Medical Image Analysis
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Follow on Instagram for UpdatesMedical Image Analysis Syllabus — Unit-wise Content
The official GTU curriculum for Medical Image Analysis (subject code ME02031021) as prescribed for BE · Semester 2 divides the course into 5 units, covering 57 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.
Download the official syllabus PDF (ME02031021)Unit 1 Introduction to Medical Imaging & Image Processing
- Medical Imaging: Fundamental concept and physics of various Imaging Modalities – X-Ray
- Computed Tomography
- Magnetic Resonance Imaging
- Ultrasound Imaging
- Positron Emission Tomography
- Single Photon Emission Computed Tomography
- Thermal Imaging
- Nuclear Medicine Imaging Image Processing: Types of Medical Images
- Types of Image format and Color model
- Sampling and Quantization in Image
- Histogram of Image and Histogram Processing
- Various Image Enhancement techniques
- Image Pre-processing/processing using various filters
- Morphological operations Difficulties in Image Acquisition and Analysis
- Objectives of Biomedical Image Analysis
Unit 2 Detection of Region of Interest
- Thresholding and Binarization
- Detection of Isolated Points and Lines
- Edge detection
- Segmentation and region growing
- Detection of Objects of known geometry
- Methods for improving contour of estimation of region of interest Application/Case Studies: Detection of Spinal Canal
- Detection of Breast boundary from mammogram
- Fuzzy set based region growing for detection of breast cancer
Unit 3 Analysis of Shape, Textures and Oriented Patterns
- Shape: Representation of Shapes and Contours
- Shape Factors
- Fourier Descriptors
- Fractional Concavity
- Analysis of Spicularity Texture: Texture in Biomedical Images
- Models for the Generation of Texture
- Statistical Analysis of Texture
- Law’s of Measures of Texture Energy
- Fractal Analysis
- Fourier domain Analysis of Texture
- Segmentation and Structural Analysis of Texture Pattern: Oriented Patterns in Images
- Measures of Directional Distribution
- Directional Filtering
- Gabor Filtering
- Directional Analysis via Multiscale Edge Detection
- Hough Radon Transform Analysis Application/Case Studies: Shape analysis of Calcifications
- Shape analysis of Breast Masses/Tumuors
- Analysis of Breast Masses Using fghfhffhfh Program Name: Master of Engineering Level: PG Branch: Biomedical Engineering Subject Code : ME02031021 Subject Name : Medical Image Analysis Texture and Gradient Measures
- Analysis of Ligament Healing
- Detection of Breast Tumours using pattern
Unit 4 Pattern Classification and Diagnostic Decision
- Supervised and Unsupervised pattern Classification
- Probabilistic Models and Statistical Decision
- Logistic Regression
- Neural Networks and Training and Test steps
- Measures of Diagnostic Accuracy Application/Case Studies: Image Enhancement for Breast Cancer Screening
- Classification of Breast Masses and Tumors via Shape Analysis
- Content based Retrieval and Analysis of Breast Masses
Unit 5 Advanced Techniques in Medical Image Analysis
- Deep learning in medical image analysis: Basics of Convolutional Neural Networks (CNNs)
- U-Net architecture for image segmentation
- Pre-trained models: VGG, ResNet, and Transfer learning
- Ethical concerns and challenges in AI-driven diagnosis Image Fusion: Image fusion concept
- Need of Image Fusion
- Types of Image Fusion methods
- Application of Image Fusion in medical imaging and classification Virtual reality (VR) and augmented reality (AR) in medical imaging
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