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Image: depiction of lung cancer; Copyright: PantherMedia / decade3d

No benefit for PORT in non-small-cell lung cancer

21/09/2020

Post-operative radiotherapy (PORT) used in patients with non-small-cell lung cancer (NSCLC) following complete resection and after (neo) adjuvant chemotherapy shows no statistically significant difference in 3-year disease-free survival (DFS), according to data presented at ESMO 2020. These results give the oncology community a long-awaited answer.
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Image: Aerial view of the unfinished hospital in the savannah; Copyright: Dagmar Braun

Much-needed medical technology: a hospital for Togo

10/02/2020

If life has given you many blessings, you should share them with others – and you also need to be a little crazy. That's Dagmar Braun's point of view. She initiated the construction of a hospital in Togo, Africa. The country currently lacks the system required to deliver comprehensive medical care. Surgical equipment and gynecology devices are much-needed to compensate for these deficits.
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Image: Robot looks at huge amount of CT images of the brain; Copyright: panthermedia.net/phonlamai

AI in imaging: how machines manage our Big Data

02/09/2019

In modern medicine, especially in the field of imaging, huge amounts of data are produced – so much that radiologists can hardly keep up with diagnosing the images. Artificial Intelligence could be the solution to this problem. But how exactly can it help in this task? How can man and machine work together? And what else will be possible in the future with the support of intelligent systems?
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Image: DLIR image of the aorta; Copyright: GE Healthcare

Deep Learning Image Reconstruction – what AI looks like in clinical routine

02/09/2019

Artificial intelligence is no longer a dream of the future in medicine. Many studies and initial application examples show that it sometimes achieves better results than human physicians. At Jena University Hospital, the work with AI is already lived practice. It is the first institution in the world to use algorithms in radiological routine to reconstruct CT images.
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Image: Robot points with his finger at CT images of the brain, in the background a CT device; Copyright: panthermedia.net/phonlamai

Man vs. machine – the benefits of AI in imaging

02/09/2019

Radiology is a field that produces large volumes of data, which can no longer be managed without the help of intelligent systems. This is especially true when it comes to the interpretation of medical images. While this takes physicians years of training and experience, several hours of work and the highest level of concentration, AI only requires a few seconds to accomplish the same task.
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Bild: Mann liegt auf dem Boden, vor ihm der mobile Roboter mit Tablet; Copyright: Fraunhofer IPA

MobiKa – programmed to help

22/05/2019

Many illnesses or old age require help with everyday tasks. Unfortunately, family members or caregivers aren’t always available to lend a hand. The MobiKa mobile service robot is designed to offer support, deliver motivation and improve the quality of life of those in need.
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Image: Screenshot of the VR app: a small penguin sitting on the treatment table of the MRI device; Copyright: Entertainment Computing Group, Uni DUE & LAVAlabs Moving Images

Gamification: how penguins help children overcome their MRI fear

23/04/2019

It's noisy, tight and scary - that's how children feel about a magnetic resonance imaging (MRI) machine. Because they are scared, they are often too fidgety and anxious during the procedure, causing the images to blur or the scan to be stopped. Researchers have now developed a VR app called Pingunauten Trainer that’s designed to gently prepare the little patients for MRI scans.
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Image: Man on a treatment table under a radiation therapy device; Copyright: panthermedia.net/adriaticphoto

Cardiac arrhythmia: treatment in the linear accelerator

08/04/2019

Cardiac arrhythmia is a group of conditions where nerve cells trigger uncontrolled contractions of the heart muscle. They are treated with either medicine or catheter ablation of the tissue. In an interdisciplinary collaboration, cardiologists and radiotherapists took a different approach and used high-precision radiation therapy to treat a patient for whom the other options proved unfeasible.
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Image: graphical steps of lung segmentation; Copyright: Universitätsklinikum Carl Gustav Carus/A. Braune

Lung segmentation: easier and faster thanks to new algorithms

01/10/2018

A look inside the lungs is a time-consuming process. To identify the boundaries of the respiratory organ from surrounding other organs, tissues, and structures requires between 200 and 500 computed tomographic images and subsequent manual markings – an elaborate process that can take up to six hours. An optimized computer program is now able to do this in only a few seconds.
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Image: Radiology assistant presses a button at the front of a CT; Copyright: panthermedia.net/Arne Trautmann

Lung cancer: Screening with low-Dose CT scans

01/10/2018

Lung cancer is one of the most common and deadliest cancers. The symptoms tend to be non-specific, often causing its detection to be too late. Currently, there is no comprehensive screening. This could change with the use of low-dose CT scans. It should be noted that this is not just an issue of technical feasibility. A screening test must also make sense from a health policy perspective.
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Image: A man is working at a computer that shows a model of the human liver; Copyright: Fraunhofer MEVIS

AI in medicine: Machines do not learn like humans

01/08/2018

For years, medicine has been exploring AI techniques aimed at easing physician workload. While computers may not have the medical expertise and skills obtained through years of study, they can recognize patterns and specific features in datasets and draw deductions.
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Image: Young female radiologist is looking at pictures of the head and takes some notes; Copyright: panthermedia.net/mark@rocketclips.com

Radiology: machine learning to support medical diagnostics

08/03/2018

Automation makes work life easier in many ways but is it also a solution for analyzing medical images? Is a computer actually reliable enough to assist in the medical decision making process? Researchers in Landshut examine how machine learning algorithms can work more reliably and support radiologists.
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