Optical and Digital Processing of Low Contrast Biological Features in Bio-Medical Imaging

תאריך: 
05/07/2016 - 14:00 - 15:00
Abstract: 

This seminar presents optical and digital techniques to obtain additional information from low contrast biological features. In the field of biological imaging, there are several limitations. The first is optical imitation, derived from the device which is used for imaging, such as diffraction limit and sensor resolution. Another set of limitations come from the nature of biological features which may be transparent, hidden, moving, or just sensitive to light\radiation. This work offers techniques to overcome imaging limitation which are related to the latter case, especially light-object interaction. In those cases there is no resolution limitation but the image features may be blurred in a way not all the information is revealed. We demonstrate several techniques for different systems:

· A new method for using phase-retrieval algorithm for de-blurring in the case where the blur is caused by low scattering diffusive media. The algorithm is demonstrated experimentally for the case of soft tissue as the diffusive media. The algorithm is using as constrains several images of the same object, taken at different focus planes.

· A new algorithm for phase retrieval, which uses a single image and digital resampling as constrains diversity. The algorithm is useful for imaging of transparent object, under “simple” microscope (not 3D technology), as demonstrated in the paper by retrieving a B16 melanoma cell image.

· Demonstration of how using differential imaging can retrieve data of neural cell development and growth, first by dividing the motion to high and low frequency and then by evaluating the motion spectrogram image.

* The work was carried out towards the Ph.D. degree in the Faculty of Engineering, Bar-Ilan University, with the supervision of Prof. Zeev Zalevsky

מרצה: 
Maya Aviv
דוא"ל להרשמה: 
Affiliation: 
Faculty of Engineering, Bar-Ilan University
מיקום: 
BIU Engineering Building 1103, Room 329