KENNETH L URISH
Medical Practice in Swatara, PA

License number
Pennsylvania MT193229
Category
Medicine
Type
Graduate Medical Trainee
Address
Address
Swatara, PA 17033

Personal information

See more information about KENNETH L URISH at radaris.com
Name
Address
Phone
Kenneth Urish, age 46
19 Green Brier, Allison Park, PA 15101
(215) 946-4256
Kenneth Urish
96 N Main St, Washington, PA 15301
(724) 493-3364
Kenneth L. Urish
Wexford, PA
(724) 935-5261
Kenneth L Urish
3 Gateway, Pgh, PA 15222
(412) 471-5500
(412) 391-1994
Kenneth L Urish
96 Main Wash, Washington, PA 15301
(724) 228-7900

Professional information

See more information about KENNETH L URISH at trustoria.com
Kenneth Urish Photo 1
Dr. Kenneth Urish, Boston MA - MD (Doctor of Medicine)

Dr. Kenneth Urish, Boston MA - MD (Doctor of Medicine)

Specialties:
Orthopedic Surgery
Address:
55 Fruit St, Boston 02114
30 Hope Dr SUITE 2400, Hershey 17033
(717) 531-5638 (Phone), (717) 531-0983 (Fax)
500 University Dr, Hershey 17033
(717) 531-8521 (Phone), (717) 531-0498 (Fax)
PENN STATE MILTON S HERSHEY MEDICAL CENTER
500 University Dr, Hershey 17033
(800) 243-1455 (Phone), (717) 531-0276 (Fax)
Languages:
English
Hospitals:
55 Fruit St, Boston 02114
500 University Dr, Hershey 17033
30 Hope Dr SUITE 2400, Hershey 17033
PENN STATE MILTON S HERSHEY MEDICAL CENTER
500 University Dr, Hershey 17033
Milton S. Hershey Medical Center
500 University Dr, Hershey 17033
Education:
Medical School
Univ Of Pittsburgh Sch Of Med
Graduated: 2009


Kenneth Urish Photo 2
Method For Detecting Arthritis And Cartilage Damage Using Magnetic Resonance Sequences

Method For Detecting Arthritis And Cartilage Damage Using Magnetic Resonance Sequences

US Patent:
2013013, May 30, 2013
Filed:
Nov 30, 2012
Appl. No.:
13/691359
Inventors:
Kenneth L. Urish - Hershey PA, US
Matthew G. Keffalas - Woburn MA, US
Timothy J. Mosher - Elizabethtown PA, US
David J. Miller - State College PA, US
International Classification:
A61B 5/055
US Classification:
600410
Abstract:
In this work, a Magnetic Resonance Imaging (MRI)-based automatic classifier was designed to predict changes due to osteoarthritis (OA) years prior to their symptomatic presentation and radiographic detection. For each patient, multiple image texture features were measured from the T2 map of the patella cartilage and the lateral and medial compartments of the femoral condyle. A support vector machine (SVM)-based linear discriminant function was trained to predict health status, as well as the affected knee compartment. Feature selection was integrated into the classifier training to drastically reduce the number of image (biomarker) features without sacrificing classification accuracy. It was found that a dominant knee compartment determined the classification decision for most patients. We demonstrate that the signal texture index (STI) predicts disease progression prior to symptoms or radiographic signs of OA. In symptomatic individuals, the STI correlates with the pain and severity of OA suggesting it is a sensitive measure of the same on T2 Maps. These observed changes localized to one knee compartment demonstrating the method can localize OA to specific regions.