CS Other Presentations

Department of Computer Science - University of Cyprus

Besides Colloquiums, the Department of Computer Science at the University of Cyprus also holds Other Presentations (Research Seminars, PhD Defenses, Short Term Courses, Demonstrations, etc.). These presentations are given by scientists who aim to present preliminary results of their research work and/or other technical material. Other Presentations serve as a forum for educating Computer Science students and related announcements are disseminated to the Department of Computer Science (i.e., the csall list):

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Presentations Coordinator: Demetris Zeinalipour

PhD Defense: AM-FM Medical Image Analysis, Kyriacos Constantinou (University of Cyprus, Cyprus), Tuesday, December 13, 2022, 11:00-12:00 EET.

The Department of Computer Science at the University of Cyprus cordially invites you to the PhD Defense entitled:

AM-FM Medical Image Analysis

Abstract:
Amplitude Modulation - Frequency Modulation (AM-FM) models provide effective representations through physically meaningful descriptors of complex non-stationary structures that can differentiate between the different lesions and normal structure. The overall objective of this research work is to in-troduce new, more powerful, more robust and more discriminatory AM-FM models and methods, and to apply them in medical image analysis. More specifically the research contributions made during the course of this dissertation work are the following. A sparse multiscale AM-FM representation accompa-nied by robust feature extraction was developed which is based on families of Gabor filterbanks. The use of multiple families of Gabor filters leads to significantly better representations than using just one filterbank. The methodology includes decompositions and reconstructions based on scalable quality, multiscale and directional representations. Special emphasis was placed on the stability of the recon-structions. Furthermore, a new model of ultrasound image analysis of atherosclerotic carotid plaque to assess risk of stroke in asymptomatic patients was developed based on multiscale AM-FM analysis. A new methodology of sparse multiscale AM-FM analysis was developed using Gabor filterbanks. AM-FM component selection criteria and parametrization were introduced to derive discriminatory AM-FM fea-tures in predicting asymptomatic vs symptomatic plaque images. The new methodology achieved better results than texture analysis features. In addition, the combination of AM-FM features sets with clinical features proved to be helpful in increasing prediction accuracy. The proposed methodologies provide a new paradigm of AM-FM analysis that opens new horizons in the analysis of medical images towards differentiating between normal and abnormal tissue.

Short Bio:
Kyriacos Constantinou is a Ph.D. candidate at the Department of Computer Science under the supervision of Prof. Constantinos Pattichis. He is a member of eHealth lab of the Department of Computer Science and the Biomedical Engineering Research Centre of the University of Cyprus. His research interests include image processing and especially medical image analysis. He holds a Master's degree in Computer Science from the University of Cyprus and a Bachelor’s degree from the Hellenic Army Academy, Greece.

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