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Scheda Riassuntiva
Anno Accademico 2018/2019
Scuola Scuola di Ingegneria Industriale e dell'Informazione
Insegnamento 096281 - BIOMEDICAL SIGNAL PROCESSING AND MEDICAL IMAGES - BIOE 440-421
  • 096280 - BIOMEDICAL SIGNAL PROCESSING AND MEDICAL IMAGES [2] - BIOE 421
Docente Signorini Maria Gabriella
Cfu 5.00 Tipo insegnamento Modulo Di Corso Strutturato

Corso di Studi Codice Piano di Studio preventivamente approvato Da (compreso) A (escluso) Insegnamento
Ing Ind - Inf (1 liv.)(ord. 270) - MI (363) INGEGNERIA BIOMEDICA*AZZZZ096281 - BIOMEDICAL SIGNAL PROCESSING AND MEDICAL IMAGES - BIOE 440-421
Ing Ind - Inf (Mag.)(ord. 270) - BV (478) NUCLEAR ENGINEERING - INGEGNERIA NUCLEARE*AZZZZ096281 - BIOMEDICAL SIGNAL PROCESSING AND MEDICAL IMAGES - BIOE 440-421
Ing Ind - Inf (Mag.)(ord. 270) - MI (471) BIOMEDICAL ENGINEERING - INGEGNERIA BIOMEDICA*AZZZZ055148 - BIOMEDICAL IMAGING - BIOE 421
098655 - MEDICAL IMAGES - BIOE 421
096281 - BIOMEDICAL SIGNAL PROCESSING AND MEDICAL IMAGES - BIOE 440-421
Ing Ind - Inf (Mag.)(ord. 270) - MI (476) ELECTRONICS ENGINEERING - INGEGNERIA ELETTRONICA*AZZZZ096281 - BIOMEDICAL SIGNAL PROCESSING AND MEDICAL IMAGES - BIOE 440-421
Ing Ind - Inf (Mag.)(ord. 270) - MI (481) COMPUTER SCIENCE AND ENGINEERING - INGEGNERIA INFORMATICA*AZZZZ096281 - BIOMEDICAL SIGNAL PROCESSING AND MEDICAL IMAGES - BIOE 440-421
098655 - MEDICAL IMAGES - BIOE 421

Obiettivi dell'insegnamento

Provide basic concepts on biomedical images.

Introduce the related clinical and diagnostic problems and illustrate principles on which techniques for processing and reconstruction are based on.

The Course is constituted by frontal lessons, exercise sessions and laboratory exercises. The attendance of the Course is strongly recommended both at frontal lessons and exercise sessions whose content is also part of the evaluation procedure.


Risultati di apprendimento attesi

Expected Learning Outcomes  During the Course the student will acquire methodological knowledge about Medical Images as well as applications and their main processing tools  Students will  be able to work on medical images with analysis and processing Matlab tools. Moreover they should be able to work autonomously in application problems different from those addressed in the lessons and/or in the practical exercises.

Dublin Descriptors

Expected learning outcomes

Knowledge and understanding

Students will learn how to:

·        To know and use image processing methods in biomedical field

  • Understand how to analyze biomedical images
  • Design and apply feature extraction
  • Identify relationships between analysis parameters and physiological systems behavior

Applying knowledge and understanding

Given specific project cases, students will be able to:

  • Identify the corresponding requirements and hypothesize technical solutions
  • Work autonomously in different practical cases also different from those addressed in the lessons and/or in the laboratory practical exercises
  • Apply the theory to assess the applicability of the chosen methods
  • Develop and test image processing solutions to solve specific application problems

Making judgements

Given a relatively complex problem, students will be able to:

·        Analyze and understand the goals, assumptions and requirements associated with that problem and to model it.

·        Define the methodological solution and evaluate its applicability

  • Identify and define all experimental and applicative steps
  • Estimate the computational effort required and the resources needed for its development, identify risks and define correction actions

Communication

Students will learn to:

  • Write a project specification document
  • Write a document summarizing the project results and make it available for a general audience
  • Communicate their work in front of their colleagues during project labs

Lifelong learning skills

  • Students will learn how to develop an applicative project
  • Students choosing to focus on the research project, will learn how to organize a research activity on some specific aspects of Biomedical  image processing through the development of innovative methodological and technical solutions and experimental data analysis.

 


Argomenti trattati

Part [2] Medical Images

Introduction to Medical Imaging modalities

Introduction to image classification. Image generation: Point Spread Function, Modulation Transfer Function, Spatial and amplitude resolution, Contrast, Signal to Noise ratio. Fourier Transform in the 2D spatial domain. Fotonic images. Human perception and Biomedical Images. Psychophysics Weber's Law. Perception thresholds for human vision.

Basic Principles for image processing and reconstruction. Sampling and quantization in the spatial domain. Discrete Fourier Transform in the 2D space domain. Convolution 2D. Image quality enhancement: spatial filters, equalization. Geometric operators. Artifacts and their removal. Tomographic reconstruction. Numeric approach to tomographic reconstruction: Radon transform, Sinogram, back-projection and blurring. Filtered back-projection. Ramp high pass filter, Central Slice Theorem.

X ray Imaging: Basic radiography, X-ray generation, radiation interaction with matter, dose. X-ray instrumentation. Digital Radiology. Mammography, Angiographic X-Ray imaging. Computed Tomography (CT): applications, history and evolution of instrumentation, spiral CT. Tomographic reconstruction application to CT images.

Nuclear medicine Imaging Radioactivity. Nuclear Emission images. General principles Single Photon Emission Tomography (SPECT). Detectors and data acquisition system. Positron emission Tomography (PET). Spatial resolution. Detectors. Instrumentation. Dual mode PET-CT scanners.

Magnetic Resonance Imaging (MRI): Principles, Instrumentation, Pulse Sequences, T1 and T2 contrast, image generation. FMRI.

Ultrasound Imaging: Principles, echography and doppler, other contrast agents.

Laboratory activities:  Exercises with Matlab implementing image analysis tools. Application to different medical images. Homework exercises with evaluation. Objective of the Lab is teaching how to work on examples of medical image analysis by the most used tools in space and in spatial frequency domain. Students will learn how to preprocess biomedical images, how to extract information which could be of pathophysiological importance. Furthermore, practical activity will introduce students to general criteria to work with medical image analysis even different from those seen in the Lab.

Part [2] Medical Images (short summary)

Introduction to the main imaging diagnostic systems: analysis of the relevant features: spatial resolution, contrast, signal to noise ratio, artifacts. Basic principles for image processing and reconstruction: 2D Fourier transform, sampling and quantization, enhancement techniques (spatial filtering, equalization), geometric operations tomographic reconstruction. Imaging modalities and their characteristics. X ray images: planar radiographs, digital radiology, angiography, transmission tomography (CT). Emission images with radiotracers: scintigraphy and gamma-camera, emission tomography (SPECT and PET). Magnetic resonance imaging (MRI): T1 and T2 contrast, construction of MRI (basic acquisition sequences, frequency and phase encoding), functional MRI (brief remark). Ultrasound (US) imaging: echography, Doppler


Prerequisiti

It is advisable to be aware of the fundamentals of digital signal processing.


Modalità di valutazione

Assessment

The final score of the exam will be based on a written exam consisting of both open-ended questions and exercises covering the image processing part of the Course and on a project developed in the Laboratory part of the Course. The project will be presented to the instructor at the end of the course. Practical assignments to be implemented in Matlab (based on topics covered during the Labs) are not mandatory but constitutes an additional opportunity to increment final score.

The score of the written exam, the project part and the practical assessments will be summed to compute the total score. 30 cum laude will be assigned when the total score is higher than 16.

The written exam will assign up to 12 points and will be considered sufficient when the score will be equal or higher than 7. The project part will assign up to 3 points. The optional Lab assignments (2) will assign up to 2 points. Students can take the written part at any exam session during the year.  No mid-term assessments will be scheduled.

Type of assessment

Description

Dublin descriptor

Written test

·        Solution of numerical problems

·        Exercises focusing on application aspects

·        Theoretical questions on all course topics with open-ended questions

1,2

1, 2, 3, 4, 5

1, 4, 5

Assessment of laboratory practical activity

Evaluation of the scientific quality of the project

Assessment of the computational and experimental work developed by students either individually or in groups

2, 3, 4, 5

Oral presentation

Evaluation of the presentation of the project work activity developed as part of laboratory activities by students either individually or in groups

2, 3, 4, 5   

 


Bibliografia
Risorsa bibliografica obbligatoriaNotes and Other course material in BEEP https://beep.metid.polimi.it/
Note:

Lesson texts can be dowloaded from Beep Platform. Other material is available and some other will be added

Risorsa bibliografica facoltativaWebb A., Introduction to Biomedical Imaging, Editore: IEEE Press - Wiley Interscience, Anno edizione: 2004
Risorsa bibliografica facoltativaValli, G, Coppini G., Bioimmagini, Editore: Patron, Bologna, Anno edizione: 2012
Note:

(terza Edizione)

Risorsa bibliografica facoltativaJ.G. Webster, Medical Instrumentation : Application and Design, Editore: Houghton Mifflin Co, Anno edizione: 2010

Forme didattiche
Tipo Forma Didattica Ore di attività svolte in aula
(hh:mm)
Ore di studio autonome
(hh:mm)
Lezione
30:00
45:00
Esercitazione
10:00
15:00
Laboratorio Informatico
10:00
15:00
Laboratorio Sperimentale
0:00
0:00
Laboratorio Di Progetto
0:00
0:00
Totale 50:00 75:00

Informazioni in lingua inglese a supporto dell'internazionalizzazione
Insegnamento erogato in lingua Inglese
Disponibilità di materiale didattico/slides in lingua inglese
Disponibilità di libri di testo/bibliografia in lingua inglese
Possibilità di sostenere l'esame in lingua inglese
Disponibilità di supporto didattico in lingua inglese
schedaincarico v. 1.6.1 / 1.6.1
Area Servizi ICT
23/10/2019