A Guide to Medical Imaging Software Development

223 05.29.2023
Vasyl Polych

Founder & CEO at Northell


Table of contents

With the evolution of digital transformation in the healthcare sector, medical imaging software development is a powerful tool to tackle the challenges of data overload, clinical errors, and time shortage. By implementing digital imaging technologies, you can reduce the workload of practitioners by helping them reduce the time it takes to interpret images, improve medical accuracy, and, as a result, treatment outcomes.

However, the list of benefits for business and care quality is much longer, giving you many opportunities to reap the advantages of powerful medical image analysis capabilities.

In this article, we’ll explore the key features, benefits, and requirements of medical imaging software, the top market trends, and the healthcare sectors and departments that require it. Enjoy our experience-based step-by-step medical imaging software development guide to help you turn your idea into a robust technical solution!

What is medical imaging software development?

As the name suggests, the definition of medical imaging software development implies designing, developing, and testing medical image analysis software for improved and quick interpretation of radiology scans. Medical imaging software development involves using advanced computer algorithms and techniques to enhance and interpret medical images, such as X-rays, computed tomography (CT) scans, magnetic resonance imaging (MRI) scans, ultrasound images, thermography, echocardiography scans, and more.

Healthcare providers, hospitals, research centers, and clinics use medical imaging software to capture, store, analyze, and visualize medical images.

Medical image analysis solutions help healthcare professionals in multiple ways:

  • Assist with a medical diagnosis
  • Plan treatment
  • Conduct medical research
  • Detect pathologies on images that do not show visible anomalies
  • Monitor disease progression
  • Streamline communication and image data sharing


As you can see, medical imaging software delivers much more options than just viewing the images. As a result, the capabilities of medical imaging software allow medical professionals to:

  • Minimize clinical errors
  • Reduce radiation exposure for patients
  • Increase recovery/survival rate
  • Reduce unnecessary procedures
  • Accelerate image processing workflow
  • Minimize hospital stays
  • Improve the quality of care
  • Save time and resources


Recommended reading: How to Develop Healthcare Software Product?[ Vendors, Standards, and Real Cases]

Top trends in medical image analysis software

According to the qualitative study published by Data Bridge Market Research, the medical imaging software market is expected to reach USD 11.12 Billion by 2030, at a CAGR of 7.5% during the forecast period 2023 to 2030. The increasing demand for medical imaging software creates a boost in the market, also driven by advances in top technology trends, including machine learning, artificial intelligence, and cloud computing technologies.

Below, we’d like to list some of the top trends in medical image analysis software supported by market statistics and research studies.

features top trends medical imaging software development

Cloud computing

With the advent of cloud computing, medical image analysis software can now be run on powerful servers, allowing faster processing and storage of large datasets. According to a report by MarketsandMarkets, the global cloud-based medical imaging market has been shifting from the on-premises model to a cloud-based infrastructure over the past years more and more.

Cloud computing is taking over as it provides healthcare providers flexibility, scalability, and cost efficiency. Applying cloud architecture to their medical imaging workflows allows them to store tons of medical images easily and securely and facilitates medical image data sharing.

Looking for a reliable technical partner to help you migrate to the cloud? Wait no more with our cloud app development services!

3D visualization

Medical image analysis software can now be used to create 3D models of organs and other body parts for planning surgical procedures and medical research. Doctors can easily view medical images and areas of interest in three dimensions, identify abnormalities on time, and increase their detection accuracy.

According to a report by Grand View Research, global 3D printing in the healthcare market is expected to reach USD 88.28 billion by 2030. These statistics demonstrate the potential for continued growth and development of medical image analysis software. Moreover, since MRI, CT, and X-Ray scanners are evolving to produce high-quality 3D images, the demand for medical image interpretation software will only increase.

Artificial intelligence (AI)

According to a report by Allied Market Research, the global market for AI in healthcare is projected to reach $194.4 billion by 2030, growing at a CAGR of 38.1% from 2021 to 2030. Not surprisingly, AI and machine learning are massively used to develop medical image analysis software that can solve most of the pain points in the medical imaging niche. Artificial intelligence is a crucial technology in modern radiology as it helps:

  • Automatically detect abnormalities
  • Assist with a medical diagnosis
  • Analyze a large amount of imaging data
  • Automate the image analysis workflow
  • Decrease the number of wrongs or missed diagnoses
  • Reduce the need for invasive diagnostic tests
  • Improve image quality by removing distortions, reducing noise and artifacts

Virtual and augmented reality (VR/AR)

AR/VR technologies are used to overlay medical images on the patient’s body, making it easier for doctors to visualize and understand complex medical conditions. AR technology helps establish a diagnosis and is used to create virtual and augmented reality simulations for medical training and education.

According to a report by MarketsandMarkets, the global market for virtual and augmented reality in healthcare is expected to reach $114.5 billion by 2027 at a market growth of 25.3% rate. The phenomenal growth in demand for virtual and augmented reality has led to the creation of many advanced imaging solutions that are revolutionizing the healthcare industry, helping doctors perform surgeries with greater accuracy.

Deep learning

Deep learning is a type of machine learning that involves training artificial neural networks to analyze and interpret complex patterns and features in medical images. Deep learning in the global healthcare market is expected to reach $13.4 billion by the end of 2025, according to a report by MarketsandMarkets.

Deep neural networks are being used to improve medical image analysis, faster and more accurate diagnosis, and greater automation, which helps streamline many aspects of medical image analysis, reducing the burden on radiologists and other healthcare professionals.


Telemedicine is the use of technology to provide healthcare services remotely. Medical image analysis software can be used to transmit and analyze medical images from remote locations, helping patients living in rural areas receive timely medical care.

According to a report by Meticulous Research, the global telemedicine market is projected to reach $539.73 billion by 2029, growing at a CAGR of 21.6% from 2022 to 2026. The report notes that tele-imaging (including medical image analysis) is among the key application areas driving the growth of the telemedicine market.


Related reading: Telemedicine Software Development: Standards, Features, and Cost

Which healthcare departments do you need medical imaging software development for?

The use of medical imaging software for diagnosis can be beneficial to many of the healthcare departments listed below. Let’s find out how.

expertise healthcare departmnets



Medical imaging software is commonly used in radiology departments to capture, store, and interpret medical images, such as X-rays, CT scans, and MRIs. By providing detailed images and data, doctors can analyze and compare them to previous scans, making more accurate diagnoses and treatment plans. It can also help radiologists manage large amounts of imaging data and collaborate with other healthcare professionals.


Medical imaging software is used in cardiology to analyze heart images, including echocardiograms, angiograms, and nuclear medicine scans. This software is widely applicable by cardiologists to identify and diagnose heart conditions, such as coronary artery disease, heart valve problems, and arrhythmias. It can also help cardiologists plan and monitor treatments, such as heart surgeries, and track patient progress over time.


Medical imaging software is used in orthopedics departments to analyze medical images of bones and joints, such as X-rays and CT scans. This software helps orthopedic surgeons diagnose and treat bone and joint conditions more accurately and use the images for implant design. The powerful capabilities of image segmentation software are also efficient in detecting different types of bone tumors, such as osteosarcoma.


Regarding image-based decision-making, medical image analysis software development for dentistry comes in handy in various ways. It helps maximize diagnosis accuracy, accelerate dentists’ workflow speed, and detect caries, osteoporosis, and other pathologies. Image analysis tools are also used for designing orthodontic appliances and dental prostheses.


Medical imaging software is used in neurology departments to view and analyze medical images of the brain and nervous system, such as CT scans, MRI scans, and PET scans. This software can help neurologists diagnose and treat conditions like strokes, tumors, and degenerative diseases like Alzheimer’s and Parkinson’s.

For example, researchers from the University of California found that AI can detect early signs of Alzheimer’s disease. They built a machine-learning model capable of identifying the disease by looking at brain images taken six years before patients were diagnosed with the disease.


Medical imaging software is used in oncology to view and analyze medical images of tumors, such as CT scans, MRI scans, and PET scans. This software can help oncologists accurately diagnose and stage cancers, plan, monitor, and optimize radiation therapy treatments for cancer patients. According to the research article in the Lancet Digital Health, AI models can identify breast tumors that are otherwise impossible to detect.

Who needs medical image analysis software development?

The application of medical image analysis software is a common practice for many participants in the healthcare industry. Let’s see how the latest technologies and tools of medical imaging software improve many aspects of their work.

top benefites who needs medical image



Hospitals use medical imaging software to capture, store, and analyze a large amount of patient data and comply with regulatory requirements for medical imaging data management and privacy. Precise medical scans allow doctors and healthcare professionals to diagnose and treat medical conditions more accurately and efficiently. It results in improved patient care and outcomes.

In addition to improved data management and treatment outcomes, medical image analysis software can be used as an effective communication and collaboration tool for different departments and healthcare professionals to improve treatment coordination.


Clinics use medical imaging software to provide diagnostic imaging services to patients. This software helps healthcare professionals analyze medical images and diagnose patients more accurately. It can also help clinics manage and store medical imaging data more efficiently, reducing costs and improving workflow.

Research institutes

With the help of modern technologies and tools, clinicians and researchers can accelerate research progress. Scientists often use medical imaging equipment to conduct different forms of research, from developing new vaccine formulations to treatment facilities, etc. Medical imaging software offers suitable scans, reports, metrics, and analytics that allows careful analyze the human body and its mechanisms. In turn, it helps research institutes formalize inventions with more precise studies and research data.

For example, AI-enabled medical imaging software help analyze various viruses, the pathway of body cells, and mutations of genetics. All these help pave the way to better experiments and studies, so research institutes are open to numerous advanced innovations in the diagnostic center.

Imaging centers

Medical imaging software can help diagnostic imaging centers improve the quality and accuracy of their diagnoses. With its help, imaging centers can also manage and store tons of critical patient data more safely and efficiently while reducing operational costs and improving the internal workflow.

Veterinary clinics

Not only people can experience the benefits of image processing software, but also our little friends. With its help, veterinary clinics can provide diagnostic imaging services to animals. This software helps veterinarians diagnose and treat various conditions in animals while ensuring maximum accuracy and veterinary workflow speed.

Medical equipment manufacturers

Medical imaging software can also help manufacturers stay competitive by offering advanced features and capabilities that meet customer needs and market demand. They use medical imaging software to develop and test new medical devices and systems, leading to better performance and user experience. This software helps to ensure that medical devices are safe, effective, accurate, and compliant with regulatory requirements and healthcare certifications.

Telemedicine software providers

Medical imaging software can help telemedicine software providers offer more comprehensive and effective remote healthcare services for people living in rural places or those who don’t have time to attend hospitals in person but still need medical help or require 24/7 health monitoring. This software is used for medical imaging and diagnosis at a distance. The diagnosis results are securely transmitted from remote locations to healthcare professionals via this software. So, it helps improve access to medical care for patients with different conditions and needs.

7-step guide to medical imaging software development

Developing medical imaging software is not a trivial task, especially if you choose to go this route from scratch. A medical imaging software engineer should clearly understand the type of medical imaging software you need, access all business requirements, and deliver software analysis software in line with global regulatory standards.

As an experienced healthcare software provider, we’d like to share a step-by-step medical imaging software development process to help you build a top-notch medical imaging solution with limited risks and budget overruns.

a step-by-step medical imaging software development


Step 1. Analyze your idea and conduct market research

Since the medical imaging software niche is diverse and there is no one-size-fits-all tech solution to suit all needs, it’s essential to start with an analysis of the idea and the market in general. This step also involves understanding the software’s requirements and functionalities, user needs, and other factors that will impact the development process.

Let’s look at what tasks we typically solve during the first step of medical image analysis software development based on our NDA case:

  1. Research the market: We first analyze similar medical imaging software available in the market. Our BAs analyze the latest trends and innovations in the healthcare industry to identify gaps in the market and develop features that will make your app competitive. For example, in our NDA case, we needed to develop a radiology platform with innovative training tools to help radiologists learn how to explain symptoms based on medical scans. However, we’ve added advanced tools for fast and accurate x-ray interpretation to make his app stand out.
  2. Define and analyze your target audience: We study the preferences and behavior of your target audience, identify their pain points and decide what functionality can help them solve their needs. For example, in our NDA case, we worked on radiology training platform development and needed to analyze three primary app personas: a radiology mentor, a student, and an admin. Each of them has specific needs that need tailored features.
  3. Conduct competitor research: We study similar offers in the medical services market and the strengths and weaknesses of direct competitors to find the best solution to the same user’s problems.
  4. Create a unique value proposition (UVP): We create a value offer that aligns with your core business goals based on research findings. For example: create feature-rich radiology training platforms that enable aspiring and practicing radiologists to learn how to diagnose patients by interpreting x-rays and growing their radiology skills.
  5. Compile technical documentation: We start creating detailed documentation that contains all our customer’s requirements, tech stacks, the scope of work, team structure, and project milestones.
  6. Estimate project timelines and costs. We perform a detailed time and cost analysis to set the required funding and schedules for the whole project.

Step 2. Compile a list of core features

After we finish all the market analysis tasks, we start compiling a list of core features for all software personas identified earlier.

As in our project, we first needed to understand user needs to develop feature sets that would help meet their needs and solve problems. For example, we first built an image-reporting simulator to help radiologists practice their skills using the high-quality image viewer. Without this feature, the platform’s value becomes unclear.

Here, essential to note that a list of features should be filtered by priority. It will highlight the most important features you should develop first to help solve core users’ needs, understand their feedback and then move on to the rest. This way, you will avoid implementing redundant functionality as well as save time and costs.

Step 3. Choose monetization plan

Healthcare providers and medical software vendors should decide on the most profitable business model to get the most out of their medical imaging products and services. Typically, several monetization plans exist for medical imaging software, including:

  • Subscription-based model. This model involves charging users a regular fee for access to the medical analysis software. The payment can be monthly, yearly, or based on a specific usage limit.
  • Pay-per-use model. With this model, users pay only for the features they use or the number of images they process. This model is popular with imaging centers or hospitals with periodic imaging needs.
  • Licensing model. The licensing model involves selling the software to healthcare organizations or medical equipment manufacturers for a one-time fee. The licensing model often provides technical support and maintenance services for a fixed period.
  • Commission-based model. With this model, you can charge a commission for every image processed or every diagnosis made using the software. This model is popular with telemedicine providers, providing remote medical consultations.
  • Value-based model. This model charges users based on the value the software provides. For example, if the software can reduce the time it takes to diagnose a condition, the fee can be calculated based on the value of that time saved.

Step 4. Gather a dedicated development team

To reap the benefits of medical imaging software, it’s essential to enlist the support of an experienced medical imaging software development company with the required specialization to create a user-friendly design and secure and compliant medical imaging solutions.

Moreover, since the technological advancements in the healthcare sector don’t stand still, you will need to constantly upgrade your software to meet urgent user needs and shifting market demands.

The optimal solution that will back up your business and software from multiple perspectives is to hire a team with a proven experience in healthcare software development.

At Northell, we have vast experience in the healthcare niche, proved by positive customer feedback, company ratings, and many successful cases from our portfolio. We have a broad market picture to help you validate your business idea and take care of the technical implementation of your medical imaging solution.

Get more insights from our in-house experts on how to build a software development team in 2023!

Step 5. Create UI/UX design

The UI/UX design stage of medical imaging software is critical to designing user-friendly and intuitive software while being robust and functional. This step requires maximum attention since you deal with healthcare products and services. In our case, your software should allow doctors, nurses, medical physicists, and technicians to access and manage images easily, enabling them to perform analysis and measurements efficiently.

At Northell, the steps we undertake during the UI/UX design stage of medical image analysis software development are:

  1. Design requirements gathering. We gather requirements from all project stakeholders to understand the needs and workflows of the healthcare providers using the software.
  2. User research. We research to study the end users, their needs, and their pain points to develop a product that meets their requirements. We also use this information to create user personas and stories to guide the design process.
  3. User flows and customer journey mapping. Our designers identify user flows and create customer journey maps to visualize how end users will engage with your product and reach their primary goal.
  4. Choosing a design framework. Our designers choose a suitable design framework for the medical imaging software based on the requirements gathered. That involves selecting a set of design patterns, best practices, and design principles.
  5. Creating style guides. A style guide is a set of guidelines for the design of the software, including typography, color schemes, and visual elements. A style guide ensures that the creation of the software is consistent across all screens and interactions.
  6. Wireframing and prototyping. Our designers typically start with creating a low-fidelity product layout to test the structure, user flow, and product navigation. After the early designs are agreed upon, we move on to more accurately represent the final product and design a preliminary model of the final software interfaces and navigation.
  7. User testing. Finally, our designers conduct user testing to ensure that the software is easy to use and meets the needs of healthcare providers and patients alike. User testing involves recruiting participants to test the software and provide feedback on its usability and functionality. Based on the feedback received, designers can make necessary adjustments before the software is handed over to developers. Northell has its own in-house UX Lab that helps us to spot even minor usability gaps and improve user experience.

Step 6. Build the MVP version and test it

Before you decide to roll out a full-fledged medical imaging software development, we recommend starting with MVP first. The main goal of MVP development is to create a functional version of the software with a basic set of features for testing and validating the concept before investing too much time and money into full-scale development.

At Northell, medical imaging software development takes 2-4 months (instead of 6+). This period is enough to start collecting feedback from the end users. Once any problems are encountered, we can easily fix them and save on effort, time, and costs. It is critical for all software products developed from scratch, as we can only fully understand whether your users will want to use your product once we test it in practice.

The testing goes iteratively, so the steps recur until the software is thoroughly fine-tuned and approved by end users.

Recommended reading:  How To Create a Minimum Viable Product (MVP)? [Startup Case Studies]

Step 7. Launch, support, and scale your product

Any technological product requires regular updates and releases of new sophisticated versions in line with up-to-date trends, standards, and technologies. Due to the medical imaging software’s complex nature, it requires ongoing attention and post-launch support. So, during the development process, it’s also essential to have a plan in place for ongoing support and updates.

Whether you need to fix bugs, perform regular software security audits (e.g., GDPR, HIPAA compliance, etc.), roll out new features, or upgrade the software, Northell offers continuous post-release support and technical help whenever you need it.

Require assistance in crafting exceptional medical imaging software? Wait no more and contact us!

Key features of medical imaging software to consider

Existing on the market medical imaging software differs in the scope of functionality and technical complexity. However, there are core functions that any medical imaging software should perform. Let’s review them.

features key features of medical imaging


Lifecycle automation

Medical imaging software can optimize healthcare providers’ communication and collaboration workflows, speed up internal processes, and drive employee productivity. Since medical imaging software deals with tons of patient data and medical imaging data, such a feature comes in handy while also freeing up space for practitioners and researchers to spend time making more accurate diagnoses.

Image registration

Image registration is aligning medical images to a common coordinate system. It allows for better comparison of images and can help doctors track changes in the patient’s condition over time.

There are multiple techniques used for image registration, including feature-based (identify and match critical features or landmarks, such as edges, corners, or points, between images), intensity-based (match the intensity values of corresponding pixels or voxels in the images using similarity metrics, such as mutual information, correlation coefficient, or mean squared error), and hybrid methods (combines both feature-based and intensity-based techniques to achieve a more robust and accurate registration result).

The image registration process includes pre-processing, feature extraction, matching, transformation, and validation. It is critical for applications such as image fusion, multi-modal image analysis, and longitudinal studies.

Image segmentation

Image segmentation is the procedure of dividing a medical image into separate parts, such as organs, bones, and tissues. This process is widely applicable for deeper diagnostic insights for doctors, allowing them to detect pathologies and abnormalities in the region of interest.

3D reconstruction and 2D visualization

Medical imaging software should be able to create 3D images from 2D images and provide 3D visualization of organs, bones, and tissues to help physicians identify and diagnose medical conditions. 3D reconstruction is the process of dividing a 3D visualization into 2D components or segmenting a 2D image into smaller sections for greater accuracy. Capable of viewing a single area of interest in 3D, clinicians can explore abnormalities more efficiently.


Quantification associates image segments with diagnostic information such as their shape, size, texture, and morphology. This feature allows physicians and researchers correctly measure and analyze various anatomical structures, tissue characteristics, and physiological parameters in medical images. It enables them to accurately assess and monitor body changes over time, particularly useful for disease diagnosis, treatment planning, and treatment effectiveness.

EMRs/ EHRs/PACS/RIS integration

The software should be able to integrate with other medical software and systems, such as electronic medical records (EMRs), electronic health records (EHRs), picture archiving and communication systems (PACS), and radiology information systems (RIS). Integration with other critical healthcare software systems is paramount for seamless access and exchange of medical images and patient information and well-optimized workflows.

Analytics tools

Built-in analytics capabilities will help you track and analyze tons of patient data more efficiently. With various analysis tools in hand, such as measurement, annotation, and comparison, physicians and radiologists can make more accurate diagnoses, which is one of the primary values of medical imaging software.

Reporting and documentation

The software must have features for generating reports and documenting the results based on medical images and data, facilitating efficient and accurate communication of findings and treatment plans. There should also be a system for managing and archiving images and reports. It can also integrate with electronic medical record (EMR) systems and provide automated notifications for critical findings, ensuring timely and appropriate follow-up actions.

Tech requirements for medical image analysis software development

There are specific tech requirements associated with the implementation of medical image analysis software you should follow to enjoy the full potential of modern technologies and minimize failures. Let’s consider them in detail.

Tech stack

Choosing the right technology stack that meets the project’s specific requirements and is scalable and maintainable for future development is essential. At Northell, we prefer a personalized tech stack that can vary from case to case, yet, we always make sure the tech stack respects all necessary standards for data safety, image quality, and regulatory compliance.

For medical image analysis software development, we recommend the following tech stack:

  • Programming languages: Python, Java, C++, and JavaScript.
  • Frameworks and libraries: TensorFlow, Keras, PyTorch, OpenCV, and Django.
  • Imaging tools and formats: DICOM, NIfTI, MINC, ECAT7, etc.
  • Cloud platforms: AWS, Azure, and Google Cloud Platform.
  • Database management systems: MySQL, PostgreSQL, and MongoDB.
  • Front-end technologies: HTML, CSS, and JavaScript frameworks like React or Angular.
  • Testing and deployment tools: Jenkins, Docker, and Kubernetes.

Security measures

Healthcare software deals with a vast amount of sensitive patient and medical data. So, it’s crucial to guarantee medical imaging software fulfills all applicable rules and standards for data privacy and security.

Some of the significant security measures we implement for medical imaging software development are:

  1. User authentication: It ensures that only authorized personnel can access medical images and patient data.
  2. Two-factor authentication: It adds an extra layer of security to user authentication, making it harder for unauthorized personnel to access medical images and patient data.
  3. Multi-level data encryption: It is crucial to encrypt data in transit and at rest to safeguard it from unauthorized access.
  4. Role-based access control: It restricts access to sensitive patient data to only authorized personnel based on their job roles.
  5. Audit trails: It is essential to log user activities, including access and modifications to medical data, to detect unauthorized changes.
  6. Regular security audits: Conduct regular security audits to identify vulnerabilities and timely mitigate them.
  7. Firewall installation: It is necessary to install a firewall to protect medical imaging software from external threats, such as malware and hackers.

Legal compliances

For any healthcare project, it’s paramount to understand and analyze compliance requirements and laws applicable in a specific application area and integrate them into the development process.

Healthcare imaging software is not an exception. Complying with these legal compliances, standards, and certifications is crucial for medical imaging software development to ensure patient privacy and safety, interoperability between systems, and adherence to quality control procedures. Otherwise, non-compliance can lead to illegal data use and security breaches, costing your business millions of dollars in legal penalties.

So, ensure your development team is aware of the following legal compliances for medical image software development:

  • HIPAA: The Health Insurance Portability and Accountability Act (HIPAA) regulates how patient data should be protected, including medical image storage and sharing standards.
  • GDPR: The General Data Protection Regulation (GDPR) applies to all companies that process the personal data of EU citizens.
  • FDA: To guarantee its effectiveness and safety, medical imaging software may be regarded as a medical device and may need the US Food and Drug Administration (FDA) approval.
  • DICOM: The Digital Imaging and Communications in Medicine (DICOM) is a standard for handling, storing, printing, and transmitting medical images and associated data.
  • HL7: A set of international standards for transferring clinical and administrative data between software applications.
  • ISO 13485: This standard for medical devices and quality management systems ensures that medical imaging software development adheres to strict quality control procedures.

Our experience in medical image analysis software development

Northell is a healthcare software development company that helps healthtech-enabled startups, SMBs, and enterprise-level healthcare providers build, modernize and scale HIPAA-compliant healthcare technology solutions. We have a solid background in developing highly-demanded medical imaging software that meets the required tech requirements, quality standards, and security protocols.

We also offer:

  • Telemedicine software development
  • Healthcare insurance software development
  • Medical billing software development
  • Hospital management software development
  • Healthcare CRM software development
  • Wellness software development


Recently, one of the largest clinics in Western Europe reached out to Northell to build a radiology platform for x-ray interpretation and online education.

Upon receiving preliminary ideas from our customers, we conducted interactive brainstorming sessions to identify the main challenges and areas for work.

  1. Redevelop and implement a fast and reliable x-ray interpretation process
  2. Provide a scalable architecture to adapt to the traffic load seamlessly
  3. Ensure strong application security and data privacy
  4. Create an easy-to-use, intuitive user interface and engaging user experience
  5. Comply with the GDPR’s key regulations and requirements 


As a result of our cohesive teamwork, we’ve built such features:

  • Easy login/sign up in two quick options: via login and password and by email
  • Radiologist dashboard where diagnosticians can access several sections: radiology sections, image reporting simulator, microlearning simulator, webinars, and online video courses
  • Image reporting simulator where users can practice on real anonymous cases online
  • Webinars library for easy user access
  • Online video conferencing and messaging to connect students with radiology mentors via reliable communication protocols
  • Text chat for more accessible communication and site navigation
  • A payment system that allows users to securely pay for purchases through the platform by card or bank transfer
  • Quiz or questionnaire users can take to check how well they have understood the material


As a result, the Northell team implemented non only an online training tool for radiologists but created a medical imaging solution for easy and accurate x-ray interpretations. Such a powerful platform’s capability significantly improves training outcomes and helps beginners, practicing radiologists, and clinics streamline and improve their medical practice.

How much does medical imaging software development cost?

The cost of medical imaging software development can vary widely depending on various factors, including:

  • Functionality scope + the number of supported platforms (IOS, Android) and complexities of features
  • Integration with other healthcare systems ( e.g., EHR, EMR, PACS, RIS, etc.)
  • The number of advanced features
  • Technology stack
  • Security measures
  • Storage capacity
  • Scalability requirements
  • The team size and experience required for the development


As a rough estimate, medical imaging software development costs can range from $50,000 to $500,000 or more, depending on the project scope, type of healthcare solution, and focus.

At Northell, we’ve estimated the average hourly rates of software specialists depending on the region and project stage.

tables rough project costs for Medical imaging software development

This picture may help calculate an approximate project cost. However, it all depends on your unique case. Consult with us for an accurate estimate based on your needs and requirements.

Medical imaging software development: summary

The demand for medical image processing, management, and analysis grows at a high pace. The primary factors behind this are the abundance of medical data, time constraints, and the demand for accurate analysis and treatment. That’s why many healthcare companies, hospitals, and clinics develop modern, efficient medical imaging solutions to address key healthcare challenges.

However, medical imaging software development is a complex process that requires technical expertise and domain knowledge. Northell’s expert team of developers can help you create bespoke software solutions to meet your unique needs and goals. So, don’t let outdated technology or lack of tech expertise hold you back – trust Northell to help you develop modern, user-friendly medical imaging software that will take your healthcare services to new heights.

Contact us today to schedule a consultation!

How to hire medical imaging software engineers?

Hiring medical imaging software engineers requires a strategic approach. Here are the main steps Northell follows during the hiring process:

- Clearly describe project needs. Examples include the technological stack, programming languages, and skill level needed for the project.
- Find potential applicants. After we've established the project requirements, we start looking for individuals. To locate the best applicants, we can look in various places, including job portals (e.g., LinkedIn, Clutch, and GoodFirms), social media, personal recommendations, and business networks.
- Screening the candidates. After discovering possible candidates, we screen them by looking at their portfolios, resumes, and references.
- Do technical interviews. After we've narrowed down a list of prospects, we perform technical interviews to evaluate each candidate's technical proficiency, familiarity with the creation of medical imaging software, and prior experience working on projects of a similar nature.
- Assessing soft skills. Assessing candidates' soft skills, including communication, teamwork, problem-solving, and flexibility, is critical.
- Making an offer. Once the ideal individual has been found, we send them a job offer that is competitive and in line with their expectations.

What skill set should professional medical imaging software engineers have?

Professional medical imaging software developers for medical imaging should possess the following competencies:

- Programming knowledge in languages like C++, Java, Python, or MATLAB.
Thorough understanding of algorithms for computer vision and image processing.
- Knowledge of frameworks for software development, such as Qt or .NET.
familiarity with medical imaging standards and file formats, including DICOM, NIfTI, and Analyze.
- Knowledge of deep learning and machine learning frameworks, such as PyTorch, Keras, or TensorFlow.
- Understanding of database management systems like MongoDB, PostgreSQL, or MySQL.
Strong analytical and problem-solving abilities.
- Having a sound knowledge of web technologies, including HTML, CSS, JavaScript, and AJAX.
- Excellent communication and teamwork abilities to work well with clients, healthcare experts, and other developers.
- Understanding of healthcare security and privacy laws including HIPAA and GDPR.

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