DEVELOPMENT OF SPACE-INVARIANT SIGNATURE ALGORITHM (SISA) - AN INNOVATIVE APPROACH FOR PROCESSING THE MEDICAL IMAGES FOR THE DETECTION AND LOCALIZATION OF EARLY ABNORMALITIES IN BIOLOGICAL TISSUES

Early detection, diagnosis and localization are some of the important issues facing the medical profession for diseases such as cancer and cardiac disorders. Therefore, it is vital that a reliable approach, which is economic, safer and less time consuming be developed for the detection and diagnosis of such disorders. In this thesis an innovative approach, Space-Invariant Signature Algorithm (SISA) is proposed and developed to process the medical images for the detection and localization of abnormalities at an early stage in active biological tissues such as cancer, potential tumor growth and damaged tissues. In this proposed SISA approach, if the SISA signature pattern is space-invariant it suggests the absence of any abnormality. A space-variant SISA signature pattern is an indication of the presence of the abnormality. The abnormality in an active system can be defined as the obstacle, which impedes the smooth flow of activities such as blood or electrical signals. In any active system under excitation, abnormalities create extra perturbations, depending on the stage of progression of the abnormality. An abnormality in the final stage or critical stage will create very high perturbations that would largely impede the smooth flow of the excitation, whereas, in early stages, the abnormality will create low perturbations and would slightly impede the smooth flow of the excitation provided to the active system. Using the SISA approach, in the absence of any abnormalities, the signature pattern should have a uniform signature pattern, whereas, in the presences of abnormalities, the SISA signature pattern will be space-variant. The degree and position of the variance in space helps in the detection and localization of the abnormality. The SISA approach was first tested on a liquid vibrating system with various types of obstacles. These abnormalities created perturbations in the system parameters that induced the vibration patterns. Furthermore, the experimental results using the SISA approach were also obtained on ultrasound images to find abnormalities in animal tissues. In each of these cases of ultrasound imaging, the SISA signature patterns were able to localize and detect the tissue abnormality. The experimental results obtained with various types of small and large impedances (obstacles), which represent respectively the early and critical stages of abnormalities in the vibrating liquid system, were very encouraging. This basic SISA study on the liquid vibrating system was extended for processing ultrasound images for the detection and localization of damaged biological tissues. These initial experiments on animal tissues using ultrasound images along with SISA processing indicate that this innovative SISA approach has a great potential for processing other types of medical images such as ultrasound, Magnetic Resonance Elastography (MRE) and Computed Tomography (CT scan) for the detection and localization of abnormalities at an incipient stage.

Name thesis:degree_name

Master of Science (M.Sc.)

Level thesis:degree_level

Masters

Discipline thesis:degree_discipline

Biomedical Engineering

Grantor

University of Saskatchewan

Year dc:date.issued

2016

Author dc:creator

• Parolia, Kushagra 1991-

Advisors dc:contributor.advisor

• Gupta, Madan M
• Babyn, Paul
• Zhang, Chris

Committee members dc:contributor.committeemember

• Gupta, Madan M
• Babyn, Paul
• Zhang, Chris
• Chapman, L Dean
• Mehr, Aryan Saadat
• Bui, Francis

• SISA
• space-invariant signature algorithm
• abnormality
• impedance
• obstacle
• signature pattern
• liquid vibrating system
• ultrasound
• early detection

Handle dc:identifier.uri

https://hdl.handle.net/10388/7343

OAI identifier oai:identifier

oai:harvest.usask.ca:10388/7343