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Bio Imaging and Signal Processing

Deriving 3D Shape Properties by Using Backward Wavelet Remesher


It is important to determine 3D shape properties of a population of 3D mesh models in biomedical imaging issues. In contrast to conventional 3D shape analysis techniques focusing on applications like shape matching and shape retrieval, we propose in this paper a strategy capable to collect statistical information of multiple triangular mesh models. Our method operates in a coarse-to-fine fashion based on wavelet synthesis. Hence, its analysis result can be invariant against the triangular tiling of the input mesh model.

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Authors:
Hao-Chiang Shao and Wen-Liang Hwang
Submitted On:
13 November 2017 - 10:30pm
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GlobalSIP2017_hcShao_upload.pdf

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[1] Hao-Chiang Shao and Wen-Liang Hwang, "Deriving 3D Shape Properties by Using Backward Wavelet Remesher", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2348. Accessed: Nov. 20, 2017.
@article{2348-17,
url = {http://sigport.org/2348},
author = {Hao-Chiang Shao and Wen-Liang Hwang },
publisher = {IEEE SigPort},
title = {Deriving 3D Shape Properties by Using Backward Wavelet Remesher},
year = {2017} }
TY - EJOUR
T1 - Deriving 3D Shape Properties by Using Backward Wavelet Remesher
AU - Hao-Chiang Shao and Wen-Liang Hwang
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2348
ER -
Hao-Chiang Shao and Wen-Liang Hwang. (2017). Deriving 3D Shape Properties by Using Backward Wavelet Remesher. IEEE SigPort. http://sigport.org/2348
Hao-Chiang Shao and Wen-Liang Hwang, 2017. Deriving 3D Shape Properties by Using Backward Wavelet Remesher. Available at: http://sigport.org/2348.
Hao-Chiang Shao and Wen-Liang Hwang. (2017). "Deriving 3D Shape Properties by Using Backward Wavelet Remesher." Web.
1. Hao-Chiang Shao and Wen-Liang Hwang. Deriving 3D Shape Properties by Using Backward Wavelet Remesher [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2348

3D SHAPE ASYMMETRY ANALYSIS USING CORRESPONDENCE BETWEEN PARTIAL GEODESIC CURVES


Analyzing the asymmetry of anatomical shapes is one of the cornerstones of efficient computerized diagnosis. In the application of scoliotic trunk analysis, one major challenge is the high variability and complexity of deformations due to the pathology itself, and to changes of body poses, for instance, torsos acquired in lateral bending poses for surgical planning. In this paper, we present a novel and fully automatic approach to analyzing the asymmetry of deformable trunk shapes.

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15 November 2017 - 11:28am
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GlobalSIP17_Slides

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[1] , "3D SHAPE ASYMMETRY ANALYSIS USING CORRESPONDENCE BETWEEN PARTIAL GEODESIC CURVES", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2328. Accessed: Nov. 20, 2017.
@article{2328-17,
url = {http://sigport.org/2328},
author = { },
publisher = {IEEE SigPort},
title = {3D SHAPE ASYMMETRY ANALYSIS USING CORRESPONDENCE BETWEEN PARTIAL GEODESIC CURVES},
year = {2017} }
TY - EJOUR
T1 - 3D SHAPE ASYMMETRY ANALYSIS USING CORRESPONDENCE BETWEEN PARTIAL GEODESIC CURVES
AU -
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2328
ER -
. (2017). 3D SHAPE ASYMMETRY ANALYSIS USING CORRESPONDENCE BETWEEN PARTIAL GEODESIC CURVES. IEEE SigPort. http://sigport.org/2328
, 2017. 3D SHAPE ASYMMETRY ANALYSIS USING CORRESPONDENCE BETWEEN PARTIAL GEODESIC CURVES. Available at: http://sigport.org/2328.
. (2017). "3D SHAPE ASYMMETRY ANALYSIS USING CORRESPONDENCE BETWEEN PARTIAL GEODESIC CURVES." Web.
1. . 3D SHAPE ASYMMETRY ANALYSIS USING CORRESPONDENCE BETWEEN PARTIAL GEODESIC CURVES [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2328

CIRCLET BASED FRAMEWORK FOR OPTIC DISK DETECTION


Optic Disc (OD) detection in retinal fundus images is a crucial stage for the automation of a screening system in diabetic ophthalmology. Most researches for automatic localization of OD benefit the regions of vessels. In this paper, we present a fast and novel method based on the Circlet Trans-form to detect OD in digital retinal fundus images that doesn’t utilize the location of the vessels. First, each R, G and B band is enhanced using CLAHE method. Then, the enhanced image in RGB color space is converted to L*a*b one.

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Authors:
Omid Sarrafzadeh, Hossein Rabbani
Submitted On:
6 September 2017 - 3:56am
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2017 ICIP Optic Disk 3.pdf

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[1] Omid Sarrafzadeh, Hossein Rabbani, "CIRCLET BASED FRAMEWORK FOR OPTIC DISK DETECTION", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1838. Accessed: Nov. 20, 2017.
@article{1838-17,
url = {http://sigport.org/1838},
author = {Omid Sarrafzadeh; Hossein Rabbani },
publisher = {IEEE SigPort},
title = {CIRCLET BASED FRAMEWORK FOR OPTIC DISK DETECTION},
year = {2017} }
TY - EJOUR
T1 - CIRCLET BASED FRAMEWORK FOR OPTIC DISK DETECTION
AU - Omid Sarrafzadeh; Hossein Rabbani
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1838
ER -
Omid Sarrafzadeh, Hossein Rabbani. (2017). CIRCLET BASED FRAMEWORK FOR OPTIC DISK DETECTION. IEEE SigPort. http://sigport.org/1838
Omid Sarrafzadeh, Hossein Rabbani, 2017. CIRCLET BASED FRAMEWORK FOR OPTIC DISK DETECTION. Available at: http://sigport.org/1838.
Omid Sarrafzadeh, Hossein Rabbani. (2017). "CIRCLET BASED FRAMEWORK FOR OPTIC DISK DETECTION." Web.
1. Omid Sarrafzadeh, Hossein Rabbani. CIRCLET BASED FRAMEWORK FOR OPTIC DISK DETECTION [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1838

ALIGNMENT OF OPTIC NERVE HEAD OPTICAL COHERENCE TOMOGRAPHY B-SCANS IN RIGHT AND LEFT EYES


Symmetry analysis of right and left eyes can be a useful tool for early detection of eye diseases. In this study, we want to compare the Optical Coherent Tomography (OCT) images captured from optic nerve head (ONH) of right and left eyes. To do this, it is necessary to align the OCT data and com-pare equivalent B-scans in right and left eyes.

icip_7.pdf

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Authors:
Marzieh Mokhtari, Hossein Rabbani, Alireza Mehri-Dehnavi
Submitted On:
5 September 2017 - 1:33am
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[1] Marzieh Mokhtari, Hossein Rabbani, Alireza Mehri-Dehnavi, "ALIGNMENT OF OPTIC NERVE HEAD OPTICAL COHERENCE TOMOGRAPHY B-SCANS IN RIGHT AND LEFT EYES", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1834. Accessed: Nov. 20, 2017.
@article{1834-17,
url = {http://sigport.org/1834},
author = {Marzieh Mokhtari; Hossein Rabbani; Alireza Mehri-Dehnavi },
publisher = {IEEE SigPort},
title = {ALIGNMENT OF OPTIC NERVE HEAD OPTICAL COHERENCE TOMOGRAPHY B-SCANS IN RIGHT AND LEFT EYES},
year = {2017} }
TY - EJOUR
T1 - ALIGNMENT OF OPTIC NERVE HEAD OPTICAL COHERENCE TOMOGRAPHY B-SCANS IN RIGHT AND LEFT EYES
AU - Marzieh Mokhtari; Hossein Rabbani; Alireza Mehri-Dehnavi
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1834
ER -
Marzieh Mokhtari, Hossein Rabbani, Alireza Mehri-Dehnavi. (2017). ALIGNMENT OF OPTIC NERVE HEAD OPTICAL COHERENCE TOMOGRAPHY B-SCANS IN RIGHT AND LEFT EYES. IEEE SigPort. http://sigport.org/1834
Marzieh Mokhtari, Hossein Rabbani, Alireza Mehri-Dehnavi, 2017. ALIGNMENT OF OPTIC NERVE HEAD OPTICAL COHERENCE TOMOGRAPHY B-SCANS IN RIGHT AND LEFT EYES. Available at: http://sigport.org/1834.
Marzieh Mokhtari, Hossein Rabbani, Alireza Mehri-Dehnavi. (2017). "ALIGNMENT OF OPTIC NERVE HEAD OPTICAL COHERENCE TOMOGRAPHY B-SCANS IN RIGHT AND LEFT EYES." Web.
1. Marzieh Mokhtari, Hossein Rabbani, Alireza Mehri-Dehnavi. ALIGNMENT OF OPTIC NERVE HEAD OPTICAL COHERENCE TOMOGRAPHY B-SCANS IN RIGHT AND LEFT EYES [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1834

A KNOWLEDGE-DRIVEN FRAMEWORK FOR ECG REPRESENTATION AND INTERPRETATION FOR WEARABLE APPLICATIONS

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Authors:
Ramasubramanian Balasubramanian, Theodora Chaspari, Shrikanth Narayanan
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28 February 2017 - 9:32pm
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ICASSP2017_ECGRepresentation.pdf

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[1] Ramasubramanian Balasubramanian, Theodora Chaspari, Shrikanth Narayanan, "A KNOWLEDGE-DRIVEN FRAMEWORK FOR ECG REPRESENTATION AND INTERPRETATION FOR WEARABLE APPLICATIONS", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1525. Accessed: Nov. 20, 2017.
@article{1525-17,
url = {http://sigport.org/1525},
author = {Ramasubramanian Balasubramanian; Theodora Chaspari; Shrikanth Narayanan },
publisher = {IEEE SigPort},
title = {A KNOWLEDGE-DRIVEN FRAMEWORK FOR ECG REPRESENTATION AND INTERPRETATION FOR WEARABLE APPLICATIONS},
year = {2017} }
TY - EJOUR
T1 - A KNOWLEDGE-DRIVEN FRAMEWORK FOR ECG REPRESENTATION AND INTERPRETATION FOR WEARABLE APPLICATIONS
AU - Ramasubramanian Balasubramanian; Theodora Chaspari; Shrikanth Narayanan
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1525
ER -
Ramasubramanian Balasubramanian, Theodora Chaspari, Shrikanth Narayanan. (2017). A KNOWLEDGE-DRIVEN FRAMEWORK FOR ECG REPRESENTATION AND INTERPRETATION FOR WEARABLE APPLICATIONS. IEEE SigPort. http://sigport.org/1525
Ramasubramanian Balasubramanian, Theodora Chaspari, Shrikanth Narayanan, 2017. A KNOWLEDGE-DRIVEN FRAMEWORK FOR ECG REPRESENTATION AND INTERPRETATION FOR WEARABLE APPLICATIONS. Available at: http://sigport.org/1525.
Ramasubramanian Balasubramanian, Theodora Chaspari, Shrikanth Narayanan. (2017). "A KNOWLEDGE-DRIVEN FRAMEWORK FOR ECG REPRESENTATION AND INTERPRETATION FOR WEARABLE APPLICATIONS." Web.
1. Ramasubramanian Balasubramanian, Theodora Chaspari, Shrikanth Narayanan. A KNOWLEDGE-DRIVEN FRAMEWORK FOR ECG REPRESENTATION AND INTERPRETATION FOR WEARABLE APPLICATIONS [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1525

EPILEPTOGENIC BRAIN CONNECTIVITY PATTERNS USING SCALP EEG

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6 December 2016 - 10:02am
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GlobalSIP_Presentation.pptx

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[1] , "EPILEPTOGENIC BRAIN CONNECTIVITY PATTERNS USING SCALP EEG", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1358. Accessed: Nov. 20, 2017.
@article{1358-16,
url = {http://sigport.org/1358},
author = { },
publisher = {IEEE SigPort},
title = {EPILEPTOGENIC BRAIN CONNECTIVITY PATTERNS USING SCALP EEG},
year = {2016} }
TY - EJOUR
T1 - EPILEPTOGENIC BRAIN CONNECTIVITY PATTERNS USING SCALP EEG
AU -
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1358
ER -
. (2016). EPILEPTOGENIC BRAIN CONNECTIVITY PATTERNS USING SCALP EEG. IEEE SigPort. http://sigport.org/1358
, 2016. EPILEPTOGENIC BRAIN CONNECTIVITY PATTERNS USING SCALP EEG. Available at: http://sigport.org/1358.
. (2016). "EPILEPTOGENIC BRAIN CONNECTIVITY PATTERNS USING SCALP EEG." Web.
1. . EPILEPTOGENIC BRAIN CONNECTIVITY PATTERNS USING SCALP EEG [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1358

Bottleneck Capacity of Random Graphs for Connectomics


With developments in experimental connectomics producing wiring diagrams of many neuronal networks, there is emerging interest in theories to understand the relationship between structure and function. Efficiency of information flow in networks has been proposed as a key functional in characterizing cognition, and we have previously shown that information-theoretic limits on information flow are predictive of behavioral speed in the nematode Caenorhabditis elegans.

Varshney.pdf

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Authors:
Lav R. Varshney
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20 March 2016 - 4:38am
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[1] Lav R. Varshney, "Bottleneck Capacity of Random Graphs for Connectomics", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/859. Accessed: Nov. 20, 2017.
@article{859-16,
url = {http://sigport.org/859},
author = {Lav R. Varshney },
publisher = {IEEE SigPort},
title = {Bottleneck Capacity of Random Graphs for Connectomics},
year = {2016} }
TY - EJOUR
T1 - Bottleneck Capacity of Random Graphs for Connectomics
AU - Lav R. Varshney
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/859
ER -
Lav R. Varshney. (2016). Bottleneck Capacity of Random Graphs for Connectomics. IEEE SigPort. http://sigport.org/859
Lav R. Varshney, 2016. Bottleneck Capacity of Random Graphs for Connectomics. Available at: http://sigport.org/859.
Lav R. Varshney. (2016). "Bottleneck Capacity of Random Graphs for Connectomics." Web.
1. Lav R. Varshney. Bottleneck Capacity of Random Graphs for Connectomics [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/859

EXTRACTION OF TONGUE CONTOUR IN REAL-TIME MAGNETIC RESONANCE IMAGING SEQUENCES


Real-time magnetic resonance imaging (rtMRI) is becoming a practical tool in speech production research and language pathology observation. It is still a challenge to extract the tongue contour accurately in rtMRI sequences, since tongue is a soft tissue and often touches other organs such as lips and upper mandible. This paper proposes a novel semi-automatic tongue contour extraction method from rtMRI sequences. The initial boundary image is obtained by combined multi-directional Sobel operators in tongue movement region; then a boundary intensity map is constructed to find the most probable tongue contour points by searching for the optimal boundary route with Viterbi algorithm; finally the tongue contour is obtained using B-Spline approximation. The proposed method could obtain accurate tongue contour from rtMRI sequences, even in the cases that some parts of tongue touch other organs. Experiments demonstrate the robustness of the proposed method.

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Authors:
Dawei Zhang, Minghao Yang, Jianhua Tao, Yang Wang, Bin Liu, Danish Bukhari
Submitted On:
19 March 2016 - 10:52am
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Poster-ICASSP-2016.pdf

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[1] Dawei Zhang, Minghao Yang, Jianhua Tao, Yang Wang, Bin Liu, Danish Bukhari, "EXTRACTION OF TONGUE CONTOUR IN REAL-TIME MAGNETIC RESONANCE IMAGING SEQUENCES", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/815. Accessed: Nov. 20, 2017.
@article{815-16,
url = {http://sigport.org/815},
author = {Dawei Zhang; Minghao Yang; Jianhua Tao; Yang Wang; Bin Liu; Danish Bukhari },
publisher = {IEEE SigPort},
title = {EXTRACTION OF TONGUE CONTOUR IN REAL-TIME MAGNETIC RESONANCE IMAGING SEQUENCES},
year = {2016} }
TY - EJOUR
T1 - EXTRACTION OF TONGUE CONTOUR IN REAL-TIME MAGNETIC RESONANCE IMAGING SEQUENCES
AU - Dawei Zhang; Minghao Yang; Jianhua Tao; Yang Wang; Bin Liu; Danish Bukhari
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/815
ER -
Dawei Zhang, Minghao Yang, Jianhua Tao, Yang Wang, Bin Liu, Danish Bukhari. (2016). EXTRACTION OF TONGUE CONTOUR IN REAL-TIME MAGNETIC RESONANCE IMAGING SEQUENCES. IEEE SigPort. http://sigport.org/815
Dawei Zhang, Minghao Yang, Jianhua Tao, Yang Wang, Bin Liu, Danish Bukhari, 2016. EXTRACTION OF TONGUE CONTOUR IN REAL-TIME MAGNETIC RESONANCE IMAGING SEQUENCES. Available at: http://sigport.org/815.
Dawei Zhang, Minghao Yang, Jianhua Tao, Yang Wang, Bin Liu, Danish Bukhari. (2016). "EXTRACTION OF TONGUE CONTOUR IN REAL-TIME MAGNETIC RESONANCE IMAGING SEQUENCES." Web.
1. Dawei Zhang, Minghao Yang, Jianhua Tao, Yang Wang, Bin Liu, Danish Bukhari. EXTRACTION OF TONGUE CONTOUR IN REAL-TIME MAGNETIC RESONANCE IMAGING SEQUENCES [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/815

Sparse Signal Recovery Methods for Variant Detection in Next-Generation Sequencing Data

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Authors:
Mario Banuelos, Rubi Almanza, Lasith Adhikari, Suzanne Sindi, Roummel Marcia
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19 March 2016 - 4:15am
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ICASSP2016_2589.pdf

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[1] Mario Banuelos, Rubi Almanza, Lasith Adhikari, Suzanne Sindi, Roummel Marcia, "Sparse Signal Recovery Methods for Variant Detection in Next-Generation Sequencing Data", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/785. Accessed: Nov. 20, 2017.
@article{785-16,
url = {http://sigport.org/785},
author = { Mario Banuelos; Rubi Almanza; Lasith Adhikari; Suzanne Sindi; Roummel Marcia },
publisher = {IEEE SigPort},
title = {Sparse Signal Recovery Methods for Variant Detection in Next-Generation Sequencing Data},
year = {2016} }
TY - EJOUR
T1 - Sparse Signal Recovery Methods for Variant Detection in Next-Generation Sequencing Data
AU - Mario Banuelos; Rubi Almanza; Lasith Adhikari; Suzanne Sindi; Roummel Marcia
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/785
ER -
Mario Banuelos, Rubi Almanza, Lasith Adhikari, Suzanne Sindi, Roummel Marcia. (2016). Sparse Signal Recovery Methods for Variant Detection in Next-Generation Sequencing Data. IEEE SigPort. http://sigport.org/785
Mario Banuelos, Rubi Almanza, Lasith Adhikari, Suzanne Sindi, Roummel Marcia, 2016. Sparse Signal Recovery Methods for Variant Detection in Next-Generation Sequencing Data. Available at: http://sigport.org/785.
Mario Banuelos, Rubi Almanza, Lasith Adhikari, Suzanne Sindi, Roummel Marcia. (2016). "Sparse Signal Recovery Methods for Variant Detection in Next-Generation Sequencing Data." Web.
1. Mario Banuelos, Rubi Almanza, Lasith Adhikari, Suzanne Sindi, Roummel Marcia. Sparse Signal Recovery Methods for Variant Detection in Next-Generation Sequencing Data [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/785

Quantifying Cooperation in Choir Singing: Respiratory and Cardiac Synchronisation

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Authors:
Apit Hemakom, Valentin Goverdovsky, Lisa Aufegger, Danilo P. Mandic
Submitted On:
24 March 2016 - 11:40pm
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20160325 ICASSP choir synchrony.pdf

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[1] Apit Hemakom, Valentin Goverdovsky, Lisa Aufegger, Danilo P. Mandic, "Quantifying Cooperation in Choir Singing: Respiratory and Cardiac Synchronisation", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/784. Accessed: Nov. 20, 2017.
@article{784-16,
url = {http://sigport.org/784},
author = {Apit Hemakom; Valentin Goverdovsky; Lisa Aufegger; Danilo P. Mandic },
publisher = {IEEE SigPort},
title = {Quantifying Cooperation in Choir Singing: Respiratory and Cardiac Synchronisation},
year = {2016} }
TY - EJOUR
T1 - Quantifying Cooperation in Choir Singing: Respiratory and Cardiac Synchronisation
AU - Apit Hemakom; Valentin Goverdovsky; Lisa Aufegger; Danilo P. Mandic
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/784
ER -
Apit Hemakom, Valentin Goverdovsky, Lisa Aufegger, Danilo P. Mandic. (2016). Quantifying Cooperation in Choir Singing: Respiratory and Cardiac Synchronisation. IEEE SigPort. http://sigport.org/784
Apit Hemakom, Valentin Goverdovsky, Lisa Aufegger, Danilo P. Mandic, 2016. Quantifying Cooperation in Choir Singing: Respiratory and Cardiac Synchronisation. Available at: http://sigport.org/784.
Apit Hemakom, Valentin Goverdovsky, Lisa Aufegger, Danilo P. Mandic. (2016). "Quantifying Cooperation in Choir Singing: Respiratory and Cardiac Synchronisation." Web.
1. Apit Hemakom, Valentin Goverdovsky, Lisa Aufegger, Danilo P. Mandic. Quantifying Cooperation in Choir Singing: Respiratory and Cardiac Synchronisation [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/784

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