General introduction to mammography and the main diseases related to the breasts. How mammography is performed and relevant adjustments. 

The aim of the course is to introduce students to mammography and the main examinations. The importance of image quality and to recognize the main image defects as well as how to correct them. How to adapt examinations to each individual.

Emphasis on the symptoms of breast cancer, professionalism and the importance of communication. General concepts and terminology of radiology will be discussed.

• Positron-emitting substances, production, and imaging.
• Radiation detectors, radiation dose, and radiation protection for staff and patients.
• Discussion on positron-emitting substances and their production.
• Work methods and radiation protection.
• Radiopharmaceutical production, cleanroom environments, and quality control.
• Imaging with positron-emitting substances (PET-CT and SPECT-CT).
• Disease diagnosis using F-18 and other positron-emitting substances.
• Radiation and radioactivity measurements, measurement techniques, and methods.
• Assessment of radiation dose and radiation protection for patients and staff in the use of radioactive substances.

This course aims to equip students with knowledge and skills in project and quality management. Students will explore strategies for improvement, quality issues in medical imaging, and the impact of management factors on quality and success. The course will also cover different management styles, change management, general principles of human resource management, and the importance of teamwork.

This course is an introduction to statistics in the life sciences. The course covers the following topics. Types of data: categorical data, count data, data on continuous variables. Descriptive statistics; numerical statistics and statistical graphs. Probability distributions, the binomial distribution, the Poisson distribution and the normal distribution. The definitions of a random sample and of a population. Sampling distributions. Confidence intervals and hypothesis testing. Comparison of means between groups. Statistical tests for frequency tables. Linear and logistic regression with ROC analysis. Survival analysis with the methods of Kaplan-Meier and Cox. The course is based on lectures and practical sessions in computer labs. In the practical sessions exercises are solved with the statistical software package R and the RStudio environment.

The course (2 ECTS) is especially aimed at students who have completed at least three years of undergraduate studies in clinical disciplines within the field of health sciences. It is a prerequisite for the clinical course Interdisciplinary clinical cooperation: The HealthSquare (2 ECTS) (health care service for university students). The course is based on the theories of interprofessional education and various teaching strategies will be used in order to encourage active participation of students. Students will work together in interdisciplinary groups. The course is mainly focused on interdisciplinary theories, professionalism, interdisciplinary cooperation, team work and ethical decisions in health care.

Assessment (pass / fail) is based on  project work, activity in project work and exams that take place in electronic form in the teaching cycle. 

Teaching arrangements:
Students are divided into interdisciplinary study groups at the beginning of the semester that plan and execute their own meeting times and hand in their final assignments before the end of October. 

This course is taught as four independent modules, that the student should choose from based on their prior education and training and to best meet everyone´s educational goals. Successful completion of each module is awarded with 2 ECTS credits. M.Sc. student should at minimum choose three (6 ECTS) and Ph.D. students should at a minimum choose two modules (4 ECTS), and one of the modules chosen needs to be either module number 2 or 3.  The student is responsible to notify the course administrator about how many credits they intend to take and what modules before registration ends. Each module contains 3-4 lectures and a project.The modules are:

1. Article reading and data presentation
   1. How to read a paper and present your data
   2. Reference search and management (computer lab session)
   3. The scientific method
   4. ASSIGNMENT - Mini conference. Students will present their research project or paper (7 min)

2. Introduction to the scientific method

   1. Research ethics
   2. The philosophy of science
   3. Dishonesty in Science
   4. Quantitative & Qualitative Methods
   5. ASSIGNMENT – online project

3. Grant application, data collection and quality management
   1. Data handling and safety
   2. Permission applications/Research animals
   3. Quality management
   4. Grant applications
   5. ASSIGNMENT – preparation of grant application

4. Graduate student’s toolbox. This module is taught with the Center for graduate studies at their location in Setberg. This module is targeted towards graduate students (M.Sc./Ph.D.). The objective of the module is teaching graduate students transferable skills that can be applied to both academic research and research-oriented jobs
   1. Time Management
   2. Managing the Graduate Student - Advisor relationship
   3. Academic English
   4. Academic CV workshop
   5. ASSIGNMENT – Students write an academic CV in English.

This course is taught as four independent modules, that the student should choose from based on their prior education and training and to best meet everyone´s educational goals. Successful completion of each module is awarded with 2 ECTS credits. M.Sc. student should at minimum choose three (6 ECTS) and Ph.D. students should at a minimum choose two modules (4 ECTS), and one of the modules chosen needs to be either module number 2 or 3.  The student is responsible to notify the course administrator about how many credits they intend to take and what modules before registration ends. Each module contains 3-4 lectures and a project. A pass for each module is granted for 75% attendance (or watching lecture online) and the timely return of an assignment. The modules are:

1. Article reading and data presentation
   1. How to read a paper and present your data
   2. Reference search and management (computer lab session)
   3. The scientific method
   4. ASSIGNMENT - Mini conference. Students will present their research project or paper (7 min)

2. Introduction to the scientific method

   1. Research ethics
   2. The philosophy of science
   3. Dishonesty in Science
   4. Quantitative & Qualitative Methods
   5. ASSIGNMENT – online project

3. Grant application, data collection and quality management
   1. Data handling and safety
   2. Permission applications/Research animals
   3. Quality management
   4. Grant applications
   5. ASSIGNMENT – preparation of grant application

4. Graduate student’s toolbox. This module is taught with the Center for graduate studies at their location in Setberg. This module is targeted towards graduate students (M.Sc./Ph.D.). The objective of the module is teaching graduate students transferable skills that can be applied to both academic research and research-oriented jobs
   1. Time Management
   2. Managing the Graduate Student - Advisor relationship
   3. Academic English
   4. Academic CV workshop
   5. ASSIGNMENT – Students write an academic CV in English.

This course is taught as four independent modules, that the student should choose from based on their prior education and training and to best meet everyone´s educational goals. Successful completion of each module is awarded with 2 ECTS credits. M.Sc. student should at minimum choose three (6 ECTS) and Ph.D. students should at a minimum choose two modules (4 ECTS), and one of the modules chosen needs to be either module number 2 or 3.  The student is responsible to notify the course administrator about how many credits they intend to take and what modules before registration ends. Each module contains 3-4 lectures and a project. A pass for each module is granted for 75% attendance (or watching lecture online) and the timely return of an assignment. The modules are:

1. Article reading and data presentation
   1. How to read a paper and present your data
   2. Reference search and management (computer lab session)
   3. The scientific method
   4. ASSIGNMENT - Mini conference. Students will present their research project or paper (7 min)

2. Introduction to the scientific method

   1. Research ethics
   2. The philosophy of science
   3. Dishonesty in Science
   4. Quantitative & Qualitative Methods
   5. ASSIGNMENT – online project

3. Grant application, data collection and quality management
   1. Data handling and safety
   2. Permission applications/Research animals
   3. Quality management
   4. Grant applications
   5. ASSIGNMENT – preparation of grant application

4. Graduate student’s toolbox. This module is taught with the Center for graduate studies at their location in Setberg. This module is targeted towards graduate students (M.Sc./Ph.D.). The objective of the module is teaching graduate students transferable skills that can be applied to both academic research and research-oriented jobs
   1. Time Management
   2. Managing the Graduate Student - Advisor relationship
   3. Academic English
   4. Academic CV workshop
   5. ASSIGNMENT – Students write an academic CV in English.

Biology of malignant diseases. Cancer symptoms and diagnostic methods. Examinations and staging. Prognostic factors and treatment. Radiation therapy, principles and purposes. Effects of radiation on tissue, side effects. Different forms of treatment. Radiation treatment planning. CT based dose planning. Target definition. The use of different image modalities in radiation treatment planning and delivery. Radiation therapy machines. Radiation biology. Quality control and radiation protection. Patient care programs with respect to both physical and psychological aspects.

The course provides insight and a deeper understanding of vascular studies and the technology used in them. Students will learn the fundamental methodologies that are applicable in clinical practice.

The course provides students with insight into information technology and the latest technological advancements in medical imaging, with a focus on image interpretation and the use of artificial intelligence in the analysis of medical images. Students will gain an understanding of data management and PACS or imaging storage systems, and how artificial intelligence can enhance both efficiency and accuracy in data processing.

The course provides students with an understanding of bone density measurements using DXA technology. Students will learn to perform, analyze, and interpret DXA scans with an emphasis on quality, safety, and accuracy.

The course covers the fundamentals of DXA technology, including bone density measurements, X-ray physics, and dual-energy absorptiometry.

Anatomy and physiology of bones: The effects of age, gender, and diseases on bone mass.
Conducting examinations: Proper patient positioning, image quality, and common measurement errors.
Image analysis and interpretation: Understanding T-score, Z-score, and fracture risk assessment.
Quality management and standards: Review of safety regulations, repeatability criteria, and consistency between different devices.
Radiation protection and safety: Guidelines and safety standards for both patients and staff.

The course provides students with practical training and a deeper understanding of the clinical implementation of specialized imaging examinations, such as MRI, ultrasound, CT scans, isotope studies, PET, angiography, radiotherapy, breast imaging, and more, depending on the imaging modality the student chooses to specialize in. Students will become familiar with the methodology, safety standards, and quality management associated with the relevant imaging techniques. Additionally, they will gain increased experience in the clinical environment.

Students and teachers lecture on and discuss interesting research.

Lectures are given by students and teachers. Conference on Radiography research. Attendance is compulsory and active participation in discussions is required.

OBS.

OBS.

General introduction to mammography and the main diseases related to the breasts. How mammography is performed and relevant adjustments. 

The aim of the course is to introduce students to mammography and the main examinations. The importance of image quality and to recognize the main image defects as well as how to correct them. How to adapt examinations to each individual.

Emphasis on the symptoms of breast cancer, professionalism and the importance of communication. General concepts and terminology of radiology will be discussed.

• Positron-emitting substances, production, and imaging.
• Radiation detectors, radiation dose, and radiation protection for staff and patients.
• Discussion on positron-emitting substances and their production.
• Work methods and radiation protection.
• Radiopharmaceutical production, cleanroom environments, and quality control.
• Imaging with positron-emitting substances (PET-CT and SPECT-CT).
• Disease diagnosis using F-18 and other positron-emitting substances.
• Radiation and radioactivity measurements, measurement techniques, and methods.
• Assessment of radiation dose and radiation protection for patients and staff in the use of radioactive substances.

This course aims to equip students with knowledge and skills in project and quality management. Students will explore strategies for improvement, quality issues in medical imaging, and the impact of management factors on quality and success. The course will also cover different management styles, change management, general principles of human resource management, and the importance of teamwork.

This course is an introduction to statistics in the life sciences. The course covers the following topics. Types of data: categorical data, count data, data on continuous variables. Descriptive statistics; numerical statistics and statistical graphs. Probability distributions, the binomial distribution, the Poisson distribution and the normal distribution. The definitions of a random sample and of a population. Sampling distributions. Confidence intervals and hypothesis testing. Comparison of means between groups. Statistical tests for frequency tables. Linear and logistic regression with ROC analysis. Survival analysis with the methods of Kaplan-Meier and Cox. The course is based on lectures and practical sessions in computer labs. In the practical sessions exercises are solved with the statistical software package R and the RStudio environment.

The course (2 ECTS) is especially aimed at students who have completed at least three years of undergraduate studies in clinical disciplines within the field of health sciences. It is a prerequisite for the clinical course Interdisciplinary clinical cooperation: The HealthSquare (2 ECTS) (health care service for university students). The course is based on the theories of interprofessional education and various teaching strategies will be used in order to encourage active participation of students. Students will work together in interdisciplinary groups. The course is mainly focused on interdisciplinary theories, professionalism, interdisciplinary cooperation, team work and ethical decisions in health care.

Assessment (pass / fail) is based on  project work, activity in project work and exams that take place in electronic form in the teaching cycle. 

Teaching arrangements:
Students are divided into interdisciplinary study groups at the beginning of the semester that plan and execute their own meeting times and hand in their final assignments before the end of October. 

This course is taught as four independent modules, that the student should choose from based on their prior education and training and to best meet everyone´s educational goals. Successful completion of each module is awarded with 2 ECTS credits. M.Sc. student should at minimum choose three (6 ECTS) and Ph.D. students should at a minimum choose two modules (4 ECTS), and one of the modules chosen needs to be either module number 2 or 3.  The student is responsible to notify the course administrator about how many credits they intend to take and what modules before registration ends. Each module contains 3-4 lectures and a project.The modules are:

1. Article reading and data presentation
   1. How to read a paper and present your data
   2. Reference search and management (computer lab session)
   3. The scientific method
   4. ASSIGNMENT - Mini conference. Students will present their research project or paper (7 min)

2. Introduction to the scientific method

   1. Research ethics
   2. The philosophy of science
   3. Dishonesty in Science
   4. Quantitative & Qualitative Methods
   5. ASSIGNMENT – online project

3. Grant application, data collection and quality management
   1. Data handling and safety
   2. Permission applications/Research animals
   3. Quality management
   4. Grant applications
   5. ASSIGNMENT – preparation of grant application

4. Graduate student’s toolbox. This module is taught with the Center for graduate studies at their location in Setberg. This module is targeted towards graduate students (M.Sc./Ph.D.). The objective of the module is teaching graduate students transferable skills that can be applied to both academic research and research-oriented jobs
   1. Time Management
   2. Managing the Graduate Student - Advisor relationship
   3. Academic English
   4. Academic CV workshop
   5. ASSIGNMENT – Students write an academic CV in English.

This course is taught as four independent modules, that the student should choose from based on their prior education and training and to best meet everyone´s educational goals. Successful completion of each module is awarded with 2 ECTS credits. M.Sc. student should at minimum choose three (6 ECTS) and Ph.D. students should at a minimum choose two modules (4 ECTS), and one of the modules chosen needs to be either module number 2 or 3.  The student is responsible to notify the course administrator about how many credits they intend to take and what modules before registration ends. Each module contains 3-4 lectures and a project. A pass for each module is granted for 75% attendance (or watching lecture online) and the timely return of an assignment. The modules are:

1. Article reading and data presentation
   1. How to read a paper and present your data
   2. Reference search and management (computer lab session)
   3. The scientific method
   4. ASSIGNMENT - Mini conference. Students will present their research project or paper (7 min)

2. Introduction to the scientific method

   1. Research ethics
   2. The philosophy of science
   3. Dishonesty in Science
   4. Quantitative & Qualitative Methods
   5. ASSIGNMENT – online project

3. Grant application, data collection and quality management
   1. Data handling and safety
   2. Permission applications/Research animals
   3. Quality management
   4. Grant applications
   5. ASSIGNMENT – preparation of grant application

4. Graduate student’s toolbox. This module is taught with the Center for graduate studies at their location in Setberg. This module is targeted towards graduate students (M.Sc./Ph.D.). The objective of the module is teaching graduate students transferable skills that can be applied to both academic research and research-oriented jobs
   1. Time Management
   2. Managing the Graduate Student - Advisor relationship
   3. Academic English
   4. Academic CV workshop
   5. ASSIGNMENT – Students write an academic CV in English.

This course is taught as four independent modules, that the student should choose from based on their prior education and training and to best meet everyone´s educational goals. Successful completion of each module is awarded with 2 ECTS credits. M.Sc. student should at minimum choose three (6 ECTS) and Ph.D. students should at a minimum choose two modules (4 ECTS), and one of the modules chosen needs to be either module number 2 or 3.  The student is responsible to notify the course administrator about how many credits they intend to take and what modules before registration ends. Each module contains 3-4 lectures and a project. A pass for each module is granted for 75% attendance (or watching lecture online) and the timely return of an assignment. The modules are:

1. Article reading and data presentation
   1. How to read a paper and present your data
   2. Reference search and management (computer lab session)
   3. The scientific method
   4. ASSIGNMENT - Mini conference. Students will present their research project or paper (7 min)

2. Introduction to the scientific method

   1. Research ethics
   2. The philosophy of science
   3. Dishonesty in Science
   4. Quantitative & Qualitative Methods
   5. ASSIGNMENT – online project

3. Grant application, data collection and quality management
   1. Data handling and safety
   2. Permission applications/Research animals
   3. Quality management
   4. Grant applications
   5. ASSIGNMENT – preparation of grant application

4. Graduate student’s toolbox. This module is taught with the Center for graduate studies at their location in Setberg. This module is targeted towards graduate students (M.Sc./Ph.D.). The objective of the module is teaching graduate students transferable skills that can be applied to both academic research and research-oriented jobs
   1. Time Management
   2. Managing the Graduate Student - Advisor relationship
   3. Academic English
   4. Academic CV workshop
   5. ASSIGNMENT – Students write an academic CV in English.

Biology of malignant diseases. Cancer symptoms and diagnostic methods. Examinations and staging. Prognostic factors and treatment. Radiation therapy, principles and purposes. Effects of radiation on tissue, side effects. Different forms of treatment. Radiation treatment planning. CT based dose planning. Target definition. The use of different image modalities in radiation treatment planning and delivery. Radiation therapy machines. Radiation biology. Quality control and radiation protection. Patient care programs with respect to both physical and psychological aspects.

The course provides insight and a deeper understanding of vascular studies and the technology used in them. Students will learn the fundamental methodologies that are applicable in clinical practice.

The course provides students with insight into information technology and the latest technological advancements in medical imaging, with a focus on image interpretation and the use of artificial intelligence in the analysis of medical images. Students will gain an understanding of data management and PACS or imaging storage systems, and how artificial intelligence can enhance both efficiency and accuracy in data processing.

The course provides students with an understanding of bone density measurements using DXA technology. Students will learn to perform, analyze, and interpret DXA scans with an emphasis on quality, safety, and accuracy.

The course covers the fundamentals of DXA technology, including bone density measurements, X-ray physics, and dual-energy absorptiometry.

Anatomy and physiology of bones: The effects of age, gender, and diseases on bone mass.
Conducting examinations: Proper patient positioning, image quality, and common measurement errors.
Image analysis and interpretation: Understanding T-score, Z-score, and fracture risk assessment.
Quality management and standards: Review of safety regulations, repeatability criteria, and consistency between different devices.
Radiation protection and safety: Guidelines and safety standards for both patients and staff.

The course provides students with practical training and a deeper understanding of the clinical implementation of specialized imaging examinations, such as MRI, ultrasound, CT scans, isotope studies, PET, angiography, radiotherapy, breast imaging, and more, depending on the imaging modality the student chooses to specialize in. Students will become familiar with the methodology, safety standards, and quality management associated with the relevant imaging techniques. Additionally, they will gain increased experience in the clinical environment.

Students and teachers lecture on and discuss interesting research.

Lectures are given by students and teachers. Conference on Radiography research. Attendance is compulsory and active participation in discussions is required.

OBS.

OBS.