International Teaching | MEDICAL IMAGE PROCESSING AND VISUALIZATION
International Teaching MEDICAL IMAGE PROCESSING AND VISUALIZATION
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cod. IE23200007
MEDICAL IMAGE PROCESSING AND VISUALIZATION
| IE23200007 | |
| DEPARTMENT OF INFORMATION AND ELECTRICAL ENGINEERING AND APPLIED MATHEMATICS | |
| EQF7 | |
| INFORMATION ENGINEERING FOR DIGITAL MEDICINE | |
| 2025/2026 |
| OBBLIGATORIO | |
| YEAR OF COURSE 1 | |
| YEAR OF DIDACTIC SYSTEM 2025 | |
| SPRING SEMESTER |
| SSD | CFU | HOURS | ACTIVITY | |
|---|---|---|---|---|
| ING-INF/05 | 4 | 32 | LESSONS | |
| ING-INF/05 | 1 | 8 | LAB | |
| ING-INF/05 | 1 | 8 | EXERCISES |
| Objectives | |
|---|---|
| THE COURSE PROVIDES THEORETICAL AND TECHNOLOGICAL KNOWLEDGE ABOUT THE MAIN TYPES OF MEDICAL IMAGES AND THE METHODS USED TO PROCESS, ENHANCE, AND EFFECTIVELY DISPLAY THEM FOR DIAGNOSTIC PURPOSES. KNOWLEDGE AND UNDERSTANDING PHASES OF AN IMAGE PROCESSING SYSTEM, WITH PARTICULAR REFERENCE TO LOW LEVEL PROCESSING PHASES (ACQUISITION, FILTERING) AND INTERMEDIATE LEVEL PROCESSING (REGION AND EDGE EXTRACTION), TOGETHER WITH BASIC TECHNIQUES FOR IMPLEMENTING SUCH FUNCTIONS USING EXISTING LIBRARIES AND FRAMEWORKS; CHARACTERISTICS OF IMAGE TYPES USED IN MEDICINE (X-RAY, CT, PET, MRI, AND ULTRASOUND IMAGES) AND THEIR REPRESENTATION; MAIN FRAMEWORKS FOR IMAGE VISUALIZATION. APPLIED KNOWLEDGE AND UNDERSTANDING DESIGN AND DEVELOP APPLICATIONS FOR MEDICAL IMAGE PROCESSING AND VISUALIZATION, INCLUDING THE USE OF SPECIFIC LIBRARIES. |
| Prerequisites | |
|---|---|
| THE COURSE REQUIRES KNOWLEDGE OF A PROGRAMMING LANGUAGE SUCH AS PYTHON. |
| Contents | |
|---|---|
| Didactic Unit 1: DIGITAL MEDICAL IMAGES: ACQUISITION AND STANDARD FORMATS (LECTURE/PRACTICE/LAB HOURS: 12/4/0) - 1 (2 HOURS Lecture): Origin of digital images. Electromagnetic radiation spectrum. Color spaces - 2 (2 HOURS Lecture): Human perception and vision mechanism. Spatial sampling. Sensors - 3 (2 HOURS Lecture): X-ray images - 4 (2 HOURS Practice): Basic operations on digital images - 5 (2 HOURS Lecture): CT: principles and images - 6 (2 HOURS Lecture): MRI: principles and images - 7 (2 HOURS Lecture): Image formats. DICOM - 8 (2 HOURS Practice): Handling DICOM images KNOWLEDGE AND UNDERSTANDING: Concept of digital medical images. Principles behind the most common modalities. Characteristics and organization of the DICOM format APPLIED KNOWLEDGE AND UNDERSTANDING: Manage DICOM files of medical images and retrieve key information. Recognize modality and main features of a medical image. Didactic Unit 2: POINT AND LOCAL OPERATIONS (LECTURE/PRACTICE/LAB HOURS: 8/4/0) - 9 (2 HOURS Lecture): Operations on digital images (point, local, global). Image histograms. Transformations for contrast enhancement - 10 (2 HOURS Lecture): Histogram equalization. Adaptive equalization - 11 (2 HOURS Practice): Implementation and use of contrast enhancement and equalization techniques - 12 (2 HOURS Lecture): 2D filters: features and properties. Noise removal filters. Bilateral filters - 13 (2 HOURS Lecture): Derivative filters. Laplacian. Sharpening - 14 (2 HOURS Practice): Implementation and application of filtering on medical images KNOWLEDGE AND UNDERSTANDING: Features and properties of major point transformation and filtering operations for medical images APPLIED KNOWLEDGE AND UNDERSTANDING: Apply point and local operations to improve the quality of medical images Didactic Unit 3: MATHEMATICAL MORPHOLOGY (LECTURE/PRACTICE/LAB HOURS: 6/2/0) - 15 (2 HOURS Lecture): Basic morphological operations on binary and grayscale images - 16 (2 HOURS Lecture): Top hat transforms. Morphological reconstruction - 17 (2 HOURS Lecture): Watershed transform - 18 (2 HOURS Practice): Application of morphological operations on medical images KNOWLEDGE AND UNDERSTANDING: Features and properties of morphological operations APPLIED KNOWLEDGE AND UNDERSTANDING: Apply morphological operations for analysis and interpretation of medical images Didactic Unit 4: MEDICAL IMAGE VISUALIZATION (LECTURE/PRACTICE/LAB HOURS: 6/6/0) - 19 (2 HOURS Lecture): Grayscale and false color visualization techniques. Visual representation of medical images. Grayscale mapping and pseudocolor encoding. Use of color to highlight diagnostic details - 20 (2 HOURS Practice): Application of colormapping and interactive visualization. Use of software tools for false color visualization and interactive 2D exploration of medical images - 21 (2 HOURS Lecture): Volume rendering: MIP, MinIP, Volume Rendering. 3D visualization techniques: Maximum Intensity Projection, Minimum Intensity Projection, and Volume Rendering. Advantages, limitations, and use cases - 22 (2 HOURS Practice): Generation and analysis of MIP and MinIP projections. Creation and interpretation of volumetric projection images. Analysis of results on CT or MRI datasets - 23 (2 HOURS Lecture): Interactive and multiplanar navigation (MPR). Exploration of medical volumes in axial, sagittal, and coronal sections. Multiplanar visualization and user interfaces in visualization software - 24 (2 HOURS Practice): Multiplanar navigation and visualization (MPR). Use of MPR visualization tools on 3D datasets. Exploration of volumes in orthogonal planes and evaluation of spatial coherence KNOWLEDGE AND UNDERSTANDING: Understand the main 2D and 3D medical image visualization methods. Recognize the value of techniques like colormapping, volume rendering, and multiplanar navigation in diagnostics APPLIED KNOWLEDGE AND UNDERSTANDING: Use software tools to represent medical images in false colors, volumetric visualizations, and multiplanar sections. Interpret various visual representations in relation to the diagnostic content of the images TOTAL LECTURE/PRACTICE/LAB HOURS: 32/16/0 |
| Teaching Methods | |
|---|---|
| THE COURSE INCLUDES THEORETICAL LECTURES AND CLASSROOM PRACTICES. DURING PRACTICES, STUDENTS, INDIVIDUALLY OR IN WORKING GROUPS, ARE ASSIGNED PROJECTS TO DEVELOP USING THE COURSE CONTENT. THESE PROJECTS ARE INTENDED NOT ONLY TO ACQUIRE SKILLS AND COMPETENCIES RELATED TO THE COURSE BUT ALSO TO DEVELOP AND STRENGTHEN TEAMWORK SKILLS. TO TAKE THE FINAL EXAM AND OBTAIN THE CREDITS FOR THIS COURSE, STUDENTS MUST HAVE ATTENDED AT LEAST 70% OF THE TOTAL HOURS OF ASSISTED TEACHING ACTIVITIES. |
| Verification of learning | |
|---|---|
| ACHIEVEMENT OF THE COURSE OBJECTIVES IS CERTIFIED THROUGH A FINAL EXAM GRADED OUT OF THIRTY. THE EXAM INCLUDES A GROUP PROJECT DISCUSSION (GROUPS OF 3–4 STUDENTS) AND AN INDIVIDUAL ORAL INTERVIEW. THE PROJECT DISCUSSION INVOLVES A PRACTICAL DEMONSTRATION OF THE SYSTEM DEVELOPED AND A DEFENSE OF THE DESIGN CHOICES DOCUMENTED IN THE PROJECT REPORT. THE ORAL INTERVIEW AIMS TO VERIFY THE STUDENT’S KNOWLEDGE AND UNDERSTANDING OF THE COURSE TOPICS, AS WELL AS THEIR PRESENTATION SKILLS. |
| Texts | |
|---|---|
| R.C. GONZALEZ, R.E. WOODS, DIGITAL IMAGE PROCESSING, 4TH ED., PEARSON COLLEGE DIV., 2017 A. WEBB, INTRODUCTION TO BIOMEDICAL IMAGING, IEEE PRESS, 2004 TEACHING MATERIAL WILL BE AVAILABLE IN THE DESIGNATED COURSE SECTION OF THE UNIVERSITY'S E-LEARNING PLATFORM (HTTP://ELEARNING.UNISA.IT), ACCESSIBLE TO ENROLLED STUDENTS VIA UNIVERSITY CREDENTIALS |
| More Information | |
|---|---|
| THE COURSE IS TAUGHT IN ENGLISH |
BETA VERSION Data source ESSE3
