Introduction to Medical Image Processing
Learn all about the basics of Medical Image Processing in this 3 months course.
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Syllabus
This course is full of best-in-class content by leading faculty and industry experts in the form of videos and projects
Course Overview
- This course deals with the core domain of Image processing applied to the healthcare/medical community.
- It mainly involves processing and analytical techniques applied to images obtained from a multitude of modalities in the broad spectrum of healthcare.
Course Syllabus
On a daily basis we talk to companies in the likes of Tata Elxsi and Mahindra to fine tune our curriculum.
Module 1 - Introduction to Digital Image Processing
- Image Processing Fundamentals
- What is a Digital Image?
- Classification of Imaging Systems
- Interaction of Steps in Image Processing
- Components of Image Processing System
- Image Sensing
- Creation of 2D Image
- Creation of 3D Image
- Digital Image Acquisition
- Image Sampling and Quantization
- Image Quality Metrics
- Noise In Image
- Digital Imaging and Communications in Medicine (DICOM)
- DICOM File Format
- Slicer Software Introduction
- Reading and Visualizing DICOM Files
Module 2 - Medical Image Formats
- What is a Medical Image?
- Components of Medical Image
- Digital Imaging and Communications in Medicine
- DICOM Elements and Objects
- Neuroimaging Informatics Technology Initiative
- NIfTI components
- Simple ITK - DICOM Data Handling
- NiBabel - NIfTI Data Handling
- Slicer 3D Visualization
- Supplementary Slides
Module 3 - Mathematics for Image Processing
- Relationship Between Pixels
- Mathematical Tools
- Image Transforms
- Intensity Transformation
- Histogram Processing
- Spatial Filtering
- Non-Linear Filters
- Frequency Domain Filtering
Module 4 - Image Pre-processing
- What is a Digital Image?
- Gray Scale and Colour Image
- Histogram of an Image
- Histogram Sliding
- Histogram Stretching
- Histogram Equalization
- Image Enhancement
- Image Thresholding
- Adaptive Thresholding
- Otsu’s Thresholding
- What are Morphological Operations?
- Mathematical Morphology
- Erosion
- Dilation
- Image Opening and Image Closing
- Morphological Gradient
- Morphological Algorithms
- Boundary Extraction
Module 5 - Image De-noising
- Image De-Noising Fundamentals
- What is Noise?
- Noise in Medical Imaging
- Noise Models
- Different Types of Noise
- Gaussian Noise
- Impulse Noise - Salt and Pepper Noise
- Poisson Noise
- Speckle Noise
- Noise Distributions in Different Modalities
- Image Denoising
- Image Denoising Techniques
- Linear Filters and Non-linear Filters
- Gaussian Filter
- Mean Filter
- Bilateral Filter
- Non-local Means
Module 6 - Image Texture Extraction and Applications
- What is Texture?
- Texture Analysis
- Texture Classification
- Texture Segmentation
- Texture Synthesis
- Texture Shape
- Challenges in Texture Analysis
- Statistical Methods-Based Approach
- Gray Level Co-occurrence
- Numeric Features of GLCM
- Fourier Approach for Texture Descriptor Concept
- Autocorrelation Function
- Gabor Filter
- Gabor Filter Bank
- Classification Phase
- K-Nearest Neighbor (KNN)
- Image Classification Metrics
- Image Texture Analysis
- Region Based Texture Segmentation
- Texture Edge Detection
Our courses have been designed by industry experts to help students achieve their dream careers
Industry Projects
Our projects are designed by experts in the industry to reflect industry standards. By working through our projects, Learners will gain a practical understanding of what they will take on at a larger-scale in the industry. In total, there are 1 Projects that are available in this program.
Internal investigation of the medical images to recognize the features present
The purpose of this project is to explore some simple image enhancement algorithms. It introduces spatial and frequency domain filters, which involve learners applying conceptual knowledge and an algorithm, processing the image and seeing the results.
Our courses have been designed by industry experts to help students achieve their dream careers
Ratings & Reviews by Learners
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Instructors profiles
Our courses are designed by leading academicians and experienced industry professionals.
1 industry expert
Our instructors are industry experts along with a passion to teach.
20 years in the experience range
Instructors with 20 years extensive industry experience.
Areas of expertise
- Machine Learning
- Medical Image Processing
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