Medical Imaging Software Development: Key Features, Cost and Requirements

In 2024 alone, the medical imaging software market size reached $8.11B. By 2029, it is projected to grow to $11.83B and up to 7.84% at a CAGR. This is a fairly predictable trend due to the development of AI. Especially since big data, cloud technologies, and other advancements are already significantly speeding up the accuracy of diagnostics. 

If you are considering custom development of medical image analysis software, now is the most favorable time. Below, we will reveal the specifics of creating such solutions and describe the requirements and the challenges you may face.

What is the definition of medical imaging software?

Medical imaging software — it's the digital tool doctors use to examine medical images. Think X-rays, MRI and CT scans, ultrasounds, PET, and other radiology scans. Basically, it helps to see the details of every complex illness and make informed decisions about patient care.

To maximize efficiency, medical imaging software integrates a range of advanced technologies. These include AI for anomaly detection, ML for image segmentation, and methods for filtering, contrast enhancement, and noise reduction to improve image quality. 

Also, 3D reconstruction technologies create volumetric models of organs and tissues. Developers also rely on the DICOM standard for medical images as it allows seamless transfer. They also use cloud tech to access data, integrated medical records, and VR and AR to visualize data and create interactive interfaces.

As a result, with medical image analysis software, healthcare organizations reduce the workload of their doctors and researchers and minimize the likelihood of misdiagnosis.

Examples of medical imaging software

To better grasp how these solutions work, we suggest you look at several medical imaging software examples that have gained worldwide recognition.

RadiAnt DICOM viewer

It is a high-performance medical imaging software that processes DICOM images. Due to its rich functionality, both doctors and researchers use it in their work. It has smart multimodality tools for 3D and 2D visualization and MPR (multiplanar reconstruction). Moreover, developers made the interface very user-friendly, so this software is also a great choice for users with low technical skills.

OsiriX MD

Specifically designed for macOS, OsiriX MD is a powerful DICOM platform that meets the needs of radiologists. Its advanced capabilities support 3D and 4D image analysis, hybrid imaging with PET-CT and PET-MRI, and integration with PACS servers. Crucially, it is FDA- and CE-certified for clinical use.

Horos

Horos is a free OsiriX-based DICOM viewer available on macOS. It has rich customization options for analyzing volumetric data, such as 3D reconstruction, and is especially useful for students and researchers. 

GE Healthcare Centricity PACS

GE Healthcare Centricity PACS is a proprietary enterprise medical image analysis software that analyzes medical images. It has EHR and EMR integration, real-time collaboration, advanced AI analysis, DICOM standards, and format support. It can be a full-fledged assistant for doctors and researchers. 

Philips IntelliSpace Portal

Tailored for large clinical institutions, Philips IntelliSpace Portal excels in medical image analysis and visualization. It integrates AI-driven automation and tools for multiparametric imaging in cardiology, neurology, and oncology; this medical imaging software supports multi-user collaboration.

Key features of medical image processing software

This section explores the key functionalities typically found in standard medical imaging software.

Tools for viewing and processing medical images

Ensure your medical imaging software works with various input data (CT scans, MRI scans, X-rays, ultrasounds, and hybrid studies like PET-CT and PET-MRI). Usually, this is done by supporting the DICOM format. In addition, you will need tools to scale, rotate, and adjust image contrast. So, optionally, develop a panel for 3D and 4D visualization, including multiplanar reconstruction.

AI-driven image analysis 

AI is key in automating the detection of anomalies in medical scans. It can identify cancerous tumors, blood clots, and fractures early, with a high degree of independence. Also, AI in your medical imaging software can classify pathologies using trained models. It can segment organs and tissues on scans and analyze multiparametric data.

Diagnostic and treatment planning tools

This includes tools for creating 3D models, surgical planning, and evaluating the effectiveness of treatment. You should also consider integrating your medical imaging software with robotic surgical systems.

Medical data management tools

To implement effective medical data management, you will probably need to integrate your medical imaging software with PACS (for storing and transmitting data), EHRs (for centralized access to personal patient information), and cloud solutions (for unimpeded access to images from anywhere in the world where there is an Internet connection).

Collaboration tools

It's mainly for remote access so doctors and specialists can chat and comment on each other's actions. It also involves integrating telemedicine platforms to discuss complex cases and hold educational seminars.

What types of organizations need medical image analysis software development?

A wide range of organizations can benefit from medical image analysis software development. Now, let's find out which areas of healthcare benefit from medical imaging software the most.

  • Cardiology.

In this field, medical imaging software is mostly used to analyze CT and MRI of the heart and angiography. In addition, it monitors treatment effectiveness, plans operations, and predicts cardiovascular disease risks.

  • Dentistry.

Inevitable for 3D scanning when planning dental implants, diagnosing jaw diseases, visualizing root canals, etc.

  • Oncology.
    Here, medical imaging software detects and classifies tumors, tracks their growth, and assesses treatment effectiveness.
  • Neurology.

In this sector, medical image analysis software analyzes brain MRIs and CTs and provides 3D visualizations to assess the spine and nerves.

  • Orthopedics.

Orthopedics studies thrive on precise X-ray analysis, which includes 3D joint modeling and spinal disease diagnostics.

  • Mammology.

Medical imaging software can detect microcalcifications and early breast cancer through comparative analysis of changes in mammary gland tissue.

  • Urology.

In this industry, medical imaging software helps diagnose kidney and bladder diseases. It does this by analyzing CT and ultrasound images. Additionally, the software can help plan operations and monitor patients with chronic diseases.

  • Pulmonology.

Industry specialists can use such software to diagnose lung diseases, analyze chest CT data, and assess COVID-19 damage.

  • Gynecology.

In most cases, medical image analysis software is used to perform pregnancy ultrasounds. It helps monitor the fetus, find pelvic tumors, and analyze the endometrium and other tissues.

  • Traumatology and emergency medicine.

In traumatology, 3D medical imaging software can quickly diagnose fractures and internal injuries. It can also visualize organs for urgent decisions.

Still, deciding on the right healthcare sector for your medical imaging project? Contact us and discuss the possibilities of its practical implementation with Darly Solutions' experienced developers.

Medical imaging software development: Steps to follow

Custom development must follow clearly defined stages that most teams use. But, it can still be approached in various ways. Below, we outline how healthcare software development services are delivered in our company.

Concept formation 

Start your medical imaging software project with market analysis. Define the target audience, prioritize tasks the software should solve, and research competitors (to identify their strengths and weaknesses). Based on the insights, our medical imaging software development team assesses the functional requirements and evaluates the need for specific technologies to handle image processing. This ensures that the chosen solutions align with the project's technical needs and optimize the processing of healthcare-related images.

Planning

Once we agree on the conditions with all stakeholders, we will write a technical specification for your medical imaging software. This document will describe its functionality, interface, API, security, and integration requirements. We will also approve the tech stack and necessary integrations. Finally, we create a roadmap that defines the milestones and deliverables for each medical imaging software development project stage.

Prototyping

Now that everything is ready, we can begin creating user stories. They include handling DICOM file uploads and 3D models, among other key tasks. For UX/UI best practices of safe data, we follow the WCAG 2.1 guidelines. They ensure accessibility for users with varying technical skills. We also test prototypes with focus groups to see feedback on complex features, which is helpful for future design improvement. Finally, after the edits are done, we develop a full-fledged design.

Coding

The frontend has algorithms to process and analyze medical images. The backend ensures secure data transfer between the medical imaging software and storage. It also encrypts data and protects against vulnerabilities like SQL injections. These involve writing database queries for smooth software interactions and data storage interactions. And last but not least — we also integrate with your healthcare org's existing systems and services (if any).

Testing

Once the code for your medical imaging software is ready and all components have passed unit tests, we run complete test cases. We check for load, functional, non-functional, security, and usability issues.

Deployment

At this stage, we are choosing hosting for your medical imaging software (usually either cloud or local servers), setting up CI/CD, and training end users, for example, by providing them with documentation, training materials, or live courses. Once we've done it, we deploy the solution (first in the test environment and then — in the actual usage environment).

Support and updates

Finally, after the medical imaging software is deployed, we set up monitoring systems to track its performance and detect errors, fix post-release bugs, optimize it according to user feedback, and add new features if required.

Key tech specifications for medical imaging software development

Such software development can be complex, especially in its early stages. Basically, there is often no clear way to turn an abstract idea into actual requirements. 

So, let's examine all  the key tech specifications that are usually implemented in medical imaging software apps:

  • Support for common medical image formats such as DICOM (including DICOM tags for metadata) and standards for storing, transmitting, and processing medical images (such as C-STORE, C-FIND, and C-MOVE).
  • Compatibility with various devices (CT, MRI, ultrasound, etc.).
  • Image processing can improve images by adjusting contrast brightness and applying filters. It can also segment them to highlight organs and tissues. Lastly, it can register them to compare scans over time.
  • 2D and 3D visualization, including volume rendering (CT/MRI), support for iso-sections and reconstructions, and interactivity (e.g., rotation, zoom, and pan).
  • Data security, including HIPAA and GDPR compliance, support for TLS (for data transfer) and AES-256 (for image and metadata storage) encryption standards, as well as access control with role-based authorization and two-factor authentication.
  • PACS and EHR/EMR integration (e.g., via HL7/FHIR).
  • Annotation (adding labels, arrows, and text comments) and providing real-time collaboration tools.
  • PDF report generation and image export.
  • Scalability (including horizontal scaling via the cloud), multi-threading, and hardware acceleration.
  • WCAG 2.1 compliance and user interface customization.
  • Logging and monitoring events (including loading, processing, and exporting scans), auditing user access, tracking system performance, and setting up failure notifications.
  • Local deployment of software on physical servers (most likely, this will require ensuring compatibility with Linux and Windows OS).
  • Setting up regular data backups and automatic recovery after system failures.

Of course, this is just a basic list of specifications. In practice, your project team will expand and refine the list of features while specifying the tools and technologies for the project's unique needs.

Medical imaging software development cost

When it comes to the development cost of medical image analysis software it depends on its complexity and the technologies used. Without data and business needs — it's hard to define the precise price, but on average, basic DICOM (Digital Imaging and Communications in Medicine) typically ranges from $30K to $300K. A customized version of Basic DICOM may cost $30K to $50K. Advanced customizations could cost $70K to $150K.

Implementation costs differ based on the size of the practice:

  • Small practices typically cost $5K to $10K and take 1 to 2 weeks.
  • Medium facilities cost $20K to $50K and take 1 to 3 months.
  • Large enterprises may cost $100K to $200K and take 3 to 6 months.

Please complete this form to calculate the precise budget for your medical imaging software development idea. We will contact you shortly.

Challenges in medical imaging software development

Let's examine the main challenges encountered when developing medical imaging software.

  • Regulatory compliance.
    Software handling sensitive data, like patient information, must comply with HIPAA, GDPR, FDA 21 CFR Part 11, and CE Marking regulations. Key security measures include code audits, RBAC, 2FA, and strong encryption (e.g., AES-256, TLS).
    To avoid fines, consult a local lawyer on medical standards.
  • Integration with existing systems.
    Integrating PACS, EHRs, and other systems requires DICOM, HL7, and FHIR support. Also, medical organizations have very different established IT infrastructures, which makes it hard to unify their software. If you create a universal solution, you must provide some middleware. It will help users adapt to various services and systems.
  • High performance and scalability.

Medical images, especially CT and MRI, are large. This can slow their processing and increase resource needs.
In this regard, you may need to implement lossless compression mechanisms for images and multithreading and parallel data processing algorithms. By the way, a common fix is to move your software to a cloud solution designed for healthcare businesses.

  • The complexity of big data management.

Storing and processing massive data, like images and metadata, require a careful choice of databases and storage. In particular, this implies a preference for distributed databases and object storage.
For even greater reliability, do not forget to provide backup and auto-recovery.

  • Risks associated with cyber attacks.

Cyber attacks that leak medical data are a serious problem for healthcare software. To solve it, you must implement constant monitoring. Also, set up regular security updates, including patches and OS updates.
Finally, train your staff on social engineering. It can reduce the risks of phishing attacks.
Providing a user-friendly interface.
Interfaces for doctors and medical personnel should be user-friendly and intuitive, requiring minimal technical training to operate efficiently. To achieve this goal, you must test hi-fi prototypes on the real target audience and perform subsequent optimizations. Also, do not forget to ensure your interface is created under the WCAG 2.1 guidelines.

The future of medical imaging software

Medical imaging software development will advance by adopting the newest technologies, process optimization, and increased integration with other medical systems. 

So, here are the core areas in which medical imaging software can be optimized:

  • Speeding up diagnostic.
  • Increasing image recognition accuracy.
  • Costs reduction.
  • Improving user experience.

This can be achieved through the implementation and development of the following technologies:

  • Artificial intelligence and machine learning.

For highly accurate and automatic analysis of medical images and accelerated diagnostics.

  • Cloud computing.

To provide quick access to medical images from anywhere in the world, process large amounts of data without the need to upgrade local infrastructure, and implement remote collaboration between healthcare specialists.

  • VR/AR.

Medical imaging software development allows anatomy and pathologies to be studied using interactive 3D models and visualize the patient's anatomy before surgery.

  • Quantum computing.

While most quantum computers are not yet available for widespread use, they will speed up processing large datasets and training neural networks for image recognition in a few years.

  • Blockchain.

To guarantee the immutability and protection of data from medical imaging software while providing patients with comprehensive control over their medical information.

Our experience in medical imaging software development

This section covers the development of the PrismaORM brain scanner. This platform was crafted for chiropractors, neurologists, and neurosurgeons to monitor brain activity and brainwaves before, during, and after chiropractic treatments.

First, we assembled a team of eight experts to bring this vision to life. They worked closely with two external teams of medical imaging software engineers. We've pointed out a tech stack based on PostgreSQL, Typescript, React Native, Nest.js, Expo, Three.js, and SQLite. This tech of choice lets us build a platform that processes real-time data from brain activity helmets. The BLE protocol transmits this data. A tablet interface visualizes it. A key to the project's success was optimizing the user experience. This included better platform performance and integrating 3D models. 

As a result — we've made a powerful tool that empowers medical professionals to conduct more precise diagnostics and offer more effective treatment recommendations. 

For a detailed look at this project, visit our portfolio.

Wrapping up

Now that you understand the specifics of medical image analysis software development, you can begin searching for a team to bring your project to life. We are a reliable provider of custom healthtech solutions, ensuring a smooth, transparent, and predictable collaboration. Simply fill out the form, and we'll get in touch as soon as possible to discuss your medical imaging software project in detail.

Have a specific task?

Contact Darly Solutions experts today for a free consultation.

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Have a specific task?

Contact Darly Solutions experts today for a free consultation.

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FAQ

What technologies can help in developing medical imaging software?
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