Date: Wednesday, 30 November 2022 (1 day)
Early bird registration: 16 November 2022
Registration Deadline: 23 November 2022
Venue: Multimedia University, Cyberjaya, Selangor.
Target Audience: Undergraduate and postgraduate students, researchers, technicians, engineers and pathologists.
Objective: To provide an introductory course to digital pathology and medical image analysis.
Part I – Introduction to Pathology
Part II – Digital Pathology
Part III – Computer-Aided Detection and Diagnosis
Part IV – Challenges and Opportunities in Digital Pathology
Speaker: Ir. Prof. Dr. Mohammad Faizal bin Ahmad Fauzi, Professor, Faculty of Engineering, Multimedia University, Malaysia
Registration link: https://forms.gle/
Overview: Pathology is a branch of medical science primarily concerning the examination of organs, tissues, and bodily fluids in order to make a diagnosis of disease, especially cancers. While imaging tests, such as X-rays, CT and MRI are helpful in detecting masses or areas of abnormality, they alone cannot differentiate cancerous cells from non-cancerous cells. For most types of cancer, pathology remains the ‘gold standard’ for the diagnosis of cancer. Digital pathology is the management and interpretation of pathology information in a digital environment that enables better, faster and cheaper diagnosis, prognosis and prediction of cancer and other important diseases. With the advent of whole slide imaging, the field of digital pathology has gained great attention and is currently regarded as one of the most promising avenues of diagnostic medicine.
The current approach in manual diagnosis is very tedious, as well as susceptible to sampling bias, subjective interpretation, and human errors. Incorporating machine learning and artificial intelligence in the process will reduce the pathologists’ workload significantly, at the same time elevating the standard of healthcare. In this course we will introduce the fundamental knowledge of clinical pathology such as slide preparation, different staining, analogue pathological workflow, and cancer diagnosis. Then we move on to digital pathology where we will discuss the digital slide system and digital workflow, followed by computer-aided detection and diagnosis in digital pathology. Finally, we will discuss the challenges and opportunities in applying artificial intelligence/machine learning into digital pathology.
For more information, click on the title of the course at https://www.mmu.edu.my/foe/
Please do not hesitate to contact us if you have any enquiries or would like to register for any of the short courses. Do not miss this opportunity!