Biomedical Signal & Image Processing
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Follow on Instagram for UpdatesBiomedical Signal & Image Processing Syllabus — Unit-wise Content
The official GTU curriculum for Biomedical Signal & Image Processing (subject code ME01031061) as prescribed for BE · Semester 1 divides the course into 6 units, covering 37 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 (ME01031061)Unit 1 Fundamentals of Digital Signal Processing
- Objectives of Biomedical Signal Analysis
- Difficulties Encountered in Biomedical Signal Acquisition & Analysis Filtering Techniques for Biomedical Signals: Random noise
- Structured Noise
- Design of IIR & FIR filter
- Optimal Filter
- Adaptive Filter
- Signal averaging
- spectral analysis
- multi resolution analysis
- Wavelet Transform: 1-D Continuous Wavelet Transform
- 1- D Discrete Wavelet Transform
- Application of Wavelet Transform in Biomedical Signal Processing
Unit 2 EEG
- Signal of the Brain
- Effect of CNS Diseases on EEG, Processing & Feature Extraction of EEG EMG: Signal of Muscles
- Processing & Feature Extraction Of EMG
- Speech Signal: Processing and Feature extraction of Speech
Unit 3 ECG
- Signal of Heart
- Effect of Cardiovascular Diseases on ECG, Processing & Feature Extraction of ECG, PCG: Sound of Heart
- Processing & Feature Extraction of PCG
Unit 4 Fundamentals of Digital Image Processing
- Image Acquisition
- Image transforms- 2D- DFT, DCT, 2-D Discrete Wavelet Transform
- Image Enhancement Techniques in Spatial & Frequency Domain
- Morphological Image Processing
Unit 5 IMAGE SEGMENTATION AND FEATURE EXTRACTION
- Intensity-based segmentation
- Edge-based segmentation
- Region- based segmentation
- Linear & Circular Hough Transform
- Simple Program Name: Engineering Level: PG Branch: Bio Medical Engineering Course / Subject Code : ME01031061 Course /Subject Name : Biomedical Signal & Image Processing active contour models-snake algorithm
- k means clustering
- Feature Extraction- Types of Image Feature
- Gabor filters method
- GLCM method Image Classification: SVM, PCA, ICA, LDA Methods
Unit 6 APPLICATIONS OF MEDICAL IMAGE ANALYSIS
- CT Image Analysis
- MRI Image Analysis
- Angiographic image analysis
- Retinal image analysis
- Fusion of PET-CT Images
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