng

2016-01-01

This study aimed to develop a new biodegradable polymeric cage to convert corticocancellous bone chips into a structured strut graft for treating segmental bone defects. A total of 24 adult New Zealand white rabbits underwent a left femoral segmental bone defect creation. Twelve rabbits in group A underwent three-dimensional (3D) printed cage insertion, corticocancellous chips implantation, and Kirschner-wire (K-wire) fixation, while the other 12 rabbits in group B received bone chips implantation and K-wire fixation only. All rabbits received a one-week activity assessment and the initial image study at postoperative 1 week. The final image study was repeated at postoperative 12 or 24 weeks before the rabbit scarification procedure on schedule. After the animals were sacrificed, both femurs of all the rabbits were prepared for leg length ratios and 3-point bending tests. The rabbits in group A showed an increase of activities during the first week postoperatively and decreased anterior cortical disruptions in the postoperative image assessments. Additionally, higher leg length ratios and 3-point bending strengths demonstrated improved final bony ingrowths within the bone defects for rabbits in group A. In conclusion, through this bone graft converting technique, orthopedic surgeons can treat segmental bone defects by using bone chips but with imitate characters of structured cortical bone graft. PMID:27104525

Prevalence and pattern of abnormal myocardial perfusion in patients with isolated coronary artery ectasia: study by 99mTc-sestamibi radionuclide scintigraphy.

PubMed

Ismail, Ahmed M; Rayan, Mona; Adel, Amr; Demerdash, Salah; Atef, Mohamed; Abdallah, Mohamed; Nammas, Wail

2014-02-01

We explored the prevalence and pattern of abnormal myocardial perfusion in patients with isolated coronary artery ectasia (CAE), as demonstrated by (99m)Tc-sestamibi scintigraphy. Prospectively, we enrolled 35 patients with angiographically documented CAE and no significant coronary obstruction, who underwent elective coronary angiography. Patients underwent Stress-rest (99m)Tc-sestamibi scintigraphy within 4 days of coronary angiography. They were divided into 2 groups: group I: with normal perfusion scan; and group II: with reversible perfusion defects. The mean age was 49.6 ± 6.9 years; 34 (97.1 %) were males. Seventy-nine (75.2 %) arteries were affected by CAE. Among 79 arteries affected by CAE, affection was diffuse in 37 (46.8 %). Thirteen (37.1 %) patients had normal perfusion scan (group I), whereas 22 (62.9 %) had reversible perfusion defects (group II). Among 22 patients with reversible perfusion defects, 20 (90.9 %) had mild and 2 (9.1 %) had moderate ischemia. Among 49 myocardial segments with reversible perfusion defects, 22 (44.9 %) were basal, 18 (36.7 %) mid-, and 9 (18.4 %) apical segments. Diffuse CAE was significantly more prevalent in group II versus group I, in all 3 major coronary arteries (p < 0.05 for all). In patients with isolated CAE who underwent elective coronary angiography, reversible perfusion defects demonstrated by (99m)Tc-sestamibi scintigraphy were rather prevalent, mostly mild, more likely to affect the basal and mid-segments of the myocardium, and more frequently associated with diffuse ectasia.

Laparoscopic ureteral reimplantation with Boari flap for the management of long- segment ureteral defect: A case series with review of the literature

PubMed Central

Bansal, Ankur; Sinha, Rahul Janak; Jhanwar, Ankur; Prakash, Gaurav; Purkait, Bimalesh; Singh, Vishwajeet

2017-01-01

Objective The incidence of ureteral stricture is showing a rising trend due to increased use of laparoscopic and upper urinary tract endoscopic procedures. Boari flap is the preferred method of repairing long- segment ureteral defects of 8–12 cm. The procedure has undergone change from classical open (transperitoneal and retroperitoneal) method to laparoscopic surgery and recently robotic surgery. Laparoscopic approach is cosmetically appealing, less morbid and with shorter hospital stay. In this case series, we report our experience of performing laparoscopic ureteral reimplantation with Boari flap in 3 patients. Material and methods This prospective study was conducted between January 2011 December 2014. The patients with a long- segment ureteral defect who had undergone laparoscopic Boari flap reconstruction were included in the study. Outcome of laparoscopic ureteral reimplantation with Boari flap for the manangement of long segment ureteral defect was evaluated. Results The procedure was performed on 3 patients, and male to female ratio was 1:2. One patient had bilateral and other two patient had left ureteral stricture. The mean length of ureteral stricture was 8.6 cm (range 8.2–9.2 cm). The mean operative time was 206 min (190 to 220 min). The average estimated blood loss was 100 mL (range 90–110 mL) and mean hospital stay was 6 days (range 5 to 7 days). The mean follow up was 19 months (range 17–22 months). None of the patients experienced any complication related to the procedure in perioperative period. Conclusion Laparoscopic ureteral reimplantation with Boari flap is safe, feasible and has excellent long term results. However, the procedure is technically challenging, requires extensive experience of intracorporeal suturing. PMID:28861304

Laparoscopic ureteral reimplantation with Boari flap for the management of long- segment ureteral defect: A case series with review of the literature.

PubMed

Bansal, Ankur; Sinha, Rahul Janak; Jhanwar, Ankur; Prakash, Gaurav; Purkait, Bimalesh; Singh, Vishwajeet

2017-09-01

The incidence of ureteral stricture is showing a rising trend due to increased use of laparoscopic and upper urinary tract endoscopic procedures. Boari flap is the preferred method of repairing long- segment ureteral defects of 8-12 cm. The procedure has undergone change from classical open (transperitoneal and retroperitoneal) method to laparoscopic surgery and recently robotic surgery. Laparoscopic approach is cosmetically appealing, less morbid and with shorter hospital stay. In this case series, we report our experience of performing laparoscopic ureteral reimplantation with Boari flap in 3 patients. This prospective study was conducted between January 2011 December 2014. The patients with a long- segment ureteral defect who had undergone laparoscopic Boari flap reconstruction were included in the study. Outcome of laparoscopic ureteral reimplantation with Boari flap for the manangement of long segment ureteral defect was evaluated. The procedure was performed on 3 patients, and male to female ratio was 1:2. One patient had bilateral and other two patient had left ureteral stricture. The mean length of ureteral stricture was 8.6 cm (range 8.2-9.2 cm). The mean operative time was 206 min (190 to 220 min). The average estimated blood loss was 100 mL (range 90-110 mL) and mean hospital stay was 6 days (range 5 to 7 days). The mean follow up was 19 months (range 17-22 months). None of the patients experienced any complication related to the procedure in perioperative period. Laparoscopic ureteral reimplantation with Boari flap is safe, feasible and has excellent long term results. However, the procedure is technically challenging, requires extensive experience of intracorporeal suturing.

All Internal Segmental Bone Transport and Optional Lengthening With a Newly Developed Universal Cylinder-Kombi-Tube Module for Motorized Nails-Description of a Surgical Technique.

PubMed

Krettek, Christian; El Naga, Ashraf

2017-10-01

Segmental transport is an effective method of treatment for segmental defects, but the need for external fixation during the transport phase is a disadvantage. To avoid external fixation, we have developed a Cylinder-Kombi-Tube Segmental Transport (CKTST) module for combination with a commercially available motorized lengthening nail. This CKTST module allows for an all-internal segmental bone transport and also allows for optional lengthening if needed. The concept and surgical technique of CKTST are described and illustrated with a clinical case.

Computer object segmentation by nonlinear image enhancement, multidimensional clustering, and geometrically constrained contour optimization

NASA Astrophysics Data System (ADS)

Bruynooghe, Michel M.

1998-04-01

In this paper, we present a robust method for automatic object detection and delineation in noisy complex images. The proposed procedure is a three stage process that integrates image segmentation by multidimensional pixel clustering and geometrically constrained optimization of deformable contours. The first step is to enhance the original image by nonlinear unsharp masking. The second step is to segment the enhanced image by multidimensional pixel clustering, using our reducible neighborhoods clustering algorithm that has a very interesting theoretical maximal complexity. Then, candidate objects are extracted and initially delineated by an optimized region merging algorithm, that is based on ascendant hierarchical clustering with contiguity constraints and on the maximization of average contour gradients. The third step is to optimize the delineation of previously extracted and initially delineated objects. Deformable object contours have been modeled by cubic splines. An affine invariant has been used to control the undesired formation of cusps and loops. Non linear constrained optimization has been used to maximize the external energy. This avoids the difficult and non reproducible choice of regularization parameters, that are required by classical snake models. The proposed method has been applied successfully to the detection of fine and subtle microcalcifications in X-ray mammographic images, to defect detection by moire image analysis, and to the analysis of microrugosities of thin metallic films. The later implementation of the proposed method on a digital signal processor associated to a vector coprocessor would allow the design of a real-time object detection and delineation system for applications in medical imaging and in industrial computer vision.

Fabric defect detection based on visual saliency using deep feature and low-rank recovery

NASA Astrophysics Data System (ADS)

Liu, Zhoufeng; Wang, Baorui; Li, Chunlei; Li, Bicao; Dong, Yan

2018-04-01

Fabric defect detection plays an important role in improving the quality of fabric product. In this paper, a novel fabric defect detection method based on visual saliency using deep feature and low-rank recovery was proposed. First, unsupervised training is carried out by the initial network parameters based on MNIST large datasets. The supervised fine-tuning of fabric image library based on Convolutional Neural Networks (CNNs) is implemented, and then more accurate deep neural network model is generated. Second, the fabric images are uniformly divided into the image block with the same size, then we extract their multi-layer deep features using the trained deep network. Thereafter, all the extracted features are concentrated into a feature matrix. Third, low-rank matrix recovery is adopted to divide the feature matrix into the low-rank matrix which indicates the background and the sparse matrix which indicates the salient defect. In the end, the iterative optimal threshold segmentation algorithm is utilized to segment the saliency maps generated by the sparse matrix to locate the fabric defect area. Experimental results demonstrate that the feature extracted by CNN is more suitable for characterizing the fabric texture than the traditional LBP, HOG and other hand-crafted features extraction method, and the proposed method can accurately detect the defect regions of various fabric defects, even for the image with complex texture.

Fast and robust brain tumor segmentation using level set method with multiple image information.

PubMed

Lok, Ka Hei; Shi, Lin; Zhu, Xianlun; Wang, Defeng

2017-01-01

Brain tumor segmentation is a challenging task for its variation in intensity. The phenomenon is caused by the inhomogeneous content of tumor tissue and the choice of imaging modality. In 2010 Zhang developed the Selective Binary Gaussian Filtering Regularizing Level Set (SBGFRLS) model that combined the merits of edge-based and region-based segmentation. To improve the SBGFRLS method by modifying the singed pressure force (SPF) term with multiple image information and demonstrate effectiveness of proposed method on clinical images. In original SBGFRLS model, the contour evolution direction mainly depends on the SPF. By introducing a directional term in SPF, the metric could control the evolution direction. The SPF is altered by statistic values enclosed by the contour. This concept can be extended to jointly incorporate multiple image information. The new SPF term is expected to bring a solution for blur edge problem in brain tumor segmentation. The proposed method is validated with clinical images including pre- and post-contrast magnetic resonance images. The accuracy and robustness is compared with sensitivity, specificity, DICE similarity coefficient and Jaccard similarity index. Experimental results show improvement, in particular the increase of sensitivity at the same specificity, in segmenting all types of tumors except for the diffused tumor. The novel brain tumor segmentation method is clinical-oriented with fast, robust and accurate implementation and a minimal user interaction. The method effectively segmented homogeneously enhanced, non-enhanced, heterogeneously-enhanced, and ring-enhanced tumor under MR imaging. Though the method is limited by identifying edema and diffuse tumor, several possible solutions are suggested to turn the curve evolution into a fully functional clinical diagnosis tool.

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.

Osteogenic effect of a gastric pentadecapeptide, BPC-157, on the healing of segmental bone defect in rabbits: a comparison with bone marrow and autologous cortical bone implantation.

PubMed

Sebecić, B; Nikolić, V; Sikirić, P; Seiwerth, S; Sosa, T; Patrlj, L; Grabarević, Z; Rucman, R; Petek, M; Konjevoda, P; Jadrijević, S; Perović, D; Slaj, M

1999-03-01

Gastrectomy often results in increased likelihood of osteoporosis, metabolic aberration, and risk of fracture, and there is a need for a gastric peptide with osteogenic activity. A novel stomach pentadecapeptide, BPC-157, improves wound and fracture healing in rats in addition to having an angiogenic effect. Therefore, in the present study, using a segmental osteoperiosteal bone defect (0.8 cm, in the middle of the left radius) that remained incompletely healed in all control rabbits for 6 weeks (assessed in 2 week intervals), pentadecapeptide BPC-157 was further studied (either percutaneously given locally [10 microg/kg body weight] into the bone defect, or applied intramuscularly [intermittently, at postoperative days 7, 9, 14, and 16 at 10 microg/kg body weight] or continuously [once per day, postoperative days 7-21 at 10 microg or 10 ng/kg body weight]). For comparison, rabbits percutaneously received locally autologous bone marrow (2 mL, postoperative day 7). As standard treatment, immediately after its formation, the bone defect was filled with an autologous cortical graft. Saline-treated (2 mL intramuscularly [i.m.] and 2 mL locally into the bone defect), injured animals were used as controls. Pentadecapeptide BPC-157 significantly improved the healing of segmental bone defects. For instance, upon radiographic assessment, the callus surface, microphotodensitometry, quantitative histomorphometry (10 microg/kg body weight i.m. for 14 days), or quantitative histomorphometry (10 ng/kg body weight i.m. for 14 days) the effect of pentadecapeptide BPC-157 was shown to correspond to improvement after local application of bone marrow or autologous cortical graft. Moreover, a comparison of the number of animals with unhealed defects (all controls) or healed defects (complete bony continuity across the defect site) showed that besides pentadecapeptide intramuscular application for 14 days (i.e., local application of bone marrow or autologous cortical graft), also following other pentadecapeptide BPC-157 regimens (local application, or intermittent intramuscular administration), the number of animals with healed defect was increased. Hopefully, in the light of the suggested stomach significance for bone homeostasis, the possible relevance of this pentadecapeptide BPC-157 effect (local or intramuscular effectiveness, lack of unwanted effects) could be a basis for methods of choice in the future management of healing impairment in humans, and requires further investigation.

Physics-Based Image Segmentation Using First Order Statistical Properties and Genetic Algorithm for Inductive Thermography Imaging.

PubMed

Gao, Bin; Li, Xiaoqing; Woo, Wai Lok; Tian, Gui Yun

2018-05-01

Thermographic inspection has been widely applied to non-destructive testing and evaluation with the capabilities of rapid, contactless, and large surface area detection. Image segmentation is considered essential for identifying and sizing defects. To attain a high-level performance, specific physics-based models that describe defects generation and enable the precise extraction of target region are of crucial importance. In this paper, an effective genetic first-order statistical image segmentation algorithm is proposed for quantitative crack detection. The proposed method automatically extracts valuable spatial-temporal patterns from unsupervised feature extraction algorithm and avoids a range of issues associated with human intervention in laborious manual selection of specific thermal video frames for processing. An internal genetic functionality is built into the proposed algorithm to automatically control the segmentation threshold to render enhanced accuracy in sizing the cracks. Eddy current pulsed thermography will be implemented as a platform to demonstrate surface crack detection. Experimental tests and comparisons have been conducted to verify the efficacy of the proposed method. In addition, a global quantitative assessment index F-score has been adopted to objectively evaluate the performance of different segmentation algorithms.

Automated Robust Image Segmentation: Level Set Method Using Nonnegative Matrix Factorization with Application to Brain MRI.

PubMed

Dera, Dimah; Bouaynaya, Nidhal; Fathallah-Shaykh, Hassan M

2016-07-01

We address the problem of fully automated region discovery and robust image segmentation by devising a new deformable model based on the level set method (LSM) and the probabilistic nonnegative matrix factorization (NMF). We describe the use of NMF to calculate the number of distinct regions in the image and to derive the local distribution of the regions, which is incorporated into the energy functional of the LSM. The results demonstrate that our NMF-LSM method is superior to other approaches when applied to synthetic binary and gray-scale images and to clinical magnetic resonance images (MRI) of the human brain with and without a malignant brain tumor, glioblastoma multiforme. In particular, the NMF-LSM method is fully automated, highly accurate, less sensitive to the initial selection of the contour(s) or initial conditions, more robust to noise and model parameters, and able to detect as small distinct regions as desired. These advantages stem from the fact that the proposed method relies on histogram information instead of intensity values and does not introduce nuisance model parameters. These properties provide a general approach for automated robust region discovery and segmentation in heterogeneous images. Compared with the retrospective radiological diagnoses of two patients with non-enhancing grade 2 and 3 oligodendroglioma, the NMF-LSM detects earlier progression times and appears suitable for monitoring tumor response. The NMF-LSM method fills an important need of automated segmentation of clinical MRI.

Improving bone repair of femoral and radial defects in rabbit by incorporating PRP into PLGA/CPC composite scaffold with unidirectional pore structure.

PubMed

He, Fupo; Chen, Yan; Li, Jiyan; Lin, Bomiao; Ouyang, Yi; Yu, Bo; Xia, Yuanyou; Yu, Bo; Ye, Jiandong

2015-04-01

In this study, a platelet-rich plasma poly(lactic-co-glycolic acid) (PRP-PLGA)/calcium phosphate cement (CPC) composite scaffold was prepared by incorporating PRP into PLGA/CPC scaffold with unidirectional pore structure, which was fabricated by the unidirectional freeze casting of CPC slurry and the following infiltration of PLGA. The results from in vitro cell experiments and in vivo implantation in femoral defects manifested that incorporation of PRP into PLGA/CPC scaffold improved in vitro cell response (cell attachment, proliferation, and differentiation), and markedly boosted bone formation, angiogenesis and material degradation. The incorporation of PRP into scaffold showed more outstanding improvement in osteogenesis as the scaffolds were used to repair the segmental radial defects, especially at the early stage. The new bone tissues grew along the unidirectional lamellar pores of scaffold. At 12 weeks postimplantation, the segmental radial defects treated with PRP-PLGA/CPC scaffold had almost recuperated, whereas treated with the scaffold without PRP was far from healed. Taken together, the PRP-PLGA/CPC scaffold with unidirectional pore structure is a promising candidate to repair bone defects at various sites. © 2014 Wiley Periodicals, Inc.

Torque test measurement in segmental bone defects using porous calcium phosphate cement implants.

PubMed

Kroese-Deutman, Henriette C; Wolke, Joop G C; Spauwen, Paul H M; Jansen, John A

2010-10-01

This study was performed to assess the bone healing supporting characteristics of porous calcium phosphate (Ca-P) cement when implanted in a rabbit segmental defect model as well as to determine the reliability of torque testing as a method to verify bone healing. The middiaphyseal radius was chosen as the area to create bilaterally increasing defect sizes (5, 10, and 15 mm), which were either filled with porous Ca-P cement or left open as a control. After 12 weeks of implantation, torque test measurements as well as histological and radiographic evaluation were performed. In two of the open 15 mm control defects, bone bridging was visible at the radiographic and histological evaluation. Bone was observed to be present in all porous Ca-P cement implants (5, 10, and 15 mm defects) after 12 weeks. No significant differences in torque measurements were observed between the 5 and 10 mm filled and open control defects using a t-test. In addition, the mechanical strength of all operated specimens was similar compared with nonoperated bone samples. The torsion data for the 15 mm open defect appeared to be lower compared with the filled 15 mm defect, but no significant difference could be proven. Within the limitation of the study design, porous Ca-P cement implants demonstrated osteoconductive properties and confirmed to be a suitable scaffold material in a weight-bearing situation. Further, the used torque testing method was found to be unreliable for testing the mechanical properties of the healed bone defect.

Robust keyword retrieval method for OCRed text

NASA Astrophysics Data System (ADS)

Fujii, Yusaku; Takebe, Hiroaki; Tanaka, Hiroshi; Hotta, Yoshinobu

2011-01-01

Document management systems have become important because of the growing popularity of electronic filing of documents and scanning of books, magazines, manuals, etc., through a scanner or a digital camera, for storage or reading on a PC or an electronic book. Text information acquired by optical character recognition (OCR) is usually added to the electronic documents for document retrieval. Since texts generated by OCR generally include character recognition errors, robust retrieval methods have been introduced to overcome this problem. In this paper, we propose a retrieval method that is robust against both character segmentation and recognition errors. In the proposed method, the insertion of noise characters and dropping of characters in the keyword retrieval enables robustness against character segmentation errors, and character substitution in the keyword of the recognition candidate for each character in OCR or any other character enables robustness against character recognition errors. The recall rate of the proposed method was 15% higher than that of the conventional method. However, the precision rate was 64% lower.

Color normalization for robust evaluation of microscopy images

NASA Astrophysics Data System (ADS)

Švihlík, Jan; Kybic, Jan; Habart, David

2015-09-01

This paper deals with color normalization of microscopy images of Langerhans islets in order to increase robustness of the islet segmentation to illumination changes. The main application is automatic quantitative evaluation of the islet parameters, useful for determining the feasibility of islet transplantation in diabetes. First, background illumination inhomogeneity is compensated and a preliminary foreground/background segmentation is performed. The color normalization itself is done in either lαβ or logarithmic RGB color spaces, by comparison with a reference image. The color-normalized images are segmented using color-based features and pixel-wise logistic regression, trained on manually labeled images. Finally, relevant statistics such as the total islet area are evaluated in order to determine the success likelihood of the transplantation.

[PHACES syndrome].

PubMed

Morcillo Azcárate, J; Bernabeu-Wittel, J; Fernández-Pineda, I; Conejo-Mir, M D; Tuduri Limousin, I; Aspiazu Salinas, D A; de Agustín Asensio, J C

2010-04-01

PHACES syndrome associates a segmental facial hemangioma with cerebral malformations, aortic branches/cranial arteries anomalies, cardiac defects, eye anomalies or ventral wall defects. The aim of this study is to analyze our experience with this syndrome. Retrospective study of the cases seen at our unit in the last year. We treat 4 cases; 3 girls and 1 child. Besides the segmental hemangioma they presented: 3 vascular cerebral malformations; 2 structural cardiopathies; 2 cerebral malformations, 1 microftalmia. We did not find ventral wall defects. A case received treatment with two cycles of metilprednisolone i.v. and oral prednisone, with favourable course; two cases received initial treatment with oral prednisone continued of oral propanolol in rising pattern up to 2 mg/kg/day, Obtaining both the detention of the tumour growth and regression of the lesion, with very good tolerance. A 7-year-old patient has been treated with colouring pulse laser for her residual lesions. When we see a segmental facial hemangioma we must perform a wide diagnostic study in order to discard a PHACES syndrome. Multidisciplinar approach to the patient by a wide expert's group gets an earlier diagnose and improves the outcome. Propranolol is a promising therapeutic alternative.

Use of Adipose Derived Stem Cells to Treat Large Bone Defects. Addendum

DTIC Science & Technology

2009-07-01

optimal delivery . We have also completed characterization of our segmental defect model, including analysis of vascular ingrowth during defect healing...cells seeded in 1.2% Keltone alginate at a density of 12-15x106cells/ml were loaded on 24-well transwell insert membranes [6]. Once hydrogel discs...process from tissue culture plates and hydrogels does not alter the surface phenotype. Gene expression of surface markers and proteins associated with

Structure Formation in Solutions of Rigid Polymers Undergoing a Phase Transition

DTIC Science & Technology

1987-04-01

cyclohexene dioxide (ERL-4206) - 10 g. nonenyl succinic anhydride (NSA) - 26 g. dimethyl amino ethanol ( DMAE ) - 0.4 g. After infiltration, short segments...existence of a significant number of defects within the individual microfibril. The presence of defects in the lateral packing of PBT chains is also suggested...of the D- and L- enantiomers yields a nematic phase. The ordered phases exhi- bit complex textures due to defects (disclinations) which depend on

Optimization of Soft Tissue Management, Spacer Design, and Grafting Strategies for Large Segmental Bone Defects using the Chronic Caprine Tibial Defect Model

DTIC Science & Technology

2016-12-01

gastrocnemius muscles. 4. Place an interlocking intramedullary nail using a custom spacer to maintain 5-cm defect length. 5. Place a pre-molded 5 cm long x...2 cm diameter PMMA spacer around the nail in the defect. 6. Irrigate the wound with normal (0.9 %) saline and close the wound. The Treatment...PMMA spacer using a “bomb bay door opening”. 4. Remove the spacer without damaging the membrane or nail . 5. Collect appropriate IM samples as

Cerebro-costo-mandibular Syndrome

PubMed Central

McNicholl, B.; Egan-Mitchell, B.; Murray, J. P.; Doyle, J. F.; Kennedy, J. D.; Crome, L.

1970-01-01

Three sibs with a hitherto unreported syndrome are described, the main features being mental handicap, palatal defects, micrognathia, and severe costovertebral defects, involving segmentation of most ribs and fusion of their dorsal ends to the vertebral bodies. In addition one infant had hypoplasia of an elbow together with defects of sacrum and coccyx; she and one other sib had minor dental defects. The syndrome is potentially lethal in the neonatal period; one of the sibs has survived. The inheritance is probably autosomal recessive. ImagesFIG. 1FIG. 2FIG. 3FIG. 4 PMID:5427859

The influence of defects of the fatigue resistance of butt and girth welds in A106B steel

NASA Technical Reports Server (NTRS)

Leis, B. N.; Goetz, D. P.; Scott, P. M.

1986-01-01

This three-phase study was directed at developing a fitness for service defect acceptance criteria for welds with defect indications. The study focussed on A106 Gr. B steel pipe. The first phase involved a literature search and critical review to develop the preliminary acceptance criteria to the extent permitted by the data. The second phase developed data for flat plate, wall segment, and vessel specimens containing artificial or natural planar or volumetric defects. The final phase developed acceptance criteria from the test data.

Intensity compensation for on-line detection of defects on fruit

NASA Astrophysics Data System (ADS)

Wen, Zhiqing; Tao, Yang

1997-10-01

A machine-vision sorting system was developed that utilizes the difference in light reflectance of fruit surfaces to distinguish the defective and good apples. To accommodate to the spherical reflectance characteristics of fruit with curved surface like apple, a spherical transform algorithm was developed that converts the original image to a non-radiant image without losing defective segments on the fruit. To prevent high-quality dark-colored fruit form being classified into the defective class and increase the defect detection rate for light-colored fruit, an intensity compensation method using maximum propagation was used. Experimental results demonstrated the effectiveness of the method based on maximum propagation and spherical transform for on-line detection of defects on apples.

Automated epidermis segmentation in histopathological images of human skin stained with hematoxylin and eosin

NASA Astrophysics Data System (ADS)

Kłeczek, Paweł; Dyduch, Grzegorz; Jaworek-Korjakowska, Joanna; Tadeusiewicz, Ryszard

2017-03-01

Background: Epidermis area is an important observation area for the diagnosis of inflammatory skin diseases and skin cancers. Therefore, in order to develop a computer-aided diagnosis system, segmentation of the epidermis area is usually an essential, initial step. This study presents an automated and robust method for epidermis segmentation in whole slide histopathological images of human skin, stained with hematoxylin and eosin. Methods: The proposed method performs epidermis segmentation based on the information about shape and distribution of transparent regions in a slide image and information about distribution and concentration of hematoxylin and eosin stains. It utilizes domain-specific knowledge of morphometric and biochemical properties of skin tissue elements to segment the relevant histopathological structures in human skin. Results: Experimental results on 88 skin histopathological images from three different sources show that the proposed method segments the epidermis with a mean sensitivity of 87 %, a mean specificity of 95% and a mean precision of 57%. It is robust to inter- and intra-image variations in both staining and illumination, and makes no assumptions about the type of skin disorder. The proposed method provides a superior performance compared to the existing techniques.

A flexible and robust approach for segmenting cell nuclei from 2D microscopy images using supervised learning and template matching

PubMed Central

Chen, Cheng; Wang, Wei; Ozolek, John A.; Rohde, Gustavo K.

2013-01-01

We describe a new supervised learning-based template matching approach for segmenting cell nuclei from microscopy images. The method uses examples selected by a user for building a statistical model which captures the texture and shape variations of the nuclear structures from a given dataset to be segmented. Segmentation of subsequent, unlabeled, images is then performed by finding the model instance that best matches (in the normalized cross correlation sense) local neighborhood in the input image. We demonstrate the application of our method to segmenting nuclei from a variety of imaging modalities, and quantitatively compare our results to several other methods. Quantitative results using both simulated and real image data show that, while certain methods may work well for certain imaging modalities, our software is able to obtain high accuracy across several imaging modalities studied. Results also demonstrate that, relative to several existing methods, the template-based method we propose presents increased robustness in the sense of better handling variations in illumination, variations in texture from different imaging modalities, providing more smooth and accurate segmentation borders, as well as handling better cluttered nuclei. PMID:23568787

Automatic segmentation of the left ventricle cavity and myocardium in MRI data.

PubMed

Lynch, M; Ghita, O; Whelan, P F

2006-04-01

A novel approach for the automatic segmentation has been developed to extract the epi-cardium and endo-cardium boundaries of the left ventricle (lv) of the heart. The developed segmentation scheme takes multi-slice and multi-phase magnetic resonance (MR) images of the heart, transversing the short-axis length from the base to the apex. Each image is taken at one instance in the heart's phase. The images are segmented using a diffusion-based filter followed by an unsupervised clustering technique and the resulting labels are checked to locate the (lv) cavity. From cardiac anatomy, the closest pool of blood to the lv cavity is the right ventricle cavity. The wall between these two blood-pools (interventricular septum) is measured to give an approximate thickness for the myocardium. This value is used when a radial search is performed on a gradient image to find appropriate robust segments of the epi-cardium boundary. The robust edge segments are then joined using a normal spline curve. Experimental results are presented with very encouraging qualitative and quantitative results and a comparison is made against the state-of-the art level-sets method.

Automatic atlas-based three-label cartilage segmentation from MR knee images

PubMed Central

Shan, Liang; Zach, Christopher; Charles, Cecil; Niethammer, Marc

2016-01-01

Osteoarthritis (OA) is the most common form of joint disease and often characterized by cartilage changes. Accurate quantitative methods are needed to rapidly screen large image databases to assess changes in cartilage morphology. We therefore propose a new automatic atlas-based cartilage segmentation method for future automatic OA studies. Atlas-based segmentation methods have been demonstrated to be robust and accurate in brain imaging and therefore also hold high promise to allow for reliable and high-quality segmentations of cartilage. Nevertheless, atlas-based methods have not been well explored for cartilage segmentation. A particular challenge is the thinness of cartilage, its relatively small volume in comparison to surrounding tissue and the difficulty to locate cartilage interfaces – for example the interface between femoral and tibial cartilage. This paper focuses on the segmentation of femoral and tibial cartilage, proposing a multi-atlas segmentation strategy with non-local patch-based label fusion which can robustly identify candidate regions of cartilage. This method is combined with a novel three-label segmentation method which guarantees the spatial separation of femoral and tibial cartilage, and ensures spatial regularity while preserving the thin cartilage shape through anisotropic regularization. Our segmentation energy is convex and therefore guarantees globally optimal solutions. We perform an extensive validation of the proposed method on 706 images of the Pfizer Longitudinal Study. Our validation includes comparisons of different atlas segmentation strategies, different local classifiers, and different types of regularizers. To compare to other cartilage segmentation approaches we validate based on the 50 images of the SKI10 dataset. PMID:25128683

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.

Robust Classification and Segmentation of Planar and Linear Features for Construction Site Progress Monitoring and Structural Dimension Compliance Control

NASA Astrophysics Data System (ADS)

Maalek, R.; Lichti, D. D.; Ruwanpura, J.

2015-08-01

The application of terrestrial laser scanners (TLSs) on construction sites for automating construction progress monitoring and controlling structural dimension compliance is growing markedly. However, current research in construction management relies on the planned building information model (BIM) to assign the accumulated point clouds to their corresponding structural elements, which may not be reliable in cases where the dimensions of the as-built structure differ from those of the planned model and/or the planned model is not available with sufficient detail. In addition outliers exist in construction site datasets due to data artefacts caused by moving objects, occlusions and dust. In order to overcome the aforementioned limitations, a novel method for robust classification and segmentation of planar and linear features is proposed to reduce the effects of outliers present in the LiDAR data collected from construction sites. First, coplanar and collinear points are classified through a robust principal components analysis procedure. The classified points are then grouped using a robust clustering method. A method is also proposed to robustly extract the points belonging to the flat-slab floors and/or ceilings without performing the aforementioned stages in order to preserve computational efficiency. The applicability of the proposed method is investigated in two scenarios, namely, a laboratory with 30 million points and an actual construction site with over 150 million points. The results obtained by the two experiments validate the suitability of the proposed method for robust segmentation of planar and linear features in contaminated datasets, such as those collected from construction sites.

Fully-automated approach to hippocampus segmentation using a graph-cuts algorithm combined with atlas-based segmentation and morphological opening.

PubMed

Kwak, Kichang; Yoon, Uicheul; Lee, Dong-Kyun; Kim, Geon Ha; Seo, Sang Won; Na, Duk L; Shim, Hack-Joon; Lee, Jong-Min

2013-09-01

The hippocampus has been known to be an important structure as a biomarker for Alzheimer's disease (AD) and other neurological and psychiatric diseases. However, it requires accurate, robust and reproducible delineation of hippocampal structures. In this study, an automated hippocampal segmentation method based on a graph-cuts algorithm combined with atlas-based segmentation and morphological opening was proposed. First of all, the atlas-based segmentation was applied to define initial hippocampal region for a priori information on graph-cuts. The definition of initial seeds was further elaborated by incorporating estimation of partial volume probabilities at each voxel. Finally, morphological opening was applied to reduce false positive of the result processed by graph-cuts. In the experiments with twenty-seven healthy normal subjects, the proposed method showed more reliable results (similarity index=0.81±0.03) than the conventional atlas-based segmentation method (0.72±0.04). Also as for segmentation accuracy which is measured in terms of the ratios of false positive and false negative, the proposed method (precision=0.76±0.04, recall=0.86±0.05) produced lower ratios than the conventional methods (0.73±0.05, 0.72±0.06) demonstrating its plausibility for accurate, robust and reliable segmentation of hippocampus. Copyright © 2013 Elsevier Inc. All rights reserved.

Cerebral vessels segmentation for light-sheet microscopy image using convolutional neural networks

NASA Astrophysics Data System (ADS)

Hu, Chaoen; Hui, Hui; Wang, Shuo; Dong, Di; Liu, Xia; Yang, Xin; Tian, Jie

2017-03-01

Cerebral vessel segmentation is an important step in image analysis for brain function and brain disease studies. To extract all the cerebrovascular patterns, including arteries and capillaries, some filter-based methods are used to segment vessels. However, the design of accurate and robust vessel segmentation algorithms is still challenging, due to the variety and complexity of images, especially in cerebral blood vessel segmentation. In this work, we addressed a problem of automatic and robust segmentation of cerebral micro-vessels structures in cerebrovascular images acquired by light-sheet microscope for mouse. To segment micro-vessels in large-scale image data, we proposed a convolutional neural networks (CNNs) architecture trained by 1.58 million pixels with manual label. Three convolutional layers and one fully connected layer were used in the CNNs model. We extracted a patch of size 32x32 pixels in each acquired brain vessel image as training data set to feed into CNNs for classification. This network was trained to output the probability that the center pixel of input patch belongs to vessel structures. To build the CNNs architecture, a series of mouse brain vascular images acquired from a commercial light sheet fluorescence microscopy (LSFM) system were used for training the model. The experimental results demonstrated that our approach is a promising method for effectively segmenting micro-vessels structures in cerebrovascular images with vessel-dense, nonuniform gray-level and long-scale contrast regions.

An elementary quantum network using robust nuclear spin qubits in diamond

NASA Astrophysics Data System (ADS)

Kalb, Norbert; Reiserer, Andreas; Humphreys, Peter; Blok, Machiel; van Bemmelen, Koen; Twitchen, Daniel; Markham, Matthew; Taminiau, Tim; Hanson, Ronald

Quantum registers containing multiple robust qubits can form the nodes of future quantum networks for computation and communication. Information storage within such nodes must be resilient to any type of local operation. Here we demonstrate multiple robust memories by employing five nuclear spins adjacent to a nitrogen-vacancy defect centre in diamond. We characterize the storage of quantum superpositions and their resilience to entangling attempts with the electron spin of the defect centre. The storage fidelity is found to be limited by the probabilistic electron spin reset after failed entangling attempts. Control over multiple memories is then utilized to encode states in decoherence protected subspaces with increased robustness. Furthermore we demonstrate memory control in two optically linked network nodes and characterize the storage capabilities of both memories in terms of the process fidelity with the identity. These results pave the way towards multi-qubit quantum algorithms in a remote network setting.

Finite element analysis on the biomechanical stability of open porous titanium scaffolds for large segmental bone defects under physiological load conditions.

PubMed

Wieding, Jan; Souffrant, Robert; Mittelmeier, Wolfram; Bader, Rainer

2013-04-01

Repairing large segmental defects in long bones caused by fracture, tumour or infection is still a challenging problem in orthopaedic surgery. Artificial materials, i.e. titanium and its alloys performed well in clinical applications, are plenary available, and can be manufactured in a wide range of scaffold designs. Although the mechanical properties are determined, studies about the biomechanical behaviour under physiological loading conditions are rare. The goal of our numerical study was to determine the suitability of open-porous titanium scaffolds to act as bone scaffolds. Hence, the mechanical stability of fourteen different scaffold designs was characterized under both axial compression and biomechanical loading within a large segmental distal femoral defect of 30mm. This defect was stabilized with an osteosynthesis plate and physiological hip reaction forces as well as additional muscle forces were implemented to the femoral bone. Material properties of titanium scaffolds were evaluated from experimental testing. Scaffold porosity was varied between 64 and 80%. Furthermore, the amount of material was reduced up to 50%. Uniaxial compression testing revealed a structural modulus for the scaffolds between 3.5GPa and 19.1GPa depending on porosity and material consumption. The biomechanical testing showed defect gap alterations between 0.03mm and 0.22mm for the applied scaffolds and 0.09mm for the intact bone. Our results revealed that minimizing the amount of material of the inner core has a smaller influence than increasing the porosity when the scaffolds are loaded under biomechanical loading. Furthermore, an advanced scaffold design was found acting similar as the intact bone. Copyright © 2012 IPEM. Published by Elsevier Ltd. All rights reserved.

Anterior segment dysgenesis correlation with epithelial-mesenchymal transition in Smad4 knockout mice.

PubMed

Li, Jing; Qin, Yu; Zhao, Fang-Kun; Wu, Di; He, Xue-Fei; Liu, Jia; Zhao, Jiang-Yue; Zhang, Jin-Song

2016-01-01

To explore the molecular mechanisms in lens development and the pathogenesis of Peters anomaly in Smad4 defective mice. Le-Cre transgenic mouse line was employed to inactivate Smad4 in the surface ectoderm selectively. Pathological techniques were used to reveal the morphological changes of the anterior segment in Smad4 defective eye. Immunohistochemical staining was employed to observe the expression of E-cadherin, N-cadherin and α-SMA in anterior segment of Smad4 defective mice and control mice at embryonic (E) day 16.5. Real-time quantitative polymerase chain reaction (qPCR) was performed to detect the expression of Snail, Zeb1, Zeb2 and Twist2 in lens of Smad4 defective mice and control mice at E16.5. Statistical evaluations were performed using the unpaired Student's t-test (two-tailed) by SPSS 11.0 software. Conditional deletion of Smad4 on eye surface ectoderm resulted in corneal dysplasia, iridocorneal angle closure, corneolenticular adhesions and cataract resembling Peters anomaly. Loss of Smad4 function inhibited E-cadherin expression in the lens epithelium cells and corneal epithelium cells in Smad4 defective eye. Expression of N-cadherin was up-regulated in corneal epithelium and corneal stroma. Both E-cadherin and N-cadherin were down-regulated at the future trabecular meshwork region in mutant eye. The qPCR results showed that the expression of Twist2 was increased significantly in the mutant lens (P<0.01). Smad4 is essential to eye development and likely a candidate pathogenic gene to Peters anomaly by regulating epithelial-mesenchymal transition. Twist2 can be regulated by Smad4 and plays an essential role in lens development.

Automatic segmentation of multimodal brain tumor images based on classification of super-voxels.

PubMed

Kadkhodaei, M; Samavi, S; Karimi, N; Mohaghegh, H; Soroushmehr, S M R; Ward, K; All, A; Najarian, K

2016-08-01

Despite the rapid growth in brain tumor segmentation approaches, there are still many challenges in this field. Automatic segmentation of brain images has a critical role in decreasing the burden of manual labeling and increasing robustness of brain tumor diagnosis. We consider segmentation of glioma tumors, which have a wide variation in size, shape and appearance properties. In this paper images are enhanced and normalized to same scale in a preprocessing step. The enhanced images are then segmented based on their intensities using 3D super-voxels. Usually in images a tumor region can be regarded as a salient object. Inspired by this observation, we propose a new feature which uses a saliency detection algorithm. An edge-aware filtering technique is employed to align edges of the original image to the saliency map which enhances the boundaries of the tumor. Then, for classification of tumors in brain images, a set of robust texture features are extracted from super-voxels. Experimental results indicate that our proposed method outperforms a comparable state-of-the-art algorithm in term of dice score.

Multiscale CNNs for Brain Tumor Segmentation and Diagnosis.

PubMed

Zhao, Liya; Jia, Kebin

2016-01-01

Early brain tumor detection and diagnosis are critical to clinics. Thus segmentation of focused tumor area needs to be accurate, efficient, and robust. In this paper, we propose an automatic brain tumor segmentation method based on Convolutional Neural Networks (CNNs). Traditional CNNs focus only on local features and ignore global region features, which are both important for pixel classification and recognition. Besides, brain tumor can appear in any place of the brain and be any size and shape in patients. We design a three-stream framework named as multiscale CNNs which could automatically detect the optimum top-three scales of the image sizes and combine information from different scales of the regions around that pixel. Datasets provided by Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) organized by MICCAI 2013 are utilized for both training and testing. The designed multiscale CNNs framework also combines multimodal features from T1, T1-enhanced, T2, and FLAIR MRI images. By comparison with traditional CNNs and the best two methods in BRATS 2012 and 2013, our framework shows advances in brain tumor segmentation accuracy and robustness.

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

PubMed

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

2013-08-01

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

New methods for the geometrical analysis of tubular organs.

PubMed

Grélard, Florent; Baldacci, Fabien; Vialard, Anne; Domenger, Jean-Philippe

2017-12-01

This paper presents new methods to study the shape of tubular organs. Determining precise cross-sections is of major importance to perform geometrical measurements, such as diameter, wall-thickness estimation or area measurement. Our first contribution is a robust method to estimate orthogonal planes based on the Voronoi Covariance Measure. Our method is not relying on a curve-skeleton computation beforehand. This means our orthogonal plane estimator can be used either on the skeleton or on the volume. Another important step towards tubular organ characterization is achieved through curve-skeletonization, as skeletons allow to compare two tubular organs, and to perform virtual endoscopy. Our second contribution is dedicated to correcting common defects of the skeleton by new pruning and recentering methods. Finally, we propose a new method for curve-skeleton extraction. Various results are shown on different types of segmented tubular organs, such as neurons, airway-tree and blood vessels. Copyright © 2017 Elsevier B.V. All rights reserved.

Repair of Segmental Load-Bearing Bone Defect by Autologous Mesenchymal Stem Cells and Plasma-Derived Fibrin Impregnated Ceramic Block Results in Early Recovery of Limb Function

PubMed Central

Ng, Min Hwei; Duski, Suryasmi; Tan, Kok Keong; Yusof, Mohd Reusmaazran; Low, Kiat Cheong; Mohamed Rose, Isa; Mohamed, Zahiah; Bin Saim, Aminuddin; Idrus, Ruszymah Bt Hj

2014-01-01

Calcium phosphate-based bone substitutes have not been used to repair load-bearing bone defects due to their weak mechanical property. In this study, we reevaluated the functional outcomes of combining ceramic block with osteogenic-induced mesenchymal stem cells and platelet-rich plasma (TEB) to repair critical-sized segmental tibial defect. Comparisons were made with fresh marrow-impregnated ceramic block (MIC) and partially demineralized allogeneic bone block (ALLO). Six New Zealand White female rabbits were used in each study group and three rabbits with no implants were used as negative controls. By Day 90, 4/6 rabbits in TEB group and 2/6 in ALLO and MIC groups resumed normal gait pattern. Union was achieved significantly faster in TEB group with a radiological score of 4.50 ± 0.78 versus ALLO (1.06 ± 0.32), MIC (1.28 ± 0.24), and negative controls (0). Histologically, TEB group scored the highest percentage of new bone (82% ± 5.1%) compared to ALLO (5% ± 2.5%) and MIC (26% ± 5.2%). Biomechanically, TEB-treated tibiae achieved the highest compressive strength (43.50 ± 12.72 MPa) compared to those treated with ALLO (15.15 ± 3.57 MPa) and MIC (23.28 ± 6.14 MPa). In conclusion, TEB can repair critical-sized segmental load-bearing bone defects and restore limb function. PMID:25165699

Repair of segmental radial defect with autologous bone marrow aspirate and hydroxyapatite in rabbit radius: A clinical and radiographic evaluation

PubMed Central

Yassine, Kalbaza Ahmed; Mokhtar, Benchohra; Houari, Hemida; Karim, Amara; Mohamed, Melizi

2017-01-01

Aim: Finding an ideal bone substitute to treat large bone defects, delayed union and nonunions remain a challenge for orthopedic surgeons and researchers. Several studies have been conducted on bone regeneration; each has its own advantages and disadvantages. The aim of this study was to evaluate the effect of a combination of hydroxyapatite (HA) powder with autologous bone marrow (BM) aspirate on the repair of segmental radial defect in a rabbit model. Materials and Methods: A total of 36 male and adult New Zealand rabbit with a mean weight of 2.25 kg were used in this study. Approximately, 5 mm defect was created in the mid-shaft of the radius to be filled with HA powder in the control group “HA” (n=18) and with a combination of HA powder and autologous BM aspirate in the test group “HA+BM” (n=18). Animals were observed daily for healing by inspection of the surgical site, and six rabbits of each group were sacrificed at 30, 60, and 90 post-operative days to perform a radiographic evaluation of defect site. Results: Obtained results revealed a better and more rapid bone regeneration in the test group: Since the defect was rapidly and completely filled with mature bone tissue after 90 days. Conclusion: Based on these findings, we could infer that adding a BM aspirate to HA is responsible of a better regeneration process leading to a complete filling of the defect. PMID:28831217

Internal Prosthetic Replacement of Skeletal Segments Lost in Combat Related Injuries.

DTIC Science & Technology

1981-08-01

1-cm segment from the proximal third to prevent distraction of the fragments. The fiber metal segment is then placed in the appropriate defect and the...articularis genu suprema. The medial collateral ligament is sectioned through this incision and the medial meniscus removed in toto. The articular capsule...the image intensifier showed no evidence of motion. A physical therapy was instituted to mobilize and strengthen her knee. Case #11. This 52 year old

[Modified anterolateral thigh perforator flap pedicled by cross-bridge microvascular anastomosis for repairing soft tissue defects in middle and lower segments of leg].

PubMed

Yang, Lin; Liu, Hongjun; Zhang, Wenzhong; Song, Guoxun; Xia, Shicong; Zhang, Naichen; Gu, Jiaxiang; Yuan, Chaoqun

2017-10-01

To explore the effectiveness of modified anterolateral thigh perforator flap pedicled by cross-bridge microvascular anastomosis in treatment of soft tissue defects in the middle and lower segments of the leg. Between March 2011 and June 2015, 15 cases with skin and soft tissue defects in the middle and lower segments of the legs were treated. There were 9 males and 6 females, aged 22-48 years (mean, 32.6 years). Of whom, 8 patients caused by traffic accidents, 5 by machine twist, and 2 by crash injury of heavy object. The mean interval from injury to admission was 82.6 hours (range, 2 hours to 1 week). The area of defect ranged from 13 cm×9 cm to 23 cm×16 cm. After primary debridement and vaccum sealing drainage treatment, the defects were repaired with modified anterolateral thigh perforator flap pedicled by cross-bridge microvascular anastomosis. The size of flap ranged from 15 cm×10 cm to 25 cm×15 cm. The donor sites were sutured directly or repaired with the skin grafts. The pedicle division was done at 4 weeks after operation. After operation, venous crisis occurred in 1 case and distal skin necrosis in 2 cases which was healed by dressing change. The other tissue flaps survived successfully and wounds healed by first intention. All skin grafts at donor site survived after operation, and primary healing of wound was obtained. All patients were followed up 6-24 months (mean, 13 months). All flaps were characterized by soft texture, satisfactory appearance, and restoring the protective sensation. Moreover, the two-point discrimination ranged from 15 to 28 mm (mean, 19.5 mm) at 6 months after operation. The function of both lower extremities were normal without obvious contracture of scar at donor site. Modified free anterolateral thigh perforator flap, with little damage in donor site, a reliable blood supply by making a cross-bridge microvascular anastomosis with pretibial or posterior tibial blood vessel on normal leg, is a reliable alternative method for repairing soft tissue defects with the main vessels of serious injury in the middle and lower segments of the leg.

Spatial correspondence of 4D CT ventilation and SPECT pulmonary perfusion defects in patients with malignant airway stenosis

NASA Astrophysics Data System (ADS)

Castillo, Richard; Castillo, Edward; McCurdy, Matthew; Gomez, Daniel R.; Block, Alec M.; Bergsma, Derek; Joy, Sarah; Guerrero, Thomas

2012-04-01

To determine the spatial overlap agreement between four-dimensional computed tomography (4D CT) ventilation and single photon emission computed tomography (SPECT) perfusion hypo-functioning pulmonary defect regions in a patient population with malignant airway stenosis. Treatment planning 4D CT images were obtained retrospectively for ten lung cancer patients with radiographically demonstrated airway obstruction due to gross tumor volume. Each patient also received a SPECT perfusion study within one week of the planning 4D CT, and prior to the initiation of treatment. Deformable image registration was used to map corresponding lung tissue elements between the extreme component phase images, from which quantitative three-dimensional (3D) images representing the local pulmonary specific ventilation were constructed. Semi-automated segmentation of the percentile perfusion distribution was performed to identify regional defects distal to the known obstructing lesion. Semi-automated segmentation was similarly performed by multiple observers to delineate corresponding defect regions depicted on 4D CT ventilation. Normalized Dice similarity coefficient (NDSC) indices were determined for each observer between SPECT perfusion and 4D CT ventilation defect regions to assess spatial overlap agreement. Tidal volumes determined from 4D CT ventilation were evaluated versus measurements obtained from lung parenchyma segmentation. Linear regression resulted in a linear fit with slope = 1.01 (R2 = 0.99). Respective values for the average DSC, NDSC1 mm and NDSC2 mm for all cases and multiple observers were 0.78, 0.88 and 0.99, indicating that, on average, spatial overlap agreement between ventilation and perfusion defect regions was comparable to the threshold for agreement within 1-2 mm uncertainty. Corresponding coefficients of variation for all metrics were similarly in the range: 0.10%-19%. This study is the first to quantitatively assess 3D spatial overlap agreement between clinically acquired SPECT perfusion and specific ventilation from 4D CT. Results suggest high correlation between methods within the sub-population of lung cancer patients with malignant airway stenosis.

Improving Bone Formation in a Rat Femur Segmental Defect by Controlling Bone Morphogenetic Protein-2 Release

DTIC Science & Technology

2011-04-01

tissue and polymer: mineralized tissue stained dark green, osteoid and collagen bright red, soft tissue pink to light green, and erythrocytes bright...of bone, soft tissue , and polymer, high-resolution digital images were acquired at 1.25 · or 20 · . The area of interest comprising the bone defect...bone, soft tissue , and polymer (when present) within the defect were quantified using Metamorph software (Molecular Devices, Inc.) and were calculated

Robust crop and weed segmentation under uncontrolled outdoor illumination

USDA-ARS?s Scientific Manuscript database

A new machine vision for weed detection was developed from RGB color model images. Processes included in the algorithm for the detection were excessive green conversion, threshold value computation by statistical analysis, adaptive image segmentation by adjusting the threshold value, median filter, ...

A defect-driven diagnostic method for machine tool spindles

PubMed Central

Vogl, Gregory W.; Donmez, M. Alkan

2016-01-01

Simple vibration-based metrics are, in many cases, insufficient to diagnose machine tool spindle condition. These metrics couple defect-based motion with spindle dynamics; diagnostics should be defect-driven. A new method and spindle condition estimation device (SCED) were developed to acquire data and to separate system dynamics from defect geometry. Based on this method, a spindle condition metric relying only on defect geometry is proposed. Application of the SCED on various milling and turning spindles shows that the new approach is robust for diagnosing the machine tool spindle condition. PMID:28065985

Automated segmentation of the prostate in 3D MR images using a probabilistic atlas and a spatially constrained deformable model.

PubMed

Martin, Sébastien; Troccaz, Jocelyne; Daanenc, Vincent

2010-04-01

The authors present a fully automatic algorithm for the segmentation of the prostate in three-dimensional magnetic resonance (MR) images. The approach requires the use of an anatomical atlas which is built by computing transformation fields mapping a set of manually segmented images to a common reference. These transformation fields are then applied to the manually segmented structures of the training set in order to get a probabilistic map on the atlas. The segmentation is then realized through a two stage procedure. In the first stage, the processed image is registered to the probabilistic atlas. Subsequently, a probabilistic segmentation is obtained by mapping the probabilistic map of the atlas to the patient's anatomy. In the second stage, a deformable surface evolves toward the prostate boundaries by merging information coming from the probabilistic segmentation, an image feature model and a statistical shape model. During the evolution of the surface, the probabilistic segmentation allows the introduction of a spatial constraint that prevents the deformable surface from leaking in an unlikely configuration. The proposed method is evaluated on 36 exams that were manually segmented by a single expert. A median Dice similarity coefficient of 0.86 and an average surface error of 2.41 mm are achieved. By merging prior knowledge, the presented method achieves a robust and completely automatic segmentation of the prostate in MR images. Results show that the use of a spatial constraint is useful to increase the robustness of the deformable model comparatively to a deformable surface that is only driven by an image appearance model.

Robust demarcation of basal cell carcinoma by dependent component analysis-based segmentation of multi-spectral fluorescence images.

PubMed

Kopriva, Ivica; Persin, Antun; Puizina-Ivić, Neira; Mirić, Lina

2010-07-02

This study was designed to demonstrate robust performance of the novel dependent component analysis (DCA)-based approach to demarcation of the basal cell carcinoma (BCC) through unsupervised decomposition of the red-green-blue (RGB) fluorescent image of the BCC. Robustness to intensity fluctuation is due to the scale invariance property of DCA algorithms, which exploit spectral and spatial diversities between the BCC and the surrounding tissue. Used filtering-based DCA approach represents an extension of the independent component analysis (ICA) and is necessary in order to account for statistical dependence that is induced by spectral similarity between the BCC and surrounding tissue. This generates weak edges what represents a challenge for other segmentation methods as well. By comparative performance analysis with state-of-the-art image segmentation methods such as active contours (level set), K-means clustering, non-negative matrix factorization, ICA and ratio imaging we experimentally demonstrate good performance of DCA-based BCC demarcation in two demanding scenarios where intensity of the fluorescent image has been varied almost two orders of magnitude. Copyright 2010 Elsevier B.V. All rights reserved.

Virtual planning of complex head and neck reconstruction results in satisfactory match between real outcomes and virtual models.

PubMed

Hanken, Henning; Schablowsky, Clemens; Smeets, Ralf; Heiland, Max; Sehner, Susanne; Riecke, Björn; Nourwali, Ibrahim; Vorwig, Oliver; Gröbe, Alexander; Al-Dam, Ahmed

2015-04-01

The reconstruction of large facial bony defects using microvascular transplants requires extensive surgery to achieve full rehabilitation of form and function. The purpose of this study is to measure the agreement between virtual plans and the actual results of maxillofacial reconstruction. This retrospective cohort study included 30 subjects receiving maxillofacial reconstruction with a preoperative virtual planning. Parameters including defect size, position, angle and volume of the transplanted segments were compared between the virtual plan and the real outcome using paired t test. A total of 63 bone segments were transplanted. The mean differences between the virtual planning and the postoperative situation were for the defect sizes 1.17 mm (95 % confidence interval (CI) (-.21 to 2.56 mm); p = 0.094), for the resection planes 1.69 mm (95 % CI (1.26-2.11); p = 0.033) and 10.16° (95 % CI (8.36°-11.96°); p < 0.001) and for the planes of the donor segments 10.81° (95 % CI (9.44°-12.17°); p < 0.001) The orientation of the segments differed by 6.68° (95 % CI (5.7°-7.66°); p < 0.001) from the virtual plan; the length of the segments differed by -0.12 mm (95 % CI (0.89-0.65 mm); not significant (n.s.)), respectively, while the volume differed by 73.3 % (95 % CI (69.4-77.6 %); p < 0.001). The distance between the transplanted segments and the remaining bone was 1.49 mm (95 % CI (1.24-1.74); p < 0.001) and between the segments 1.49 mm (95 % CI (1.16-1.81); p < 0.001). Virtual plans for mandibular and maxillofacial reconstruction can be realised with excellent match. These highly satisfactory postoperative results are the basis for an optimal functional and aesthetic reconstruction in a single surgical procedure. The technique should be further investigated in larger study populations and should be further improved.

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.

Computed tomography arterial portography for assessment of portal vein injury after blunt hepatic trauma.

PubMed

Fu, Chen Ju; Wong, Yon Cheong; Tsang, Yuk Ming; Wang, Li Jen; Chen, Huan Wu; Ku, Yi Kang; Wu, Cheng Hsien; Chen, Huan Wen; Kang, Shih Ching

2015-01-01

Intrahepatic portal vein injuries secondary to blunt abdominal trauma are difficult to diagnose and can result in insidious bleeding. We aimed to compare computed tomography arterial portography (CTAP), reperfusion CTAP (rCTAP), and conventional computed tomography (CT) for diagnosing portal vein injuries after blunt hepatic trauma. Patients with blunt hepatic trauma, who were eligible for nonoperative management, underwent CTAP, rCTAP, and CT. The number and size of perfusion defects observed using the three methods were compared. A total of 13 patients (seven males/six females) with a mean age of 34.5±14.1 years were included in the study. A total of 36 hepatic segments had perfusion defects on rCTAP and CT, while there were 47 hepatic segments with perfusion defects on CTAP. The size of perfusion defects on CT (239 cm3; interquartile range [IQR]: 129.5, 309.5) and rCTAP (238 cm3; IQR: 129.5, 310.5) were significantly smaller compared with CTAP (291 cm3; IQR: 136, 371) (both, P = 0.002). Perfusion defects measured by CTAP were significantly greater than those determined by either rCTAP or CT in cases of blunt hepatic trauma. This finding suggests that CTAP is superior to rCTAP and CT in evaluating portal vein injuries after blunt liver trauma.

7 CFR 51.1175 - Classification of defects.

Code of Federal Regulations, 2012 CFR

2012-01-01

... STANDARDS) United States Standards for Grades of Florida Oranges and Tangelos Definitions § 51.1175... segments more than 1/4 inch (6.4 mm) at stem end, or the equivalent of this amount, by volume, when occurring in other portions of the fruit Affecting all segments more than 1/2 inch (12.7 mm) at stem end, or...

7 CFR 51.1175 - Classification of defects.

Code of Federal Regulations, 2011 CFR

2011-01-01

... STANDARDS) United States Standards for Grades of Florida Oranges and Tangelos Definitions § 51.1175... segments more than 1/4 inch (6.4 mm) at stem end, or the equivalent of this amount, by volume, when occurring in other portions of the fruit Affecting all segments more than 1/2 inch (12.7 mm) at stem end, or...

Active learning based segmentation of Crohns disease from abdominal MRI.

PubMed

Mahapatra, Dwarikanath; Vos, Franciscus M; Buhmann, Joachim M

2016-05-01

This paper proposes a novel active learning (AL) framework, and combines it with semi supervised learning (SSL) for segmenting Crohns disease (CD) tissues from abdominal magnetic resonance (MR) images. Robust fully supervised learning (FSL) based classifiers require lots of labeled data of different disease severities. Obtaining such data is time consuming and requires considerable expertise. SSL methods use a few labeled samples, and leverage the information from many unlabeled samples to train an accurate classifier. AL queries labels of most informative samples and maximizes gain from the labeling effort. Our primary contribution is in designing a query strategy that combines novel context information with classification uncertainty and feature similarity. Combining SSL and AL gives a robust segmentation method that: (1) optimally uses few labeled samples and many unlabeled samples; and (2) requires lower training time. Experimental results show our method achieves higher segmentation accuracy than FSL methods with fewer samples and reduced training effort. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Segmentation of the Speaker's Face Region with Audiovisual Correlation

NASA Astrophysics Data System (ADS)

Liu, Yuyu; Sato, Yoichi

The ability to find the speaker's face region in a video is useful for various applications. In this work, we develop a novel technique to find this region within different time windows, which is robust against the changes of view, scale, and background. The main thrust of our technique is to integrate audiovisual correlation analysis into a video segmentation framework. We analyze the audiovisual correlation locally by computing quadratic mutual information between our audiovisual features. The computation of quadratic mutual information is based on the probability density functions estimated by kernel density estimation with adaptive kernel bandwidth. The results of this audiovisual correlation analysis are incorporated into graph cut-based video segmentation to resolve a globally optimum extraction of the speaker's face region. The setting of any heuristic threshold in this segmentation is avoided by learning the correlation distributions of speaker and background by expectation maximization. Experimental results demonstrate that our method can detect the speaker's face region accurately and robustly for different views, scales, and backgrounds.

Improved fuzzy clustering algorithms in segmentation of DC-enhanced breast MRI.

PubMed

Kannan, S R; Ramathilagam, S; Devi, Pandiyarajan; Sathya, A

2012-02-01

Segmentation of medical images is a difficult and challenging problem due to poor image contrast and artifacts that result in missing or diffuse organ/tissue boundaries. Many researchers have applied various techniques however fuzzy c-means (FCM) based algorithms is more effective compared to other methods. The objective of this work is to develop some robust fuzzy clustering segmentation systems for effective segmentation of DCE - breast MRI. This paper obtains the robust fuzzy clustering algorithms by incorporating kernel methods, penalty terms, tolerance of the neighborhood attraction, additional entropy term and fuzzy parameters. The initial centers are obtained using initialization algorithm to reduce the computation complexity and running time of proposed algorithms. Experimental works on breast images show that the proposed algorithms are effective to improve the similarity measurement, to handle large amount of noise, to have better results in dealing the data corrupted by noise, and other artifacts. The clustering results of proposed methods are validated using Silhouette Method.

7 CFR 51.1175 - Classification of defects.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Definitions § 51.1175 Classification of defects. Table I Factor Injury Damage Serious damage Very serious... mushy condition Affecting all segments more than 1/4 inch (6.4 mm) at stem end, or the equivalent of... 1/2 inch (12.7 mm) at stem end, or the equivalent of this amount, by volume, when occurring in other...

7 CFR 51.784 - Classification of defects.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Definitions § 51.784 Classification of defects. Table I Factor Injury Damage Serious damage Very serious.../4 inch (6.4 mm) at stem end, or the equivalent of this amount, by volume, when occurring in other portions of the fruit Affecting all segments more than 1/2 inch (12.7 mm) at stem end, or the equivalent of...

7 CFR 51.784 - Classification of defects.

Code of Federal Regulations, 2013 CFR

2013-01-01

... Definitions § 51.784 Classification of defects. Table I Factor Injury Damage Serious damage Very serious.../4 inch (6.4 mm) at stem end, or the equivalent of this amount, by volume, when occurring in other portions of the fruit Affecting all segments more than 1/2 inch (12.7 mm) at stem end, or the equivalent of...

7 CFR 51.1175 - Classification of defects.

Code of Federal Regulations, 2013 CFR

2013-01-01

... Definitions § 51.1175 Classification of defects. Table I Factor Injury Damage Serious damage Very serious... mushy condition Affecting all segments more than 1/4 inch (6.4 mm) at stem end, or the equivalent of... 1/2 inch (12.7 mm) at stem end, or the equivalent of this amount, by volume, when occurring in other...

Optimization of Soft Tissue Management, Spacer Design, and Grafting Strategies for Large Segmental Bone Defects using the Chronic Caprine Tibial Defect Model

DTIC Science & Technology

2014-10-01

histology, and microCT analysis. In the current phase of work he will receive more specialized ` training and orientation to microCT analysis...fibrous connective tissue. • Performed histology on goat autogenous bone graft which demonstrated that the quantity and quality of cancellous bone graft

Needle segmentation using 3D Hough transform in 3D TRUS guided prostate transperineal therapy

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

Qiu Wu; Imaging Research Laboratories, Robarts Research Institute, Western University, London, Ontario N6A 5K8; Yuchi Ming

Purpose: Prostate adenocarcinoma is the most common noncutaneous malignancy in American men with over 200 000 new cases diagnosed each year. Prostate interventional therapy, such as cryotherapy and brachytherapy, is an effective treatment for prostate cancer. Its success relies on the correct needle implant position. This paper proposes a robust and efficient needle segmentation method, which acts as an aid to localize the needle in three-dimensional (3D) transrectal ultrasound (TRUS) guided prostate therapy. Methods: The procedure of locating the needle in a 3D TRUS image is a three-step process. First, the original 3D ultrasound image containing a needle is cropped;more » the cropped image is then converted to a binary format based on its histogram. Second, a 3D Hough transform based needle segmentation method is applied to the 3D binary image in order to locate the needle axis. The position of the needle endpoint is finally determined by an optimal threshold based analysis of the intensity probability distribution. The overall efficiency is improved through implementing a coarse-fine searching strategy. The proposed method was validated in tissue-mimicking agar phantoms, chicken breast phantoms, and 3D TRUS patient images from prostate brachytherapy and cryotherapy procedures by comparison to the manual segmentation. The robustness of the proposed approach was tested by means of varying parameters such as needle insertion angle, needle insertion length, binarization threshold level, and cropping size. Results: The validation results indicate that the proposed Hough transform based method is accurate and robust, with an achieved endpoint localization accuracy of 0.5 mm for agar phantom images, 0.7 mm for chicken breast phantom images, and 1 mm for in vivo patient cryotherapy and brachytherapy images. The mean execution time of needle segmentation algorithm was 2 s for a 3D TRUS image with size of 264 Multiplication-Sign 376 Multiplication-Sign 630 voxels. Conclusions: The proposed needle segmentation algorithm is accurate, robust, and suitable for 3D TRUS guided prostate transperineal therapy.« less

Unilateral advancement of the maxillary minor segment by distraction osteogenesis in patients with repaired unilateral cleft lip and palate: report of two cases.

PubMed

Kuroe, Kazuto; Iino, Shoichiro; Shomura, Kenji; Okubo, Akiro; Sugihara, Kazumasa; Ito, Gakuji

2003-05-01

Collapse of the maxillary minor segment with lateral crossbite is a common feature in patients with repaired unilateral cleft lip/palate because of maxillary alveolar bony defect and palatal scar tissue. Distraction osteogenesis (DOG) is an effective technique of lengthening and augmentation for bone and gingiva. This case report describes the effects of unilateral advancement of the maxillary minor segment by DOG in two patients with the repaired unilateral cleft lip/palate.

Evaluation of rhBMP-2/collagen/TCP-HA bone graft with and without bone marrow cells in the canine femoral multi defect model.

PubMed

Luangphakdy, V; Shinohara, K; Pan, H; Boehm, C; Samaranska, A; Muschler, G F

2015-01-12

Recombinant human bone morphogenetic protein-2, when applied to an absorbable type 1 bovine collagen sponge (rhBMP-2/ACS) is an effective therapy in many bone grafting settings. Bone marrow aspirate (BMA) has also been used as a source of transplantable osteogenic connective tissue progenitors. This study was designed to characterize the performance of a scaffold comprising rhBMP-2/ACS in which the sponge wraps around tri-calcium phosphate hydroxyapatite granules (rhBMP-2/ACS/TCP-HA) and to test the hypothesis that addition of BMA will improve the performance of this construct in the Canine Femoral Multi Defect Model. In each subject, two sites were grafted with rhBMP-2/ACS/TCP-HA scaffold loaded with BMA clot and two other sites with rhBMP-2/ACS/TCP-HA scaffold loaded with wound blood (WB). After correction for unresorbed TCP-HA granules, sites grafted with rhBMP-2/ACS/TCP-HA+BMA and rhBMP-2/ACS/TCP-HA+WB were similar, with mean percent bone volumes of 10.9 %±1.2 and 11.2 %±1.2, respectively. No differences were seen in quantitative histomorphometry. While bone formation using both constructs was robust, this study did not support the hypothesis that the addition of unprocessed bone marrow aspirate clot improved bone regeneration in a site engrafted with rhBMP-2/ACS/TCP-HA+BMA. In contrast to prior studies using this model, new bone formation was greater at the center of the defect where TCP-HA was distributed. This finding suggests a potential synergy between rhBMP-2 and the centrally placed ceramic and cellular components of the graft construct. Further optimization may also require more uniform distribution of TCP-HA, alternative cell delivery strategies, and a more rigorous large animal segmental defect model.

Rigid shape matching by segmentation averaging.

PubMed

Wang, Hongzhi; Oliensis, John

2010-04-01

We use segmentations to match images by shape. The new matching technique does not require point-to-point edge correspondence and is robust to small shape variations and spatial shifts. To address the unreliability of segmentations computed bottom-up, we give a closed form approximation to an average over all segmentations. Our method has many extensions, yielding new algorithms for tracking, object detection, segmentation, and edge-preserving smoothing. For segmentation, instead of a maximum a posteriori approach, we compute the "central" segmentation minimizing the average distance to all segmentations of an image. For smoothing, instead of smoothing images based on local structures, we smooth based on the global optimal image structures. Our methods for segmentation, smoothing, and object detection perform competitively, and we also show promising results in shape-based tracking.

Numerical simulation of fluid field and in vitro three-dimensional fabrication of tissue-engineered bones in a rotating bioreactor and in vivo implantation for repairing segmental bone defects.

PubMed

Song, Kedong; Wang, Hai; Zhang, Bowen; Lim, Mayasari; Liu, Yingchao; Liu, Tianqing

2013-03-01

In this paper, two-dimensional flow field simulation was conducted to determine shear stresses and velocity profiles for bone tissue engineering in a rotating wall vessel bioreactor (RWVB). In addition, in vitro three-dimensional fabrication of tissue-engineered bones was carried out in optimized bioreactor conditions, and in vivo implantation using fabricated bones was performed for segmental bone defects of Zelanian rabbits. The distribution of dynamic pressure, total pressure, shear stress, and velocity within the culture chamber was calculated for different scaffold locations. According to the simulation results, the dynamic pressure, velocity, and shear stress around the surface of cell-scaffold construction periodically changed at different locations of the RWVB, which could result in periodical stress stimulation for fabricated tissue constructs. However, overall shear stresses were relatively low, and the fluid velocities were uniform in the bioreactor. Our in vitro experiments showed that the number of cells cultured in the RWVB was five times higher than those cultured in a T-flask. The tissue-engineered bones grew very well in the RWVB. This study demonstrates that stress stimulation in an RWVB can be beneficial for cell/bio-derived bone constructs fabricated in an RWVB, with an application for repairing segmental bone defects.

Automatic segmentation of brain MRIs and mapping neuroanatomy across the human lifespan

NASA Astrophysics Data System (ADS)

Keihaninejad, Shiva; Heckemann, Rolf A.; Gousias, Ioannis S.; Rueckert, Daniel; Aljabar, Paul; Hajnal, Joseph V.; Hammers, Alexander

2009-02-01

A robust model for the automatic segmentation of human brain images into anatomically defined regions across the human lifespan would be highly desirable, but such structural segmentations of brain MRI are challenging due to age-related changes. We have developed a new method, based on established algorithms for automatic segmentation of young adults' brains. We used prior information from 30 anatomical atlases, which had been manually segmented into 83 anatomical structures. Target MRIs came from 80 subjects (~12 individuals/decade) from 20 to 90 years, with equal numbers of men, women; data from two different scanners (1.5T, 3T), using the IXI database. Each of the adult atlases was registered to each target MR image. By using additional information from segmentation into tissue classes (GM, WM and CSF) to initialise the warping based on label consistency similarity before feeding this into the previous normalised mutual information non-rigid registration, the registration became robust enough to accommodate atrophy and ventricular enlargement with age. The final segmentation was obtained by combination of the 30 propagated atlases using decision fusion. Kernel smoothing was used for modelling the structural volume changes with aging. Example linear correlation coefficients with age were, for lateral ventricular volume, rmale=0.76, rfemale=0.58 and, for hippocampal volume, rmale=-0.6, rfemale=-0.4 (allρ<0.01).

Loss- and Gain-of-Function Mutations in the F1-HAMP Region of the Escherichia coli Aerotaxis Transducer Aer

PubMed Central

del Carmen Burón-Barral, Maria; Gosink, Khoosheh K.; Parkinson, John S.

2006-01-01

The Escherichia coli Aer protein contains an N-terminal PAS domain that binds flavin adenine dinucleotide (FAD), senses aerotactic stimuli, and communicates with the output signaling domain. To explore the roles of the intervening F1 and HAMP segments in Aer signaling, we isolated plasmid-borne aerotaxis-defective mutations in a host strain lacking all chemoreceptors of the methyl-accepting chemotaxis protein (MCP) family. Under these conditions, Aer alone established the cell's run/tumble swimming pattern and modulated that behavior in response to oxygen gradients. We found two classes of Aer mutants: null and clockwise (CW) biased. Most mutant proteins exhibited the null phenotype: failure to elicit CW flagellar rotation, no aerosensing behavior in MCP-containing hosts, and no apparent FAD-binding ability. However, null mutants had low Aer expression levels caused by rapid degradation of apparently nonnative subunits. Their functional defects probably reflect the absence of a protein product. In contrast, CW-biased mutant proteins exhibited normal expression levels, wild-type FAD binding, and robust aerosensing behavior in MCP-containing hosts. The CW lesions evidently shift unstimulated Aer output to the CW signaling state but do not block the Aer input-output pathway. The distribution and properties of null and CW-biased mutations suggest that the Aer PAS domain may engage in two different interactions with HAMP and the HAMP-proximal signaling domain: one needed for Aer maturation and another for promoting CW output from the Aer signaling domain. Most aerotaxis-defective null mutations in these regions seemed to affect maturation only, indicating that these two interactions involve structurally distinct determinants. PMID:16672601

Robustness of Radiomic Features in [11C]Choline and [18F]FDG PET/CT Imaging of Nasopharyngeal Carcinoma: Impact of Segmentation and Discretization.

PubMed

Lu, Lijun; Lv, Wenbing; Jiang, Jun; Ma, Jianhua; Feng, Qianjin; Rahmim, Arman; Chen, Wufan

2016-12-01

Radiomic features are increasingly utilized to evaluate tumor heterogeneity in PET imaging and to enable enhanced prediction of therapy response and outcome. An important ingredient to success in translation of radiomic features to clinical reality is to quantify and ascertain their robustness. In the present work, we studied the impact of segmentation and discretization on 88 radiomic features in 2-deoxy-2-[ 18 F]fluoro-D-glucose ([ 18 F]FDG) and [ 11 C]methyl-choline ([ 11 C]choline) positron emission tomography/X-ray computed tomography (PET/CT) imaging of nasopharyngeal carcinoma. Forty patients underwent [ 18 F]FDG PET/CT scans. Of these, nine patients were imaged on a different day utilizing [ 11 C]choline PET/CT. Tumors were delineated using reference manual segmentation by the consensus of three expert physicians, using 41, 50, and 70 % maximum standardized uptake value (SUV max ) threshold with background correction, Nestle's method, and watershed and region growing methods, and then discretized with fixed bin size (0.05, 0.1, 0.2, 0.5, and 1) in units of SUV. A total of 88 features, including 21 first-order intensity features, 10 shape features, and 57 second- and higher-order textural features, were extracted from the tumors. The robustness of the features was evaluated via the intraclass correlation coefficient (ICC) for seven kinds of segmentation methods (involving all 88 features) and five kinds of discretization bin size (involving the 57 second- and higher-order features). Forty-four (50 %) and 55 (63 %) features depicted ICC ≥0.8 with respect to segmentation as obtained from [ 18 F]FDG and [ 11 C]choline, respectively. Thirteen (23 %) and 12 (21 %) features showed ICC ≥0.8 with respect to discretization as obtained from [ 18 F]FDG and [ 11 C]choline, respectively. Six features were obtained from both [ 18 F]FDG and [ 11 C]choline having ICC ≥0.8 for both segmentation and discretization, five of which were gray-level co-occurrence matrix (GLCM) features (SumEntropy, Entropy, DifEntropy, Homogeneity1, and Homogeneity2) and one of which was an neighborhood gray-tone different matrix (NGTDM) feature (Coarseness). Discretization generated larger effects on features than segmentation in both tracers. Features extracted from [ 11 C]choline were more robust than [ 18 F]FDG for segmentation. Discretization had very similar effects on features extracted from both tracers.

[Research on K-means clustering segmentation method for MRI brain image based on selecting multi-peaks in gray histogram].

PubMed

Chen, Zhaoxue; Yu, Haizhong; Chen, Hao

2013-12-01

To solve the problem of traditional K-means clustering in which initial clustering centers are selected randomly, we proposed a new K-means segmentation algorithm based on robustly selecting 'peaks' standing for White Matter, Gray Matter and Cerebrospinal Fluid in multi-peaks gray histogram of MRI brain image. The new algorithm takes gray value of selected histogram 'peaks' as the initial K-means clustering center and can segment the MRI brain image into three parts of tissue more effectively, accurately, steadily and successfully. Massive experiments have proved that the proposed algorithm can overcome many shortcomings caused by traditional K-means clustering method such as low efficiency, veracity, robustness and time consuming. The histogram 'peak' selecting idea of the proposed segmentootion method is of more universal availability.

Human region segmentation and description methods for domiciliary healthcare monitoring using chromatic methodology

NASA Astrophysics Data System (ADS)

Al-Temeemy, Ali A.

2018-03-01

A descriptor is proposed for use in domiciliary healthcare monitoring systems. The descriptor is produced from chromatic methodology to extract robust features from the monitoring system's images. It has superior discrimination capabilities, is robust to events that normally disturb monitoring systems, and requires less computational time and storage space to achieve recognition. A method of human region segmentation is also used with this descriptor. The performance of the proposed descriptor was evaluated using experimental data sets, obtained through a series of experiments performed in the Centre for Intelligent Monitoring Systems, University of Liverpool. The evaluation results show high recognition performance for the proposed descriptor in comparison to traditional descriptors, such as moments invariant. The results also show the effectiveness of the proposed segmentation method regarding distortion effects associated with domiciliary healthcare systems.

Quantitative segmentation of fluorescence microscopy images of heterogeneous tissue: Approach for tuning algorithm parameters

NASA Astrophysics Data System (ADS)

Mueller, Jenna L.; Harmany, Zachary T.; Mito, Jeffrey K.; Kennedy, Stephanie A.; Kim, Yongbaek; Dodd, Leslie; Geradts, Joseph; Kirsch, David G.; Willett, Rebecca M.; Brown, J. Quincy; Ramanujam, Nimmi

2013-02-01

The combination of fluorescent contrast agents with microscopy is a powerful technique to obtain real time images of tissue histology without the need for fixing, sectioning, and staining. The potential of this technology lies in the identification of robust methods for image segmentation and quantitation, particularly in heterogeneous tissues. Our solution is to apply sparse decomposition (SD) to monochrome images of fluorescently-stained microanatomy to segment and quantify distinct tissue types. The clinical utility of our approach is demonstrated by imaging excised margins in a cohort of mice after surgical resection of a sarcoma. Representative images of excised margins were used to optimize the formulation of SD and tune parameters associated with the algorithm. Our results demonstrate that SD is a robust solution that can advance vital fluorescence microscopy as a clinically significant technology.

Microscopy image segmentation tool: Robust image data analysis

NASA Astrophysics Data System (ADS)

Valmianski, Ilya; Monton, Carlos; Schuller, Ivan K.

2014-03-01

We present a software package called Microscopy Image Segmentation Tool (MIST). MIST is designed for analysis of microscopy images which contain large collections of small regions of interest (ROIs). Originally developed for analysis of porous anodic alumina scanning electron images, MIST capabilities have been expanded to allow use in a large variety of problems including analysis of biological tissue, inorganic and organic film grain structure, as well as nano- and meso-scopic structures. MIST provides a robust segmentation algorithm for the ROIs, includes many useful analysis capabilities, and is highly flexible allowing incorporation of specialized user developed analysis. We describe the unique advantages MIST has over existing analysis software. In addition, we present a number of diverse applications to scanning electron microscopy, atomic force microscopy, magnetic force microscopy, scanning tunneling microscopy, and fluorescent confocal laser scanning microscopy.

Bone Marrow Aspirate Concentrate in Animal Long Bone Healing: An Analysis of Basic Science Evidence.

PubMed

Gianakos, Arianna; Ni, Amelia; Zambrana, Lester; Kennedy, John G; Lane, Joseph M

2016-01-01

Long bone fractures that fail to heal or show a delay in healing can lead to increased morbidity. Bone marrow aspirate concentrate (BMAC) containing bone mesenchymal stem cells (BMSCs) has been suggested as an autologous biologic adjunct to aid long bone healing. The purpose of this study was to systematically review the basic science in vivo evidence for the use of BMAC with BMSCs in the treatment of segmental defects in animal long bones. The PubMed/MEDLINE and EMBASE databases were screened in July 14-25, 2014. The following search criteria were used: [("bmac" OR "bone marrow aspirate concentrate" OR "bmc" OR "bone marrow concentrate" OR "mesenchymal stem cells") AND ("bone" OR "osteogenesis" OR "fracture healing" OR "nonunion" OR "delayed union")]. Three authors extracted data and analyzed for trends. Quality of evidence score was given to each study. Results are presented as Hedge G standardized effect sizes with 95% confidence intervals. The search yielded 35 articles for inclusion. Of studies reporting statistics, 100% showed significant increase in bone formation in the BMAC group on radiograph. Ninety percent reported significant improvement in earlier bone healing on histologic/histomorphometric assessment. Eighty-one percent reported a significant increase in bone area on micro-computed tomography. Seventy-eight percent showed a higher torsional stiffness for the BMAC-treated defects. In the in vivo studies evaluated, BMAC confer beneficial effects on the healing of segmental defects in animal long bone models when compared with a control. Proof-of-concept has been established for BMAC in the treatment of animal segmental bone defects.

Defect detection of castings in radiography images using a robust statistical feature.

PubMed

Zhao, Xinyue; He, Zaixing; Zhang, Shuyou

2014-01-01

One of the most commonly used optical methods for defect detection is radiographic inspection. Compared with methods that extract defects directly from the radiography image, model-based methods deal with the case of an object with complex structure well. However, detection of small low-contrast defects in nonuniformly illuminated images is still a major challenge for them. In this paper, we present a new method based on the grayscale arranging pairs (GAP) feature to detect casting defects in radiography images automatically. First, a model is built using pixel pairs with a stable intensity relationship based on the GAP feature from previously acquired images. Second, defects can be extracted by comparing the difference of intensity-difference signs between the input image and the model statistically. The robustness of the proposed method to noise and illumination variations has been verified on casting radioscopic images with defects. The experimental results showed that the average computation time of the proposed method in the testing stage is 28 ms per image on a computer with a Pentium Core 2 Duo 3.00 GHz processor. For the comparison, we also evaluated the performance of the proposed method as well as that of the mixture-of-Gaussian-based and crossing line profile methods. The proposed method achieved 2.7% and 2.0% false negative rates in the noise and illumination variation experiments, respectively.

Ultrasonic Welded Resorbable Mesh (SonicWeld Rx System) in Reconstruction of Segmental Mandibular Defects: Technical Note and Report of 2 Cases.

PubMed

Shanti, Rabie M; Yampolsky, Andrew; Milles, Maano; Braidy, Hani

2015-11-01

The present report describes 2 patients who underwent mandibular reconstruction after segmental mandibulectomy for benign pathology. The potential of an ultrasonic-aided biodegradable system for containment of a nonvascularized bone graft is discussed. Copyright © 2015 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.

Multiple sclerosis lesion segmentation using an automatic multimodal graph cuts.

PubMed

García-Lorenzo, Daniel; Lecoeur, Jeremy; Arnold, Douglas L; Collins, D Louis; Barillot, Christian

2009-01-01

Graph Cuts have been shown as a powerful interactive segmentation technique in several medical domains. We propose to automate the Graph Cuts in order to automatically segment Multiple Sclerosis (MS) lesions in MRI. We replace the manual interaction with a robust EM-based approach in order to discriminate between MS lesions and the Normal Appearing Brain Tissues (NABT). Evaluation is performed in synthetic and real images showing good agreement between the automatic segmentation and the target segmentation. We compare our algorithm with the state of the art techniques and with several manual segmentations. An advantage of our algorithm over previously published ones is the possibility to semi-automatically improve the segmentation due to the Graph Cuts interactive feature.

[The method of accelerating osteanagenesis and revascularization of tissue engineered bone in big animal in vivo].

PubMed

Chen, Bin; Pei, Guo-xian; Wang, Ke; Jin, Dan; Wei, Kuan-hai; Ren, Gao-hong

2003-02-01

To study whether tissue engineered bone can repair the large segment bone defect of large animal or not. To observe what character the fascia flap played during the osteanagenesis and revascularization process of tissue engineered bone. 9 Chinese goats were made 2 cm left tibia diaphyseal defect. The repairing effect of the defects was evaluated by ECT, X-ray and histology. 27 goats were divided into three groups: group of CHAP, the defect was filled with coral hydroxyapatite (CHAP); group of tissue engineered bone, the defect was filled with CHAP + bone marrow stroma cells (BMSc); group of fascia flap, the defect was filled with CHAP + BMSc + fascia flap. After finished culturing and inducing the BMSc, CHAP of group of tissue engineered bone and of fascia flap was combined with it. Making fascia flap, different materials as described above were then implanted separately into the defects. Radionuclide bone imaging was used to monitor the revascularization of the implants at 2, 4, 8 weeks after operation. X-ray examination, optical density index of X-ray film, V-G staining of tissue slice of the implants were used at 4, 8, 12 weeks after operation, and the biomechanical character of the specimens were tested at 12 weeks post operation. In the first study, the defect showed no bone regeneration phenomenon. 2 cm tibia defect was an ideal animal model. In the second study, group of CHAP manifested a little trace of bone regeneration, as to group of tissue engineered bone, the defect was almost repaired totally. In group of fascia flap, with the assistance of fascia flap which gave more chance to making implants to get more nutrient, the repair was quite complete. The model of 2 cm caprine tibia diaphyseal defect cannot be repaired by goat itself and can satisfy the tissue engineering's demands. Tissue engineered bone had good ability to repair large segment tibia defect of goat. Fascia flap can accelerate the revascularization process of tissue engineered bone. And by this way, it augment the ability of tissue engineered bone to repair the large bone defect of goat.

Robust QRS detection for HRV estimation from compressively sensed ECG measurements for remote health-monitoring systems.

PubMed

Pant, Jeevan K; Krishnan, Sridhar

2018-03-15

To present a new compressive sensing (CS)-based method for the acquisition of ECG signals and for robust estimation of heart-rate variability (HRV) parameters from compressively sensed measurements with high compression ratio. CS is used in the biosensor to compress the ECG signal. Estimation of the locations of QRS segments is carried out by applying two algorithms on the compressed measurements. The first algorithm reconstructs the ECG signal by enforcing a block-sparse structure on the first-order difference of the signal, so the transient QRS segments are significantly emphasized on the first-order difference of the signal. Multiple block-divisions of the signals are carried out with various block lengths, and multiple reconstructed signals are combined to enhance the robustness of the localization of the QRS segments. The second algorithm removes errors in the locations of QRS segments by applying low-pass filtering and morphological operations. The proposed CS-based method is found to be effective for the reconstruction of ECG signals by enforcing transient QRS structures on the first-order difference of the signal. It is demonstrated to be robust not only to high compression ratio but also to various artefacts present in ECG signals acquired by using on-body wireless sensors. HRV parameters computed by using the QRS locations estimated from the signals reconstructed with a compression ratio as high as 90% are comparable with that computed by using QRS locations estimated by using the Pan-Tompkins algorithm. The proposed method is useful for the realization of long-term HRV monitoring systems by using CS-based low-power wireless on-body biosensors.

Myocardial perfusion abnormalities in asymptomatic patients with systemic lupus erythematosus

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

Hosenpud, J.D.; Montanaro, A.; Hart, M.V.

1984-08-01

Accelerated coronary artery disease and myocardial infarction in young patients with systemic lupus erythematosus is well documented; however, the prevalence of coronary involvement is unknown. Accordingly, 26 patients with systemic lupus were selected irrespective of previous cardiac history to undergo exercise thallium-201 cardiac scintigraphy. Segmental perfusion abnormalities were present in 10 of the 26 studies (38.5 percent). Five patients had reversible defects suggesting ischemia, four patients had persistent defects consistent with scar, and one patient had both reversible and persistent defects in two areas. There was no correlation between positive thallium results and duration of disease, amount of corticosteroid treatment,more » major organ system involvement or age. Only a history of pericarditis appeared to be associated with positive thallium-201 results (p less than 0.05). It is concluded that segmental myocardial perfusion abnormalities are common in patients with systemic lupus erythematosus. Whether this reflects large-vessel coronary disease or small-vessel abnormalities remains to be determined.« less

Segmenting words from natural speech: subsegmental variation in segmental cues.

PubMed

Rytting, C Anton; Brew, Chris; Fosler-Lussier, Eric

2010-06-01

Most computational models of word segmentation are trained and tested on transcripts of speech, rather than the speech itself, and assume that speech is converted into a sequence of symbols prior to word segmentation. We present a way of representing speech corpora that avoids this assumption, and preserves acoustic variation present in speech. We use this new representation to re-evaluate a key computational model of word segmentation. One finding is that high levels of phonetic variability degrade the model's performance. While robustness to phonetic variability may be intrinsically valuable, this finding needs to be complemented by parallel studies of the actual abilities of children to segment phonetically variable speech.

Identification of Matra Region and Overlapping Characters for OCR of Printed Bengali Scripts

NASA Astrophysics Data System (ADS)

Goswami, Subhra Sundar

One of the important reasons for poor recognition rate in optical character recognition (OCR) system is the error in character segmentation. In case of Bangla scripts, the errors occur due to several reasons, which include incorrect detection of matra (headline), over-segmentation and under-segmentation. We have proposed a robust method for detecting the headline region. Existence of overlapping characters (in under-segmented parts) in scanned printed documents is a major problem in designing an effective character segmentation procedure for OCR systems. In this paper, a predictive algorithm is developed for effectively identifying overlapping characters and then selecting the cut-borders for segmentation. Our method can be successfully used in achieving high recognition result.

Three-dimensional segmentation of luminal and adventitial borders in serial intravascular ultrasound images

NASA Technical Reports Server (NTRS)

Shekhar, R.; Cothren, R. M.; Vince, D. G.; Chandra, S.; Thomas, J. D.; Cornhill, J. F.

1999-01-01

Intravascular ultrasound (IVUS) provides exact anatomy of arteries, allowing accurate quantitative analysis. Automated segmentation of IVUS images is a prerequisite for routine quantitative analyses. We present a new three-dimensional (3D) segmentation technique, called active surface segmentation, which detects luminal and adventitial borders in IVUS pullback examinations of coronary arteries. The technique was validated against expert tracings by computing correlation coefficients (range 0.83-0.97) and William's index values (range 0.37-0.66). The technique was statistically accurate, robust to image artifacts, and capable of segmenting a large number of images rapidly. Active surface segmentation enabled geometrically accurate 3D reconstruction and visualization of coronary arteries and volumetric measurements.

Analysis of image thresholding segmentation algorithms based on swarm intelligence

NASA Astrophysics Data System (ADS)

Zhang, Yi; Lu, Kai; Gao, Yinghui; Yang, Bo

2013-03-01

Swarm intelligence-based image thresholding segmentation algorithms are playing an important role in the research field of image segmentation. In this paper, we briefly introduce the theories of four existing image segmentation algorithms based on swarm intelligence including fish swarm algorithm, artificial bee colony, bacteria foraging algorithm and particle swarm optimization. Then some image benchmarks are tested in order to show the differences of the segmentation accuracy, time consumption, convergence and robustness for Salt & Pepper noise and Gaussian noise of these four algorithms. Through these comparisons, this paper gives qualitative analyses for the performance variance of the four algorithms. The conclusions in this paper would give a significant guide for the actual image segmentation.

Medical image segmentation based on SLIC superpixels model

NASA Astrophysics Data System (ADS)

Chen, Xiang-ting; Zhang, Fan; Zhang, Ruo-ya

2017-01-01

Medical imaging has been widely used in clinical practice. It is an important basis for medical experts to diagnose the disease. However, medical images have many unstable factors such as complex imaging mechanism, the target displacement will cause constructed defect and the partial volume effect will lead to error and equipment wear, which increases the complexity of subsequent image processing greatly. The segmentation algorithm which based on SLIC (Simple Linear Iterative Clustering, SLIC) superpixels is used to eliminate the influence of constructed defect and noise by means of the feature similarity in the preprocessing stage. At the same time, excellent clustering effect can reduce the complexity of the algorithm extremely, which provides an effective basis for the rapid diagnosis of experts.

Surgical repair of sciatic nerve traumatic rupture: technical considerations and approaches.

PubMed

Abou-Al-Shaar, Hussam; Yoon, Nam; Mahan, Mark A

2018-01-01

Traumatic proximal sciatic nerve rupture poses surgical repair dilemmas. Disruption often causes a large nerve gap after proximal neuroma and distal scar removal. Also, autologous graft material to bridge the segmental defect may be insufficient, given the sciatic nerve diameter. The authors utilized knee flexion to allow single neurorrhaphy repair of a large sciatic nerve defect, bringing healthy proximal stump to healthy distal segment. To avoid aberrant regeneration, the authors split the sciatic nerve into common peroneal and tibial divisions. After 3 months, the patient can fully extend the knee and has evidence of distal regeneration and nerve continuity without substantial injury. The video can be found here: https://youtu.be/lsezRT5I8MU .

Video Segmentation Descriptors for Event Recognition

DTIC Science & Technology

2014-12-08

Velastin, 3D Extended Histogram of Oriented Gradients (3DHOG) for Classification of Road Users in Urban Scenes , BMVC, 2009. [3] M.-Y. Chen and A. Hauptmann...computed on 3D volume outputted by the hierarchical segmentation . Each video is described as follows. Each supertube is temporally divided in n-frame...strength of these descriptors is their adaptability to the scene variations since they are grounded on a video segmentation . This makes them naturally robust

Context-based automated defect classification system using multiple morphological masks

DOEpatents

Gleason, Shaun S.; Hunt, Martin A.; Sari-Sarraf, Hamed

2002-01-01

Automatic detection of defects during the fabrication of semiconductor wafers is largely automated, but the classification of those defects is still performed manually by technicians. This invention includes novel digital image analysis techniques that generate unique feature vector descriptions of semiconductor defects as well as classifiers that use these descriptions to automatically categorize the defects into one of a set of pre-defined classes. Feature extraction techniques based on multiple-focus images, multiple-defect mask images, and segmented semiconductor wafer images are used to create unique feature-based descriptions of the semiconductor defects. These feature-based defect descriptions are subsequently classified by a defect classifier into categories that depend on defect characteristics and defect contextual information, that is, the semiconductor process layer(s) with which the defect comes in contact. At the heart of the system is a knowledge database that stores and distributes historical semiconductor wafer and defect data to guide the feature extraction and classification processes. In summary, this invention takes as its input a set of images containing semiconductor defect information, and generates as its output a classification for the defect that describes not only the defect itself, but also the location of that defect with respect to the semiconductor process layers.

Segmental transport after unreamed intramedullary nailing. Preliminary report of a "Monorail" system.

PubMed

Raschke, M J; Mann, J W; Oedekoven, G; Claudi, B F

1992-09-01

The Ilizarov method of segmental bone transport has been shown to be an alternative to more conventional treatments of posttraumatic bony defects. After extensive clinical experience with the unreamed tibial nail in open fractures up to Grade IIIb, a new monorail fixation system for callus distraction and segmental bone transport was devised. This Monorail system is composed of an unreamed intramedullary (IM) nail and a unilateral AO distraction device. The new fixation method and the preliminary clinical experience are reported here. Four patients who previously sustained Grades II-IIIb open tibial fractures had an average bony defect of 9 cm. Two patients had previous bony infections. All patients had had serial debridements and myocutaneous flaps were required in three patients. An unreamed IM nail was inserted, and the transport device was applied. After an osteotomy, segmental transport was carried out until docking was achieved. The external fixator was removed after interlocking of the transported segment. The mean duration of external fixation was 17.9 days/cm and the mean period until roentgenographic consolidation of the distraction and nonunion site was 41.2 days/cm. There were two pin-tract infections but no IM infections. One nail broke after osseous consolidation of the regenerate at the distal interlocking site and required exchange. The goal of transport was achieved in all cases without angular or rotational deformity or length discrepancy. There were no neurovascular injuries.

Computed tomography arterial portography for assessment of portal vein injury after blunt hepatic trauma

PubMed Central

Fu, Chen-Ju; Wong, Yon-Cheong; Tsang, Yuk-Ming; Wang, Li-Jen; Chen, Huan-Wu; Ku, Yi-Kang; Wu, Cheng-Hsien; Chen, Huan-Wen; Kang, Shih-Ching

2015-01-01

PURPOSE Intrahepatic portal vein injuries secondary to blunt abdominal trauma are difficult to diagnose and can result in insidious bleeding. We aimed to compare computed tomography arterial portography (CTAP), reperfusion CTAP (rCTAP), and conventional computed tomography (CT) for diagnosing portal vein injuries after blunt hepatic trauma. METHODS Patients with blunt hepatic trauma, who were eligible for nonoperative management, underwent CTAP, rCTAP, and CT. The number and size of perfusion defects observed using the three methods were compared. RESULTS A total of 13 patients (seven males/six females) with a mean age of 34.5±14.1 years were included in the study. A total of 36 hepatic segments had perfusion defects on rCTAP and CT, while there were 47 hepatic segments with perfusion defects on CTAP. The size of perfusion defects on CT (239 cm3; interquartile range [IQR]: 129.5, 309.5) and rCTAP (238 cm3; IQR: 129.5, 310.5) were significantly smaller compared with CTAP (291 cm3; IQR: 136, 371) (both, P = 0.002). CONCLUSION Perfusion defects measured by CTAP were significantly greater than those determined by either rCTAP or CT in cases of blunt hepatic trauma. This finding suggests that CTAP is superior to rCTAP and CT in evaluating portal vein injuries after blunt liver trauma. PMID:26268303

Robust and efficient fiducial tracking for augmented reality in HD-laparoscopic video streams

NASA Astrophysics Data System (ADS)

Mueller, M.; Groch, A.; Baumhauer, M.; Maier-Hein, L.; Teber, D.; Rassweiler, J.; Meinzer, H.-P.; Wegner, In.

2012-02-01

Augmented Reality (AR) is a convenient way of porting information from medical images into the surgical field of view and can deliver valuable assistance to the surgeon, especially in laparoscopic procedures. In addition, high definition (HD) laparoscopic video devices are a great improvement over the previously used low resolution equipment. However, in AR applications that rely on real-time detection of fiducials from video streams, the demand for efficient image processing has increased due to the introduction of HD devices. We present an algorithm based on the well-known Conditional Density Propagation (CONDENSATION) algorithm which can satisfy these new demands. By incorporating a prediction around an already existing and robust segmentation algorithm, we can speed up the whole procedure while leaving the robustness of the fiducial segmentation untouched. For evaluation purposes we tested the algorithm on recordings from real interventions, allowing for a meaningful interpretation of the results. Our results show that we can accelerate the segmentation by a factor of 3.5 on average. Moreover, the prediction information can be used to compensate for fiducials that are temporarily occluded or out of scope, providing greater stability.

Electrocardiogram ST-Segment Morphology Delineation Method Using Orthogonal Transformations

PubMed Central

2016-01-01

Differentiation between ischaemic and non-ischaemic transient ST segment events of long term ambulatory electrocardiograms is a persisting weakness in present ischaemia detection systems. Traditional ST segment level measuring is not a sufficiently precise technique due to the single point of measurement and severe noise which is often present. We developed a robust noise resistant orthogonal-transformation based delineation method, which allows tracing the shape of transient ST segment morphology changes from the entire ST segment in terms of diagnostic and morphologic feature-vector time series, and also allows further analysis. For these purposes, we developed a new Legendre Polynomials based Transformation (LPT) of ST segment. Its basis functions have similar shapes to typical transient changes of ST segment morphology categories during myocardial ischaemia (level, slope and scooping), thus providing direct insight into the types of time domain morphology changes through the LPT feature-vector space. We also generated new Karhunen and Lo ève Transformation (KLT) ST segment basis functions using a robust covariance matrix constructed from the ST segment pattern vectors derived from the Long Term ST Database (LTST DB). As for the delineation of significant transient ischaemic and non-ischaemic ST segment episodes, we present a study on the representation of transient ST segment morphology categories, and an evaluation study on the classification power of the KLT- and LPT-based feature vectors to classify between ischaemic and non-ischaemic ST segment episodes of the LTST DB. Classification accuracy using the KLT and LPT feature vectors was 90% and 82%, respectively, when using the k-Nearest Neighbors (k = 3) classifier and 10-fold cross-validation. New sets of feature-vector time series for both transformations were derived for the records of the LTST DB which is freely available on the PhysioNet website and were contributed to the LTST DB. The KLT and LPT present new possibilities for human-expert diagnostics, and for automated ischaemia detection. PMID:26863140

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.

SOM-based nonlinear least squares twin SVM via active contours for noisy image segmentation

NASA Astrophysics Data System (ADS)

Xie, Xiaomin; Wang, Tingting

2017-02-01

In this paper, a nonlinear least square twin support vector machine (NLSTSVM) with the integration of active contour model (ACM) is proposed for noisy image segmentation. Efforts have been made to seek the kernel-generated surfaces instead of hyper-planes for the pixels belonging to the foreground and background, respectively, using the kernel trick to enhance the performance. The concurrent self organizing maps (SOMs) are applied to approximate the intensity distributions in a supervised way, so as to establish the original training sets for the NLSTSVM. Further, the two sets are updated by adding the global region average intensities at each iteration. Moreover, a local variable regional term rather than edge stop function is adopted in the energy function to ameliorate the noise robustness. Experiment results demonstrate that our model holds the higher segmentation accuracy and more noise robustness.

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.

Determination of Isthmocele Using a Foley Catheter During Laparoscopic Repair of Cesarean Scar Defect.

PubMed

Akdemir, Ali; Sahin, Cagdas; Ari, Sabahattin Anil; Ergenoglu, Mete; Ulukus, Murat; Karadadas, Nedim

2018-01-01

To demonstrate a new technique of isthmocele repair via laparoscopic surgery. Case report (Canadian Task Force classification III). The local Ethics Committee waived the requirement for approval. Isthmocele localized at a low uterine segment is a defect of a previous caesarean scar due to poor myometrial healing after surgery [1]. This pouch accumulates menstrual bleeding, which can cause various disturbances and irregularities, including abnormal uterine bleeding, infertility, pelvic pain, and scar pregnancy [2-6]. Given the absence of a clearly defined surgical method in the literature, choosing the proper approach to treating isthmocele can be arduous. Laparoscopy provides a minimally invasive procedure in women with previous caesarean scar defects. A 28-year-old woman, gravida 2 para 2, presented with a complaint of prolonged postmenstrual bleeding for 5 years. She had undergone 2 cesarean deliveries. Transvaginal ultrasonography revealed a hypoechogenic area with menstrual blood in the anterior lower uterine segment. Magnetic resonance imaging showed an isthmocele localized at the anterior left lateral side of the uterus, with an estimated volume of approximately 12 cm 3 . After patient preparation, laparoscopy was performed. To repair the defect, the uterovesical peritoneal fold was incised and the bladder was mobilized from the lower uterine segment. During this surgery, differentiating the isthmocele from the abdomen can be challenging. Here we used a Foley catheter to identify the isthmocele. To do this, after mobilizing the bladder from the lower uterine segment, we inserted a Foley catheter into the uterine cavity through the cervical canal. We then filled the balloon of the catheter at the lower uterine segment under laparoscopic view, which allowed clear identification of the isthmocele pouch. The uterine defect was then incised. The isthmocele cavity was accessed, the margins of the pouch were debrided, and the edges were surgically reapproximated with continuous nonlocking single layer 2-0 polydioxanone sutures. We believed that single-layer suturing could provide for proper healing without necrosis due to suturation. During the procedure, the vesicouterine space was dissected without difficulty. A urine bag was collected with clear urine, and there was no gas leakage; thus, we considered a safety test for the bladder superfluous. Based on concerns about the possible increased risk of adhesions, we did not cover peritoneum over the suture. The patients experienced no associated complications, and she reported complete resolution of prolonged postmenstrual bleeding at a 3-month follow-up. Even though the literature is cloudy in this area, a laparoscopic approach to repairing an isthmocele is a safe and minimally invasive procedure. Our approach described here involves inserting a Foley catheter in the uterine cavity through the cervical canal, then filling the balloon in the lower uterine segment under laparoscopic view to identify the isthmocele. Copyright © 2017 AAGL. Published by Elsevier Inc. All rights reserved.

Accurate Detection of Dysmorphic Nuclei Using Dynamic Programming and Supervised Classification.

PubMed

Verschuuren, Marlies; De Vylder, Jonas; Catrysse, Hannes; Robijns, Joke; Philips, Wilfried; De Vos, Winnok H

2017-01-01

A vast array of pathologies is typified by the presence of nuclei with an abnormal morphology. Dysmorphic nuclear phenotypes feature dramatic size changes or foldings, but also entail much subtler deviations such as nuclear protrusions called blebs. Due to their unpredictable size, shape and intensity, dysmorphic nuclei are often not accurately detected in standard image analysis routines. To enable accurate detection of dysmorphic nuclei in confocal and widefield fluorescence microscopy images, we have developed an automated segmentation algorithm, called Blebbed Nuclei Detector (BleND), which relies on two-pass thresholding for initial nuclear contour detection, and an optimal path finding algorithm, based on dynamic programming, for refining these contours. Using a robust error metric, we show that our method matches manual segmentation in terms of precision and outperforms state-of-the-art nuclear segmentation methods. Its high performance allowed for building and integrating a robust classifier that recognizes dysmorphic nuclei with an accuracy above 95%. The combined segmentation-classification routine is bound to facilitate nucleus-based diagnostics and enable real-time recognition of dysmorphic nuclei in intelligent microscopy workflows.

Accurate Detection of Dysmorphic Nuclei Using Dynamic Programming and Supervised Classification

PubMed Central

Verschuuren, Marlies; De Vylder, Jonas; Catrysse, Hannes; Robijns, Joke; Philips, Wilfried

2017-01-01

A vast array of pathologies is typified by the presence of nuclei with an abnormal morphology. Dysmorphic nuclear phenotypes feature dramatic size changes or foldings, but also entail much subtler deviations such as nuclear protrusions called blebs. Due to their unpredictable size, shape and intensity, dysmorphic nuclei are often not accurately detected in standard image analysis routines. To enable accurate detection of dysmorphic nuclei in confocal and widefield fluorescence microscopy images, we have developed an automated segmentation algorithm, called Blebbed Nuclei Detector (BleND), which relies on two-pass thresholding for initial nuclear contour detection, and an optimal path finding algorithm, based on dynamic programming, for refining these contours. Using a robust error metric, we show that our method matches manual segmentation in terms of precision and outperforms state-of-the-art nuclear segmentation methods. Its high performance allowed for building and integrating a robust classifier that recognizes dysmorphic nuclei with an accuracy above 95%. The combined segmentation-classification routine is bound to facilitate nucleus-based diagnostics and enable real-time recognition of dysmorphic nuclei in intelligent microscopy workflows. PMID:28125723

New robust algorithm for tracking cells in videos of Drosophila morphogenesis based on finding an ideal path in segmented spatio-temporal cellular structures.

PubMed

Bellaïche, Yohanns; Bosveld, Floris; Graner, François; Mikula, Karol; Remesíková, Mariana; Smísek, Michal

2011-01-01

In this paper, we present a novel algorithm for tracking cells in time lapse confocal microscopy movie of a Drosophila epithelial tissue during pupal morphogenesis. We consider a 2D + time video as a 3D static image, where frames are stacked atop each other, and using a spatio-temporal segmentation algorithm we obtain information about spatio-temporal 3D tubes representing evolutions of cells. The main idea for tracking is the usage of two distance functions--first one from the cells in the initial frame and second one from segmented boundaries. We track the cells backwards in time. The first distance function attracts the subsequently constructed cell trajectories to the cells in the initial frame and the second one forces them to be close to centerlines of the segmented tubular structures. This makes our tracking algorithm robust against noise and missing spatio-temporal boundaries. This approach can be generalized to a 3D + time video analysis, where spatio-temporal tubes are 4D objects.

A prior feature SVM – MRF based method for mouse brain segmentation

PubMed Central

Wu, Teresa; Bae, Min Hyeok; Zhang, Min; Pan, Rong; Badea, Alexandra

2012-01-01

We introduce an automated method, called prior feature Support Vector Machine- Markov Random Field (pSVMRF), to segment three-dimensional mouse brain Magnetic Resonance Microscopy (MRM) images. Our earlier work, extended MRF (eMRF) integrated Support Vector Machine (SVM) and Markov Random Field (MRF) approaches, leading to improved segmentation accuracy; however, the computation of eMRF is very expensive, which may limit its performance on segmentation and robustness. In this study pSVMRF reduces training and testing time for SVM, while boosting segmentation performance. Unlike the eMRF approach, where MR intensity information and location priors are linearly combined, pSVMRF combines this information in a nonlinear fashion, and enhances the discriminative ability of the algorithm. We validate the proposed method using MR imaging of unstained and actively stained mouse brain specimens, and compare segmentation accuracy with two existing methods: eMRF and MRF. C57BL/6 mice are used for training and testing, using cross validation. For formalin fixed C57BL/6 specimens, pSVMRF outperforms both eMRF and MRF. The segmentation accuracy for C57BL/6 brains, stained or not, was similar for larger structures like hippocampus and caudate putamen, (~87%), but increased substantially for smaller regions like susbtantia nigra (from 78.36% to 91.55%), and anterior commissure (from ~50% to ~80%). To test segmentation robustness against increased anatomical variability we add two strains, BXD29 and a transgenic mouse model of Alzheimer’s Disease. Segmentation accuracy for new strains is 80% for hippocampus, and caudate putamen, indicating that pSVMRF is a promising approach for phenotyping mouse models of human brain disorders. PMID:21988893

A prior feature SVM-MRF based method for mouse brain segmentation.

PubMed

Wu, Teresa; Bae, Min Hyeok; Zhang, Min; Pan, Rong; Badea, Alexandra

2012-02-01

We introduce an automated method, called prior feature Support Vector Machine-Markov Random Field (pSVMRF), to segment three-dimensional mouse brain Magnetic Resonance Microscopy (MRM) images. Our earlier work, extended MRF (eMRF) integrated Support Vector Machine (SVM) and Markov Random Field (MRF) approaches, leading to improved segmentation accuracy; however, the computation of eMRF is very expensive, which may limit its performance on segmentation and robustness. In this study pSVMRF reduces training and testing time for SVM, while boosting segmentation performance. Unlike the eMRF approach, where MR intensity information and location priors are linearly combined, pSVMRF combines this information in a nonlinear fashion, and enhances the discriminative ability of the algorithm. We validate the proposed method using MR imaging of unstained and actively stained mouse brain specimens, and compare segmentation accuracy with two existing methods: eMRF and MRF. C57BL/6 mice are used for training and testing, using cross validation. For formalin fixed C57BL/6 specimens, pSVMRF outperforms both eMRF and MRF. The segmentation accuracy for C57BL/6 brains, stained or not, was similar for larger structures like hippocampus and caudate putamen, (~87%), but increased substantially for smaller regions like susbtantia nigra (from 78.36% to 91.55%), and anterior commissure (from ~50% to ~80%). To test segmentation robustness against increased anatomical variability we add two strains, BXD29 and a transgenic mouse model of Alzheimer's disease. Segmentation accuracy for new strains is 80% for hippocampus, and caudate putamen, indicating that pSVMRF is a promising approach for phenotyping mouse models of human brain disorders. Copyright © 2011 Elsevier Inc. All rights reserved.

A Study of BMP-2-Loaded Bipotential Electrolytic Complex around a Biphasic Calcium Phosphate-Derived (BCP) Scaffold for Repair of Large Segmental Bone Defect

PubMed Central

Paul, Kallyanashis; Padalhin, Andrew R.; Linh, Nguyen Thuy Ba; Kim, Boram; Sarkar, Swapan Kumar; Lee, Byong Taek

2016-01-01

A bipotential polyelectrolyte complex with biphasic calcium phosphate (BCP) powder dispersion provides an excellent option for protein adsorption and cell attachment and can facilitate enhanced bone regeneration. Application of the bipotential polyelectrolyte complex embedded in a spongy scaffold for faster healing of large segmental bone defects (LSBD) can be a promising endeavor in tissue engineering application. In the present study, a hollow scaffold suitable for segmental long bone replacement was fabricated by the sponge replica method applying the microwave sintering process. The fabricated scaffold was coated with calcium alginate at the shell surface, and genipin-crosslinked chitosan with biphasic calcium phosphate (BCP) dispersion was loaded at the central hollow core. The chitosan core was subsequently loaded with BMP-2. The electrolytic complex was characterized using SEM, porosity measurement, FTIR spectroscopy and BMP-2 release for 30 days. In vitro studies such as MTT, live/dead, cell proliferation and cell differentiation were performed. The scaffold was implanted into a 12 mm critical size defect of a rabbit radius. The efficacy of this complex is evaluated through an in vivo study, one and two month post implantation. BV/TV ratio for BMP-2 loaded sample was (42±1.76) higher compared with hollow BCP scaffold (32±0.225). PMID:27711142

The Midline Protein Regulates Axon Guidance by Blocking the Reiteration of Neuroblast Rows within the Drosophila Ventral Nerve Cord

PubMed Central

Manavalan, Mary Ann; Gaziova, Ivana; Bhat, Krishna Moorthi

2013-01-01

Guiding axon growth cones towards their targets is a fundamental process that occurs in a developing nervous system. Several major signaling systems are involved in axon-guidance, and disruption of these systems causes axon-guidance defects. However, the specific role of the environment in which axons navigate in regulating axon-guidance has not been examined in detail. In Drosophila, the ventral nerve cord is divided into segments, and half-segments and the precursor neuroblasts are formed in rows and columns in individual half-segments. The row-wise expression of segment-polarity genes within the neuroectoderm provides the initial row-wise identity to neuroblasts. Here, we show that in embryos mutant for the gene midline, which encodes a T-box DNA binding protein, row-2 neuroblasts and their neuroectoderm adopt a row-5 identity. This reiteration of row-5 ultimately creates a non-permissive zone or a barrier, which prevents the extension of interneuronal longitudinal tracts along their normal anterior-posterior path. While we do not know the nature of the barrier, the axon tracts either stall when they reach this region or project across the midline or towards the periphery along this zone. Previously, we had shown that midline ensures ancestry-dependent fate specification in a neuronal lineage. These results provide the molecular basis for the axon guidance defects in midline mutants and the significance of proper specification of the environment to axon-guidance. These results also reveal the importance of segmental polarity in guiding axons from one segment to the next, and a link between establishment of broad segmental identity and axon guidance. PMID:24385932

A shape prior-based MRF model for 3D masseter muscle segmentation

NASA Astrophysics Data System (ADS)

Majeed, Tahir; Fundana, Ketut; Lüthi, Marcel; Beinemann, Jörg; Cattin, Philippe

2012-02-01

Medical image segmentation is generally an ill-posed problem that can only be solved by incorporating prior knowledge. The ambiguities arise due to the presence of noise, weak edges, imaging artifacts, inhomogeneous interior and adjacent anatomical structures having similar intensity profile as the target structure. In this paper we propose a novel approach to segment the masseter muscle using the graph-cut incorporating additional 3D shape priors in CT datasets, which is robust to noise; artifacts; and shape deformations. The main contribution of this paper is in translating the 3D shape knowledge into both unary and pairwise potentials of the Markov Random Field (MRF). The segmentation task is casted as a Maximum-A-Posteriori (MAP) estimation of the MRF. Graph-cut is then used to obtain the global minimum which results in the segmentation of the masseter muscle. The method is tested on 21 CT datasets of the masseter muscle, which are noisy with almost all possessing mild to severe imaging artifacts such as high-density artifacts caused by e.g. the very common dental fillings and dental implants. We show that the proposed technique produces clinically acceptable results to the challenging problem of muscle segmentation, and further provide a quantitative and qualitative comparison with other methods. We statistically show that adding additional shape prior into both unary and pairwise potentials can increase the robustness of the proposed method in noisy datasets.

An efficient global energy optimization approach for robust 3D plane segmentation of point clouds

NASA Astrophysics Data System (ADS)

Dong, Zhen; Yang, Bisheng; Hu, Pingbo; Scherer, Sebastian

2018-03-01

Automatic 3D plane segmentation is necessary for many applications including point cloud registration, building information model (BIM) reconstruction, simultaneous localization and mapping (SLAM), and point cloud compression. However, most of the existing 3D plane segmentation methods still suffer from low precision and recall, and inaccurate and incomplete boundaries, especially for low-quality point clouds collected by RGB-D sensors. To overcome these challenges, this paper formulates the plane segmentation problem as a global energy optimization because it is robust to high levels of noise and clutter. First, the proposed method divides the raw point cloud into multiscale supervoxels, and considers planar supervoxels and individual points corresponding to nonplanar supervoxels as basic units. Then, an efficient hybrid region growing algorithm is utilized to generate initial plane set by incrementally merging adjacent basic units with similar features. Next, the initial plane set is further enriched and refined in a mutually reinforcing manner under the framework of global energy optimization. Finally, the performances of the proposed method are evaluated with respect to six metrics (i.e., plane precision, plane recall, under-segmentation rate, over-segmentation rate, boundary precision, and boundary recall) on two benchmark datasets. Comprehensive experiments demonstrate that the proposed method obtained good performances both in high-quality TLS point clouds (i.e., http://SEMANTIC3D.NET)

3D statistical shape models incorporating 3D random forest regression voting for robust CT liver segmentation

NASA Astrophysics Data System (ADS)

Norajitra, Tobias; Meinzer, Hans-Peter; Maier-Hein, Klaus H.

2015-03-01

During image segmentation, 3D Statistical Shape Models (SSM) usually conduct a limited search for target landmarks within one-dimensional search profiles perpendicular to the model surface. In addition, landmark appearance is modeled only locally based on linear profiles and weak learners, altogether leading to segmentation errors from landmark ambiguities and limited search coverage. We present a new method for 3D SSM segmentation based on 3D Random Forest Regression Voting. For each surface landmark, a Random Regression Forest is trained that learns a 3D spatial displacement function between the according reference landmark and a set of surrounding sample points, based on an infinite set of non-local randomized 3D Haar-like features. Landmark search is then conducted omni-directionally within 3D search spaces, where voxelwise forest predictions on landmark position contribute to a common voting map which reflects the overall position estimate. Segmentation experiments were conducted on a set of 45 CT volumes of the human liver, of which 40 images were randomly chosen for training and 5 for testing. Without parameter optimization, using a simple candidate selection and a single resolution approach, excellent results were achieved, while faster convergence and better concavity segmentation were observed, altogether underlining the potential of our approach in terms of increased robustness from distinct landmark detection and from better search coverage.

Vertebra identification using template matching modelmp and K-means clustering.

PubMed

Larhmam, Mohamed Amine; Benjelloun, Mohammed; Mahmoudi, Saïd

2014-03-01

Accurate vertebra detection and segmentation are essential steps for automating the diagnosis of spinal disorders. This study is dedicated to vertebra alignment measurement, the first step in a computer-aided diagnosis tool for cervical spine trauma. Automated vertebral segment alignment determination is a challenging task due to low contrast imaging and noise. A software tool for segmenting vertebrae and detecting subluxations has clinical significance. A robust method was developed and tested for cervical vertebra identification and segmentation that extracts parameters used for vertebra alignment measurement. Our contribution involves a novel combination of a template matching method and an unsupervised clustering algorithm. In this method, we build a geometric vertebra mean model. To achieve vertebra detection, manual selection of the region of interest is performed initially on the input image. Subsequent preprocessing is done to enhance image contrast and detect edges. Candidate vertebra localization is then carried out by using a modified generalized Hough transform (GHT). Next, an adapted cost function is used to compute local voted centers and filter boundary data. Thereafter, a K-means clustering algorithm is applied to obtain clusters distribution corresponding to the targeted vertebrae. These clusters are combined with the vote parameters to detect vertebra centers. Rigid segmentation is then carried out by using GHT parameters. Finally, cervical spine curves are extracted to measure vertebra alignment. The proposed approach was successfully applied to a set of 66 high-resolution X-ray images. Robust detection was achieved in 97.5 % of the 330 tested cervical vertebrae. An automated vertebral identification method was developed and demonstrated to be robust to noise and occlusion. This work presents a first step toward an automated computer-aided diagnosis system for cervical spine trauma detection.

A robust firearm identification algorithm of forensic ballistics specimens

NASA Astrophysics Data System (ADS)

Chuan, Z. L.; Jemain, A. A.; Liong, C.-Y.; Ghani, N. A. M.; Tan, L. K.

2017-09-01

There are several inherent difficulties in the existing firearm identification algorithms, include requiring the physical interpretation and time consuming. Therefore, the aim of this study is to propose a robust algorithm for a firearm identification based on extracting a set of informative features from the segmented region of interest (ROI) using the simulated noisy center-firing pin impression images. The proposed algorithm comprises Laplacian sharpening filter, clustering-based threshold selection, unweighted least square estimator, and segment a square ROI from the noisy images. A total of 250 simulated noisy images collected from five different pistols of the same make, model and caliber are used to evaluate the robustness of the proposed algorithm. This study found that the proposed algorithm is able to perform the identical task on the noisy images with noise levels as high as 70%, while maintaining a firearm identification accuracy rate of over 90%.

Multi-spectral brain tissue segmentation using automatically trained k-Nearest-Neighbor classification.

PubMed

Vrooman, Henri A; Cocosco, Chris A; van der Lijn, Fedde; Stokking, Rik; Ikram, M Arfan; Vernooij, Meike W; Breteler, Monique M B; Niessen, Wiro J

2007-08-01

Conventional k-Nearest-Neighbor (kNN) classification, which has been successfully applied to classify brain tissue in MR data, requires training on manually labeled subjects. This manual labeling is a laborious and time-consuming procedure. In this work, a new fully automated brain tissue classification procedure is presented, in which kNN training is automated. This is achieved by non-rigidly registering the MR data with a tissue probability atlas to automatically select training samples, followed by a post-processing step to keep the most reliable samples. The accuracy of the new method was compared to rigid registration-based training and to conventional kNN-based segmentation using training on manually labeled subjects for segmenting gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF) in 12 data sets. Furthermore, for all classification methods, the performance was assessed when varying the free parameters. Finally, the robustness of the fully automated procedure was evaluated on 59 subjects. The automated training method using non-rigid registration with a tissue probability atlas was significantly more accurate than rigid registration. For both automated training using non-rigid registration and for the manually trained kNN classifier, the difference with the manual labeling by observers was not significantly larger than inter-observer variability for all tissue types. From the robustness study, it was clear that, given an appropriate brain atlas and optimal parameters, our new fully automated, non-rigid registration-based method gives accurate and robust segmentation results. A similarity index was used for comparison with manually trained kNN. The similarity indices were 0.93, 0.92 and 0.92, for CSF, GM and WM, respectively. It can be concluded that our fully automated method using non-rigid registration may replace manual segmentation, and thus that automated brain tissue segmentation without laborious manual training is feasible.

Vancomycin-bearing synthetic bone graft delivers rhBMP-2 and promotes healing of critical rat femoral segmental defects.

PubMed

Skelly, Jordan D; Lange, Jeffrey; Filion, Tera M; Li, Xinning; Ayers, David C; Song, Jie

2014-12-01

Bone grafts simultaneously delivering therapeutic proteins and antibiotics may be valuable in orthopaedic trauma care. Previously, we developed a poly(2-hydroxyethyl methacrylate)-nanocrystalline hydroxyapatite (pHEMA-nHA) synthetic bone graft that, when preabsorbed with 400-ng rhBMP-2/7, facilitated the functional repair of critical-size rat femoral defects. Recently, we showed that pHEMA-nHA effectively retains/releases vancomycin and rhBMP-2 in vitro. The success of such a strategy requires that the incorporation of vancomycin does not compromise the structural integrity of the graft nor its ability to promote bone healing. (1) To evaluate the ability of pHEMA-nHA-vancomycin composites in combination with 3-µg rhBMP-2 to repair 5 mm rat femoral segmental defects, and (2) To determine if the encapsulated vancomycin impairs the graft/rhBMP-2-assisted bone repair. pHEMA-nHA-vancomycin, pHEMA-nHA, or collagen sponge control with/without 3-µg rhBMP-2 were press-fit in 5 mm femoral defects in SASCO-SD male rats (289-300 g). Histology, microcomputed tomography, and torsion testing were performed on 8- and 12-week explants to evaluate the extent and quality of repair. The effect of vancomycin on the temporal absorption of endogenous BMP-2 and stromal cell-derived factor-1 was evaluated by immunohistochemistry. These factors are important for bone healing initiation and stem cell recruitment, respectively. Partial bridging of the defect with bony callus by 12 weeks was observed with pHEMA-nHA-vancomycin without rhBMP-2 while full bridging with substantially mineralized callus and partial restoration of torsional strength was achieved with 3-µg rhBMP-2. The presence of vancomycin changed the absorption patterns of endogenous proteins on the grafts, but did not appear to substantially compromise graft healing. The composite pHEMA-nHA-vancomycin preabsorbed with 3-µg rhBMP-2 promoted repair of 5 mm rat femoral segmental defects. With the sample sizes applied, vancomycin encapsulation did not appear to have a negative effect on bone healing. pHEMA-nHA-vancomycin preabsorbed with rhBMP-2 may be useful in the repair of critical-size long bone defects prone to infections.

Dishevelled 2 is essential for cardiac outflow tract development, somite segmentation and neural tube closure.

PubMed

Hamblet, Natasha S; Lijam, Nardos; Ruiz-Lozano, Pilar; Wang, Jianbo; Yang, Yasheng; Luo, Zhenge; Mei, Lin; Chien, Kenneth R; Sussman, Daniel J; Wynshaw-Boris, Anthony

2002-12-01

The murine dishevelled 2 (Dvl2) gene is an ortholog of the Drosophila segment polarity gene Dishevelled, a member of the highly conserved Wingless/Wnt developmental pathway. Dvl2-deficient mice were produced to determine the role of Dvl2 in mammalian development. Mice containing null mutations in Dvl2 present with 50% lethality in both inbred 129S6 and in a hybrid 129S6-NIH Black Swiss background because of severe cardiovascular outflow tract defects, including double outlet right ventricle, transposition of the great arteries and persistent truncus arteriosis. The majority of the surviving Dvl2(-/-) mice were female, suggesting that penetrance was influenced by sex. Expression of Pitx2 and plexin A2 was attenuated in Dvl2 null mutants, suggesting a defect in cardiac neural crest development during outflow tract formation. In addition, approximately 90% of Dvl2(-/-) mice have vertebral and rib malformations that affect the proximal as well as the distal parts of the ribs. These skeletal abnormalities were more pronounced in mice deficient for both Dvl1 and Dvl2. Somite differentiation markers used to analyze Dvl2(-/-) and Dvl1(-/-);Dvl2(-/-) mutant embryos revealed mildly aberrant expression of Uncx4.1, delta 1 and myogenin, suggesting defects in somite segmentation. Finally, 2-3% of Dvl2(-/-) embryos displayed thoracic spina bifida, while virtually all Dvl1/2 double mutant embryos displayed craniorachishisis, a completely open neural tube from the midbrain to the tail. Thus, Dvl2 is essential for normal cardiac morphogenesis, somite segmentation and neural tube closure, and there is functional redundancy between Dvl1 and Dvl2 in some phenotypes.

Effects of Pore Size on the Osteoconductivity and Mechanical Properties of Calcium Phosphate Cement in a Rabbit Model.

PubMed

Zhao, Yi-Nan; Fan, Jun-Jun; Li, Zhi-Quan; Liu, Yan-Wu; Wu, Yao-Ping; Liu, Jian

2017-02-01

Calcium phosphate cement (CPC) porous scaffold is widely used as a suitable bone substitute to repair bone defect, but the optimal pore size is unclear yet. The current study aimed to evaluate the effect of different pore sizes on the processing of bone formation in repairing segmental bone defect of rabbits using CPC porous scaffolds. Three kinds of CPC porous scaffolds with 5 mm diameters and 12 mm length were prepared with the same porosity but different pore sizes (Group A: 200-300 µm, Group B: 300-450 µm, Group C: 450-600 µm, respectively). Twelve millimeter segmental bone defects were created in the middle of the radius bone and filled with different kinds of CPC cylindrical scaffolds. After 4, 12, and 24 weeks, alkaline phosphatase (ALP), histological assessment, and mechanical properties evaluation were performed in all three groups. After 4 weeks, ALP activity increased in all groups but was highest in Group A with smallest pore size. The new bone formation within the scaffolds was not obvious in all groups. After 12 weeks, the new bone formation within the scaffolds was obvious in each group and highest in Group A. At 24 weeks, no significant difference in new bone formation was observed among different groups. Besides the osteoconductive effect, Group A with smallest pore size also had the best mechanical properties in vivo at 12 weeks. We demonstrate that pore size has a significant effect on the osteoconductivity and mechanical properties of calcium phosphate cement porous scaffold in vivo. Small pore size favors the bone formation in the early stage and may be more suitable for repairing segmental bone defect in vivo. © 2016 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

Repair of bone segment defects with surface porous fiber-reinforced polymethyl methacrylate (PMMA) composite prosthesis: histomorphometric incorporation model and characterization by SEM.

PubMed

Hautamäki, Mikko P; Aho, Allan J; Alander, Pasi; Rekola, Jami; Gunn, Jarmo; Strandberg, Niko; Vallittu, Pekka K

2008-08-01

Polymer technology has provided solutions for filling of bone defects in situations where there may be technical or biological complications with autografts, allografts, and metal prostheses. We present an experimental study on segmental bone defect reconstruction using a polymethylmethacrylate-(PMMA-) based bulk polymer implant prosthesis. We concentrated on osteoconductivity and surface characteristics. A critical size segment defect of the rabbit tibia in 19 animals aged 18-24 weeks was reconstructed with a surface porous glass fiber-reinforced (SPF) prosthesis made of polymethylmethacrylate (PMMA). The biomechanical properties of SPF implant material were previously adjusted technically to mimic the properties of normal cortical bone. A plain PMMA implant with no porosity or fiber reinforcement was used as a control. Radiology, histomorphometry, and scanning electron microscopy (SEM) were used for analysis of bone growth into the prosthesis during incorporation. The radiographic and histological incorporation model showed good host bone contact, and strong formation of new bone as double cortex. Histomorphometric evaluation showed that the bone contact index (BCI) at the posterior surface interface was higher with the SPF implant than for the control. The total appositional bone growth over the posterior surface (area %) was also stronger for the SPF implant than for controls. Both bone growth into the porous surface and the BCI results were related to the quality, coverage, and regularity of the microstructure of the porous surface. Porous surface structure enhanced appositional bone growth onto the SPF implant. Under load-bearing conditions the implant appears to function like an osteoconductive prosthesis, which enables direct mobilization and rapid return to full weight bearing.

Biomechanical stability of novel mechanically adapted open-porous titanium scaffolds in metatarsal bone defects of sheep.

PubMed

Wieding, Jan; Lindner, Tobias; Bergschmidt, Philipp; Bader, Rainer

2015-04-01

Open-porous titanium scaffolds for large segmental bone defects offer advantages like early weight-bearing and limited risk of implant failure. The objective of this experimental study was to determine the biomechanical behavior of novel open-porous titanium scaffolds with mechanical-adapted properties in vivo. Two types of the custom-made, open-porous scaffolds made of Ti6Al4V (Young's modulus: 6-8 GPa and different pore sizes) were implanted into a 20 mm segmental defect in the mid-diaphysis of the metatarsus of sheep, and were stabilized with an osteosynthesis plate. After 12 and 24 weeks postoperatively, torsional testing was performed on the implanted bone and compared to the contralateral non-treated side. Maximum torque, maximum angle, torsional stiffness, fracture energy, shear modulus and shear stress were investigated. Furthermore, bone mineral density (BMD) of the newly formed bone was determined. Mechanical loading capabilities for both scaffolds were similar and about 50% after 12 weeks (e.g., max. torque of approximately 20 Nm). A further increase after 24 weeks was found for most of the investigated parameters. Results for torsional stiffness and shear modulus as well as bone formation depended on the type of scaffold. Increased BMD after 24 weeks was found for one scaffold type but remained constant for the other one. The present data showed the capability of mechanically adapted open-porous titanium scaffolds to function as bone scaffolds for large segmental defects and the influence of the scaffold's stiffness. A further increase in the biomechanical stability can be assumed for longer observation periods of greater than six months. Copyright © 2014 Elsevier Ltd. All rights reserved.

Lung perfusion characteristics in pulmonary arterial hypertension (PAH) and peripheral forms of chronic thromboembolic pulmonary hypertension (pCTEPH): Dual-energy CT experience in 31 patients.

PubMed

Giordano, Jessica; Khung, Suonita; Duhamel, Alain; Hossein-Foucher, Claude; Bellèvre, Dimitri; Lamblin, Nicolas; Remy, Jacques; Remy-Jardin, Martine

2017-04-01

To compare lung perfusion in PAH and pCTEPH on dual-energy CT (DECT) examinations. Thirty-one patients with PAH (group 1; n = 19) and pCTEPH (group 2; n = 12) underwent a dual-energy chest CTA with reconstruction of diagnostic and perfusion images. Perfusion alterations were analysed at a segmental level. V/Q scintigraphy was available in 22 patients (group 1: 13/19; group 2: 9/12). CT perfusion was abnormal in 52.6 % of group 1 patients and in 100 % of group 2 patients (p = 0.0051). The patterns of perfusion alteration significantly differed between the two groups (p < 0.0001): (1) in group 1, 96.6 % of segments with abnormal perfusion showed patchy defects; (2) in group 2, the most frequent abnormalities consisted of patchy (58.5 %) and PE-type (37.5 %) defects. Paired comparison of CT perfusion and scintigraphy showed concordant findings in 76.9 % of group 1 (10/13) and 100 % of group 2 (9/9) patients, with a predominant or an exclusive patchy pattern in group 1 and a mixed pattern of abnormalities in group 2. Lung perfusion alterations at DECT are less frequent and more homogeneous in PAH than in pCTEPH, with a high level of concordant findings with V/Q scintigraphy. • Depiction of chronic pulmonary embolism exclusively located on peripheral arteries is difficult. • The main differential diagnosis of pCTEPH is PAH. • The pattern of DECT perfusion changes can help differentiate PAH and pCETPH. • In PAH, almost all segments with abnormal perfusion showed patchy defects. • In pCTEPH, patchy and PE-type defects were the most frequent abnormalities.

Haemodynamic changes in hepatocellular carcinoma and liver parenchyma under balloon occlusion of the hepatic artery.

PubMed

Sugihara, Fumie; Murata, Satoru; Ueda, Tatsuo; Yasui, Daisuke; Yamaguchi, Hidenori; Miki, Izumi; Kawamoto, Chiaki; Uchida, Eiji; Kumita, Shin-Ichiro

2017-06-01

To investigate haemodynamic changes in hepatocellular carcinoma (HCC) and liver under hepatic artery occlusion. Thirty-eight HCC nodules in 25 patients were included. Computed tomography (CT) during hepatic arteriography (CTHA) with and without balloon occlusion of the hepatic artery was performed. CT attenuation and enhancement volume of HCC and liver with and without balloon occlusion were measured on CTHA. Influence of balloon position (segmental or subsegmental branch) was evaluated based on differences in HCC-to-liver attenuation ratio (H/L ratio) and enhancement volume of HCC and liver. In the segmental group (n = 20), H/L ratio and enhancement volume of HCC and liver were significantly lower with balloon occlusion than without balloon occlusion. However, in the subsegmental group (n = 18), H/L ratio was significantly higher and liver enhancement volume was significantly lower with balloon occlusion; HCC enhancement volume was similar with and without balloon occlusion. Rate of change in H/L ratio and enhancement volume of HCC and liver were lower in the segmental group than in the subsegmental group. There were significantly more perfusion defects in HCC in the segmental group. Hepatic artery occlusion causes haemodynamic changes in HCC and liver, especially with segmental occlusion. • Hepatic artery occlusion causes haemodynamic changes in hepatocellular carcinoma and liver. • Segmental occlusion decreased rate of change in hepatocellular carcinoma-to-liver attenuation ratio. • Subsegmental occlusion increased rate of change in hepatocellular carcinoma-to-liver attenuation ratio. • Hepatic artery occlusion decreased enhancement volume of hepatocellular carcinoma and liver. • Hepatic artery occlusion causes perfusion defects in hepatocellular carcinoma.

Probing topological protection using a designer surface plasmon structure

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

Gao, Fei; Gao, Zhen; Shi, Xihang

Topological photonic states, inspired by robust chiral edge states in topological insulators, have recently been demonstrated in a few photonic systems, including an array of coupled on-chip ring resonators at communication wavelengths. However, the intrinsic difference between electrons and photons determines that the 'topological protection' in time-reversal-invariant photonic systems does not share the same robustness as its counterpart in electronic topological insulators. Here in a designer surface plasmon platform consisting of tunable metallic sub-wavelength structures, we construct photonic topological edge states and probe their robustness against a variety of defect classes, including some common time-reversal-invariant photonic defects that can breakmore » the topological protection, but do not exist in electronic topological insulators. Furthermore, this is also an experimental realization of anomalous Floquet topological edge states, whose topological phase cannot be predicted by the usual Chern number topological invariants.« less

Probing topological protection using a designer surface plasmon structure

DOE PAGES

Gao, Fei; Gao, Zhen; Shi, Xihang; ...

2016-05-20

Topological photonic states, inspired by robust chiral edge states in topological insulators, have recently been demonstrated in a few photonic systems, including an array of coupled on-chip ring resonators at communication wavelengths. However, the intrinsic difference between electrons and photons determines that the 'topological protection' in time-reversal-invariant photonic systems does not share the same robustness as its counterpart in electronic topological insulators. Here in a designer surface plasmon platform consisting of tunable metallic sub-wavelength structures, we construct photonic topological edge states and probe their robustness against a variety of defect classes, including some common time-reversal-invariant photonic defects that can breakmore » the topological protection, but do not exist in electronic topological insulators. Furthermore, this is also an experimental realization of anomalous Floquet topological edge states, whose topological phase cannot be predicted by the usual Chern number topological invariants.« less

Robustness analysis of superpixel algorithms to image blur, additive Gaussian noise, and impulse noise

NASA Astrophysics Data System (ADS)

Brekhna, Brekhna; Mahmood, Arif; Zhou, Yuanfeng; Zhang, Caiming

2017-11-01

Superpixels have gradually become popular in computer vision and image processing applications. However, no comprehensive study has been performed to evaluate the robustness of superpixel algorithms in regard to common forms of noise in natural images. We evaluated the robustness of 11 recently proposed algorithms to different types of noise. The images were corrupted with various degrees of Gaussian blur, additive white Gaussian noise, and impulse noise that either made the object boundaries weak or added extra information to it. We performed a robustness analysis of simple linear iterative clustering (SLIC), Voronoi Cells (VCells), flooding-based superpixel generation (FCCS), bilateral geodesic distance (Bilateral-G), superpixel via geodesic distance (SSS-G), manifold SLIC (M-SLIC), Turbopixels, superpixels extracted via energy-driven sampling (SEEDS), lazy random walk (LRW), real-time superpixel segmentation by DBSCAN clustering, and video supervoxels using partially absorbing random walks (PARW) algorithms. The evaluation process was carried out both qualitatively and quantitatively. For quantitative performance comparison, we used achievable segmentation accuracy (ASA), compactness, under-segmentation error (USE), and boundary recall (BR) on the Berkeley image database. The results demonstrated that all algorithms suffered performance degradation due to noise. For Gaussian blur, Bilateral-G exhibited optimal results for ASA and USE measures, SLIC yielded optimal compactness, whereas FCCS and DBSCAN remained optimal for BR. For the case of additive Gaussian and impulse noises, FCCS exhibited optimal results for ASA, USE, and BR, whereas Bilateral-G remained a close competitor in ASA and USE for Gaussian noise only. Additionally, Turbopixel demonstrated optimal performance for compactness for both types of noise. Thus, no single algorithm was able to yield optimal results for all three types of noise across all performance measures. Conclusively, to solve real-world problems effectively, more robust superpixel algorithms must be developed.

Segmentation of Nerve Bundles and Ganglia in Spine MRI Using Particle Filters

PubMed Central

Dalca, Adrian; Danagoulian, Giovanna; Kikinis, Ron; Schmidt, Ehud; Golland, Polina

2011-01-01

Automatic segmentation of spinal nerve bundles that originate within the dural sac and exit the spinal canal is important for diagnosis and surgical planning. The variability in intensity, contrast, shape and direction of nerves seen in high resolution myelographic MR images makes segmentation a challenging task. In this paper, we present an automatic tracking method for nerve segmentation based on particle filters. We develop a novel approach to particle representation and dynamics, based on Bézier splines. Moreover, we introduce a robust image likelihood model that enables delineation of nerve bundles and ganglia from the surrounding anatomical structures. We demonstrate accurate and fast nerve tracking and compare it to expert manual segmentation. PMID:22003741

Segmentation of nerve bundles and ganglia in spine MRI using particle filters.

PubMed

Dalca, Adrian; Danagoulian, Giovanna; Kikinis, Ron; Schmidt, Ehud; Golland, Polina

2011-01-01

Automatic segmentation of spinal nerve bundles that originate within the dural sac and exit the spinal canal is important for diagnosis and surgical planning. The variability in intensity, contrast, shape and direction of nerves seen in high resolution myelographic MR images makes segmentation a challenging task. In this paper, we present an automatic tracking method for nerve segmentation based on particle filters. We develop a novel approach to particle representation and dynamics, based on Bézier splines. Moreover, we introduce a robust image likelihood model that enables delineation of nerve bundles and ganglia from the surrounding anatomical structures. We demonstrate accurate and fast nerve tracking and compare it to expert manual segmentation.

Usefulness of automatic QT dispersion measurement for detecting exercise-induced myocardial ischemia.

PubMed

Takase, Bonpei; Masaki, Nobuyuki; Hattori, Hidemi; Ishihara, Masayuki; Kurita, Akira

2009-06-01

The electrocardiographic index of QT dispersion (QTd) is related to the occurrence of arrhythmia. In patients with suspected or known coronary artery disease, QTd may be affected by exercise. We investigated whether QTd that is automatically calculated by a newly developed computer system could be used as a marker of exercise-induced myocardial ischemia. The design of this study was prospective and observational. Eighty-three consecutive patients were enrolled in this study. Their QTd was measured at rest and after 3 min of exercise during exercise-stress Thallium-201 scintigraphy and compared with conventional ST-segment changes. The patients were classified into 4 groups (normal group, redistribution group, fixed defect group, redistribution with fixed defect group) based on the result of single photon emission computed tomography. As statistical analysis, one-way ANOVA with post-hoc Scheffe's method, receiver-operating characteristics (ROC) and multiple logistic regression analysis were performed. At rest, QTd was significantly greater (p<0.05) in the fixed defect group (52+/-21 ms) and the redistribution with fixed defect group (53+/-20 ms) than in the normal group (32+/-14 ms) and the redistribution group (31+/-16 ms). However, QTd tended to increase after exercise in the redistribution group, while QTd tended to decrease in the normal group, the fixed defect group, and the redistribution with fixed defect group (QTd after exercise, normal group, 28+/-17 ms, redistribution group, 35+/-19 ms, fixed defect group, 43+/-25 ms, redistribution with fixed defect group, 49+/-27 ms). Exercise significantly increased QTcd (RR interval-corrected QT dispersion) in the redistribution group. The best cut-off values of QTd and QTcd obtained from ROC curves for exercise-induced myocardial ischemia were 41.6 ms and 40.4 ms, respectively (Qtd--AUC 0.68, 95%CI 0.53- 0.83 and QTcd--AUC 0.67, 95%CI 0.55-0.80). Using these values as cut-off ones, QTd, QTcd, and conventional ST-segment change had comparable sensitivities and specificities for detecting exercise-induced myocardial ischemia (sensitivity - 60%, 58% and 49%, respectively;specificity - 78%, 80% and 83%, respectively). In addition, multiple logistic regression analysis showed that QTd (OR=2.01, 95%CI 1.15-4.10, p<0.05), QTcd (OR=2.12, 95% CI 1.02-4.30, p<0.05) and ST-segment change (OR=1.89, 95%CI 1.03-3.40, p<0.05), were the significantly associated with exercise-induced myocardial ischemia. QT dispersion and/or QTcd after exercise could be a useful marker for exercise-induced myocardial ischemia in routine clinical practice.

Improved Healing of Large, Osseous, Segmental Defects by Reverse Dynamization: Evaluation in a Sheep Model

DTIC Science & Technology

2016-10-01

characterization of a novel external fixator for dynamizing ovine osseous defects. Poster No. 2185. Orthopedic Research Society Annual Meeting, Orlando...REPORT: Annual PREPARED FOR: U.S. Army Medical Research and Materiel Command Fort Detrick, Maryland 21702-5012 DISTRIBUTION STATEMENT...SPONSOR/MONITOR’S ACRONYM(S) U.S. Army Medical Research and Materiel Command Fort Detrick, Maryland 21702-5012 11. SPONSOR/MONITOR’S REPORT NUMBER(S

Functional Reconstruction of a Combined Tendocutaneous Defect of the Achilles Using a Segmental Rectus Femoris Myofascial Construct: A Viable Alternative

PubMed Central

DeFazio, Michael Vincent; Han, Kevin Dong

2014-01-01

The composite anterolateral thigh flap with vascularized fascia lata has emerged as a workhorse at our institution for complex Achilles defects requiring both tendon and soft tissue reconstruction. Safe elevation of this flap, however, is occasionally challenged by absent or inadequate perforators supplying the anterolateral thigh. When discovered intraoperatively, alternative options derived from the same vascular network can be pursued. We present the case of a 74-year-old male who underwent composite Achilles defect reconstruction using a segmental rectus femoris myofascial free flap. Following graduated rehabilitation, postoperatively, the patient resumed full activity and was able to ambulate on his tip-toes. At 1-year follow-up, active total range of motion of the reconstructed ankle exceeded 85% of the unaffected side, and donor site morbidity was negligible. American Orthopaedic Foot and Ankle Society and Short Form-36 scores improved by 78.8% and 28.8%, respectively, compared to preoperative baseline assessments. Based on our findings, we advocate for use of the combined rectus femoris myofascial free flap as a rescue option for reconstructing composite Achilles tendon/posterior leg defects in the setting of inadequate anterolateral thigh perforators. To our knowledge, this is the first report to describe use of this flap for such an indication. PMID:24883281

Observation of zone folding induced acoustic topological insulators and the role of spin-mixing defects

NASA Astrophysics Data System (ADS)

Deng, Yuanchen; Ge, Hao; Tian, Yuan; Lu, Minghui; Jing, Yun

2017-11-01

This article reports on the experimental realization of a flow-free, pseudospin-based acoustic topological insulator designed using the strategy of zone folding. Robust sound one-way propagation is demonstrated with the presence of non-spin-mixing defects. On the other hand, it is shown that spin-mixing defects, which break the geometric symmetry and therefore the pseudo-time-reversal symmetry, can open up nontrivial band gaps within the edge state frequency band, and their width can be tailored by the extent of the defect. This provides a possible route for realizing tunable acoustic topological insulators.

Effects of CT resolution and radiodensity threshold on the CFD evaluation of nasal airflow.

PubMed

Quadrio, Maurizio; Pipolo, Carlotta; Corti, Stefano; Messina, Francesco; Pesci, Chiara; Saibene, Alberto M; Zampini, Samuele; Felisati, Giovanni

2016-03-01

The article focuses on the robustness of a CFD-based procedure for the quantitative evaluation of the nasal airflow. CFD ability to yield robust results with respect to the unavoidable procedural and modeling inaccuracies must be demonstrated to allow this tool to become part of the clinical practice in this field. The present article specifically addresses the sensitivity of the CFD procedure to the spatial resolution of the available CT scans, as well as to the choice of the segmentation level of the CT images. We found no critical problems concerning these issues; nevertheless, the choice of the segmentation level is potentially delicate if carried out by an untrained operator.

Robust Spatial Autoregressive Modeling for Hardwood Log Inspection

Treesearch

Dongping Zhu; A.A. Beex

1994-01-01

We explore the application of a stochastic texture modeling method toward a machine vision system for log inspection in the forest products industry. This machine vision system uses computerized tomography (CT) imaging to locate and identify internal defects in hardwood logs. The application of CT to such industrial vision problems requires efficient and robust image...

Spine Patterning Is Guided by Segmentation of the Notochord Sheath.

PubMed

Wopat, Susan; Bagwell, Jennifer; Sumigray, Kaelyn D; Dickson, Amy L; Huitema, Leonie F A; Poss, Kenneth D; Schulte-Merker, Stefan; Bagnat, Michel

2018-02-20

The spine is a segmented axial structure made of alternating vertebral bodies (centra) and intervertebral discs (IVDs) assembled around the notochord. Here, we show that, prior to centra formation, the outer epithelial cell layer of the zebrafish notochord, the sheath, segments into alternating domains corresponding to the prospective centra and IVD areas. This process occurs sequentially in an anteroposterior direction via the activation of Notch signaling in alternating segments of the sheath, which transition from cartilaginous to mineralizing domains. Subsequently, osteoblasts are recruited to the mineralized domains of the notochord sheath to form mature centra. Tissue-specific manipulation of Notch signaling in sheath cells produces notochord segmentation defects that are mirrored in the spine. Together, our findings demonstrate that notochord sheath segmentation provides a template for vertebral patterning in the zebrafish spine. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

The Palatal Approach to Distraction Osteogenesis of the Anterior Maxillary Alveolus.

PubMed

Bell, Robert E

2015-07-01

This report describes the palatal approach to gain access for osteodistraction of the anterior maxilla to improve the vector of force during distraction. This case report illustrates a novel approach to anterior maxillary osteodistraction. The palatal approach allows the maxillary segment to be moved anteriorly and inferiorly. This is in contrast to the buccal approach, in which the palatal tissue creates a vector of force toward the palate. The vascular pedicle for the transport segment is the labial mucosa and musculature. In the present case, the alveolar segment was advanced 3.6 mm anteriorly and 12.2 mm inferiorly as measured by pre- and postoperative computed tomograms. This patient with a large vertical alveolar defect and high smile line had successful restoration with dental implants. The result has been stable for 14 months. In this case, the palatal approach to the anterior maxillary osteotomy was shown to be an effective method of reconstructing a large vertical anterior defect. Copyright © 2015 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.

Hierarchical layered and semantic-based image segmentation using ergodicity map

NASA Astrophysics Data System (ADS)

Yadegar, Jacob; Liu, Xiaoqing

2010-04-01

Image segmentation plays a foundational role in image understanding and computer vision. Although great strides have been made and progress achieved on automatic/semi-automatic image segmentation algorithms, designing a generic, robust, and efficient image segmentation algorithm is still challenging. Human vision is still far superior compared to computer vision, especially in interpreting semantic meanings/objects in images. We present a hierarchical/layered semantic image segmentation algorithm that can automatically and efficiently segment images into hierarchical layered/multi-scaled semantic regions/objects with contextual topological relationships. The proposed algorithm bridges the gap between high-level semantics and low-level visual features/cues (such as color, intensity, edge, etc.) through utilizing a layered/hierarchical ergodicity map, where ergodicity is computed based on a space filling fractal concept and used as a region dissimilarity measurement. The algorithm applies a highly scalable, efficient, and adaptive Peano- Cesaro triangulation/tiling technique to decompose the given image into a set of similar/homogenous regions based on low-level visual cues in a top-down manner. The layered/hierarchical ergodicity map is built through a bottom-up region dissimilarity analysis. The recursive fractal sweep associated with the Peano-Cesaro triangulation provides efficient local multi-resolution refinement to any level of detail. The generated binary decomposition tree also provides efficient neighbor retrieval mechanisms for contextual topological object/region relationship generation. Experiments have been conducted within the maritime image environment where the segmented layered semantic objects include the basic level objects (i.e. sky/land/water) and deeper level objects in the sky/land/water surfaces. Experimental results demonstrate the proposed algorithm has the capability to robustly and efficiently segment images into layered semantic objects/regions with contextual topological relationships.

History, heresy and radiology in scientific discovery.

PubMed

McCredie, J

2009-10-01

Nowadays, most drugs reach the market after research has established their pharmacology, safety and efficacy. That was not always the case 50 years ago. Thalidomide was used before its target cell or mode of action were known. Commencing with the thalidomide catastrophe--an epidemic of gross birth defects (1958-1962)--thalidomide's origins are revisited to show how this drug came to be made and sold in the 1950s. Thalidomide intersected with Australian radiology in the 1970s. The site and mode of action of the drug was deduced from X-rays of thalidomide-induced bone defects, which have classical radiological signs of sensory neuropathic osteoarthropathy. The longitudinal reduction deformities follow the distribution of segmental sensory innervation of the limb skeleton, indicating neural crest as the target organ. Injury to one level of neural crest halts normal neurotrophism and deletes the dependent segment--a previously unrecognised embryonic mechanism that explains most non-genetic birth defects. The final common pathway is neural crest injury and failure of normal neurotrophism to result in longitudinal reduction deformities, for example, phocomelia.

Functional end-arterial circulation of the choroid assessed by using fat embolism and electric circuit simulation.

PubMed

Lee, Ji Eun; Ahn, Ki Su; Park, Keun Heung; Pak, Kang Yeun; Kim, Hak Jin; Byon, Ik Soo; Park, Sung Who

2017-05-30

The discrepancy in the choroidal circulation between anatomy and function has remained unsolved for several decades. Postmortem cast studies revealed extensive anastomotic channels, but angiographic studies indicated end-arterial circulation. We carried out experimental fat embolism in cats and electric circuit simulation. Perfusion defects were observed in two categories. In the scatter perfusion defects suggesting an embolism at the terminal arterioles, fluorescein dye filled the non-perfused lobule slowly from the adjacent perfused lobule. In the segmental perfusion defects suggesting occlusion of the posterior ciliary arteries, the hypofluorescent segment became perfused by spontaneous resolution of the embolism without subsequent smaller infarction. The angiographic findings could be simulated with an electric circuit. Although electric currents flowed to the disconnected lobule, the level was very low compared with that of the connected ones. The choroid appeared to be composed of multiple sectors with no anastomosis to other sectors, but to have its own anastomotic arterioles in each sector. Blood flows through the continuous choriocapillaris bed in an end-arterial nature functionally to follow a pressure gradient due to the drainage through the collector venule.

The retinal phenotype of Usher syndrome: pathophysiological insights from animal models.

PubMed

El-Amraoui, Aziz; Petit, Christine

2014-03-01

The Usher syndrome (USH) is the most prevalent cause of inherited deaf-blindness. Three clinical subtypes, USH1-3, have been defined, and ten USH genes identified. The hearing impairment due to USH gene defects has been shown to result from improper organisation of the hair bundle, the sound receptive structure of sensory hair cells. In contrast, the cellular basis of the visual defect is less well understood as this phenotype is absent in almost all the USH mouse models that faithfully mimic the human hearing impairment. Structural and molecular interspecies discrepancies regarding photoreceptor calyceal processes and the association with the distribution of USH1 proteins have recently been unravelled, and have led to the conclusion that a defect in the USH1 protein complex-mediated connection between the photoreceptor outer segment and the surrounding calyceal processes (in both rods and cones), and the inner segment (in rods only), probably causes the USH1 retinal dystrophy in humans. Copyright © 2013 Académie des sciences. Published by Elsevier SAS. All rights reserved.

Fully automatic segmentation of the femur from 3D-CT images using primitive shape recognition and statistical shape models.

PubMed

Ben Younes, Lassad; Nakajima, Yoshikazu; Saito, Toki

2014-03-01

Femur segmentation is well established and widely used in computer-assisted orthopedic surgery. However, most of the robust segmentation methods such as statistical shape models (SSM) require human intervention to provide an initial position for the SSM. In this paper, we propose to overcome this problem and provide a fully automatic femur segmentation method for CT images based on primitive shape recognition and SSM. Femur segmentation in CT scans was performed using primitive shape recognition based on a robust algorithm such as the Hough transform and RANdom SAmple Consensus. The proposed method is divided into 3 steps: (1) detection of the femoral head as sphere and the femoral shaft as cylinder in the SSM and the CT images, (2) rigid registration between primitives of SSM and CT image to initialize the SSM into the CT image, and (3) fitting of the SSM to the CT image edge using an affine transformation followed by a nonlinear fitting. The automated method provided good results even with a high number of outliers. The difference of segmentation error between the proposed automatic initialization method and a manual initialization method is less than 1 mm. The proposed method detects primitive shape position to initialize the SSM into the target image. Based on primitive shapes, this method overcomes the problem of inter-patient variability. Moreover, the results demonstrate that our method of primitive shape recognition can be used for 3D SSM initialization to achieve fully automatic segmentation of the femur.

Fully automatic segmentation of femurs with medullary canal definition in high and in low resolution CT scans.

PubMed

Almeida, Diogo F; Ruben, Rui B; Folgado, João; Fernandes, Paulo R; Audenaert, Emmanuel; Verhegghe, Benedict; De Beule, Matthieu

2016-12-01

Femur segmentation can be an important tool in orthopedic surgical planning. However, in order to overcome the need of an experienced user with extensive knowledge on the techniques, segmentation should be fully automatic. In this paper a new fully automatic femur segmentation method for CT images is presented. This method is also able to define automatically the medullary canal and performs well even in low resolution CT scans. Fully automatic femoral segmentation was performed adapting a template mesh of the femoral volume to medical images. In order to achieve this, an adaptation of the active shape model (ASM) technique based on the statistical shape model (SSM) and local appearance model (LAM) of the femur with a novel initialization method was used, to drive the template mesh deformation in order to fit the in-image femoral shape in a time effective approach. With the proposed method a 98% convergence rate was achieved. For high resolution CT images group the average error is less than 1mm. For the low resolution image group the results are also accurate and the average error is less than 1.5mm. The proposed segmentation pipeline is accurate, robust and completely user free. The method is robust to patient orientation, image artifacts and poorly defined edges. The results excelled even in CT images with a significant slice thickness, i.e., above 5mm. Medullary canal segmentation increases the geometric information that can be used in orthopedic surgical planning or in finite element analysis. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.

Chevron Defect at the Intersection of Grain Boundaries with Free Surfaces in Au

NASA Astrophysics Data System (ADS)

Radetic, T.; Lançon, F.; Dahmen, U.

2002-08-01

We have identified a new defect at the intersection between grain boundaries and surfaces in Au using atomic resolution transmission electron microscopy. At the junction line of 90° <110> tilt grain boundaries of (110)-(001) orientation with the free surface, a small segment of the grain boundary, about 1nm in length, dissociates into a triangular region with a chevronlike stacking disorder and a distorted hcp structure. The structure and stability of these defects are confirmed by atomistic simulations, and we point out the relationship with the one-dimensional incommensurate structure of the grain boundary.

Evaluation of changes in perfusion defect and left ventricular systolic function using Tc-99m Tetrofosmin single photon emission computed tomography over 3 month period in patients of Acute Myocardial Infarction undergoing primary angioplasty.

PubMed

Kumar, Avs Anil; Kumar, P G; Swami, Ajay; Dinker, Yateendra

2018-01-01

After a primary transluminal coronary angioplasty (PTCA) following AMI (acute myocardial infarction), the perfusion defect and LV (left ventricular) function recover/change over a period of time. The analysis immediately after the procedure may not be true depiction of the exact success of the procedure. There is varying and scanty information available on the natural course of changes in these parameters after a successful PTCA. We hypothesized that majority of change occurs at 3-4 month period. Hence, we undertook this study on the natural course of recovery/changes occurring in perfusion defect size and LV function in first 3 months after primary angioplasty MATERIAL AND METHODS: 30 consecutive cases of first AMI who were taken up for Primary angioplasty were enrolled into the study. Resting MPI(Myocardial perfusion imaging) was done within 24-72 hrs of admission using Tc-99m-Tetrofosmin and after 10-14 weeks. Analysis of LVEF (left ventricular ejection fraction), summed segmental score and extent of perfusion defect was done. Images were processed using autocardiac software of emory tool box and quantification was done using QPS (quantitative perfusion SPECT) and QGS (qualitative perfusion SPECT) softwares. 20 segment scoring method was used for quantification on bull's eye images. Student t test (two tailed, dependent) was used to find the significance of study parameters on continuous scale within each group. Effect size was computed to find the effect. Pearson correlation between perfusion defect and LVEF was performed at acute stage and after 10-14 weeks. The average acute perfusion defect extent was 19.76 ± 12.89% which after 3months became 16.79 ± 12.61%. The summed segmental score changed from 14.31 ± 10.58 to 11.38 ± 10.03 and LVEF improved from 48.40 ± 13.15% to 53.37 ± 12.8%. There was significant improvement in LVEF from acute setting to 10-14 weeks (p = 0.001). There was significant lowering of summed score (p = 0.007). Perfusion defect size showed significant reduction (p = 0.030). Three patients showed deterioration in perfusion defect size and in summed score with reduction in LVEF. Four patients had no change in any of the parameters. Correlation between perfusion defect and LVEF was strong both at baseline (r = -0.705, p < 0.001) and after 10-18 weeks (r = -0.766, p < 0.001). The changes we found in 3 months are similar to earlier studies and also to studies using follow up at 6 months to 1 year. We feel that 3 months is a good enough time to accurately assess the success of primary angioplasty.

Semi-automated brain tumor segmentation on multi-parametric MRI using regularized non-negative matrix factorization.

PubMed

Sauwen, Nicolas; Acou, Marjan; Sima, Diana M; Veraart, Jelle; Maes, Frederik; Himmelreich, Uwe; Achten, Eric; Huffel, Sabine Van

2017-05-04

Segmentation of gliomas in multi-parametric (MP-)MR images is challenging due to their heterogeneous nature in terms of size, appearance and location. Manual tumor segmentation is a time-consuming task and clinical practice would benefit from (semi-) automated segmentation of the different tumor compartments. We present a semi-automated framework for brain tumor segmentation based on non-negative matrix factorization (NMF) that does not require prior training of the method. L1-regularization is incorporated into the NMF objective function to promote spatial consistency and sparseness of the tissue abundance maps. The pathological sources are initialized through user-defined voxel selection. Knowledge about the spatial location of the selected voxels is combined with tissue adjacency constraints in a post-processing step to enhance segmentation quality. The method is applied to an MP-MRI dataset of 21 high-grade glioma patients, including conventional, perfusion-weighted and diffusion-weighted MRI. To assess the effect of using MP-MRI data and the L1-regularization term, analyses are also run using only conventional MRI and without L1-regularization. Robustness against user input variability is verified by considering the statistical distribution of the segmentation results when repeatedly analyzing each patient's dataset with a different set of random seeding points. Using L1-regularized semi-automated NMF segmentation, mean Dice-scores of 65%, 74 and 80% are found for active tumor, the tumor core and the whole tumor region. Mean Hausdorff distances of 6.1 mm, 7.4 mm and 8.2 mm are found for active tumor, the tumor core and the whole tumor region. Lower Dice-scores and higher Hausdorff distances are found without L1-regularization and when only considering conventional MRI data. Based on the mean Dice-scores and Hausdorff distances, segmentation results are competitive with state-of-the-art in literature. Robust results were found for most patients, although careful voxel selection is mandatory to avoid sub-optimal segmentation.

Biomechanical Evaluation of an Injectable and Biodegradable Copolymer P(PF-co-CL) in a Cadaveric Vertebral Body Defect Model

PubMed Central

Fang, Zhong; Giambini, Hugo; Zeng, Heng; Camp, Jon J.; Dadsetan, Mahrokh; Robb, Richard A.; An, Kai-Nan; Yaszemski, Michael J.

2014-01-01

A novel biodegradable copolymer, poly(propylene fumarate-co-caprolactone) [P(PF-co-CL)], has been developed in our laboratory as an injectable scaffold for bone defect repair. In the current study, we evaluated the ability of P(PF-co-CL) to reconstitute the load-bearing capacity of vertebral bodies with lytic lesions. Forty vertebral bodies from four fresh-frozen cadaveric thoracolumbar spines were used for this study. They were randomly divided into four groups: intact vertebral body (intact control), simulated defect without treatment (negative control), defect treated with P(PF-co-CL) (copolymer group), and defect treated with poly(methyl methacrylate) (PMMA group). Simulated metastatic lytic defects were made by removing a central core of the trabecular bone in each vertebral body with an approximate volume of 25% through an access hole in the side of the vertebrae. Defects were then filled by injecting either P(PF-co-CL) or PMMA in situ crosslinkable formulations. After the spines were imaged with quantitative computerized tomography, single vertebral body segments were harvested for mechanical testing. Specimens were compressed until failure or to 25% reduction in body height and ultimate strength and elastic modulus of each specimen were then calculated from the force–displacement data. The average failure strength of the copolymer group was 1.83 times stronger than the untreated negative group and it closely matched the intact vertebral bodies (intact control). The PMMA-treated vertebrae, however, had a failure strength 1.64 times larger compared with the intact control. The elastic modulus followed the same trend. This modulus mismatch between PMMA-treated vertebrae and the host vertebrae could potentially induce a fracture cascade and degenerative changes in adjacent intervertebral discs. In contrast, P(PF-co-CL) restored the mechanical properties of the treated segments similar to the normal, intact, vertebrae. Therefore, P(PF-co-CL) may be a suitable alternative to PMMA for vertebroplasty treatment of vertebral bodies with lytic defects. PMID:24256208

Reversibility by dipyridamole of thallium-201 myocardial scan defects in patients with sarcoidosis

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

Tellier, P.; Paycha, F.; Antony, I.

1988-08-01

In order to clarify the significance of anginal pain and myocardial thallium-201 scan defects in cardiac sarcoidosis, the pharmacologic effect of dipyridamole on myocardial perfusion was assessed by planar thallium-201 myocardial scintigraphy in patients with sarcoidosis. Thallium-201 myocardial scintigraphy was performed at rest and after 0.56 mg/kg intravenous dipyridamole during four minutes in 16 patients with sarcoidosis. The myocardial scan (45-degree and 70-degree left anterior oblique, and anterior views) was divided into 15 segments. Results were evaluated by the number of segmental defects and with a global perfusion score (from 0 to 60) by a semi-quantitative index depending on themore » size and severity of myocardial thallium-201 defects. Thirteen of the 16 patients showed partial or total reversion of their thallium-201 defects on redistribution scanning either at rest or after dipyridamole. The mean (+/- SD) number of myocardial perfusion defects that were present in all the patients decreased from 5.31 +/- 1.78 at rest to 3.25 +/- 2.52 after redistribution (p less than 0.001) and to 2.19 +/- 2.10 after dipyridamole (p less than 0.001). The mean global perfusion score increased from 53.2 +/- 3.0 at rest to 56.2 +/- 2.9 after redistribution (p less than 0.001) and to 57.2 +/- 2.7 after dipyridamole (p less than 0.001). A significant correlation (r = 0.82, p less than 0.001) was found between the increase of global perfusion score on redistribution and after dipyridamole. The reversibility of myocardial scan defects is a common finding in sarcoidosis. It makes unlikely the role of scar fibrosis or extensive confluent granulomas as a mechanism for such defects. The effect of dipyridamole suggests the presence of reversible disorders lying at the coronary microvascular level.« less

Registration of MRI to Intraoperative Radiographs for Target Localization in Spinal Interventions

PubMed Central

De Silva, T; Uneri, A; Ketcha, M D; Reaungamornrat, S; Goerres, J; Jacobson, M W; Vogt, S; Kleinszig, G; Khanna, A J; Wolinsky, J-P; Siewerdsen, J H

2017-01-01

Purpose Decision support to assist in target vertebra localization could provide a useful aid to safe and effective spine surgery. Previous solutions have shown 3D-2D registration of preoperative CT to intraoperative radiographs to reliably annotate vertebral labels for assistance during level localization. We present an algorithm (referred to as MR-LevelCheck) to perform 3D-2D registration based on a preoperative MRI to accommodate the increasingly common clinical scenario in which MRI is used instead of CT for preoperative planning. Methods Straightforward adaptation of gradient/intensity-based methods appropriate to CT-to-radiograph registration is confounded by large mismatch and noncorrespondence in image intensity between MRI and radiographs. The proposed method overcomes such challenges with a simple vertebrae segmentation step using vertebra centroids as seed points (automatically defined within existing workflow). Forwards projections are computed using segmented MRI and registered to radiographs via gradient orientation (GO) similarity and the CMA-ES (Covariance-Matrix-Adaptation Evolutionary-Strategy) optimizer. The method was tested in an IRB-approved study involving 10 patients undergoing cervical, thoracic, or lumbar spine surgery following preoperative MRI. Results The method successfully registered each preoperative MRI to intraoperative radiographs and maintained desirable properties of robustness against image content mismatch and large capture range. Robust registration performance was achieved with projection distance error (PDE) (median ± iqr) = 4.3 ± 2.6 mm (median ± iqr) and 0% failure rate. Segmentation accuracy for the continuous max-flow method yielded Dice coefficient = 88.1 ± 5.2, Accuracy = 90.6 ± 5.7, RMSE = 1.8 ± 0.6 mm, and contour affinity ratio (CAR) = 0.82 ± 0.08. Registration performance was found to be robust for segmentation methods exhibiting RMSE < 3 mm and CAR > 0.50. Conclusion The MR-LevelCheck method provides a potentially valuable extension to a previously developed decision support tool for spine surgery target localization by extending its utility to preoperative MRI while maintaining characteristics of accuracy and robustness. PMID:28050972

TU-H-206-04: An Effective Homomorphic Unsharp Mask Filtering Method to Correct Intensity Inhomogeneity in Daily Treatment MR Images

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

Yang, D; Gach, H; Li, H

Purpose: The daily treatment MRIs acquired on MR-IGRT systems, like diagnostic MRIs, suffer from intensity inhomogeneity issue, associated with B1 and B0 inhomogeneities. An improved homomorphic unsharp mask (HUM) filtering method, automatic and robust body segmentation, and imaging field-of-view (FOV) detection methods were developed to compute the multiplicative slow-varying correction field and correct the intensity inhomogeneity. The goal is to improve and normalize the voxel intensity so that the images could be processed more accurately by quantitative methods (e.g., segmentation and registration) that require consistent image voxel intensity values. Methods: HUM methods have been widely used for years. A bodymore » mask is required, otherwise the body surface in the corrected image would be incorrectly bright due to the sudden intensity transition at the body surface. In this study, we developed an improved HUM-based correction method that includes three main components: 1) Robust body segmentation on the normalized image gradient map, 2) Robust FOV detection (needed for body segmentation) using region growing and morphologic filters, and 3) An effective implementation of HUM using repeated Gaussian convolution. Results: The proposed method was successfully tested on patient images of common anatomical sites (H/N, lung, abdomen and pelvis). Initial qualitative comparisons showed that this improved HUM method outperformed three recently published algorithms (FCM, LEMS, MICO) in both computation speed (by 50+ times) and robustness (in intermediate to severe inhomogeneity situations). Currently implemented in MATLAB, it takes 20 to 25 seconds to process a 3D MRI volume. Conclusion: Compared to more sophisticated MRI inhomogeneity correction algorithms, the improved HUM method is simple and effective. The inhomogeneity correction, body mask, and FOV detection methods developed in this study would be useful as preprocessing tools for many MRI-related research and clinical applications in radiotherapy. Authors have received research grants from ViewRay and Varian.« less

Noonan syndrome: crossed fused ectopic kidneys and focal segmental glomerulosclerosis-a rare association.

PubMed

Gupta, Ankur; Khaira, Ambar; Lal, Charanjit; Mahajan, Sandeep; Tiwari, Suresh C

2009-10-01

Noonan syndrome is characterised by short stature, typical facial dysmorphology and congenital heart defects. Urogenital abnormalities are reported in 10% of the cases. We present a 14-year-old girl with characteristic features of Noonan syndrome and nephrotic-range proteinuria. She had crossed fused ectopic kidneys. Renal biopsy showed focal segmental glomerulosclerosis. Oral steroids were instituted and she responded well. The case highlights this novel renal presentation of Noonan syndrome.

Mandibular kinematics and maximum voluntary bite force following segmental resection of the mandible without or with reconstruction.

PubMed

Linsen, Sabine S; Oikonomou, Annina; Martini, Markus; Teschke, Marcus

2018-05-01

The purpose was to analyze mandibular kinematics and maximum voluntary bite force in patients following segmental resection of the mandible without and with reconstruction (autologous bone, alloplastic total temporomandibular joint replacement (TMJ TJR)). Subjects operated from April 2002 to August 2014 were enrolled in the study. Condylar (CRoM) and incisal (InRoM) range of motion and deflection during opening, condylar retrusion, incisal lateral excursion, mandibular rotation angle during opening, and maximum voluntary bite force were determined on the non-affected site and compared between groups. Influence of co-factors (defect size, soft tissue deficit, neck dissection, radiotherapy, occlusal contact zones (OCZ), and time) was determined. Twelve non-reconstructed and 26 reconstructed patients (13 autologous, 13 TMJ TJR) were included in the study. InRoM opening and bite force were significantly higher (P ≤ .024), and both condylar and incisal deflection during opening significantly lower (P ≤ .027) in reconstructed patients compared with non-reconstructed. Differences between the autologous and the TMJ TJR group were statistically not significant. Co-factors defect size, soft tissue deficit, and neck dissection had the greatest impact on kinematics and number of OCZs on bite force. Reconstructed patients (both autologous and TMJ TJR) have better overall function than non-reconstructed patients. Reconstruction of segmental mandibular resection has positive effects on mandibular function. TMJ TJR seems to be a suitable technique for the reconstruction of mandibular defects including the TMJ complex.

Optimization of Soft Tissue Management, Spacer Design, and Grafting Strategies for Large Segmental Bone Defects using the Chronic Caprine Tibial Defect Model

DTIC Science & Technology

2015-10-01

Several target genes such as Oct4, Sox2, TGFB, and Col1A1 were generally up-regulated in all sections. In distal sections, VWF, PDGFB, and EGFR were...TGFB, and Col1A1 in all sections. No significant main effects were found for target gene fold-change between outer or inner membrane position or distal

When Mommy Comes to the Rescue of Statistics: Infants Combine Top-Down and Bottom-Up Cues to Segment Speech

ERIC Educational Resources Information Center

Mersad, Karima; Nazzi, Thierry

2012-01-01

Transitional Probability (TP) computations are regarded as a powerful learning mechanism that is functional early in development and has been proposed as an initial bootstrapping device for speech segmentation. However, a recent study casts doubt on the robustness of early statistical word-learning. Johnson and Tyler (2010) showed that when…

Scene Segmentation For Autonomous Robotic Navigation Using Sequential Laser Projected Structured Light

NASA Astrophysics Data System (ADS)

Brown, C. David; Ih, Charles S.; Arce, Gonzalo R.; Fertell, David A.

1987-01-01

Vision systems for mobile robots or autonomous vehicles navigating in an unknown terrain environment must provide a rapid and accurate method of segmenting the scene ahead into regions of pathway and background. A major distinguishing feature between the pathway and background is the three dimensional texture of these two regions. Typical methods of textural image segmentation are very computationally intensive, often lack the required robustness, and are incapable of sensing the three dimensional texture of various regions of the scene. A method is presented where scanned laser projected lines of structured light, viewed by a stereoscopically located single video camera, resulted in an image in which the three dimensional characteristics of the scene were represented by the discontinuity of the projected lines. This image was conducive to processing with simple regional operators to classify regions as pathway or background. Design of some operators and application methods, and demonstration on sample images are presented. This method provides rapid and robust scene segmentation capability that has been implemented on a microcomputer in near real time, and should result in higher speed and more reliable robotic or autonomous navigation in unstructured environments.

Hierarchical extraction of urban objects from mobile laser scanning data

NASA Astrophysics Data System (ADS)

Yang, Bisheng; Dong, Zhen; Zhao, Gang; Dai, Wenxia

2015-01-01

Point clouds collected in urban scenes contain a huge number of points (e.g., billions), numerous objects with significant size variability, complex and incomplete structures, and variable point densities, raising great challenges for the automated extraction of urban objects in the field of photogrammetry, computer vision, and robotics. This paper addresses these challenges by proposing an automated method to extract urban objects robustly and efficiently. The proposed method generates multi-scale supervoxels from 3D point clouds using the point attributes (e.g., colors, intensities) and spatial distances between points, and then segments the supervoxels rather than individual points by combining graph based segmentation with multiple cues (e.g., principal direction, colors) of the supervoxels. The proposed method defines a set of rules for merging segments into meaningful units according to types of urban objects and forms the semantic knowledge of urban objects for the classification of objects. Finally, the proposed method extracts and classifies urban objects in a hierarchical order ranked by the saliency of the segments. Experiments show that the proposed method is efficient and robust for extracting buildings, streetlamps, trees, telegraph poles, traffic signs, cars, and enclosures from mobile laser scanning (MLS) point clouds, with an overall accuracy of 92.3%.

Statistical segmentation of multidimensional brain datasets

NASA Astrophysics Data System (ADS)

Desco, Manuel; Gispert, Juan D.; Reig, Santiago; Santos, Andres; Pascau, Javier; Malpica, Norberto; Garcia-Barreno, Pedro

2001-07-01

This paper presents an automatic segmentation procedure for MRI neuroimages that overcomes part of the problems involved in multidimensional clustering techniques like partial volume effects (PVE), processing speed and difficulty of incorporating a priori knowledge. The method is a three-stage procedure: 1) Exclusion of background and skull voxels using threshold-based region growing techniques with fully automated seed selection. 2) Expectation Maximization algorithms are used to estimate the probability density function (PDF) of the remaining pixels, which are assumed to be mixtures of gaussians. These pixels can then be classified into cerebrospinal fluid (CSF), white matter and grey matter. Using this procedure, our method takes advantage of using the full covariance matrix (instead of the diagonal) for the joint PDF estimation. On the other hand, logistic discrimination techniques are more robust against violation of multi-gaussian assumptions. 3) A priori knowledge is added using Markov Random Field techniques. The algorithm has been tested with a dataset of 30 brain MRI studies (co-registered T1 and T2 MRI). Our method was compared with clustering techniques and with template-based statistical segmentation, using manual segmentation as a gold-standard. Our results were more robust and closer to the gold-standard.

A Computational Framework for Automation of Point Defect Calculations

NASA Astrophysics Data System (ADS)

Goyal, Anuj; Gorai, Prashun; Peng, Haowei; Lany, Stephan; Stevanovic, Vladan; National Renewable Energy Laboratory, Golden, Colorado 80401 Collaboration

A complete and rigorously validated open-source Python framework to automate point defect calculations using density functional theory has been developed. The framework provides an effective and efficient method for defect structure generation, and creation of simple yet customizable workflows to analyze defect calculations. The package provides the capability to compute widely accepted correction schemes to overcome finite-size effects, including (1) potential alignment, (2) image-charge correction, and (3) band filling correction to shallow defects. Using Si, ZnO and In2O3as test examples, we demonstrate the package capabilities and validate the methodology. We believe that a robust automated tool like this will enable the materials by design community to assess the impact of point defects on materials performance. National Renewable Energy Laboratory, Golden, Colorado 80401.

Robust frequency diversity based algorithm for clutter noise reduction of ultrasonic signals using multiple sub-spectrum phase coherence

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

Gongzhang, R.; Xiao, B.; Lardner, T.

2014-02-18

This paper presents a robust frequency diversity based algorithm for clutter reduction in ultrasonic A-scan waveforms. The performance of conventional spectral-temporal techniques like Split Spectrum Processing (SSP) is highly dependent on the parameter selection, especially when the signal to noise ratio (SNR) is low. Although spatial beamforming offers noise reduction with less sensitivity to parameter variation, phased array techniques are not always available. The proposed algorithm first selects an ascending series of frequency bands. A signal is reconstructed for each selected band in which a defect is present when all frequency components are in uniform sign. Combining all reconstructed signalsmore » through averaging gives a probability profile of potential defect position. To facilitate data collection and validate the proposed algorithm, Full Matrix Capture is applied on the austenitic steel and high nickel alloy (HNA) samples with 5MHz transducer arrays. When processing A-scan signals with unrefined parameters, the proposed algorithm enhances SNR by 20dB for both samples and consequently, defects are more visible in B-scan images created from the large amount of A-scan traces. Importantly, the proposed algorithm is considered robust, while SSP is shown to fail on the austenitic steel data and achieves less SNR enhancement on the HNA data.« less

Deep Learning Automates the Quantitative Analysis of Individual Cells in Live-Cell Imaging Experiments.

PubMed

Van Valen, David A; Kudo, Takamasa; Lane, Keara M; Macklin, Derek N; Quach, Nicolas T; DeFelice, Mialy M; Maayan, Inbal; Tanouchi, Yu; Ashley, Euan A; Covert, Markus W

2016-11-01

Live-cell imaging has opened an exciting window into the role cellular heterogeneity plays in dynamic, living systems. A major critical challenge for this class of experiments is the problem of image segmentation, or determining which parts of a microscope image correspond to which individual cells. Current approaches require many hours of manual curation and depend on approaches that are difficult to share between labs. They are also unable to robustly segment the cytoplasms of mammalian cells. Here, we show that deep convolutional neural networks, a supervised machine learning method, can solve this challenge for multiple cell types across the domains of life. We demonstrate that this approach can robustly segment fluorescent images of cell nuclei as well as phase images of the cytoplasms of individual bacterial and mammalian cells from phase contrast images without the need for a fluorescent cytoplasmic marker. These networks also enable the simultaneous segmentation and identification of different mammalian cell types grown in co-culture. A quantitative comparison with prior methods demonstrates that convolutional neural networks have improved accuracy and lead to a significant reduction in curation time. We relay our experience in designing and optimizing deep convolutional neural networks for this task and outline several design rules that we found led to robust performance. We conclude that deep convolutional neural networks are an accurate method that require less curation time, are generalizable to a multiplicity of cell types, from bacteria to mammalian cells, and expand live-cell imaging capabilities to include multi-cell type systems.

Deep Learning Automates the Quantitative Analysis of Individual Cells in Live-Cell Imaging Experiments

DOE PAGES

Van Valen, David A.; Kudo, Takamasa; Lane, Keara M.; ...

2016-11-04

Live-cell imaging has opened an exciting window into the role cellular heterogeneity plays in dynamic, living systems. A major critical challenge for this class of experiments is the problem of image segmentation, or determining which parts of a microscope image correspond to which individual cells. Current approaches require many hours of manual curation and depend on approaches that are difficult to share between labs. They are also unable to robustly segment the cytoplasms of mammalian cells. Here, we show that deep convolutional neural networks, a supervised machine learning method, can solve this challenge for multiple cell types across the domainsmore » of life. We demonstrate that this approach can robustly segment fluorescent images of cell nuclei as well as phase images of the cytoplasms of individual bacterial and mammalian cells from phase contrast images without the need for a fluorescent cytoplasmic marker. These networks also enable the simultaneous segmentation and identification of different mammalian cell types grown in co-culture. A quantitative comparison with prior methods demonstrates that convolutional neural networks have improved accuracy and lead to a significant reduction in curation time. We relay our experience in designing and optimizing deep convolutional neural networks for this task and outline several design rules that we found led to robust performance. We conclude that deep convolutional neural networks are an accurate method that require less curation time, are generalizable to a multiplicity of cell types, from bacteria to mammalian cells, and expand live-cell imaging capabilities to include multi-cell type systems.« less

Deep Learning Automates the Quantitative Analysis of Individual Cells in Live-Cell Imaging Experiments

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

Van Valen, David A.; Kudo, Takamasa; Lane, Keara M.

Live-cell imaging has opened an exciting window into the role cellular heterogeneity plays in dynamic, living systems. A major critical challenge for this class of experiments is the problem of image segmentation, or determining which parts of a microscope image correspond to which individual cells. Current approaches require many hours of manual curation and depend on approaches that are difficult to share between labs. They are also unable to robustly segment the cytoplasms of mammalian cells. Here, we show that deep convolutional neural networks, a supervised machine learning method, can solve this challenge for multiple cell types across the domainsmore » of life. We demonstrate that this approach can robustly segment fluorescent images of cell nuclei as well as phase images of the cytoplasms of individual bacterial and mammalian cells from phase contrast images without the need for a fluorescent cytoplasmic marker. These networks also enable the simultaneous segmentation and identification of different mammalian cell types grown in co-culture. A quantitative comparison with prior methods demonstrates that convolutional neural networks have improved accuracy and lead to a significant reduction in curation time. We relay our experience in designing and optimizing deep convolutional neural networks for this task and outline several design rules that we found led to robust performance. We conclude that deep convolutional neural networks are an accurate method that require less curation time, are generalizable to a multiplicity of cell types, from bacteria to mammalian cells, and expand live-cell imaging capabilities to include multi-cell type systems.« less

Deep Learning Automates the Quantitative Analysis of Individual Cells in Live-Cell Imaging Experiments

PubMed Central

Van Valen, David A.; Lane, Keara M.; Quach, Nicolas T.; Maayan, Inbal

2016-01-01

Live-cell imaging has opened an exciting window into the role cellular heterogeneity plays in dynamic, living systems. A major critical challenge for this class of experiments is the problem of image segmentation, or determining which parts of a microscope image correspond to which individual cells. Current approaches require many hours of manual curation and depend on approaches that are difficult to share between labs. They are also unable to robustly segment the cytoplasms of mammalian cells. Here, we show that deep convolutional neural networks, a supervised machine learning method, can solve this challenge for multiple cell types across the domains of life. We demonstrate that this approach can robustly segment fluorescent images of cell nuclei as well as phase images of the cytoplasms of individual bacterial and mammalian cells from phase contrast images without the need for a fluorescent cytoplasmic marker. These networks also enable the simultaneous segmentation and identification of different mammalian cell types grown in co-culture. A quantitative comparison with prior methods demonstrates that convolutional neural networks have improved accuracy and lead to a significant reduction in curation time. We relay our experience in designing and optimizing deep convolutional neural networks for this task and outline several design rules that we found led to robust performance. We conclude that deep convolutional neural networks are an accurate method that require less curation time, are generalizable to a multiplicity of cell types, from bacteria to mammalian cells, and expand live-cell imaging capabilities to include multi-cell type systems. PMID:27814364

Segmental liver ischemia/infarction after elective transjugular intrahepatic portosystemic shunt creation: clinical outcomes in 10 patients.

PubMed

Lopera, Jorge E; Katabathina, Venkata; Bosworth, Brian; Garg, Deepak; Kroma, Ghazwan; Garza-Berlanga, Andres; Suri, Rajeev; Wholey, Michael

2015-06-01

To determine the clinical significance and potential mechanisms of segmental liver ischemia and infarction following elective creation of a transjugular intrahepatic portosystemic shunt (TIPS). A retrospective review of 374 elective TIPS creations between March 2006 and September 2014 was performed, yielding 77 contrast-enhanced scans for review. Patients with imaging evidence of segmental perfusion defects were identified. Model for End-stage Liver Disease scores, liver volume, and percentage of liver ischemia/infarct were calculated. Clinical outcomes after TIPS creation were reviewed. Ten patients showed segmental liver ischemia/infarction on contrast-enhanced imaging after elective TIPS creation. Associated imaging findings included thrombosis of the posterior division (n = 7) and anterior division (n = 3) of the right portal vein (PV). The right hepatic vein was thrombosed in 5 patients, as was the middle hepatic vein in 3 and the left hepatic vein in 1. One patient had acute thrombosis of the shunt and main PV. Three patients developed acute liver failure: 2 died within 30 days and 1 required emergent liver transplantation. One patient died of acute renal failure 20 days after TIPS creation. A large infarct in a transplant recipient resulted in biloma formation. Five patients survived without additional interventions with follow-up times ranging from 3 months to 5 years. Segmental perfusion defects are not an uncommon imaging finding after elective TIPS creation. Segmental ischemia was associated with thrombosis of major branches of the PVs and often of the hepatic veins. Clinical outcomes varied significantly, from transient problems to acute liver failure with high mortality rates. Copyright © 2015 SIR. Published by Elsevier Inc. All rights reserved.

Reconstruction of Traumatic Bone Defect With In Situ Implantation of Dropped Traumatic Segmental Bone Fragments.

PubMed

Lin, Dasheng; Luo, Deqing; Lian, Kejian; Zhai, Wenliang; Ding, Zhenqi

2016-01-01

This study was conducted to determine whether in situ implantation of a dropped traumatic segmental bone fragment is safe and whether the authors' method would reduce the incidence of infectious and related complications. The authors retrospectively reviewed 16 patients with open fractures, including 11 with Gustilo-Anderson type IIIA fractures and 5 with Gustilo-Anderson type IIIB fractures who had a dropped traumatic segmental bone fragment between January 2002 and January 2012. Mean patient age was 35.4 years (range, 19-47 years). There were 10 femurs and 6 tibias. Average postoperative follow-up was 26.8 months (range, 12-60 months). The dropped traumatic segmental bone fragments were cleaned with 3% hydrogen peroxide, placed in separate sterile cups, and soaked in 1% iodophor for 30 minutes. Initial treatment included surgical debridement, wound irrigation, in situ implantation of the dropped traumatic segmental bone fragment, and temporary external fixation. Approximately 4 to 8 weeks later, after successful reconstruction of the soft tissue envelope, minimally invasive plate osteosynthesis was performed. Mean duration of treatment was 8 weeks (range, 6-14 weeks). All patients had fracture union at final follow-up. Mean healing time was 21.8 weeks (range, 14-48 weeks). One patient did not achieve primary union and required bone grafting. One patient with a Gustilo-Anderson type IIIB fracture had deep infection and removal of the dropped traumatic segmental bone fragment and bone grafting. According to the Klemm and Börner classification, 11 patients had excellent results, 3 had good results, and 2 had poor results. With adequate soft tissue coverage, this method was acceptable for the management of open fractures with bone defects. Copyright 2016, SLACK Incorporated.

Detection of small surface defects using DCT based enhancement approach in machine vision systems

NASA Astrophysics Data System (ADS)

He, Fuqiang; Wang, Wen; Chen, Zichen

2005-12-01

Utilizing DCT based enhancement approach, an improved small defect detection algorithm for real-time leather surface inspection was developed. A two-stage decomposition procedure was proposed to extract an odd-odd frequency matrix after a digital image has been transformed to DCT domain. Then, the reverse cumulative sum algorithm was proposed to detect the transition points of the gentle curves plotted from the odd-odd frequency matrix. The best radius of the cutting sector was computed in terms of the transition points and the high-pass filtering operation was implemented. The filtered image was then inversed and transformed back to the spatial domain. Finally, the restored image was segmented by an entropy method and some defect features are calculated. Experimental results show the proposed small defect detection method can reach the small defect detection rate by 94%.

Reconstruction of a Post Traumatic Anterior Maxillary Defect by Transport Distraction Osteogenesis.

PubMed

Rajkumar, K; Neelakandan, R S; Devadoss, Pradeep; Bandyopadhyay, T K

2017-03-01

Rehabilitation of segmental defects of maxilla presents a reconstructive challenge to obtain an ideal osseous form and height with adequate soft tissue investment. Though variety of prosthetic and surgical reconstructive options like the use of vascularized and non vascularized bone grafts are available they produce less than optimal results. Bone transport distraction is a reliable procedure in various maxillofacial bony defect reconstruction techniques. We describe herein a technique of maxillary bone transport distraction using an indigenously designed, custom made trifocal transport distractor performed in a post traumatic avulsive defect of the anterior maxilla. Transport distraction was successful for anterior maxillary alveolar bony regeneration, with excellent soft tissue cover and vestibular depth, which also helped close an oroantral/oronasal fistula.

A Review of Algorithms for Segmentation of Optical Coherence Tomography from Retina

PubMed Central

Kafieh, Raheleh; Rabbani, Hossein; Kermani, Saeed

2013-01-01

Optical coherence tomography (OCT) is a recently established imaging technique to describe different information about the internal structures of an object and to image various aspects of biological tissues. OCT image segmentation is mostly introduced on retinal OCT to localize the intra-retinal boundaries. Here, we review some of the important image segmentation methods for processing retinal OCT images. We may classify the OCT segmentation approaches into five distinct groups according to the image domain subjected to the segmentation algorithm. Current researches in OCT segmentation are mostly based on improving the accuracy and precision, and on reducing the required processing time. There is no doubt that current 3-D imaging modalities are now moving the research projects toward volume segmentation along with 3-D rendering and visualization. It is also important to develop robust methods capable of dealing with pathologic cases in OCT imaging. PMID:24083137

Statistical shape (ASM) and appearance (AAM) models for the segmentation of the cerebellum in fetal ultrasound

NASA Astrophysics Data System (ADS)

Reyes López, Misael; Arámbula Cosío, Fernando

2017-11-01

The cerebellum is an important structure to determine the gestational age of the fetus, moreover most of the abnormalities it presents are related to growth disorders. In this work, we present the results of the segmentation of the fetal cerebellum applying statistical shape and appearance models. Both models were tested on ultrasound images of the fetal brain taken from 23 pregnant women, between 18 and 24 gestational weeks. The accuracy results obtained on 11 ultrasound images show a mean Hausdorff distance of 6.08 mm between the manual segmentation and the segmentation using active shape model, and a mean Hausdorff distance of 7.54 mm between the manual segmentation and the segmentation using active appearance model. The reported results demonstrate that the active shape model is more robust in the segmentation of the fetal cerebellum in ultrasound images.

Development of the segment alignment maintenance system (SAMS) for the Hobby-Eberly Telescope

NASA Astrophysics Data System (ADS)

Booth, John A.; Adams, Mark T.; Ames, Gregory H.; Fowler, James R.; Montgomery, Edward E.; Rakoczy, John M.

2000-07-01

A sensing and control system for maintaining optical alignment of ninety-one 1-meter mirror segments forming the Hobby-Eberly Telescope (HET) primary mirror array is now under development. The Segment Alignment Maintenance System (SAMS) is designed to sense relative shear motion between each segment edge pair and calculated individual segment tip, tilt, and piston position errors. Error information is sent to the HET primary mirror control system, which corrects the physical position of each segment as often as once per minute. Development of SAMS is required to meet optical images quality specifications for the telescope. Segment misalignment over time is though to be due to thermal inhomogeneity within the steel mirror support truss. Challenging problems of sensor resolution, dynamic range, mechanical mounting, calibration, stability, robust algorithm development, and system integration must be overcome to achieve a successful operational solution.

Three-dimensional model simulation and reconstruction of composite total maxillectomy defects with fibula osteomyocutaneous flap flow-through from radial forearm flap.

PubMed

He, Yue; Zhu, Han Guang; Zhang, Zhi Yuan; He, Jie; Sader, Robert

2009-12-01

A total maxillectomy always causes composite defects of maxilla, zygomatic bone, orbital floor or rim, and palatal and nasal mucosa lining. This leads to significant functional and cosmetic consequences after ablative surgery. The purpose of this clinical study was to preliminarily 3-dimensionally reconstruct the defect of total maxillectomy with sufficient bone support and soft tissue lining. Three-dimensional model simulation technique and free fibula osteomyocutaneous flap flow-through from radial forearm flap were used to reconstruct a total maxillectomy defect for a 21-year-old female patient. Preoperatively, the 3-dimensional (3D) simulated resin models of skeleton and fibula were used to design the osteotomies and bone segment replacement. At surgery, a 22-cm-length free fibula was divided into 4 segments to make 1 maxilla skeletal framework in the schedule of the preoperative model surgical planning with a radial forearm flap flow-through for the free fibula flap with skin paddle to repair the palatal and nasal region. Free fibula and radial forearm flap were alive, and the patient was satisfied with the results both esthetically and functionally after dental rehabilitation which was carried out 6 months after surgery. This preliminarily clinical study and case demonstrated that: the fibula osteomyocutaneous flap is an ideal donor site in 3D total maxillectomy defect reconstruction, because of its thickness, length, and bone uniformity which makes ideal support for dental rehabilitation; the flow-through forearm radial flap not only serves as the vascular bridge to midface reconstruction, but also provides sufficient soft tissue cover for the intraoral defect; and the 3D model simulation and preoperative surgical planning are effective methods to refine reconstruction surgery, shorten the surgical time, and predict the outcome after operation.

User-guided segmentation for volumetric retinal optical coherence tomography images

PubMed Central

Yin, Xin; Chao, Jennifer R.; Wang, Ruikang K.

2014-01-01

Abstract. Despite the existence of automatic segmentation techniques, trained graders still rely on manual segmentation to provide retinal layers and features from clinical optical coherence tomography (OCT) images for accurate measurements. To bridge the gap between this time-consuming need of manual segmentation and currently available automatic segmentation techniques, this paper proposes a user-guided segmentation method to perform the segmentation of retinal layers and features in OCT images. With this method, by interactively navigating three-dimensional (3-D) OCT images, the user first manually defines user-defined (or sketched) lines at regions where the retinal layers appear very irregular for which the automatic segmentation method often fails to provide satisfactory results. The algorithm is then guided by these sketched lines to trace the entire 3-D retinal layer and anatomical features by the use of novel layer and edge detectors that are based on robust likelihood estimation. The layer and edge boundaries are finally obtained to achieve segmentation. Segmentation of retinal layers in mouse and human OCT images demonstrates the reliability and efficiency of the proposed user-guided segmentation method. PMID:25147962

In Situ 3D Segmentation of Individual Plant Leaves Using a RGB-D Camera for Agricultural Automation.

PubMed

Xia, Chunlei; Wang, Longtan; Chung, Bu-Keun; Lee, Jang-Myung

2015-08-19

In this paper, we present a challenging task of 3D segmentation of individual plant leaves from occlusions in the complicated natural scene. Depth data of plant leaves is introduced to improve the robustness of plant leaf segmentation. The low cost RGB-D camera is utilized to capture depth and color image in fields. Mean shift clustering is applied to segment plant leaves in depth image. Plant leaves are extracted from the natural background by examining vegetation of the candidate segments produced by mean shift. Subsequently, individual leaves are segmented from occlusions by active contour models. Automatic initialization of the active contour models is implemented by calculating the center of divergence from the gradient vector field of depth image. The proposed segmentation scheme is tested through experiments under greenhouse conditions. The overall segmentation rate is 87.97% while segmentation rates for single and occluded leaves are 92.10% and 86.67%, respectively. Approximately half of the experimental results show segmentation rates of individual leaves higher than 90%. Nevertheless, the proposed method is able to segment individual leaves from heavy occlusions.

User-guided segmentation for volumetric retinal optical coherence tomography images.

PubMed

Yin, Xin; Chao, Jennifer R; Wang, Ruikang K

2014-08-01

Despite the existence of automatic segmentation techniques, trained graders still rely on manual segmentation to provide retinal layers and features from clinical optical coherence tomography (OCT) images for accurate measurements. To bridge the gap between this time-consuming need of manual segmentation and currently available automatic segmentation techniques, this paper proposes a user-guided segmentation method to perform the segmentation of retinal layers and features in OCT images. With this method, by interactively navigating three-dimensional (3-D) OCT images, the user first manually defines user-defined (or sketched) lines at regions where the retinal layers appear very irregular for which the automatic segmentation method often fails to provide satisfactory results. The algorithm is then guided by these sketched lines to trace the entire 3-D retinal layer and anatomical features by the use of novel layer and edge detectors that are based on robust likelihood estimation. The layer and edge boundaries are finally obtained to achieve segmentation. Segmentation of retinal layers in mouse and human OCT images demonstrates the reliability and efficiency of the proposed user-guided segmentation method.

The segment polarity network is a robust developmental module

NASA Astrophysics Data System (ADS)

von Dassow, George; Meir, Eli; Munro, Edwin M.; Odell, Garrett M.

2000-07-01

All insects possess homologous segments, but segment specification differs radically among insect orders. In Drosophila, maternal morphogens control the patterned activation of gap genes, which encode transcriptional regulators that shape the patterned expression of pair-rule genes. This patterning cascade takes place before cellularization. Pair-rule gene products subsequently `imprint' segment polarity genes with reiterated patterns, thus defining the primordial segments. This mechanism must be greatly modified in insect groups in which many segments emerge only after cellularization. In beetles and parasitic wasps, for instance, pair-rule homologues are expressed in patterns consistent with roles during segmentation, but these patterns emerge within cellular fields. In contrast, although in locusts pair-rule homologues may not control segmentation, some segment polarity genes and their interactions are conserved. Perhaps segmentation is modular, with each module autonomously expressing a characteristic intrinsic behaviour in response to transient stimuli. If so, evolution could rearrange inputs to modules without changing their intrinsic behaviours. Here we suggest, using computer simulations, that the Drosophila segment polarity genes constitute such a module, and that this module is resistant to variations in the kinetic constants that govern its behaviour.

In Situ 3D Segmentation of Individual Plant Leaves Using a RGB-D Camera for Agricultural Automation

PubMed Central

Xia, Chunlei; Wang, Longtan; Chung, Bu-Keun; Lee, Jang-Myung

2015-01-01

In this paper, we present a challenging task of 3D segmentation of individual plant leaves from occlusions in the complicated natural scene. Depth data of plant leaves is introduced to improve the robustness of plant leaf segmentation. The low cost RGB-D camera is utilized to capture depth and color image in fields. Mean shift clustering is applied to segment plant leaves in depth image. Plant leaves are extracted from the natural background by examining vegetation of the candidate segments produced by mean shift. Subsequently, individual leaves are segmented from occlusions by active contour models. Automatic initialization of the active contour models is implemented by calculating the center of divergence from the gradient vector field of depth image. The proposed segmentation scheme is tested through experiments under greenhouse conditions. The overall segmentation rate is 87.97% while segmentation rates for single and occluded leaves are 92.10% and 86.67%, respectively. Approximately half of the experimental results show segmentation rates of individual leaves higher than 90%. Nevertheless, the proposed method is able to segment individual leaves from heavy occlusions. PMID:26295395

Impact damage detection in sandwich composite structures using Lamb waves and laser vibrometry

NASA Astrophysics Data System (ADS)

Lamboul, B.; Passilly, B.; Roche, J.-M.; Osmont, D.

2013-01-01

This experimental study explores the feasibility of impact damage detection in composite sandwich structures using Lamb wave excitation and signals acquired with a laser Doppler vibrometer. Energy maps are computed from the transient velocity wave fields and used to highlight defect areas in impacted coupons of foam core and honeycomb core sandwich materials. The technique performs well for the detection of barely visible damage in this type of material, and is shown to be robust in the presence of wave reverberation. Defect extent information is not always readily retrieved from the obtained defect signatures, which depend on the wave - defect interaction mechanisms.

A functional-based segmentation of human body scans in arbitrary postures.

PubMed

Werghi, Naoufel; Xiao, Yijun; Siebert, Jan Paul

2006-02-01

This paper presents a general framework that aims to address the task of segmenting three-dimensional (3-D) scan data representing the human form into subsets which correspond to functional human body parts. Such a task is challenging due to the articulated and deformable nature of the human body. A salient feature of this framework is that it is able to cope with various body postures and is in addition robust to noise, holes, irregular sampling and rigid transformations. Although whole human body scanners are now capable of routinely capturing the shape of the whole body in machine readable format, they have not yet realized their potential to provide automatic extraction of key body measurements. Automated production of anthropometric databases is a prerequisite to satisfying the needs of certain industrial sectors (e.g., the clothing industry). This implies that in order to extract specific measurements of interest, whole body 3-D scan data must be segmented by machine into subsets corresponding to functional human body parts. However, previously reported attempts at automating the segmentation process suffer from various limitations, such as being restricted to a standard specific posture and being vulnerable to scan data artifacts. Our human body segmentation algorithm advances the state of the art to overcome the above limitations and we present experimental results obtained using both real and synthetic data that confirm the validity, effectiveness, and robustness of our approach.

Computer aided segmentation of kidneys using locally shape constrained deformable models on CT images

NASA Astrophysics Data System (ADS)

Erdt, Marius; Sakas, Georgios

2010-03-01

This work presents a novel approach for model based segmentation of the kidney in images acquired by Computed Tomography (CT). The developed computer aided segmentation system is expected to support computer aided diagnosis and operation planning. We have developed a deformable model based approach based on local shape constraints that prevents the model from deforming into neighboring structures while allowing the global shape to adapt freely to the data. Those local constraints are derived from the anatomical structure of the kidney and the presence and appearance of neighboring organs. The adaptation process is guided by a rule-based deformation logic in order to improve the robustness of the segmentation in areas of diffuse organ boundaries. Our work flow consists of two steps: 1.) a user guided positioning and 2.) an automatic model adaptation using affine and free form deformation in order to robustly extract the kidney. In cases which show pronounced pathologies, the system also offers real time mesh editing tools for a quick refinement of the segmentation result. Evaluation results based on 30 clinical cases using CT data sets show an average dice correlation coefficient of 93% compared to the ground truth. The results are therefore in most cases comparable to manual delineation. Computation times of the automatic adaptation step are lower than 6 seconds which makes the proposed system suitable for an application in clinical practice.

Implications of segment mismatch for influenza A virus evolution

PubMed Central

White, Maria C.; Lowen, Anice C.

2018-01-01

Influenza A virus (IAV) is an RNA virus with a segmented genome. These viral properties allow for the rapid evolution of IAV under selective pressure, due to mutation occurring from error-prone replication and the exchange of gene segments within a co-infected cell, termed reassortment. Both mutation and reassortment give rise to genetic diversity, but constraints shape their impact on viral evolution: just as most mutations are deleterious, most reassortment events result in genetic incompatibilities. The phenomenon of segment mismatch encompasses both RNA- and protein-based incompatibilities between co-infecting viruses and results in the production of progeny viruses with fitness defects. Segment mismatch is an important determining factor of the outcomes of mixed IAV infections and has been addressed in multiple risk assessment studies undertaken to date. However, due to the complexity of genetic interactions among the eight viral gene segments, our understanding of segment mismatch and its underlying mechanisms remain incomplete. Here, we summarize current knowledge regarding segment mismatch and discuss the implications of this phenomenon for IAV reassortment and diversity. PMID:29244017

BDA: A novel method for identifying defects in body-centered cubic crystals.

PubMed

Möller, Johannes J; Bitzek, Erik

2016-01-01

The accurate and fast identification of crystallographic defects plays a key role for the analysis of atomistic simulation output data. For face-centered cubic (fcc) metals, most existing structure analysis tools allow for the direct distinction of common defects, such as stacking faults or certain low-index surfaces. For body-centered cubic (bcc) metals, on the other hand, a robust way to identify such defects is currently not easily available. We therefore introduce a new method for analyzing atomistic configurations of bcc metals, the BCC Defect Analysis (BDA). It uses existing structure analysis algorithms and combines their results to uniquely distinguish between typical defects in bcc metals. In essence, the BDA method offers the following features:•Identification of typical defect structures in bcc metals.•Reduction of erroneously identified defects by iterative comparison to the defects in the atom's neighborhood.•Availability as ready-to-use Python script for the widespread visualization tool OVITO [http://ovito.org].

High-Throughput Histopathological Image Analysis via Robust Cell Segmentation and Hashing

PubMed Central

Zhang, Xiaofan; Xing, Fuyong; Su, Hai; Yang, Lin; Zhang, Shaoting

2015-01-01

Computer-aided diagnosis of histopathological images usually requires to examine all cells for accurate diagnosis. Traditional computational methods may have efficiency issues when performing cell-level analysis. In this paper, we propose a robust and scalable solution to enable such analysis in a real-time fashion. Specifically, a robust segmentation method is developed to delineate cells accurately using Gaussian-based hierarchical voting and repulsive balloon model. A large-scale image retrieval approach is also designed to examine and classify each cell of a testing image by comparing it with a massive database, e.g., half-million cells extracted from the training dataset. We evaluate this proposed framework on a challenging and important clinical use case, i.e., differentiation of two types of lung cancers (the adenocarcinoma and squamous carcinoma), using thousands of lung microscopic tissue images extracted from hundreds of patients. Our method has achieved promising accuracy and running time by searching among half-million cells. PMID:26599156

Airborne digital-image data for monitoring the Colorado River corridor below Glen Canyon Dam, Arizona, 2009 - Image-mosaic production and comparison with 2002 and 2005 image mosaics

USGS Publications Warehouse

Davis, Philip A.

2012-01-01

Airborne digital-image data were collected for the Arizona part of the Colorado River ecosystem below Glen Canyon Dam in 2009. These four-band image data are similar in wavelength band (blue, green, red, and near infrared) and spatial resolution (20 centimeters) to image collections of the river corridor in 2002 and 2005. These periodic image collections are used by the Grand Canyon Monitoring and Research Center (GCMRC) of the U.S. Geological Survey to monitor the effects of Glen Canyon Dam operations on the downstream ecosystem. The 2009 collection used the latest model of the Leica ADS40 airborne digital sensor (the SH52), which uses a single optic for all four bands and collects and stores band radiance in 12-bits, unlike the image sensors that GCMRC used in 2002 and 2005. This study examined the performance of the SH52 sensor, on the basis of the collected image data, and determined that the SH52 sensor provided superior data relative to the previously employed sensors (that is, an early ADS40 model and Zeiss Imaging's Digital Mapping Camera) in terms of band-image registration, dynamic range, saturation, linearity to ground reflectance, and noise level. The 2009 image data were provided as orthorectified segments of each flightline to constrain the size of the image files; each river segment was covered by 5 to 6 overlapping, linear flightlines. Most flightline images for each river segment had some surface-smear defects and some river segments had cloud shadows, but these two conditions did not generally coincide in the majority of the overlapping flightlines for a particular river segment. Therefore, the final image mosaic for the 450-kilometer (km)-long river corridor required careful selection and editing of numerous flightline segments (a total of 513 segments, each 3.2 km long) to minimize surface defects and cloud shadows. The final image mosaic has a total of only 3 km of surface defects. The final image mosaic for the western end of the corridor has areas of cloud shadow because of persistent inclement weather during data collection. This report presents visual comparisons of the 2002, 2005, and 2009 digital-image mosaics for various physical, biological, and cultural resources within the Colorado River ecosystem. All of the comparisons show the superior quality of the 2009 image data. In fact, the 2009 four-band image mosaic is perhaps the best image dataset that exists for the entire Arizona part of the Colorado River.

Final project report for NEET pulsed ion beam project

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

Kucheyev, S. O.

The major goal of this project was to develop and demonstrate a novel experimental approach to access the dynamic regime of radiation damage formation in nuclear materials. In particular, the project exploited a pulsed-ion-beam method in order to gain insight into defect interaction dynamics by measuring effective defect interaction time constants and defect diffusion lengths. This project had the following four major objectives: (i) the demonstration of the pulsed ion beam method for a prototypical nuclear ceramic material, SiC; (ii) the evaluation of the robustness of the pulsed beam method from studies of defect generation rate effects; (iii) the measurementmore » of the temperature dependence of defect dynamics and thermally activated defect-interaction processes by pulsed ion beam techniques; and (iv) the demonstration of alternative characterization techniques to study defect dynamics. As we describe below, all these objectives have been met.« less

Bone regeneration with active angiogenesis by basic fibroblast growth factor gene transfected mesenchymal stem cells seeded on porous beta-TCP ceramic scaffolds.

PubMed

Guo, Xiaodong; Zheng, Qixin; Kulbatski, Iris; Yuan, Quan; Yang, Shuhua; Shao, Zengwu; Wang, Hong; Xiao, Baojun; Pan, Zhengqi; Tang, Shuo

2006-09-01

Large segmental bone defect repair remains a clinical and scientific challenge with increasing interest focused on combining gene transfer with tissue engineering techniques. Basic fibroblast growth factor (bFGF) is one of the most prominent osteogenic growth factors that has the potential to accelerate bone healing by promoting the proliferation and differentiation of mesenchymal stem cells (MSCs) and the regeneration of capillary vasculature. However, the short biological half-lives of growth factors may impose severe restraints on their clinical usefulness. Gene-based delivery systems provide a better way of achieving a sustained high concentration of growth factors locally in the defect and delivering a more biologically active product than that achieved by exogenous application of recombinant proteins. The objective of this experimental study was to investigate whether the bFGF gene modified MSCs could enhance the repair of large segmental bone defects. The pcDNA3-bFGF gene transfected MSCs were seeded on biodegradable porous beta tricalcium phosphate (beta-TCP) ceramics and allografted into the 15 mm critical-sized segmental bone defects in the radius of 18 New Zealand White rabbits. The pcDNA3 vector gene transfected MSCs were taken as the control. The follow-up times were 2, 4, 6, 8, 10 and 12 weeks. Scanning electron microscopic, roentgenographic, histologic and immunohistological studies were used to assess angiogenesis and bone regeneration. In vitro, the proliferation and differentiation of bFGF gene transfected MSCs were more active than that of the control groups. In vivo, significantly more new bone formation accompanied by abundant active capillary regeneration was observed in pores of the ceramics loaded with bFGF gene transfected MSCs, compared with control groups. Transfer of gene encoding bFGF to MSCs increases their osteogenic properties by enhancing capillary regeneration, thus providing a rich blood supply for new bone formation. This new bFGF gene enhanced tissue engineering strategy could be of potential benefit to accelerate bone healing, especially in defects caused by atrophic nonunion and avascular necrosis of the femoral head.

Reconstruction of large diaphyseal bone defect by simplified bone transport over nail technique: A 7-case series.

PubMed

Ferchaud, F; Rony, L; Ducellier, F; Cronier, P; Steiger, V; Hubert, L

2017-11-01

Reconstruction of large diaphyseal bone defect is complex and the complications rate is high. This study aimed to assess a simplified technique of segmental bone transport by monorail external fixator over an intramedullary nail.A prospective study included 7 patients: 2 femoral and 5 tibial defects. Mean age was 31years (range: 16-61years). Mean follow-up was 62 months (range: 46-84months). Defects were post-traumatic, with a mean length of 7.2cm (range: 4 to 9.5cm). For 3 patients, reconstruction followed primary failure. In 4 cases, a covering flap was necessary. Transport used an external fixator guided by an intramedullary nail, at a rate of 1mm per day. One pin was implanted on either side of the distraction zone. The external fixator was removed 1 month after bone contact at the docking site. Mean bone transport time was 11 weeks (range: 7-15 weeks). Mean external fixation time was 5.1months (range: 3.5 to 8months). Full weight-bearing was allowed 5.7months (range: 3.5-13months) after initiation of transport. In one patient, a pin had to be repositioned. In 3 patients, the transported segment re-ascended after external fixatorablation, requiring repeat external fixation and resumption of transport. There was just 1 case of superficial pin infection. Reconstruction quality was considered "excellent" on the Paley-Marr criteria in 6 cases. The present technique provided excellent reconstruction quality in 6 of the 7 cases. External fixation time was shorter and resumption of weight-bearing earlier than with other reconstruction techniques, notably including bone autograft, vascularized bone graft or the induced membrane technique. Nailing facilitated control of limb axis and length. The complications rate was 50%, comparable to other techniques. This study raises the question of systematic internal fixation of the docking site, to avoid any mobilization of the transported segment. The bone quality, axial control and rapidity shown by the present technique make it well-adapted to reconstruction of diaphyseal bone defect. Four-case series. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Variable styles of rifting expressed in crustal structure across three rift segments of the Gulf of California

NASA Astrophysics Data System (ADS)

Lizarralde, D. D.; Axen, G. J.; Brown, H. E.; Fletcher, J. M.; Fernandez, A. G.; Harding, A. J.; Holbrook, W. S.; Kent, G. M.; Paramo, P.; Sutherland, F. H.; Umhoefer, P. J.

2007-05-01

We present a summary of results from a crustal-scale seismic experiment conducted in the southern Gulf of California. This experiment, the PESCADOR experiment, imaged crustal structure across three rift segments, the Alarcon, Guaymas, and San José del Cabo to Puerto Vallarta (Cabo-PV) segments, using seismic refraction/wide-angle reflection data acquired with airgun sources and recorded by closely spaced (10-15 km) ocean-bottom seismometers (OBSs). The imaged crustal structure reveals a surprisingly large variation in rifting style and magmatism between these segments: the Alarcon segment is a wide rift with apparently little syn-rift magmatism; the Guaymas segment is a narrow, magmatically robust rift; and the Cabo-PV segment is a narrow, magmatically "normal" rift. Our explanation for the observed variability is non-traditional in that we do not invoke mantle temperature, the factor commonly invoked to explain end-member volcanic and non-volcanic rifted margins, as the source of the considerable, though non-end-member variability we observe. Instead, we invoke mantle depletion related to pre-rift arc volcanism to account for observed wide, magma-poor rifting and mantle fertility and possibly the influence of sediments to account for robust rift and post-rift magmatism. These factors may commonly vary over small lateral spatial scales in regions that have transitioned from convergent to extensional tectonics, as is the case for the Gulf of California and many other rifts. Our hypothesis suggests that substantial lateral variability may exist within the uppermost mantle beneath the Gulf of California today, and it is hoped that ongoing efforts to image upper mantle structure here will provide tests for this hypothesis.

Segmentation of epidermal tissue with histopathological damage in images of haematoxylin and eosin stained human skin

PubMed Central

2014-01-01

Background Digital image analysis has the potential to address issues surrounding traditional histological techniques including a lack of objectivity and high variability, through the application of quantitative analysis. A key initial step in image analysis is the identification of regions of interest. A widely applied methodology is that of segmentation. This paper proposes the application of image analysis techniques to segment skin tissue with varying degrees of histopathological damage. The segmentation of human tissue is challenging as a consequence of the complexity of the tissue structures and inconsistencies in tissue preparation, hence there is a need for a new robust method with the capability to handle the additional challenges materialising from histopathological damage. Methods A new algorithm has been developed which combines enhanced colour information, created following a transformation to the L*a*b* colourspace, with general image intensity information. A colour normalisation step is included to enhance the algorithm’s robustness to variations in the lighting and staining of the input images. The resulting optimised image is subjected to thresholding and the segmentation is fine-tuned using a combination of morphological processing and object classification rules. The segmentation algorithm was tested on 40 digital images of haematoxylin & eosin (H&E) stained skin biopsies. Accuracy, sensitivity and specificity of the algorithmic procedure were assessed through the comparison of the proposed methodology against manual methods. Results Experimental results show the proposed fully automated methodology segments the epidermis with a mean specificity of 97.7%, a mean sensitivity of 89.4% and a mean accuracy of 96.5%. When a simple user interaction step is included, the specificity increases to 98.0%, the sensitivity to 91.0% and the accuracy to 96.8%. The algorithm segments effectively for different severities of tissue damage. Conclusions Epidermal segmentation is a crucial first step in a range of applications including melanoma detection and the assessment of histopathological damage in skin. The proposed methodology is able to segment the epidermis with different levels of histological damage. The basic method framework could be applied to segmentation of other epithelial tissues. PMID:24521154

Ready-to-Use Tissue Construct for Military Bone and Cartilage Trauma

DTIC Science & Technology

2012-10-01

times. We hypothesize that our Ready-to-Use constructs can successfully restore 3 cm critical size segmental defects in dog tibiae. We will examine the...defects) of the grant. The approved IACUC protocol permits 3 pilot dogs for Aim 1 and 3 pilot dogs for Aim 2. Several minor modifications to the...original IACUC protocol were required which are provided in the Appendix. All the pilot dogs were to receive scaffolds composed of 90% poly-caprolactone

Pathology of Podocytopathies Causing Nephrotic Syndrome in Children.

PubMed

Ranganathan, Sarangarajan

2016-01-01

Nephrotic syndrome (NS) in children includes a diverse group of diseases that range from genetic diseases without any immunological defects to causes that are primarily due to immunological effects. Recent advances in molecular and genomic studies have resulted in a plethora of genetic defects that have been localized to the podocyte, the basic structure that is instrumental in normal filtration process. Although the disease can manifest from birth and into adulthood, the primary focus of this review would be to describe the novel genes and pathology of primary podocyte defects that cause NS in children. This review will restrict itself to the pathology of congenital NS, minimal change disease (MCD), and its variants and focal segmental glomerulosclerosis (FSGS). The two major types of congenital NS are Finnish type characterized by dilated sausage shaped tubules morphologically and diffuse mesangial sclerosis characterized by glomerulosclerosis. MCD has usually normal appearing biopsy features on light microscopy and needs electron microscopy for diagnosis, whereas FSGS in contrast has classic segmental sclerosing lesions identified in different portions of the glomeruli and tubular atrophy. This review summarizes the pathological characteristics of these conditions and also delves into the various genetic defects that have been described as the cause of these primary podocytopathies. Other secondary causes of NS in children, such as membranoproliferative and membranous glomerulonephritis, will not be covered in this review.

Review methods for image segmentation from computed tomography images

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

Mamat, Nurwahidah; Rahman, Wan Eny Zarina Wan Abdul; Soh, Shaharuddin Cik

Image segmentation is a challenging process in order to get the accuracy of segmentation, automation and robustness especially in medical images. There exist many segmentation methods that can be implemented to medical images but not all methods are suitable. For the medical purposes, the aims of image segmentation are to study the anatomical structure, identify the region of interest, measure tissue volume to measure growth of tumor and help in treatment planning prior to radiation therapy. In this paper, we present a review method for segmentation purposes using Computed Tomography (CT) images. CT images has their own characteristics that affectmore » the ability to visualize anatomic structures and pathologic features such as blurring of the image and visual noise. The details about the methods, the goodness and the problem incurred in the methods will be defined and explained. It is necessary to know the suitable segmentation method in order to get accurate segmentation. This paper can be a guide to researcher to choose the suitable segmentation method especially in segmenting the images from CT scan.« less

Using multimodal information for the segmentation of fluorescent micrographs with application to virology and microbiology.

PubMed

Held, Christian; Wenzel, Jens; Webel, Rike; Marschall, Manfred; Lang, Roland; Palmisano, Ralf; Wittenberg, Thomas

2011-01-01

In order to improve reproducibility and objectivity of fluorescence microscopy based experiments and to enable the evaluation of large datasets, flexible segmentation methods are required which are able to adapt to different stainings and cell types. This adaption is usually achieved by the manual adjustment of the segmentation methods parameters, which is time consuming and challenging for biologists with no knowledge on image processing. To avoid this, parameters of the presented methods automatically adapt to user generated ground truth to determine the best method and the optimal parameter setup. These settings can then be used for segmentation of the remaining images. As robust segmentation methods form the core of such a system, the currently used watershed transform based segmentation routine is replaced by a fast marching level set based segmentation routine which incorporates knowledge on the cell nuclei. Our evaluations reveal that incorporation of multimodal information improves segmentation quality for the presented fluorescent datasets.

Robust Multiple-Range Coherent Quantum State Transfer.

PubMed

Chen, Bing; Peng, Yan-Dong; Li, Yong; Qian, Xiao-Feng

2016-07-01

We propose a multiple-range quantum communication channel to realize coherent two-way quantum state transport with high fidelity. In our scheme, an information carrier (a qubit) and its remote partner are both adiabatically coupled to the same data bus, i.e., an N-site tight-binding chain that has a single defect at the center. At the weak interaction regime, our system is effectively equivalent to a three level system of which a coherent superposition of the two carrier states constitutes a dark state. The adiabatic coupling allows a well controllable information exchange timing via the dark state between the two carriers. Numerical results show that our scheme is robust and efficient under practically inevitable perturbative defects of the data bus as well as environmental dephasing noise.

Axenfeld-Rieger syndrome.

PubMed

Seifi, M; Walter, M A

2018-06-01

Axenfeld-Rieger syndrome (ARS) is a clinically and genetically heterogeneous group of developmental disorders affecting primarily the anterior segment of the eye, often leading to secondary glaucoma. Patients with ARS may also present with systemic changes, including dental defects, mild craniofacial dysmorphism, and umbilical anomalies. ARS is inherited in an autosomal-dominant fashion; the underlying defect in 40% of patients is mutations in PITX2 or FOXC1. Here, an overview of the clinical spectrum of ARS is provided. As well, the known underlying genetic defects, clinical diagnostic possibilities, genetic counseling and treatments of ARS are discussed in detail. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

[Gemstone computed tomography in the evaluation of material distribution in pulmonary parenchyma for pulmonary embolism].

PubMed

Zhang, Lan; Lü, Lei; Wu, Hua-wei; Zhang, Hao; Zhang, Ji-wei

2011-12-06

To present our initial experiences with pulmonary high-definition multidetector computed tomography (HDCT) in patients with acute venous thromboembolism (AVTE) to evaluate their corresponding clinical manifestations. Since December 2009 to March 2010, 23 AVTE patients underwent HDCT at our hospital. Pulmonary embolism (PE) was diagnosed based on the 3D-reconstructed images of computed tomography pulmonary angiography (CTPA). The post processed data were collected by spectral imaging system software to detect the iodine distribution maps. Perfusion defects, calculated as the values of iodine content, were compared with those of normal lung parenchymal perfusion in the absence of PE. Among them, 14 AVTE patients were definitely diagnosed with PE. Prior to anticoagulant therapy, their values of iodine content in defective perfusion area were significantly lower than those in normal perfusion area. After a 3-month anticoagulant therapy, the values of iodine content for the defective perfusion area increased significantly (P < 0.05). There was no significant correlation between the values of iodine content for segmental/subsegmental filling defect area and clinical risk score of DVT (r = 2.68, P > 0.05). But there was a significant negative correlation between the values of iodine content for segmental/subsegmental filling defection area and clinical probability score of PE (r = 0.78, P < 0.05). HDCT is a promising modality of visualizing pulmonary microvasculature as a correlative manifestation of regional perfusion. PE results in hypoperfusion with decreased values of iodine content in affected lung parenchyma. Hemodynamic changes in affected areas correlate with the severity of clinical manifestations of PE.

Vitreoretinal Interface Characteristics in Eyes with Idiopathic Macular Holes: Qualitative and Quantitative Analysis.

PubMed

Seyhan Karatepe, Arzu; Menteş, Jale; Erakgün, E Tansu; Afrashi, Filiz; Nalçacı, Serhad; Akkın, Cezmi; Ateş, Yeşim

2018-04-01

To determine the qualitative and quantitative vitreoretinal interface characteristics with spectral domain optical coherence tomography (SD-OCT) in eyes with macular hole (MH) and investigate their relation with best corrected visual acuity (BCVA) and MH duration. Sixty-one eyes of 46 consecutive patients diagnosed with idiopathic MH were included in the study. The mean age of the patients was 66.7±7.5 (51-79) years. Complete ophthalmologic examination and SD-OCT examination were performed in all eyes and MH stages were determined according to SD-OCT findings. Qualitative characteristics of the vitreoretinal interface were investigated, including vitreomacular traction, vitreopapillary traction, maculopapillary traction, vitreoschisis, intraretinal cyst, presence of epiretinal membrane, and the integrity of the photoreceptor inner segment-outer segment junction (IS/OS) and external limiting membrane (ELM). In addition, MH diameter, MH base diameter (MHBD), ELM defect diameter, IS/OS defect diameter, and MH height were quantitatively measured and the MH index was calculated. Out of 61 eyes, 9.8% were classified as stage 1a, 19.7% as stage 1b, 18% as stage 2, 23% as stage 3, and 29.5% as stage 4. Mean BCVA was 0.28±0.24 (1 mps-1.0) Snellen and MH duration was 10.08±18.6 (1-108) months. The most common interface characteristics associated with MH were determined as intraretinal cyst (91.8%), IS/OS defect (78.7%) and ELM defect (63.9%). Duration and stage of MH were inversely proportional to BCVA but directly proportional to the presence and diameter of IS/OS and ELM defects. BCVA was significantly lower in eyes with IS/OS and ELM defects (p<0.0001; p<0.0001 Mann-Whitney U test). We determined that the most important factors affecting BCVA in cases with idiopathic MH were MH stage, MH duration, MHBD, and the presence and diameter of IS/OS and ELM defects, which suggests that these parameters should be considered while making decisions about prognosis and treatment.

Robust and automated three-dimensional segmentation of densely packed cell nuclei in different biological specimens with Lines-of-Sight decomposition.

PubMed

Mathew, B; Schmitz, A; Muñoz-Descalzo, S; Ansari, N; Pampaloni, F; Stelzer, E H K; Fischer, S C

2015-06-08

Due to the large amount of data produced by advanced microscopy, automated image analysis is crucial in modern biology. Most applications require reliable cell nuclei segmentation. However, in many biological specimens cell nuclei are densely packed and appear to touch one another in the images. Therefore, a major difficulty of three-dimensional cell nuclei segmentation is the decomposition of cell nuclei that apparently touch each other. Current methods are highly adapted to a certain biological specimen or a specific microscope. They do not ensure similarly accurate segmentation performance, i.e. their robustness for different datasets is not guaranteed. Hence, these methods require elaborate adjustments to each dataset. We present an advanced three-dimensional cell nuclei segmentation algorithm that is accurate and robust. Our approach combines local adaptive pre-processing with decomposition based on Lines-of-Sight (LoS) to separate apparently touching cell nuclei into approximately convex parts. We demonstrate the superior performance of our algorithm using data from different specimens recorded with different microscopes. The three-dimensional images were recorded with confocal and light sheet-based fluorescence microscopes. The specimens are an early mouse embryo and two different cellular spheroids. We compared the segmentation accuracy of our algorithm with ground truth data for the test images and results from state-of-the-art methods. The analysis shows that our method is accurate throughout all test datasets (mean F-measure: 91%) whereas the other methods each failed for at least one dataset (F-measure≤69%). Furthermore, nuclei volume measurements are improved for LoS decomposition. The state-of-the-art methods required laborious adjustments of parameter values to achieve these results. Our LoS algorithm did not require parameter value adjustments. The accurate performance was achieved with one fixed set of parameter values. We developed a novel and fully automated three-dimensional cell nuclei segmentation method incorporating LoS decomposition. LoS are easily accessible features that ensure correct splitting of apparently touching cell nuclei independent of their shape, size or intensity. Our method showed superior performance compared to state-of-the-art methods, performing accurately for a variety of test images. Hence, our LoS approach can be readily applied to quantitative evaluation in drug testing, developmental and cell biology.

[Medical image segmentation based on the minimum variation snake model].

PubMed

Zhou, Changxiong; Yu, Shenglin

2007-02-01

It is difficult for traditional parametric active contour (Snake) model to deal with automatic segmentation of weak edge medical image. After analyzing snake and geometric active contour model, a minimum variation snake model was proposed and successfully applied to weak edge medical image segmentation. This proposed model replaces constant force in the balloon snake model by variable force incorporating foreground and background two regions information. It drives curve to evolve with the criterion of the minimum variation of foreground and background two regions. Experiments and results have proved that the proposed model is robust to initial contours placements and can segment weak edge medical image automatically. Besides, the testing for segmentation on the noise medical image filtered by curvature flow filter, which preserves edge features, shows a significant effect.

Anterior segment dysgenesis (Peters' anomaly) in two snow leopard (Panthera uncia) cubs.

PubMed

Hamoudi, Hassan; Rudnick, Jens-Christian; Prause, Jan U; Tauscher, Kerstin; Breithaupt, Angele; Teifke, Jens P; Heegaard, Steffen

2013-07-01

Two sibling snow leopards, a male and a female, with bilateral anterior segment dysgenesis (ASD), are reported. Both snow leopards also had colobomas of both upper eyelids. All eyes exhibited a central corneal opacity associated with a defect in posterior corneal stroma, endothelium and Descemet's membrane. Iris strands were present attached to the termination of Descemet's membrane and to the periphery of the posterior corneal defect. The iris was hypoplastic, and cataract was present in all four eyes. The left eye of the female was microphthalmic, with no trabecular meshwork and with persistent remnant of the hyaloid artery. The male had hydrocephalus and thus some of the features of Peters' plus syndrome (Peters' anomaly in addition to systemic malformations). The histological findings in the eyes of these snow leopard siblings are identical with those described in humans with Peters' anomaly. © 2012 American College of Veterinary Ophthalmologists.

Real-time image sequence segmentation using curve evolution

NASA Astrophysics Data System (ADS)

Zhang, Jun; Liu, Weisong

2001-04-01

In this paper, we describe a novel approach to image sequence segmentation and its real-time implementation. This approach uses the 3D structure tensor to produce a more robust frame difference signal and uses curve evolution to extract whole objects. Our algorithm is implemented on a standard PC running the Windows operating system with video capture from a USB camera that is a standard Windows video capture device. Using the Windows standard video I/O functionalities, our segmentation software is highly portable and easy to maintain and upgrade. In its current implementation on a Pentium 400, the system can perform segmentation at 5 frames/sec with a frame resolution of 160 by 120.

Image Mosaic Method Based on SIFT Features of Line Segment

PubMed Central

Zhu, Jun; Ren, Mingwu

2014-01-01

This paper proposes a novel image mosaic method based on SIFT (Scale Invariant Feature Transform) feature of line segment, aiming to resolve incident scaling, rotation, changes in lighting condition, and so on between two images in the panoramic image mosaic process. This method firstly uses Harris corner detection operator to detect key points. Secondly, it constructs directed line segments, describes them with SIFT feature, and matches those directed segments to acquire rough point matching. Finally, Ransac method is used to eliminate wrong pairs in order to accomplish image mosaic. The results from experiment based on four pairs of images show that our method has strong robustness for resolution, lighting, rotation, and scaling. PMID:24511326

Multi-scale hippocampal parcellation improves atlas-based segmentation accuracy

NASA Astrophysics Data System (ADS)

Plassard, Andrew J.; McHugo, Maureen; Heckers, Stephan; Landman, Bennett A.

2017-02-01

Known for its distinct role in memory, the hippocampus is one of the most studied regions of the brain. Recent advances in magnetic resonance imaging have allowed for high-contrast, reproducible imaging of the hippocampus. Typically, a trained rater takes 45 minutes to manually trace the hippocampus and delineate the anterior from the posterior segment at millimeter resolution. As a result, there has been a significant desire for automated and robust segmentation of the hippocampus. In this work we use a population of 195 atlases based on T1-weighted MR images with the left and right hippocampus delineated into the head and body. We initialize the multi-atlas segmentation to a region directly around each lateralized hippocampus to both speed up and improve the accuracy of registration. This initialization allows for incorporation of nearly 200 atlases, an accomplishment which would typically involve hundreds of hours of computation per target image. The proposed segmentation results in a Dice similiarity coefficient over 0.9 for the full hippocampus. This result outperforms a multi-atlas segmentation using the BrainCOLOR atlases (Dice 0.85) and FreeSurfer (Dice 0.75). Furthermore, the head and body delineation resulted in a Dice coefficient over 0.87 for both structures. The head and body volume measurements also show high reproducibility on the Kirby 21 reproducibility population (R2 greater than 0.95, p < 0.05 for all structures). This work signifies the first result in an ongoing work to develop a robust tool for measurement of the hippocampus and other temporal lobe structures.

Computer aided weld defect delineation using statistical parametric active contours in radiographic inspection.

PubMed

Goumeidane, Aicha Baya; Nacereddine, Nafaa; Khamadja, Mohammed

2015-01-01

A perfect knowledge of a defect shape is determinant for the analysis step in automatic radiographic inspection. Image segmentation is carried out on radiographic images and extract defects indications. This paper deals with weld defect delineation in radiographic images. The proposed method is based on a new statistics-based explicit active contour. An association of local and global modeling of the image pixels intensities is used to push the model to the desired boundaries. Furthermore, other strategies are proposed to accelerate its evolution and make the convergence speed depending only on the defect size as selecting a band around the active contour curve. The experimental results are very promising, since experiments on synthetic and radiographic images show the ability of the proposed model to extract a piece-wise homogenous object from very inhomogeneous background, even in a bad quality image.

Biomechanical evaluation of a novel suturing scheme for grafting load-bearing collagen scaffolds for rotator cuff repair

PubMed Central

Islam, Anowarul; Bohl, Michael S.; Tsai, Andrew G; Younesi, Mousa; Gillespie, Robert; Akkus, Ozan

2015-01-01

Background Currently, there are no well-established suture protocols to attach fully load-bearing scaffolds which span tendon defects between bone and muscle for repair of critical sized tendon tears. Methods to attach load-bearing tissue repair scaffolds could enable functional repair of tendon injuries. Methods Sixteen rabbit shoulders were dissected (New Zealand white rabbits, 1 yr. old, female) to isolate the humeral-infraspinatus muscle complex. A unique suture technique was developed to allow for a 5 mm segmental defect in infraspinatus tendon to be replaced with a mechanically strong bioscaffold woven from pure collagen threads. The suturing pattern resulted in a fully load-bearing scaffold. The tensile stiffness and strength of scaffold repair was compared with intact infraspinatus and regular direct repair. Findings The failure load and displacement at failure of the scaffold repair group were 59.9 N (Standard Deviation, SD = 10.7) and 10.3 mm (SD = 2.9), respectively and matched those obtained by direct repair group which were 57.5 N (SD = 15.3) and 8.6 mm (SD = 1.5), (p > 0.05). Failure load, displacement at failure and stiffness of both of the repair groups were half of the intact infraspinatus shoulder group. Interpretation With the developed suture technique, scaffolds repair showed similar failure load, displacement at failure and stiffness to the direct repair. This novel suturing pattern and the mechanical robustness of the scaffold at time zero indicates that the proposed model is mechanically viable for future in vivo studies which has a higher potential to translate into clinical uses. PMID:26009492

CLASSIFICATION AND QUANTITATIVE ANALYSIS OF GEOGRAPHIC ATROPHY JUNCTIONAL ZONE USING SPECTRAL DOMAIN OPTICAL COHERENCE TOMOGRAPHY.

PubMed

Qu, Jinfeng; Velaga, Swetha Bindu; Hariri, Amir H; Nittala, Muneeswar Gupta; Sadda, Srinivas

2017-08-22

The junctional zone at the border of areas of geographic atrophy (GA) in eyes with nonneovascular age-related macular degeneration is an important target region for future therapeutic strategies. The goal of this study was to perform a detailed classification and quantitative characterization of the junctional zone using spectral domain optical coherence tomography. Spectral domain optical coherence tomography volume cube scans (Spectralis OCT, 1024 × 37, Automatic Real Time > 9) were obtained from 15 eyes of 11 patients with GA because of nonneovascular age-related macular degeneration. Volume optical coherence tomography data were imported into previously described validated grading software (3D-OCTOR), and manual segmentation of the retinal pigment epithelium (RPE) and photoreceptor layers was performed on all B-scans (total of 555). Retinal pigment epithelium and photoreceptor defect maps were produced for each case. The borders of the photoreceptor defect area and RPE defect area were delineated individually on separate annotation layers. The two outlines were then superimposed to compare the areas of overlap and nonoverlap. The perimeter of the RPE defect area was calculated by the software in pixels. The superimposed outline of the photoreceptor defect area and the RPE defect area was scrutinized to classify the overlap configuration of the junctional zone into one of three categories: Type 0, exact correspondence between the edge of the RPE defect and photoreceptor defect; Type 1, loss of photoreceptors outside and beyond the edge of the RPE defect; Type 2, preservation of photoreceptors beyond the edge of the RPE defect. The relative proportion of the various border configurations was expressed as a percentage of the perimeter of the RPE defect. Each configuration was then classified into four subgroups according to irregularity of the RPE band and the presence of debris. Fifteen eyes of 11 patients (mean age: 79.3 ± 4.3 years; range: 79-94 years) were included in this study. Seventeen GA lesions were analyzed. Two hundred and thirty-two B-scans were found to pass through the GA lesions, yielding 612 individual GA borders which were separately analyzed and classified. The mean area of the RPE defect was 4.0 ± 4.4 mm, which was significantly smaller than that of the photoreceptor defect which measured 4.4 ± 4.1 mm (paired t test, P = 0.037). On average, 18.0 ± 9.6% (range, 2.3-36.6%) of the junctional zone was of the Type 0 configuration, 57.3 ± 19.0% (range, 21.3-96.8%) was Type 1, and 24.7 ± 18.0% (range, 0.9-64.4%) was Type 2. Type 1 was more prevalent than Type 0 and 2 (analysis of variance, P = 0.000). Debris was present at the margin of the defect in 24.3% (149 of 612) of all assessed junctional zones; 20.0% (14 of 70) of Type 0 junctions, 28.7% (120 of 418) of Type 1, and 12.1% (15 of 124) of Type 2. Debris was more common in Type 1 than Type 2 junctions (P < 0.001). Retinal pigment epithelial irregularity was present at the margin of the defect in 34.8% (213 of 612) of all assessed junctional zones; 52.9% (37 of 70) of Type 0 junctions, 38.0% (159 of 418) of Type 1, and 13.7% (17 of 124) of Type 2. Retinal pigment epithelial irregularity was present more often at Type 0 and Type 1 than at Type 2 junctions (P < 0.001 for both). The size of the optical coherence tomography-visible RPE and photoreceptor defect in GA lesions differ significantly. There were significant areas where the photoreceptor outer segments were preserved despite the absence of visible RPE cells, and also areas of photoreceptor outer segment loss despite apparent RPE preservation. These findings have implications for development of therapeutic strategies, particularly cell-replacement approaches.

A case of junctional neural tube defect associated with a lipoma of the filum terminale: a new subtype of junctional neural tube defect?

PubMed

Florea, Simona Mihaela; Faure, Alice; Brunel, Hervé; Girard, Nadine; Scavarda, Didier

2018-06-01

The embryological development of the central nervous system takes place during the neurulation process, which includes primary and secondary neurulation. A new form of dysraphism, named junctional neural tube defect (JNTD), was recently reported, with only 4 cases described in the literature. The authors report a fifth case of JNTD. This 5-year-old boy, who had been operated on during his 1st month of life for a uretero-rectal fistula, was referred for evaluation of possible spinal dysraphism. He had urinary incontinence, clubfeet, and a history of delayed walking ability. MRI showed a spinal cord divided in two, with an upper segment ending at the T-11 level and a lower segment at the L5-S1 level, with a thickened filum terminale. The JNTDs represent a recently classified dysraphism caused by an error during junctional neurulation. The authors suggest that their patient should be included in this category as the fifth case reported in the literature and note that this would be the first reported case of JNTD in association with a lipomatous filum terminale.

Chromophores in phenylenevinylene-based conjugated polymers: role of conformational kinks and chemical defects.

PubMed

Hennebicq, Emmanuelle; Deleener, Caroline; Brédas, Jean-Luc; Scholes, Gregory D; Beljonne, David

2006-08-07

The influence of chemical defects and conformational kinks on the nature of the lowest electronic excitations in phenylenevinylene-based polymers is assessed at the semiempirical quantum-chemical level. The amount of excited-state localization and the amplitude of through-space (Coulomb-like) versus through-bond (charge-transfer-like) interactions have been quantified by comparing the results provided by excitonic and supermolecular models. While excitation delocalization among conjugated segments delineated by the defects occurs in the acceptor configuration, self-confinement on individual chromophores follows from geometric relaxation in the excited-state donor configuration. The extent of excited-state localization is found to be sensitive to both the nature of the defect and the length of the conjugated chains. Implications for resonant energy transfer along conjugated polymer chains are discussed.

Reconstruction of Canine Mandibular Bone Defects Using a Bone Transport Reconstruction Plate

PubMed Central

Elsalanty, Mohammed E.; Zakhary, Ibrahim; Akeel, Sara; Benson, Byron; Mulone, Timothy; Triplett, Gilbert R.; Opperman, Lynne A.

2010-01-01

Objectives Reconstruction of mandibular segmental bone defects is a challenging task. This study tests a new device used for reconstructing mandibular defects based on the principle of bone transport distraction osteogenesis. Methods Thirteen beagle dogs were divided into control and experimental groups. In all animals, a 3 cm defect was created on one side of the mandible. In eight control animals, the defect was stabilized with a reconstruction plate without further reconstruction and the animals were sacrificed two to three months after surgery. The remaining five animals were reconstructed with a bone transport reconstruction plate (BTRP), comprising a reconstruction plate with attached intraoral transport unit, and were sacrificed after one month of consolidation. Results Clinical evaluation, cone-beam CT densitometry, three-dimensional histomorphometry, and docking site histology revealed significant new bone formation within the defect in the distracted group. Conclusion The physical dimensions and architectural parameters of the new bone were comparable to the contralateral normal bone. Bone union at the docking site remains a problem. PMID:19770704

Genetic Evidence for an Interferon-Antagonistic Function of Rift Valley Fever Virus Nonstructural Protein NSs

PubMed Central

Bouloy, Michèle; Janzen, Christian; Vialat, Pierre; Khun, Huot; Pavlovic, Jovan; Huerre, Michel; Haller, Otto

2001-01-01

Rift Valley fever virus (RVFV), a phlebovirus of the family Bunyaviridae, is a major public health threat in Egypt and sub-Saharan Africa. The viral and host cellular factors that contribute to RVFV virulence and pathogenicity are still poorly understood. All pathogenic RVFV strains direct the synthesis of a nonstructural phosphoprotein (NSs) that is encoded by the smallest (S) segment of the tripartite genome and has an undefined accessory function. In this report, we show that MP12 and clone 13, two attenuated RVFV strains with mutations in the NSs gene, were highly virulent in IFNAR−/− mice lacking the alpha/beta interferon (IFN-α/β) receptor but remained attenuated in IFN-γ receptor-deficient mice. Both attenuated strains proved to be excellent inducers of early IFN-α/β production. In contrast, the virulent strain ZH548 failed to induce detectable amounts of IFN-α/β and replicated extensively in both IFN-competent and IFN-deficient mice. Clone 13 has a defective NSs gene with a large in-frame deletion. This defect in the NSs gene results in expression of a truncated protein which is rapidly degraded. To investigate whether the presence of the wild-type NSs gene correlated with inhibition of IFN-α/β production, we infected susceptible IFNAR−/− mice with S gene reassortant viruses. When the S segment of ZH548 was replaced by that of clone 13, the resulting reassortants became strong IFN inducers. When the defective S segment of clone 13 was exchanged with the wild-type S segment of ZH548, the reassortant virus lost the capacity to stimulate IFN-α/β production. These results demonstrate that the ability of RVFV to inhibit IFN-α/β production correlates with viral virulence and suggest that the accessory protein NSs is an IFN antagonist. PMID:11152510

Early detection of radiation-induced heart disease using (99m)Tc-MIBI SPECT gated myocardial perfusion imaging in patients with oesophageal cancer during radiotherapy.

PubMed

Zhang, Peng; Hu, Xudong; Yue, Jinbo; Meng, Xue; Han, Dali; Sun, Xindong; Yang, Guoren; Wang, Shijiang; Wang, Xiaohui; Yu, Jinming

2015-05-01

The primary aim of this prospective study was to investigate the value of (99m)Tc-methoxyisobutylisonitrile (MIBI) single photon emission computed tomography (SPECT) gated myocardial perfusion imaging (GMPI) in the detection of radiation-induced heart disease (RIHD) as early as during radiotherapy (RT) for oesophageal cancer (EC). The second aim was to analyse the correlation between cardiac toxicity and the dose-volume factors. The (99m)Tc-MIBI SPECT GMPI was performed both pre-RT and during RT (40Gray). The results of the SPECT were quantitatively analysed with QGS/QPS software and read by two experienced nuclear medicine physicians. The correlation between the changes in the SPECT parameters and the RT dosimetric data was analysed. Eighteen patients with locally advanced EC were enrolled in the study. Compared with the baseline, the imaging during RT showed not only significant decreases in the wall motion (WM) (1/20 segments), wall thickening (WT) (2/20 segments), end-diastolic perfusion (EDP) (5/20 segments) and end-systolic perfusion (ESP) (8/20 segments) (p<0.05) but also a significant increase in the heart rate (74.63±7.79 vs 81.49±9.90, p=0.036). New myocardial perfusion defects were observed in 8 of the 18 patients. The V37-V40 was significantly higher (p<0.05) in the patients with the new perfusion defects during RT than in the patients who did not exhibit these defects. Radiotherapy for EC induces cardiac damage from an early stage. (99m)Tc-MIBI SPECT GMPI can detect the occurrence of cardiac impairment during RT. The WM, WT, EDP and ESP may be valuable as early indicators of RIHD. The percentage of the heart volume that receives a high dose is an important factor that is correlated with RIHD. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

The washout rate of (123)I-BMIPP and the evolution of left ventricular function in patients with successfully reperfused ST-segment elevation myocardial infarction: comparisons with the echocardiography.

PubMed

Biswas, Shankar K; Sarai, Masayoshi; Yamada, Akira; Toyama, Hiroshi; Motoyama, Sadako; Harigaya, Hiroto; Hara, Tomonori; Naruse, Hiroyuki; Hishida, Hitoshi; Ozaki, Yukio

2010-02-01

The evolution of the oxidative metabolism of (11)C acetate parallels the recovery of left ventricular(LV) contraction following acute myocardial infarction(AMI). This study was designed to unravel, for the first time, the impact of the global washout rate(WR) of (123)I-beta-methyl-p-iodophenylpentadecanoic acid (BMIPP) on the recovery of LV function followingAMI, as evidenced from conventional echocardiography.Twenty consecutive patients (age: 58 +/- 13 years; 16 males and 4 females) with ST-segment elevation myocardial infarction (STEMI) were enrolled and all of them underwent successful percutaneous coronary intervention (PCI). (123)I-BMIPP cardiac scintigraphy was performed at 7 +/- 3 days after admission. The WR was calculated from the polar map and the regional BMIPP defect score was calculated using a 17 segment model. Echocardiography was performed within 24 h of admission and at 3 months to record the ejection fraction (EF), the wall motion score index (WMSI), the ratio of the mitralinflow velocity to the early diastolic velocity (E/E0)and the myocardial performance index (MPI). The mean global WR of the BMIPP was 22.12 +/- 7.22%, and it was significantly correlated with the improvement of the WMSI (r = 0.61, P\\0.004). However,the relative changes of the EF, E/E0 and MPI were not correlated with the WR. The BMIPP defect score (18 +/- 10) was significantly correlated with the WMSI on admission (r = 0.74, P = 0.0002), but the defect score was not correlated with the relative changes of any of the echocardiographic parameters. We proved that the WR of the BMIPP is a promising indicator of improvement of the LV wall motion (WMSI) following ST-segment elevation myocardial infarction and successful reperfusion.

Fast automatic 3D liver segmentation based on a three-level AdaBoost-guided active shape model

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

He, Baochun; Huang, Cheng; Zhou, Shoujun

Purpose: A robust, automatic, and rapid method for liver delineation is urgently needed for the diagnosis and treatment of liver disorders. Until now, the high variability in liver shape, local image artifacts, and the presence of tumors have complicated the development of automatic 3D liver segmentation. In this study, an automatic three-level AdaBoost-guided active shape model (ASM) is proposed for the segmentation of the liver based on enhanced computed tomography images in a robust and fast manner, with an emphasis on the detection of tumors. Methods: The AdaBoost voxel classifier and AdaBoost profile classifier were used to automatically guide three-levelmore » active shape modeling. In the first level of model initialization, fast automatic liver segmentation by an AdaBoost voxel classifier method is proposed. A shape model is then initialized by registration with the resulting rough segmentation. In the second level of active shape model fitting, a prior model based on the two-class AdaBoost profile classifier is proposed to identify the optimal surface. In the third level, a deformable simplex mesh with profile probability and curvature constraint as the external force is used to refine the shape fitting result. In total, three registration methods—3D similarity registration, probability atlas B-spline, and their proposed deformable closest point registration—are used to establish shape correspondence. Results: The proposed method was evaluated using three public challenge datasets: 3Dircadb1, SLIVER07, and Visceral Anatomy3. The results showed that our approach performs with promising efficiency, with an average of 35 s, and accuracy, with an average Dice similarity coefficient (DSC) of 0.94 ± 0.02, 0.96 ± 0.01, and 0.94 ± 0.02 for the 3Dircadb1, SLIVER07, and Anatomy3 training datasets, respectively. The DSC of the SLIVER07 testing and Anatomy3 unseen testing datasets were 0.964 and 0.933, respectively. Conclusions: The proposed automatic approach achieves robust, accurate, and fast liver segmentation for 3D CTce datasets. The AdaBoost voxel classifier can detect liver area quickly without errors and provides sufficient liver shape information for model initialization. The AdaBoost profile classifier achieves sufficient accuracy and greatly decreases segmentation time. These results show that the proposed segmentation method achieves a level of accuracy comparable to that of state-of-the-art automatic methods based on ASM.« less

Fast automatic 3D liver segmentation based on a three-level AdaBoost-guided active shape model.

PubMed

He, Baochun; Huang, Cheng; Sharp, Gregory; Zhou, Shoujun; Hu, Qingmao; Fang, Chihua; Fan, Yingfang; Jia, Fucang

2016-05-01

A robust, automatic, and rapid method for liver delineation is urgently needed for the diagnosis and treatment of liver disorders. Until now, the high variability in liver shape, local image artifacts, and the presence of tumors have complicated the development of automatic 3D liver segmentation. In this study, an automatic three-level AdaBoost-guided active shape model (ASM) is proposed for the segmentation of the liver based on enhanced computed tomography images in a robust and fast manner, with an emphasis on the detection of tumors. The AdaBoost voxel classifier and AdaBoost profile classifier were used to automatically guide three-level active shape modeling. In the first level of model initialization, fast automatic liver segmentation by an AdaBoost voxel classifier method is proposed. A shape model is then initialized by registration with the resulting rough segmentation. In the second level of active shape model fitting, a prior model based on the two-class AdaBoost profile classifier is proposed to identify the optimal surface. In the third level, a deformable simplex mesh with profile probability and curvature constraint as the external force is used to refine the shape fitting result. In total, three registration methods-3D similarity registration, probability atlas B-spline, and their proposed deformable closest point registration-are used to establish shape correspondence. The proposed method was evaluated using three public challenge datasets: 3Dircadb1, SLIVER07, and Visceral Anatomy3. The results showed that our approach performs with promising efficiency, with an average of 35 s, and accuracy, with an average Dice similarity coefficient (DSC) of 0.94 ± 0.02, 0.96 ± 0.01, and 0.94 ± 0.02 for the 3Dircadb1, SLIVER07, and Anatomy3 training datasets, respectively. The DSC of the SLIVER07 testing and Anatomy3 unseen testing datasets were 0.964 and 0.933, respectively. The proposed automatic approach achieves robust, accurate, and fast liver segmentation for 3D CTce datasets. The AdaBoost voxel classifier can detect liver area quickly without errors and provides sufficient liver shape information for model initialization. The AdaBoost profile classifier achieves sufficient accuracy and greatly decreases segmentation time. These results show that the proposed segmentation method achieves a level of accuracy comparable to that of state-of-the-art automatic methods based on ASM.

Content-based audio authentication using a hierarchical patchwork watermark embedding

NASA Astrophysics Data System (ADS)

Gulbis, Michael; Müller, Erika

2010-05-01

Content-based audio authentication watermarking techniques extract perceptual relevant audio features, which are robustly embedded into the audio file to protect. Manipulations of the audio file are detected on the basis of changes between the original embedded feature information and the anew extracted features during verification. The main challenges of content-based watermarking are on the one hand the identification of a suitable audio feature to distinguish between content preserving and malicious manipulations. On the other hand the development of a watermark, which is robust against content preserving modifications and able to carry the whole authentication information. The payload requirements are significantly higher compared to transaction watermarking or copyright protection. Finally, the watermark embedding should not influence the feature extraction to avoid false alarms. Current systems still lack a sufficient alignment of watermarking algorithm and feature extraction. In previous work we developed a content-based audio authentication watermarking approach. The feature is based on changes in DCT domain over time. A patchwork algorithm based watermark was used to embed multiple one bit watermarks. The embedding process uses the feature domain without inflicting distortions to the feature. The watermark payload is limited by the feature extraction, more precisely the critical bands. The payload is inverse proportional to segment duration of the audio file segmentation. Transparency behavior was analyzed in dependence of segment size and thus the watermark payload. At a segment duration of about 20 ms the transparency shows an optimum (measured in units of Objective Difference Grade). Transparency and/or robustness are fast decreased for working points beyond this area. Therefore, these working points are unsuitable to gain further payload, needed for the embedding of the whole authentication information. In this paper we present a hierarchical extension of the watermark method to overcome the limitations given by the feature extraction. The approach is a recursive application of the patchwork algorithm onto its own patches, with a modified patch selection to ensure a better signal to noise ratio for the watermark embedding. The robustness evaluation was done by compression (mp3, ogg, aac), normalization, and several attacks of the stirmark benchmark for audio suite. Compared on the base of same payload and transparency the hierarchical approach shows improved robustness.

Segmented molecular design of self-healing proteinaceous materials

PubMed Central

Sariola, Veikko; Pena-Francesch, Abdon; Jung, Huihun; Çetinkaya, Murat; Pacheco, Carlos; Sitti, Metin; Demirel, Melik C.

2015-01-01

Hierarchical assembly of self-healing adhesive proteins creates strong and robust structural and interfacial materials, but understanding of the molecular design and structure–property relationships of structural proteins remains unclear. Elucidating this relationship would allow rational design of next generation genetically engineered self-healing structural proteins. Here we report a general self-healing and -assembly strategy based on a multiphase recombinant protein based material. Segmented structure of the protein shows soft glycine- and tyrosine-rich segments with self-healing capability and hard beta-sheet segments. The soft segments are strongly plasticized by water, lowering the self-healing temperature close to body temperature. The hard segments self-assemble into nanoconfined domains to reinforce the material. The healing strength scales sublinearly with contact time, which associates with diffusion and wetting of autohesion. The finding suggests that recombinant structural proteins from heterologous expression have potential as strong and repairable engineering materials. PMID:26323335

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.

A spectral k-means approach to bright-field cell image segmentation.

PubMed

Bradbury, Laura; Wan, Justin W L

2010-01-01

Automatic segmentation of bright-field cell images is important to cell biologists, but difficult to complete due to the complex nature of the cells in bright-field images (poor contrast, broken halo, missing boundaries). Standard approaches such as level set segmentation and active contours work well for fluorescent images where cells appear as round shape, but become less effective when optical artifacts such as halo exist in bright-field images. In this paper, we present a robust segmentation method which combines the spectral and k-means clustering techniques to locate cells in bright-field images. This approach models an image as a matrix graph and segment different regions of the image by computing the appropriate eigenvectors of the matrix graph and using the k-means algorithm. We illustrate the effectiveness of the method by segmentation results of C2C12 (muscle) cells in bright-field images.

Segmented molecular design of self-healing proteinaceous materials

NASA Astrophysics Data System (ADS)

Sariola, Veikko; Pena-Francesch, Abdon; Jung, Huihun; Çetinkaya, Murat; Pacheco, Carlos; Sitti, Metin; Demirel, Melik C.

2015-09-01

Hierarchical assembly of self-healing adhesive proteins creates strong and robust structural and interfacial materials, but understanding of the molecular design and structure-property relationships of structural proteins remains unclear. Elucidating this relationship would allow rational design of next generation genetically engineered self-healing structural proteins. Here we report a general self-healing and -assembly strategy based on a multiphase recombinant protein based material. Segmented structure of the protein shows soft glycine- and tyrosine-rich segments with self-healing capability and hard beta-sheet segments. The soft segments are strongly plasticized by water, lowering the self-healing temperature close to body temperature. The hard segments self-assemble into nanoconfined domains to reinforce the material. The healing strength scales sublinearly with contact time, which associates with diffusion and wetting of autohesion. The finding suggests that recombinant structural proteins from heterologous expression have potential as strong and repairable engineering materials.

Segmented molecular design of self-healing proteinaceous materials.

PubMed

Sariola, Veikko; Pena-Francesch, Abdon; Jung, Huihun; Çetinkaya, Murat; Pacheco, Carlos; Sitti, Metin; Demirel, Melik C

2015-09-01

Hierarchical assembly of self-healing adhesive proteins creates strong and robust structural and interfacial materials, but understanding of the molecular design and structure-property relationships of structural proteins remains unclear. Elucidating this relationship would allow rational design of next generation genetically engineered self-healing structural proteins. Here we report a general self-healing and -assembly strategy based on a multiphase recombinant protein based material. Segmented structure of the protein shows soft glycine- and tyrosine-rich segments with self-healing capability and hard beta-sheet segments. The soft segments are strongly plasticized by water, lowering the self-healing temperature close to body temperature. The hard segments self-assemble into nanoconfined domains to reinforce the material. The healing strength scales sublinearly with contact time, which associates with diffusion and wetting of autohesion. The finding suggests that recombinant structural proteins from heterologous expression have potential as strong and repairable engineering materials.

An Algorithm to Automate Yeast Segmentation and Tracking

PubMed Central

Doncic, Andreas; Eser, Umut; Atay, Oguzhan; Skotheim, Jan M.

2013-01-01

Our understanding of dynamic cellular processes has been greatly enhanced by rapid advances in quantitative fluorescence microscopy. Imaging single cells has emphasized the prevalence of phenomena that can be difficult to infer from population measurements, such as all-or-none cellular decisions, cell-to-cell variability, and oscillations. Examination of these phenomena requires segmenting and tracking individual cells over long periods of time. However, accurate segmentation and tracking of cells is difficult and is often the rate-limiting step in an experimental pipeline. Here, we present an algorithm that accomplishes fully automated segmentation and tracking of budding yeast cells within growing colonies. The algorithm incorporates prior information of yeast-specific traits, such as immobility and growth rate, to segment an image using a set of threshold values rather than one specific optimized threshold. Results from the entire set of thresholds are then used to perform a robust final segmentation. PMID:23520484

Potential impacts of robust surface roughness indexes on DTM-based segmentation

NASA Astrophysics Data System (ADS)

Trevisani, Sebastiano; Rocca, Michele

2017-04-01

In this study, we explore the impact of robust surface texture indexes based on MAD (median absolute differences), implemented by Trevisani and Rocca (2015), in the unsupervised morphological segmentation of an alpine basin. The area was already object of a geomorphometric analysis, consisting in the roughness-based segmentation of the landscape (Trevisani et al. 2012); the roughness indexes were calculated on a high resolution DTM derived by means of airborne Lidar using the variogram as estimator. The calculated roughness indexes have been then used for the fuzzy clustering (Odeh et al., 1992; Burrough et al., 2000) of the basin, revealing the high informative geomorphometric content of the roughness-based indexes. However, the fuzzy clustering revealed a high fuzziness and a high degree of mixing between textural classes; this was ascribed both to the morphological complexity of the basin and to the high sensitivity of variogram to non-stationarity and signal-noise. Accordingly, we explore how the new implemented roughness indexes based on MAD affect the morphological segmentation of the studied basin. References Burrough, P.A., Van Gaans, P.F.M., MacMillan, R.A., 2000. High-resolution landform classification using fuzzy k-means. Fuzzy Sets and Systems 113, 37-52. Odeh, I.O.A., McBratney, A.B., Chittleborough, D.J., 1992. Soil pattern recognition with fuzzy-c-means: application to classification and soil-landform interrelationships. Soil Sciences Society of America Journal 56, 505-516. Trevisani, S., Cavalli, M. & Marchi, L. 2012, "Surface texture analysis of a high-resolution DTM: Interpreting an alpine basin", Geomorphology, vol. 161-162, pp. 26-39. Trevisani, S. & Rocca, M. 2015, "MAD: Robust image texture analysis for applications in high resolution geomorphometry", Computers and Geosciences, vol. 81, pp. 78-92.

Enhanced Bone Formation in Segmental Defects with BMP2 in a Biologically Relevant Molecular Context

DTIC Science & Technology

2016-10-16

gun shots . These do not heal on their own once a ‘critical size’ segment of bone is missing. One strategy to induce healing is to use bone-inducing...accelerate BMP2-induced bone formation by presenting the growth factor in a more biologically relevant context. This is based on our observation...that manganese increases the binding of BMP2 to COMP. The next steps are to validate these observations using BMP2:COMP on HA/PLG scaffolds in-vitro

Deep learning and texture-based semantic label fusion for brain tumor segmentation

NASA Astrophysics Data System (ADS)

Vidyaratne, L.; Alam, M.; Shboul, Z.; Iftekharuddin, K. M.

2018-02-01

Brain tumor segmentation is a fundamental step in surgical treatment and therapy. Many hand-crafted and learning based methods have been proposed for automatic brain tumor segmentation from MRI. Studies have shown that these approaches have their inherent advantages and limitations. This work proposes a semantic label fusion algorithm by combining two representative state-of-the-art segmentation algorithms: texture based hand-crafted, and deep learning based methods to obtain robust tumor segmentation. We evaluate the proposed method using publicly available BRATS 2017 brain tumor segmentation challenge dataset. The results show that the proposed method offers improved segmentation by alleviating inherent weaknesses: extensive false positives in texture based method, and the false tumor tissue classification problem in deep learning method, respectively. Furthermore, we investigate the effect of patient's gender on the segmentation performance using a subset of validation dataset. Note the substantial improvement in brain tumor segmentation performance proposed in this work has recently enabled us to secure the first place by our group in overall patient survival prediction task at the BRATS 2017 challenge.

Deep Learning and Texture-Based Semantic Label Fusion for Brain Tumor Segmentation.

PubMed

Vidyaratne, L; Alam, M; Shboul, Z; Iftekharuddin, K M

2018-01-01

Brain tumor segmentation is a fundamental step in surgical treatment and therapy. Many hand-crafted and learning based methods have been proposed for automatic brain tumor segmentation from MRI. Studies have shown that these approaches have their inherent advantages and limitations. This work proposes a semantic label fusion algorithm by combining two representative state-of-the-art segmentation algorithms: texture based hand-crafted, and deep learning based methods to obtain robust tumor segmentation. We evaluate the proposed method using publicly available BRATS 2017 brain tumor segmentation challenge dataset. The results show that the proposed method offers improved segmentation by alleviating inherent weaknesses: extensive false positives in texture based method, and the false tumor tissue classification problem in deep learning method, respectively. Furthermore, we investigate the effect of patient's gender on the segmentation performance using a subset of validation dataset. Note the substantial improvement in brain tumor segmentation performance proposed in this work has recently enabled us to secure the first place by our group in overall patient survival prediction task at the BRATS 2017 challenge.

Unmanned Ground Vehicle for Autonomous Non-Destructive Testing of FRP Bridge Decks

NASA Astrophysics Data System (ADS)

Klinkhachorn, P.; Mercer, A. Scott; Halabe, Udaya B.; GangaRao, Hota V. S.

2007-03-01

Current non-destructive techniques for defect analysis of FRP bridge decks have a narrow scope. These techniques are very good at detecting certain types of defects but are not robust enough to detect all defects by themselves. For example, infrared thermography (IRT) can detect air filled defects and Ground Penetrating Radar (GPR) is good at detecting water filled ones. These technologies can be combined to create a more robust defect detection scheme. To accomplish this, an Unmanned Ground Vehicle (UGV) has been designed that incorporates both IR and GPR analysis to create a comprehensive defect map of a bridge deck. The UGV autonomously surveys the deck surface and acquires data. The UGV has two 1.5 GHz ground coupled GPR antennas that are mounted on the front of the UGV to collect GPR data. It also incorporates an active heating source and a radiometric IR camera to capture IR images of the deck, even in less than ideal weather scenarios such as cold cloudy days. The UGV is designed so that it can collect data in an assembly line fashion. It moves in 1 foot increments. When moving, it collects GPR data from the two antennas. When it stops it heats a section of the deck. The next time it stops to heat a section, the IR camera is analyzing the preheated deck section while preparing for the next section. Because the data is being continually collected using this method, the UGV can survey the entire deck in an efficient and timely manner.

Enhanced Healing of Segmental Bone Defects by Modulation of the Mechanical Environment

DTIC Science & Technology

2012-10-01

5.5 µg BMP-2, it was largely disorganized, woven bone with non-osseous soft tissue interspersed. The highest 4 dose (11 µg) of BMP-2, in contrast...various doses of BMP-2. Top row: 16x magnification Bottom row: 100x magnification N= new cortex M= marrow T=trabecular bone F= fibrous tissue ...areas of cartilagenous tissue (figure 5) it was clear that substantial areas of cartilage remained in the defects treated with 5.5 µg BMP-2. These may

Lethal Progressive Thoracic Insufficiency in a Neonate Due to Jarcho Levin Syndrome

PubMed Central

Bhutia, Euden; Maria, Arti; Verma, Arushi; Sethi, Sidharth Kumar

2014-01-01

A rare case of Jarcho Levin syndrome (JLS) presenting as a lethal progressive respiratory insufficiency in early neonatal period is reported. The neonate had classical features of this syndrome including vertebral segmentation defects, typical costo-vertebral fusion defects and scoliosis resulting in small thoracic volume and limited chest expansion; all consistent with a clinical diagnosis of JLS with thoracic insufficiency. In addition, our case had a rare association of dextrocardia and acyanotic congenital heart disease. PMID:24741543

Optimization of Soft Tissue Management, Spacer Design, and Grafting Strategies For Large Segmental Bone Defects Using The Chronic Caprine Tibial Defect Model

DTIC Science & Technology

2014-10-01

spacer placed at the time of the “Pre-Procedure”. Autogenous Cancellous Bone Graft (ACBG harvested from the sternum at the time of the treatment...will receive more specialized training and orientation to microCT analysis, both on a theoretical and practical level. He will work with raw CT...adjacent to the PMMA) composed of mononuclear cells and exhibited extensive, diffuse fibrous connective tissue.  Performed histology on goat autogenous

Improved Healing of Large, Osseous, Segmental Defects by Reverse Dynamization: Evaluation in a Sheep Model

DTIC Science & Technology

2014-10-01

initiated. One such fixator has been tested on a cadaveric sheep tibia. In the unlocked, loose position, the axial stiffness of the tibia and fixator...suggested by our previous studies using rats. This aspect of the project is the present focus of attention, and additional cadaver legs will be tested...characterize external fixators). A 3 mm tibial defect was created in the leg of a cadaveric sheep, and stabilized with an experimental external

Auto-segmentation of normal and target structures in head and neck CT images: a feature-driven model-based approach.

PubMed

Qazi, Arish A; Pekar, Vladimir; Kim, John; Xie, Jason; Breen, Stephen L; Jaffray, David A

2011-11-01

Intensity modulated radiation therapy (IMRT) allows greater control over dose distribution, which leads to a decrease in radiation related toxicity. IMRT, however, requires precise and accurate delineation of the organs at risk and target volumes. Manual delineation is tedious and suffers from both interobserver and intraobserver variability. State of the art auto-segmentation methods are either atlas-based, model-based or hybrid however, robust fully automated segmentation is often difficult due to the insufficient discriminative information provided by standard medical imaging modalities for certain tissue types. In this paper, the authors present a fully automated hybrid approach which combines deformable registration with the model-based approach to accurately segment normal and target tissues from head and neck CT images. The segmentation process starts by using an average atlas to reliably identify salient landmarks in the patient image. The relationship between these landmarks and the reference dataset serves to guide a deformable registration algorithm, which allows for a close initialization of a set of organ-specific deformable models in the patient image, ensuring their robust adaptation to the boundaries of the structures. Finally, the models are automatically fine adjusted by our boundary refinement approach which attempts to model the uncertainty in model adaptation using a probabilistic mask. This uncertainty is subsequently resolved by voxel classification based on local low-level organ-specific features. To quantitatively evaluate the method, they auto-segment several organs at risk and target tissues from 10 head and neck CT images. They compare the segmentations to the manual delineations outlined by the expert. The evaluation is carried out by estimating two common quantitative measures on 10 datasets: volume overlap fraction or the Dice similarity coefficient (DSC), and a geometrical metric, the median symmetric Hausdorff distance (HD), which is evaluated slice-wise. They achieve an average overlap of 93% for the mandible, 91% for the brainstem, 83% for the parotids, 83% for the submandibular glands, and 74% for the lymph node levels. Our automated segmentation framework is able to segment anatomy in the head and neck region with high accuracy within a clinically-acceptable segmentation time.

Causal Video Object Segmentation From Persistence of Occlusions

DTIC Science & Technology

2015-05-01

Precision, recall, and F-measure are reported on the ground truth anno - tations converted to binary masks. Note we cannot evaluate “number of...to lack of occlusions. References [1] P. Arbelaez, M. Maire, C. Fowlkes, and J . Malik. Con- tour detection and hierarchical image segmentation. TPAMI...X. Bai, J . Wang, D. Simons, and G. Sapiro. Video snapcut: robust video object cutout using localized classifiers. In ACM Transactions on Graphics

Improved Estimation of Cardiac Function Parameters Using a Combination of Independent Automated Segmentation Results in Cardiovascular Magnetic Resonance Imaging.

PubMed

Lebenberg, Jessica; Lalande, Alain; Clarysse, Patrick; Buvat, Irene; Casta, Christopher; Cochet, Alexandre; Constantinidès, Constantin; Cousty, Jean; de Cesare, Alain; Jehan-Besson, Stephanie; Lefort, Muriel; Najman, Laurent; Roullot, Elodie; Sarry, Laurent; Tilmant, Christophe; Frouin, Frederique; Garreau, Mireille

2015-01-01

This work aimed at combining different segmentation approaches to produce a robust and accurate segmentation result. Three to five segmentation results of the left ventricle were combined using the STAPLE algorithm and the reliability of the resulting segmentation was evaluated in comparison with the result of each individual segmentation method. This comparison was performed using a supervised approach based on a reference method. Then, we used an unsupervised statistical evaluation, the extended Regression Without Truth (eRWT) that ranks different methods according to their accuracy in estimating a specific biomarker in a population. The segmentation accuracy was evaluated by estimating six cardiac function parameters resulting from the left ventricle contour delineation using a public cardiac cine MRI database. Eight different segmentation methods, including three expert delineations and five automated methods, were considered, and sixteen combinations of the automated methods using STAPLE were investigated. The supervised and unsupervised evaluations demonstrated that in most cases, STAPLE results provided better estimates than individual automated segmentation methods. Overall, combining different automated segmentation methods improved the reliability of the segmentation result compared to that obtained using an individual method and could achieve the accuracy of an expert.

Improved Estimation of Cardiac Function Parameters Using a Combination of Independent Automated Segmentation Results in Cardiovascular Magnetic Resonance Imaging

PubMed Central

Lebenberg, Jessica; Lalande, Alain; Clarysse, Patrick; Buvat, Irene; Casta, Christopher; Cochet, Alexandre; Constantinidès, Constantin; Cousty, Jean; de Cesare, Alain; Jehan-Besson, Stephanie; Lefort, Muriel; Najman, Laurent; Roullot, Elodie; Sarry, Laurent; Tilmant, Christophe

2015-01-01

This work aimed at combining different segmentation approaches to produce a robust and accurate segmentation result. Three to five segmentation results of the left ventricle were combined using the STAPLE algorithm and the reliability of the resulting segmentation was evaluated in comparison with the result of each individual segmentation method. This comparison was performed using a supervised approach based on a reference method. Then, we used an unsupervised statistical evaluation, the extended Regression Without Truth (eRWT) that ranks different methods according to their accuracy in estimating a specific biomarker in a population. The segmentation accuracy was evaluated by estimating six cardiac function parameters resulting from the left ventricle contour delineation using a public cardiac cine MRI database. Eight different segmentation methods, including three expert delineations and five automated methods, were considered, and sixteen combinations of the automated methods using STAPLE were investigated. The supervised and unsupervised evaluations demonstrated that in most cases, STAPLE results provided better estimates than individual automated segmentation methods. Overall, combining different automated segmentation methods improved the reliability of the segmentation result compared to that obtained using an individual method and could achieve the accuracy of an expert. PMID:26287691

Retina Image Vessel Segmentation Using a Hybrid CGLI Level Set Method

PubMed Central

Chen, Meizhu; Li, Jichun; Zhang, Encai

2017-01-01

As a nonintrusive method, the retina imaging provides us with a better way for the diagnosis of ophthalmologic diseases. Extracting the vessel profile automatically from the retina image is an important step in analyzing retina images. A novel hybrid active contour model is proposed to segment the fundus image automatically in this paper. It combines the signed pressure force function introduced by the Selective Binary and Gaussian Filtering Regularized Level Set (SBGFRLS) model with the local intensity property introduced by the Local Binary fitting (LBF) model to overcome the difficulty of the low contrast in segmentation process. It is more robust to the initial condition than the traditional methods and is easily implemented compared to the supervised vessel extraction methods. Proposed segmentation method was evaluated on two public datasets, DRIVE (Digital Retinal Images for Vessel Extraction) and STARE (Structured Analysis of the Retina) (the average accuracy of 0.9390 with 0.7358 sensitivity and 0.9680 specificity on DRIVE datasets and average accuracy of 0.9409 with 0.7449 sensitivity and 0.9690 specificity on STARE datasets). The experimental results show that our method is effective and our method is also robust to some kinds of pathology images compared with the traditional level set methods. PMID:28840122

Fully Bayesian inference for structural MRI: application to segmentation and statistical analysis of T2-hypointensities.

PubMed

Schmidt, Paul; Schmid, Volker J; Gaser, Christian; Buck, Dorothea; Bührlen, Susanne; Förschler, Annette; Mühlau, Mark

2013-01-01

Aiming at iron-related T2-hypointensity, which is related to normal aging and neurodegenerative processes, we here present two practicable approaches, based on Bayesian inference, for preprocessing and statistical analysis of a complex set of structural MRI data. In particular, Markov Chain Monte Carlo methods were used to simulate posterior distributions. First, we rendered a segmentation algorithm that uses outlier detection based on model checking techniques within a Bayesian mixture model. Second, we rendered an analytical tool comprising a Bayesian regression model with smoothness priors (in the form of Gaussian Markov random fields) mitigating the necessity to smooth data prior to statistical analysis. For validation, we used simulated data and MRI data of 27 healthy controls (age: [Formula: see text]; range, [Formula: see text]). We first observed robust segmentation of both simulated T2-hypointensities and gray-matter regions known to be T2-hypointense. Second, simulated data and images of segmented T2-hypointensity were analyzed. We found not only robust identification of simulated effects but also a biologically plausible age-related increase of T2-hypointensity primarily within the dentate nucleus but also within the globus pallidus, substantia nigra, and red nucleus. Our results indicate that fully Bayesian inference can successfully be applied for preprocessing and statistical analysis of structural MRI data.

Automatic segmentation of white matter hyperintensities robust to multicentre acquisition and pathological variability

NASA Astrophysics Data System (ADS)

Samaille, T.; Colliot, O.; Cuingnet, R.; Jouvent, E.; Chabriat, H.; Dormont, D.; Chupin, M.

2012-02-01

White matter hyperintensities (WMH), commonly seen on FLAIR images in elderly people, are a risk factor for dementia onset and have been associated with motor and cognitive deficits. We present here a method to fully automatically segment WMH from T1 and FLAIR images. Iterative steps of non linear diffusion followed by watershed segmentation were applied on FLAIR images until convergence. Diffusivity function and associated contrast parameter were carefully designed to adapt to WMH segmentation. It resulted in piecewise constant images with enhanced contrast between lesions and surrounding tissues. Selection of WMH areas was based on two characteristics: 1) a threshold automatically computed for intensity selection, 2) main location of areas in white matter. False positive areas were finally removed based on their proximity with cerebrospinal fluid/grey matter interface. Evaluation was performed on 67 patients: 24 with amnestic mild cognitive impairment (MCI), from five different centres, and 43 with Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoaraiosis (CADASIL) acquired in a single centre. Results showed excellent volume agreement with manual delineation (Pearson coefficient: r=0.97, p<0.001) and substantial spatial correspondence (Similarity Index: 72%+/-16%). Our method appeared robust to acquisition differences across the centres as well as to pathological variability.

49 CFR 195.230 - Welds: Repair or removal of defects.

Code of Federal Regulations, 2012 CFR

2012-10-01

... adversely affect the quality of the weld repair. After repair, the segment of the weld that was repaired... welding procedure used to make the original weld are met upon completion of the final weld repair. [Amdt...

49 CFR 195.230 - Welds: Repair or removal of defects.

Code of Federal Regulations, 2014 CFR

2014-10-01

... adversely affect the quality of the weld repair. After repair, the segment of the weld that was repaired... welding procedure used to make the original weld are met upon completion of the final weld repair. [Amdt...

49 CFR 195.230 - Welds: Repair or removal of defects.

Code of Federal Regulations, 2011 CFR

2011-10-01

... adversely affect the quality of the weld repair. After repair, the segment of the weld that was repaired... welding procedure used to make the original weld are met upon completion of the final weld repair. [Amdt...

49 CFR 195.230 - Welds: Repair or removal of defects.

Code of Federal Regulations, 2013 CFR

2013-10-01

... adversely affect the quality of the weld repair. After repair, the segment of the weld that was repaired... welding procedure used to make the original weld are met upon completion of the final weld repair. [Amdt...

49 CFR 195.230 - Welds: Repair or removal of defects.

Code of Federal Regulations, 2010 CFR

2010-10-01

... adversely affect the quality of the weld repair. After repair, the segment of the weld that was repaired... welding procedure used to make the original weld are met upon completion of the final weld repair. [Amdt...

A multi-layer steganographic method based on audio time domain segmented and network steganography

NASA Astrophysics Data System (ADS)

Xue, Pengfei; Liu, Hanlin; Hu, Jingsong; Hu, Ronggui

2018-05-01

Both audio steganography and network steganography are belong to modern steganography. Audio steganography has a large capacity. Network steganography is difficult to detect or track. In this paper, a multi-layer steganographic method based on the collaboration of them (MLS-ATDSS&NS) is proposed. MLS-ATDSS&NS is realized in two covert layers (audio steganography layer and network steganography layer) by two steps. A new audio time domain segmented steganography (ATDSS) method is proposed in step 1, and the collaboration method of ATDSS and NS is proposed in step 2. The experimental results showed that the advantage of MLS-ATDSS&NS over others is better trade-off between capacity, anti-detectability and robustness, that means higher steganographic capacity, better anti-detectability and stronger robustness.

A cascaded two-step Kalman filter for estimation of human body segment orientation using MEMS-IMU.

PubMed

Zihajehzadeh, S; Loh, D; Lee, M; Hoskinson, R; Park, E J

2014-01-01

Orientation of human body segments is an important quantity in many biomechanical analyses. To get robust and drift-free 3-D orientation, raw data from miniature body worn MEMS-based inertial measurement units (IMU) should be blended in a Kalman filter. Aiming at less computational cost, this work presents a novel cascaded two-step Kalman filter orientation estimation algorithm. Tilt angles are estimated in the first step of the proposed cascaded Kalman filter. The estimated tilt angles are passed to the second step of the filter for yaw angle calculation. The orientation results are benchmarked against the ones from a highly accurate tactical grade IMU. Experimental results reveal that the proposed algorithm provides robust orientation estimation in both kinematically and magnetically disturbed conditions.

Segmentation and tracking of lung nodules via graph-cuts incorporating shape prior and motion from 4D CT.

PubMed

Cha, Jungwon; Farhangi, Mohammad Mehdi; Dunlap, Neal; Amini, Amir A

2018-01-01

We have developed a robust tool for performing volumetric and temporal analysis of nodules from respiratory gated four-dimensional (4D) CT. The method could prove useful in IMRT of lung cancer. We modified the conventional graph-cuts method by adding an adaptive shape prior as well as motion information within a signed distance function representation to permit more accurate and automated segmentation and tracking of lung nodules in 4D CT data. Active shape models (ASM) with signed distance function were used to capture the shape prior information, preventing unwanted surrounding tissues from becoming part of the segmented object. The optical flow method was used to estimate the local motion and to extend three-dimensional (3D) segmentation to 4D by warping a prior shape model through time. The algorithm has been applied to segmentation of well-circumscribed, vascularized, and juxtapleural lung nodules from respiratory gated CT data. In all cases, 4D segmentation and tracking for five phases of high-resolution CT data took approximately 10 min on a PC workstation with AMD Phenom II and 32 GB of memory. The method was trained based on 500 breath-held 3D CT data from the LIDC data base and was tested on 17 4D lung nodule CT datasets consisting of 85 volumetric frames. The validation tests resulted in an average Dice Similarity Coefficient (DSC) = 0.68 for all test data. An important by-product of the method is quantitative volume measurement from 4D CT from end-inspiration to end-expiration which will also have important diagnostic value. The algorithm performs robust segmentation of lung nodules from 4D CT data. Signed distance ASM provides the shape prior information which based on the iterative graph-cuts framework is adaptively refined to best fit the input data, preventing unwanted surrounding tissue from merging with the segmented object. © 2017 American Association of Physicists in Medicine.

Novel multimodality segmentation using level sets and Jensen-Rényi divergence

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

Markel, Daniel, E-mail: daniel.markel@mail.mcgill.ca; Zaidi, Habib; Geneva Neuroscience Center, Geneva University, CH-1205 Geneva

2013-12-15

Purpose: Positron emission tomography (PET) is playing an increasing role in radiotherapy treatment planning. However, despite progress, robust algorithms for PET and multimodal image segmentation are still lacking, especially if the algorithm were extended to image-guided and adaptive radiotherapy (IGART). This work presents a novel multimodality segmentation algorithm using the Jensen-Rényi divergence (JRD) to evolve the geometric level set contour. The algorithm offers improved noise tolerance which is particularly applicable to segmentation of regions found in PET and cone-beam computed tomography. Methods: A steepest gradient ascent optimization method is used in conjunction with the JRD and a level set activemore » contour to iteratively evolve a contour to partition an image based on statistical divergence of the intensity histograms. The algorithm is evaluated using PET scans of pharyngolaryngeal squamous cell carcinoma with the corresponding histological reference. The multimodality extension of the algorithm is evaluated using 22 PET/CT scans of patients with lung carcinoma and a physical phantom scanned under varying image quality conditions. Results: The average concordance index (CI) of the JRD segmentation of the PET images was 0.56 with an average classification error of 65%. The segmentation of the lung carcinoma images had a maximum diameter relative error of 63%, 19.5%, and 14.8% when using CT, PET, and combined PET/CT images, respectively. The estimated maximal diameters of the gross tumor volume (GTV) showed a high correlation with the macroscopically determined maximal diameters, with aR{sup 2} value of 0.85 and 0.88 using the PET and PET/CT images, respectively. Results from the physical phantom show that the JRD is more robust to image noise compared to mutual information and region growing. Conclusions: The JRD has shown improved noise tolerance compared to mutual information for the purpose of PET image segmentation. Presented is a flexible framework for multimodal image segmentation that can incorporate a large number of inputs efficiently for IGART.« less

Novel multimodality segmentation using level sets and Jensen-Rényi divergence.

PubMed

Markel, Daniel; Zaidi, Habib; El Naqa, Issam

2013-12-01

Positron emission tomography (PET) is playing an increasing role in radiotherapy treatment planning. However, despite progress, robust algorithms for PET and multimodal image segmentation are still lacking, especially if the algorithm were extended to image-guided and adaptive radiotherapy (IGART). This work presents a novel multimodality segmentation algorithm using the Jensen-Rényi divergence (JRD) to evolve the geometric level set contour. The algorithm offers improved noise tolerance which is particularly applicable to segmentation of regions found in PET and cone-beam computed tomography. A steepest gradient ascent optimization method is used in conjunction with the JRD and a level set active contour to iteratively evolve a contour to partition an image based on statistical divergence of the intensity histograms. The algorithm is evaluated using PET scans of pharyngolaryngeal squamous cell carcinoma with the corresponding histological reference. The multimodality extension of the algorithm is evaluated using 22 PET/CT scans of patients with lung carcinoma and a physical phantom scanned under varying image quality conditions. The average concordance index (CI) of the JRD segmentation of the PET images was 0.56 with an average classification error of 65%. The segmentation of the lung carcinoma images had a maximum diameter relative error of 63%, 19.5%, and 14.8% when using CT, PET, and combined PET/CT images, respectively. The estimated maximal diameters of the gross tumor volume (GTV) showed a high correlation with the macroscopically determined maximal diameters, with a R(2) value of 0.85 and 0.88 using the PET and PET/CT images, respectively. Results from the physical phantom show that the JRD is more robust to image noise compared to mutual information and region growing. The JRD has shown improved noise tolerance compared to mutual information for the purpose of PET image segmentation. Presented is a flexible framework for multimodal image segmentation that can incorporate a large number of inputs efficiently for IGART.

Dual-threshold segmentation using Arimoto entropy based on chaotic bee colony optimization

NASA Astrophysics Data System (ADS)

Li, Li

2018-03-01

In order to extract target from complex background more quickly and accurately, and to further improve the detection effect of defects, a method of dual-threshold segmentation using Arimoto entropy based on chaotic bee colony optimization was proposed. Firstly, the method of single-threshold selection based on Arimoto entropy was extended to dual-threshold selection in order to separate the target from the background more accurately. Then intermediate variables in formulae of Arimoto entropy dual-threshold selection was calculated by recursion to eliminate redundant computation effectively and to reduce the amount of calculation. Finally, the local search phase of artificial bee colony algorithm was improved by chaotic sequence based on tent mapping. The fast search for two optimal thresholds was achieved using the improved bee colony optimization algorithm, thus the search could be accelerated obviously. A large number of experimental results show that, compared with the existing segmentation methods such as multi-threshold segmentation method using maximum Shannon entropy, two-dimensional Shannon entropy segmentation method, two-dimensional Tsallis gray entropy segmentation method and multi-threshold segmentation method using reciprocal gray entropy, the proposed method can segment target more quickly and accurately with superior segmentation effect. It proves to be an instant and effective method for image segmentation.

Robust flow of light in three-dimensional dielectric photonic crystals.

PubMed

Chen, Wen-Jie; Jiang, Shao-Ji; Dong, Jian-Wen

2013-09-01

Chiral defect waveguides and waveguide bend geometry were designed in diamond photonic crystal to mold the flow of light in three dimensions. Propagations of electromagnetic waves in chiral waveguides are robust against isotropic obstacles, which would suppress backscattering in waveguides or integrated devices. Finite-difference time-domain simulations demonstrate that high coupling efficiency through the bend corner is preserved in the polarization gap, as it provides an additional constraint on the polarization state of the backscattered wave. Transport robustness is also demonstrated by inserting two metallic slabs into the waveguide bend.

A support vector machine approach for classification of welding defects from ultrasonic signals

NASA Astrophysics Data System (ADS)

Chen, Yuan; Ma, Hong-Wei; Zhang, Guang-Ming

2014-07-01

Defect classification is an important issue in ultrasonic non-destructive evaluation. A layered multi-class support vector machine (LMSVM) classification system, which combines multiple SVM classifiers through a layered architecture, is proposed in this paper. The proposed LMSVM classification system is applied to the classification of welding defects from ultrasonic test signals. The measured ultrasonic defect echo signals are first decomposed into wavelet coefficients by the wavelet packet transform. The energy of the wavelet coefficients at different frequency channels are used to construct the feature vectors. The bees algorithm (BA) is then used for feature selection and SVM parameter optimisation for the LMSVM classification system. The BA-based feature selection optimises the energy feature vectors. The optimised feature vectors are input to the LMSVM classification system for training and testing. Experimental results of classifying welding defects demonstrate that the proposed technique is highly robust, precise and reliable for ultrasonic defect classification.

Atomic defects in monolayer WSe2 tunneling FETs studied by systematic ab initio calculations

NASA Astrophysics Data System (ADS)

Wu, Jixuan; Fan, Zhiqiang; Chen, Jiezhi; Jiang, Xiangwei

2018-05-01

Atomic defects in monolayer WSe2 tunneling FETs (TFETs) are studied through systematic ab initio calculations aiming at performance predictions and enhancements. The effects of various defect positions and different passivation atoms are characterized in WSe2 TFETs by rigorous ab initio quantum transport simulations. It is suggested that the Se vacancy (VSe) defect located in the gate-controlled channel region tends to increase the OFF current (I off), whereas it can be well suppressed by oxygen passivation. It is demonstrated that chlorine (Cl) passivation at the source-side tunneling region can largely suppress I off, leading to an impressively improved on–off ratio (I on/I off) compared with that without any defect. However, it is also observed that randomly positioned atomic defects tend to induce significant fluctuation of the TFET output. Further discussions are made with focus on the performance-variability trade-off for robust circuit design.

Inferring the most probable maps of underground utilities using Bayesian mapping model

NASA Astrophysics Data System (ADS)

Bilal, Muhammad; Khan, Wasiq; Muggleton, Jennifer; Rustighi, Emiliano; Jenks, Hugo; Pennock, Steve R.; Atkins, Phil R.; Cohn, Anthony

2018-03-01

Mapping the Underworld (MTU), a major initiative in the UK, is focused on addressing social, environmental and economic consequences raised from the inability to locate buried underground utilities (such as pipes and cables) by developing a multi-sensor mobile device. The aim of MTU device is to locate different types of buried assets in real time with the use of automated data processing techniques and statutory records. The statutory records, even though typically being inaccurate and incomplete, provide useful prior information on what is buried under the ground and where. However, the integration of information from multiple sensors (raw data) with these qualitative maps and their visualization is challenging and requires the implementation of robust machine learning/data fusion approaches. An approach for automated creation of revised maps was developed as a Bayesian Mapping model in this paper by integrating the knowledge extracted from sensors raw data and available statutory records. The combination of statutory records with the hypotheses from sensors was for initial estimation of what might be found underground and roughly where. The maps were (re)constructed using automated image segmentation techniques for hypotheses extraction and Bayesian classification techniques for segment-manhole connections. The model consisting of image segmentation algorithm and various Bayesian classification techniques (segment recognition and expectation maximization (EM) algorithm) provided robust performance on various simulated as well as real sites in terms of predicting linear/non-linear segments and constructing refined 2D/3D maps.

Bilateral anterior segment dysgenesis with the presumed Peters' anomaly in a cat.

PubMed

Park, Sangwan; Kim, Kiwoong; Kim, Youngbeum; Seo, Kangmoon

2018-02-20

A seven-month-old female domestic shorthaired cat was presented for buphthalmos in the right eye and corneal cloudiness in the left eye. Full ophthalmic examinations were performed for both eyes and enucleation was done for the right nonvisual eye. Congenital glaucoma caused by anterior segment dysgenesis was confirmed for the right eye. In the left eye, slit-lamp examination revealed focal corneal edema with several iris strands from iris collarette to the affected posterior corneal surfaces. Circular posterior corneal defect was suggested to be the cause of edema. Goniodysgenesis, additionally, was identified. Taken together, the diagnosis of Peters' anomaly which is a subtype of anterior segment dysgenesis was suggested in the left eye.

A multiple-feature and multiple-kernel scene segmentation algorithm for humanoid robot.

PubMed

Liu, Zhi; Xu, Shuqiong; Zhang, Yun; Chen, Chun Lung Philip

2014-11-01

This technical correspondence presents a multiple-feature and multiple-kernel support vector machine (MFMK-SVM) methodology to achieve a more reliable and robust segmentation performance for humanoid robot. The pixel wise intensity, gradient, and C1 SMF features are extracted via the local homogeneity model and Gabor filter, which would be used as inputs of MFMK-SVM model. It may provide multiple features of the samples for easier implementation and efficient computation of MFMK-SVM model. A new clustering method, which is called feature validity-interval type-2 fuzzy C-means (FV-IT2FCM) clustering algorithm, is proposed by integrating a type-2 fuzzy criterion in the clustering optimization process to improve the robustness and reliability of clustering results by the iterative optimization. Furthermore, the clustering validity is employed to select the training samples for the learning of the MFMK-SVM model. The MFMK-SVM scene segmentation method is able to fully take advantage of the multiple features of scene image and the ability of multiple kernels. Experiments on the BSDS dataset and real natural scene images demonstrate the superior performance of our proposed method.

Vision Sensor-Based Road Detection for Field Robot Navigation

PubMed Central

Lu, Keyu; Li, Jian; An, Xiangjing; He, Hangen

2015-01-01

Road detection is an essential component of field robot navigation systems. Vision sensors play an important role in road detection for their great potential in environmental perception. In this paper, we propose a hierarchical vision sensor-based method for robust road detection in challenging road scenes. More specifically, for a given road image captured by an on-board vision sensor, we introduce a multiple population genetic algorithm (MPGA)-based approach for efficient road vanishing point detection. Superpixel-level seeds are then selected in an unsupervised way using a clustering strategy. Then, according to the GrowCut framework, the seeds proliferate and iteratively try to occupy their neighbors. After convergence, the initial road segment is obtained. Finally, in order to achieve a globally-consistent road segment, the initial road segment is refined using the conditional random field (CRF) framework, which integrates high-level information into road detection. We perform several experiments to evaluate the common performance, scale sensitivity and noise sensitivity of the proposed method. The experimental results demonstrate that the proposed method exhibits high robustness compared to the state of the art. PMID:26610514

Robust Multiple-Range Coherent Quantum State Transfer

PubMed Central

Chen, Bing; Peng, Yan-Dong; Li, Yong; Qian, Xiao-Feng

2016-01-01

We propose a multiple-range quantum communication channel to realize coherent two-way quantum state transport with high fidelity. In our scheme, an information carrier (a qubit) and its remote partner are both adiabatically coupled to the same data bus, i.e., an N-site tight-binding chain that has a single defect at the center. At the weak interaction regime, our system is effectively equivalent to a three level system of which a coherent superposition of the two carrier states constitutes a dark state. The adiabatic coupling allows a well controllable information exchange timing via the dark state between the two carriers. Numerical results show that our scheme is robust and efficient under practically inevitable perturbative defects of the data bus as well as environmental dephasing noise. PMID:27364891

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.

Aerial images visual localization on a vector map using color-texture segmentation

NASA Astrophysics Data System (ADS)

Kunina, I. A.; Teplyakov, L. M.; Gladkov, A. P.; Khanipov, T. M.; Nikolaev, D. P.

2018-04-01

In this paper we study the problem of combining UAV obtained optical data and a coastal vector map in absence of satellite navigation data. The method is based on presenting the territory as a set of segments produced by color-texture image segmentation. We then find such geometric transform which gives the best match between these segments and land and water areas of the georeferenced vector map. We calculate transform consisting of an arbitrary shift relatively to the vector map and bound rotation and scaling. These parameters are estimated using the RANSAC algorithm which matches the segments contours and the contours of land and water areas of the vector map. To implement this matching we suggest computing shape descriptors robust to rotation and scaling. We performed numerical experiments demonstrating the practical applicability of the proposed method.

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).

[Three-dimensional finite element analysis of three conjunctive methods of free iliac bone graft for established mandibular body defects].

PubMed

Wang, Dong; Yang, Zhuang-qun; Hu, Xiao-yi

2007-08-01

To analyze the stress and displacement distribution of 3D-FE models in three conjunctive methods of vascularized iliac bone graft for established mandibular body defects. Using computer image process technique, a series of spiral CT images were put into Ansys preprocess programe to establish three 3D-FE models of different conjunctions. The three 3D-FE models of established mandibular body defects by vascularized iliac bone graft were built up. The distribution of Von Mises stress and displacement around mandibular segment, grafted ilium, plates and screws was obtained. It may be determined successfully that the optimal conjunctive shape be the on-lay conjunction.

Development of a Novel Segmental Bone Defect Construct

DTIC Science & Technology

2016-10-01

from chicken egg white (90%) were purchased from Sigma Aldrich (St. Louis, MO). Ethylene glycol, sodium metabisulfite (SMS), urea, and hydrogen...HRP-conjugated polyclonal anti-LYZ (chicken egg white) was purchased from United States Biological (Swampscott, MA). N-(3-Sulfopropyl)- N

Improved and Robust Detection of Cell Nuclei from Four Dimensional Fluorescence Images

PubMed Central

Bashar, Md. Khayrul; Yamagata, Kazuo; Kobayashi, Tetsuya J.

2014-01-01

Segmentation-free direct methods are quite efficient for automated nuclei extraction from high dimensional images. A few such methods do exist but most of them do not ensure algorithmic robustness to parameter and noise variations. In this research, we propose a method based on multiscale adaptive filtering for efficient and robust detection of nuclei centroids from four dimensional (4D) fluorescence images. A temporal feedback mechanism is employed between the enhancement and the initial detection steps of a typical direct method. We estimate the minimum and maximum nuclei diameters from the previous frame and feed back them as filter lengths for multiscale enhancement of the current frame. A radial intensity-gradient function is optimized at positions of initial centroids to estimate all nuclei diameters. This procedure continues for processing subsequent images in the sequence. Above mechanism thus ensures proper enhancement by automated estimation of major parameters. This brings robustness and safeguards the system against additive noises and effects from wrong parameters. Later, the method and its single-scale variant are simplified for further reduction of parameters. The proposed method is then extended for nuclei volume segmentation. The same optimization technique is applied to final centroid positions of the enhanced image and the estimated diameters are projected onto the binary candidate regions to segment nuclei volumes.Our method is finally integrated with a simple sequential tracking approach to establish nuclear trajectories in the 4D space. Experimental evaluations with five image-sequences (each having 271 3D sequential images) corresponding to five different mouse embryos show promising performances of our methods in terms of nuclear detection, segmentation, and tracking. A detail analysis with a sub-sequence of 101 3D images from an embryo reveals that the proposed method can improve the nuclei detection accuracy by 9 over the previous methods, which used inappropriate large valued parameters. Results also confirm that the proposed method and its variants achieve high detection accuracies ( 98 mean F-measure) irrespective of the large variations of filter parameters and noise levels. PMID:25020042

Tensor voting for image correction by global and local intensity alignment.

PubMed

Jia, Jiaya; Tang, Chi-Keung

2005-01-01

This paper presents a voting method to perform image correction by global and local intensity alignment. The key to our modeless approach is the estimation of global and local replacement functions by reducing the complex estimation problem to the robust 2D tensor voting in the corresponding voting spaces. No complicated model for replacement function (curve) is assumed. Subject to the monotonic constraint only, we vote for an optimal replacement function by propagating the curve smoothness constraint using a dense tensor field. Our method effectively infers missing curve segments and rejects image outliers. Applications using our tensor voting approach are proposed and described. The first application consists of image mosaicking of static scenes, where the voted replacement functions are used in our iterative registration algorithm for computing the best warping matrix. In the presence of occlusion, our replacement function can be employed to construct a visually acceptable mosaic by detecting occlusion which has large and piecewise constant color. Furthermore, by the simultaneous consideration of color matches and spatial constraints in the voting space, we perform image intensity compensation and high contrast image correction using our voting framework, when only two defective input images are given.

Identification of a Recurrent Microdeletion at 17q23.1q23.2 Flanked by Segmental Duplications Associated with Heart Defects and Limb Abnormalities

PubMed Central

Ballif, Blake C.; Theisen, Aaron; Rosenfeld, Jill A.; Traylor, Ryan N.; Gastier-Foster, Julie; Thrush, Devon Lamb; Astbury, Caroline; Bartholomew, Dennis; McBride, Kim L.; Pyatt, Robert E.; Shane, Kate; Smith, Wendy E.; Banks, Valerie; Gallentine, William B.; Brock, Pamela; Rudd, M. Katharine; Adam, Margaret P.; Keene, Julia A.; Phillips, John A.; Pfotenhauer, Jean P.; Gowans, Gordon C.; Stankiewicz, Pawel; Bejjani, Bassem A.; Shaffer, Lisa G.

2010-01-01

Segmental duplications, which comprise ∼5%–10% of the human genome, are known to mediate medically relevant deletions, duplications, and inversions through nonallelic homologous recombination (NAHR) and have been suggested to be hot spots in chromosome evolution and human genomic instability. We report seven individuals with microdeletions at 17q23.1q23.2, identified by microarray-based comparative genomic hybridization (aCGH). Six of the seven deletions are ∼2.2 Mb in size and flanked by large segmental duplications of >98% sequence identity and in the same orientation. One of the deletions is ∼2.8 Mb in size and is flanked on the distal side by a segmental duplication, whereas the proximal breakpoint falls between segmental duplications. These characteristics suggest that NAHR mediated six out of seven of these rearrangements. These individuals have common features, including mild to moderate developmental delay (particularly speech delay), microcephaly, postnatal growth retardation, heart defects, and hand, foot, and limb abnormalities. Although all individuals had at least mild dysmorphic facial features, there was no characteristic constellation of features that would elicit clinical suspicion of a specific disorder. The identification of common clinical features suggests that microdeletions at 17q23.1q23.2 constitute a novel syndrome. Furthermore, the inclusion in the minimal deletion region of TBX2 and TBX4, transcription factors belonging to a family of genes implicated in a variety of developmental pathways including those of heart and limb, suggests that these genes may play an important role in the phenotype of this emerging syndrome. PMID:20206336

Uromodulin retention in thick ascending limb of Henle's loop affects SCD1 in neighboring proximal tubule: renal transcriptome studies in mouse models of uromodulin-associated kidney disease.

PubMed

Horsch, Marion; Beckers, Johannes; Fuchs, Helmut; Gailus-Durner, Valérie; Hrabě de Angelis, Martin; Rathkolb, Birgit; Wolf, Eckhard; Aigner, Bernhard; Kemter, Elisabeth

2014-01-01

Uromodulin-associated kidney disease (UAKD) is a hereditary progressive renal disease which can lead to renal failure and requires renal replacement therapy. UAKD belongs to the endoplasmic reticulum storage diseases due to maturation defect of mutant uromodulin and its retention in the enlarged endoplasmic reticulum in the cells of the thick ascending limb of Henle's loop (TALH). Dysfunction of TALH represents the key pathogenic mechanism of UAKD causing the clinical symptoms of this disease. However, the molecular alterations underlying UAKD are not well understood. In this study, transcriptome profiling of whole kidneys of two mouse models of UAKD, UmodA227T and UmodC93F, was performed. Genes differentially abundant in UAKD affected kidneys of both Umod mutant lines at different disease stages were identified and verified by RT-qPCR. Additionally, differential protein abundances of SCD1 and ANGPTL7 were validated by immunohistochemistry and Western blot analysis. ANGPTL7 expression was down-regulated in TALH cells of Umod mutant mice which is the site of the mutant uromodulin maturation defect. SCD1 was expressed selectively in the S3 segment of proximal tubule cells, and SCD1 abundance was increased in UAKD affected kidneys. This finding demonstrates that a cross talk between two functionally distinct tubular segments of the kidney, the TALH segment and the S3 segment of proximal tubule, exists.

Combination of platelet-rich plasma with degradable bioactive borate glass for segmental bone defect repair.

PubMed

Zhang, Ya-Dong; Wang, Gang; Sun, Yan; Zhang, Chang-Qing

2011-02-01

Porous scaffold biomaterials may offer a clinical alternative to bone grafts; however, scaffolds alone are typically insufficient to heal large bone defects. Numerous studies have demonstrated that osteoinductive growth factor significantly improves bone repair. In this study, a strategy combining degradable bioactive borate glass (BG) scaffolds with platelet-rich plasma (PRP) was tested. The bone defect was filled with BG alone, BG combined with autologous PRP or left empty. Bone formation was analyzed at 4, 8 and 12 weeks using both histology and radiology. The PRP treated group yielded better bone formation than the pure BG scaffold as determined by both histology and microcomputer tomography after 12 weeks. In conclusion, PRP improved bone healing in a diaphyseal rabbit model on BG. The combination of PRP and BG may be an effective approach to repair critical defects.

The fixation effect of a silk fibroin-bacterial cellulose composite plate in segmental defects of the zygomatic arch: an experimental study.

PubMed

Lee, Jung Min; Kim, Ji Heui; Lee, Ok Joo; Park, Chan Hum

2013-06-01

Bioresorbable fixation systems have been popular for the treatment of facial fractures. However, their mechanical properties are uncertain and complications have been reported. To overcome these problems, we developed a bioresorbable fixation plate using a composite of silk fibroin and bacterial cellulose (SF-BC) with biodegradability and increased biocompatibility. To investigate the regenerative effect of the bioresorbable SF-BC fixation plate on zygomatic arch defects in rats. In vivo animal study. The SF-BC composite plate had a tensile strength similar to that of a polylactic acid plate and a tight, pore-free microstructure. Bilateral segmental bone defects (2 mm in length) were created in the zygomatic arches of adult rats. One side was fixed with the SF-BC composite plate, and the other side was left without fixation. Academic research laboratory. Fifteen adult Sprague-Dawley rats. Fixation of the zygomatic arch defect with the SF-BC composite plate. Micro-computed tomography and histological evaluation of bone samples. Gross inspection revealed no specific complication. At 1, 2, 4, and 8 postoperative weeks, the zygomatic arches were explored by micro-computed tomography and histological examination. Control sides did not heal completely and showed bony degeneration and necrosis during the 8-week follow-up. However, we observed new bone formation in sides treated with the SF-BC composite plate, and bony defects were completely healed within 8 weeks. The SF-BC composite plate is a potential candidate for a new bioresorbable fixation system. Our composite material could considerably shorten bone regeneration time. Additional study of the control of biodegradability and mechanical properties of SF-BC composite plates and a comparative study with the resorbable plates currently in use should be undertaken.

CD22ΔE12 as a molecular target for corrective repair using a RNA trans-splicing strategy: Anti-leukemic activity of a rationally designed RNA trans-splicing molecule

PubMed Central

Uckun, Fatih M.; Qazi, Sanjive; Ma, Hong; Reaman, Gregory H.; Mitchell, Lloyd G.

2015-01-01

Our recent studies have demonstrated that the CD22 exon 12 deletion (CD22ΔE12) is a characteristic genetic defect of therapy-refractory clones in pediatric B-precursor acute lymphoblastic leukemia (BPL) and implicated the CD22ΔE12 genetic defect in the aggressive biology of relapsed or therapy-refractory pediatric BPL. The purpose of the present study was to further evaluate the biologic significance of the CD22ΔE12 molecular lesion and determine if it could serve as a molecular target for corrective repair using RNA trans-splicing therapy. We show that both pediatric and adult B-lineage lymphoid malignancies are characterized by a very high incidence of the CD22ΔE12 genetic defect. We provide experimental evidence that the correction of the CD22ΔE12 genetic defect in human CD22ΔE12+ BPL cells using a rationally designed CD22 RNA trans-splicing molecule (RTM) caused a pronounced reduction of their clonogenicity. The RTM-mediated correction replaced the downstream mutation-rich segment of Intron 12 and remaining segments of the mutant CD22 pre-mRNA with wildtype CD22 Exons 10-14, thereby preventing the generation of the cis-spliced aberrant CD22ΔE12 product. The anti-leukemic activity of this RTM against BPL xenograft clones derived from CD22ΔE12+ leukemia patients provides the preclinical proof-of-concept that correcting the CD22ΔE12 defect with rationally designed CD22 RTMs may provide the foundation for therapeutic innovations that are needed for successful treatment of high-risk and relapsed BPL patients. PMID:25567759

Quantitative analysis of hyperpolarized 129Xe ventilation imaging in healthy volunteers and subjects with chronic obstructive pulmonary disease

PubMed Central

Virgincar, Rohan S.; Cleveland, Zackary I.; Kaushik, S. Sivaram; Freeman, Matthew S.; Nouls, John; Cofer, Gary P.; Martinez-Jimenez, Santiago; He, Mu; Kraft, Monica; Wolber, Jan; McAdams, H. Page; Driehuys, Bastiaan

2013-01-01

In this study, hyperpolarized (HP) 129Xe MR ventilation and 1H anatomical images were obtained from 3 subject groups: young healthy volunteers (HV), subjects with chronic obstructive pulmonary disease (COPD), and age-matched control subjects (AMC). Ventilation images were quantified by 2 methods: an expert reader-based ventilation defect score percentage (VDS%) and a semi-automatic segmentation-based ventilation defect percentage (VDP). Reader-based values were assigned by two experienced radiologists and resolved by consensus. In the semi-automatic analysis, 1H anatomical images and 129Xe ventilation images were both segmented following registration, to obtain the thoracic cavity volume (TCV) and ventilated volume (VV), respectively, which were then expressed as a ratio to obtain the VDP. Ventilation images were also characterized by generating signal intensity histograms from voxels within the TCV, and heterogeneity was analyzed using the coefficient of variation (CV). The reader-based VDS% correlated strongly with the semi-automatically generated VDP (r = 0.97, p < 0.0001), and with CV (r = 0.82, p < 0.0001). Both 129Xe ventilation defect scoring metrics readily separated the 3 groups from one another and correlated significantly with FEV1 (VDS%: r = -0.78, p = 0.0002; VDP: r = -0.79, p = 0.0003; CV: r = -0.66, p = 0.0059) and other pulmonary function tests. In the healthy subject groups (HV and AMC), the prevalence of ventilation defects also increased with age (VDS%: r = 0.61, p = 0.0002; VDP: r = 0.63, p = 0.0002). Moreover, ventilation histograms and their associated CVs distinguished between COPD subjects with similar ventilation defect scores but visibly different ventilation patterns. PMID:23065808

Shortest-path constraints for 3D multiobject semiautomatic segmentation via clustering and Graph Cut.

PubMed

Kéchichian, Razmig; Valette, Sébastien; Desvignes, Michel; Prost, Rémy

2013-11-01

We derive shortest-path constraints from graph models of structure adjacency relations and introduce them in a joint centroidal Voronoi image clustering and Graph Cut multiobject semiautomatic segmentation framework. The vicinity prior model thus defined is a piecewise-constant model incurring multiple levels of penalization capturing the spatial configuration of structures in multiobject segmentation. Qualitative and quantitative analyses and comparison with a Potts prior-based approach and our previous contribution on synthetic, simulated, and real medical images show that the vicinity prior allows for the correct segmentation of distinct structures having identical intensity profiles and improves the precision of segmentation boundary placement while being fairly robust to clustering resolution. The clustering approach we take to simplify images prior to segmentation strikes a good balance between boundary adaptivity and cluster compactness criteria furthermore allowing to control the trade-off. Compared with a direct application of segmentation on voxels, the clustering step improves the overall runtime and memory footprint of the segmentation process up to an order of magnitude without compromising the quality of the result.

Semi-automatic segmentation of brain tumors using population and individual information.

PubMed

Wu, Yao; Yang, Wei; Jiang, Jun; Li, Shuanqian; Feng, Qianjin; Chen, Wufan

2013-08-01

Efficient segmentation of tumors in medical images is of great practical importance in early diagnosis and radiation plan. This paper proposes a novel semi-automatic segmentation method based on population and individual statistical information to segment brain tumors in magnetic resonance (MR) images. First, high-dimensional image features are extracted. Neighborhood components analysis is proposed to learn two optimal distance metrics, which contain population and patient-specific information, respectively. The probability of each pixel belonging to the foreground (tumor) and the background is estimated by the k-nearest neighborhood classifier under the learned optimal distance metrics. A cost function for segmentation is constructed through these probabilities and is optimized using graph cuts. Finally, some morphological operations are performed to improve the achieved segmentation results. Our dataset consists of 137 brain MR images, including 68 for training and 69 for testing. The proposed method overcomes segmentation difficulties caused by the uneven gray level distribution of the tumors and even can get satisfactory results if the tumors have fuzzy edges. Experimental results demonstrate that the proposed method is robust to brain tumor segmentation.

Watershed-based segmentation of the corpus callosum in diffusion MRI

NASA Astrophysics Data System (ADS)

Freitas, Pedro; Rittner, Leticia; Appenzeller, Simone; Lapa, Aline; Lotufo, Roberto

2012-02-01

The corpus callosum (CC) is one of the most important white matter structures of the brain, interconnecting the two cerebral hemispheres, and is related to several neurodegenerative diseases. Since segmentation is usually the first step for studies in this structure, and manual volumetric segmentation is a very time-consuming task, it is important to have a robust automatic method for CC segmentation. We propose here an approach for fully automatic 3D segmentation of the CC in the magnetic resonance diffusion tensor images. The method uses the watershed transform and is performed on the fractional anisotropy (FA) map weighted by the projection of the principal eigenvector in the left-right direction. The section of the CC in the midsagittal slice is used as seed for the volumetric segmentation. Experiments with real diffusion MRI data showed that the proposed method is able to quickly segment the CC without any user intervention, with great results when compared to manual segmentation. Since it is simple, fast and does not require parameter settings, the proposed method is well suited for clinical applications.

Automatic segmentation of bones from digital hand radiographs

NASA Astrophysics Data System (ADS)

Liu, Brent J.; Taira, Ricky K.; Shim, Hyeonjoon; Keaton, Patricia

1995-05-01

The purpose of this paper is to develop a robust and accurate method that automatically segments phalangeal and epiphyseal bones from digital pediatric hand radiographs exhibiting various stages of growth. The algorithm uses an object-oriented approach comprising several stages beginning with the most general objects to be segmented, such as the outline of the hand from background, and proceeding in a succession of stages to the most specific object, such as a specific phalangeal bone from a digit of the hand. Each stage carries custom operators unique to the needs of that specific stage which will aid in more accurate results. The method is further aided by a knowledge base where all model contours and other information such as age, race, and sex, are stored. Shape models, 1-D wrist profiles, as well as an interpretation tree are used to map model and data contour segments. Shape analysis is performed using an arc-length orientation transform. The method is tested on close to 340 phalangeal and epiphyseal objects to be segmented from 17 cases of pediatric hand images obtained from our clinical PACS. Patient age ranges from 2 - 16 years. A pediatric radiologist preliminarily assessed the results of the object contours and were found to be accurate to within 95% for cases with non-fused bones and to within 85% for cases with fused bones. With accurate and robust results, the method can be applied toward areas such as the determination of bone age, the development of a normal hand atlas, and the characterization of many congenital and acquired growth diseases. Furthermore, this method's architecture can be applied to other image segmentation problems.

Adaptive local thresholding for robust nucleus segmentation utilizing shape priors

NASA Astrophysics Data System (ADS)

Wang, Xiuzhong; Srinivas, Chukka

2016-03-01

This paper describes a novel local thresholding method for foreground detection. First, a Canny edge detection method is used for initial edge detection. Then, tensor voting is applied on the initial edge pixels, using a nonsymmetric tensor field tailored to encode prior information about nucleus size, shape, and intensity spatial distribution. Tensor analysis is then performed to generate the saliency image and, based on that, the refined edge. Next, the image domain is divided into blocks. In each block, at least one foreground and one background pixel are sampled for each refined edge pixel. The saliency weighted foreground histogram and background histogram are then created. These two histograms are used to calculate a threshold by minimizing the background and foreground pixel classification error. The block-wise thresholds are then used to generate the threshold for each pixel via interpolation. Finally, the foreground is obtained by comparing the original image with the threshold image. The effective use of prior information, combined with robust techniques, results in far more reliable foreground detection, which leads to robust nucleus segmentation.

Food Choice Questionnaire (FCQ) revisited. Suggestions for the development of an enhanced general food motivation model.

PubMed

Fotopoulos, Christos; Krystallis, Athanasios; Vassallo, Marco; Pagiaslis, Anastasios

2009-02-01

Recognising the need for a more statistically robust instrument to investigate general food selection determinants, the research validates and confirms Food Choice Questionnaire (FCQ's) factorial design, develops ad hoc a more robust FCQ version and tests its ability to discriminate between consumer segments in terms of the importance they assign to the FCQ motivational factors. The original FCQ appears to represent a comprehensive and reliable research instrument. However, the empirical data do not support the robustness of its 9-factorial design. On the other hand, segmentation results at the subpopulation level based on the enhanced FCQ version bring about an optimistic message for the FCQ's ability to predict food selection behaviour. The paper concludes that some of the basic components of the original FCQ can be used as a basis for a new general food motivation typology. The development of such a new instrument, with fewer, of higher abstraction FCQ-based dimensions and fewer items per dimension, is a right step forward; yet such a step should be theory-driven, while a rigorous statistical testing across and within population would be necessary.

Automated recognition of quasi-planar ignimbrite sheets and paleo-surfaces via robust segmentation of DTM - examples from the Western Cordillera of the Central Andes

NASA Astrophysics Data System (ADS)

Székely, B.; Karátson, D.; Koma, Zs.; Dorninger, P.; Wörner, G.; Brandmeier, M.; Nothegger, C.

2012-04-01

The Western slope of the Central Andes between 22° and 17°S is characterized by large, quasi-planar landforms with tilted ignimbrite surfaces and overlying younger sedimentary deposits (e.g. Nazca, Oxaya, Huaylillas ignimbrites). These surfaces were only modified by tectonic uplift and tilting of the Western Cordillera preserving minor now fossilized drainage systems. Several deep, canyons started to form from about 5 Ma ago. Due to tectonic oversteepening in a arid region of very low erosion rates, gravitational collapses and landslides additionally modified the Andean slope and valley flanks. Large areas of fossil surfaces, however, remain. The age of these surfaces has been dated between 11 Ma and 25 Ma at elevations of 3500 m in the Precordillera and at c. 1000 m near the coast. Due to their excellent preservation, our aim is to identify, delineate, and reconstruct these original ignimbrite and sediment surfaces via a sophisticated evaluation of SRTM DEMs. The technique we use here is a robust morphological segmentation method that is insensitive to a certain amount of outliers, even if they are spatially correlated. This paves the way to identify common local planar features and combine these into larger areas of a particular surface segment. Erosional dissection and faulting, tilting and folding define subdomains, and thus the original quasi-planar surfaces are modified. Additional processes may create younger surfaces, such as sedimentary floodplains and salt pans. The procedure is tuned to provide a distinction of these features. The technique is based on the evaluation of local normal vectors (perpendicular to the actual surface) that are obtained by determination of locally fitting planes. Then, this initial set of normal vectors are gradually classified into groups with similar properties providing candidate point clouds that are quasi co-planar. The quasi co-planar sets of points are analysed further against other criteria, such as number of minimum points, maximized standard deviation of spatial scatter, maximum point-to-plane surface, etc. SRTM DEMs of selected areas of the Western slope of the Central Andes have been processed with various parameter sets. The resulting domain structure shows strong correlation with tectonic features (e.g. faulting) and younger depositional surfaces whereas other segmentation features appear or disappear depending on parameters of the analysis. For example, a fine segmentation results - for a given study area - in ca. 2500 planar features (of course not all are geologically meaningful), whereas a more meaningful result has an order of magnitude less planes, ca. 270. The latter segmentation still covers the key areas, and the dissecting features (e.g., large incised canyons) are typically identified. For the fine segmentation version an area of 3863 km2 is covered by fitted planes for the ignimbrite surfaces, whereas for the more robust segmentation this area is 2555 km2. The same values for the sedimentary surfaces are 3162 km2 and 2080 km2, respectively. The total processed area was 14498 km2. As the previous numbers and the 18,1% and 18,6% decrease in the coverage suggest, the robust segmentation remains meaningful for large parts of the area while the number of planar features decreased by an order of magnitude. This result also emphasizes the importance of the initial parameters. To verify the results in more detail, residuals (difference between measured and modelled elevation) are also evaluated, and the results are fed back to the segmentation procedure. Steeper landscapes (young volcanic edifices) are clearly separated from higher-order (long-wavelength) structures. This method allows to quantitatively identify uniform surface segments and to relate these to geologically and morphologically meaningful parameters (type of depositional surface, rock type, surface age).

Robust generative asymmetric GMM for brain MR image segmentation.

PubMed

Ji, Zexuan; Xia, Yong; Zheng, Yuhui

2017-11-01

Accurate segmentation of brain tissues from magnetic resonance (MR) images based on the unsupervised statistical models such as Gaussian mixture model (GMM) has been widely studied during last decades. However, most GMM based segmentation methods suffer from limited accuracy due to the influences of noise and intensity inhomogeneity in brain MR images. To further improve the accuracy for brain MR image segmentation, this paper presents a Robust Generative Asymmetric GMM (RGAGMM) for simultaneous brain MR image segmentation and intensity inhomogeneity correction. First, we develop an asymmetric distribution to fit the data shapes, and thus construct a spatial constrained asymmetric model. Then, we incorporate two pseudo-likelihood quantities and bias field estimation into the model's log-likelihood, aiming to exploit the neighboring priors of within-cluster and between-cluster and to alleviate the impact of intensity inhomogeneity, respectively. Finally, an expectation maximization algorithm is derived to iteratively maximize the approximation of the data log-likelihood function to overcome the intensity inhomogeneity in the image and segment the brain MR images simultaneously. To demonstrate the performances of the proposed algorithm, we first applied the proposed algorithm to a synthetic brain MR image to show the intermediate illustrations and the estimated distribution of the proposed algorithm. The next group of experiments is carried out in clinical 3T-weighted brain MR images which contain quite serious intensity inhomogeneity and noise. Then we quantitatively compare our algorithm to state-of-the-art segmentation approaches by using Dice coefficient (DC) on benchmark images obtained from IBSR and BrainWeb with different level of noise and intensity inhomogeneity. The comparison results on various brain MR images demonstrate the superior performances of the proposed algorithm in dealing with the noise and intensity inhomogeneity. In this paper, the RGAGMM algorithm is proposed which can simply and efficiently incorporate spatial constraints into an EM framework to simultaneously segment brain MR images and estimate the intensity inhomogeneity. The proposed algorithm is flexible to fit the data shapes, and can simultaneously overcome the influence of noise and intensity inhomogeneity, and hence is capable of improving over 5% segmentation accuracy comparing with several state-of-the-art algorithms. Copyright © 2017 Elsevier B.V. All rights reserved.

The anterior segment disorder autosomal dominant keratitis is linked to the Aniridia/PAX-6 gene

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

Mirzayans, F.; Pearce, W.G.; Mah, T.S.

1994-09-01

Autosomal dominant keratitis (ADK) is an eye disease characterized by anterior stromal corneal opacification and vascularization in the peripheral cornea. Progression into the central cornea may compromise visual acuity. Other anterior segment features include minimal radial defects of the iris stroma. Posterior segment involvement is characterized by foveal hypoplasia with minimal effect on visual acuity. Aniridia is a second autosomal dominantly inherited ocular disorder defined by structural defects of the iris, frequently severe enough to cause an almost complete absence of iris. This may be accompanied by other anterior segment manifestations, including cataract and keratitis. Posterior segment involvement in aniridiamore » is characterized by foveal hypoplasia resulting in a highly variable impairment of visual acuity, often with nystagmus. Aniridia is usually inherited as an autosomal dominant disease and occurs in 1 in 50,000 to 100,000 people. Aniridia has been shown to result from mutations in PAX-6, a gene thought to regulate fetal eye development. The similar clinical findings in ADK and aniridia, with the similar patterns of inheritance, compelled us to investigate if these two ocular disorders are variants of the same genetic disorder. We have tested for linkage between PAX-6 and ADK within an ADK family with 33 members over four generations, including 11 affected individuals. Linkage studies reveal that D11S914 (located within 3 cM of PAX-6) does not recombine with ADK (LOD score 3.61; {theta} = 0.00), consistent with PAX-6 mutations being responsible for ADK. Direct sequencing of PAX-6 RT-PCR products from ADK patients is underway to identify the mutation within the PAX-6 gene that results in ADK. The linkage of PAX-6 with ADK, along with a recent report that mutations in PAX-6 also underlie Peter`s anomaly, implicates PAX-6 widely in anterior segment malformations.« less

Differences in neural crest sensitivity to ethanol account for the infrequency of anterior segment defects in the eye compared with craniofacial anomalies in a zebrafish model of fetal alcohol syndrome.

PubMed

Eason, Jessica; Williams, Antionette L; Chawla, Bahaar; Apsey, Christian; Bohnsack, Brenda L

2017-09-01

Ethanol (ETOH) exposure during pregnancy is associated with craniofacial and neurologic abnormalities, but infrequently disrupts the anterior segment of the eye. In these studies, we used zebrafish to investigate differences in the teratogenic effect of ETOH on craniofacial, periocular, and ocular neural crest. Zebrafish eye and neural crest development was analyzed by means of live imaging, TUNEL (terminal deoxynucleotidyl transferase dUTP nick end labeling) assay, immunostaining, detection of reactive oxygen species, and in situ hybridization. Our studies demonstrated that foxd3-positive neural crest cells in the periocular mesenchyme and developing eye were less sensitive to ETOH than sox10-positive craniofacial neural crest cells that form the pharyngeal arches and jaw. ETOH increased apoptosis in the retina, but did not affect survival of periocular and ocular neural crest cells. ETOH also did not increase reactive oxygen species within the eye. In contrast, ETOH increased ventral neural crest apoptosis and reactive oxygen species production in the facial mesenchyme. In the eye and craniofacial region, sod2 showed high levels of expression in the anterior segment and in the setting of Sod2 knockdown, low levels of ETOH decreased migration of foxd3-positive neural crest cells into the developing eye. However, ETOH had minimal effect on the periocular and ocular expression of transcription factors (pitx2 and foxc1) that regulate anterior segment development. Neural crest cells contributing to the anterior segment of the eye exhibit increased ability to withstand ETOH-induced oxidative stress and apoptosis. These studies explain the rarity of anterior segment dysgenesis despite the frequent craniofacial abnormalities in fetal alcohol syndrome. Birth Defects Research 109:1212-1227, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Repair of segmental bone defects with bone marrow and BMP-2 adenovirus in the rabbit radius

NASA Astrophysics Data System (ADS)

Cheng, Lijia; Lu, Xiaofeng; Shi, Yujun; Li, Li; Xue, Jing; Zhang, Li; Xia, Jie; Wang, Yujia; Zhang, Xingdong; Bu, Hong

2012-12-01

Bone tissue engineering (BTE) is approached via implantation of autogenous mesenchymal stem cells (MSCs), marrow cells, or platelet-rich plasma, etc. To the contrary, gene therapy combining with the bone marrow (BM) has not been often reported. This study was performed to investigate whether a modified BTE method, that is, the BM and a recombinant human bone morphogenetic protein-2 adenovirus (Ad.hBMP-2) gene administering in hydroxyapatite/β-tricalcium phosphate (HA/β-TCP) ceramics could accelerate the healing of segmental defects in the rabbit radius. In our study, ceramics were immersed in the adenovirus overnight, and half an hour before surgery, autologous BM aspirates were thoroughly mixed with the ceramics; at the same time, a 15-mm radius defect was introduced in the bilateral forelimbs of all animals, after that, this defect was filled with the following: (1) Ad.hBMP-2 + HA/β-TCP + autologous BM (group 1); (2) HA/β-TCP + Ad.hBMP-2 (group 2); (3) HA/β-TCP alone (group 3); (4) an empty defect as a control (group 4). Histological observation and μ-CT analyses were performed on the specimens at weeks 2, 4, 8, and 12, respectively. In group 1, new bone was observed at week 4 and BM appeared at week 12, in groups 2 and 3, new bone was observed at week 8 and it was more mature at week 12, in contrast, the defect was not bridged in group 4 at week 12. The new bone area percentage in group 1 was significantly higher than that in groups 2 and 3. Our study indicated that BM combined with hBMP-2 adenovirus and porous ceramics could significantly increase the amount of newly formed bone. And this modified BTE method thus might have potentials in future clinical application.

Optimal and robust control of quantum state transfer by shaping the spectral phase of ultrafast laser pulses.

PubMed

Guo, Yu; Dong, Daoyi; Shu, Chuan-Cun

2018-04-04

Achieving fast and efficient quantum state transfer is a fundamental task in physics, chemistry and quantum information science. However, the successful implementation of the perfect quantum state transfer also requires robustness under practically inevitable perturbative defects. Here, we demonstrate how an optimal and robust quantum state transfer can be achieved by shaping the spectral phase of an ultrafast laser pulse in the framework of frequency domain quantum optimal control theory. Our numerical simulations of the single dibenzoterrylene molecule as well as in atomic rubidium show that optimal and robust quantum state transfer via spectral phase modulated laser pulses can be achieved by incorporating a filtering function of the frequency into the optimization algorithm, which in turn has potential applications for ultrafast robust control of photochemical reactions.

Patient-specific and global convolutional neural networks for robust automatic liver tumor delineation in follow-up CT studies.

PubMed

Vivanti, Refael; Joskowicz, Leo; Lev-Cohain, Naama; Ephrat, Ariel; Sosna, Jacob

2018-03-10

Radiological longitudinal follow-up of tumors in CT scans is essential for disease assessment and liver tumor therapy. Currently, most tumor size measurements follow the RECIST guidelines, which can be off by as much as 50%. True volumetric measurements are more accurate but require manual delineation, which is time-consuming and user-dependent. We present a convolutional neural networks (CNN) based method for robust automatic liver tumor delineation in longitudinal CT studies that uses both global and patient specific CNNs trained on a small database of delineated images. The inputs are the baseline scan and the tumor delineation, a follow-up scan, and a liver tumor global CNN voxel classifier built from radiologist-validated liver tumor delineations. The outputs are the tumor delineations in the follow-up CT scan. The baseline scan tumor delineation serves as a high-quality prior for the tumor characterization in the follow-up scans. It is used to evaluate the global CNN performance on the new case and to reliably predict failures of the global CNN on the follow-up scan. High-scoring cases are segmented with a global CNN; low-scoring cases, which are predicted to be failures of the global CNN, are segmented with a patient-specific CNN built from the baseline scan. Our experimental results on 222 tumors from 31 patients yield an average overlap error of 17% (std = 11.2) and surface distance of 2.1 mm (std = 1.8), far better than stand-alone segmentation. Importantly, the robustness of our method improved from 67% for stand-alone global CNN segmentation to 100%. Unlike other medical imaging deep learning approaches, which require large annotated training datasets, our method exploits the follow-up framework to yield accurate tumor tracking and failure detection and correction with a small training dataset. Graphical abstract Flow diagram of the proposed method. In the offline mode (orange), a global CNN is trained as a voxel classifier to segment liver tumor as in [31]. The online mode (blue) is used for each new case. The input is baseline scan with delineation and the follow-up CT scan to be segmented. The main novelty is the ability to predict failures by trying the system on the baseline scan and the ability to correct them using the patient-specific CNN.

Graph run-length matrices for histopathological image segmentation.

PubMed

Tosun, Akif Burak; Gunduz-Demir, Cigdem

2011-03-01

The histopathological examination of tissue specimens is essential for cancer diagnosis and grading. However, this examination is subject to a considerable amount of observer variability as it mainly relies on visual interpretation of pathologists. To alleviate this problem, it is very important to develop computational quantitative tools, for which image segmentation constitutes the core step. In this paper, we introduce an effective and robust algorithm for the segmentation of histopathological tissue images. This algorithm incorporates the background knowledge of the tissue organization into segmentation. For this purpose, it quantifies spatial relations of cytological tissue components by constructing a graph and uses this graph to define new texture features for image segmentation. This new texture definition makes use of the idea of gray-level run-length matrices. However, it considers the runs of cytological components on a graph to form a matrix, instead of considering the runs of pixel intensities. Working with colon tissue images, our experiments demonstrate that the texture features extracted from "graph run-length matrices" lead to high segmentation accuracies, also providing a reasonable number of segmented regions. Compared with four other segmentation algorithms, the results show that the proposed algorithm is more effective in histopathological image segmentation.

Graph-based surface reconstruction from stereo pairs using image segmentation

NASA Astrophysics Data System (ADS)

Bleyer, Michael; Gelautz, Margrit

2005-01-01

This paper describes a novel stereo matching algorithm for epipolar rectified images. The method applies colour segmentation on the reference image. The use of segmentation makes the algorithm capable of handling large untextured regions, estimating precise depth boundaries and propagating disparity information to occluded regions, which are challenging tasks for conventional stereo methods. We model disparity inside a segment by a planar equation. Initial disparity segments are clustered to form a set of disparity layers, which are planar surfaces that are likely to occur in the scene. Assignments of segments to disparity layers are then derived by minimization of a global cost function via a robust optimization technique that employs graph cuts. The cost function is defined on the pixel level, as well as on the segment level. While the pixel level measures the data similarity based on the current disparity map and detects occlusions symmetrically in both views, the segment level propagates the segmentation information and incorporates a smoothness term. New planar models are then generated based on the disparity layers' spatial extents. Results obtained for benchmark and self-recorded image pairs indicate that the proposed method is able to compete with the best-performing state-of-the-art algorithms.

Segmentation of the Clustered Cells with Optimized Boundary Detection in Negative Phase Contrast Images

PubMed Central

Wang, Yuliang; Zhang, Zaicheng; Wang, Huimin; Bi, Shusheng

2015-01-01

Cell image segmentation plays a central role in numerous biology studies and clinical applications. As a result, the development of cell image segmentation algorithms with high robustness and accuracy is attracting more and more attention. In this study, an automated cell image segmentation algorithm is developed to get improved cell image segmentation with respect to cell boundary detection and segmentation of the clustered cells for all cells in the field of view in negative phase contrast images. A new method which combines the thresholding method and edge based active contour method was proposed to optimize cell boundary detection. In order to segment clustered cells, the geographic peaks of cell light intensity were utilized to detect numbers and locations of the clustered cells. In this paper, the working principles of the algorithms are described. The influence of parameters in cell boundary detection and the selection of the threshold value on the final segmentation results are investigated. At last, the proposed algorithm is applied to the negative phase contrast images from different experiments. The performance of the proposed method is evaluated. Results show that the proposed method can achieve optimized cell boundary detection and highly accurate segmentation for clustered cells. PMID:26066315

Laboratory demonstration of an optical vortex mask coronagraph using photonic crystal

NASA Astrophysics Data System (ADS)

Murakami, N.; Baba, N.; Ise, A.; Sakamoto, M.; Oka, K.

2010-10-01

Photonic crystal, artificial periodic nanostructure, is an attractive device for constructing focal-plane phase-mask coronagraphs such as segmented phase masks (four-quadrant, eight-octant, and 4N-segmented ones) and an optical vortex mask (OVM), because of its extremely small manufacturing defect. Recently, speckle-noise limited contrast has been demonstrated for two monochromatic lasers by using the eight-octant phase-mask made of the photonic crystal (Murakami et al. 2010, ApJ, 714, 772). We applied the photonic-crystal device to the OVM coronagraph. The OVM is more advantageous over the segmented phase masks because it does not have discontinuities other than a central singular point and provides a full on-sky field of view. For generating an achromatic optical vortex, we manufactured an axially-symmetric half-wave plate (ASHWP). It is expected that a size of the manufacturing defect due to the central singularity is an order of several hundreds nanometers. The ASHWP is placed between two circular polarizers for modulating a Pancharatnam phase. A continuous spiral phase modulation is then implemented achromatically. We carried out preliminary laboratory demonstration of the OVM coronagraph using two monochromatic lasers as a model star (wavelengths of 532 nm and 633 nm). We report a principle of the achromatic optical-vortex generation, and results of the laboratory demonstration of the OVM coronagraph.

High frequency QRS ECG predicts ischemic defects during myocardial perfusion imaging

NASA Technical Reports Server (NTRS)

2004-01-01

Changes in high frequency QRS components of the electrocardiogram (HF QRS ECG) (150-250 Hz) are more sensitive than changes in conventional ST segments for detecting myocardial ischemia. We investigated the accuracy of 12-lead HF QRS ECG in detecting ischemia during adenosine tetrofosmin myocardial perfusion imaging (MPI). 12-lead HF QRS ECG recordings were obtained from 45 patients before and during adenosine technetium-99 tetrofosmin MPI tests. Before the adenosine infusions, recordings of HF QRS were analyzed according to a morphological score that incorporated the number, type and location of reduced amplitude zones (RAZs) present in the 12 leads. During the adenosine infusions, recordings of HF QRS were analyzed according to the maximum percentage changes (in both the positive and negative directions) that occurred in root mean square (RMS) voltage amplitudes within the 12 leads. The best set of prospective HF QRS criteria had a sensitivity of 94% and a specificity of 83% for correctly identifying the MPI result. The sensitivity of simultaneous ST segment changes (18%) was significantly lower than that of any individual HF QRS criterion (P less than 0.00l). Analysis of 12-lead HF QRS ECG is highly sensitive and specific for detecting ischemic perfusion defects during adenosine MPI stress tests and significantly more sensitive than analysis of conventional ST segments.

High frequency QRS ECG predicts ischemic defects during myocardial perfusion imaging

NASA Technical Reports Server (NTRS)

Rahman, Atiar

2006-01-01

Background: Changes in high frequency QRS components of the electrocardiogram (HF QRS ECG) (150-250 Hz) are more sensitive than changes in conventional ST segments for detecting myocardial ischemia. We investigated the accuracy of 12-lead HF QRS ECG in detecting ischemia during adenosine tetrofosmin myocardial perfusion imaging (MPI). Methods and Results: 12-lead HF QRS ECG recordings were obtained from 45 patients before and during adenosine technetium-99 tetrofosmin MPI tests. Before the adenosine infusions, recordings of HF QRS were analyzed according to a morphological score that incorporated the number, type and location of reduced amplitude zones (RAZs) present in the 12 leads. During the adenosine infusions, recordings of HF QRS were analyzed according to the maximum percentage changes (in both the positive and negative directions) that occurred in root mean square (RMS) voltage amplitudes within the 12 leads. The best set of prospective HF QRS criteria had a sensitivity of 94% and a specificity of 83% for correctly identifying the MPI result. The sensitivity of simultaneous ST segment changes (18%) was significantly lower than that of any individual HF QRS criterion (P<0.001). Conclusions: Analysis of 12-lead HF QRS ECG is highly sensitive and specific for detecting ischemic perfusion defects during adenosine MPI stress tests and significantly more sensitive than analysis of conventional ST segments.

SEGMENTING CT PROSTATE IMAGES USING POPULATION AND PATIENT-SPECIFIC STATISTICS FOR RADIOTHERAPY.

PubMed

Feng, Qianjin; Foskey, Mark; Tang, Songyuan; Chen, Wufan; Shen, Dinggang

2009-08-07

This paper presents a new deformable model using both population and patient-specific statistics to segment the prostate from CT images. There are two novelties in the proposed method. First, a modified scale invariant feature transform (SIFT) local descriptor, which is more distinctive than general intensity and gradient features, is used to characterize the image features. Second, an online training approach is used to build the shape statistics for accurately capturing intra-patient variation, which is more important than inter-patient variation for prostate segmentation in clinical radiotherapy. Experimental results show that the proposed method is robust and accurate, suitable for clinical application.

SEGMENTING CT PROSTATE IMAGES USING POPULATION AND PATIENT-SPECIFIC STATISTICS FOR RADIOTHERAPY

PubMed Central

Feng, Qianjin; Foskey, Mark; Tang, Songyuan; Chen, Wufan; Shen, Dinggang

2010-01-01

This paper presents a new deformable model using both population and patient-specific statistics to segment the prostate from CT images. There are two novelties in the proposed method. First, a modified scale invariant feature transform (SIFT) local descriptor, which is more distinctive than general intensity and gradient features, is used to characterize the image features. Second, an online training approach is used to build the shape statistics for accurately capturing intra-patient variation, which is more important than inter-patient variation for prostate segmentation in clinical radiotherapy. Experimental results show that the proposed method is robust and accurate, suitable for clinical application. PMID:21197416

Automatic segmentation of cortical vessels in pre- and post-tumor resection laser range scan images

NASA Astrophysics Data System (ADS)

Ding, Siyi; Miga, Michael I.; Thompson, Reid C.; Garg, Ishita; Dawant, Benoit M.

2009-02-01

Measurement of intra-operative cortical brain movement is necessary to drive mechanical models developed to predict sub-cortical shift. At our institution, this is done with a tracked laser range scanner. This device acquires both 3D range data and 2D photographic images. 3D cortical brain movement can be estimated if 2D photographic images acquired over time can be registered. Previously, we have developed a method, which permits this registration using vessels visible in the images. But, vessel segmentation required the localization of starting and ending points for each vessel segment. Here, we propose a method, which automates the segmentation process further. This method involves several steps: (1) correction of lighting artifacts, (2) vessel enhancement, and (3) vessels' centerline extraction. Result obtained on 5 images obtained in the operating room suggests that our method is robust and is able to segment vessels reliably.

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.

Consistency functional map propagation for repetitive patterns

NASA Astrophysics Data System (ADS)

Wang, Hao

2017-09-01

Repetitive patterns appear frequently in both man-made and natural environments. Automatically and robustly detecting such patterns from an image is a challenging problem. We study repetitive pattern alignment by embedding segmentation cue with a functional map model. However, this model cannot tackle the repetitive patterns directly due to the large photometric and geometric variations. Thus, a consistency functional map propagation (CFMP) algorithm that extends the functional map with dynamic propagation is proposed to address this issue. This propagation model is acquired in two steps. The first one aligns the patterns from a local region, transferring segmentation functions among patterns. It can be cast as an L norm optimization problem. The latter step updates the template segmentation for the next round of pattern discovery by merging the transferred segmentation functions. Extensive experiments and comparative analyses have demonstrated an encouraging performance of the proposed algorithm in detection and segmentation of repetitive patterns.

Robust Nucleus/Cell Detection and Segmentation in Digital Pathology and Microscopy Images: A Comprehensive Review.

PubMed

Xing, Fuyong; Yang, Lin

2016-01-01

Digital pathology and microscopy image analysis is widely used for comprehensive studies of cell morphology or tissue structure. Manual assessment is labor intensive and prone to interobserver variations. Computer-aided methods, which can significantly improve the objectivity and reproducibility, have attracted a great deal of interest in recent literature. Among the pipeline of building a computer-aided diagnosis system, nucleus or cell detection and segmentation play a very important role to describe the molecular morphological information. In the past few decades, many efforts have been devoted to automated nucleus/cell detection and segmentation. In this review, we provide a comprehensive summary of the recent state-of-the-art nucleus/cell segmentation approaches on different types of microscopy images including bright-field, phase-contrast, differential interference contrast, fluorescence, and electron microscopies. In addition, we discuss the challenges for the current methods and the potential future work of nucleus/cell detection and segmentation.

One-stage reconstruction of the complex midfoot defect with a multiple osteotomized free fibular osteocutaneous flap: case report and literature review.

PubMed

Lykoudis, Efstathios G; Dimitrios, Pafilas; Alexandros, Beris E

2010-01-01

Complex midfoot defects represent a reconstructive challenge since midfoot plays a key role in standing and gait. We report the case of a 27-year-old patient with a complex midfoot defect due to a high-energy gun shot injury. The defect included the tarsometatarsal complex, all three arches of the foot, and the overlying dorsal skin of the foot. Reconstruction was achieved in a single stage with a free fibular osteocutaneous flap. The fibula was osteotomized into three segments, which were used to reconstruct the bone defects, while the skin paddle of the flap was used for stable soft tissue coverage of the reconstructed bony skeleton. Early and late postoperative periods were uneventful. Bone incorporation was radiographically evident at 12 weeks, and full weight bearing was possible at 6 months postop. Final follow up, at 2 years postop, showed a very good functional and esthetic outcome.

TU-F-BRF-06: 3D Pancreas MRI Segmentation Using Dictionary Learning and Manifold Clustering

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

Gou, S; Rapacchi, S; Hu, P

2014-06-15

Purpose: The recent advent of MRI guided radiotherapy machines has lent an exciting platform for soft tissue target localization during treatment. However, tools to efficiently utilize MRI images for such purpose have not been developed. Specifically, to efficiently quantify the organ motion, we develop an automated segmentation method using dictionary learning and manifold clustering (DLMC). Methods: Fast 3D HASTE and VIBE MR images of 2 healthy volunteers and 3 patients were acquired. A bounding box was defined to include pancreas and surrounding normal organs including the liver, duodenum and stomach. The first slice of the MRI was used for dictionarymore » learning based on mean-shift clustering and K-SVD sparse representation. Subsequent images were iteratively reconstructed until the error is less than a preset threshold. The preliminarily segmentation was subject to the constraints of manifold clustering. The segmentation results were compared with the mean shift merging (MSM), level set (LS) and manual segmentation methods. Results: DLMC resulted in consistently higher accuracy and robustness than comparing methods. Using manual contours as the ground truth, the mean Dices indices for all subjects are 0.54, 0.56 and 0.67 for MSM, LS and DLMC, respectively based on the HASTE image. The mean Dices indices are 0.70, 0.77 and 0.79 for the three methods based on VIBE images. DLMC is clearly more robust on the patients with the diseased pancreas while LS and MSM tend to over-segment the pancreas. DLMC also achieved higher sensitivity (0.80) and specificity (0.99) combining both imaging techniques. LS achieved equivalent sensitivity on VIBE images but was more computationally inefficient. Conclusion: We showed that pancreas and surrounding normal organs can be reliably segmented based on fast MRI using DLMC. This method will facilitate both planning volume definition and imaging guidance during treatment.« less

Robust electromagnetic absorption by graphene/polymer heterostructures

NASA Astrophysics Data System (ADS)

Lobet, Michaël; Reckinger, Nicolas; Henrard, Luc; Lambin, Philippe

2015-07-01

Polymer/graphene heterostructures present good shielding efficiency against GHz electromagnetic perturbations. Theory and experiments demonstrate that there is an optimum number of graphene planes, separated by thin polymer spacers, leading to maximum absorption for millimeter waves Batrakov et al (2014 Sci. Rep. 4 7191). Here, electrodynamics of ideal polymer/graphene multilayered material is first approached with a well-adapted continued-fraction formalism. In a second stage, rigorous coupled wave analysis is used to account for the presence of defects in graphene that are typical of samples produced by chemical vapor deposition, namely microscopic holes, microscopic dots (embryos of a second layer) and grain boundaries. It is shown that the optimum absorbance of graphene/polymer multilayers does not weaken to the first order in defect concentration. This finding testifies to the robustness of the shielding efficiency of the proposed absorption device.

Fault tolerant control based on interval type-2 fuzzy sliding mode controller for coaxial trirotor aircraft.

PubMed

Zeghlache, Samir; Kara, Kamel; Saigaa, Djamel

2015-11-01

In this paper, a robust controller for a Six Degrees of Freedom (6 DOF) coaxial trirotor helicopter control is proposed in presence of defects in the system. A control strategy based on the coupling of the interval type-2 fuzzy logic control and sliding mode control technique are used to design a controller. The main purpose of this work is to eliminate the chattering phenomenon and guaranteeing the stability and the robustness of the system. In order to achieve this goal, interval type-2 fuzzy logic control has been used to generate the discontinuous control signal. The simulation results have shown that the proposed control strategy can greatly alleviate the chattering effect, and perform good reference tracking in presence of defects in the system. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

[Plaque segmentation of intracoronary optical coherence tomography images based on K-means and improved random walk algorithm].

PubMed

Wang, Guanglei; Wang, Pengyu; Han, Yechen; Liu, Xiuling; Li, Yan; Lu, Qian

2017-06-01

In recent years, optical coherence tomography (OCT) has developed into a popular coronary imaging technology at home and abroad. The segmentation of plaque regions in coronary OCT images has great significance for vulnerable plaque recognition and research. In this paper, a new algorithm based on K -means clustering and improved random walk is proposed and Semi-automated segmentation of calcified plaque, fibrotic plaque and lipid pool was achieved. And the weight function of random walk is improved. The distance between the edges of pixels in the image and the seed points is added to the definition of the weight function. It increases the weak edge weights and prevent over-segmentation. Based on the above methods, the OCT images of 9 coronary atherosclerotic patients were selected for plaque segmentation. By contrasting the doctor's manual segmentation results with this method, it was proved that this method had good robustness and accuracy. It is hoped that this method can be helpful for the clinical diagnosis of coronary heart disease.

[RSF model optimization and its application to brain tumor segmentation in MRI].

PubMed

Cheng, Zhaoning; Song, Zhijian

2013-04-01

Magnetic resonance imaging (MRI) is usually obscure and non-uniform in gray, and the tumors inside are poorly circumscribed, hence the automatic tumor segmentation in MRI is very difficult. Region-scalable fitting (RSF) energy model is a new segmentation approach for some uneven grayscale images. However, the level set formulation (LSF) of RSF model is not suitable for the environment with different grey level distribution inside and outside the intial contour, and the complex intensity environment of MRI always makes it hard to get ideal segmentation results. Therefore, we improved the model by a new LSF and combined it with the mean shift method, which can be helpful for tumor segmentation and has better convergence and target direction. The proposed method has been utilized in a series of studies for real MRI images, and the results showed that it could realize fast, accurate and robust segmentations for brain tumors in MRI, which has great clinical significance.

TuMore: generation of synthetic brain tumor MRI data for deep learning based segmentation approaches

NASA Astrophysics Data System (ADS)

Lindner, Lydia; Pfarrkirchner, Birgit; Gsaxner, Christina; Schmalstieg, Dieter; Egger, Jan

2018-03-01

Accurate segmentation and measurement of brain tumors plays an important role in clinical practice and research, as it is critical for treatment planning and monitoring of tumor growth. However, brain tumor segmentation is one of the most challenging tasks in medical image analysis. Since manual segmentations are subjective, time consuming and neither accurate nor reliable, there exists a need for objective, robust and fast automated segmentation methods that provide competitive performance. Therefore, deep learning based approaches are gaining interest in the field of medical image segmentation. When the training data set is large enough, deep learning approaches can be extremely effective, but in domains like medicine, only limited data is available in the majority of cases. Due to this reason, we propose a method that allows to create a large dataset of brain MRI (Magnetic Resonance Imaging) images containing synthetic brain tumors - glioblastomas more specifically - and the corresponding ground truth, that can be subsequently used to train deep neural networks.

Mean curvature and texture constrained composite weighted random walk algorithm for optic disc segmentation towards glaucoma screening.

PubMed

Panda, Rashmi; Puhan, N B; Panda, Ganapati

2018-02-01

Accurate optic disc (OD) segmentation is an important step in obtaining cup-to-disc ratio-based glaucoma screening using fundus imaging. It is a challenging task because of the subtle OD boundary, blood vessel occlusion and intensity inhomogeneity. In this Letter, the authors propose an improved version of the random walk algorithm for OD segmentation to tackle such challenges. The algorithm incorporates the mean curvature and Gabor texture energy features to define the new composite weight function to compute the edge weights. Unlike the deformable model-based OD segmentation techniques, the proposed algorithm remains unaffected by curve initialisation and local energy minima problem. The effectiveness of the proposed method is verified with DRIVE, DIARETDB1, DRISHTI-GS and MESSIDOR database images using the performance measures such as mean absolute distance, overlapping ratio, dice coefficient, sensitivity, specificity and precision. The obtained OD segmentation results and quantitative performance measures show robustness and superiority of the proposed algorithm in handling the complex challenges in OD segmentation.

Modeling heading and path perception from optic flow in the case of independently moving objects

PubMed Central

Raudies, Florian; Neumann, Heiko

2013-01-01

Humans are usually accurate when estimating heading or path from optic flow, even in the presence of independently moving objects (IMOs) in an otherwise rigid scene. To invoke significant biases in perceived heading, IMOs have to be large and obscure the focus of expansion (FOE) in the image plane, which is the point of approach. For the estimation of path during curvilinear self-motion no significant biases were found in the presence of IMOs. What makes humans robust in their estimation of heading or path using optic flow? We derive analytical models of optic flow for linear and curvilinear self-motion using geometric scene models. Heading biases of a linear least squares method, which builds upon these analytical models, are large, larger than those reported for humans. This motivated us to study segmentation cues that are available from optic flow. We derive models of accretion/deletion, expansion/contraction, acceleration/deceleration, local spatial curvature, and local temporal curvature, to be used as cues to segment an IMO from the background. Integrating these segmentation cues into our method of estimating heading or path now explains human psychophysical data and extends, as well as unifies, previous investigations. Our analysis suggests that various cues available from optic flow help to segment IMOs and, thus, make humans' heading and path perception robust in the presence of such IMOs. PMID:23554589

An automated, high-throughput plant phenotyping system using machine learning-based plant segmentation and image analysis.

PubMed

Lee, Unseok; Chang, Sungyul; Putra, Gian Anantrio; Kim, Hyoungseok; Kim, Dong Hwan

2018-01-01

A high-throughput plant phenotyping system automatically observes and grows many plant samples. Many plant sample images are acquired by the system to determine the characteristics of the plants (populations). Stable image acquisition and processing is very important to accurately determine the characteristics. However, hardware for acquiring plant images rapidly and stably, while minimizing plant stress, is lacking. Moreover, most software cannot adequately handle large-scale plant imaging. To address these problems, we developed a new, automated, high-throughput plant phenotyping system using simple and robust hardware, and an automated plant-imaging-analysis pipeline consisting of machine-learning-based plant segmentation. Our hardware acquires images reliably and quickly and minimizes plant stress. Furthermore, the images are processed automatically. In particular, large-scale plant-image datasets can be segmented precisely using a classifier developed using a superpixel-based machine-learning algorithm (Random Forest), and variations in plant parameters (such as area) over time can be assessed using the segmented images. We performed comparative evaluations to identify an appropriate learning algorithm for our proposed system, and tested three robust learning algorithms. We developed not only an automatic analysis pipeline but also a convenient means of plant-growth analysis that provides a learning data interface and visualization of plant growth trends. Thus, our system allows end-users such as plant biologists to analyze plant growth via large-scale plant image data easily.

BEaST: brain extraction based on nonlocal segmentation technique.

PubMed

Eskildsen, Simon F; Coupé, Pierrick; Fonov, Vladimir; Manjón, José V; Leung, Kelvin K; Guizard, Nicolas; Wassef, Shafik N; Østergaard, Lasse Riis; Collins, D Louis

2012-02-01

Brain extraction is an important step in the analysis of brain images. The variability in brain morphology and the difference in intensity characteristics due to imaging sequences make the development of a general purpose brain extraction algorithm challenging. To address this issue, we propose a new robust method (BEaST) dedicated to produce consistent and accurate brain extraction. This method is based on nonlocal segmentation embedded in a multi-resolution framework. A library of 80 priors is semi-automatically constructed from the NIH-sponsored MRI study of normal brain development, the International Consortium for Brain Mapping, and the Alzheimer's Disease Neuroimaging Initiative databases. In testing, a mean Dice similarity coefficient of 0.9834±0.0053 was obtained when performing leave-one-out cross validation selecting only 20 priors from the library. Validation using the online Segmentation Validation Engine resulted in a top ranking position with a mean Dice coefficient of 0.9781±0.0047. Robustness of BEaST is demonstrated on all baseline ADNI data, resulting in a very low failure rate. The segmentation accuracy of the method is better than two widely used publicly available methods and recent state-of-the-art hybrid approaches. BEaST provides results comparable to a recent label fusion approach, while being 40 times faster and requiring a much smaller library of priors. Copyright © 2011 Elsevier Inc. All rights reserved.

Step-by-Step Technique for Segmental Reconstruction of Reverse Hill-Sachs Lesions Using Homologous Osteochondral Allograft.

PubMed

Alkaduhimi, Hassanin; van den Bekerom, Michel P J; van Deurzen, Derek F P

2017-06-01

Posterior shoulder dislocations are accompanied by high forces and can result in an anteromedial humeral head impression fracture called a reverse Hill-Sachs lesion. This reverse Hill-Sachs lesion can result in serious complications including posttraumatic osteoarthritis, posterior dislocations, osteonecrosis, persistent joint stiffness, and loss of shoulder function. Treatment is challenging and depends on the amount of bone loss. Several techniques have been reported to describe the surgical treatment of lesions larger than 20%. However, there is still limited evidence with regard to the optimal procedure. Favorable results have been reported by performing segmental reconstruction of the reverse Hill-Sachs lesion with bone allograft. Although the procedure of segmental reconstruction has been used in several studies, its technique has not yet been well described in detail. In this report we propose a step-by-step description of the technique how to perform a segmental reconstruction of a reverse Hill-Sachs defect.

Tumor-Cut: segmentation of brain tumors on contrast enhanced MR images for radiosurgery applications.

PubMed

Hamamci, Andac; Kucuk, Nadir; Karaman, Kutlay; Engin, Kayihan; Unal, Gozde

2012-03-01

In this paper, we present a fast and robust practical tool for segmentation of solid tumors with minimal user interaction to assist clinicians and researchers in radiosurgery planning and assessment of the response to the therapy. Particularly, a cellular automata (CA) based seeded tumor segmentation method on contrast enhanced T1 weighted magnetic resonance (MR) images, which standardizes the volume of interest (VOI) and seed selection, is proposed. First, we establish the connection of the CA-based segmentation to the graph-theoretic methods to show that the iterative CA framework solves the shortest path problem. In that regard, we modify the state transition function of the CA to calculate the exact shortest path solution. Furthermore, a sensitivity parameter is introduced to adapt to the heterogeneous tumor segmentation problem, and an implicit level set surface is evolved on a tumor probability map constructed from CA states to impose spatial smoothness. Sufficient information to initialize the algorithm is gathered from the user simply by a line drawn on the maximum diameter of the tumor, in line with the clinical practice. Furthermore, an algorithm based on CA is presented to differentiate necrotic and enhancing tumor tissue content, which gains importance for a detailed assessment of radiation therapy response. Validation studies on both clinical and synthetic brain tumor datasets demonstrate 80%-90% overlap performance of the proposed algorithm with an emphasis on less sensitivity to seed initialization, robustness with respect to different and heterogeneous tumor types, and its efficiency in terms of computation time.

Automatic training and reliability estimation for 3D ASM applied to cardiac MRI segmentation

NASA Astrophysics Data System (ADS)

Tobon-Gomez, Catalina; Sukno, Federico M.; Butakoff, Constantine; Huguet, Marina; Frangi, Alejandro F.

2012-07-01

Training active shape models requires collecting manual ground-truth meshes in a large image database. While shape information can be reused across multiple imaging modalities, intensity information needs to be imaging modality and protocol specific. In this context, this study has two main purposes: (1) to test the potential of using intensity models learned from MRI simulated datasets and (2) to test the potential of including a measure of reliability during the matching process to increase robustness. We used a population of 400 virtual subjects (XCAT phantom), and two clinical populations of 40 and 45 subjects. Virtual subjects were used to generate simulated datasets (MRISIM simulator). Intensity models were trained both on simulated and real datasets. The trained models were used to segment the left ventricle (LV) and right ventricle (RV) from real datasets. Segmentations were also obtained with and without reliability information. Performance was evaluated with point-to-surface and volume errors. Simulated intensity models obtained average accuracy comparable to inter-observer variability for LV segmentation. The inclusion of reliability information reduced volume errors in hypertrophic patients (EF errors from 17 ± 57% to 10 ± 18% LV MASS errors from -27 ± 22 g to -14 ± 25 g), and in heart failure patients (EF errors from -8 ± 42% to -5 ± 14%). The RV model of the simulated images needs further improvement to better resemble image intensities around the myocardial edges. Both for real and simulated models, reliability information increased segmentation robustness without penalizing accuracy.

Automatic training and reliability estimation for 3D ASM applied to cardiac MRI segmentation.

PubMed

Tobon-Gomez, Catalina; Sukno, Federico M; Butakoff, Constantine; Huguet, Marina; Frangi, Alejandro F

2012-07-07

Training active shape models requires collecting manual ground-truth meshes in a large image database. While shape information can be reused across multiple imaging modalities, intensity information needs to be imaging modality and protocol specific. In this context, this study has two main purposes: (1) to test the potential of using intensity models learned from MRI simulated datasets and (2) to test the potential of including a measure of reliability during the matching process to increase robustness. We used a population of 400 virtual subjects (XCAT phantom), and two clinical populations of 40 and 45 subjects. Virtual subjects were used to generate simulated datasets (MRISIM simulator). Intensity models were trained both on simulated and real datasets. The trained models were used to segment the left ventricle (LV) and right ventricle (RV) from real datasets. Segmentations were also obtained with and without reliability information. Performance was evaluated with point-to-surface and volume errors. Simulated intensity models obtained average accuracy comparable to inter-observer variability for LV segmentation. The inclusion of reliability information reduced volume errors in hypertrophic patients (EF errors from 17 ± 57% to 10 ± 18%; LV MASS errors from -27 ± 22 g to -14 ± 25 g), and in heart failure patients (EF errors from -8 ± 42% to -5 ± 14%). The RV model of the simulated images needs further improvement to better resemble image intensities around the myocardial edges. Both for real and simulated models, reliability information increased segmentation robustness without penalizing accuracy.

Fully automated prostate segmentation in 3D MR based on normalized gradient fields cross-correlation initialization and LOGISMOS refinement

NASA Astrophysics Data System (ADS)

Yin, Yin; Fotin, Sergei V.; Periaswamy, Senthil; Kunz, Justin; Haldankar, Hrishikesh; Muradyan, Naira; Cornud, François; Turkbey, Baris; Choyke, Peter

2012-02-01

Manual delineation of the prostate is a challenging task for a clinician due to its complex and irregular shape. Furthermore, the need for precisely targeting the prostate boundary continues to grow. Planning for radiation therapy, MR-ultrasound fusion for image-guided biopsy, multi-parametric MRI tissue characterization, and context-based organ retrieval are examples where accurate prostate delineation can play a critical role in a successful patient outcome. Therefore, a robust automated full prostate segmentation system is desired. In this paper, we present an automated prostate segmentation system for 3D MR images. In this system, the prostate is segmented in two steps: the prostate displacement and size are first detected, and then the boundary is refined by a shape model. The detection approach is based on normalized gradient fields cross-correlation. This approach is fast, robust to intensity variation and provides good accuracy to initialize a prostate mean shape model. The refinement model is based on a graph-search based framework, which contains both shape and topology information during deformation. We generated the graph cost using trained classifiers and used coarse-to-fine search and region-specific classifier training. The proposed algorithm was developed using 261 training images and tested on another 290 cases. The segmentation performance using mean DSC ranging from 0.89 to 0.91 depending on the evaluation subset demonstrates state of the art performance. Running time for the system is about 20 to 40 seconds depending on image size and resolution.

Multi scales based sparse matrix spectral clustering image segmentation

NASA Astrophysics Data System (ADS)

Liu, Zhongmin; Chen, Zhicai; Li, Zhanming; Hu, Wenjin

2018-04-01

In image segmentation, spectral clustering algorithms have to adopt the appropriate scaling parameter to calculate the similarity matrix between the pixels, which may have a great impact on the clustering result. Moreover, when the number of data instance is large, computational complexity and memory use of the algorithm will greatly increase. To solve these two problems, we proposed a new spectral clustering image segmentation algorithm based on multi scales and sparse matrix. We devised a new feature extraction method at first, then extracted the features of image on different scales, at last, using the feature information to construct sparse similarity matrix which can improve the operation efficiency. Compared with traditional spectral clustering algorithm, image segmentation experimental results show our algorithm have better degree of accuracy and robustness.

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.

Knee cartilage segmentation using active shape models and local binary patterns

NASA Astrophysics Data System (ADS)

González, Germán.; Escalante-Ramírez, Boris

2014-05-01

Segmentation of knee cartilage has been useful for opportune diagnosis and treatment of osteoarthritis (OA). This paper presents a semiautomatic segmentation technique based on Active Shape Models (ASM) combined with Local Binary Patterns (LBP) and its approaches to describe the surrounding texture of femoral cartilage. The proposed technique is tested on a 16-image database of different patients and it is validated through Leave- One-Out method. We compare different segmentation techniques: ASM-LBP, ASM-medianLBP, and ASM proposed by Cootes. The ASM-LBP approaches are tested with different ratios to decide which of them describes the cartilage texture better. The results show that ASM-medianLBP has better performance than ASM-LBP and ASM. Furthermore, we add a routine which improves the robustness versus two principal problems: oversegmentation and initialization.

Image processing based detection of lung cancer on CT scan images

NASA Astrophysics Data System (ADS)

Abdillah, Bariqi; Bustamam, Alhadi; Sarwinda, Devvi

2017-10-01

In this paper, we implement and analyze the image processing method for detection of lung cancer. Image processing techniques are widely used in several medical problems for picture enhancement in the detection phase to support the early medical treatment. In this research we proposed a detection method of lung cancer based on image segmentation. Image segmentation is one of intermediate level in image processing. Marker control watershed and region growing approach are used to segment of CT scan image. Detection phases are followed by image enhancement using Gabor filter, image segmentation, and features extraction. From the experimental results, we found the effectiveness of our approach. The results show that the best approach for main features detection is watershed with masking method which has high accuracy and robust.

Defect detection and classification of galvanized stamping parts based on fully convolution neural network

NASA Astrophysics Data System (ADS)

Xiao, Zhitao; Leng, Yanyi; Geng, Lei; Xi, Jiangtao

2018-04-01

In this paper, a new convolution neural network method is proposed for the inspection and classification of galvanized stamping parts. Firstly, all workpieces are divided into normal and defective by image processing, and then the defective workpieces extracted from the region of interest (ROI) area are input to the trained fully convolutional networks (FCN). The network utilizes an end-to-end and pixel-to-pixel training convolution network that is currently the most advanced technology in semantic segmentation, predicts result of each pixel. Secondly, we mark the different pixel values of the workpiece, defect and background for the training image, and use the pixel value and the number of pixels to realize the recognition of the defects of the output picture. Finally, the defect area's threshold depended on the needs of the project is set to achieve the specific classification of the workpiece. The experiment results show that the proposed method can successfully achieve defect detection and classification of galvanized stamping parts under ordinary camera and illumination conditions, and its accuracy can reach 99.6%. Moreover, it overcomes the problem of complex image preprocessing and difficult feature extraction and performs better adaptability.

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

Soffientini, Chiara Dolores, E-mail: chiaradolores.soffientini@polimi.it; Baselli, Giuseppe; De Bernardi, Elisabetta

Purpose: Quantitative {sup 18}F-fluorodeoxyglucose positron emission tomography is limited by the uncertainty in lesion delineation due to poor SNR, low resolution, and partial volume effects, subsequently impacting oncological assessment, treatment planning, and follow-up. The present work develops and validates a segmentation algorithm based on statistical clustering. The introduction of constraints based on background features and contiguity priors is expected to improve robustness vs clinical image characteristics such as lesion dimension, noise, and contrast level. Methods: An eight-class Gaussian mixture model (GMM) clustering algorithm was modified by constraining the mean and variance parameters of four background classes according to the previousmore » analysis of a lesion-free background volume of interest (background modeling). Hence, expectation maximization operated only on the four classes dedicated to lesion detection. To favor the segmentation of connected objects, a further variant was introduced by inserting priors relevant to the classification of neighbors. The algorithm was applied to simulated datasets and acquired phantom data. Feasibility and robustness toward initialization were assessed on a clinical dataset manually contoured by two expert clinicians. Comparisons were performed with respect to a standard eight-class GMM algorithm and to four different state-of-the-art methods in terms of volume error (VE), Dice index, classification error (CE), and Hausdorff distance (HD). Results: The proposed GMM segmentation with background modeling outperformed standard GMM and all the other tested methods. Medians of accuracy indexes were VE <3%, Dice >0.88, CE <0.25, and HD <1.2 in simulations; VE <23%, Dice >0.74, CE <0.43, and HD <1.77 in phantom data. Robustness toward image statistic changes (±15%) was shown by the low index changes: <26% for VE, <17% for Dice, and <15% for CE. Finally, robustness toward the user-dependent volume initialization was demonstrated. The inclusion of the spatial prior improved segmentation accuracy only for lesions surrounded by heterogeneous background: in the relevant simulation subset, the median VE significantly decreased from 13% to 7%. Results on clinical data were found in accordance with simulations, with absolute VE <7%, Dice >0.85, CE <0.30, and HD <0.81. Conclusions: The sole introduction of constraints based on background modeling outperformed standard GMM and the other tested algorithms. Insertion of a spatial prior improved the accuracy for realistic cases of objects in heterogeneous backgrounds. Moreover, robustness against initialization supports the applicability in a clinical setting. In conclusion, application-driven constraints can generally improve the capabilities of GMM and statistical clustering algorithms.« less

Vision-based in-line fabric defect detection using yarn-specific shape features

NASA Astrophysics Data System (ADS)

Schneider, Dorian; Aach, Til

2012-01-01

We develop a methodology for automatic in-line flaw detection in industrial woven fabrics. Where state of the art detection algorithms apply texture analysis methods to operate on low-resolved ({200 ppi) image data, we describe here a process flow to segment single yarns in high-resolved ({1000 ppi) textile images. Four yarn shape features are extracted, allowing a precise detection and measurement of defects. The degree of precision reached allows a classification of detected defects according to their nature, providing an innovation in the field of automatic fabric flaw detection. The design has been carried out to meet real time requirements and face adverse conditions caused by loom vibrations and dirt. The entire process flow is discussed followed by an evaluation using a database with real-life industrial fabric images. This work pertains to the construction of an on-loom defect detection system to be used in manufacturing practice.

A Novel Defect Inspection Method for Semiconductor Wafer Based on Magneto-Optic Imaging

NASA Astrophysics Data System (ADS)

Pan, Z.; Chen, L.; Li, W.; Zhang, G.; Wu, P.

2013-03-01

The defects of semiconductor wafer may be generated from the manufacturing processes. A novel defect inspection method of semiconductor wafer is presented in this paper. The method is based on magneto-optic imaging, which involves inducing eddy current into the wafer under test, and detecting the magnetic flux associated with eddy current distribution in the wafer by exploiting the Faraday rotation effect. The magneto-optic image being generated may contain some noises that degrade the overall image quality, therefore, in this paper, in order to remove the unwanted noise present in the magneto-optic image, the image enhancement approach using multi-scale wavelet is presented, and the image segmentation approach based on the integration of watershed algorithm and clustering strategy is given. The experimental results show that many types of defects in wafer such as hole and scratch etc. can be detected by the method proposed in this paper.

Optimal reinforcement of training datasets in semi-supervised landmark-based segmentation

NASA Astrophysics Data System (ADS)

Ibragimov, Bulat; Likar, Boštjan; Pernuš, Franjo; Vrtovec, Tomaž

2015-03-01

During the last couple of decades, the development of computerized image segmentation shifted from unsupervised to supervised methods, which made segmentation results more accurate and robust. However, the main disadvantage of supervised segmentation is a need for manual image annotation that is time-consuming and subjected to human error. To reduce the need for manual annotation, we propose a novel learning approach for training dataset reinforcement in the area of landmark-based segmentation, where newly detected landmarks are optimally combined with reference landmarks from the training dataset and therefore enriches the training process. The approach is formulated as a nonlinear optimization problem, where the solution is a vector of weighting factors that measures how reliable are the detected landmarks. The detected landmarks that are found to be more reliable are included into the training procedure with higher weighting factors, whereas the detected landmarks that are found to be less reliable are included with lower weighting factors. The approach is integrated into the landmark-based game-theoretic segmentation framework and validated against the problem of lung field segmentation from chest radiographs.

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.

Quantum computing with defects.

PubMed

Weber, J R; Koehl, W F; Varley, J B; Janotti, A; Buckley, B B; Van de Walle, C G; Awschalom, D D

2010-05-11

Identifying and designing physical systems for use as qubits, the basic units of quantum information, are critical steps in the development of a quantum computer. Among the possibilities in the solid state, a defect in diamond known as the nitrogen-vacancy (NV(-1)) center stands out for its robustness--its quantum state can be initialized, manipulated, and measured with high fidelity at room temperature. Here we describe how to systematically identify other deep center defects with similar quantum-mechanical properties. We present a list of physical criteria that these centers and their hosts should meet and explain how these requirements can be used in conjunction with electronic structure theory to intelligently sort through candidate defect systems. To illustrate these points in detail, we compare electronic structure calculations of the NV(-1) center in diamond with those of several deep centers in 4H silicon carbide (SiC). We then discuss the proposed criteria for similar defects in other tetrahedrally coordinated semiconductors.

Response to defects in multipartite and bipartite entanglement of isotropic quantum spin networks

NASA Astrophysics Data System (ADS)

Roy, Sudipto Singha; Dhar, Himadri Shekhar; Rakshit, Debraj; SenDe, Aditi; Sen, Ujjwal

2018-05-01

Quantum networks are an integral component in performing efficient computation and communication tasks that are not accessible using classical systems. A key aspect in designing an effective and scalable quantum network is generating entanglement between its nodes, which is robust against defects in the network. We consider an isotropic quantum network of spin-1/2 particles with a finite fraction of defects, where the corresponding wave function of the network is rotationally invariant under the action of local unitaries. By using quantum information-theoretic concepts like strong subadditivity of von Neumann entropy and approximate quantum telecloning, we prove analytically that in the presence of defects, caused by loss of a finite fraction of spins, the network, composed of a fixed numbers of lattice sites, sustains genuine multisite entanglement and at the same time may exhibit finite moderate-range bipartite entanglement, in contrast to the network with no defects.

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.

Validation tools for image segmentation

NASA Astrophysics Data System (ADS)

Padfield, Dirk; Ross, James

2009-02-01

A large variety of image analysis tasks require the segmentation of various regions in an image. For example, segmentation is required to generate accurate models of brain pathology that are important components of modern diagnosis and therapy. While the manual delineation of such structures gives accurate information, the automatic segmentation of regions such as the brain and tumors from such images greatly enhances the speed and repeatability of quantifying such structures. The ubiquitous need for such algorithms has lead to a wide range of image segmentation algorithms with various assumptions, parameters, and robustness. The evaluation of such algorithms is an important step in determining their effectiveness. Therefore, rather than developing new segmentation algorithms, we here describe validation methods for segmentation algorithms. Using similarity metrics comparing the automatic to manual segmentations, we demonstrate methods for optimizing the parameter settings for individual cases and across a collection of datasets using the Design of Experiment framework. We then employ statistical analysis methods to compare the effectiveness of various algorithms. We investigate several region-growing algorithms from the Insight Toolkit and compare their accuracy to that of a separate statistical segmentation algorithm. The segmentation algorithms are used with their optimized parameters to automatically segment the brain and tumor regions in MRI images of 10 patients. The validation tools indicate that none of the ITK algorithms studied are able to outperform with statistical significance the statistical segmentation algorithm although they perform reasonably well considering their simplicity.

Flip-avoiding interpolating surface registration for skull reconstruction.

PubMed

Xie, Shudong; Leow, Wee Kheng; Lee, Hanjing; Lim, Thiam Chye

2018-03-30

Skull reconstruction is an important and challenging task in craniofacial surgery planning, forensic investigation and anthropological studies. Existing methods typically reconstruct approximating surfaces that regard corresponding points on the target skull as soft constraints, thus incurring non-zero error even for non-defective parts and high overall reconstruction error. This paper proposes a novel geometric reconstruction method that non-rigidly registers an interpolating reference surface that regards corresponding target points as hard constraints, thus achieving low reconstruction error. To overcome the shortcoming of interpolating a surface, a flip-avoiding method is used to detect and exclude conflicting hard constraints that would otherwise cause surface patches to flip and self-intersect. Comprehensive test results show that our method is more accurate and robust than existing skull reconstruction methods. By incorporating symmetry constraints, it can produce more symmetric and normal results than other methods in reconstructing defective skulls with a large number of defects. It is robust against severe outliers such as radiation artifacts in computed tomography due to dental implants. In addition, test results also show that our method outperforms thin-plate spline for model resampling, which enables the active shape model to yield more accurate reconstruction results. As the reconstruction accuracy of defective parts varies with the use of different reference models, we also study the implication of reference model selection for skull reconstruction. Copyright © 2018 John Wiley & Sons, Ltd.

Autogenous bone particle/titanium fiber composites for bone regeneration in a rabbit radius critical-size defect model.

PubMed

Xie, Huanxin; Ji, Ye; Tian, Qi; Wang, Xintao; Zhang, Nan; Zhang, Yicai; Xu, Jun; Wang, Nanxiang; Yan, Jinglong

2017-11-01

To explore the effects of autogenous bone particle/titanium fiber composites on repairing segmental bone defects in rabbits. A model of bilateral radial bone defect was established in 36 New Zealand white rabbits which were randomly divided into 3 groups according to filling materials used for bilaterally defect treatment: in group C, 9 animal bone defect areas were prepared into simple bilateral radius bone defect (empty sham) as the control group; 27 rabbits were used in groups ABP and ABP-Ti. In group ABP, left defects were simply implanted with autogenous bone particles; meanwhile, group ABP-Ti animals had right defects implanted with autogenous bone particle/titanium fiber composites. Animals were sacrificed at 4, 8, and 12 weeks, respectively, after operation. Micro-CT showed that group C could not complete bone regeneration. Bone volume to tissue volume values in group ABP-Ti were better than group ABP. From histology and histomorphometry Groups ABP and ABP-Ti achieved bone repair, the bone formation of group ABP-Ti was better. The mechanical strength of group ABP-Ti was superior to that of other groups. These results confirmed the effectiveness of autologous bone particle/titanium fiber composites for promoting bone regeneration and mechanical strength.

Sparsity guided empirical wavelet transform for fault diagnosis of rolling element bearings

NASA Astrophysics Data System (ADS)

Wang, Dong; Zhao, Yang; Yi, Cai; Tsui, Kwok-Leung; Lin, Jianhui

2018-02-01

Rolling element bearings are widely used in various industrial machines, such as electric motors, generators, pumps, gearboxes, railway axles, turbines, and helicopter transmissions. Fault diagnosis of rolling element bearings is beneficial to preventing any unexpected accident and reducing economic loss. In the past years, many bearing fault detection methods have been developed. Recently, a new adaptive signal processing method called empirical wavelet transform attracts much attention from readers and engineers and its applications to bearing fault diagnosis have been reported. The main problem of empirical wavelet transform is that Fourier segments required in empirical wavelet transform are strongly dependent on the local maxima of the amplitudes of the Fourier spectrum of a signal, which connotes that Fourier segments are not always reliable and effective if the Fourier spectrum of the signal is complicated and overwhelmed by heavy noises and other strong vibration components. In this paper, sparsity guided empirical wavelet transform is proposed to automatically establish Fourier segments required in empirical wavelet transform for fault diagnosis of rolling element bearings. Industrial bearing fault signals caused by single and multiple railway axle bearing defects are used to verify the effectiveness of the proposed sparsity guided empirical wavelet transform. Results show that the proposed method can automatically discover Fourier segments required in empirical wavelet transform and reveal single and multiple railway axle bearing defects. Besides, some comparisons with three popular signal processing methods including ensemble empirical mode decomposition, the fast kurtogram and the fast spectral correlation are conducted to highlight the superiority of the proposed method.

3D robust Chan-Vese model for industrial computed tomography volume data segmentation

NASA Astrophysics Data System (ADS)

Liu, Linghui; Zeng, Li; Luan, Xiao

2013-11-01

Industrial computed tomography (CT) has been widely applied in many areas of non-destructive testing (NDT) and non-destructive evaluation (NDE). In practice, CT volume data to be dealt with may be corrupted by noise. This paper addresses the segmentation of noisy industrial CT volume data. Motivated by the research on the Chan-Vese (CV) model, we present a region-based active contour model that draws upon intensity information in local regions with a controllable scale. In the presence of noise, a local energy is firstly defined according to the intensity difference within a local neighborhood. Then a global energy is defined to integrate local energy with respect to all image points. In a level set formulation, this energy is represented by a variational level set function, where a surface evolution equation is derived for energy minimization. Comparative analysis with the CV model indicates the comparable performance of the 3D robust Chan-Vese (RCV) model. The quantitative evaluation also shows the segmentation accuracy of 3D RCV. In addition, the efficiency of our approach is validated under several types of noise, such as Poisson noise, Gaussian noise, salt-and-pepper noise and speckle noise.

A New Feedback-Based Method for Parameter Adaptation in Image Processing Routines.

PubMed

Khan, Arif Ul Maula; Mikut, Ralf; Reischl, Markus

2016-01-01

The parametrization of automatic image processing routines is time-consuming if a lot of image processing parameters are involved. An expert can tune parameters sequentially to get desired results. This may not be productive for applications with difficult image analysis tasks, e.g. when high noise and shading levels in an image are present or images vary in their characteristics due to different acquisition conditions. Parameters are required to be tuned simultaneously. We propose a framework to improve standard image segmentation methods by using feedback-based automatic parameter adaptation. Moreover, we compare algorithms by implementing them in a feedforward fashion and then adapting their parameters. This comparison is proposed to be evaluated by a benchmark data set that contains challenging image distortions in an increasing fashion. This promptly enables us to compare different standard image segmentation algorithms in a feedback vs. feedforward implementation by evaluating their segmentation quality and robustness. We also propose an efficient way of performing automatic image analysis when only abstract ground truth is present. Such a framework evaluates robustness of different image processing pipelines using a graded data set. This is useful for both end-users and experts.

A New Feedback-Based Method for Parameter Adaptation in Image Processing Routines

PubMed Central

Mikut, Ralf; Reischl, Markus

2016-01-01

The parametrization of automatic image processing routines is time-consuming if a lot of image processing parameters are involved. An expert can tune parameters sequentially to get desired results. This may not be productive for applications with difficult image analysis tasks, e.g. when high noise and shading levels in an image are present or images vary in their characteristics due to different acquisition conditions. Parameters are required to be tuned simultaneously. We propose a framework to improve standard image segmentation methods by using feedback-based automatic parameter adaptation. Moreover, we compare algorithms by implementing them in a feedforward fashion and then adapting their parameters. This comparison is proposed to be evaluated by a benchmark data set that contains challenging image distortions in an increasing fashion. This promptly enables us to compare different standard image segmentation algorithms in a feedback vs. feedforward implementation by evaluating their segmentation quality and robustness. We also propose an efficient way of performing automatic image analysis when only abstract ground truth is present. Such a framework evaluates robustness of different image processing pipelines using a graded data set. This is useful for both end-users and experts. PMID:27764213

Vessel formation is induced prior to the appearance of cartilage in BMP-2-mediated heterotopic ossification

USDA-ARS?s Scientific Manuscript database

Heterotopic ossification (HO), or endochondral bone formation at nonskeletal sites, often results from traumatic injury and can lead to devastating consequences. Alternatively, the ability to harness this phenomenon would greatly enhance current orthopedic tools for treating segmental bone defects. ...

Enhanced Healing of Segmental Bone Defects by Modulation of the Mechanical Environment

DTIC Science & Technology

2013-10-01

Employment opportunities received based upon experience/ training supported by this award Partly based upon her research during the completion of...School, Coventry CV4 7AL, United Kingdom References 1. Stevenson S. Enhancement of fracture healing with autogenous and allogeneic bone grafts. Clin

SU-E-I-96: A Study About the Influence of ROI Variation On Tumor Segmentation in PET

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

Li, L; Tan, S; Lu, W

2014-06-01

Purpose: To study the influence of different regions of interest (ROI) on tumor segmentation in PET. Methods: The experiments were conducted on a cylindrical phantom. Six spheres with different volumes (0.5ml, 1ml, 6ml, 12ml, 16ml and 20 ml) were placed inside a cylindrical container to mimic tumors of different sizes. The spheres were filled with 11C solution as sources and the cylindrical container was filled with 18F-FDG solution as the background. The phantom was continuously scanned in a Biograph-40 True Point/True View PET/CT scanner, and 42 images were reconstructed with source-to-background ratio (SBR) ranging from 16:1 to 1.8:1. We tookmore » a large and a small ROI for each sphere, both of which contain the whole sphere and does not contain any other spheres. Six other ROIs of different sizes were then taken between the large and the small ROI. For each ROI, all images were segmented by eitht thresholding methods and eight advanced methods, respectively. The segmentation results were evaluated by dice similarity index (DSI), classification error (CE) and volume error (VE). The robustness of different methods to ROI variation was quantified using the interrun variation and a generalized Cohen's kappa. Results: With the change of ROI, the segmentation results of all tested methods changed more or less. Compared with all advanced methods, thresholding methods were less affected by the ROI change. In addition, most of the thresholding methods got more accurate segmentation results for all sphere sizes. Conclusion: The results showed that the segmentation performance of all tested methods was affected by the change of ROI. Thresholding methods were more robust to this change and they can segment the PET image more accurately. This work was supported in part by National Natural Science Foundation of China (NNSFC), under Grant Nos. 60971112 and 61375018, and Fundamental Research Funds for the Central Universities, under Grant No. 2012QN086. Wei Lu was supported in part by the National Institutes of Health (NIH) Grant No. R01 CA172638.« less

Right ventricle functional parameters estimation in arrhythmogenic right ventricular dysplasia using a robust shape based deformable model.

PubMed

Oghli, Mostafa Ghelich; Dehlaghi, Vahab; Zadeh, Ali Mohammad; Fallahi, Alireza; Pooyan, Mohammad

2014-07-01

Assessment of cardiac right-ventricle functions plays an essential role in diagnosis of arrhythmogenic right ventricular dysplasia (ARVD). Among clinical tests, cardiac magnetic resonance imaging (MRI) is now becoming the most valid imaging technique to diagnose ARVD. Fatty infiltration of the right ventricular free wall can be visible on cardiac MRI. Finding right-ventricle functional parameters from cardiac MRI images contains segmentation of right-ventricle in each slice of end diastole and end systole phases of cardiac cycle and calculation of end diastolic and end systolic volume and furthermore other functional parameters. The main problem of this task is the segmentation part. We used a robust method based on deformable model that uses shape information for segmentation of right-ventricle in short axis MRI images. After segmentation of right-ventricle from base to apex in end diastole and end systole phases of cardiac cycle, volume of right-ventricle in these phases calculated and then, ejection fraction calculated. We performed a quantitative evaluation of clinical cardiac parameters derived from the automatic segmentation by comparison against a manual delineation of the ventricles. The manually and automatically determined quantitative clinical parameters were statistically compared by means of linear regression. This fits a line to the data such that the root-mean-square error (RMSE) of the residuals is minimized. The results show low RMSE for Right Ventricle Ejection Fraction and Volume (≤ 0.06 for RV EF, and ≤ 10 mL for RV volume). Evaluation of segmentation results is also done by means of four statistical measures including sensitivity, specificity, similarity index and Jaccard index. The average value of similarity index is 86.87%. The Jaccard index mean value is 83.85% which shows a good accuracy of segmentation. The average of sensitivity is 93.9% and mean value of the specificity is 89.45%. These results show the reliability of proposed method in these cases that manual segmentation is inapplicable. Huge shape variety of right-ventricle led us to use a shape prior based method and this work can develop by four-dimensional processing for determining the first ventricular slices.

Effects on Ridge Segmentation, Magmatic Plumbing and Eruption Style Caused by Weak Hot-spot to Ridge Interaction: the Central Indian Ridge and Rodrigues Hot-spot Couplet.

NASA Astrophysics Data System (ADS)

Murton, B. J.; Parson, L. M.; Sauter, D.

2001-12-01

The intermediate spreading, Central Indian Ridge (CIR) forms a couplet with a weak hot-spot of which the Rodrigues archipelago is an expression. Recently collected bathymetry shows that despite having little in the way of a significant topographic swell, the hot-spot is associated with a change in offset sense across adjacent transforms of the CIR causing the ridge to draw nearer to the Rodrigues island system. The most proximal ridge segment of the CIR is over 20km long and comprises three non-transform bounded sub-segments. The most northerly sub-segment has a shallow (<3000m), narrow (<5km) and featureless flat rift valley. TOBI sidescan sonar imagery shows that the segment is host to a 15km-long, 5km-wide single sheet flow. Elsewhere in the segment the valley floor is characterised by long (>5km), narrow (<1km) ridges that often terminate in conical seamounts. These ridges are the loci of some of the acoustically freshest volcanic facies in the rift valley. Samples recovered from these ridges have similar petrology along strike. With increasing distance south along the CIR, the ridge segments are typically 500m deeper than to the north. Here they are about 75km long and bounded by transform offsets that are 50 km long. However, even in the deepest parts of these segments, where the axial floor is over 4000m deep at the ridge-transform-intersections, there is fresh lava and other evidence for abundant volcanic activity. Within these segments, the rift valley comprises mainly seamounts and hummocky volcanic features. We believe the westward stepping trend of the CIR towards the Rodrigues islands is a function of the hot spot. The elevated temperature and volatile content to the west reduces mantle viscosity which, combined with thinner and hence weaker lithosphere, influencec the loci of initial oceanic rifting and the relative position of the ridge axis. The unusually great length of the northern segment has a similar origin with the presence of thin and weak lithosphere and less viscous mantle reducing the tectonic ``memory" of the ridge system. Despite being farther from the hot-spot, the southern segments have a similarly robust melt supply to the northern segment. The main difference is melt delivery, with the northern segments supplied via long dikes that also erupt as fissure ridges, while to the south the supply is more disseminated. The massive lava sheet and robust and narrow axial valley in the northernmost sub-segment coincides with the tip of a southward propagating system. This system appears to herald the onset of more productive melting a may represent a relocation of the hot-spot-ridge interaction.

A Novel Segmentation Approach Combining Region- and Edge-Based Information for Ultrasound Images

PubMed Central

Luo, Yaozhong; Liu, Longzhong; Li, Xuelong

2017-01-01

Ultrasound imaging has become one of the most popular medical imaging modalities with numerous diagnostic applications. However, ultrasound (US) image segmentation, which is the essential process for further analysis, is a challenging task due to the poor image quality. In this paper, we propose a new segmentation scheme to combine both region- and edge-based information into the robust graph-based (RGB) segmentation method. The only interaction required is to select two diagonal points to determine a region of interest (ROI) on the original image. The ROI image is smoothed by a bilateral filter and then contrast-enhanced by histogram equalization. Then, the enhanced image is filtered by pyramid mean shift to improve homogeneity. With the optimization of particle swarm optimization (PSO) algorithm, the RGB segmentation method is performed to segment the filtered image. The segmentation results of our method have been compared with the corresponding results obtained by three existing approaches, and four metrics have been used to measure the segmentation performance. The experimental results show that the method achieves the best overall performance and gets the lowest ARE (10.77%), the second highest TPVF (85.34%), and the second lowest FPVF (4.48%). PMID:28536703

Maximum-likelihood techniques for joint segmentation-classification of multispectral chromosome images.

PubMed

Schwartzkopf, Wade C; Bovik, Alan C; Evans, Brian L

2005-12-01

Traditional chromosome imaging has been limited to grayscale images, but recently a 5-fluorophore combinatorial labeling technique (M-FISH) was developed wherein each class of chromosomes binds with a different combination of fluorophores. This results in a multispectral image, where each class of chromosomes has distinct spectral components. In this paper, we develop new methods for automatic chromosome identification by exploiting the multispectral information in M-FISH chromosome images and by jointly performing chromosome segmentation and classification. We (1) develop a maximum-likelihood hypothesis test that uses multispectral information, together with conventional criteria, to select the best segmentation possibility; (2) use this likelihood function to combine chromosome segmentation and classification into a robust chromosome identification system; and (3) show that the proposed likelihood function can also be used as a reliable indicator of errors in segmentation, errors in classification, and chromosome anomalies, which can be indicators of radiation damage, cancer, and a wide variety of inherited diseases. We show that the proposed multispectral joint segmentation-classification method outperforms past grayscale segmentation methods when decomposing touching chromosomes. We also show that it outperforms past M-FISH classification techniques that do not use segmentation information.

Joint Segmentation of Anatomical and Functional Images: Applications in Quantification of Lesions from PET, PET-CT, MRI-PET, and MRI-PET-CT Images

PubMed Central

Bagci, Ulas; Udupa, Jayaram K.; Mendhiratta, Neil; Foster, Brent; Xu, Ziyue; Yao, Jianhua; Chen, Xinjian; Mollura, Daniel J.

2013-01-01

We present a novel method for the joint segmentation of anatomical and functional images. Our proposed methodology unifies the domains of anatomical and functional images, represents them in a product lattice, and performs simultaneous delineation of regions based on random walk image segmentation. Furthermore, we also propose a simple yet effective object/background seed localization method to make the proposed segmentation process fully automatic. Our study uses PET, PET-CT, MRI-PET, and fused MRI-PET-CT scans (77 studies in all) from 56 patients who had various lesions in different body regions. We validated the effectiveness of the proposed method on different PET phantoms as well as on clinical images with respect to the ground truth segmentation provided by clinicians. Experimental results indicate that the presented method is superior to threshold and Bayesian methods commonly used in PET image segmentation, is more accurate and robust compared to the other PET-CT segmentation methods recently published in the literature, and also it is general in the sense of simultaneously segmenting multiple scans in real-time with high accuracy needed in routine clinical use. PMID:23837967

Robust vehicle detection in different weather conditions: Using MIPM

PubMed Central

Menéndez, José Manuel; Jiménez, David

2018-01-01

Intelligent Transportation Systems (ITS) allow us to have high quality traffic information to reduce the risk of potentially critical situations. Conventional image-based traffic detection methods have difficulties acquiring good images due to perspective and background noise, poor lighting and weather conditions. In this paper, we propose a new method to accurately segment and track vehicles. After removing perspective using Modified Inverse Perspective Mapping (MIPM), Hough transform is applied to extract road lines and lanes. Then, Gaussian Mixture Models (GMM) are used to segment moving objects and to tackle car shadow effects, we apply a chromacity-based strategy. Finally, performance is evaluated through three different video benchmarks: own recorded videos in Madrid and Tehran (with different weather conditions at urban and interurban areas); and two well-known public datasets (KITTI and DETRAC). Our results indicate that the proposed algorithms are robust, and more accurate compared to others, especially when facing occlusions, lighting variations and weather conditions. PMID:29513664

Chinese License Plates Recognition Method Based on A Robust and Efficient Feature Extraction and BPNN Algorithm

NASA Astrophysics Data System (ADS)

Zhang, Ming; Xie, Fei; Zhao, Jing; Sun, Rui; Zhang, Lei; Zhang, Yue

2018-04-01

The prosperity of license plate recognition technology has made great contribution to the development of Intelligent Transport System (ITS). In this paper, a robust and efficient license plate recognition method is proposed which is based on a combined feature extraction model and BPNN (Back Propagation Neural Network) algorithm. Firstly, the candidate region of the license plate detection and segmentation method is developed. Secondly, a new feature extraction model is designed considering three sets of features combination. Thirdly, the license plates classification and recognition method using the combined feature model and BPNN algorithm is presented. Finally, the experimental results indicate that the license plate segmentation and recognition both can be achieved effectively by the proposed algorithm. Compared with three traditional methods, the recognition accuracy of the proposed method has increased to 95.7% and the consuming time has decreased to 51.4ms.

Using process monitor wafers to understand directed self-assembly defects

NASA Astrophysics Data System (ADS)

Cao, Yi; Her, YoungJun; Delgadillo, Paulina R.; Vandenbroeck, Nadia; Gronheid, Roel; Chan, Boon Teik; Hashimoto, Yukio; Romo, Ainhoa; Somervell, Mark; Nafus, Kathleen; Nealey, Paul F.

2013-03-01

As directed self-assembly (DSA) has gained momentum over the past few years, questions about its application to high volume manufacturing have arisen. One of the major concerns is about the fundamental limits of defectivity that can be attained with the technology. If DSA applications demonstrate defectivity that rivals of traditional lithographic technologies, the pathway to the cost benefits of the technology creates a very compelling case for its large scale implementation. To address this critical question, our team at IMEC has established a process monitor flow to track the defectivity behaviors of an exemplary chemo-epitaxy application for printing line/space patterns. Through establishing this baseline, we have been able to understand both traditional lithographic defect sources in new materials as well as new classes of assembly defects associated with DSA technology. Moreover, we have explored new materials and processing to lower the level of the defectivity baseline. The robustness of the material sets and process is investigated as well. In this paper, we will report the understandings learned from the IMEC DSA process monitor flow.

Tyrosine-mutant AAV8 delivery of human MERTK provides long-term retinal preservation in RCS rats.

PubMed

Deng, Wen-Tao; Dinculescu, Astra; Li, Qiuhong; Boye, Sanford L; Li, Jie; Gorbatyuk, Marina S; Pang, Jijing; Chiodo, Vince A; Matthes, Michael T; Yasumura, Douglas; Liu, Li; Alkuraya, Fowzan S; Zhang, Kang; Vollrath, Douglas; LaVail, Matthew M; Hauswirth, William W

2012-04-06

The absence of Mertk in RCS rats results in defective RPE phagocytosis, accumulation of outer segment (OS) debris in the subretinal space, and subsequent death of photoreceptors. Previous research utilizing Mertk gene replacement therapy in RCS rats provided proof of concept for treatment of this form of recessive retinitis pigmentosa (RP); however, the beneficial effects on retinal function were transient. In the present study, we evaluated whether delivery of a MERTK transgene using a tyrosine-mutant AAV8 capsid could lead to more robust and longer-term therapeutic outcomes than previously reported. An AAV8 Y733F vector expressing a human MERTK cDNA driven by a RPE-selective promoter was administrated subretinally at postnatal day 2. Functional and morphological analyses were performed at 4 months and 8 months post-treatment. Retinal vasculature and Müller cell activation were analyzed by quantifying acellular capillaries and glial fibrillary acidic protein immunostaining, respectively. Electroretinographic responses from treated eyes were more than one-third of wild-type levels and OS were well preserved in the injection area even at 8 months. Rescue of RPE phagocytosis, prevention of retinal vasculature degeneration, and inhibition of Müller cell activation were demonstrated in the treated eyes for at least 8 months. This research describes a longer and much more robust functional and morphological rescue than previous studies. We also demonstrate for the first time that an AAV8 mutant capsid serotype vector has a substantial therapeutic potential for RPE-specific gene delivery. These results suggest that tyrosine-mutant AAV8 vectors hold promise for the treatment of individuals with MERTK-associated RP.

Tyrosine-Mutant AAV8 Delivery of Human MERTK Provides Long-Term Retinal Preservation in RCS Rats

PubMed Central

Deng, Wen-Tao; Dinculescu, Astra; Li, Qiuhong; Boye, Sanford L.; Li, Jie; Gorbatyuk, Marina S.; Pang, Jijing; Chiodo, Vince A.; Matthes, Michael T.; Yasumura, Douglas; Liu, Li; Alkuraya, Fowzan S.; Zhang, Kang; Vollrath, Douglas; LaVail, Matthew M.; Hauswirth, William W.

2012-01-01

Purpose. The absence of Mertk in RCS rats results in defective RPE phagocytosis, accumulation of outer segment (OS) debris in the subretinal space, and subsequent death of photoreceptors. Previous research utilizing Mertk gene replacement therapy in RCS rats provided proof of concept for treatment of this form of recessive retinitis pigmentosa (RP); however, the beneficial effects on retinal function were transient. In the present study, we evaluated whether delivery of a MERTK transgene using a tyrosine-mutant AAV8 capsid could lead to more robust and longer-term therapeutic outcomes than previously reported. Methods. An AAV8 Y733F vector expressing a human MERTK cDNA driven by a RPE-selective promoter was administrated subretinally at postnatal day 2. Functional and morphological analyses were performed at 4 months and 8 months post-treatment. Retinal vasculature and Müller cell activation were analyzed by quantifying acellular capillaries and glial fibrillary acidic protein immunostaining, respectively. Results. Electroretinographic responses from treated eyes were more than one-third of wild-type levels and OS were well preserved in the injection area even at 8 months. Rescue of RPE phagocytosis, prevention of retinal vasculature degeneration, and inhibition of Müller cell activation were demonstrated in the treated eyes for at least 8 months. Conclusions. This research describes a longer and much more robust functional and morphological rescue than previous studies. We also demonstrate for the first time that an AAV8 mutant capsid serotype vector has a substantial therapeutic potential for RPE-specific gene delivery. These results suggest that tyrosine-mutant AAV8 vectors hold promise for the treatment of individuals with MERTK-associated RP. PMID:22408006

Chaotic CDMA watermarking algorithm for digital image in FRFT domain

NASA Astrophysics Data System (ADS)

Liu, Weizhong; Yang, Wentao; Feng, Zhuoming; Zou, Xuecheng

2007-11-01

A digital image-watermarking algorithm based on fractional Fourier transform (FRFT) domain is presented by utilizing chaotic CDMA technique in this paper. As a popular and typical transmission technique, CDMA has many advantages such as privacy, anti-jamming and low power spectral density, which can provide robustness against image distortions and malicious attempts to remove or tamper with the watermark. A super-hybrid chaotic map, with good auto-correlation and cross-correlation characteristics, is adopted to produce many quasi-orthogonal codes (QOC) that can replace the periodic PN-code used in traditional CDAM system. The watermarking data is divided into a lot of segments that correspond to different chaotic QOC respectively and are modulated into the CDMA watermarking data embedded into low-frequency amplitude coefficients of FRFT domain of the cover image. During watermark detection, each chaotic QOC extracts its corresponding watermarking segment by calculating correlation coefficients between chaotic QOC and watermarked data of the detected image. The CDMA technique not only can enhance the robustness of watermark but also can compress the data of the modulated watermark. Experimental results show that the watermarking algorithm has good performances in three aspects: better imperceptibility, anti-attack robustness and security.

Improving Electronic Sensor Reliability by Robust Outlier Screening

PubMed Central

Moreno-Lizaranzu, Manuel J.; Cuesta, Federico

2013-01-01

Electronic sensors are widely used in different application areas, and in some of them, such as automotive or medical equipment, they must perform with an extremely low defect rate. Increasing reliability is paramount. Outlier detection algorithms are a key component in screening latent defects and decreasing the number of customer quality incidents (CQIs). This paper focuses on new spatial algorithms (Good Die in a Bad Cluster with Statistical Bins (GDBC SB) and Bad Bin in a Bad Cluster (BBBC)) and an advanced outlier screening method, called Robust Dynamic Part Averaging Testing (RDPAT), as well as two practical improvements, which significantly enhance existing algorithms. Those methods have been used in production in Freescale® Semiconductor probe factories around the world for several years. Moreover, a study was conducted with production data of 289,080 dice with 26 CQIs to determine and compare the efficiency and effectiveness of all these algorithms in identifying CQIs. PMID:24113682

Improving electronic sensor reliability by robust outlier screening.

PubMed

Moreno-Lizaranzu, Manuel J; Cuesta, Federico

2013-10-09

Electronic sensors are widely used in different application areas, and in some of them, such as automotive or medical equipment, they must perform with an extremely low defect rate. Increasing reliability is paramount. Outlier detection algorithms are a key component in screening latent defects and decreasing the number of customer quality incidents (CQIs). This paper focuses on new spatial algorithms (Good Die in a Bad Cluster with Statistical Bins (GDBC SB) and Bad Bin in a Bad Cluster (BBBC)) and an advanced outlier screening method, called Robust Dynamic Part Averaging Testing (RDPAT), as well as two practical improvements, which significantly enhance existing algorithms. Those methods have been used in production in Freescale® Semiconductor probe factories around the world for several years. Moreover, a study was conducted with production data of 289,080 dice with 26 CQIs to determine and compare the efficiency and effectiveness of all these algorithms in identifying CQIs.

A robust approach to optimal matched filter design in ultrasonic non-destructive evaluation (NDE)

NASA Astrophysics Data System (ADS)

Li, Minghui; Hayward, Gordon

2017-02-01

The matched filter was demonstrated to be a powerful yet efficient technique to enhance defect detection and imaging in ultrasonic non-destructive evaluation (NDE) of coarse grain materials, provided that the filter was properly designed and optimized. In the literature, in order to accurately approximate the defect echoes, the design utilized the real excitation signals, which made it time consuming and less straightforward to implement in practice. In this paper, we present a more robust and flexible approach to optimal matched filter design using the simulated excitation signals, and the control parameters are chosen and optimized based on the real scenario of array transducer, transmitter-receiver system response, and the test sample, as a result, the filter response is optimized and depends on the material characteristics. Experiments on industrial samples are conducted and the results confirm the great benefits of the method.

View-Invariant Gait Recognition Through Genetic Template Segmentation

NASA Astrophysics Data System (ADS)

Isaac, Ebenezer R. H. P.; Elias, Susan; Rajagopalan, Srinivasan; Easwarakumar, K. S.

2017-08-01

Template-based model-free approach provides by far the most successful solution to the gait recognition problem in literature. Recent work discusses how isolating the head and leg portion of the template increase the performance of a gait recognition system making it robust against covariates like clothing and carrying conditions. However, most involve a manual definition of the boundaries. The method we propose, the genetic template segmentation (GTS), employs the genetic algorithm to automate the boundary selection process. This method was tested on the GEI, GEnI and AEI templates. GEI seems to exhibit the best result when segmented with our approach. Experimental results depict that our approach significantly outperforms the existing implementations of view-invariant gait recognition.

Robust Skull-Stripping Segmentation Based on Irrational Mask for Magnetic Resonance Brain Images.

PubMed

Moldovanu, Simona; Moraru, Luminița; Biswas, Anjan

2015-12-01

This paper proposes a new method for simple, efficient, and robust removal of the non-brain tissues in MR images based on an irrational mask for filtration within a binary morphological operation framework. The proposed skull-stripping segmentation is based on two irrational 3 × 3 and 5 × 5 masks, having the sum of its weights equal to the transcendental number π value provided by the Gregory-Leibniz infinite series. It allows maintaining a lower rate of useful pixel loss. The proposed method has been tested in two ways. First, it has been validated as a binary method by comparing and contrasting with Otsu's, Sauvola's, Niblack's, and Bernsen's binary methods. Secondly, its accuracy has been verified against three state-of-the-art skull-stripping methods: the graph cuts method, the method based on Chan-Vese active contour model, and the simplex mesh and histogram analysis skull stripping. The performance of the proposed method has been assessed using the Dice scores, overlap and extra fractions, and sensitivity and specificity as statistical methods. The gold standard has been provided by two neurologist experts. The proposed method has been tested and validated on 26 image series which contain 216 images from two publicly available databases: the Whole Brain Atlas and the Internet Brain Segmentation Repository that include a highly variable sample population (with reference to age, sex, healthy/diseased). The approach performs accurately on both standardized databases. The main advantage of the proposed method is its robustness and speed.

Hand-Based Biometric Analysis

NASA Technical Reports Server (NTRS)

Bebis, George (Inventor); Amayeh, Gholamreza (Inventor)

2015-01-01

Hand-based biometric analysis systems and techniques are described which provide robust hand-based identification and verification. An image of a hand is obtained, which is then segmented into a palm region and separate finger regions. Acquisition of the image is performed without requiring particular orientation or placement restrictions. Segmentation is performed without the use of reference points on the images. Each segment is analyzed by calculating a set of Zernike moment descriptors for the segment. The feature parameters thus obtained are then fused and compared to stored sets of descriptors in enrollment templates to arrive at an identity decision. By using Zernike moments, and through additional manipulation, the biometric analysis is invariant to rotation, scale, or translation or an in put image. Additionally, the analysis utilizes re-use of commonly-seen terms in Zernike calculations to achieve additional efficiencies over traditional Zernike moment calculation.

Hand-Based Biometric Analysis

NASA Technical Reports Server (NTRS)

Bebis, George

2013-01-01

Hand-based biometric analysis systems and techniques provide robust hand-based identification and verification. An image of a hand is obtained, which is then segmented into a palm region and separate finger regions. Acquisition of the image is performed without requiring particular orientation or placement restrictions. Segmentation is performed without the use of reference points on the images. Each segment is analyzed by calculating a set of Zernike moment descriptors for the segment. The feature parameters thus obtained are then fused and compared to stored sets of descriptors in enrollment templates to arrive at an identity decision. By using Zernike moments, and through additional manipulation, the biometric analysis is invariant to rotation, scale, or translation or an input image. Additionally, the analysis uses re-use of commonly seen terms in Zernike calculations to achieve additional efficiencies over traditional Zernike moment calculation.

Knowledge-based segmentation and feature analysis of hand and wrist radiographs

NASA Astrophysics Data System (ADS)

Efford, Nicholas D.

1993-07-01

The segmentation of hand and wrist radiographs for applications such as skeletal maturity assessment is best achieved by model-driven approaches incorporating anatomical knowledge. The reasons for this are discussed, and a particular frame-based or 'blackboard' strategy for the simultaneous segmentation of the hand and estimation of bone age via the TW2 method is described. The new approach is structured for optimum robustness and computational efficiency: features of interest are detected and analyzes in order of their size and prominence in the image, the largest and most distinctive being dealt with first, and the evidence generated by feature analysis is used to update a model of hand anatomy and hence guide later stages of the segmentation. Closed bone boundaries are formed by a hybrid technique combining knowledge-based, one-dimensional edge detection with model-assisted heuristic tree searching.

Segmentation propagation for the automated quantification of ventricle volume from serial MRI

NASA Astrophysics Data System (ADS)

Linguraru, Marius George; Butman, John A.

2009-02-01

Accurate ventricle volume estimates could potentially improve the understanding and diagnosis of communicating hydrocephalus. Postoperative communicating hydrocephalus has been recognized in patients with brain tumors where the changes in ventricle volume can be difficult to identify, particularly over short time intervals. Because of the complex alterations of brain morphology in these patients, the segmentation of brain ventricles is challenging. Our method evaluates ventricle size from serial brain MRI examinations; we (i) combined serial images to increase SNR, (ii) automatically segmented this image to generate a ventricle template using fast marching methods and geodesic active contours, and (iii) propagated the segmentation using deformable registration of the original MRI datasets. By applying this deformation to the ventricle template, serial volume estimates were obtained in a robust manner from routine clinical images (0.93 overlap) and their variation analyzed.

Interactive prostate segmentation using atlas-guided semi-supervised learning and adaptive feature selection

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

Park, Sang Hyun; Gao, Yaozong, E-mail: yzgao@cs.unc.edu; Shi, Yinghuan, E-mail: syh@nju.edu.cn

Purpose: Accurate prostate segmentation is necessary for maximizing the effectiveness of radiation therapy of prostate cancer. However, manual segmentation from 3D CT images is very time-consuming and often causes large intra- and interobserver variations across clinicians. Many segmentation methods have been proposed to automate this labor-intensive process, but tedious manual editing is still required due to the limited performance. In this paper, the authors propose a new interactive segmentation method that can (1) flexibly generate the editing result with a few scribbles or dots provided by a clinician, (2) fast deliver intermediate results to the clinician, and (3) sequentially correctmore » the segmentations from any type of automatic or interactive segmentation methods. Methods: The authors formulate the editing problem as a semisupervised learning problem which can utilize a priori knowledge of training data and also the valuable information from user interactions. Specifically, from a region of interest near the given user interactions, the appropriate training labels, which are well matched with the user interactions, can be locally searched from a training set. With voting from the selected training labels, both confident prostate and background voxels, as well as unconfident voxels can be estimated. To reflect informative relationship between voxels, location-adaptive features are selected from the confident voxels by using regression forest and Fisher separation criterion. Then, the manifold configuration computed in the derived feature space is enforced into the semisupervised learning algorithm. The labels of unconfident voxels are then predicted by regularizing semisupervised learning algorithm. Results: The proposed interactive segmentation method was applied to correct automatic segmentation results of 30 challenging CT images. The correction was conducted three times with different user interactions performed at different time periods, in order to evaluate both the efficiency and the robustness. The automatic segmentation results with the original average Dice similarity coefficient of 0.78 were improved to 0.865–0.872 after conducting 55–59 interactions by using the proposed method, where each editing procedure took less than 3 s. In addition, the proposed method obtained the most consistent editing results with respect to different user interactions, compared to other methods. Conclusions: The proposed method obtains robust editing results with few interactions for various wrong segmentation cases, by selecting the location-adaptive features and further imposing the manifold regularization. The authors expect the proposed method to largely reduce the laborious burdens of manual editing, as well as both the intra- and interobserver variability across clinicians.« less

Registration of MRI to intraoperative radiographs for target localization in spinal interventions

NASA Astrophysics Data System (ADS)

De Silva, T.; Uneri, A.; Ketcha, M. D.; Reaungamornrat, S.; Goerres, J.; Jacobson, M. W.; Vogt, S.; Kleinszig, G.; Khanna, A. J.; Wolinsky, J.-P.; Siewerdsen, J. H.

2017-01-01

Decision support to assist in target vertebra localization could provide a useful aid to safe and effective spine surgery. Previous solutions have shown 3D-2D registration of preoperative CT to intraoperative radiographs to reliably annotate vertebral labels for assistance during level localization. We present an algorithm (referred to as MR-LevelCheck) to perform 3D-2D registration based on a preoperative MRI to accommodate the increasingly common clinical scenario in which MRI is used instead of CT for preoperative planning. Straightforward adaptation of gradient/intensity-based methods appropriate to CT-to-radiograph registration is confounded by large mismatch and noncorrespondence in image intensity between MRI and radiographs. The proposed method overcomes such challenges with a simple vertebrae segmentation step using vertebra centroids as seed points (automatically defined within existing workflow). Forwards projections are computed using segmented MRI and registered to radiographs via gradient orientation (GO) similarity and the CMA-ES (covariance-matrix-adaptation evolutionary-strategy) optimizer. The method was tested in an IRB-approved study involving 10 patients undergoing cervical, thoracic, or lumbar spine surgery following preoperative MRI. The method successfully registered each preoperative MRI to intraoperative radiographs and maintained desirable properties of robustness against image content mismatch and large capture range. Robust registration performance was achieved with projection distance error (PDE) (median  ±  IQR)  =  4.3  ±  2.6 mm (median  ±  IQR) and 0% failure rate. Segmentation accuracy for the continuous max-flow method yielded dice coefficient  =  88.1  ±  5.2, accuracy  =  90.6  ±  5.7, RMSE  =  1.8  ±  0.6 mm, and contour affinity ratio (CAR)  =  0.82  ±  0.08. Registration performance was found to be robust for segmentation methods exhibiting RMSE  <3 mm and CAR  >0.50. The MR-LevelCheck method provides a potentially valuable extension to a previously developed decision support tool for spine surgery target localization by extending its utility to preoperative MRI while maintaining characteristics of accuracy and robustness.

Abnormal photoreceptor outer segment development and early retinal degeneration in kif3a mutant zebrafish.

PubMed

Raghupathy, Rakesh K; Zhang, Xun; Alhasani, Reem H; Zhou, Xinzhi; Mullin, Margaret; Reilly, James; Li, Wenchang; Liu, Mugen; Shu, Xinhua

2016-08-01

Photoreceptors are highly specialized sensory neurons that possess a modified primary cilium called the outer segment. Photoreceptor outer segment formation and maintenance require highly active protein transport via a process known as intraflagellar transport. Anterograde transport in outer segments is powered by the heterotrimeric kinesin II and coordinated by intraflagellar transport proteins. Here, we describe a new zebrafish model carrying a nonsense mutation in the kinesin II family member 3A (kif3a) gene. Kif3a mutant zebrafish exhibited curved body axes and kidney cysts. Outer segments were not formed in most parts of the mutant retina, and rhodopsin was mislocalized, suggesting KIF3A has a role in rhodopsin trafficking. Both rod and cone photoreceptors degenerated rapidly between 4 and 9 days post fertilization, and electroretinography response was not detected in 7 days post fertilization mutant larvae. Loss of KIF3A in zebrafish also resulted in an intracellular transport defect affecting anterograde but not retrograde transport of organelles. Our results indicate KIF3A plays a conserved role in photoreceptor outer segment formation and intracellular transport. Copyright © 2016 John Wiley & Sons, Ltd.

Small bowel obstruction caused by congenital transmesenteric defect.

PubMed

Nouira, F; Dhaou, Ben M; Charieg, A; Ghorbel, S; Jlidi, S; Chaouachi, B

2011-01-01

Transmesenteric hernias are extremely rare. A strangulated hernia through a mesenteric opening is a rare operative finding. Preoperative diagnosis still is difficult in spite of the imaging techniques currently available. The authors describe two cases of paediatric patients presenting with bowel obstruction resulting from a congenital mesenteric hernia. The first patient had a 3-cm wide congenital defect in the ileal mesentery through which the sigmoid colon had herniated. The second patient is a newborn infant who presented with symptoms and radiographic evidence of neonatal occlusion. At surgical exploration, a long segment of the small bowel had herniated in a defect in the ileal mesentery. A brief review of epidemiology and anatomy of transmesenteric hernias is included, along with a discussion of the difficulties in diagnosis and treatment of this condition.

3D-SIFT-Flow for atlas-based CT liver image segmentation

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

Xu, Yan, E-mail: xuyan04@gmail.com; Xu, Chenchao, E-mail: chenchaoxu33@gmail.com; Kuang, Xiao, E-mail: kuangxiao.ace@gmail.com

Purpose: In this paper, the authors proposed a new 3D registration algorithm, 3D-scale invariant feature transform (SIFT)-Flow, for multiatlas-based liver segmentation in computed tomography (CT) images. Methods: In the registration work, the authors developed a new registration method that takes advantage of dense correspondence using the informative and robust SIFT feature. The authors computed the dense SIFT features for the source image and the target image and designed an objective function to obtain the correspondence between these two images. Labeling of the source image was then mapped to the target image according to the former correspondence, resulting in accurate segmentation.more » In the fusion work, the 2D-based nonparametric label transfer method was extended to 3D for fusing the registered 3D atlases. Results: Compared with existing registration algorithms, 3D-SIFT-Flow has its particular advantage in matching anatomical structures (such as the liver) that observe large variation/deformation. The authors observed consistent improvement over widely adopted state-of-the-art registration methods such as ELASTIX, ANTS, and multiatlas fusion methods such as joint label fusion. Experimental results of liver segmentation on the MICCAI 2007 Grand Challenge are encouraging, e.g., Dice overlap ratio 96.27% ± 0.96% by our method compared with the previous state-of-the-art result of 94.90% ± 2.86%. Conclusions: Experimental results show that 3D-SIFT-Flow is robust for segmenting the liver from CT images, which has large tissue deformation and blurry boundary, and 3D label transfer is effective and efficient for improving the registration accuracy.« less

Inter-slice bidirectional registration-based segmentation of the prostate gland in MR and CT image sequences

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

Khalvati, Farzad, E-mail: farzad.khalvati@uwaterloo.ca; Tizhoosh, Hamid R.; Salmanpour, Aryan

Purpose: Accurate segmentation and volume estimation of the prostate gland in magnetic resonance (MR) and computed tomography (CT) images are necessary steps in diagnosis, treatment, and monitoring of prostate cancer. This paper presents an algorithm for the prostate gland volume estimation based on the semiautomated segmentation of individual slices in T2-weighted MR and CT image sequences. Methods: The proposedInter-Slice Bidirectional Registration-based Segmentation (iBRS) algorithm relies on interslice image registration of volume data to segment the prostate gland without the use of an anatomical atlas. It requires the user to mark only three slices in a given volume dataset, i.e., themore » first, middle, and last slices. Next, the proposed algorithm uses a registration algorithm to autosegment the remaining slices. We conducted comprehensive experiments to measure the performance of the proposed algorithm using three registration methods (i.e., rigid, affine, and nonrigid techniques). Results: The results with the proposed technique were compared with manual marking using prostate MR and CT images from 117 patients. Manual marking was performed by an expert user for all 117 patients. The median accuracies for individual slices measured using the Dice similarity coefficient (DSC) were 92% and 91% for MR and CT images, respectively. The iBRS algorithm was also evaluated regarding user variability, which confirmed that the algorithm was robust to interuser variability when marking the prostate gland. Conclusions: The proposed algorithm exploits the interslice data redundancy of the images in a volume dataset of MR and CT images and eliminates the need for an atlas, minimizing the computational cost while producing highly accurate results which are robust to interuser variability.« less

Inter-slice bidirectional registration-based segmentation of the prostate gland in MR and CT image sequences

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

Khalvati, Farzad, E-mail: farzad.khalvati@uwaterloo.ca; Tizhoosh, Hamid R.; Salmanpour, Aryan

2013-12-15

Purpose: Accurate segmentation and volume estimation of the prostate gland in magnetic resonance (MR) and computed tomography (CT) images are necessary steps in diagnosis, treatment, and monitoring of prostate cancer. This paper presents an algorithm for the prostate gland volume estimation based on the semiautomated segmentation of individual slices in T2-weighted MR and CT image sequences. Methods: The proposedInter-Slice Bidirectional Registration-based Segmentation (iBRS) algorithm relies on interslice image registration of volume data to segment the prostate gland without the use of an anatomical atlas. It requires the user to mark only three slices in a given volume dataset, i.e., themore » first, middle, and last slices. Next, the proposed algorithm uses a registration algorithm to autosegment the remaining slices. We conducted comprehensive experiments to measure the performance of the proposed algorithm using three registration methods (i.e., rigid, affine, and nonrigid techniques). Results: The results with the proposed technique were compared with manual marking using prostate MR and CT images from 117 patients. Manual marking was performed by an expert user for all 117 patients. The median accuracies for individual slices measured using the Dice similarity coefficient (DSC) were 92% and 91% for MR and CT images, respectively. The iBRS algorithm was also evaluated regarding user variability, which confirmed that the algorithm was robust to interuser variability when marking the prostate gland. Conclusions: The proposed algorithm exploits the interslice data redundancy of the images in a volume dataset of MR and CT images and eliminates the need for an atlas, minimizing the computational cost while producing highly accurate results which are robust to interuser variability.« less

Deformable segmentation via sparse representation and dictionary learning.

PubMed

Zhang, Shaoting; Zhan, Yiqiang; Metaxas, Dimitris N

2012-10-01

"Shape" and "appearance", the two pillars of a deformable model, complement each other in object segmentation. In many medical imaging applications, while the low-level appearance information is weak or mis-leading, shape priors play a more important role to guide a correct segmentation, thanks to the strong shape characteristics of biological structures. Recently a novel shape prior modeling method has been proposed based on sparse learning theory. Instead of learning a generative shape model, shape priors are incorporated on-the-fly through the sparse shape composition (SSC). SSC is robust to non-Gaussian errors and still preserves individual shape characteristics even when such characteristics is not statistically significant. Although it seems straightforward to incorporate SSC into a deformable segmentation framework as shape priors, the large-scale sparse optimization of SSC has low runtime efficiency, which cannot satisfy clinical requirements. In this paper, we design two strategies to decrease the computational complexity of SSC, making a robust, accurate and efficient deformable segmentation system. (1) When the shape repository contains a large number of instances, which is often the case in 2D problems, K-SVD is used to learn a more compact but still informative shape dictionary. (2) If the derived shape instance has a large number of vertices, which often appears in 3D problems, an affinity propagation method is used to partition the surface into small sub-regions, on which the sparse shape composition is performed locally. Both strategies dramatically decrease the scale of the sparse optimization problem and hence speed up the algorithm. Our method is applied on a diverse set of biomedical image analysis problems. Compared to the original SSC, these two newly-proposed modules not only significant reduce the computational complexity, but also improve the overall accuracy. Copyright © 2012 Elsevier B.V. All rights reserved.