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Publications (10 of 85) Show all publications
del Aguila Pla, P. & Jaldén, J. (2018). Cell detection on image-based immunoassays. In: 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018): . Paper presented at 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), Washington, DC, USA, April 4-7, 2018 (pp. 431-435). IEEE
Open this publication in new window or tab >>Cell detection on image-based immunoassays
2018 (English)In: 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), IEEE, 2018, p. 431-435Conference paper, Published paper (Refereed)
Abstract [en]

Cell detection and counting in the image-based ELISPOT and Fluorospot immunoassays is considered a bottleneck.The task has remained hard to automatize, and biomedical researchers often have to rely on results that are not accurate.Previously proposed solutions are heuristic, and data-based solutions are subject to a lack of objective ground truth data. In this paper, we analyze a partial differential equations model for ELISPOT, Fluorospot, and assays of similar design. This leads us to a mathematical observation model forthe images generated by these assays. We use this model to motivate a methodology for cell detection. Finally, we provide a real-data example that suggests that this cell detection methodology and a human expert perform comparably.

Place, publisher, year, edition, pages
IEEE, 2018
Keyword
Inverse problems, Optimization, Source localization, Immunoassays
National Category
Signal Processing Medical Image Processing
Research subject
Technology and Health; Electrical Engineering
Identifiers
urn:nbn:se:kth:diva-223933 (URN)10.1109/ISBI.2018.8363609 (DOI)978-1-5386-3636-7 (ISBN)978-1-5386-3637-4 (ISBN)978-1-5386-3635-0 (ISBN)
Conference
2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), Washington, DC, USA, April 4-7, 2018
Funder
Swedish Research Council, 2015-04026
Note

QC 20180611

Available from: 2018-03-15 Created: 2018-03-15 Last updated: 2018-06-11Bibliographically approved
del Aguila Pla, P. & Jaldén, J. (2018). Convolutional group-sparse coding and source localization. In: : . Paper presented at IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), April 15-20, Calgary, Alberta, Canada. IEEE Signal Processing Society
Open this publication in new window or tab >>Convolutional group-sparse coding and source localization
2018 (English)Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we present a new interpretation of non-negativelyconstrained convolutional coding problems as blind deconvolution problems with spatially variant point spread function. In this light, we propose an optimization framework that generalizes our previous work on non-negative group sparsity for convolutional models. We then link these concepts to source localization problems that arise in scientific imaging, and provide a visual example on an image derived from data captured by the Hubble telescope.

Place, publisher, year, edition, pages
IEEE Signal Processing Society, 2018
Keyword
Sparse representation, Source localization, Non-negative group sparsity
National Category
Signal Processing
Research subject
Electrical Engineering; Computer Science
Identifiers
urn:nbn:se:kth:diva-224253 (URN)
Conference
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), April 15-20, Calgary, Alberta, Canada
Funder
Swedish Research Council, 2015-04026
Note

QCR 20180319

Available from: 2018-03-15 Created: 2018-03-15 Last updated: 2018-03-19Bibliographically approved
Ulman, V., Magnusson, K. E. G., Jaldén, J., Ortiz-de-Solorzano, C. & et al., . (2017). An objective comparison of cell-tracking algorithms. Nature Methods, 14(12), 1141-+
Open this publication in new window or tab >>An objective comparison of cell-tracking algorithms
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2017 (English)In: Nature Methods, ISSN 1548-7091, E-ISSN 1548-7105, Vol. 14, no 12, p. 1141-+Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
NATURE PUBLISHING GROUP, 2017
National Category
Biochemistry and Molecular Biology
Identifiers
urn:nbn:se:kth:diva-221073 (URN)10.1038/nmeth.4473 (DOI)000416604800015 ()29083403 (PubMedID)2-s2.0-85036663036 (Scopus ID)
Note

QC 20180111

Available from: 2018-01-11 Created: 2018-01-11 Last updated: 2018-01-11Bibliographically approved
Tarighati, A., Gross, J. & Jaldén, J. (2017). Decentralized Hypothesis Testing in Energy Harvesting Wireless Sensor Networks. IEEE Transactions on Signal Processing, 65(18), 4862-4873
Open this publication in new window or tab >>Decentralized Hypothesis Testing in Energy Harvesting Wireless Sensor Networks
2017 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 65, no 18, p. 4862-4873Article in journal (Refereed) Published
Abstract [en]

We consider the problem of decentralized hypothesis testing in a network of energy harvesting sensors, where sensors make noisy observations of a phenomenon and send quantized information about the phenomenon towards a fusion center. The fusion center makes a decision about the present hypothesis using the aggregate received data during a time interval. We explicitly consider a scenario under which the messages are sent through parallel access channels towards the fusion center. To avoid limited lifetime issues, we assume each sensor is capable of harvesting all the energy it needs for the communication from the environment. Each sensor has an energy buffer (battery) to save its harvested energy for use in other time intervals. Our key contribution is to formulate the problem of decentralized detection in a sensor network with energy harvesting devices. Our analysis is based on a queuing-theoretic model for the battery and we propose a sensor decision design method by considering long term energy management at the sensors. We show how the performance of the system changes for different battery capacities. We then numerically show how our findings can be used in the design of sensor networks with energy harvesting sensors.

Place, publisher, year, edition, pages
IEEE, 2017
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-208654 (URN)10.1109/TSP.2017.2716909 (DOI)000405705900013 ()
Note

QC 20170706

Available from: 2017-06-10 Created: 2017-06-10 Last updated: 2017-08-08Bibliographically approved
Carlsson, H., Skog, I. & Jaldén, J. (2017). On-The-Fly Geometric Calibration of Inertial Sensor Arrays. In: 2017 INTERNATIONAL CONFERENCE ON INDOOR POSITIONING AND INDOOR NAVIGATION (IPIN): . Paper presented at 8th International Conference on Indoor Positioning and Indoor Navigation (IPIN), SEP 18-21, 2017, Sapporo, JAPAN.
Open this publication in new window or tab >>On-The-Fly Geometric Calibration of Inertial Sensor Arrays
2017 (English)In: 2017 INTERNATIONAL CONFERENCE ON INDOOR POSITIONING AND INDOOR NAVIGATION (IPIN), 2017Conference paper, Published paper (Refereed)
Abstract [en]

We present a maximum likelihood estimator for estimating the positions of accelerometers in an inertial sensor array. This method simultaneously estimates the positions of the accelerometers and the motion dynamics of the inertial sensor array and, therefore, does not require a predefined motion sequence nor any external equipment. Using an iterative block coordinate descent optimization strategy, the calibration problem can be solved with a complexity that is linear in the number of time samples. The proposed method is evaluated by Monte-Carlo simulations of an inertial sensor array built out of 32 inertial measurement units. The simulation results show that, if the array experiences sufficient dynamics, the position error is inversely proportional to the number of time samples used in the calibration sequence. Further, results show that for the considered array geometry and motion dynamics in the order of 2000 degrees/s and 2000 degrees/s(2), the positions of the accelerometers can be estimated with an accuracy in the order of 10(-6) m using only 1000 time samples. This enables fast on-the-fly calibration of the geometric errors in an inertial sensor array by simply twisting it by hand for a few seconds.

Series
International Conference on Indoor Positioning and Indoor Navigation, ISSN 2162-7347
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-220651 (URN)000417415600018 ()978-1-5090-6299-7 (ISBN)
Conference
8th International Conference on Indoor Positioning and Indoor Navigation (IPIN), SEP 18-21, 2017, Sapporo, JAPAN
Note

QC 20180111

Available from: 2018-01-11 Created: 2018-01-11 Last updated: 2018-02-20Bibliographically approved
Tarighati, A., Gross, J. & Jaldén, J. (2016). Decentralized Detection in Energy Harvesting Wireless Sensor Networks. In: 2016 24TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO): . Paper presented at 24th European Signal Processing Conference (EUSIPCO), AUG 28-SEP 02, 2016, Budapest, HUNGARY (pp. 567-571). IEEE conference proceedings
Open this publication in new window or tab >>Decentralized Detection in Energy Harvesting Wireless Sensor Networks
2016 (English)In: 2016 24TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO), IEEE conference proceedings, 2016, p. 567-571Conference paper, Published paper (Refereed)
Abstract [en]

We consider a decentralized hypothesis testing problem in which several peripheral energy harvesting sensors are arranged in parallel. Each sensor makes a noisy observation of a time varying phenomenon, and sends a message about the present hypothesis towards a fusion center at each time instance t. The fusion center, using the aggregate of the received messages during the time instance t, makes a decision about the state of the present hypothesis. We assume that each sensor is an energy harvesting device and is capable of harvesting all the energy it needs to communicate from its environment. Our contribution is to formulate and analyze the decentralized detection problem when the energy harvesting sensors are allowed to form a long term energy usage policy. Our analysis is based on a queuing-theoretic model for the battery. Then, by using numerical simulations, we show how the resulting performance differs from the energy-unconstrained case.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2016
Series
European Signal Processing Conference, ISSN 2076-1465
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-201278 (URN)10.1109/EUSIPCO.2016.7760312 (DOI)000391891900111 ()2-s2.0-85005959803 (Scopus ID)978-0-9928-6265-7 (ISBN)
Conference
24th European Signal Processing Conference (EUSIPCO), AUG 28-SEP 02, 2016, Budapest, HUNGARY
Note

QC 20170215

Available from: 2017-02-15 Created: 2017-02-15 Last updated: 2017-02-15Bibliographically approved
Tarighati, A., Gross, J. & Jalden, J. (2016). Distributed detection in energy harvesting wireless sensor networks. In: European Signal Process. Conf. (EUSIPCO), Aug. 2016: . Paper presented at European Signal Process. Conf. (EUSIPCO). August 29-Sept. 2, 2016. Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>Distributed detection in energy harvesting wireless sensor networks
2016 (English)In: European Signal Process. Conf. (EUSIPCO), Aug. 2016, Institute of Electrical and Electronics Engineers (IEEE), 2016Conference paper, Published paper (Refereed)
Abstract [en]

We consider a decentralized hypothesis testing problem in which several peripheral energy harvesting sensors arearranged in parallel. Each sensor makes a noisy observation of a time varying phenomenon, and sends a message about the present hypothesis towards a fusion center at each time instance t. The fusion center, using the aggregate of the received messages during the time instance t, makes a decision about the state of the present hypothesis. We assume that each sensor is an energy harvesting device and is capable of harvesting all the energy it needs to communicate from its environment. Our contribution is to formulate and analyze the decentralized detection problem when the energy harvesting sensors are allowed to form a long term energy usage policy. Our analysis is based on a queuing-theoretic model for the battery. Then, by using numerical simulations, we show how the resulting performance differs from the energy-unconstrained case.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2016
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-189862 (URN)
External cooperation:
Conference
European Signal Process. Conf. (EUSIPCO). August 29-Sept. 2, 2016
Note

QC 20160907

Available from: 2016-07-20 Created: 2016-07-20 Last updated: 2016-11-02Bibliographically approved
Tarighati, A. & Jalden, J. (2016). Optimality of Rate Balancing in Wireless Sensor Networks. IEEE Transactions on Signal Processing, 64(14)
Open this publication in new window or tab >>Optimality of Rate Balancing in Wireless Sensor Networks
2016 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 64, no 14Article in journal (Refereed) Published
Abstract [en]

We consider the problem of distributed binary hypothesis testing in a parallel network topology where sensors independently observe some phenomenon and send a finite rate summary of their observations to a fusion center for the final decision. We explicitly consider a scenario under which (integer) rate messages are sent over an error free multiple access channel, modeled by a sum rate constraint at the fusion center. This problem was previously studied by Chamberland and Veeravalli, who provided sufficient conditions for the optimality of one bit sensor messages. Their result is however crucially dependent on the feasibility of having as many one bit sensors as the (integer) sum rate constraint of the multiple access channel, an assumption that can often not be satisfied in practice. This prompts us to consider the case of an a-priori limited number of sensors and we provide sufficient condition under which having no two sensors with rate difference more than one bit, so called rate balancing, is an optimal strategy with respect to the Bhattacharyya distance between the hypotheses at the input to the fusion center. We further discuss explicit observation models under which these sufficient conditions are satisfied.

Place, publisher, year, edition, pages
IEEE Signal Processing Society, 2016
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-184672 (URN)10.1109/TSP.2016.2551691 (DOI)000377370500014 ()2-s2.0-84974633341 (Scopus ID)
Note

QC 20160414

Available from: 2016-04-02 Created: 2016-04-02 Last updated: 2017-11-30Bibliographically approved
Sadanandan, S. K., Baltekin, O., Magnusson, K. E. G., Boucharin, A., Ranefall, P., Jalden, J., . . . Wahlby, C. (2016). Segmentation and Track-Analysis in Time-Lapse Imaging of Bacteria. IEEE Journal on Selected Topics in Signal Processing, 10(1), 174-184
Open this publication in new window or tab >>Segmentation and Track-Analysis in Time-Lapse Imaging of Bacteria
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2016 (English)In: IEEE Journal on Selected Topics in Signal Processing, ISSN 1932-4553, E-ISSN 1941-0484, Vol. 10, no 1, p. 174-184Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
IEEE Communications Society, 2016
Keyword
E. coli, microscopy, segmentation, time-lapse, tracking
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-183199 (URN)10.1109/JSTSP.2015.2491304 (DOI)000369495900015 ()2-s2.0-84962911002 (Scopus ID)
Funder
Swedish Research Council, 2012-4968EU, European Research Council, 616047
Note

QC 20160303

Available from: 2016-03-03 Created: 2016-03-03 Last updated: 2017-11-30Bibliographically approved
Tarighati, A. & Jalden, J. (2015). Bayesian Design of Tandem Networks for Distributed Detection With Multi-bit Sensor Decisions. IEEE Transactions on Signal Processing, 63(7), 1821-1831
Open this publication in new window or tab >>Bayesian Design of Tandem Networks for Distributed Detection With Multi-bit Sensor Decisions
2015 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 63, no 7, p. 1821-1831Article in journal (Refereed) Published
Abstract [en]

We consider the problem of decentralized hypothesis testing under communication constraints in a topology where several peripheral nodes are arranged in tandem. Each node receives an observation and transmits a message to its successor, and the last node then decides which hypothesis is true. We assume that the observations at different nodes are, conditioned on the true hypothesis, independent and the channel between any two successive nodes is considered error-free but rate-constrained. We propose a cyclic numerical design algorithm for the design of nodes using a person-by-person methodology with the minimum expected error probability as a design criterion, where the number of communicated messages is not necessarily equal to the number of hypotheses. The number of peripheral nodes in the proposed method is in principle arbitrary and the information rate constraints are satisfied by quantizing the input of each node. The performance of the proposed method for different information rate constraints, in a binary hypothesis test, is compared to the optimum rate-one solution due to Swaszek and a method proposed by Cover, and it is shown numerically that increasing the channel rate can significantly enhance the performance of the tandem network. Simulation results for $M$-ary hypothesis tests also show that by increasing the channel rates the performance of the tandem network significantly improves.

Place, publisher, year, edition, pages
IEEE Signal Processing Society, 2015
National Category
Electrical Engineering, Electronic Engineering, Information Engineering Signal Processing
Identifiers
urn:nbn:se:kth:diva-159597 (URN)10.1109/TSP.2015.2401535 (DOI)000350880900016 ()2-s2.0-84924674518 (Scopus ID)
Note

QC 201502010

Available from: 2015-02-05 Created: 2015-02-05 Last updated: 2017-12-05Bibliographically approved
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Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-6630-243X

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