Preserving Clarity: Enhancing Image and Signal Quality for Computer-Aided Diagnosis and Treatment in Biomedical Engineering
December 1st, 2023 (GMT+3)
Department of Biomedical Engineering, Faculty of Engineering and Architecture, Eskişehir Osmangazi University
Omer Burak Istanbullu is an Assistant Professor and department vice chair of Biomedical Engineering Department at Eskisehir Osmangazi University. After studying in the field of biomedical engineering and specializing on tumor segmentation from magnetic resonance images at Erciyes University, he then pursued a Master's program at Istanbul Technical University and Erciyes University with the scope of biomaterial-medical imaging device compatibility. Following the Master's degree, he received a Ph.D. from Erciyes University, in the field of biocompatibility improvement of implantable intravascular biomaterials using biomimetic surface modification approaches. Dr. Istanbullu is experienced in the development and improvement of biocompatible materials using biomimetic approaches, combining the computational methods and experimental analysis to achieve the most effective solutions for the challenges related to biomaterials. His research interests include surface modification by biomimetic approaches, diamond-like carbon and carbon nanotubes, electrochemical, thermal and mechanical characterization of biomaterials, anticorrosive and biocompatible surface development. The overall goal of Dr. Istanbullu through his work is contributing to the development of new and innovative biomaterials that have the potential to reduce the biomaterial-based risks in the field of biomedical engineering.
Biomedical engineering has revolutionized computer-aided diagnosis and treatment, enabling accurate and efficient clinical decision-making processes. However, the reliability of these systems depends on the quality of medical images and signals used for analysis. Nevertheless, various factors such as biomaterial-based deterioration, noise, artifacts, and limitations in imaging devices can compromise the clarity of these critical data. Preserving and enhancing the quality of medical images and signals have become imperative to ensure accurate diagnoses and effective treatment planning. Addressing these challenges requires innovative approaches and advanced techniques in image and signal processing, machine learning, and multi-modality imaging. The workshop on "Preserving Clarity: Enhancing Image and Signal Quality for Computer-Aided Diagnosis and Treatment in Biomedical Engineering" serves as a platform for researchers and experts to explore the latest advancements, share insights, and collaborate to overcome the limitations associated with image and signal quality degradation in computer-aided diagnosis and treatment.
The workshop aims to address the critical problem of preserving and enhancing image and signal quality in computer-aided diagnosis and treatment. Recent advances in image and signal processing, machine learning, multi-modality imaging, and medical image-dependent radiotherapy have shown promising potential for overcoming the challenges in this field. By bringing together researchers, practitioners, and experts from diverse disciplines, this workshop aims to foster discussions and collaborations to explore innovative approaches and advanced techniques for mitigating image and signal quality degradation in computer-aided diagnosis and treatment. Participants will have the opportunity to share their research findings and explore solutions to improve the clarity of medical images and signals. The workshop also aims to identify the gaps in existing methodologies and explore avenues for future research in this field. This collaborative effort is aimed to contribute to the development of robust and reliable computer-aided diagnostic systems that can significantly impact clinical decision-making and patient care, and treatment outcomes. Participants can expect to engage in discussions, gain insights into the latest research advancements, and establish connections with experts in the field. By encouraging collaboration and joint efforts, the workshop aims to pave the path towards improved image and signal quality in computer-aided diagnosis, thereby driving advancements in healthcare practices.
Scope and Information for Participants:
The workshop invites researchers, academicians, practitioners, and professionals in the fields of biomedical engineering, medical imaging, computer vision, and signal processing. The scope of this workshop encompasses various themes, including image and signal processing algorithms for noise reduction and artifact removal, techniques for resolution enhancement and contrast improvement, deep learning and machine learning methods for image and signal restoration, as well as optimization of acquisition protocols. We encourage participants to contribute their expertise in addressing the challenges of preserving clarity in computer-aided diagnosis and treatment. The workshop will provide a collaborative environment for exchanging ideas, sharing research insights, and fostering interdisciplinary collaborations to advance the field.
Büyükdere Meşelik Yerleşkesi, 26040 Odunpazarı/Eskişehir, Turkey
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