Medical Image Analysis Software
ScienceSoft brings 19 years in healthcare IT to deliver medical imaging apps backing up doctors’ experience with sophisticated algorithms.
Image analysis enables medical device manufacturers and researchers to minimize clinical errors, unneeded tests, misdiagnosis cases, and raise care quality.
Market Overview and Trends
In 2023, the international medical image analysis software market was estimated at $3.27 billion. It is forecasted to grow at a CAGR of 7.8% from 2024 to 2030. The need for robust and efficient medical imaging solutions is increasing due to:
- A growing number of people with chronic diseases. According to CDC, 6 in 10 US citizens live with one or more chronic diseases.
- Increasing consumer trust. According to research, 79% of respondents feel confident about an analytics-assisted radiology diagnosis.
- The need to speed up medical image analysis. The specialized solutions improve medical imaging staff productivity by 30%.
Driving Clinical and Research Benefits
We offer technological support to researchers, medical innovators and medical device manufacturers for tackling complex challenges in preventing, diagnosing and treating diseases. Enabling both manual and automated (via artificial neural networks) analysis of 3D medical images, you unlock the following opportunities to the benefit of providers and patients:
- Machine learning systems to facilitate early diagnostics for higher cure and survival rates;
- Neural networks for diagnosis validation;
- Research-specific algorithms to find hidden patterns and valuable insights to improve drug development as well as examination of complex conditions with adverse symptoms;
- Segmentation solutions to pinpoint a treatment area and thus minimize possible damage to healthy tissue during an invasive procedure;
- Applications integrating 3D imaging with virtual reality (VR) devices to enable immersive training of health specialists, patient education, and advanced diagnostics.
Medical Image Analysis Powered by Machine Learning
To aid in medical image analysis, machine learning algorithms process large amounts of medical data and identify complex patterns. ML is efficient for the following tasks:
- Disease diagnostics.
- Medical image segmentation.
- Tissue type identification.
- Health outcomes prediction.
Our Approach to Your Challenges
You strive to supply clinical stakeholders with unprecedented medical image analysis solutions that make diagnostics, treatment and research evolve. We believe that achieving these goals depends on reliability and proficiency of the partner you choose for the journey. Our approach to your needs always includes:
Communication with professionals in your language
Being on the same page is key to ensure the results you expect. Therefore, not only our solutions speak healthcare, but everyone who will contact you.
Technical experience that matches the clinical need
Our teams of technical specialists rule over math algorithms and do the job to deliver only a reliable solution. To create high-performing and cost-effective solutions for image processing in the medical field, we bring 35 years in C++ and R development on Linux, Windows and OS X. To support computing-intensive tasks, we also offer parallel computing and performance optimization. On top of that, we organize our workflows according to the ISO 13485:2016 and IEC 62304:2006 / Amd 1:2015 standards.
ScienceSoft In Brief
- Image analysis software development since 2013.
- Working in healthcare and mobile domains for 19 years.
- Quality management system for medical devices and SaMD backed by ISO 13485:2016 certification.
- Deep knowledge of healthcare data exchange standards (e.g., HL7, ICD-10, CPT, XDS/XDS-I).
- Guidance on regulatory compliance with HIPAA, GDPR, MDR, FDA, NCPDP D.0, and more.
- ScienceSoft's expertise in medical image analysis was acknowledged in 2022 market leaders researches by MarketsandMarkets and Coherent Market Insights.
- Health Tech Digital named ScienceSoft’s RPM solution the Best Healthcare Technology Solution Award 2022.
What makes ScienceSoft different
We achieve project success no matter what
ScienceSoft does not pass off mere project administration for project management, which, unfortunately, often happens on the market. We practice real project management, achieving project success for our clients no matter what.
Modalities We Are Proficient In
Depending on the type of diagnostics patient requires, medical staff can use various medical imaging devices: CT scanners, ultrasound machines, and others. ScienceSoft is experienced in creating analysis software for the following modalities:
- CT (computed tomography), e.g., chest or abdomen CT scans.
- MRI (magnetic resonance imaging), e.g., brain or cardiac MRI scans.
- PET (positron emission tomography) used for the assessment of cancers, neurological or cardiovascular diseases.
- SPECT (single-photon emission computed tomography) used to diagnose and monitor bone, neurological, and cardiac disorders.
- Ultrasound images used for disease prevention, diagnosing, and monitoring in various medical specialties.
- X-ray (radiography) scans, often used in injury care, dentistry, pulmonary care, and other medical specialties.
- Mammography for breast cancer prevention and monitoring.
- Other modalities.
Body Mapping
3D image analysis of particular body parts has certain specifics to it. We are ready to handle your needs in analyzing tissues, bones, muscles and organs in depth, including:
- Abdominal system (liver, spleen, kidneys, gallbladder, etc.)
- Genitourinary and endocrine systems (urinary bladder, prostate, reproductive organs, thyroid, etc.)
- Cardiovascular system
- Respiratory system
- Brain and spinal cord
- Mammary glands and more
Our Top Medical Image Analysis Projects
Technologies We Use
Image formats
We support a wide range of common standards and specialized extensions, including:
- DICOM
- Analyze
- MINC
- NIfTI
- ECAT7 and more
Methods
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We apply image quality improvement methods at the preprocessing stage to reduce noise, remove artefacts, compensate spatial aliasing and enhance contrast. With improved images, health specialists can ensure the right diagnosis and subsequent treatment, as well as enable automated image analysis further. |
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Segmentation allows us to separate a bone, tissue, vessel, organ or other analyzed structure from the surroundings. For example, to isolate brain tissue from the scull and peripheral tissue. |
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We leverage image fusion / registration methods either for images acquired in different modalities (e.g., CT and PET) or within one modality but in different timeframes. Fusion or registration allows monitoring a lesion's growth and form change, analyze nonlinear tissue deformations, help with interventional procedures and more. |
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Through quantification, we define already segmented structures on medical images with diagnostic information about their size, form, texture, morphology and specific aspects of dynamics in time. |