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Christine B Swisher, 5829 Arch St, Loyalsockville, PA 17754

Christine Swisher Phones & Addresses

29 Arch St, Montoursville, PA 17754   

East Stroudsburg, PA   

25 High St, Somerville, MA 02144    617-6660625   

West Somerville, MA   

Wyoming, PA   

Chambersburg, PA   

Work

Position: Administration/Managerial

Emails

Mentions for Christine B Swisher

Resumes & CV records

Resumes

Christine Swisher Photo 21

Adjunct Professor

Location:
Montoursville, PA
Industry:
Higher Education
Work:
Lycoming College
Adjunct Professor
Penn State University Jan 2016 - May 2016
Adjunct Professor
Susquehanna University Jan 2016 - May 2016
Adjunct Professor
Education:
Penn State University 2004 - 2015
Doctorates, Doctor of Philosophy, Art History, Philosophy
Tufts University 2002 - 2004
Masters, Art History
Hood College
Bachelors, Bachelor of Arts, Visual Communications, Art
Skills:
Higher Education, Tutoring, Lecturing
Christine Swisher Photo 22

Assistant Manager

Work:
Onemain
Assistant Manager
Christine Swisher Photo 23

Christine Leon Swisher

Christine Swisher Photo 24

Christine Swisher

Publications & IP owners

Us Patents

Fat Layer Identification With Ultrasound Imaging

US Patent:
2021032, Oct 21, 2021
Filed:
Aug 30, 2019
Appl. No.:
17/272989
Inventors:
- Eindhoven, NL
Raghavendra SRINIVASA NAIDU - Auburndale MA, US
Christine SWISHER - San Diego CA, US
Hua XIE - Cambridge MA, US
International Classification:
A61B 8/08
A61B 8/14
A61B 8/00
G06N 3/04
Abstract:
The present disclosure describes imaging systems configured to identify features within image frames and improve the frames by implementing image quality adjustments. An ultrasound imaging system can include a transducer configured to acquire echo signals responsive to ultrasound pulses transmitted toward a target. The system can also include a user interface configured to display an image and one or more processors configured to identify one or more features within the image. The processors can cause the interface to display elements associated with at least two image quality operations specific to the identified feature. A first image quality operation can include a manual adjustment of a transducer setting, and a second image quality operation can include an automatic adjustment of the identified feature derived from reference frames including the identified feature. The processors can receive a user selection of one or more elements and apply the operations to modify the image.

Fast And Personalized Recommender System For Radiation Therapy Planning Enhancement Via Closed Loop Physician Feedback

US Patent:
2021002, Jan 28, 2021
Filed:
Mar 14, 2019
Appl. No.:
17/040119
Inventors:
- EINDHOVEN, NL
Kevin LYONS - CAMBRIDGE MA, US
Gajendra Jung KATUWAL - SOMERVILLE MA, US
Christine Menking SWISHER - SAN DIEGO CA, US
Assignee:
KONINKLIJKE PHILIPS N.V. - EINDHOVEN
International Classification:
G16H 20/40
G16H 40/20
G16H 50/70
A61N 5/10
Abstract:
A non-transitory computer-readable medium stores a preferences database (); instructions readable and executable by at least one electronic processor () to perform a proposed radiation treatment plan review process (), including: via a reviewing graphical user interface (GUI) (), presenting a proposed radiation treatment plan to a reviewer; via the reviewing GUI, receiving one of (i) an acceptance of the proposed radiation treatment plan or (ii) a rejection of the proposed radiation treatment plan in combination with annotations of the rejected proposed radiation treatment plan from the reviewer; and updating radiation treatment plan preferences of the reviewer stored in the preferences database based on the acceptance of the proposed radiation treatment plan or based on the annotations of the rejected proposed radiation treatment plan; and instructions readable and executable by at least one electronic processor () to perform a radiation treatment planning process () including: optimizing radiation treatment parameters for a patient with respect to dose objectives and using at least one planning image of a patient to generate one or more candidate radiation treatment plans for the patient; retrieving, from the preferences database to a planning GUI (), radiation treatment plan preferences of a reviewer associated with the patient; and displaying the radiation treatment plan preferences of the reviewer associated with the patient at the planning GUI.

Guided-Transcranial Ultrasound Imaging Using Neural Networks And Associated Devices, Systems, And Methods

US Patent:
2020035, Nov 12, 2020
Filed:
Jan 23, 2019
Appl. No.:
16/963553
Inventors:
- ElNDHOVEN, NL
JONATHAN THOMAS SUTTON - BOSTON MA, US
CHRISTINE SWISHER - SAN DIEGO CA, US
HAIBO WANG - MELROSE MA, US
International Classification:
A61B 8/08
A61B 8/06
A61B 8/00
Abstract:
Ultrasound image devices, systems, and methods are provided. A medical ultrasound imaging system, comprising an interface in communication with an ultrasound imaging component and configured to receive a first image representative of blood vessels of a brain of a patient while the ultrasound imaging component is positioned at a first imaging position with respect to the patient; and a processing component in communication with the interface and configured to apply a convolutional network (CNN) to the first image to produce a motion control configuration for repositioning the ultrasound imaging component from the first imaging position to a second imaging position associated with a transcranial examination, the CNN trained based on at least a known blood vessel topography.

Intelligent Ultrasound System For Detecting Image Artefacts

US Patent:
2020029, Sep 24, 2020
Filed:
Oct 29, 2018
Appl. No.:
16/760962
Inventors:
- EINDHOVEN, NL
MAN NGUYEN - MELROSE MA, US
CHRISTINE MENKING SWISHER - SAN DIEGO CA, US
International Classification:
A61B 8/00
A61B 8/08
G06N 3/02
Abstract:
The present disclosure describes ultrasound imaging systems and methods configured to identify and remove image artefacts from ultrasound image frames by applying a neural network to the frames. Systems may include an ultrasound transducer configured to acquire echo signals responsive to ultrasound pulses transmitted toward a target region. One or more processors communicatively coupled with the ultrasound transducer may be configured to generate an image frame from the ultrasound echoes and apply a neural network to the image frame. The neural network determines whether an artefact is present in the image frame, and identifies the type of artefact detected. The processors can also generate an indicator conveying the presence of the artefact, which can be displayed on a user interface. The processors can further generate an instruction for adjusting the ultrasound transducer based on the presence and type of artefact present within the image frame.

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