BCS Data Management specialist group
12:30 - Welcome, with update on DMSG events
12:32 - Introduction: webinar topic and speaker
12:35 - Presentation
13:15 - Q&A
13:32 - Closing remarks
In the medical field, it's crucial to provide an early diagnosis for dangerous diseases such as breast cancer in order to increase treatment success. The symptoms of breast cancer are different and the diagnosis process includes mammography, physical exam and biopsy. In biopsy, a tissue part is surgically taken away to be analysed. This tissue part can indicate cancerous cells and provide which type of cancer these cells linked to. Biopsy imaging data are large and has a complex structure. This makes it very hard for pathologists to deal with the huge workload associated with histopathological cancer diagnosis.
Recently, Deep Learning (DL) techniques have been considered to tackle problems of medical image diagnosis. One of the associated issues is that the size of Biopsy images make it hard for hardware systems to process them. Patch-based DL methods are proposed where the input image is divided into small patches. These patches are used for feature extraction in some models and used for final image classification by applying majority voting for class labels of all patches.
In this webinar, the challenges encountered in histopathological cancer diagnosis will be introduced. Next, different solutions utilised in the research will be presented and how this research will be beneficial for industry and the NHS.
About the speaker
Zakaria Senousy is currently pursuing a PhD in Computing (Artificial Intelligence) at Birmingham City University. Specifically he is conducting research in medical Image processing using deep learning techniques. Zac’s focus is in dealing with various medical imaging cases and finding different intelligent methods to boost the automated diagnosis accuracy and to introduce an initial stage of explainability for complex cases.
Zakaria holds a BSc and MSc in Computer Engineering. Prior to his PhD Study, Zakaria has worked as Assistant Lecturer in Computer Engineering for seven years. During his time in academia, he gained experience preparing and delivering different modules in Computer Science and Engineering as well as assessing students based on different examinations and module projects. His areas of expertise include computer vision, machine learning, high performance computing, operating systems, microprocessor systems, database systems.
This event is brought to you by: BCS Data Management specialist group