Blog
Exploring the reuse of clinical data for advanced AI pharma research purposes
Unlock the potential of medical data for research with our custom algorithms development services.
The power of predictive analytics in medical algorithms development
Predictive analytics revolutionizes healthcare. In the previous post, we presented case studies illustrating the application of predictive analytics. Today, we delve into the field.
AI in Healthcare – news picked by GLI /07
Are you intrigued by the use cases of AI in healthcare? Explore the latest updates on this subject.
Predictive algorithms development in healthcare area: survey
Rapid technological advancements and abundant health data have paved the way for predictive algorithms to revolutionize healthcare services. Take part in our survey.
Predictive analytics in medical algorithms development: the real applications
Predictive analytics is gaining popularity in medical software development, revolutionizing healthcare with efficient and personalized solutions.
AI in Healthcare – news picked by GLI /06
Is AI in healthcare a topic that piques your interest? Dive into our collection of the most recent news in this field.
How cloud computing influences the security of medical software?
Medical and healthcare organizations benefit from various advantages of cloud computing data. Learn more about the role of cloud computing in healthcare.
Cloud computing in healthcare – a promising avenue for the industry’s advancement?
Discover the power of cloud computing in healthcare. Explore the solutions that are reshaping the future through scalable cloud technology.
Automating Coronary Artery Calcium Scoring With AI
Learn about our AI-based algorithm designed to analyze ECG-gated non-contrast calcium score CT scans and perform the segmentation of coronary artery calcifications.
Understanding legacy code in medical software development
We can audit your legacy code requirements and check how we can update your software. Learn more about our legacy code update services and read about our expertise.
AI in Healthcare – news picked by GLI /05
The subject of AI in healthcare sparks extensive debate. Explore our compilation of the latest news within this domain.
Radiology AI Landscape in numbers (and money)
Radiology AI is emerging at the forefront when it comes to the use of AI in medicine. But do the numbers truly confirm this?
Can AI reduce ionizing radiation exposure in the diagnosis of CAD using CT?
We investigated the hypothesis that AI-enabled automatic analysis of a single contrast CT scan can provide information not only about coronary arteries but also calcified plaques as well.
AI in radiology and a reduction of interobserver variability in assessing patient response
Can AI assist in interobserver variability reduction? How reliable & consistent can it be when analyzing the same patient response over time?
AI in Healthcare – news picked by GLI /04
The subject of artificial intelligence in the realm of healthcare has sparked a widespread and thorough discussion. Explore our collection of the latest updates in this domain.
The recruitment: mission (not) impossible
Recruitment in the IT industry is a very difficult mission, but not mission impossible. Read an interview with HR specialist Graylight Imaging.
AI in Healthcare – news picked by GLI /03
The topic of AI in healthcare is extensively debated. Check out our roundup of the most recent news in this field.
Automated RANO and automated RECIST algorithms at your service?
We’ve developed a fully automated RANO algorithm. It offers a number of advantages – the segmentation of tumours into subregions and the calclulation of their volume.
AI in Healthcare – news picked by GLI /02
AI in healthcare is a widely discussed topic, but where is artificial intelligence currently having a tangible impact in this domain?
AI in Healthcare – news picked by GLI /01
AI in healthcare is the subject of much discussion. But where artificial intelligence is truly making a difference in this area now?
Generative Adversarial Networks (GANs) in healthcare
We discuss Generative Adversarial Networks (GANs) which can be used for various healthcare and medical imaging applications like e.g., modality translation.
Medical Device Regulation (MDR) – complete documentation is the key to success
We present a list of documents which we prepare when implementing a medical device development project. The list is each time adjusted to the client’s needs.
DICOM to STL? Patient-specific printable 3D models
Additive manufacturing and 3D modelling have significant and increasing value in patient-specific surgery planning and medical education.
Multi-class brain tumor segmentation and volumetric measurements
Tumor burden assessment by magnetic resonance imaging (MRI) is crucial to the evaluation of glioblastoma treatment response.
BioTechX – our brain tumor segmentation algorithm
The largest european conference on diagnostics, precision medicine, and digital revolution in drug development and healthcare – BioTechX – is starting tomorrow in Basel.
Generating Smooth Connections in 3D Mesh Models of Brain Arteries
Check our proven approach in generating the actual mesh and appending it to a model in a seamless manner.
Generating 3D printable mesh models of brain arteries
In this article, the author will focus on the step, which consisted of creating walls around the 3D model that had a pre-set thickness over the entire volume.
Brain tumor segmentation challenges – Graylight Imaging’s success
Our deep-learning model for brain tumor segmentation is top ranked in BraTS and FeTS 2022 competing against world-class specialists in AI.
Semi-automatic segmentation
In the area of medical imaging the semi-automatic segmentation term can be encountered. We provide a short explanation & examples of its use.
Automatic and seamless connections for brain aneurysm mesh
Learn how we worked on the automated connection of the inflows and outflows of a segmented 3D model of brain aneurysm to points in a 3D space.
Our contribution to ITK-SNAP open-source software
We use ITK-SNAP in our projects. Our extension allows for defining and setting predefined contrast windows for specific tissue types.
Radiomics: a great potential to impact the future landscape of digital healthcare
We introduce basic radiomics pipelines and dive into the current challenges and opportunities of this promising field of research.
The Beauty of Seeing Beyond the Visible: Automating the DCE-MRI Analysis of Brain Tumors
Imaging biomarkers provide information on tumor prognosis & characteristics promising better a better future of cancer patients.
Assessment of tumor volume in oncology drug development process
AI algorithms in drug development allow us for quicker patient response assessment and earlier go/no-go decisions.
Drug development and clinical trials – what the pharmaceutical market is facing
AI-enabled analysis of medical images becomes more and more needed in clinical trials and the pharmaceutical industry.
Med-Team – the foundation of any GLI ML project
One of the most essential processes of medical imaging is image segmentation. Quality of our resulting AI technologies starts with Med-Team.
World Cancer Day AMA 2022 – You ask, we answer!
We have organized an Ask Us Anything session (#ama) with our BraTS challenge team – the answer all your questions about deep learning models.
Women In Science Day at Graylight Imaging
At Graylight Imaging we are dedicated to lowering the barriers that limit girls and #WomenInScience.
Segmenting pediatric optic pathway gliomas from MRI using deep learning – our contribution
How our experience in AI-enabled MRI analysis of LGG/HGG has translated into an algorithm to segment pediatric optic pathway gliomas from MRI?
Graylight Imaging Data Scientists top ranked in RSNA-ASNR-MICCAI 2021 Brain Tumor Segmentation (BraTS) Challenge
Graylight Imaging team took sixth place at this prestigious challenge – Brain Tumor Segmentation (BraTS) Challenge.
Graylight Imaging – a new brand of Future Processing Healthcare
Explore the new brand of Future Processing Healthcare – Graylight Imaging and discover the many ways you can innovate with us.
Artificial Radiologist – the difference between ML and AI in healthcare
Is artificial intelligence in healthcare a mindless pattern comparator, that does not understand the essence of the disease it is diagnosing?
Automated Medical Image Analysis using AI: The Why, The How, and The What
AI-powered medical image analysis can not only build automated pipelines for the most tedious tasks but can make us see beyond the visible.
The road to perfection in medical image segmentation process
The path we have gone through in the process of medical image segmentation allows our AI-enabled segmentations to meet high standards.
3D medical image processing in cardiology
3D medical image processing cardiovascular models prepared via the segmentation process have very wide applications.
Medical image segmentation as a method for the preparation of learning data
We will look at the medical image segmentation process and our methodology and give some tips on how to improve this process.
Medical image segmentation as an advancement in medical imaging
Digital medical image segmentation and analysis is a natural consequence of advances in medical imaging technology.
Ground-truth in a medical machine learning project
Well prepared data is the basis in medical machine learning project. We present our own process of ground-truth preparation.
Take a deep breath: fast and accurate lung segmentation using conventional image processing
Lung segmentation algorithms are based on conventional image processing or ML or a combination of both. Read about the first method.
Risk management in medical devices
The key to risk management in medical devices is the safety of patients and users of our products. Is it any different for software?
2020 – did it sink or soar for AI healthcare company?
2020 was full of world-shifting events, but also in our team – AI healthcare company – some major things happened.
User experience in medical software projects
We would like to discuss the challenges user experience design in medical software faces while designing for health information technology
Features of an “ideal” grant partner
Grant partner – how to determine the attributes that would characterize our potential partner or subcontractor? We give you some hints.
Applications of AI in medicine: Intelligent Health AI 2020’s Impressions
Impressions on applications of AI in medicine from Intelligent Health AI 2020 by our Machine Learning experts.
Artificial Intelligence in Radiology: highlights of ECR 2020
Artificial intelligence in radiology is the proper weapon that we need to empower radiologists with. Read our highlights from ECR 2020!
Pandemic experiences that let us see the future in brighter colours
Our insights into the pandemic experiences we all share, which in our opinion have a chance to contribute a lot of good.
The greatest ills in managing medical software development
Is managing medical software development different from managing other projects? Our Team Leader talks openly about practice.
Quality assurance in a medical project
Quality assurance in a medical project is an area where it is important to understand the nature of the industry and its needs
Software outsourcing partner and organizational culture – success factors
How to address concerns about the organizational culture of a software outsourcing partner and its impact on the success of a project?
Managing dispersed teams in medical software projects
The number of projects carried out by remote teams or hybrid teams grows every year. We share our experience in managing such dispersed teams.
ISO 13485 software provider– is it really crucial?
A couple of reflections on requirements involved when it comes to software as a medical device. Is ISO 13485 software provider crucial?
Mean Opinion Score as a method for the validation of R&D project results in imaging diagnostics
How to establish an objective measurement, crucial for clinical assessment, to gauge the quality of our results in a medical r&d project?
Roles in a medical software outsourcing project – what does it look like?
How do you make sure that the priorities are well understood? Read abour the roles in IT projects.
Mission: to recruit programmers
Recruitment process in IT – by being close to this market, we see some constants and share our perspective.
Medical project estimation – what is worth remembering?
Read about the proper sequence of actions and help yourself with a few proven tools.
How do Machine Learning algorithms learn?
Krzysztof Kotowski, our AI Specialist, tackles techniques of algorithms-training.
How to verify the medical software product idea?
I would like to raise the issue of the analysis of the medical product idea, which is an attempt to assess if it has a chance of success.
Medical MVP development – how to guide?
Is medical MVP development possible? Does the MVP idea apply to healthcare products where certification is a must?
Medical software development difficult beginnings. How to cooperate?
I share my observations regarding the development of medical software from the application service provider point of view.
What exactly is Machine Learning?
How about simplifying the “application of artificial intelligence in the medical sector” issue by going BACK TO BASICS?
ISO 13485 certification – how to prepare?
To deliver a solution compliant with medical standards be aware that ISO 13485 certification is not a simple list of instructions.
Comparing medical imaging software development: in-house vs. outsourcing
A comparison of both ways in terms of such areas as culture, talent pool, confidentiality, communication, control, risk and projects’ price.
R&D outsourcing: 6 reasons why
Although r&d outsourcing has its cost-related history, the trends begin to change as companies strive to gain a competitive advantage.
