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Prof. Tohru Kamiya
Kyushu Institute of Technology, Japan
Tohru Kamiya received his B.A. degree in Electrical Engineering from Kyushu Institute of Technology in 1994, the Masters and Ph.D. degree from Kyushu Institute of Technology in 1996 and 2001, respectively. He is a professor in the Department of Mechanical and Control Engineering at Kyushu Institute of Technology. His research interests are focused on image processing, medical application of image analysis. He is currently working on computer aided diagnosis based on CT, MR imaging, fluorescence microscope imaging, and automatic classification of respiratory sound.
Speech Title: "A Computer Aided Diagnosis for Medical Imaging"
Abstract: In the medical image processing fields, to assist the radiologists some related works such as segmentation, registration and classification techniques are reported to develop the CAD system. For reducing the load to radiologist and improving of detection accuracy, a CAD (Computer Aided Diagnosis) system is expected from medical fields. In this talk, I will introduce why CAD is required in medical field and some related technical issues. Especially, non-rigid image registration techniques from the thoracic MD CT images with some experimental results are shown.Also, we developed a CAD system to support the diagnosis of respiratory sounds.I will show some deep learning techniques to classified abnormal sound from respiratory sounds.
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Prof. Mohd Shafry bin Mohd Rahim
Universiti Teknologi Malaysia, Malaysia
Professor Dr. Mohd Shafry Mohd Rahim currently holds the position of Deputy Vice-Chancellor (Academic & International) at the Universiti Teknologi Malaysia (UTM) in Skudai, Johor, Malaysia. Currently serving as a Professor of Image Processing at the Faculty of Computing at UTM, Malaysia, Professor Mohd Shafry Mohd Rahim also holds the position of Research Fellow for Media and Game Innovation of Excellence (MaGICX) at the Institute of Human-Centred Engineering (iHuMeN), UTM. His leadership extends to spearheading Medical Image Processing and Application Research Initiatives, showcasing his dedication to advancing research and fostering innovation. Motivated by a passion for groundbreaking inventions, Professor Shafry focuses on processing diverse image types for emerging applications, aligning with the ongoing technological revolution in Medical Applications aimed at enhancing lives. His extensive research interests span image enhancement, feature extraction, segmentation, recognition, detection, and classification, reflecting his multifaceted expertise in the field. Additionally, he has a profound understanding of deep learning, computer graphics, computer vision, and digital media. Recognizing the importance of collaboration between academia and industry, Professor Shafry has successfully secured research funding from various sources, including the University, the Malaysian Government, Industries, and international programs such as HORIZON 2020 ¨C EU Research and Innovation Programme.
Speech Title: "Artificial Intelligence (AI) and Generative Artificial Intelligence (GAI) in Medical Image Processing"
Abstract: Artificial Intelligence (AI) plays a pivotal role in contemporary research and technological advancements, particularly in the fields of health and medicine. These applications have significantly contributed to innovative developments that align with the achievement of Sustainable Development Goals (SDGs) for improving lives. The integration of technology and AI has not only fostered progress but has also proven instrumental in addressing complex challenges and meeting human needs. One notable application of AI, specifically Generative AI, has demonstrated remarkable efficacy within Medical Image Processing. This technology enhances recognition and classification activities across various health and image analysis applications. Its impact on refining the precision of computer vision systems is particularly noteworthy, providing valuable insights that contribute to more informed decision-making in the diagnostic process. This keynote presentation aims to share insights from research endeavours that leverage AI in Medical Image Processing and Health Applications. The primary focus will be on enhancing the methodology used in image processing to facilitate Generative AI in making accurate decisions. Practical examples showcasing the application of Generative AI in Medical Image Processing will be explored, offering attendees a deeper understanding of the advancements in utilizing AI for tasks related to medical imaging. The presentation not only highlights achievements but also provides valuable perspectives on the challenges encountered and potential avenues for future research. As the synergy between AI and medical image-related technologies continues to evolve, this keynote serves as a platform for knowledge exchange and aims to inspire further innovation in the realm of Generative AI and its applications in Medical Image Processing.
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