Statistical signal processing and estimation theory
Compressive sensing with application to single molecule microscopy
Image and signal processing, biomedical image analysis with applications to fluorescence microscopy
Single molecule localization and tracking in live cells
Mammography image analysis
Pattern recognition (cognitive, statistical)
Real-time image and signal processing on TMS320C6xxx platforms
Work and Research Experiance
Ward-Ober Lab, Department of Immunology, UT Southwestern Medical Center, Dallas, USA, Sep 2011 - present.
Satellite Research Center (SRC), Iran University of Science and Technology (IUST), Tehran, Iran, Dec 2010 - Jul 2011.
Optoelectronics and Machine Vision Research Lab., Department of Electrical Engineering, Iran University of Science and Technology (IUST), Tehran, Iran, Sep 2009 - Dec 2010.
Satellite Research Center (SRC), Iran University of Science and Technology (IUST), Tehran, Iran, Jun 2009 - Feb 2010.
Shayan Tarh Co., Shiraz, Iran, summer 2008.
Digital Signal Processing Research Lab., Department of Electrical Engineering, Shiraz University of Technology (SuTech), Shiraz, Iran, Mar 2008 - Jun 2008.
List of selected projects (by year)
For more information about each project (downloading the code, etc.), click the
corresponding link.
A tool to calculate the fundamental localization accuracy measure (FLAM),
the practical localization accuracy measure (PLAM),
the fundamental resolution measure (FREM) and the practical resolution measure (PREM)
in both 2D and 3D, i.e. to calculate Fisher information matrix (FIM) and Cramer Rao lower
bound (CRLB), which can aid in the design and execution of imaging experiments. For more
information please visit
FandPLimitTool homepage.
This project was supported by National Institutes of Health
(NIH).
A. Tahmasbi,
"FandPLimitTool and MUMDesignTool step by step tutorial,"
Ward Ober Lab, University of Texas Southwestern Medical Center,
Dallas, USA, 2012.
A tool to design the focal plane spacing for a MUM setup (up to 10 focal planes).
It is developed to interactively calculate and plot the different elements of the Fisher information matrix
(FIM) and the practical localization accuracy measure (PLAM) along the z-axis in the runtime.
For more information please visit
MUMDesignTool homepage.
This project was supported by National Institutes of Health
(NIH).
A high bit-rate S-Band transceiver developed to transfer the image payload data of a LEO satellite at 600 Kbps. It is equipped with distinct
AGC and AFC blocks to correct the receiver sensitivity as well as the Doppler effect. A modified version of HDLC is utilized as the data
handling and transferring algorithm.
This project was supported by Iranian Space Agency (ISA).
A. Tahmasbi, S. Jahangirzadeh, S. M. Seyedzadeh, F. Saki, S. B. Shokouhi,
"An Effective Approach for Data Extraction from Antenna Polar Patterns,"
in Proc. IEEE, 7th Iranian Conference on Machine Vision and Image Processing (MVIP'2011),
Tehran, Iran, 2011, pp. 1-4.
In many signal processing applications such as airborne laser bathymetry, Doppler radar, EEG and EOG,
differentiation is followed by low-pass filtering; differentiation is used to extract information about sharp transients in the signal
while Low-pass filtering is used to reject high frequency noises. In this project, we introduced several optimized IIR low-pass differentiators
(LPD) with an almost linear phase in the pass-band. The proposed LPDs can approximate high-order Parks-McClellan FIR LPDs with a good level
of accuracy.
A. Tahmasbi, S. B. Shokouhi,
"New Approach for Approximating Parks McClellan Low-Pass Differentiators,"
in Proc. IEEE, Int. Conf. on Signal Acquisition and Processing (ICSAP'2010),
Bangalore, India, 2010, pp. 188-192.
A. Tahmasbi, S. B. Shokouhi,
"New Optimized IIR Low-Pass Differentiators,
"in Proc. IEEE, Int. Conf. on Signal Acquisition and Processing (ICSAP'2010),
Bangalore, India, 2010, pp. 205-209.
Real-time Face Detection and Recognition System (2008)
S. M. Seyedzade, S. Mirzakuchaki, A. Tahmasbi,
"Using Subclass Discriminant Analysis, Fuzzy Integral and Symlet Decomposition for Face Recognition,"
in Proc. IEEE, Int. Conf. on Signal Processing Systems (ICSPS'2010),
Dalian, China, 2010, vol. 1, pp. 372-377.
S. M. Seyedzade, S. Mirzakuchaki, A. Tahmasbi,
"Using Symlet Decomposition Method, Fuzzy Integral and Fisherface Algorithm for Face Recognition,"
in Proc. IEEE, Int. Conf. on Computer Engineering and Applications (ICCEA'2010),
Bali, Indonesia, 2010, vol. 2, pp. 83-88.
