George Jeffrey Washko

US Patent:

20100172558, Jul 8, 2010

Filed:

Oct 3, 2007

Appl. No.:

12/444188

Inventors:

Raúl San José Estépar - Cambridge MA, US
George G. Washko - West Roxbury MA, US
Edwin K. Silverman - Arlington MA, US
John J. Reilly - Wellesley MA, US
Ron Kikinis - Chestnut Hill MA, US
Carl-Fredrik Westin - Cambridge MA, US

Assignee:

THE BRIGHAM AND WOMEN S HOSPITAL, INC. - Boston MA

International Classification:

G06K 9/40
G06K 9/00

US Classification:

382131, 382260

Abstract:

A method for reconstructing an image includes receiving tomographic data representative of an image signal; deriving, from the image signal, a plurality of components; identifying a spatial location associated with maximum phase congruency of the components; incorporating, into an image, an edge at the spatial location; and providing an output representative of the image.

US Patent:

20210350934, Nov 11, 2021

Filed:

May 6, 2021

Appl. No.:

17/313525

Inventors:

- Newton MA, US
Raul San Jose Estepar - Wellesley MA, US
George Washko - West Roxbury MA, US

International Classification:

G16H 50/50
G06T 11/00
G06K 9/62
G06F 30/23
G06F 30/27
G16H 50/70
G16H 30/20
G16H 30/40
G16H 50/20
G16H 20/10
G16H 20/30
G16H 70/60

Abstract:

Systems and methods for creating therapeutic response predictions based on a synthetic tumor model generated based on micro-scale data associated with one or more parameters representative of one or more biological characteristics of tumors, where synthetic CT images constructed via back projection of the synthetic tumor model and distribution/response of one or more therapeutic therapies predicted for the synthetic tumor model are used to train an unsupervised learning model for determining a personalized treatment plan for a patient's tumor.

US Patent:

20210350935, Nov 11, 2021

Filed:

May 6, 2021

Appl. No.:

17/313553

Inventors:

- NEWTON MA, US
Raul San Jose Estepar - Wellesley MA, US
George Washko - West Roxbury MA, US

International Classification:

G16H 50/50
G06N 20/10
G06N 3/08
G16H 30/00

Abstract:

Systems and methods for creating therapeutic response predictions based on a synthetic tumor model generated based on micro-scale data associated with one or more parameters representative of one or more biological characteristics of tumors, where synthetic CT images constructed via back projection of the synthetic tumor model and distribution/response of one or more therapeutic therapies predicted for the synthetic tumor model are used to train an unsupervised learning model for determining a personalized treatment plan for a patient's tumor.