Title

Automating the Detection of Atypical Pigment Network Using Texture Segmentation

Presenter Information

Cory Gassner

Department

Electrical and Computer Engineering

Major

Computer Engineering

Research Advisor

Shrestha, Bijaya

Advisor's Department

Electrical and Computer Engineering

Funding Source

Missouri S&T Opportunities for Undergraduate Research Experiences (OURE) Program

Abstract

A software program called CVIPtools is used to calculate texture features in skin lesion images with the goal of finding atypical pigment networks in these images. The atypical pigment network is a critical feature in attempting to diagnose melanoma versus benign nevus from an image. Using CVIPtools is a long and arduous process. New software was developed to automate this laborious process. The software uses a map to segment an image for atypical pigment networks. The segmented image would mark the areas with and without atypical pigment networks. The results of the automated process are identical to CVIPtool’s results when using grayscale images, and only 1-5% different when using a color image as the input.

Biography

Cory Gassner completed his primary and secondary education in Jefferson City, MO. He is currently working on his Bachelor’s degree in Computer. He worked as an Undergraduate Research Assistant with the DERMVIS group of skin cancer research from August 2008 to April 2009.

Research Category

Engineering

Presentation Type

Oral Presentation

Document Type

Presentation

Location

Gasconade Room

Presentation Date

08 Apr 2009, 10:00 am - 10:30 am

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Apr 8th, 10:00 AM Apr 8th, 10:30 AM

Automating the Detection of Atypical Pigment Network Using Texture Segmentation

Gasconade Room

A software program called CVIPtools is used to calculate texture features in skin lesion images with the goal of finding atypical pigment networks in these images. The atypical pigment network is a critical feature in attempting to diagnose melanoma versus benign nevus from an image. Using CVIPtools is a long and arduous process. New software was developed to automate this laborious process. The software uses a map to segment an image for atypical pigment networks. The segmented image would mark the areas with and without atypical pigment networks. The results of the automated process are identical to CVIPtool’s results when using grayscale images, and only 1-5% different when using a color image as the input.