Thursday, June 10, 2010

New website

The University of Rochester SPIE Student Chapter has moved to this website.

Thursday, August 6, 2009

SPIE Student Chapter

Seminar Series

hosted by the Institute of Optics


Second Harmonic Generation Microscopy”


Xiaoxing Han

Graduate Student

Institute of Optics

University of Rochester Medical Center


Tuesday, 11 August 2009

11:00 AM - 12:00 PM

Sloan Auditorium, Room 101, Goergen Hall

University of Rochester


Abstract

Second Harmonic Combination (SHG) is the non-absorptive combination of two excitation photons into one emission photon within a non-centrosymmetric medium such as a crystal surface, or properly ordered fibers. In practice, SHG microscopy is quite similar to Two Photon Excitation Fluorescence (TPEF) microscopy. However, there is acrucial difference between SHG and TPEF. SHG is based onscattering, meaning that it is a coherent phenomenon, whereas TPEF is based on fluorescence (i.e. absorption followed by emission),meaning that it is incoherent. My research work is focused onexploiting these coherent properties of SHG emission to study the molecule structure of collagen fiber in tumor Extra Cellular Matrix (ECM). The two coherent properties I used to study tumor collagen molecule structures are polarization and the ratio of forward vs. backward propagating SHG

Wednesday, July 8, 2009

Seminar Series: July 14, 2009

SPIE Student Chapter

Seminar Series

hosted by the Biomedical Engineering Dept. and Institute of Optics


Optical Interference Coatings: Modern Design Methods”


Jennifer Kruschwitz

Principal Engineer

JK Consulting


Adjunct Faculty

Institute of Optics

University of Rochester



Tuesday, 14 July 2009

11:00 AM - 12:00 PM

Sloan Auditorium, Room 101, Goergen Hall

University of Rochester


Abstract

Optical interference coatings are an integral part of most optical systems. System requirements have increased in complexity in the past 20 years and the modern designer not only has to meet customer specifications, but also enable the manufacturer to create product easily and efficiently. This presentation will review several design projects supported by JK Consulting in the past 10 years and some of the design methodologies used.





Thursday, June 25, 2009

Student Seminar: June 30, 2009

SPIE Student Chapter

Seminar Series

hosted by the Biomedical Engineering Dept. and Institute of Optics



Two-Photon Fields: Coherence, Interference, and Entanglement”

Anand Jha

Ph.D. candidate

Institute of Optics

University of Rochester

Tuesday, 30 June 2009

11:00 AM - 12:00 PM

Sloan Auditorium, Room 101, Goergen Hall

University of Rochester


Abstract

Parametric down-conversion is a second-order nonlinear process in which a pump photon breaks up into two separate photons known as the signal photon and the idler photon. Due to the phase-matching constraints, the signal and idler photons are rendered entangled in their: energy and emission-time, position and transverse momentum, and angular position and orbital angular momentum. Because of these correlations, the signal and idler photons can be described adequately only as a single, two-photon system. In this talk, I am going to present our studies on the coherence and entanglement properties of the down-converted two-photon field, through two-photon interference effects in temporal, spatial and angular domains.


Bio

Anand Kumar Jha is a PhD student in the research group of Prof. Robert W. Boyd at the Institute of Optics, University of Rochester, New York. He transferred there in 2003 from the Physics PhD program at the University of Illinois at Urbana-Champaign. He received the BSc and MSc in Physics in 2002 from the Indian Institute of Technology (IIT), Kharagpur, India. Anand also plays a mean game of badminton.

Friday, June 19, 2009

Student Seminar: June 23, 2009

SPIE Student Chapter

Seminar Series

hosted by Department of Biomedical Engineering


"Quantum Ghost Image Discrimination with A Single Pair of Photons"


Mehul Malik

Institute of Optics Graduate Student

University of Rochester

Tuesday, 23 June 2009

11:00 AM - 12:00 PM

Room 209, Computer Studies Building (CSB)

Tuesday, June 9, 2009

Student Seminar: June 16, 2009

SPIE Student Chapter

Seminar Series

hosted by Department of Biomedical Engineering


"Computed tomography-based lung nodule detection, growth and treatment"


Walter G. O'Dell, Ph.D.

Assistant Professor,

Departments of Radiation Oncology and Biomedical Engineering

University of Rochester Medical Center


Tuesday, 16 June 2009

10:30-11:30 AM

Room 209, Computer Studies Building (CSB)
University of Rochester

Tuesday, June 2, 2009

Student Seminar: June 9, 2009

SPIE Student Chapter

Seminar Series

hosted by Department of Biomedical Engineering

Spectral Remote Sensing: What is the "dimension" of my image, how do I calculate it, and why do I care?”


David W. Messinger, Ph.D.

Director, Digital Imaging and Remote Sensing Laboratory

Chester F. Carlson Center for Imaging Science

Rochester Institute of Technology


Tuesday, 9 June 2009

1:00-2:30 PM

Room 109, Goergen Hall

University of Rochester


Abstract

Spectral remote sensing uses advanced digital imaging techniques to collect images, typically from aircraft or satellites, in not one spectral band (i.e., black and white), or three bands (i.e., blue, green, and red), or even the rainbow of seven colors (i.e., ROYGBIV). Instead, we are able to collect hundreds of spectral bands for each pixel on the ground typically covering wavelengths from 0.4 - 2.0 um. This allows us to use techniques from spectroscopy to better differentiate between materials on the ground as each unique material has a unique spectral reflectance. Typical applications include land cover classification and target detection. In some sense, these images are measured in hundreds of "dimensions" - one for each spectral

band collected. However, due to the physics of the photon interactions along the sun-surface-sensor path, the data can be correlated and don't "fill up" the full hyperspace. A method will be presented using a simple algorithm based on Point Density Estimation to calculate the inherent dimensionality of samples from a spectral image and we will show that it is typically very small (~5-10). We will also show how the dimension estimation methodology can lead to algorithms to extract information out of the image.