Shahar Gottlieb

Shahar Gottlieb

 

My name is Shahar Gottlieb and I was born in 1993. In high school I majored in physics and music.

I think there is a lot in common between musicians and engineers! When graduating high school, I became a tank commander in the IDF for 3 years.

Then- after a year of backpacking abroad I’m currently studying computer engineering at the Technion. In my free time, I love hiking and to sing and play music on various instruments.

 

 

Yuval Silman

Yuval Silman

I was born in 1992, in Haifa. In high school I studied physics and chemistry.

I served in the IDF, in the unit of bomb disposal (EOD specialist) as a combat soldier and as a commander.

After my military service I worked on MSC cruise ships as the Chief Security on board. When I returned back to Israel I studied the real estate field and experienced entrepreneur. I enjoy overcoming obstacles and expanding my horizons.

 

 

Super-Resolution Optical Fluctuation Imaging Simulator

Supervisor(s): Prof. Yonina Eldar, Oren Solomon
Abstract: For 120 years, people believed that Abbe’s diffraction law in far field optics, which sets a minimal separation distance for two adjacent objects in an image, cannot be circumvented. 2014 stood out as a celebrated year for super-resolution microscopy, in which three Nobel Prize winners proved us wrong and were acknowledged for their contribution to super-resolution optical fluorescence microscopy. Today, super-resolution imaging techniques such as STORM and PALM enable biologists and other researchers see beyond the diffraction limit and observe intra-cellular entities and dynamics within living cells. Due to several limitations within these techniques, a new technique termed SOFI emerged, which utilizes not only spatial information, but also temporal information in order to construct super-resolution images of cells.
Description: PDF

Super-Resolution in Computer Tomography (CT)

Supervisor(s): Prof. Yonina Eldar, Shahar Tsiper
Abstract: X-Ray Computer Tomography, known as CT, is one of the main tools Doctors use today to examine patients. In every main hospital, there are CT machines that work 24/7 to provide Doctors with in-depth views of the human body. CT Scans enable them to save lives on a daily basis. Today, 3rd generation CTs can scan over 100 patients a day, but their radiation dose is relatively high. For instance, an abdomen CT scan radiation dose is equivalent to almost a 1000 chest Xray scans.It is highly desirable to reduce the radiation dose, while preserving the resolution and details of the scans. This is where we come in. In this project the students will first study the basics of computer aided tomography, advanced mathematical imaging tools and cutting edge techniques in digital signal processing. The students will then research, design and implement a novel reconstruction algorithm for CT scans, which could allow faster scan times and reduced radiation dosage. The basis for this algorithm will implement principles from novel fields such as “Compressed Sensing” and “Super Resolution by Dictionary Learning”.
Description: PDF