DR. MOHAMED E SALAMA, MD
Medical Practice at Medical Dr, Salt Lake City, UT

License number
Utah 6284873-1205
Category
Medical Practice
Type
Anatomic Pathology & Clinical Pathology
Address
Address
50 N Medical Dr, Salt Lake City, UT 84132
Phone
(801) 581-2507

Personal information

See more information about MOHAMED E SALAMA at radaris.com
Name
Address
Phone
Mohamed E Salama, age 54
6538 Bouchelle Cv, Salt Lake City, UT 84121
(801) 943-0915

Professional information

Mohamed E Salama Photo 1

Dr. Mohamed E Salama - MD (Doctor of Medicine)

Hospitals:
ARUP Laboratories
500 Chipeta Way, Salt Lake City 84108
University of Utah Health Care
50 North Medical Dr, Salt Lake City 84132
ARUP Laboratories
500 Chipeta Way, Salt Lake City 84108
University of Utah Health Care
50 North Medical Dr, Salt Lake City 84132
Education:
Medical Schools
University Of Cairo, Faculty Of Medicine
Graduated: 1994


Mohamed Salama Photo 2

Associate Professor At University Of Utah

Position:
Associate Professor at University of Utah
Location:
Salt Lake City, Utah
Industry:
Higher Education
Work:
University of Utah - Greater Salt Lake City Area since Jun 2006 - Associate Professor
Education:
Cairo University 1987 - 1994
MD, Medicine


Mohamed E Salama Photo 3

Mohamed E Salama, Salt Lake City UT

Specialties:
Pathology, Anatomic Pathology & Clinical Pathology, Hematology
Work:
Uumc Pathology Dept
50 N Medical Dr, Salt Lake City, UT 84132
Education:
University Of Cairo (1994)


Mohamed Salama Photo 4

Methods And Systems For Segmentation Of Cells For An Automated Differential Counting System

US Patent:
2013009, Apr 18, 2013
Filed:
Oct 12, 2012
Appl. No.:
13/650387
Inventors:
Tolga Tasdizen - Salt Lake City UT, US
Nisha Ramesh - Salt Lake City UT, US
Mohamed Salama - Salt Lake City UT, US
International Classification:
G06K 9/34
US Classification:
382134
Abstract:
A method of identifying individual cells in an image of a cytological preparation. The method includes the steps of obtaining an image of a cytological preparation including a plurality of cells; identifying a first region of the image, the first region having a region boundary encompassing at least one lobe, wherein the first region includes at least one cell; detecting at least one circle within the first region, where the at least one circle substantially covers the at least one lobe of the first region; and if the first region has more than one circle, splitting the region into at least two subregions.