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Binsheng Zhao

from Forest Hills, NY
Age ~61
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Connected to:
Baobin Zhao, 58Baoshu E Zhao, 63Carmel J Zhao, 29Changhui Zhao, 40Chaobo Zhao, 57Ching H Zhao, 66Chinong Zhao, 55Chonghua Zhao, 63Chongqiu Zhao, 35Chunyi Zhao, 57

Binsheng Zhao Phones & Addresses

  • 11011 Queens Blvd APT 8L, Forest Hills, NY 11375
  • Flushing, NY
  • 450 63Rd St, New York, NY 10021 (212) 750-6102
  • Hollis, NY

Resumes

Resumes

Binsheng Zhao Photo 1

Associate Professor At Columbia University Medical Center

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Location:
New York, NY
Industry:
Hospital & Health Care
Work:
Columbia University Medical Center
Associate Professor at Columbia University Medical Center
Binsheng Zhao Photo 2

Associate Attending Physicist

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Location:
New York, NY
Industry:
Hospital & Health Care
Work:
Memorial Sloan-Kettering Cancer Center
Associate Attending Physicist
Binsheng Zhao Photo 3

Associate Professor

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Location:
New York, NY
Industry:
Hospital & Health Care
Work:
Columbia University Medical Center
Associate Professor

Publications

Us Patents

Automated Determination Of Lymph Nodes In Scanned Images

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US Patent:
8355552, Jan 15, 2013
Filed:
Jun 19, 2008
Appl. No.:
12/142766
Inventors:
Lawrence H. Schwartz - New York NY, US
Binsheng Zhao - Forest Hills NY, US
Jiayong Yan - Roosevelt Island NY, US
Assignee:
The Trustees of Columbia University in the City of New York - New York NY
International Classification:
G06K 9/00
US Classification:
382131, 382133
Abstract:
Techniques include automatically detecting a lymph node in a scanned image of a body without human intervention, using one or more of three approaches. First, a subset of scanned images is determined, which belongs to one anatomical domain. A search region for lymph tissue is in a particular spatial relationship outside an anatomical object in the domain. Second, scanned images are segmented without human intervention to determine a boundary of a particular lymph node. The scanned images and outline data are received. Some of these embodiments automatically segment by determining an external marker, based on the outline data, and an internal marker, based on a geometric center of the outline data or thresholds determined automatically inside detected edges, or both, for a marker-controlled watershed algorithm. Third, based on lymph node data at a particular time, a second scanned image at a different time is segmented automatically, without human intervention.

Method And Systems For Quality Assurance Of Cross Sectional Imaging Scans

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US Patent:
20140029828, Jan 30, 2014
Filed:
Mar 15, 2012
Appl. No.:
14/005544
Inventors:
Lawrence H. Schwartz - New York NY, US
Yongqiang Tan - Elmhurst NY, US
Binsheng Zhao - Forest Hills NY, US
International Classification:
G06T 7/00
US Classification:
382131
Abstract:
A method of verifying compliance of a cross sectional imaging scan of a subject is provided, which includes determining one or more body volumes covered by the cross sectional imaging scan, and for each of the determined one or more body volumes, locating a presence of at least a portion of one or more internal organs of the subject encompassed in a corresponding determined volume, thereby verifying whether the cross sectional imaging scan is compliant with predetermined criteria. The predetermined criteria can be body coverage criteria for a scan of one or more body regions of the subject. Additionally, a method for verifying whether an image series of a cross sectional imaging scan is performed with contrast is provided.

Automatic Detection Of Pulmonary Nodules On Volumetric Computed Tomography Images Using A Local Density Maximum Algorithm

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US Patent:
6728334, Apr 27, 2004
Filed:
Oct 23, 2002
Appl. No.:
10/279592
Inventors:
Binsheng Zhao - Forest Hills NY
Assignee:
Cornell Research Foundation, Inc. - Ithaca NY
International Classification:
G01N 2304
US Classification:
378 62, 378 4, 378901, 382131
Abstract:
A three dimensional mask of the lungs can be automatically created by thresholding, labeling connected components, selecting the dominant object, and alternately employing dilation and erosion operations. With this mask the lungs can be separated from the other anatomic structures on volumetric CT images. Local density maxima in the lungs are then determined by sequentially decreasing thresholds. As the threshold declines, more and more objects (a 3D object is a group of connected voxels with density values larger than the threshold) become apparent. Geometrically overlapped objects at the subsequent threshold levels are either merged into one object or identified as local density maximum (maxima) and plateau. This process terminates if the threshold reaches a predefined density value. Other information about small lung nodules such as compact shape and size are combined into the algorithm to further remove those detected local density maxima that are not likely to be nodules.

Medical Imaging Based On Calibrated Post Contrast Timing

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US Patent:
20210279868, Sep 9, 2021
Filed:
May 21, 2021
Appl. No.:
17/303145
Inventors:
- New York NY, US
Laurent Dercle - New York NY, US
Binsheng Zhao - Forest Hills NY, US
Lin Lu - New York NY, US
Lawrence H. Schwartz - New York NY, US
International Classification:
G06T 7/00
G06N 3/08
G06K 9/32
Abstract:
Techniques measuring post contrast phase include collecting 3D medical imagery of a subject after injection with a contrast agent. A first set of slices is obtained in which each includes a first anatomical feature selected from a portal vein, aorta, inferior vena cava, liver, spleen or renal cortex. A second set of slices is obtained in which each includes a different second anatomical feature. A first image region is obtained from the first set and a different second image region from the second set. A trained convolutional neural network is configured to input the first image region to a first plurality of convolutional hidden layers and the second image region to a second plurality of convolutional hidden layers and output from both to a fully connected hidden layer that outputs a post contrast phase. Output data is presented based on the post contrast phase.

Techniques For Segmentation Of Lymph Nodes, Lung Lesions And Other Solid Or Part-Solid Objects

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US Patent:
20190355117, Nov 21, 2019
Filed:
Jun 3, 2019
Appl. No.:
16/430175
Inventors:
- New York NY, US
Binsheng Zhao - Forest Hills NY, US
Lawrence H. Schwartz - New York NY, US
International Classification:
G06T 7/00
G06T 15/06
G06T 7/12
G06T 7/149
G06T 7/155
G06T 7/136
Abstract:
Techniques for segmentation include determining an edge of voxels in a range associated with a target object. A center voxel is determined. Target size is determined based on the center voxel. In some embodiments, edges near the center are suppressed, markers are determined based on the center, and an initial boundary is determined using a watershed transform. Some embodiments include determining multiple rays originating at the center in 3D, and determining adjacent rays for each. In some embodiments, a 2D field of amplitudes is determined on a first dimension for distance along a ray and a second dimension for successive rays in order. An initial boundary is determined based on a path of minimum cost to connect each ray. In some embodiments, active contouring is performed using a novel term to refine the initial boundary. In some embodiments, boundaries of part-solid target objects are refined using Markov models.

Method And Apparatus To Perform Local De-Noising Of A Scanning Imager Image

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US Patent:
20190073748, Mar 7, 2019
Filed:
Mar 14, 2017
Appl. No.:
16/085611
Inventors:
Lin Lu - New York NY, US
Binsheng Zhao - Forest Hills NY, US
International Classification:
G06T 5/00
G06K 9/62
G06K 9/46
Abstract:
A method is provided to perform local de-noising of an image. The method includes obtaining a region of interest and a region of noise within a scan. The method also includes determining, for a first image based on the region of interest and a second image based on the region of noise, sample blocks and atoms for each image, where each atom contributes to a weighted sum that approximates a sample block in the image. The method also includes determining a measure of similarity of each atom from the first image with atoms from the second image and removing an atom from the first image if the measure of similarity exceeds a predetermined threshold value. The method also includes reconstructing a de-noised image based on atoms remaining in the first image after removing the atom from the first image, and presenting the de-noised image on a display device.

Methods And Systems For Segmentation Of Organs And Tumors And Objects

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US Patent:
20150078640, Mar 19, 2015
Filed:
Apr 11, 2013
Appl. No.:
14/394097
Inventors:
Xiaotao Guo - Bronx NY, US
Binsheng Zhao - Forest Hills NY, US
Lawrence H. Schwartz - New York NY, US
Assignee:
The Trustees of Columbia University in the City of New York - New York NY
International Classification:
G06T 7/00
US Classification:
382131
Abstract:
Techniques for segmentation of organs and tumors and cells in image data include revising a position of a boundary by evaluating an evolution equation that includes differences of amplitude values for voxels on the boundary from a statistical metric of amplitude of voxels inside, and from a statistical metric of amplitude of voxels outside, for a limited region that lies within a distance r of the boundary. The distance r is small compared to a perimeter of the first boundary. Some techniques include determining a revised position of multiple boundaries by evaluating an evolution equation that includes differences in a first topographical distance from a first marker and a second topographical distance from a second marker for each voxel on the boundary, and also includes at least one other term related to boundary detection.

Techniques For Segmentation Of Lymph Nodes, Lung Lesions And Other Solid Or Part-Solid Objects

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US Patent:
20150078641, Mar 19, 2015
Filed:
Apr 11, 2013
Appl. No.:
14/394098
Inventors:
Yongqiang Tan - Forest Hills NY, US
Binsheng Zhao - Forest Hills NY, US
Lawrence H. Schwartz - New York NY, US
Assignee:
The Trustees of Columbia University in the City of New York - New York NY
International Classification:
G06T 7/00
US Classification:
382131
Abstract:
Techniques for segmentation include determining an edge of voxels in a range associated with a target object. A center voxel is determined. Target size is determined based on the center voxel. In some embodiments, edges near the center are suppressed, markers are determined based on the center, and an initial boundary is determined using a watershed transform. Some embodiments include determining multiple rays originating at the center in 3D, and determining adjacent rays for each. In some embodiments, a 2D field of amplitudes is determined on a first dimension for distance along a ray and a second dimension for successive rays in order. An initial boundary is determined based on a path of minimum cost to connect each ray. In some embodiments, active contouring is performed using a novel term to refine the initial boundary. In some embodiments, boundaries of part-solid target objects are refined using Markov models.
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Binsheng Zhao from Forest Hills, NY, age ~61 Get Report