How to Develop High-Quality Medical Image Analysis Software
Every year, about a billion X-ray examinations are performed worldwide. A radiologist must review each image and manually prepare an examination report. X-ray results are not always interpreted correctly: NCBI mentions about 3-5% errors in screening interpretation. And this is approximately 30 million cases. Healthcare institutions can minimize errors in the processing of X-ray data by implementing medical image analysis software.
Medical Image Analysis Software: Definition
Medical image analysis software examines, analyzes, and interprets information obtained during X-ray examinations. Such a program scans data from images of computerized tomography (CT), echocardiography (ECG), and magnetic resonance imaging (MRI) and finds discrepancies with the norm.
Modern image analysis programs use machine learning, AI algorithms, and Big Data to perform the following operations:
- to accurately detect problem areas;
- identify possible pathologies that are not visible to the human eye;
- study hundreds of images per second, find anomalies, and prioritize patients according to the complexity of their diseases;
- make diagnoses;
- track the dynamics of treatment by comparing previous and recent images;
- help doctors share images to speed up treatment or reduce radiation exposure for patients.
Thus, a program for image analysis eliminates errors in the interpretation of radiological results and speeds up the work of doctors. It helps patients avoid unnecessary research and re-irradiation and detects diseases at an early stage (doctors cannot recognize these signs themselves). For clinics and hospitals, it means saving time and resources. It is also an efficient way to improve the quality of care.
Market Potential of Medical Image Analysis Software
The growing use of computer diagnostics has fueled interest in the development of medical image analysis software. In 2021, the software solutions market was estimated at $3.5 billion. By 2028, it is expected to reach $5.97 billion.
Markets and Markets research company states that cardiology will become the leader in the use of AI programs. Orthopedists, oncologists, urologists, gynecologists, dentists, nephrologists, and other specialists will also need special applications.
Hospitals are interested in developing healthcare mobile apps.
Healthcare mobile apps often conduct X-ray studies and these data are needed for surgical operations.
Benefits of Medical Image Analysis Software
Medical image analysis software is becoming an indispensable tool for clinicians because it:
- Gives accurate results. ML and AI algorithms are trained on thousands of images, acquiring impeccable accuracy in data analysis. Such a program works flawlessly unlike doctors, who can make mistakes due to fatigue or haste.
- Prevents the development of diseases. A program finds problems where the human eye does not see pathologies. A doctor takes predictions into account and prescribes preventive treatment before the disease progresses. Patients are more likely to recover soon.
- Speeds up diagnostics. An algorithm processes hundreds of images at the same time, without the fatigue and interruptions that a doctor needs for normal work.
- Allows specialists to easily import files. When X-ray images need to be linked to an electronic health record (EHR) and other sources (HIS, RIS), a system exports images in a compatible format so that doctors can use the data to treat patients, conduct research, or educate students.
- Provides a 3D view. Such a program can combine many 2D photographs to present an object from different angles. It is easier for radiologists to find pathologies using a three-dimensional model of an object.
Features Worth Implementing in Medical Image Analysis Software
Image analysis applications differ in functionality, but there are basic elements that are implemented in each system:
- Image management, the ability to archive, change the format, compress, and export files.
- Editing. It is more convenient for a doctor to analyze images and identify a problem area if they can edit an image (remove color distortion or adjust brightness/contrast).
- Segmentation. To see the pathology in an organ more clearly, doctors need the ability to segment images. For example, when it is necessary to separately study organs, tissues, bones, and blood vessels.
- Registering pictures. In the medical community, registration refers to the combination of data from several images. For example, when it is necessary to compare the results of old and new studies and identify changes.
- 3D reconstruction. A program can create a three-dimensional image by combining 2D images from different angles.
- Quantification. It is important to implement functionality for a description of study results (the characteristics of pathology or disease staging). Physicians must be able to record a description of an organ under examination (its shape, size, texture, and so on).
If a healthcare facility needs additional features, it can discuss them with the custom healthcare software development company that implements a project.
How to Develop Medical Image Analysis Software?
Developing medical imaging software follows the same pattern as building any healthcare application. You should take the following steps:
Conduct Market Research
If you want your application to be useful, try to understand the target audience. It is important to find out users’ problems and needs and implement such functionality that will help solve them. You should also analyze competitor applications, take note of good ideas and improve them in your product. You need to determine what will help your future software stand out in the market.
Consider Industry Legislation
Medical image analysis software stores personal images of patients, so it must protect data under HIPAA, GDPR, or other regulations. Legal issues should be taken into account before the start of the healthcare software development process.
Before starting development, you need to think over the main functions of the future software product. Plan a custom doctor path that will work with images and consult with healthcare professionals to determine what steps are missing and what should be considered in the application design. It is important to eliminate inaccuracies before they become a major problem.
Start Development with an MVP
To create an application with less expense and fewer errors, you can start development with a minimum viable product (MVP). This is the basic version of a program. It includes functionality that is critical for the operation of a system. Users begin to work with an MVP, and developers are finalizing it at the same time. New features are gradually added, and the “draft” turns into a full-fledged product that completely suits the target audience. As you use it, doctors will tell you what elements are missing in your medical image analysis software. The team will supplement the system with only relevant functions, without adding unnecessary features.
Medical image analysis software gives radiologists the accuracy and speed to interpret results without sacrificing quality. Such an application will simplify the work of physicians and bring benefits to your clinic if the healthcare software development process is properly organized. First of all, you should find a reliable IT partner, a company that has already implemented similar projects and knows the features of this type of software. The development team will implement the functionality necessary for radiologists, take into account the specifics of your organization’s work and comply with the requirements of industry legislation.