Drew A Torigian

US Patent:

20220254026, Aug 11, 2022

Filed:

Feb 10, 2021

Appl. No.:

17/172741

Inventors:

- Philadelphia PA, US
Vibhu Agrawal - Philadelphia PA, US
Yubing Tong - Springfield PA, US
Drew A. Torigian - Philadelphia PA, US

International Classification:

G06T 7/00
G06N 3/08
G06N 3/04
G06T 7/11
G06K 9/62

Abstract:

Provided are systems and methods for analyzing medical images to localize body regions using deep learning techniques. A combination of convolutional neural network (CNN) and a recurrent neural network (RNN) can be applied to medical images, identifying axial slices of a body region. In accordance with embodiments, boundaries, e.g., superior and inferior boundaries of various body regions in computed tomography images can be automatically demarcated.

US Patent:

20230129957, Apr 27, 2023

Filed:

Mar 4, 2021

Appl. No.:

17/908730

Inventors:

- Phitadelpnia PA, US
Tiange LIU - Qinhuangdao, CN
Yubing TONG - Chesterbroook PA, US
Drew A. TORIGIAN - Philadelphia PA, US

International Classification:

A61B 6/03
A61B 6/00
G06T 7/00
G06T 7/10

Abstract:

Methods and systems are described for determining body composition information. An example method can comprise receiving imaging data associated with a patient, causing the imaging data to be input into a convolutional neural network stored on one or more computing devices, determining, based on output data resulting from inputting the imaging data into the convolutional neural network, body composition information, and causing output of the body composition information.

US Patent:

20230111593, Apr 13, 2023

Filed:

Feb 12, 2021

Appl. No.:

17/799171

Inventors:

- Basel, CH
- Philadelphia PA, US
Jayaram K. UDUPA - Philadelphia PA, US
Drew A. TORIGIAN - Philadelphia PA, US

International Classification:

G16H 50/50
A61K 35/17
A61K 38/17
A61P 35/00
G06V 10/82
G06V 10/764
G06T 7/00

Abstract:

This disclosure provides methods and systems for determining a lesion-level treatment response to a chimeric antigen receptor (CAR) therapy, e.g., a CAR CD19 therapy, and uses of said methods and systems for evaluating the responsiveness of a subject to a CAR CD19 therapy, and for treating a subject with a CAR CD19 therapy.

US Patent:

20230050512, Feb 16, 2023

Filed:

Feb 10, 2021

Appl. No.:

17/794032

Inventors:

- Philadelphia PA, US
Drew A. Torigian - Philadelphia PA, US
You Hao - Philadelphia PA, US
Changjian Sun - Philadelphia PA, US
Joseph M. McDonough - Ambler PA, US
Patrick J. Cahill - Merion Station PA, US

International Classification:

A61B 5/00
G06T 7/11
G06T 7/174
G06T 7/00
G06T 7/20
G06V 10/22
G06T 7/62
G06T 17/00

Abstract:

A method of analyzing thoracic insufficiency syndrome (TIS) in a subject by performing quantitative dynamic magnetic resonance imaging (QdMRI) analysis. The QdMRI analysis includes performing four-dimensional (4D) image construction of a TIS subject's thoracic cavity. The 4D image includes a sequence of two dimensional (2D) images of the TIS subject's thoracic cavity over a respiratory cycle of the TIS subject. The QdMRI analysis also includes segmenting a region of interest (ROI) within the 4D image, determining TIS measurements within the ROI, comparing the TIS measurements to normal measurements determined from ROIs in 4D images of the thoracic cavities of normal subjects that are not afflicted by TIS, and outputting quantitative markers indicating deviation of the thoracic cavity of the TIS subject relative to the thoracic cavities of the normal subjects.

US Patent:

20210251581, Aug 19, 2021

Filed:

Feb 13, 2021

Appl. No.:

17/175655

Inventors:

- Philadelphia PA, US
Aliasghar Mortazi - Philadelphia PA, US
Yubing Tong - Springfield PA, US
Drew A. Torigian - Philadelphia PA, US
Dewey Odhner - Horsham PA, US

International Classification:

A61B 6/03
A61B 6/00

Abstract:

Methods and systems are described for processing images. An example method may comprise receiving a plurality of images based on positron emission tomography, determining, based on the plurality of images, a plurality of calibration parameters indicative of standardized intensity values for corresponding percentiles of intensity values, determining at least one image associated with a patient. The method may comprise applying, based on the plurality of calibration parameters, a transformation to the at least one image associated with the patient. The method may comprise providing the transformed at least one image. A model may be determined based on a plurality of transformed images. The model may be used to determine an estimated disease burden of an anatomic region.

US Patent:

20190259159, Aug 22, 2019

Filed:

Feb 11, 2019

Appl. No.:

16/271949

Inventors:

- Philadelphia PA, US
Tiange Liu - Qinhuangdao, CN
Drew A. Torigian - Philadelphia PA, US
Dewey Odhner - Horsham PA, US
Yubing Tong - Norwood PA, US

International Classification:

G06T 7/11
G06T 7/00
G06T 7/187
G06K 9/32
G06F 16/51
G16H 30/40
A61B 5/00
A61B 6/00
A61B 34/10
A61B 5/055
A61B 6/03

Abstract:

Quantification of body composition plays an important role in many clinical and research applications. Radiologic imaging techniques such as Dual-energy X-ray absorptiometry, magnetic resonance imaging (MRI), and computed tomography (CT) imaging make accurate quantification of the body composition possible. This disclosure presents an automated, efficient, accurate, and practical body composition quantification method for low dose CT images; method for quantification of disease from images; and methods for implementing virtual landmarks.

US Patent:

20170091574, Mar 30, 2017

Filed:

May 14, 2015

Appl. No.:

15/311675

Inventors:

- Philadelphai PA, US
Dewey ODHNER - Horsham PA, US
Drew A. TORIGIAN - Philadelphia PA, US
Yubing TONG - Norwood PA, US

International Classification:

G06K 9/46
A61N 5/10
G06T 7/00
G06T 7/136
G06T 7/70
G06T 7/11

Abstract:

A computerized method of providing automatic anatomy recognition (AAR) includes gathering image data from patient image sets, formulating precise definitions of each body region and organ and delineating them following the definitions, building hierarchical fuzzy anatomy models of organs for each body region, recognizing and locating organs in given images by employing the hierarchical models, and delineating the organs following the hierarchy. The method may be applied, for example, to body regions including the thorax, abdomen and neck regions to identify organs.

US Patent:

20160284071, Sep 29, 2016

Filed:

Mar 25, 2016

Appl. No.:

15/080871

Inventors:

- Philadelphia PA, US
Dewey Odhner - Horsham PA, US
Yubing Tong - Norwood PA, US
Drew A. Torigian - Philadelphia PA, US

International Classification:

G06T 5/00
G06T 7/00
G06T 5/50

Abstract:

Interactive non-uniformity correction (NC) and interactive intensity standardization (IS) require sample tissue regions to be specified for several different types of tissues. Interactive NC estimates the degree of non-uniformity at each voxel in a given image, builds a global function for non-uniformity correction, and then corrects the image to improve quality. Interactive IS includes two steps: a calibration step and a transformation step. In the first step, tissue intensity signatures of each tissue from a few subjects are utilized to set up key landmarks in a standardized intensity space. In the second step, a piecewise linear intensity mapping function is built between the same tissue signatures derived from the given image and those in the standardized intensity space to transform the intensity of the given image into standardized intensity. Interactive IS for MR images combined with interactive NC can substantially improve numeric characterization of tissues.