Medical Image Science

Musculoskeletal Imaging Using Photon-Counting Computed Tomography

CMIV Research School

CMIV offers a doctoral program with both medical and technological entries and coherent research education. A basic principle for the program is a close connection between different disciplines i.e medicine, health, technology, and natural sciences.

Bayesian fMRI tumour

In this CENIIT project, Bayesian methods for fMRI informed brain tumour treatment planning, the goal is to improve treatment of brain tumours, by including images of brain activity in Elektas software for tumour treatment planning.

Biomedical Image Science

We develop methods & techniques for depicting anatomy & function in the human body & its organs. From imaging techniques, through methods of analysis and quantification of image information, to validation of new methods and image-based biomarkers

EPSONiP

EPSONIP explores the link between fatty liver, epicardial fat and cardiovascular disease in type 2 diabetes.

Bigpicture

The 6-year, €70 million project called BIGPICTURE, will herald a new era in pathology and take AI development in pathology to the next level: we will develop the world’s biggest repository for sharing of pathology data.

Simulation of Cardiac Blood Flow from CT

Advanced CT creates amazing visualization of the beating heart. However, the complex interactions of blood flow are not fully reflected by these images. This project aims to extract blood flow data from CT images using image-based simulations.

Carotid plaque assessment

This project develops novel methods for better risk assessment of carotid plaque by focusing on plaque composition and blood flow parameters rather than level of vessel constriction.

Experiencing the Self through Touch

Through functional magnetic resonance imaging (fMRI) this project gathers information about the boundaries between the self and others and compares the outcome of the reactions of neurotypical volunteers with participants with a psychiatric disorder

Seeing Organ Function

Seeing organ function (SOF) is a visionary project with ambitious goals. By starting with a medical problem we work interdisciplinary, linking medical research and clinical use with novel technique.

Nucleic Acids Technologies Lab

The Nucleic Acids Technologies Lab explores the use of nucleic acids as biorecognition molecules to develop highly specific and sensitive systems, with various detection modalities.

Imaging for Stereotactic Neurosurgery

This project works with MRI protocols for stereotactic neurosurgery and has developed a tool based on laser Doppler technique which can be used with the DBS probe to give more data on the surrounding tissue.

AIDA

Analytic Imaging Diagnostics Arena (AIDA) is a national arena for research and innovation on analytic image-based diagnostics.

Non-alcoholic fatty liver disease

Our research purposes are to further characterize the natural history of NAFLD, identify factors that influence the progression and to develop and validate diagnostic methods for NAFLD.

Mitral Valve Surgery

Mitral valve regurgitation is the most common indication for mitral valve surgery. A repair of the valve results in a more beneficial outcome than a replacement with a prosthesis.

MRI-based Body Composition Analysis

Metabolic risk related to body-fat accumulation is strongly dependent on fat distribution. This project has developed a method for quantitative assessment of body composition that measures both fat distribution and muscle volume.

Effects of rTMS on alcohol use

Craving alcohol and an impaired ability to stop drinking despite adverse consequences are key features of alcohol addiction. This project aims to find a noninvasive brain stimulation method that can be used as treatment for addiction.

PRECIIS

PRECIIS aims towards significantly better outcomes and patient safety at a significantly lower cost, through ground-breaking improvement of precision in orthopedic surgery.

Diagnosis and rehabilitation for Whiplash Associated Disorders

Endocrine tumors

Molecular genetic analysis of endocrine tumors (thyroid, parathyroid, adrenal, neuroendocrine): pathogenesis and development of metastases.

Methods in Neuroimaging Genetics

In this VR project, the goal is to combine brain images and genetic data to better understand brain diseases.

Unique Resource for AI Research in Medical Imaging

One of the world's most powerful systems for artificial intelligence (AI) computation has landed at Linköping University. The system will serve as a national resource for projects within AIDA.

An AI computer lab using medical images from SCAPIS

Scientists plan to use the same technology as that used to create deepfake videos to build AI-generated medical images. The synthesised images will present data from the big SCAPIS study, and will be used for research into AI solutions in healthcare.

Creating a new generation of contrast agents

Peter Eriksson has defended a thesis at LiU showing that integrating gadolinium into the crystal structure of cerium oxide creates a contrast agent that is less harmful to the body and also gives better contrast in magnetic resonance imaging, MRI.

17.8 million Swedish crowns to Kajsa Uvdal

Kajsa Uvdal has been awarded SEK 17.8 million from the Swedish Research Council for an interdisciplinary research environment combining physics, medicine and image sciences. The objective is to obtain improved treatments for heart disease and cancer.

Magnetic resonance finds fatty liver

Taking tissue samples to diagnose fatty liver can be replaced in most cases by a painless magnetic resonance investigation, according to a new study.

Softwares for fMRI yield erroneous results

Common statistical methods used to analyse brain activity through images taken with MRI scanners cannot be trusted, as shown by Anders Eklund and Hans Knutsson of Linköping University, in the highly-ranked journal PNAS.

Better images of the heart - less radiation

The Center for Medical Image Science and Visualization (CMIV) in Linköping is upgrading its equipment and ensuring its place as a world leader in its field.