Image techniques for Bio-Medical has become a major
aspect of engineering sciences and radiology in
particular has become a dominant player in the field. Recent development have made it possible to use
biomedical imaging to view the human body from an anatomical or physiological prospective in a
non-invasive fashion.
By the increasing use of direct digital imaging
systems for medical diagnostics, digital image
processing becomes more and more important in health care. In additional to originally digital
methods. Such as Computed Tomography (CT) or Magnetic Resonance Imaging (MRI), initially analogue imaging modalities such as endoscopy or radiography are nowadays equipped with digital sensors. Digital images are composed of individual pixels to which discrete brightness or color values are assigned. They can be efficiently processed, objectively evaluated, and made available at many places at the time by means of appropriate communication networks such as PACS and DICOM protocol. Based on digital
imaging techniques, the entire spectrum of digital image processing is now applicable in medicine.
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Course Objectives
“Imaging Techniques for Practical BioMedical Applications” is two-day hands-on practical course on introduction to medical image
processing techniques in area of auto brightness and contrast techniques. It will be conducted in a workshop-like manner , with a balance mix of theory and hands-on coding and simulation in MATLAB.
Extensive exercises are provided throughout the course to cover every angle of algorithm design and implementation using MATLAB.
Course Methodology
The course begins with an overview of medical
imaging, image modalities, and a review on the basic concepts image processing. The image enhancement and image segmentation are introduced in turn, each offering improvement/enhancement. The derivation of the main algorithms are covered to enable better understanding and to provide insight on the
conceptual ideas behind these algorithms. Application examples are provided at the end of each section to help reconcile theory with actual practice. |
Course highlights
This course is intended as a practical
introduction to image processing techniques for bio medical applications. As such, there will be a series of hands-on exercises which are generally aimed to help translate the theoretical models to practical applications.
Course Agenda
Fundamental of Medical Imaging?
DICOM Format
Image Modalities
• Computed Tomography
• The Formation of CT Image
• CT Number of Brain Soft Tissues
• Digital Imaging and Communication in Medicine
• CT Image Conversion with DICOM
• CT Image Presentation
• Window Setting for Ischaemic Stroke
Detection
• General Measurement of Performance
• Contrast Enhancement
• Mathematical Definitions of Contrast
• Fundamental of Contrast Enhancement
• Contrast Enhancement of Medical Images
• Histogram Equalisation
• Conventional Histogram Equalisation
• Pros and Cons of Conventional Histogram Equalisation |
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Image Quality Measurement
• Mean Square Error
• Peak Signal-to-Noise Ratio
• The Measure of Image Enhancement
Practical and application specific exercises, and case studies
All cases studies will cover the basic practice by medical doctors, spatial based
transformation, contrast and brightness
enhancement, image representation , image quality enhancement.
• Assisted breast tissue abnormality
differentiation using Magnetic Resonance Images
• Brain early infarct detection through CT-Scan
• Image Quality Enhancement for Endoscopic Imaging System
• Automated Spoligotype Recognition for
Mycobacterium tuberculosis Strain Typing
Prerequisites
A basic knowledge of image processing knowledge and some basic MATLAB programing knowledge will have advantage |