Prostate cancer recognition in ultrasound images

Our purpose is to aid medical doctors in prostate cancer detection via computer automated analysis of prostatic ultrasound imagery. Absorption of ultrasound signals is different in cancerous areas than in non-cancerous areas. The energy of the signal, the continuity of the signal, the autocorrelation function and frequency domain properties of prostatic ultrasound images are different in normal tissue than in cancerous tissue; This thesis presents an algorithm for automated cancer recognition in prostatic ultrasound imagery. Statistical and morphological based models are employed to classify regions of ultrasound imagery as either cancerous or non-cancerous. Application of our algorithm onto a limited set of cancerous and non-cancerous ultrasound images shows that our method has the ability to recognize cancer in cancerous ultrasound images. Misclassification occurs when cancerous tissue is classified as non-cancerous and noncancerous tissue is classified as cancerous. Occurrences of misclassification have been observed and investigated. (Abstract shortened by UMI.).

Name thesis:degree_name

Master of Science (MS)

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Computer Science

Grantor dc:publisher

University of Nevada, Las Vegas

Year

2002

Author dc:creator

• Lazarakis, Theodores Dimitrios

Contributors dc:contributor

• Evangelos A. Yfantis

Statement dc:rights

• IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/

Language dc:language

English

Identifier

https://oasis.library.unlv.edu/rtds/1456

OAI identifier oai:identifier

oai:oasis.library.unlv.edu:rtds-2455