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 titleauthorsabstracttypejournalpublished year
DetailsCombining Learning-based
Intensity Distributions
with Nonparametric Shape
Priors for Image
Abdurrahim Soganli,
Gokhan Uzunbas, Müjdat
Integration of shape prior information into level
set formulations has led to great improvements in
image segmentation in the presence of missing information
occlusion and noise However most ...
Journal PaperSpringer Signal, Image
and Video Processing,
vol. 8, no. 4, pp.
789-798, May 2014
DetailsStandardized evaluation
methodology and reference
database for evaluating
IVUS image segmentation
Balocco S, Gatta C,
Ciompi F, Wahle A, Radeva
P, Carlier S, Unal G,
Sanidas E, Mauri J,
Carillo X, Kovarnik T,
Wang CW, Chen HC,
Exarchos TP, Fotiadis DI,
Destrempes F, Cloutier G,
Pujol O, Alberti M,
Mendizabal-Ruiz EG,
Rivera M, Aksoy T, Downe
RW, Kakadiaris IA.
This paper describes an evaluation framework that
allows a standardized and quantitative comparison
of IVUS lumen and media segmentation algorithms
This framework has been introduced at the ...
Journal PaperComput Med Imaging Graph.
2014 Mar;38(2):70-90
DetailsFeature compression: A
framework for multi-view
multi-person tracking in
visual sensor networks
Serhan Cosar, Müjdat
Visual sensor networks (VSNs) consist of image sensors
embedded processors and wireless transceivers which
are powered by batteries Since the energy and bandwidth
resources are limited setting
Journal Paper Journal of Visual
Communication and Image
Representation, vol. 25,
no. 5, pp. 864-873, July
DetailsSparsity-Driven Synthetic
Aperture Radar Imaging:
Autofocusing, Moving
Targets, and Compressed
Müjdat Çetin, Ivana
Stojanovic, N. Ozben
Onhon, Kush R. Varshney,
Sadegh Samadi, W. Clem
Karl, and Alan S. Willsky
This article presents a survey of recent research
on sparsity driven synthetic aperture radar (SAR)
imag ing In particular it reviews 1) the analysis
and synthe sis based sparse signal ...
Journal PaperIEEE Signal Processing
Magazine, vol. 31, no. 4,
pp. 27-40, July 2014
DetailsDecentralized Human
Tracking in Visual Sensor
Networks: Using Sparse
Representation for
Efficient Communication
Serhan Cosar, Müjdat
 Book ChapterHuman Behaviour
Understanding in
Networked (distributed)
Sensing - Theory and
applications of networks
of sensors, P. Spagnolo,
P. L. Mazzeo and C.
Distante (eds.),
Springer, 2014
DetailsProbabilistic Graphical
Models for Brain Computer
Jaime Delgado SaaBrain computer interfaces (BCI) are systems that
aim to establish a new communication path for subjects
who suffer from motor disabilities allowing interaction
with the environment through ...
Thesis 2014
DetailsDesign and Analysis of a
Interface-based Robotic
Rehabilitation System
Ela KoyasIn this thesis we have investigated the effect
of brain computer interfaces (BCI) which enable
direct communication between a brain and a computer
to increase the patient's active involvement to
Thesis 2014
DetailsDictionary Learning and
Low-rank Sparse Matrix
Decomposition for
Sparsity-driven SAR Image
Abdurrahim SoganliSynthetic aperture radar (SAR) is one of the most
widely used remote sensing modalities providing
images for a variety of applications including those
in defense environmental science and ...
Thesis 2014
DetailsScreened Poisson
Hyper-Fields for Shape
R. A. Guler, S. Tari, G.
We present a novel perspective on shape characterization
using the screened Poisson equation We discuss
that the effect of the screening parameter is a
change of measure of the underlying metric ...
Journal PaperSIAM Journal on Imaging
Sciences, Dec 2014
DetailsAutomatic Dendritic Spine
Detection using
Multiscale Dot
Enhancement Filters and
Sift Features
Lavdie Rada, Ertunc
Erdil, A. Ozgur Argunsah,
Devrim Unay, Mujdat Cetin
Statistical characterization of morphological changes
of dendritic spines is becoming of crucial interest
in the field of neurobiology Automatic detection
and segmentation of dendritic spines ...
Conference PaperICIP 20142014
DetailsOptimization of
Decentralized Random
Field Estimation Networks
under Communication
Constraints through Monte
Carlo Methods
Murat Üney, Müjdat
We propose a new methodology for designing decentralized
random field estimation schemes that takes the tradeoff
between the estimation accuracy and the cost of
communications into account We ...
Journal PaperDigital Signal
Processing, vol. 34, pp.
16-28, November 2014
Adaptation of Motor
Imagery Based BCI Systems
Ismail Yılmaz, Sümeyra
Demir, Tolga Tasdizen,
Müjdat Çetin
One of the main problems in Brain Computer Interface
(BCI) systems is the non stationary behavior of
the electroencephalography (EEG) signals causing
problems in real time applications Another ...
Conference PaperSIU 20152015
DetailsAdaptive Neurofeedback on
Parieto-Occipital Cortex
for Motor Learning
Ozan Özdenizci, Timm
Meyer, Müjdat Çetin,
Moritz Grosse-Wentrup
Numerous electroencephalogram (EEG) based Brain
Computer Interface (BCI) systems are being used
as alter native means of communication for locked
in patients Beyond these BCIs are also ...
Conference PaperSIU 20152015
DetailsDendritic Spine Shape
Classification from
Two-Photon Microscopy
Muhammad Usman Ghani,
Sümeyra Demir Kanık,
Ali Özgür Argunsah,
Tolga Tasdizen, Devrim
Ünay, Müjdat Çetin
Functional properties of a neuron are coupled with
its morphology particularly the morphology of dendritic
spines Spine volume has been used as the primary
morphological parameter in order the ...
Conference PaperSIU 20152015
DetailsA Joint Classification
And Segmentation Approach
For Dendritic Spine
Segmentation in 2-photon
Microscopy Images
Ertunc Erdil, A. Ozgur
Argunsah, Tolga Tasdizen,
Devrim Unay, Mujdat Cetin
Shape priors have been successfully used in challenging
biomedical imaging problems However when the shape
distribution involves multiple shape classes leading
to a multimodal shape density ...
Conference PaperIEEE International
Symposium Biomedical
Imaging, ISBI 2015, New
DetailsAutomated Dendritic Spine
Tracking on 2-Photon
Microscopic Images
Biike Kılıç, Lavdie
Rada, Ertunç Erdil, A.
Özgür Argunsah, Müjdat
Çetin, Devrim Ünay
The rapid and spontaneous morphological changes
of dendritic spines have been an important observation
to understand how information is stored in brain
Manual assessment of spine structure has ...
Conference PaperSIU 20152015
decentralized tracking in
visual sensor networks
Serhan Cosar, Müjdat
Recent developments in low cost CMOS cameras have
created the opportunity of bringing imaging capabilities
to sensor networks and a new field called visual
sensor networks (VSNs) has emerged VSNs ...
Journal PaperComputer Vision and Image
Understanding, vol. 139,
pp. 40-58, October 2015
DetailsOn the Quality and
Timeliness of Fusion in a
Random Access Sensor
Abdurrahim Soganli, Ozgur
Ercetin, Müjdat Çetin
In this letter we investigate the trade off between
the quality of multi sensor fusion decision and
the delay of making that decision in a random access
sensor network in a particular setting ...
Journal PaperIEEE Signal Processing
Letters, vol. 22, no. 9,
pp. 1259-1263, September
DetailsWord-level Language
Modeling for P300
Spellers based on
Discriminative Graphical
Jaime Fernando Delgado
Saa, Adriana de Pesters,
Dennis McFarland, Müjdat
In this work we propose a probabilistic graphical
model framework that uses language priors at the
level of words as a mechanism to increase the performance
of P300 based spellers Approach This ...
Journal PaperJournal of Neural
Engineering, vol. 12, no.
2, p. 026007, April 2015
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