Automated segmentation of multiple red blood cells with digital holographic microscopy.

We present a method to automatically segment red blood cells (RBCs) visualized by digital holographic microscopy (DHM), which is based on the marker-controlled watershed algorithm. Quantitative phase images of RBCs can be obtained by using off-axis DHM along to provide some important information about each RBC, including size, shape, volume, hemoglobin content, etc. The most important process of segmentation based on marker-controlled watershed is to perform an accurate localization of internal and external markers. Here, we first obtain the binary image via Otsu algorithm. Then, we apply morphological operations to the binary image to get the internal markers. We then apply the distance transform algorithm combined with the watershed algorithm to generate external markers based on internal markers. Finally, combining the internal and external markers, we modify the original gradient image and apply the watershed algorithm. By appropriately identifying the internal and external markers, the problems of oversegmentation and undersegmentation are avoided. Furthermore, the internal and external parts of the RBCs phase image can also be segmented by using the marker-controlled watershed combined with our method, which can identify the internal and external markers appropriately. Our experimental results show that the proposed method achieves good performance in terms of segmenting RBCs and could thus be helpful when combined with an automated classification of RBCs.

Automatic Segmentation of the Eye in 3D Magnetic Resonance Imaging: A Novel Statistical Shape Model for Treatment Planning of Retinoblastoma.

PURPOSE: Proper delineation of ocular anatomy in 3-dimensional (3D) imaging is a big challenge, particularly when developing treatment plans for ocular diseases. Magnetic resonance imaging (MRI) is presently used in clinical practice for diagnosis confirmation and treatment planning for treatment of retinoblastoma in infants, where it serves as a source of information, complementary to the fundus or ultrasonographic imaging. Here we present a framework to fully automatically segment the eye anatomy for MRI based on 3D active shape models (ASM), and we validate the results and present a proof of concept to automatically segment pathological eyes. METHODS AND MATERIALS: Manual and automatic segmentation were performed in 24 images of healthy children's eyes (3.29 ± 2.15 years of age). Imaging was performed using a 3-T MRI scanner. The ASM consists of the lens, the vitreous humor, the sclera, and the cornea. The model was fitted by first automatically detecting the position of the eye center, the lens, and the optic nerve, and then aligning the model and fitting it to the patient. We validated our segmentation method by using a leave-one-out cross-validation. The segmentation results were evaluated by measuring the overlap, using the Dice similarity coefficient (DSC) and the mean distance error. RESULTS: We obtained a DSC of 94.90 ± 2.12% for the sclera and the cornea, 94.72 ± 1.89% for the vitreous humor, and 85.16 ± 4.91% for the lens. The mean distance error was 0.26 ± 0.09 mm. The entire process took 14 seconds on average per eye. CONCLUSION: We provide a reliable and accurate tool that enables clinicians to automatically segment the sclera, the cornea, the vitreous humor, and the lens, using MRI. We additionally present a proof of concept for fully automatically segmenting eye pathology. This tool reduces the time needed for eye shape delineation and thus can help clinicians when planning eye treatment and confirming the extent of the tumor.

Exploring Different Types of Sharing: A Proposed Segmentation of the Market for "Sharing Businesses"

Sharing instead of buying is regaining traction among today's consumers. This study aims at identifying segments of sharing consumers to unearth potentially viable clusters of a consumer behavior that is a market of growing economic relevance. By means of a qualitative study and a survey with a roughly representative sample of 1121 Swiss-German and German consumers, a set of trait-related, motivational, and perceived socioeconomic variables is identified that can be used to group individuals into segments that differ with regard to their approach to sharing. A cluster analysis based on these variables suggests four potential clusters of sharing consumers-sharing idealists, sharing opponents, sharing pragmatists, and sharing normatives. Two sets of testable propositions are derived that can guide further research in this domain and pave the way to a more targeted approach to the growing market of "sharing" businesses.

The use of tricyclic antidepressants in the treatment of temporomandibular joint disorders: systematic review of the literature of the last 20 years

Many therapies have been proposed for the management of temporomandibular disorders, including the use of different drugs. However, lack of knowledge about the mechanisms behind the pain associated with this pathology, and the fact that the studies carried out so far use highly disparate patient selection criteria, mean that results on the effectiveness of the different medications are inconclusive. This study makes a systematic review of the literature published on the use of tricyclic antidepressants for the treatment of temporomandibular disorders, using the SORT criteria (Strength of recommendation taxonomy) to consider the level of scientific evidence of the different studies. Following analysis of the articles, and in function of their scientific quality, a type B recommendation is given in favor of the use of tricyclic antidepressants for the treatment of temporomandibular disorders.

Treatment of Prosthetic Joint Infections

Prosthetic joint replacement is one of the most successful surgical procedures of the last century and the number of implanted artificial joints is rapidly growing. While the result of the procedure is generally positive, infections may occur leading to patient suffering, surgeon's frustration and important costs to the health system. Infection after prosthetic joint replacement is thus a feared complication as healing rates can be low, functional result poor and satisfaction of the patient abysmal. However, if a patient-adapted treatment of infected total joints is used, an overall success rate of above 90 % can be obtained. The patient-adapted treatment concept is based on five strong pillars: teamwork, understanding biofilm, proper diagnostics, proper definition and classification and patient-tailored treatment.

The Methods of Possible Joint Treatment of Manure and Sewage Sludge in the Leningrad Region

The nutrient load to the Gulf of Finland has started to increase as a result of the strong economic recovery in agriculture and livestock farming in the Leningrad region. Also sludge produced from municipal wastewater treatment plant of the Leningrad region causes the great impact on the environment, but still the main options for its treatment is disposal on the sludge beds or Landfills. The aim of this study was to evaluate the implementation of possible joint treatment methods of manure form livestock and poultry enterprises and sewage sludge produced from municipal wastewater treatment plants in the Leningrad region. The study is based on published data. The most attention was put on the anaerobic digestion and incineration methods. The manure and sewage sludge generation for the whole Leningrad region and energy potential produced from their treatment were estimated. The calculations showed that total amount of sewage sludge generation is 1 348 000 t/a calculated on wet matter and manure generation is 3 445 000 t/a calculated on wet matter. The potential heat release from anaerobic digestion process and incineration process is 4 880 000 GJ/a and 5 950 000 GJ/a, respectively. Furthermore, the work gives the overview of the general Russian and Finnish legislation concerning manure and sewage sludge treatment. In the Gatchina district it was chosen the WWTP and livestock and poultry enterprises for evaluation of the centralized treatment plant implementation based on anaerobic digestion and incineration methods. The electricity and heat power of plant based on biogas combustion process is 4.3 MW and 7.8 MW, respectively. The electricity and heat power of plant based on manure and sewage sludge incineration process is 3.0 MW and 6.1 MW, respectively.

Segmentation of Industrial Customers – Case: Finnish Mechanical Engineering Companies

Segmentointi on perinteisesti ollut erityisesti kuluttajamarkkinoinnin työkalu, mutta siirtymä tuotteista palveluihin on lisännyt segmentointitarvetta myös teollisilla markkinoilla. Tämän tutkimuksen tavoite on löytää selkeästi toisistaan erottuvia asiakasryhmiä suomalaisen liikkeenjohdon konsultointiyritys Synocus Groupin tarjoaman case-materiaalin pohjalta. K-means-klusteroinnin avulla löydetään kolme potentiaalista markkinasegmenttiä perustuen siihen, mitkä tarjoamaelementit 105 valikoitua suomalaisen kone- ja metallituoteteollisuuden asiakasta ovat maininneet tärkeimmiksi. Ensimmäinen klusteri on hintatietoiset asiakkaat, jotka laskevat yksikkökohtaisia hintoja. Toinen klusteri koostuu huolto-orientoituneista asiakkaista, jotka laskevat tuntikustannuksia ja maksimoivat konekannan käyttötunteja. Tälle kohderyhmälle kannattaisi ehkä markkinoida teknisiä palveluja ja huoltosopimuksia. Kolmas klusteri on tuottavuussuuntautuneet asiakkaat, jotka ovat kiinnostuneita suorituskyvyn kehittämisestä ja laskevat tonnikohtaisia kustannuksia. He tavoittelevat alempia kokonaiskustannuksia lisääntyneen suorituskyvyn, pidemmän käyttöiän ja alempien huoltokustannusten kautta.

Segmentation of overlapping convex objects

This thesis presents a framework for segmentation of clustered overlapping convex objects. The proposed approach is based on a three-step framework in which the tasks of seed point extraction, contour evidence extraction, and contour estimation are addressed. The state-of-art techniques for each step were studied and evaluated using synthetic and real microscopic image data. According to obtained evaluation results, a method combining the best performers in each step was presented. In the proposed method, Fast Radial Symmetry transform, edge-to-marker association algorithm and ellipse fitting are employed for seed point extraction, contour evidence extraction and contour estimation respectively. Using synthetic and real image data, the proposed method was evaluated and compared with two competing methods and the results showed a promising improvement over the competing methods, with high segmentation and size distribution estimation accuracy.

Expression of MMP-2 and MMP-9 in the rat trigeminal ganglion during the development of temporomandibular joint inflammation

Orofacial pain is a prevalent symptom in modern society. Some musculoskeletal orofacial pain is caused by temporomandibular disorders (TMDs). This condition has a multi-factorial etiology, including emotional factors and alteration of the masticator muscle and temporomandibular joints (TMJs). TMJ inflammation is considered to be a cause of pain in patients with TMD. Extracellular proteolytic enzymes, specifically the matrix metalloproteinases (MMPs), have been shown to modulate inflammation and pain. The purpose of this investigation was to determine whether the expression and level of gelatinolytic activity of MMP-2 and MMP-9 in the trigeminal ganglion are altered during different stages of temporomandibular inflammation, as determined by gelatin zymography. This study also evaluated whether mechanical allodynia and orofacial hyperalgesia, induced by the injection of complete Freund's adjuvant into the TMJ capsule, were altered by an MMP inhibitor (doxycycline, DOX). TMJ inflammation was measured by plasma extravasation in the periarticular tissue (Evans blue test) and infiltration of polymorphonuclear neutrophils into the synovial fluid (myeloperoxidase enzyme quantification). MMP expression in the trigeminal ganglion was shown to vary during the phases of the inflammatory process. MMP-9 regulated the early phase and MMP-2 participated in the late phase of this process. Furthermore, increases in plasma extravasation in periarticular tissue and myeloperoxidase activity in the joint tissue, which occurred throughout the inflammation process, were diminished by treatment with DOX, a nonspecific MMP inhibitor. Additionally, the increases of mechanical allodynia and orofacial hyperalgesia were attenuated by the same treatment.

Tourist Profiles and Characteristics vis-à-vis Market Segmentation of Ecotourism Destinations in Kerala

Kerala, a classic ecotourism destination in India, provides significant opportunities for livelihood options to the people who depend on the resources from the forest and those who live in difficult terrains. This article analyses the socio-demographic, psychographic and travel behavior patterns and its sub-characteristics in the background of foreign and domestic tourists. The data source for the article has been obtained from a primary survey of 350 randomly chosen tourists, 175 each from domestic and foreign tourists, visiting Kerala’s ecotourists destinations during August-December 2010-11. Several socio-demographic, psychographic and life style factors have been identified based on the inference from field survey. There is considerable divergence in most of the factors identified in the case of domestic and international tourists. Post-trip attributes like satisfaction and intentions to return show that the ecotourism destinations in Kerala have significant potential that can help communities in the region.

Segmentation of Brain Tissue from Magnetic Resonance Images

Segmentation of medical imagery is a challenging problem due to the complexity of the images, as well as to the absence of models of the anatomy that fully capture the possible deformations in each structure. Brain tissue is a particularly complex structure, and its segmentation is an important step for studies in temporal change detection of morphology, as well as for 3D visualization in surgical planning. In this paper, we present a method for segmentation of brain tissue from magnetic resonance images that is a combination of three existing techniques from the Computer Vision literature: EM segmentation, binary morphology, and active contour models. Each of these techniques has been customized for the problem of brain tissue segmentation in a way that the resultant method is more robust than its components. Finally, we present the results of a parallel implementation of this method on IBM's supercomputer Power Visualization System for a database of 20 brain scans each with 256x256x124 voxels and validate those against segmentations generated by neuroanatomy experts.