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Detta examensarbete skapades med målet att undersöka skillnader i preferensen gällande arpeggios i NES- och Famicom-musik baserat på kultur. Bakgrundskapitlet tar upp tidigare forskning inom tangentiella ämnen, samt beskriver arpeggios och hur NES- och Famicom-konsolerna är uppbyggda. En kvantitativ metod utvecklas sedan, och problematiseras. Detta följs av en beskrivning av det förarbete som gjordes, och skapandet av de två artefakter som användes. En enkät genomfördes efter förarbetet, och resultatet av denna analyseras därefter i rapporten. Resultatet visar på att det finns vissa skillnader i preferens mellan svenska och japanska lyssnare. Denna slutsats, samt resterande delar av rapporten diskuteras sedan och till sist skrivs det om framtida arbete, så som att en plug-in möjligtvis skulle kunna skapas efter detta arbete har gjorts. Denna plugin skulle göra det lättare att få musik att låta mer europeisk eller japansk.

We present a combined report on the results of three editions of the Cell Tracking Challenge, an ongoing initiative aimed at promoting the development and objective evaluation of cell segmentation and tracking algorithms. With 21 participating algorithms and a data repository consisting of 13 data sets from various microscopy modalities, the challenge displays today's state-of-the-art methodology in the field. We analyzed the challenge results using performance measures for segmentation and tracking that rank all participating methods. We also analyzed the performance of all of the algorithms in terms of biological measures and practical usability. Although some methods scored high in all technical aspects, none obtained fully correct solutions. We found that methods that either take prior information into account using learning strategies or analyze cells in a global spatiotemporal video context performed better than other methods under the segmentation and tracking scenarios included in the challenge., QC 20180111

QC 20171115

In this paper, we have developed tools to analyze prokaryotic cells growing in monolayers in a microfluidic device. Individual bacterial cells are identified using a novel curvature based approach and tracked over time for several generations. The resulting tracks are thereafter assessed and filtered based on track quality for subsequent analysis of bacterial growth rates. The proposed method performs comparable to the state-of-the-art methods for segmenting phase contrast and fluorescent images, and we show a 10-fold increase in analysis speed., eSSENCE

In this paper, we have developed tools to analyze prokaryotic cells growing in monolayers in a microfluidic device. Individual bacterial cells are identified using a novel curvature based approach and tracked over time for several generations. The resulting tracks are thereafter assessed and filtered based on track quality for subsequent analysis of bacterial growth rates. The proposed method performs comparable to the state-of-the-art methods for segmenting phase contrast and fluorescent images, and we show a 10-fold increase in analysis speed., QC 20160303

Automated tracking of living cells in microscopy image sequences is an important and challenging problem. With this application in mind, we propose a global track linking algorithm, which links cell outlines generated by a segmentation algorithm into tracks. The algorithm adds tracks to the image sequence one at a time, in a way which uses information from the complete image sequence in every linking decision. This is achieved by finding the tracks which give the largest possible increases to a probabilistically motivated scoring function, using the Viterbi algorithm. We also present a novel way to alter previously created tracks when new tracks are created, thus mitigating the effects of error propagation. The algorithm can handle mitosis, apoptosis, and migration in and out of the imaged area, and can also deal with false positives, missed detections, and clusters of jointly segmented cells. The algorithm performance is demonstrated on two challenging datasets acquired using bright-field microscopy, but in principle, the algorithm can be used with any cell type and any imaging technique, presuming there is a suitable segmentation algorithm., QC 20150518

We present a global tracking algorithm for tracking particles with dynamic motion models. The tracking algorithm augments a existing global track linking algorithm based on the Viterbi algorithm with a Gaussian Mixture Probability Hypothesis Density filter. This allows the tracking algorithm to use the target velocities to link tracks. The algorithm can handle clutter, missed detections, and random appearance and disappearance of particles in the field of view. The algorithm can also handle targets that switch between different motion models according to a Markov process. The algorithm is evaluated on the synthetic datasets used in the ISBI 2012 Particle Tracking Challenge, which simulate vesicles, receptors, microtubules, and viruses at different particle densities and signal to noise ratios. The evaluation shows that our algorithm performs well across a wide range of particle tracking problems in both 2D and 3D., QC 20160316

Particle tracking is of key importance for quantitative analysis of intracellular dynamic processes from time-lapse microscopy image data. Because manually detecting and following large numbers of individual particles is not feasible, automated computational methods have been developed for these tasks by many groups. Aiming to perform an objective comparison of methods, we gathered the community and organized an open competition in which participating teams applied their own methods independently to a commonly defined data set including diverse scenarios. Performance was assessed using commonly defined measures. Although no single method performed best across all scenarios, the results revealed clear differences between the various approaches, leading to notable practical conclusions for users and developers., QC 20140425

The goal of regenerative medicine is to restore form and function to damaged and aging tissues. Adult stem cells, present in tissues such as skeletal muscle, comprise a reservoir of cells with a remarkable capacity to proliferate and repair tissue damage. Muscle stem cells, known as satellite cells, reside in a quiescent state in an anatomically distinct compartment, or niche, ensheathed between the membrane of the myofiber and the basal lamina. Recently, procedures for isolating satellite cells were developed and experiments testing their function upon transplantation into muscles revealed an extraordinary potential to contribute to muscle fibers and access and replenish the satellite cell compartment. However, these properties are rapidly lost once satellite cells are plated in culture. Accordingly, elucidating the role of extrinsic factors in controlling muscle stem cell fate, in particular self-renewal, is critical. Through careful design of bioengineered culture platforms, analysis of specific proteins presented to stem cells is possible. Critical to the success of the approach is single cell analysis, as more rapidly proliferating progenitors may mask the behavior of stem cells that proliferate slowly. Bioengineering approaches provide a potent means of gaining insight into the role of extrinsic factors in the stem cell microenvironment on stem cell function and the mechanisms that control their diverse fates. Ultimately, the multidisciplinary approach presented here will lead to novel therapeutic strategies for degenerative diseases., QC 20120424

Advances in microscope hardware in the last couple of decades have made it possible to acquire large data sets with image sequences of living cells grown in cell culture. This has led to a demand for automated ways of analyzing the acquired images. This article presents a new algorithm for tracking cells and constructing cell lineages in such image sequences. The algorithm uses information from the entire sequence to make local decisions about cell tracks and can therefore make more robust decisions than algorithms that process the data sequentially. It also incorporates image-based likelihoods of cell division and cell death into the tracking, without having to resort to separate detection algorithms or post processing of tracks. The algorithm consists of a scoring function to rank tracks and an iterative algorithm that searches for the highest scoring tracks, in a computationally efficient way, using the Viterbi algorithm., QC 20120905

Stem cells that naturally reside in adult tissues, such as muscle stem cells (MuSCs), exhibit robust regenerative capacity in vivo that is rapidly lost in culture. Using a bioengineered substrate to recapitulate key biophysical and biochemical niche features in conjunction with a highly automated single-cell tracking algorithm, we show that substrate elasticity is a potent regulator of MuSC fate in culture. Unlike MuSCs on rigid plastic dishes (similar to 10(6) kilopascals), MuSCs cultured on soft hydrogel substrates that mimic the elasticity of muscle (12 kilopascals) self-renew in vitro and contribute extensively to muscle regeneration when subsequently transplanted into mice and assayed histologically and quantitatively by noninvasive bioluminescence imaging. Our studies provide novel evidence that by recapitulating physiological tissue rigidity, propagation of adult muscle stem cells is possible, enabling future cell-based therapies for muscle-wasting diseases., QC 20101206

Methods are provided for the ex vivo manipulation of cells, stem cells and other reproductive cells, by manipulating the cells in a container or device comprising an elastic substrate, wherein the substrate has an elasticity that mimics the elasticity of a native microenvironment of the cell., QS 2014

This paper describes several algorithms for generating an optimal schedule for multiple access on a shared channel by utilizing range information in a fully connected network. We also provide detailed analysis for the proposed algorithms in terms of their complexity, convergence, and effect of non-idealities in the network. The performance of the proposed schemes are compared with non-aided methods to quantify the benefits of using the range information in the communication. We argue that the proposed techniques yield significant benefits as the number of nodes in the network increases. We provide simulation results in support of the claim. The proposed methods indicate that the throughput can be increased on average by 3-10 times for typical network configurations., QS 2016

Natural killer (NK) cell cytotoxicity is highly dependent on the ability of NK cells to migrate through the extracellular matrix (ECM) microenvironment. Traditional imaging studies of NK cell migration and cytotoxicity have utilized 2-D surfaces, which do not properly reproduce the structural and mechanical cues that shape the migratory response of NK cells in vivo. In addition, current in vivo imaging does not allow for the accurate long-term single-cell imaging required to dissect the functional heterogeneity of NK cell populations, and importantly, it does not allow studies of human cells. Therefore, it is desirable to implement in vitro migration and killing assays that better mimic in vivo conditions. We have combined a microwell assay that allows long-term imaging and tracking of small, well-defined populations of NK cells with an interstitial ECM-like matrix to more closely approximate in vivo conditions. The microwells, which are loaded with a gel mixture containing NK and target cells, allows for long-term imaging of NK–target cell interactions within a confined 3-D volume. The microwells were optically sectioned by confocal fluorescence microscopy once every 2 min for 12 h. NK cells were tracked by the Baxter Algorithms to assess motility parameters and interactions with target cells were manually scored for duration and outcome. We found marked differences in motility between individual cells with a significant fraction of the cells moving slowly and being confined to a small area within the matrix, while other cells moved more freely, probably reflecting local variations in the matrix structure and inherent difference in motility between individual cells. A majority of NK cells also exhibited transient variation in their mobility alternating between periods of migration arrest and random movement. NK cells that alternated between different modes of migration switched on average once every 3 h. NK cells made fewer and shorter contacts with target cells th, QCR 20170109

This paper describes several algorithms for generating an optimal schedule for multiple access on a shared channel by utilizing range information in a fully connected network. We also provide detailed analysis for the proposed algorithms in terms of their complexity, convergence, and effect of non-idealities in the network. The performance of the proposed schemes are compared with non-aided methods to quantify the benefits of using the range information in the communication. We argue that the proposed techniques yield significant benefits as the number of nodes in the network increases. We provide simulation results in support of the claim. The proposed methods indicate that the throughput can be increased on average by 3-10 times for typical network configurations., QS 2016

We present a combined report on the results of three editions of the Cell Tracking Challenge, an ongoing initiative aimed at promoting the development and objective evaluation of cell segmentation and tracking algorithms. With 21 participating algorithms and a data repository consisting of 13 data sets from various microscopy modalities, the challenge displays today's state-of-the-art methodology in the field. We analyzed the challenge results using performance measures for segmentation and tracking that rank all participating methods. We also analyzed the performance of all of the algorithms in terms of biological measures and practical usability. Although some methods scored high in all technical aspects, none obtained fully correct solutions. We found that methods that either take prior information into account using learning strategies or analyze cells in a global spatiotemporal video context performed better than other methods under the segmentation and tracking scenarios included in the challenge.

We present a combined report on the results of three editions of the Cell Tracking Challenge, an ongoing initiative aimed at promoting the development and objective evaluation of cell segmentation and tracking algorithms. With 21 participating algorithms and a data repository consisting of 13 data sets from various microscopy modalities, the challenge displays today's state-of-the-art methodology in the field. We analyzed the challenge results using performance measures for segmentation and tracking that rank all participating methods. We also analyzed the performance of all of the algorithms in terms of biological measures and practical usability. Although some methods scored high in all technical aspects, none obtained fully correct solutions. We found that methods that either take prior information into account using learning strategies or analyze cells in a global spatiotemporal video context performed better than other methods under the segmentation and tracking scenarios included in the challenge.

We present a combined report on the results of three editions of the Cell Tracking Challenge, an ongoing initiative aimed at promoting the development and objective evaluation of cell segmentation and tracking algorithms. With 21 participating algorithms and a data repository consisting of 13 data sets from various microscopy modalities, the challenge displays today's state-of-the-art methodology in the field. We analyzed the challenge results using performance measures for segmentation and tracking that rank all participating methods. We also analyzed the performance of all of the algorithms in terms of biological measures and practical usability. Although some methods scored high in all technical aspects, none obtained fully correct solutions. We found that methods that either take prior information into account using learning strategies or analyze cells in a global spatiotemporal video context performed better than other methods under the segmentation and tracking scenarios included in the challenge.

We present a combined report on the results of three editions of the Cell Tracking Challenge, an ongoing initiative aimed at promoting the development and objective evaluation of cell segmentation and tracking algorithms. With 21 participating algorithms and a data repository consisting of 13 data sets from various microscopy modalities, the challenge displays today's state-of-the-art methodology in the field. We analyzed the challenge results using performance measures for segmentation and tracking that rank all participating methods. We also analyzed the performance of all of the algorithms in terms of biological measures and practical usability. Although some methods scored high in all technical aspects, none obtained fully correct solutions. We found that methods that either take prior information into account using learning strategies or analyze cells in a global spatiotemporal video context performed better than other methods under the segmentation and tracking scenarios included in the challenge.

This paper describes several algorithms for generating an optimal schedule for multiple access on a shared channel by utilizing range information in a fully connected network. We also provide detailed analysis for the proposed algorithms in terms of their complexity, convergence, and effect of non-idealities in the network. The performance of the proposed schemes are compared with non-aided methods to quantify the benefits of using the range information in the communication. We argue that the proposed techniques yield significant benefits as the number of nodes in the network increases. We provide simulation results in support of the claim. The proposed methods indicate that the throughput can be increased on average by 3-10 times for typical network configurations., QS 2016

This paper describes several algorithms for generating an optimal schedule for multiple access on a shared channel by utilizing range information in a fully connected network. We also provide detailed analysis for the proposed algorithms in terms of their complexity, convergence, and effect of non-idealities in the network. The performance of the proposed schemes are compared with non-aided methods to quantify the benefits of using the range information in the communication. We argue that the proposed techniques yield significant benefits as the number of nodes in the network increases. We provide simulation results in support of the claim. The proposed methods indicate that the throughput can be increased on average by 3-10 times for typical network configurations., QS 2016

This paper describes several algorithms for generating an optimal schedule for multiple access on a shared channel by utilizing range information in a fully connected network. We also provide detailed analysis for the proposed algorithms in terms of their complexity, convergence, and effect of non-idealities in the network. The performance of the proposed schemes are compared with non-aided methods to quantify the benefits of using the range information in the communication. We argue that the proposed techniques yield significant benefits as the number of nodes in the network increases. We provide simulation results in support of the claim. The proposed methods indicate that the throughput can be increased on average by 3-10 times for typical network configurations., QS 2016

We present a combined report on the results of three editions of the Cell Tracking Challenge, an ongoing initiative aimed at promoting the development and objective evaluation of cell segmentation and tracking algorithms. With 21 participating algorithms and a data repository consisting of 13 data sets from various microscopy modalities, the challenge displays today's state-of-the-art methodology in the field. We analyzed the challenge results using performance measures for segmentation and tracking that rank all participating methods. We also analyzed the performance of all of the algorithms in terms of biological measures and practical usability. Although some methods scored high in all technical aspects, none obtained fully correct solutions. We found that methods that either take prior information into account using learning strategies or analyze cells in a global spatiotemporal video context performed better than other methods under the segmentation and tracking scenarios included in the challenge.