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Bioimaging and microscopy

BACT-3D: A LEVEL SET SEGMENTATION APPROACH FOR DENSE MULTI-LAYERED 3D BACTERIAL BIOFILMS


In microscopy, new super-resolution methods are emerging that produce three-dimensional images at resolutions ten times smaller than that provided by traditional light microscopy. Such technology is enabling the exploration of structure and function in living tissues such as bacterial biofilms that have mysterious interconnections and organization. Unfortunately, the standard tools used in the image analysis community to perform segmentation and other higher-level analyses cannot be applied naively to these data.

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Authors:
R. Sarkar, A. Aziz, A. Vaccari, A. Gahlmann and S. T. Acton
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16 September 2017 - 9:24pm
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ICIP 2017 BACT-3D

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[1] R. Sarkar, A. Aziz, A. Vaccari, A. Gahlmann and S. T. Acton, "BACT-3D: A LEVEL SET SEGMENTATION APPROACH FOR DENSE MULTI-LAYERED 3D BACTERIAL BIOFILMS", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2202. Accessed: Nov. 22, 2017.
@article{2202-17,
url = {http://sigport.org/2202},
author = {R. Sarkar; A. Aziz; A. Vaccari; A. Gahlmann and S. T. Acton },
publisher = {IEEE SigPort},
title = {BACT-3D: A LEVEL SET SEGMENTATION APPROACH FOR DENSE MULTI-LAYERED 3D BACTERIAL BIOFILMS},
year = {2017} }
TY - EJOUR
T1 - BACT-3D: A LEVEL SET SEGMENTATION APPROACH FOR DENSE MULTI-LAYERED 3D BACTERIAL BIOFILMS
AU - R. Sarkar; A. Aziz; A. Vaccari; A. Gahlmann and S. T. Acton
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2202
ER -
R. Sarkar, A. Aziz, A. Vaccari, A. Gahlmann and S. T. Acton. (2017). BACT-3D: A LEVEL SET SEGMENTATION APPROACH FOR DENSE MULTI-LAYERED 3D BACTERIAL BIOFILMS. IEEE SigPort. http://sigport.org/2202
R. Sarkar, A. Aziz, A. Vaccari, A. Gahlmann and S. T. Acton, 2017. BACT-3D: A LEVEL SET SEGMENTATION APPROACH FOR DENSE MULTI-LAYERED 3D BACTERIAL BIOFILMS. Available at: http://sigport.org/2202.
R. Sarkar, A. Aziz, A. Vaccari, A. Gahlmann and S. T. Acton. (2017). "BACT-3D: A LEVEL SET SEGMENTATION APPROACH FOR DENSE MULTI-LAYERED 3D BACTERIAL BIOFILMS." Web.
1. R. Sarkar, A. Aziz, A. Vaccari, A. Gahlmann and S. T. Acton. BACT-3D: A LEVEL SET SEGMENTATION APPROACH FOR DENSE MULTI-LAYERED 3D BACTERIAL BIOFILMS [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2202

Blur Estimation for Photon-Limited Images


Blur estimation is critical to blind image deconvolution. In this work, by taking Gaussian kernel as an example, we propose an approach to estimate the blur size for photon-limited images. This estimation is based on the minimization of a novel criterion, blur-PURE (Poisson unbiased risk estimate), which makes use of the Poisson noise statistics of the measurement. Experimental results demonstrate the effectiveness of the proposed method in various scenarios.

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Authors:
Jizhou Li, Feng Xue, and Thierry Blu
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14 September 2017 - 5:00am
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Slides_blurPURE_ICIP17.pdf

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[1] Jizhou Li, Feng Xue, and Thierry Blu, "Blur Estimation for Photon-Limited Images", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2001. Accessed: Nov. 22, 2017.
@article{2001-17,
url = {http://sigport.org/2001},
author = {Jizhou Li; Feng Xue; and Thierry Blu },
publisher = {IEEE SigPort},
title = {Blur Estimation for Photon-Limited Images},
year = {2017} }
TY - EJOUR
T1 - Blur Estimation for Photon-Limited Images
AU - Jizhou Li; Feng Xue; and Thierry Blu
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2001
ER -
Jizhou Li, Feng Xue, and Thierry Blu. (2017). Blur Estimation for Photon-Limited Images. IEEE SigPort. http://sigport.org/2001
Jizhou Li, Feng Xue, and Thierry Blu, 2017. Blur Estimation for Photon-Limited Images. Available at: http://sigport.org/2001.
Jizhou Li, Feng Xue, and Thierry Blu. (2017). "Blur Estimation for Photon-Limited Images." Web.
1. Jizhou Li, Feng Xue, and Thierry Blu. Blur Estimation for Photon-Limited Images [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2001

A Two-Stage Minimum Spanning Tree (MST) based Clustering Algorithm for 2D Deformable Registration of Time Sequenced Images


Significant cardiac and respiratory motion of the living subject, occasional spells of defocus, drifts in the field of view,
and long image sequences make the registration of in-vivo microscopy image sequences used in atherosclerosis study an
onerous task. In this study we developed and implemented a novel Minimum Spanning Tree (MST)-based clustering
method for image sequence registration that first constructs a minimum spanning tree for the input image sequence. The

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Authors:
Nilanjan Ray, Sara McArdle, and Klaus Ley
Submitted On:
11 September 2017 - 3:35pm
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ICIP2017_Registration.pdf

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[1] Nilanjan Ray, Sara McArdle, and Klaus Ley, "A Two-Stage Minimum Spanning Tree (MST) based Clustering Algorithm for 2D Deformable Registration of Time Sequenced Images", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1916. Accessed: Nov. 22, 2017.
@article{1916-17,
url = {http://sigport.org/1916},
author = {Nilanjan Ray; Sara McArdle; and Klaus Ley },
publisher = {IEEE SigPort},
title = {A Two-Stage Minimum Spanning Tree (MST) based Clustering Algorithm for 2D Deformable Registration of Time Sequenced Images},
year = {2017} }
TY - EJOUR
T1 - A Two-Stage Minimum Spanning Tree (MST) based Clustering Algorithm for 2D Deformable Registration of Time Sequenced Images
AU - Nilanjan Ray; Sara McArdle; and Klaus Ley
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1916
ER -
Nilanjan Ray, Sara McArdle, and Klaus Ley. (2017). A Two-Stage Minimum Spanning Tree (MST) based Clustering Algorithm for 2D Deformable Registration of Time Sequenced Images. IEEE SigPort. http://sigport.org/1916
Nilanjan Ray, Sara McArdle, and Klaus Ley, 2017. A Two-Stage Minimum Spanning Tree (MST) based Clustering Algorithm for 2D Deformable Registration of Time Sequenced Images. Available at: http://sigport.org/1916.
Nilanjan Ray, Sara McArdle, and Klaus Ley. (2017). "A Two-Stage Minimum Spanning Tree (MST) based Clustering Algorithm for 2D Deformable Registration of Time Sequenced Images." Web.
1. Nilanjan Ray, Sara McArdle, and Klaus Ley. A Two-Stage Minimum Spanning Tree (MST) based Clustering Algorithm for 2D Deformable Registration of Time Sequenced Images [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1916

IMAGE-BASED MEASUREMENT OF CARGO TRAFFIC FLOW IN COMPLEX NEURITE NETWORKS


Neurons depend critically on active transport of cargoes throughout their complex neurite networks for their survival and function. Defects in this process have been strongly associated with many human neurodevelopmental and neurodegenerative diseases. To understand related neuronal physiology and disease mechanisms, it is essential to measure the traffic flow within the neurite networks. Currently, however, image analysis methods required for this measurement are lacking.

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Authors:
Douglas Qian, Qinle Ba, Angran Li, Jessica Zhang, Ge Yang
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8 September 2017 - 4:17pm
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ICIP_poster_XiaoqiChai.pdf

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[1] Douglas Qian, Qinle Ba, Angran Li, Jessica Zhang, Ge Yang, "IMAGE-BASED MEASUREMENT OF CARGO TRAFFIC FLOW IN COMPLEX NEURITE NETWORKS", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1878. Accessed: Nov. 22, 2017.
@article{1878-17,
url = {http://sigport.org/1878},
author = {Douglas Qian; Qinle Ba; Angran Li; Jessica Zhang; Ge Yang },
publisher = {IEEE SigPort},
title = {IMAGE-BASED MEASUREMENT OF CARGO TRAFFIC FLOW IN COMPLEX NEURITE NETWORKS},
year = {2017} }
TY - EJOUR
T1 - IMAGE-BASED MEASUREMENT OF CARGO TRAFFIC FLOW IN COMPLEX NEURITE NETWORKS
AU - Douglas Qian; Qinle Ba; Angran Li; Jessica Zhang; Ge Yang
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1878
ER -
Douglas Qian, Qinle Ba, Angran Li, Jessica Zhang, Ge Yang. (2017). IMAGE-BASED MEASUREMENT OF CARGO TRAFFIC FLOW IN COMPLEX NEURITE NETWORKS. IEEE SigPort. http://sigport.org/1878
Douglas Qian, Qinle Ba, Angran Li, Jessica Zhang, Ge Yang, 2017. IMAGE-BASED MEASUREMENT OF CARGO TRAFFIC FLOW IN COMPLEX NEURITE NETWORKS. Available at: http://sigport.org/1878.
Douglas Qian, Qinle Ba, Angran Li, Jessica Zhang, Ge Yang. (2017). "IMAGE-BASED MEASUREMENT OF CARGO TRAFFIC FLOW IN COMPLEX NEURITE NETWORKS." Web.
1. Douglas Qian, Qinle Ba, Angran Li, Jessica Zhang, Ge Yang. IMAGE-BASED MEASUREMENT OF CARGO TRAFFIC FLOW IN COMPLEX NEURITE NETWORKS [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1878

A data-driven approach to feature space selection for robust micro-endoscopic image reconstruction

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7 September 2017 - 9:06am
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Bourdonp_ICIP2017_2017_08_28.pdf

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[1] , "A data-driven approach to feature space selection for robust micro-endoscopic image reconstruction", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1853. Accessed: Nov. 22, 2017.
@article{1853-17,
url = {http://sigport.org/1853},
author = { },
publisher = {IEEE SigPort},
title = {A data-driven approach to feature space selection for robust micro-endoscopic image reconstruction},
year = {2017} }
TY - EJOUR
T1 - A data-driven approach to feature space selection for robust micro-endoscopic image reconstruction
AU -
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1853
ER -
. (2017). A data-driven approach to feature space selection for robust micro-endoscopic image reconstruction. IEEE SigPort. http://sigport.org/1853
, 2017. A data-driven approach to feature space selection for robust micro-endoscopic image reconstruction. Available at: http://sigport.org/1853.
. (2017). "A data-driven approach to feature space selection for robust micro-endoscopic image reconstruction." Web.
1. . A data-driven approach to feature space selection for robust micro-endoscopic image reconstruction [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1853

ICIP 2017 Paper #1525 poster

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6 September 2017 - 5:10am
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posterICIP_LeDuan.pdf

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[1] , "ICIP 2017 Paper #1525 poster", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1839. Accessed: Nov. 22, 2017.
@article{1839-17,
url = {http://sigport.org/1839},
author = { },
publisher = {IEEE SigPort},
title = {ICIP 2017 Paper #1525 poster},
year = {2017} }
TY - EJOUR
T1 - ICIP 2017 Paper #1525 poster
AU -
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1839
ER -
. (2017). ICIP 2017 Paper #1525 poster. IEEE SigPort. http://sigport.org/1839
, 2017. ICIP 2017 Paper #1525 poster. Available at: http://sigport.org/1839.
. (2017). "ICIP 2017 Paper #1525 poster." Web.
1. . ICIP 2017 Paper #1525 poster [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1839

STROMULE BRANCH TIP DETECTION BASED ON ACCURATE CELL IMAGE SEGMENTATION


Based on the dynamic structure, we design a system that can perform accurate stromule image segmentation, branch tip detection and tracking automatically. We substitute the user constraints in active contour segmentation by spatial fuzzy c-means clustering for providing more precise segmentation result. Based on the segmented contour after smoothing, we create a surface normal based feature that can accurately detect
the branch tips. We further combine normal information together with tip position coordinate to apply ICP to track the branch tips moving path.

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Authors:
Guoyu Lu, Li Ren, Jeffrey Caplan, Chandra Kambhamettu
Submitted On:
27 August 2017 - 12:32am
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ICIP_poster.pdf

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[1] Guoyu Lu, Li Ren, Jeffrey Caplan, Chandra Kambhamettu, "STROMULE BRANCH TIP DETECTION BASED ON ACCURATE CELL IMAGE SEGMENTATION", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1807. Accessed: Nov. 22, 2017.
@article{1807-17,
url = {http://sigport.org/1807},
author = {Guoyu Lu; Li Ren; Jeffrey Caplan; Chandra Kambhamettu },
publisher = {IEEE SigPort},
title = {STROMULE BRANCH TIP DETECTION BASED ON ACCURATE CELL IMAGE SEGMENTATION},
year = {2017} }
TY - EJOUR
T1 - STROMULE BRANCH TIP DETECTION BASED ON ACCURATE CELL IMAGE SEGMENTATION
AU - Guoyu Lu; Li Ren; Jeffrey Caplan; Chandra Kambhamettu
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1807
ER -
Guoyu Lu, Li Ren, Jeffrey Caplan, Chandra Kambhamettu. (2017). STROMULE BRANCH TIP DETECTION BASED ON ACCURATE CELL IMAGE SEGMENTATION. IEEE SigPort. http://sigport.org/1807
Guoyu Lu, Li Ren, Jeffrey Caplan, Chandra Kambhamettu, 2017. STROMULE BRANCH TIP DETECTION BASED ON ACCURATE CELL IMAGE SEGMENTATION. Available at: http://sigport.org/1807.
Guoyu Lu, Li Ren, Jeffrey Caplan, Chandra Kambhamettu. (2017). "STROMULE BRANCH TIP DETECTION BASED ON ACCURATE CELL IMAGE SEGMENTATION." Web.
1. Guoyu Lu, Li Ren, Jeffrey Caplan, Chandra Kambhamettu. STROMULE BRANCH TIP DETECTION BASED ON ACCURATE CELL IMAGE SEGMENTATION [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1807

GDSPIKE: AN ACCURATE SPIKE ESTIMATION ALGORITHM FROM NOISY CALCIUM FLUORESCENCE SIGNALS


Accurate estimation of spike train from calcium (Ca2+) fluorescence signals is challenging owing to significant fluctuations of fluorescence level. This paper proposes a non-model-based approach for spike train inference using group delay (GD) analysis. It primarily exploits the property that change in Ca2+ fluorescence corresponding to a spike can be characterized by an onset, an attack, and a decay. The proposed algorithm, GDspike, is compared with state-of-the-art systems on five datasets. F-measure is best for GDspike (41%) followed by STM (40%), MLspike (39%), and Vogelstein (35%).

main_jilt.pdf

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Authors:
Jilt Sebastian, Mari Ganesh Kumar, Y. S. Sreekar, Rajeev Vijay Rikhye, Mriganka Sur, Hema A. Murthy
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7 March 2017 - 1:28pm
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main_jilt.pdf

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[1] Jilt Sebastian, Mari Ganesh Kumar, Y. S. Sreekar, Rajeev Vijay Rikhye, Mriganka Sur, Hema A. Murthy, " GDSPIKE: AN ACCURATE SPIKE ESTIMATION ALGORITHM FROM NOISY CALCIUM FLUORESCENCE SIGNALS", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1690. Accessed: Nov. 22, 2017.
@article{1690-17,
url = {http://sigport.org/1690},
author = {Jilt Sebastian; Mari Ganesh Kumar; Y. S. Sreekar; Rajeev Vijay Rikhye; Mriganka Sur; Hema A. Murthy },
publisher = {IEEE SigPort},
title = { GDSPIKE: AN ACCURATE SPIKE ESTIMATION ALGORITHM FROM NOISY CALCIUM FLUORESCENCE SIGNALS},
year = {2017} }
TY - EJOUR
T1 - GDSPIKE: AN ACCURATE SPIKE ESTIMATION ALGORITHM FROM NOISY CALCIUM FLUORESCENCE SIGNALS
AU - Jilt Sebastian; Mari Ganesh Kumar; Y. S. Sreekar; Rajeev Vijay Rikhye; Mriganka Sur; Hema A. Murthy
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1690
ER -
Jilt Sebastian, Mari Ganesh Kumar, Y. S. Sreekar, Rajeev Vijay Rikhye, Mriganka Sur, Hema A. Murthy. (2017). GDSPIKE: AN ACCURATE SPIKE ESTIMATION ALGORITHM FROM NOISY CALCIUM FLUORESCENCE SIGNALS. IEEE SigPort. http://sigport.org/1690
Jilt Sebastian, Mari Ganesh Kumar, Y. S. Sreekar, Rajeev Vijay Rikhye, Mriganka Sur, Hema A. Murthy, 2017. GDSPIKE: AN ACCURATE SPIKE ESTIMATION ALGORITHM FROM NOISY CALCIUM FLUORESCENCE SIGNALS. Available at: http://sigport.org/1690.
Jilt Sebastian, Mari Ganesh Kumar, Y. S. Sreekar, Rajeev Vijay Rikhye, Mriganka Sur, Hema A. Murthy. (2017). " GDSPIKE: AN ACCURATE SPIKE ESTIMATION ALGORITHM FROM NOISY CALCIUM FLUORESCENCE SIGNALS." Web.
1. Jilt Sebastian, Mari Ganesh Kumar, Y. S. Sreekar, Rajeev Vijay Rikhye, Mriganka Sur, Hema A. Murthy. GDSPIKE: AN ACCURATE SPIKE ESTIMATION ALGORITHM FROM NOISY CALCIUM FLUORESCENCE SIGNALS [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1690

ICASSP_poster_Paper_1008


This paper proposes a reliable 3D fish tracking method using a novel master-slave camera setup. Instead of conventional dynamic models that rely on prior knowledge about target kinematics, the proposed method learns the kinematic model with a Long Short-Term Memory (LSTM) network. On this basis, the 3D state of fish at each moment is predicted by LSTM network. We propose to use an innovative master-view-tracking-first strategy. The fish are first tracked in the master view. Cross-view association is then established utilizing motion continuity and epipolar constraint cues.

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Authors:
Shuo Hong Wang, Jingwen Zhao, Xiang Liu, Zhi-Ming Qian, Ye Liu, Yan Qiu Chen
Submitted On:
1 March 2017 - 10:13am
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Poster_ICASSP2017_Paper_1008.pdf

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[1] Shuo Hong Wang, Jingwen Zhao, Xiang Liu, Zhi-Ming Qian, Ye Liu, Yan Qiu Chen, "ICASSP_poster_Paper_1008", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1537. Accessed: Nov. 22, 2017.
@article{1537-17,
url = {http://sigport.org/1537},
author = {Shuo Hong Wang; Jingwen Zhao; Xiang Liu; Zhi-Ming Qian; Ye Liu; Yan Qiu Chen },
publisher = {IEEE SigPort},
title = {ICASSP_poster_Paper_1008},
year = {2017} }
TY - EJOUR
T1 - ICASSP_poster_Paper_1008
AU - Shuo Hong Wang; Jingwen Zhao; Xiang Liu; Zhi-Ming Qian; Ye Liu; Yan Qiu Chen
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1537
ER -
Shuo Hong Wang, Jingwen Zhao, Xiang Liu, Zhi-Ming Qian, Ye Liu, Yan Qiu Chen. (2017). ICASSP_poster_Paper_1008. IEEE SigPort. http://sigport.org/1537
Shuo Hong Wang, Jingwen Zhao, Xiang Liu, Zhi-Ming Qian, Ye Liu, Yan Qiu Chen, 2017. ICASSP_poster_Paper_1008. Available at: http://sigport.org/1537.
Shuo Hong Wang, Jingwen Zhao, Xiang Liu, Zhi-Ming Qian, Ye Liu, Yan Qiu Chen. (2017). "ICASSP_poster_Paper_1008." Web.
1. Shuo Hong Wang, Jingwen Zhao, Xiang Liu, Zhi-Ming Qian, Ye Liu, Yan Qiu Chen. ICASSP_poster_Paper_1008 [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1537

A Hybrid Task Graph Scheduler for High Performance Image Processing Workflows


Image Stitching Hybrid Task Graph

The scalability of applications is a key requirement to improving performance in hybrid and cluster computing. Scheduling code to utilize parallelism is difficult, particularly when dealing with dependencies, memory management, data motion, and processor occupancy. The Hybrid Task Graph Scheduler (HTGS) increases programmer productivity to implement hybrid workflows that scale to multi-GPU systems.

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Authors:
Walid Keyrouz, Milton Halem, Shuvra Bhattacharyya, Mary Brady
Submitted On:
23 February 2016 - 1:44pm
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GlobalSIP-Hybrid Task Graph Scheduler.pptx

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[1] Walid Keyrouz, Milton Halem, Shuvra Bhattacharyya, Mary Brady, "A Hybrid Task Graph Scheduler for High Performance Image Processing Workflows", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/451. Accessed: Nov. 22, 2017.
@article{451-15,
url = {http://sigport.org/451},
author = {Walid Keyrouz; Milton Halem; Shuvra Bhattacharyya; Mary Brady },
publisher = {IEEE SigPort},
title = {A Hybrid Task Graph Scheduler for High Performance Image Processing Workflows},
year = {2015} }
TY - EJOUR
T1 - A Hybrid Task Graph Scheduler for High Performance Image Processing Workflows
AU - Walid Keyrouz; Milton Halem; Shuvra Bhattacharyya; Mary Brady
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/451
ER -
Walid Keyrouz, Milton Halem, Shuvra Bhattacharyya, Mary Brady. (2015). A Hybrid Task Graph Scheduler for High Performance Image Processing Workflows. IEEE SigPort. http://sigport.org/451
Walid Keyrouz, Milton Halem, Shuvra Bhattacharyya, Mary Brady, 2015. A Hybrid Task Graph Scheduler for High Performance Image Processing Workflows. Available at: http://sigport.org/451.
Walid Keyrouz, Milton Halem, Shuvra Bhattacharyya, Mary Brady. (2015). "A Hybrid Task Graph Scheduler for High Performance Image Processing Workflows." Web.
1. Walid Keyrouz, Milton Halem, Shuvra Bhattacharyya, Mary Brady. A Hybrid Task Graph Scheduler for High Performance Image Processing Workflows [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/451

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