DocumentCode :
3775894
Title :
Tutorial I: Medical image analysis
Author :
Sarah Barman
Author_Institution :
Kingston University, UK
fYear :
2015
Abstract :
The opportunities to use imaging to assist clinicians with diagnosis and assessment of the effectiveness of treatment plans have increased rapidly over the last few decades due to developments in imaging technologies and computer processing power. Many different medical image modalities exist such as Ultrasound, Magnetic Resonance Imaging (MRI), Computed Tomography (CT), etc. Development of computer vision algorithms have allowed researchers to refine medical image analysis techniques to assist clinicians in many aspects of patient medical care and research into causes of different conditions. Examples include diverse applications that range from diagnosis of lung nodules in MRI images, to recognition of the first signs of diabetic retinopathy in screening programmes that examine retinal fundus images. The computer vision techniques employed to achieve effective medical image analysis applications, encompass many areas of research and range from machine learning approaches to morphological techniques.
Publisher :
ieee
Conference_Titel :
Pattern Recognition (ACPR), 2015 3rd IAPR Asian Conference on
Electronic_ISBN :
2327-0985
Type :
conf
DOI :
10.1109/ACPR.2015.7486452
Filename :
7486452
Link To Document :
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