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Melvin H Lax

Deceased

from Summit, NJ

Melvin Lax Phones & Addresses

  • 12 High St, Summit, NJ 07901 • 908 273-6188
  • Concord, MA
  • New York, NY

Wikipedia References

Melvin Lax Photo 1

Melvin Lax

About:
Born:

1922

Died:

2002

Work:
Area of science:

Physicist

Company:

City College of New York • Syracuse University faculty

Position:

Chairman

Education:
Studied at:

Massachusetts Institute of Technology • New York University

Academic degree:

Member of the United States National Academy of Sciences • Professor

Skills & Activities:

He was also a Fellow of the American Academy of Arts and Sciences, the American Physical Society, the American Association for the Advancement of Science, and the Optical Society of America....

Isbn (Books And Publications)

  • Random Processes In Physics And Finance

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  • Author:
    Melvin Lax
  • ISBN #:
    0198567766
  • Symmetry Principles In Solid State And Molecular Physics

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  • Author:
    Melvin J. Lax
  • ISBN #:
    0486420019
  • Symmetry Principles In Solid State And Molecular Physics

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  • Author:
    Melvin J. Lax
  • ISBN #:
    0471519030
  • Symmetry Principles In Solid State And Molecular Physics

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  • Author:
    Melvin J. Lax
  • ISBN #:
    0471519049
  • Frontiers In Condensed Matter Theory: Proceedings Of A U.s. - U.s.s.r. Conference Held In New York City, December 4-8, 1989

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  • Author:
    Melvin J. Lax
  • ISBN #:
    0883187728

Us Patents

  • Time-Resolved Diffusion Tomographic 2D And 3D Imaging In Highly Scattering Turbid Media

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  • US Patent:
    59317892, Aug 3, 1999
  • Filed:
    Feb 7, 1997
  • Appl. No.:
    8/797028
  • Inventors:
    Robert R. Alfano - Bronx NY
    Wei Cai - Bronx NY
    Feng Liu - Bronx NY
    Melvin Lax - Summit NJ
    Bidyut B. Das - Flushing NY
  • Assignee:
    The Research Foundation City College of New York - New York NY
  • International Classification:
    A61B 500
  • US Classification:
    600473
  • Abstract:
    A method for imaging objects in highly scattering turbid media. According to one embodiment of the invention, the method involves using a plurality of intersecting source/detectors sets and time-resolving equipment to generate a plurality of time-resolved intensity curves for the diffusive component of light emergent from the medium. For each of the curves, the intensities at a plurality of times are then inputted into the following inverse reconstruction algorithm to form an image of the medium: ##EQU1## wherein W is a matrix relating output at source and detector positions r. sub. s and r. sub. d, at time t, to position r,. LAMBDA. is a regularization matrix, chosen for convenience to be diagonal, but selected in a way related to the ratio of the noise, to fluctuations in the absorption (or diffusion) X. sub. j that we are trying to determine:. LAMBDA. sub. ij =. lambda. sub. j. delta. sub. ij with. lambda. sub. j =/
  • Time-Resolved Diffusion Tomographic Imaging In Highly Scattering Turbid Media

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  • US Patent:
    58139885, Sep 29, 1998
  • Filed:
    Mar 18, 1996
  • Appl. No.:
    8/618471
  • Inventors:
    Robert R. Alfano - Bronx NY
    Wei Cai - Bronx NY
    Feng Liu - Bronx NY
    Melvin Lax - Summit NJ
    Bidyut B. Das - Flushing NY
  • Assignee:
    Research Foundation - New York NY
  • International Classification:
    A61B 500
  • US Classification:
    600476
  • Abstract:
    A method for imaging objects in highly scattering turbid media. According to one embodiment of the invention, the method involves using a plurality of intersecting source/detectors sets and time-resolving equipment to generate a plurality of time-resolved intensity curves for the diffusive component of light emergent from the medium. For each of the curves, the intensities at a plurality of times are then inputted into the following inverse reconstruction algorithm to form an image of the medium: X. sup. (k+1). spsp. T =�Y. sup. T W+X. sup. (k). spsp. T. LAMBDA. !�W. sup. T W+. LAMBDA. !. sup. -1 wherein W is a matrix relating output at detector position r. sub. d, at time t, to source at position r. sub. s,. LAMBDA. is a regularization matrix, chosen for convenience to be diagonal, but selected in a way related to the ratio of the noise, to fluctuations in the absorption (or diffusion) X. sub. j that we are trying to determine:. LAMBDA. sub. ij =. lambda. sub. j. delta. sub. ij with. lambda. sub.
  • Time-Resolved Optical Backscattering Tomographic Image Reconstruction In Scattering Turbid Media

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  • US Patent:
    62053531, Mar 20, 2001
  • Filed:
    Dec 22, 1998
  • Appl. No.:
    9/218199
  • Inventors:
    R. R. Alfano - Bronx NY
    Wei Cai - Bronx NY
    Melvin Lax - Summit NJ
  • Assignee:
    Research Foundation of CUNY - New York NY
  • International Classification:
    A61B 505
  • US Classification:
    600476
  • Abstract:
    A method for imaging objects in a highly scattering turbid medium, such as breast, brain, prostate in human body and clouds, smoke in atmosphere environment, using backscattered light. The method involves using a group of sources and detectors setting on same side of medium to generate a plurality of time-resolved intensity data of backscattered light from the medium. The inverse computation using a reconstruction algorithm, taking the measured data as input, produces a three-dimensional image map of the internal structure of a turbid medium. The invention teaches (1) developing an accurate analytical solution of the Boltzmann photon transport equation in a uniform infinite medium, and its extension to the case of a semi-infinite medium, which serves as a background Green's function for the forward model; (2) building a forward physical model of relationship between measurement of backscattered light and inhomogeneity structure of the medium; (3) designing an inverse algorithm for backscattering tomography; (4) designing experimental setups for breast tumor detection using backscattering tomography; (5) using fsec, psec, and nsec laser pulse with different wavelengths in the near infrared spectral region; and (6) using pico-second time gating system as detectors to collect time-slicing data.

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