Search results for: segmentation of bone structures on hip radiographs

Authors: Aicha Majda, Abdelhamid El Hassani

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Lung CT image segmentation is a prerequisite in lung CT image analysis. Most of the conventional methods need a post-processing to deal with the abnormal lung CT scans such as lung nodules or other lesions. The simplest similarity measure in the standard Graph Cuts Algorithm consists of directly comparing the pixel values of the two neighboring regions, which is not accurate because this kind of metrics is extremely sensitive to minor transformations such as noise or other artifacts problems. In this work, we propose an improved version of the standard graph cuts algorithm based on the Patch-Based similarity metric. The boundary penalty term in the graph cut algorithm is defined Based on Patch-Based similarity measurement instead of the simple intensity measurement in the standard method. The weights between each pixel and its neighboring pixels are Based on the obtained new term. The graph is then created using theses weights between its nodes. Finally, the segmentation is completed with the minimum cut/Max-Flow algorithm. Experimental results show that the proposed method is very accurate and efficient, and can directly provide explicit lung regions without any post-processing operations compared to the standard method.

Keywords: graph cuts, lung CT scan, lung parenchyma segmentation, patch-based similarity metric

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Authors: Nuseiba M. Altarawneh, Suhuai Luo, Brian Regan, Guijin Tang

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Liver segmentation from medical images poses more challenges than analogous segmentations of other organs. This contribution introduces a liver segmentation method from a series of computer tomography images. Overall, we present a novel method for segmenting liver by coupling density matching with shape priors. Density matching signifies a tracking method which operates via maximizing the Bhattacharyya similarity measure between the photometric distribution from an estimated image region and a model photometric distribution. Density matching controls the direction of the evolution process and slows down the evolving contour in regions with weak edges. The shape prior improves the robustness of density matching and discourages the evolving contour from exceeding liver’s boundaries at regions with weak boundaries. The model is implemented using a modified distance regularized level set (DRLS) model. The experimental results show that the method achieves a satisfactory result. By comparing with the original DRLS model, it is evident that the proposed model herein is more effective in addressing the over segmentation problem. Finally, we gauge our performance of our model against matrices comprising of accuracy, sensitivity and specificity.

Keywords: Bhattacharyya distance, distance regularized level set (DRLS) model, liver segmentation, level set method

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Authors: Q. Ni, J. A. Serna, D. Holland, X. Wang

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The objective of this study is to develop Nuclear Magnetic Resonance (NMR) techniques to enhance bone related research applied on normal and disuse (Biglycan knockout) mice bone in vitro by using both low-field and high-field NMR simultaneously. It is known that the total amplitude of T₂ relaxation envelopes, measured by the Carr-Purcell-Meiboom-Gill NMR spin echo train (CPMG), is a representation of the liquid phase inside the pores. Therefore, the NMR CPMG magnetization amplitude can be transferred to the volume of water after calibration with the NMR signal amplitude of the known volume of the selected water. In this study, the distribution of mobile water, porosity that can be determined by using low-field (20 MHz) CPMG relaxation technique, and the pore size distributions can be determined by a computational inversion relaxation method. It is also known that the total proton intensity of magnetization from the NMR free induction decay (FID) signal is due to the water present inside the pores (mobile water), the water that has undergone hydration with the bone (bound water), and the protons in the collagen and mineral matter (solid-like protons). Therefore, the components of total mobile and bound water within bone that can be determined by low-field NMR free induction decay technique. Furthermore, the bound water in solid phase (mineral and organic constituents), especially, the dominated component of calcium hydroxyapatite (Ca₁₀(OH)₂(PO₄)₆) can be determined by using high-field (400 MHz) magic angle spinning (MAS) NMR. With MAS technique reducing NMR spectral linewidth inhomogeneous broadening and susceptibility broadening of liquid-solid mix, in particular, we can conduct further research into the ¹H and ³¹P elements and environments of bone materials to identify the locations of bound water such as OH- group within minerals and bone architecture. We hypothesize that with low-field and high-field magic angle spinning NMR can provide a more complete interpretation of water distribution, particularly, in bound water, and these data are important to access bone quality and predict the mechanical behavior of bone.

Keywords: bone, mice bone, NMR, water in bone

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Authors: Hernandez Pardo Diego F., Guiza Arguello Viviana R., Coy Echeverria Ana, Viejo Abrante Fernando

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The biological hydroxyapatite obtained from bovine bone arouses great interest in its application as a material for bone regeneration due to its better bioactive behavior in comparison with synthetic hydroxyapatite. For this reason, the objective of the present investigation was to determine the effect of chemical and thermal treatments in obtaining biological bovine hydroxyapatite of high purity and crystallinity. Two different chemical reagents were evaluated (NaOH and HCl) with the aim to remove the organic matrix of the bovine cortical bone. On the other hand, for analyzing the effect of thermal treatment temperature was ranged between 500 and 1000°C for a holding time of 4 hours. To accomplish the above, the materials before and after the chemical and thermal treatments were characterized by elemental compositional analysis (CHN), infrared spectroscopy by Fourier transform (FTIR), RAMAN spectroscopy, scanning electron microscopy (SEM), thermogravimetric analysis (TGA) and X-ray diffraction (XRD) and energy dispersion X-ray spectroscopy (EDS). The results allowed to establish that NaOH is more effective in the removal of the organic matrix of the bone when compared to HCl, whereas a thermal treatment at 700ºC for 4 hours was enough to obtain biological hydroxyapatite of high purity and crystallinity.

Keywords: bovine bone, hydroxyapatite, biomaterials, thermal treatment

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Authors: Sweeti, Anoop Kant Godiyal, Neha Singh, Sneh Anand, B. K. Panigrahi, Jayasree Santhosh

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This work is about developing a tool for visualization and segmentation of Electroencephalograph (EEG) signals based on frequency domain features. Change in the frequency domain characteristics are correlated with change in mental state of the subject under study. Proposed algorithm provides a way to represent the change in the mental states using the different frequency band powers in form of segmented EEG signal. Many segmentation algorithms have been suggested in literature having application in brain computer interface, epilepsy and cognition studies that have been used for data classification. But the proposed method focusses mainly on the better presentation of signal and that’s why it could be a good utilization tool for clinician. Algorithm performs the basic filtering using band pass and notch filters in the range of 0.1-45 Hz. Advanced filtering is then performed by principal component analysis and wavelet transform based de-noising method. Frequency domain features are used for segmentation; considering the fact that the spectrum power of different frequency bands describes the mental state of the subject. Two sliding windows are further used for segmentation; one provides the time scale and other assigns the segmentation rule. The segmented data is displayed second by second successively with different color codes. Segment’s length can be selected as per need of the objective. Proposed algorithm has been tested on the EEG data set obtained from University of California in San Diego’s online data repository. Proposed tool gives a better visualization of the signal in form of segmented epochs of desired length representing the power spectrum variation in data. The algorithm is designed in such a way that it takes the data points with respect to the sampling frequency for each time frame and so it can be improved to use in real time visualization with desired epoch length.

Keywords: de-noising, multi-channel data, PCA, power spectra, segmentation

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Authors: Vimal Kumar Dewangan, T. S. Sampath Kumar, Mukesh Doble, Viju Daniel Varghese

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The apatite-based, i.e., calcium-deficient hydroxyapatite (CDHAp) bone cement is well-known potential bone graft/substitute in orthopaedics due to its similar chemical composition with natural bone minerals. Therefore, an easy approach was attempted to fabricate the apatite-based (CDHAp) bone cement with improved injectability, bioresorbability, and macroporosity. In this study, the desired bone cement was developed by mixing the solid phase (consisting of wet chemically synthesized nanocrystalline hydroxyapatite and commercially available (synthetic) tricalcium phosphate) and the liquid phase (consisting of cement binding accelerator with few biopolymers in a dilute acidic solution) along with a liquid porogen as polysorbate or a solid porogen as mannitol (for comparison) in an optimized liquid-to-powder ratio. The fabricated cement sets within clinically preferred setting time (≤20 minutes) are better injectable (>70%) and also stable at ~7.3-7.4 (physiological pH). The CDHAp phased bone cement was resulted by immersing the fabricated after-set cement in phosphate buffer solution and other similar artificial body fluids and incubated at physiological conditions for seven days, confirmed through the X-ray diffraction and Fourier transform-infrared spectroscopy analyses. The so-formed synthetic apatite-based bone cement holds the acceptable compressive strength (within the range of trabecular bone) with average interconnected pores size falls in a macropores range (~50-200μm) inside the cement, verified by scanning electron microscopy (SEM), mercury intrusion porosimetry and micro-CT analysis techniques. Also, it is biodegradable (degrades ~19-22% within 10-12 weeks) when incubated in artificial body fluids under physiological conditions. The biocompatibility study of the bone cement, when incubated with MG63 cells, shows a significant increase in the cell viability after 3rd day of incubation compared with the control, and the cells were well-attached and spread completely on the surface of the bone cement, confirmed through SEM and fluorescence microscopy analyses. With this all, we can conclude that the developed synthetic macroporous apatite-based bone cement may have the potential to become promising material used as a trabecular bone substitute.

Keywords: calcium deficient hydroxyapatite, synthetic apatite-based bone cement, injectability, macroporosity, trabecular bone substitute

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Authors: Aftab Ahmed, Ghulam Mehboob

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The object of presentation is to highlight the importance of condition which is a very rare genetic disorder although Paget’s disease is common but its juvenile type is very rare and a late presentation due to very slow onset and lack of earlier standard management. We present a case of 25 years old male with a chronic history of bone pain and a slow onset of mild swelling, later on diagnosed as juvenile Paget disease of bone. Rarity of this condition with inaccessibility for standard health treatment can lead to a significant delay in presentation and its management. There have been 50 reported cases worldwide according to Genetic Home Reference. There is increased osteoclastic activity along with osteoblastic activity related to gene alteration and osteoprotegrin deficiency. Morbidity of disease is very significant which lead children to become immobilize.

Keywords: juvenile, Paget’s disease, bone, Northern Area of Pakistan

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Authors: P. Shrivastava, S. Vijayalakshmi, A. K. Singh, S. Dalai, R. Teotia, P. Sharma, J. Bellare

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This paper focuses on the synthesis and application of nanobioactive glass for bone regeneration studies. Nanobioactive glass has been synthesized by sol gel method having a combination of silicon, calcium and phosphorous in the molar ratio of 75:21:4. The prepared particles were analyzed for surface morphology by FEG SEM and FEG TEM. Physiochemical properties were investigated using ICP AES, FTIR spectroscopy and X-ray diffraction (XRD) techniques. To ascertain their use for therapeutic use, biocompatibility evaluation of the particles was done by performing soaking studies in SBF and in vitro cell culture studies on MG63 cell lines. Cell morphology was observed by FE SEM and phase contrast microscopy. Nanobioactive glasses (NBG) thus prepared were of 30-200 nm in size, which makes them suitable for nano-biomedical applications. The spherical shape of the particles imparts high surface to volume ratio, promoting fast growth of hydroxyapatite (HA), which is the mineral component of bone. As evaluated by in vitro cell culture studies the NBG was found to enhance the surface activation which enhances osteoblast adhesion. This is an essential parameter to improve bone tissue integration, thereby making nanobioactive glass therapeutically suitable for correcting bone defects.

Keywords: biocompatibility, bone tissue engineering, hydroxyapatite, nanobioactive glass

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Authors: Kyi Pyar Zaw, Zin Mar Kyu

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Character recognition is the process of converting a text image file into editable and searchable text file. Feature Extraction is the heart of any character recognition system. The character recognition rate may be low or high depending on the extracted features. In the proposed paper, 25 features for one character are used in character recognition. Basically, there are three steps of character recognition such as character segmentation, feature extraction and classification. In segmentation step, horizontal cropping method is used for line segmentation and vertical cropping method is used for character segmentation. In the Feature extraction step, features are extracted in two ways. The first way is that the 8 features are extracted from the entire input character using eight direction chain code frequency extraction. The second way is that the input character is divided into 16 blocks. For each block, although 8 feature values are obtained through eight-direction chain code frequency extraction method, we define the sum of these 8 feature values as a feature for one block. Therefore, 16 features are extracted from that 16 blocks in the second way. We use the number of holes feature to cluster the similar characters. We can recognize the almost Myanmar common characters with various font sizes by using these features. All these 25 features are used in both training part and testing part. In the classification step, the characters are classified by matching the all features of input character with already trained features of characters.

Keywords: chain code frequency, character recognition, feature extraction, features matching, segmentation

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Authors: Ling-Ling E., Hong-Chen Liu, Dong-Sheng Wang, Fang Su, Xia Wu, Zhan-Ping Shi, Yan Lv, Jia-Zhu Wang

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Objective: The objective of the present study is to evaluate the capacity of a tissue-engineered bone complex of recombinant human bone morphogenetic protein 2 (rhBMP-2) mediated dental pulp stem cells (DPSCs) and nano-hydroxyapatite/collagen/poly(L-lactide)(nHAC/PLA) to reconstruct critical-size alveolar bone defects in New Zealand rabbit. Methods: Autologous DPSCs were isolated from rabbit dental pulp tissue and expanded ex vivo to enrich DPSCs numbers, and then their attachment and differentiation capability were evaluated when cultured on the culture plate or nHAC/PLA. The alveolar bone defects were treated with nHAC/PLA, nHAC/PLA+rhBMP-2, nHAC/PLA+DPSCs, nHAC/PLA+DPSCs+rhBMP-2, and autogenous bone (AB) obtained from iliac bone or were left untreated as a control. X-ray and a polychrome sequential fluorescent labeling were performed post-operatively and the animals were sacrificed 12 weeks after operation for histological observation and histomorphometric analysis. Results: Our results showed that DPSCs expressed STRO-1 and vementin, and favoured osteogenesis and adipogenesis in conditioned media. DPSCs attached and spread well, and retained their osteogenic phenotypes on nHAC/PLA. The rhBMP-2 could significantly increase protein content, alkaline phosphatase (ALP) activity/protein, osteocalcin (OCN) content, and mineral formation of DPSCs cultured on nHAC/PLA. The X-ray graph, the fluorescent, histological observation and histomorphometric analysis showed that the nHAC/PLA+DPSCs+rhBMP-2 tissue-engineered bone complex had an earlier mineralization and more bone formation inside the scaffold than nHAC/PLA, nHAC/PLA+rhBMP-2 and nHAC/PLA+DPSCs, or even autologous bone. Implanted DPSCs contribution to new bone were detected through transfected eGFP genes. Conclutions: Our findings indicated that stem cells existed in adult rabbit dental pulp tissue. The rhBMP-2 promoted osteogenic capability of DPSCs as a potential cell source for periodontal bone regeneration. The nHAC/PLA could serve as a good scaffold for autologous DPSCs seeding, proliferation and differentiation. The tissue-engineered bone complex with nHAC/PLA, rhBMP-2, and autologous DPSCs might be a better alternative to autologous bone for the clinical reconstruction of periodontal bone defects.

Keywords: nano-hydroxyapatite/collagen/poly (L-lactide), dental pulp stem cell, recombinant human bone morphogenetic protein, bone tissue engineering, alveolar bone

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Authors: Sandra Pietri, Helene Dubout, Sabrina Ena, Candice Hoste, Enrico Bastianelli

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Bone Therapeutics is a bone cell therapy company addressing high unmet medical needs in the field of bone fracture repair, more specifically in non-union and delayed-union fractures where the bone repair process is impaired. The company has developed a unique allogeneic osteoblastic cell product (ALLOB®) derived from bone marrow which is currently tested in humans in the indication of delayed-union fractures. The purpose of our study was to directly compare ALLOB® vs. non-differentiated mesenchymal stem cells (MSC) for their in vitro osteogenic characteristics and their in vivo osteogenic potential in order to determine which cellular type would be the most adapted for bone fracture repair. Methods: Healthy volunteers’ bone marrow aspirates (n=6) were expended (i) into BM-MSCs using a complete MSC culture medium or (ii) into ALLOB® cells according to its manufacturing process. Cells were characterized in vitro by morphology, immunophenotype, gene expression and differentiation potential. Additionally, their osteogenic potential was assessed in vivo in the subperiosteal calvaria bone formation model in nude mice. Results: The in vitro side-by-side comparison studies showed that although ALLOB® and BM-MSC shared some common general characteristics such as the 3 minimal MSC criteria, ALLOB® expressed significantly higher levels of chondro/osteoblastic genes such as BMP2 (fold change (FC) > 100), ALPL (FC > 12), CBFA1 (FC > 3) and differentiated significantly earlier than BM-MSC toward the osteogenic lineage. Moreover the bone formation model in nude mice demonstrated that used at the same cellular concentration, ALLOB® was able to induce significantly more (160% vs.107% for control animals) bone formation than BM-MSC (118% vs. 107 % for control animals) two weeks after administration. Conclusion: Our side-by-side comparison studies demonstrated that in vitro and in vivo, ALLOB® displays superior osteogenic capacity to BM-MScs and is therefore a better candidate for the treatment of bone fractures.

Keywords: gene expression, histomorphometry, mesenchymal stem cells, osteogenic differentiation potential, preclinical

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Authors: Tudor Barbu

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An automatic moment-based texture segmentation approach is proposed in this paper. First, we describe the related work in this computer vision domain. Our texture feature extraction, the first part of the texture recognition process, produces a set of moment-based feature vectors. For each image pixel, a texture feature vector is computed as a sequence of area moments. Second, an automatic pixel classification approach is proposed. The feature vectors are clustered using some unsupervised classification algorithm, the optimal number of clusters being determined using a measure based on validation indexes. From the resulted pixel classes one determines easily the desired texture regions of the image.

Keywords: image segmentation, moment-based, texture analysis, automatic classification, validation indexes

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Authors: S. Alireza Mirghasemi, Elly Trepman, Mohammad Saleh Sadeghi, Narges Rahimi Gabaran, Shervin Rashidinia

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Bone marrow edema syndrome (BMES) is an uncommon and self-limited syndrome characterized by atraumatic extremity pain with unknown of etiology. Symptom onset may include sudden or gradual swelling and pain at rest or during activity, usually at night. This syndrome mostly affects middle-aged men and younger women who have pain in the lower extremities. The most common sites involved with BMES, in decreasing order of frequency, are the bones about the hip, knee, ankle, and foot. The diagnosis of BMES is made with magnetic resonance imaging to exclude other causes of bone marrow edema. The correct diagnosis often is delayed because of the low prevalence and nonspecific signs in the foot and ankle. This delay may intensify bone pain and impair patient function and quality of life. The goal of BMES treatment is to relieve pain and shorten disease duration. Treatment options are limited and may include symptomatic treatment, pharmacologic treatment, and surgery.

Keywords: transient osteoporosis, bone marrow edema syndrome, iloprost, bisphosphonates

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Authors: Mawloud Mosbah, Bachir Boucheham

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Color Histogram is considered as the oldest method used by CBIR systems for indexing images. In turn, the global histograms do not include the spatial information; this is why the other techniques coming later have attempted to encounter this limitation by involving the segmentation task as a preprocessing step. The weak segmentation is employed by the local histograms while other methods as CCV (Color Coherent Vector) are based on strong segmentation. The indexation based on local histograms consists of splitting the image into N overlapping blocks or sub-regions, and then the histogram of each block is computed. The dissimilarity between two images is reduced, as consequence, to compute the distance between the N local histograms of the both images resulting then in N*N values; generally, the lowest value is taken into account to rank images, that means that the lowest value is that which helps to designate which sub-region utilized to index images of the collection being asked. In this paper, we make under light the local histogram indexation method in the hope to compare the results obtained against those given by the global histogram. We address also another noteworthy issue when Relying on local histograms namely which value, among N*N values, to trust on when comparing images, in other words, which sub-region among the N*N sub-regions on which we base to index images. Based on the results achieved here, it seems that relying on the local histograms, which needs to pose an extra overhead on the system by involving another preprocessing step naming segmentation, does not necessary mean that it produces better results. In addition to that, we have proposed here some ideas to select the local histogram on which we rely on to encode the image rather than relying on the local histogram having lowest distance with the query histograms.

Keywords: CBIR, color global histogram, color local histogram, weak segmentation, Euclidean distance

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Authors: Azin Zargham, Gholamreza Rouhi, Allahyar Geramy

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One of the most prevalent types of alveolar bone loss is horizontal bone loss (HBL) in which the bone height around teeth is reduced homogenously. In the presence of HBL the magnitudes of forces during orthodontic treatment should be altered according to the degree of HBL, in a way that without further bone loss, desired tooth movement can be obtained. In order to investigate the appropriate orthodontic force system in the presence of HBL, a three-dimensional numerical model capable of the simulation of orthodontic tooth movement was developed. The main goal of this research was to evaluate the effect of different degrees of HBL on a long-term orthodontic tooth movement. Moreover, the effect of different force magnitudes on orthodontic tooth movement in the presence of HBL was studied. Five three-dimensional finite element models of a maxillary lateral incisor with 0 mm, 1.5 mm, 3 mm, 4.5 mm and 6 mm of HBL were constructed. The long-term orthodontic tooth tipping movements were attained during a 4-weeks period in an iterative process through the external remodeling of the alveolar bone based on strains in periodontal ligament as the bone remodeling mechanical stimulus. To obtain long-term orthodontic tooth movement in each iteration, first the strains in periodontal ligament under a 1-N tipping force were calculated using finite element analysis. Then, bone remodeling and the subsequent tooth movement were computed in a post-processing software using a custom written program. Incisal edge, cervical, and apical area displacement in the models with different alveolar bone heights (0, 1.5, 3, 4.5, 6 mm bone loss) in response to a 1-N tipping force were calculated. Maximum tooth displacement was found to be 2.65 mm at the top of the crown of the model with a 6 mm bone loss. Minimum tooth displacement was 0.45 mm at the cervical level of the model with a normal bone support. Tooth tipping degrees of models in response to different tipping force magnitudes were also calculated for models with different degrees of HBL. Degrees of tipping tooth movement increased as force level was increased. This increase was more prominent in the models with smaller degrees of HBL. By using finite element method and bone remodeling theories, this study indicated that in the presence of HBL, under the same load, long-term orthodontic tooth movement will increase. The simulation also revealed that even though tooth movement increases with increasing the force, this increase was only prominent in the models with smaller degrees of HBL, and tooth models with greater degrees of HBL will be less affected by the magnitude of an orthodontic force. Based on our results, the applied force magnitude must be reduced in proportion of degree of HBL.

Keywords: bone remodeling, finite element method, horizontal bone loss, orthodontic tooth movement.

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Authors: David Jurado, Carlos Ávila

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Detection of early signs of breast cancer development is crucial to quickly diagnose the disease and to define adequate treatment to increase the survival probability of the patient. Computer Aided Detection systems (CADs), along with modern data techniques such as Machine Learning (ML) and Neural Networks (NN), have shown an overall improvement in digital mammography cancer diagnosis, reducing the false positive and false negative rates becoming important tools for the diagnostic evaluations performed by specialized radiologists. However, ML and NN-based algorithms rely on datasets that might bring issues to the segmentation tasks. In the present work, an automatic segmentation and detection algorithm is described. This algorithm uses image processing techniques along with the Hough transform to automatically identify microcalcifications that are highly correlated with breast cancer development in the early stages. Along with image processing, automatic segmentation of high-contrast objects is done using edge extraction and circle Hough transform. This provides the geometrical features needed for an automatic mask design which extracts statistical features of the regions of interest. The results shown in this study prove the potential of this tool for further diagnostics and classification of mammographic images due to the low sensitivity to noisy images and low contrast mammographies.

Keywords: breast cancer, segmentation, X-ray imaging, hough transform, image analysis

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Authors: Indu Lata Kanwar, Preeti K. Suresh

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The aim of this study is to fabricate hydroxyapatite based nanocomposites for local drug delivery in periodontal pockets. Hydroxyapatite is chemically similar to the mineral component of bones and hard tissues in mammals. Synthetic biocompatibility and bioactivity with human teeth and bone, making it very attractive for biomedical applications. Nanocomposite is a multiphase solid material where one of the phases has one, two or three dimensions of less than 100 nanometres (nm), or structures having nano­scale repeat distances between the different phases that make up the material. Nanostructured calcium phosphate materials play an important role in the formation of hard tissues in nature. It is reported that calcium phosphates materials in nano-size can mimic the dimensions of constituent components of calcified tissues. Nano-sized materials offer improved performances compared with conventional materials due to their large surface-to-volume ratios. The specific biological properties of the nanocomposites, as well as their interaction with cells, include the use of bioactive molecules. The approach of periodontal tissue engineering is considered promising to restore bone defect through the use of engineered materials with the aim that they will prohibit the invasion of fibrous connective tissue and help repair the function during bone regeneration.

Keywords: bioactive, hydroxyapatite, nanocomposities, periondontal

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Authors: Noureddine Henka, Sami Tazi, Mohamad Assaad

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The electrical grid is a highly intricate system designed to transfer electricity from production areas to consumption areas. The Transmission System Operator (TSO) is responsible for ensuring the efficient distribution of electricity and maintaining the grid's safety and quality. However, due to the increasing integration of intermittent renewable energy sources, there is a growing level of uncertainty, which requires a faster responsive approach. A potential solution involves the use of electrical segmentation, which involves creating coherence zones where electrical disturbances mainly remain within the zone. Indeed, by means of coherent electrical zones, it becomes possible to focus solely on the sub-zone, reducing the range of possibilities and aiding in managing uncertainty. It allows faster execution of operational processes and easier learning for supervised machine learning algorithms. Electrical segmentation can be applied to various applications, such as electrical control, minimizing electrical loss, and ensuring voltage stability. Since the electrical grid can be modeled as a graph, where the vertices represent electrical buses and the edges represent electrical lines, identifying coherent electrical zones can be seen as a clustering task on graphs, generally called community detection. Nevertheless, a critical criterion for the zones is their ability to remain resilient to the electrical evolution of the grid over time. This evolution is due to the constant changes in electricity generation and consumption, which are reflected in graph structure variations as well as line flow changes. One approach to creating a resilient segmentation is to design robust zones under various circumstances. This issue can be represented through a multiplex graph, where each layer represents a specific situation that may arise on the grid. Consequently, resilient segmentation can be achieved by conducting community detection on this multiplex graph. The multiplex graph is composed of multiple graphs, and all the layers share the same set of vertices. Our proposal involves a model that utilizes a unified representation to compute a flattening of all layers. This unified situation can be penalized to obtain (K) connected components representing the robust electrical segmentation clusters. We compare our robust segmentation to the segmentation based on a single reference situation. The robust segmentation proves its relevance by producing clusters with high intra-electrical perturbation and low variance of electrical perturbation. We saw through the experiences when robust electrical segmentation has a benefit and in which context.

Keywords: community detection, electrical segmentation, multiplex graph, power grid

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Authors: Kenan Morani, Esra Kaya Ayana

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This study aimed to develop a novel pipeline for COVID-19 detection using a large and rigorously annotated database of computed tomography (CT) images. The pipeline consists of UNet-based segmentation, lung extraction, and a classification part, with the addition of optional slice removal techniques following the segmentation part. In this work, a batch normalization was added to the original UNet model to produce lighter and better localization, which is then utilized to build a full pipeline for COVID-19 diagnosis. To evaluate the effectiveness of the proposed pipeline, various segmentation methods were compared in terms of their performance and complexity. The proposed segmentation method with batch normalization outperformed traditional methods and other alternatives, resulting in a higher dice score on a publicly available dataset. Moreover, at the slice level, the proposed pipeline demonstrated high validation accuracy, indicating the efficiency of predicting 2D slices. At the patient level, the full approach exhibited higher validation accuracy and macro F1 score compared to other alternatives, surpassing the baseline. The classification component of the proposed pipeline utilizes a convolutional neural network (CNN) to make final diagnosis decisions. The COV19-CT-DB dataset, which contains a large number of CT scans with various types of slices and rigorously annotated for COVID-19 detection, was utilized for classification. The proposed pipeline outperformed many other alternatives on the dataset.

Keywords: classification, computed tomography, lung extraction, macro F1 score, UNet segmentation

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Authors: Joanna Maj, Awais Hussain, Lyndsey Vu, Catherine Roxas

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Background: Bone injuries in babies are common conditions that arise during delivery. Fractures of the clavicle, humerus, femur, and skull are the most common neonatal bone injuries sustained from labor and delivery. During operative deliveries, zealous tractions, ineffective delivery techniques, improper uterine incision, and inadequate relaxation of the uterus can lead to bone fractures in the newborn. Neonatal anatomy is unique. Just as children are not mini-adults, newborns are not mini children. A newborn’s anatomy and physiology are significantly different from a pediatric patient's. In this paper, we describe common orthopedic trauma in newborn babies. We provide a comprehensive overview of the different types of bone injuries in newborns. We hypothesize that the rate of bone fractures sustained at birth is higher in cases of operative deliveries. Methods: Relevant literature was selected by using the PubMed database. Search terms included orthopedic conditions in newborns, neonatal anatomy, and bone fractures in neonates during operative deliveries. Inclusion criteria included age, gender, race, type of bone injury and progression of bone injury. Exclusion criteria were limited in the medical history of cases reviewed and comorbidities. Results: This review finds that a clavicle fracture is the most common type of neonatal orthopedic injury sustained at birth in both operative and non-operative deliveries. We confirm the hypothesis that infants born via operative deliveries have a significantly higher rate of bone fractures than non-cesarean section deliveries. Conclusion: Newborn babies born via operative deliveries have a higher rate of bone fractures of the clavicle, humerus, and femur. A clavicle bone fracture in newborns is most common during emergency operative deliveries in new mothers. We conclude that infants born via an operative delivery sustained more bone injuries than infants born via non-cesarean section deliveries.

Keywords: clavicle fracture, humerus fracture, neonates, newborn orthopedics, orthopedic surgery, pediatrics, orthopedic trauma, orthopedic trauma during delivery, cesarean section, obstetrics, neonatal anatomy, neonatal fractures, operative deliveries, labor and delivery, bone injuries in neonates

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Authors: Hye Kyung Kim, Myung-Gyou Kim, Kang-Hyun Leem

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Postmenopausal osteoporosis is characterized by low bone density which leads to increased bone fragility and greater susceptibility to fracture. Current treatments for osteoporosis are dominated by drugs that inhibit bone resorption although they also suppress bone formation that may contribute to pathogenesis of osteonecrosis. To restore the extensive bone loss, there is a great need for anabolic treatments that induce osteoblasts to build new bone. Pre-osteoblastic cells produce proteins of the extra-cellular matrix, including type I collagen at first, and then to successively produce alkaline phosphatase (ALP) and osteocalcin during differentiation to osteoblasts. Finally, osteoblasts deposit calcium. Present study investigated the effects of egg yolk peptide (EYP) on osteogenic activities and bone matrix gene expressions in human osteoblastic MG-63 cells. The effects of EYP on cell proliferation, alkaline phosphatase (ALP) activity, collagen synthesis, and mineralization were measured. The expression of osteogenic genes including COL1A1 (collagen, type I, alpha 1), ALP, BGLAP (osteocalcin), and SPP1 (secreted phosphoprotein 1, osteopontin) were measured by quantitative realtime PCR. EYP dose-dependently increased MG-63 cell proliferation, ALP activity, collagen synthesis, and calcium deposition. Furthermore, COL1A1, ALP, and SPP1 gene expressions were increased by EYP treatment. Present study suggested that EYP treatment enhanced osteogenic activities and increased bone matrix osteogenicgenes. These results could provide a mechanistic explanation for the bone-strengthening effects of EYP.

Keywords: egg yolk peptide, osteoblastic MG-63 cells, alkaline phosphatase, collagen synthesis, osteogenic genes, COL1A1, osteocalcin, osteopontin

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Authors: Rik van Leeuwen, Ger Koole

Abstract:

Within hospitality, marketing departments use segmentation to create tailored strategies to ensure personalized marketing. This study provides a data-driven approach by segmenting guest profiles via hierarchical clustering based on an extensive set of features. The industry requires understandable outcomes that contribute to adaptability for marketing departments to make data-driven decisions and ultimately driving profit. A marketing department specified a business question that guides the unsupervised machine learning algorithm. Features of guests change over time; therefore, there is a probability that guests transition from one segment to another. The purpose of the study is to provide steps in the process from raw data to actionable insights, which serve as a guideline for how hospitality companies can adopt an algorithmic approach.

Keywords: hierarchical cluster analysis, hospitality, market segmentation

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Authors: Abbas Al-Refaie, Nour Bata

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A distributor of Apple products' experiences numerous difficulties in developing marketing strategies for new and existing mobile product entries that maximize customer satisfaction and the firm's profitability. This research, therefore, integrates market segmentation in platform-based product family design and conjoint analysis to identify iSystem combinations that increase customer satisfaction and business profits. First, the enhanced market segmentation grid is created. Then, the estimated demand model is formulated. Finally, the profit models are constructed then used to determine the ideal product family design that maximizes profit. Conjoint analysis is used to explore customer preferences with their satisfaction levels. A total of 200 surveys are collected about customer preferences. Then, simulation is used to determine the importance values for each attribute. Finally, sensitivity analysis is conducted to determine the product family design that maximizes both objectives. In conclusion, the results of this research shall provide great support to Apple distributors in determining the best marketing strategies that enhance their market share.

Keywords: market segmentation, conjoint analysis, market strategies, optimization

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Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan

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The most aggressive form of brain tumor is called glioma. Glioma is kind of tumor that arises from glial tissue of the brain and occurs quite often. A fully automatic 2D-CNN model for brain tumor segmentation is presented in this paper. We performed pre-processing steps to remove noise and intensity variances using N4ITK and standard intensity correction, respectively. We used Keras open-source library with Theano as backend for fast implementation of CNN model. In addition, we used BRATS 2015 MRI dataset to evaluate our proposed model. Furthermore, we have used SimpleITK open-source library in our proposed model to analyze images. Moreover, we have extracted random 2D patches for proposed 2D-CNN model for efficient brain segmentation. Extracting 2D patched instead of 3D due to less dimensional information present in 2D which helps us in reducing computational time. Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.77 for complete, 0.76 for core, 0.77 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

Keywords: brain tumor segmentation, convolutional neural networks, deep learning, LGG

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Authors: Al-Nouri Doha Mostfa, Al-Khalifa Abdulrahman Salih

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The effects of long-term supplementation with different dietary omega-6/omega-3 (ω-6/ω-3) polyunsaturated fatty acid (PUFAs) ratios on the bone marrow fatty acids level, plasma biomarkers of bone metabolism, and minerals content in bone were evaluated in rabbits. Weanling male and female New Zealand white rabbits were randomly assigned to five groups and fed ad libitum for 100 days on diets containing 70 g/kg different dietary oils which providing the following ω-6/ω-3 ratios: soy bean oil (SBO control, 8.68), sesame oil (SO, 21.75), fish oil (FO, 0.39), DHA algae oil (DHA, 0.63), and DHA and ARA algae oils (DHA/ARA, 0.68). The bone marrow arachidonic (ARA), eicosapentaenoic (EPA), and docosahexaenoic (DHA) fatty acid levels were significantly influenced by and reflected the dietary ω-6/ω-3 ratios fed to rabbits. Rabbits fed on the FO diet maintained a lower ω-6/ω-3 ratio and a higher EPA and DHA levels, those fed on the DHA/ARA diet maintained a lower ω-6/ω-3 ratio and a higher ARA level, while those fed on the SO diet maintained a higher ω-6/ω-3 ratio and a lower ARA level. Plasma alkaline phosphatase (ALP) activity was significantly higher in male and female rabbits fed the DHA/ARA diet compared with those fed the control, SO, FO, or DHA diets. There was a significant main effect of dietary treatment on femur calcium (Ca), phosphorous (P), magnesium (Mg), and zinc (Zn) contents in both genders. This study confirmed that different dietary oil sources with varying ω-6/ω-3 ratios significantly altered the fatty acids level of bone marrow. In addition, the significant elevation in minerals content and the maintenance of optimal Ca/P ratio in bone of DHA/ARA and DHA fed groups beside the significant elevation in ALP activity in the DHA/ARA fed group proved that marine algae oils may be promising dietary sources for promoting bone mineralization and formation, thus improving bone mass during the growth stage.

Keywords: arachidonic (ARA), docosahexaenoic (DHA), eicosapentaenoic (EPA), growing rabbits

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Authors: Seynabou Toure, Oumar Diop, Kidiyo Kpalma, Amadou S. Maiga

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Color and texture are the two most determinant elements for perception and recognition of the objects in an image. For this reason, color and texture analysis find a large field of application, for example in image classification and segmentation. But, the pioneering work in texture analysis was conducted on grayscale images, thus discarding color information. Many grey-level texture descriptors have been proposed and successfully used in numerous domains for image classification: face recognition, industrial inspections, food science medical imaging among others. Taking into account color in the definition of these descriptors makes it possible to better characterize images. Color texture is thus the subject of recent work, and the analysis of color texture images is increasingly attracting interest in the scientific community. In optical remote sensing systems, sensors measure separately different parts of the electromagnetic spectrum; the visible ones and even those that are invisible to the human eye. The amounts of light reflected by the earth in spectral bands are then transformed into grayscale images. The primary natural colors Red (R) Green (G) and Blue (B) are then used in mixtures of different spectral bands in order to produce RGB images. Thus, good color texture discrimination can be achieved using RGB under controlled illumination conditions. Some previous works investigate the effect of using different color space for color texture classification. However, the selection of the best performing color space in land-sea segmentation is an open question. Its resolution may bring considerable improvements in certain applications like coastline detection, where the detection result is strongly dependent on the performance of the land-sea segmentation. The aim of this paper is to present the results of a study conducted on different color spaces in order to show the best-performing color space for land-sea segmentation. In this sense, an experimental analysis is carried out using five different color spaces (RGB, XYZ, Lab, HSV, YCbCr). For each color space, the Haar wavelet decomposition is used to extract different color texture features. These color texture features are then used for Fusion of Over Segmentation (FOOS) based classification; this allows segmentation of the land part from the sea one. By analyzing the different results of this study, the HSV color space is found as the best classification performance while using color and texture features; which is perfectly coherent with the results presented in the literature.

Keywords: classification, coastline, color, sea-land segmentation

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Authors: Sizhu Wang, Cuisong Tang, Lin Zhang, Guangyu Tang

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Objective: We aimed to detect the composition of bone marrow fatty acids early after ovariectomized (OVX) surgery and explore the potential mechanism. Methods: Thirty-two female Sprague-Dawley (SD) rats (12 weeks) were randomly divided into OVX group and Sham group (N=16/group), and received ovariectomy or sham surgery respectively. After 3 and 28 days, eight rats in each group were sacrificed to detect the composition of bone marrow fatty acids by gas chromatography–mass spectrometry (GC–MS) and evaluate the trabecular bone microarchitecture by micro-CT. Significant different fatty acids in the early stage of post-menopausal osteoporosis were selected by OPLS-DA and t test. Then selected fatty acids were further studied in the process of osteogenic differentiation through RT-PCR and Alizarin Red S staining. Results: An apparent sample clustering and group separation were observed between OVX group and sham group three days after surgery, which suggested the role of bone marrow fatty acids in the early stage of postmenopausal osteoporosis. Specifically, myristate, palmitoleate and arachidonate were found to play an important role in classification between OVX group and sham group. We further investigated the effect of palmitoleate and arachidonate on osteogenic differentiation and found that palmitoleate promoted the osteogenic differentiation of MC3T3-E1 cells while arachidonate inhibited this process. Conclusion: Profound bone marrow fatty acids changes have taken place in the early stage of post-menopausal osteoporosis. Bone marrow fatty acids may begin to affect osteogenic differentiation shortly after deficiency of estrogen.

Keywords: bone marrow fatty acids, GC-MS, osteoblast, osteoporosis, post-menopausal

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Authors: Laila Montaser, Hala Gabr, Maha El-Bassuony, Gehan Tawfeek

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Orthotropic liver transplantation (OLT) is the final procedure of both end stage and metabolic liver diseases. Hepatocyte transplantation is an alternative for OLT, but the sources of hepatocytes are limited. Bone marrow mesenchymal stem cells (BM-MSCs) can differentiate into hepatocyte-like cells and are a potential alternative source for hepatocytes. The MSCs from bone marrow are a promising target population as they are capable of differentiating along multiple lineages and, at least in vitro, have significant expansion capability. MSCs from bone marrow may have the potential to differentiate in vitro and in vivo into hepatocytes. Our study examined whether mesenchymal stem cells (MSCs), which are stem cells originated from human bone marrow, are able to differentiate into functional hepatocyte-like cells in vitro. Our aim was to investigate the differentiation potential of BM-MSCs into hepatocyte-like cells. Adult stem cell therapy could solve the problem of degenerative disorders, including liver disease.

Keywords: bone marrow, differentiation, hepatocyte, stem cells

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Authors: Dong Nyoung Heo, Il Keun Kwon

Abstract:

Three-dimensional (3D) technology is a promising method for bone tissue engineering. In order to enhance bone tissue regeneration, it is important to have ideal 3D constructs with biomimetic mechanical strength, structure interconnectivity, roughened surface, and the presence of chemical functionality. In this respect, a 3D printing system combined with cold atmospheric plasma (CAP) was developed to fabricate a 3D construct that has a rough surface with polar functional chemical groups. The CAP-etching process leads to oxidation of chemical groups existing on the polycaprolactone (PCL) surface without conformational change. The surface morphology, chemical composition, mean roughness of the CAP-treated PCL surfaces were evaluated. 3D printed constructs composed of CAP-treated PCL showed an effective increment in the hydrophilicity and roughness of the PCL surface. Also, an in vitro study revealed that CAP-treated 3D PCL constructs had higher cellular behaviors such as cell adhesion, cell proliferation, and osteogenic differentiation. Therefore, a 3D printing system with CAP can be a highly useful fabrication method for bone tissue regeneration.

Keywords: bone tissue engineering, cold atmospheric plasma, PCL, 3D printing

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Authors: Görkem Cemali̇, Avram Aruh, Gamze Torun Köse, Erde Can ŞAfak

Abstract:

In order to heal bone disorders, the conventional methods which involve the use of autologous and allogenous bone grafts or permanent implants have certain disadvantages such as limited supply, disease transmission, or adverse immune response. A biodegradable material that acts as structural support to the damaged bone area and serves as a scaffold that enhances bone regeneration and guides bone formation is one desirable solution. Poly(propylene fumarate) (PPF) which is an unsaturated polyester that can be copolymerized with appropriate vinyl monomers to give biodegradable network structures, is a promising candidate polymer to prepare bone tissue engineering scaffolds. In this study, hydroxyl-terminated PPF was synthesized and thermally cured with vinyl phosphonic acid (VPA) and diethyl vinyl phosphonate (VPES) in the presence of radical initiator benzoyl peroxide (BP), with changing co-monomer weight ratios (10-40wt%). In addition, the synthesized PPF was cured with VPES comonomer at body temperature (37oC) in the presence of BP initiator, N, N-Dimethyl para-toluidine catalyst and varying amounts of Beta-tricalcium phosphate (0-20 wt% ß-TCP) as filler via radical polymerization to prepare composite materials that can be used in injectable forms. Thermomechanical properties, compressive properties, hydrophilicity and biodegradability of the PPF/VPA and PPF/VPES copolymers were determined and analyzed with respect to the copolymer composition. Biocompatibility of the resulting polymers and their composites was determined by the MTS assay and osteoblast activity was explored with von kossa, alkaline phosphatase and osteocalcin activity analysis and the effects of VPA and VPES comonomer composition on these properties were investigated. Thermally cured PPF/VPA and PPF/VPES copolymers with different compositions exhibited compressive modulus and strength values in the wide range of 10–836 MPa and 14–119 MPa, respectively. MTS assay studies showed that the majority of the tested compositions were biocompatible and the overall results indicated that PPF/VPA and PPF/VPES network polymers show significant potential for applications as bone tissue engineering scaffolds where varying PPF and co-monomer ratio provides adjustable and controllable properties of the end product. The body temperature cured PPF/VPES/ß-TCP composites exhibited significantly lower compressive modulus and strength values than the thermal cured PPF/VPES copolymers and were therefore found to be useful as scaffolds for cartilage tissue engineering applications.

Keywords: biodegradable, bone tissue, copolymer, poly(propylene fumarate), scaffold

Procedia PDF Downloads 144