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Artificial intelligence systems using medical image analysis

12 November 2019 – 10:00
Laboratorio Magistrale 5° Piano
Dipartimento di Informatica
Relatrice: Fatcma Taher (Zayed University, Dubai)
Responsabile: Prof. Ernesto Damiani

Abstract

The seminar offers an introduction to the application of Artificial Intelligence in Medical image Analysis and outlines some relevant challenges that the research community is today facing.

In particular, the presented research will focus on:

  • CAD System for Early Detection of Lung Cancer based on Sputum Color Image Analysis
  • Early Detection of Lung Injury using 4D-CT Chest Images
  • A non-invasive CAD System for Early Detection of Acute Renal Rejection
  • A non-invasive DW-MRI based Diagnostic System for Early Diagnosis of Prostate Cancer
  • Big Data in Autism
  • Cerebrovascular Segmentation from MRA Images

Biography

Dr. Fatma Taher is an associate professor and an assistant dean for Research and Outreach in the College of Technological Innovation and the CEO of Happiness and Wellbeing at Zayed University, Dubai, UAE. Her research interests are in the areas of signal and image processing, pattern recognition, artificial intelligent, medical image analysis, especially in detecting of the cancerous cells, kidney transplant, autism and Cerebrovascular Segmentation from MRA Images. In addition to that, remote sensing and satellite images researches. She received her PhD from Khalifa University of Science, Technology and Research, UAE, in 2014. So that she is the first UAE local that graduated with PhD in Engineering inside the UAE, and Khalifa University considered as the first University to grant PhD degrees in computer engineering.

Dr. Fatma Taher has published more than 60 papers in international Journals and conferences. She served as a member of the steering, organizing and technical program committees of many international conferences, and has served on many editorial and reviewing boards of international journals and conferences. Dr. Fatma is the chair of IEEE UAE section.

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07 novembre 2019
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