November 2024
The global AI in ultrasound imaging market is estimated to grow from USD 881.2 million in 2022 to reach an estimated USD 2,001.51 million by 2032, growing at a CAGR of 8.6% between 2023 and 2032, as a result of the increasing prevalence of several chronic and lifestyle disorders.
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The Impact of Advanced 3D and Real-time 4D on Surgical Precision and Fetal Health, due to these Transformative Technologies Sets a New Benchmark in Healthcare Innovation and Driving Demand for Enhanced Imaging Solution Worldwide.
Diagnostic ultrasound is non-invasive imaging technique using transducer that emit high-frequency sound waves that frequency above the threshold of human earing. most of diagnostic probe is to be place in the skin, they can also be inserted in the internally through Gastrointestinal tract, Vagina, or Blood Vessels for the better image quality. In surgery sterile probe can used. Artificial Intelligence in Ultrasound Imaging potentially elevate the use of medical Ultrasound Imaging with broad uses in clinical setting. the main application of Artificial Intelligence in Ultrasound Imaging is to Assist Physician for the diagnosis and triage the patient.
Ultrasound (US), a Flexible Green Imaging Modality, is expanding Globally as 1st line Imaging technique in clinical field following with High performing Ultrasound-AI.
Components of AI-based Ultrasound Imaging System:
The global market for Artificial Intelligence in Imaging has witnessed a significant growth in recent years. AI technologies are increasingly integrated into ultrasound system to enhance image quality, diagnostic accuracy, and workflow efficiency. These advancements aim to assist healthcare professionals in interpreting ultrasound scan, detecting abnormalities, and improving overall patient care. The integration of AI Algorithms holds promise for faster and more precise diagnostic, contributing to the expansion of the ultrasound imaging market on a global scale.
For Instance,
Cardiovascular diseases and digestive disorders are on the rise globally. According to WHO, Heart Attack and Stroke account for 85% of Worldwide deaths. In 2021, cardiovascular diseases resulted in 17.9 million deaths annually, and Digestive disorders contributed to 375,170 deaths, with a crude rate of 37.2 deaths per 100,000 population. Because of this prevalence, diseases necessitate faster and more accurate diagnostic procedures. Due to the global prevalence rate of diseases, Hospitals and Clinics are facing an increasing need for advanced Artificial Intelligence Ultrasound Imaging to cope with rising diseases.
AI-ultrasound imaging is crucial medical equipment for early detection; it facilitates faster and more efficient diagnosis. The demand for AI in Ultrasound Imaging is growing to meet escalating requirements for improved medical imaging solutions—early detection through AI-enhanced ultrasound Imaging in Timely and effective medical intervention. AI in ultrasound imaging works as an intelligent helper for doctors; it helps them find problems faster, especially in cardiovascular diseases, digestive disorders, and obstructive and gynaecology. Due to this, the demand for AI in Ultrasound imaging is increasing. It's not about just finding the problems. It's about treating the issue sooner, which is very important for dealing with Global prevalence.
AI applications in ultrasound have revolutionized medical imaging, providing navigation and automated quantification tools for analyzing diverse areas such as the breast, prostate, liver, heart, and obstetric/gynaecological domains. In obstetrics, AI facilitates workload management by automatically detecting standard planes, ensuring quality assurance in fetal ultrasound. Moreover, it aids in gynaecological assessments by automatically detecting endometrial thickness and classifying ovarian cysts. AI contributes to precise cardiac evaluations, vessel characterization, liver imaging, and pathology detection in cardiovascular and gastroenterology ultrasound. This technology enhances diagnostic capabilities and drives the global AI Ultrasound Imaging market's growth, offering advanced solutions for pregnancy monitoring and expanding its reach across diverse medical fields.
Ultrasonography stands out for its convenience, low cost, real-time capabilities, and non-invasive nature, making it the most widely used imaging modality. Antenatal ultrasound (US) examinations play a pivotal role in assessing fetal growth and detecting birth defects, enabling timely and effective interventions. The potential for reducing severe birth defects through the timely termination of pregnancies with poor prognoses underscores the significance of this process.
Research in radiology with AI has flourished with a particular focus on AI-assisted diagnosis in the field of ultrasound. Noteworthy successes have been achieved in the intelligent diagnosis of liver, thyroid, and breast diseases. Despite these breakthroughs in measurement, imaging, and diagnosis, the application of AI in prenatal ultrasound diagnosis remains in its early stages. The integration of AI in prenatal ultrasound not only enhances efficiency but also addresses the inexperience and skill gaps among examiners. This is particularly crucial given the time-sensitive nature of antenatal care. Importantly, as the global market for ultrasound technology expands, driven by advancements in AI applications, the reach and impact of these technologies are poised to play a pivotal role in shaping the future of prenatal diagnostics. In this review, we delve into recent literature on the application of AI in prenatal ultrasound diagnosis, recognizing its evolving role in the broader landscape of healthcare.
| AI Application | Description | Clinical Utility |
| Fetal Biometric Plane Finder | Standard fetal biometric planes are automatically acquired, measured and stored | Reduce repetitive caliper adjustment clicks; reduce operator bias; instant quality control |
| Probe Guidance | Operator is guided how to manipulate probe to acquire fetal biometric plane | Facilitate sonographer training; basic scanning can be performed by non-expert (e.g. general practitioner) |
| Anomaly Highlighting | Unusual fetal findings are identified in a standard plane | Highlight suspected abnormal finding; assist sonographer with referral decision Improve consistency; reduce likelihood of error |
| Anomaly Scan Completeness | Anomaly scan checklist of mandatory planes is populated automatically | Ensure completeness of imaging and that all parts of anatomy are checked |
| Lung Scans for Ob/Gyn | Ob/Gyn experts are taught how to perform lung ultrasound in patients with COVID19 | Reduce learning curve |
The ability of a computer program to carry out tasks related to cognitive abilities, such as reasoning, learning, modification, sensory understanding, and interaction, is known as artificial intelligence, or AI.is a well-known innovator in the medical field that has already contributed to the development of new medications, the support of clinical judgments, and the provision of ultrasound imaging quality assurance. Applications of artificial intelligence (AI) in ultrasound imaging have been approved by the European Union and the USA the Food and Drug Administration (FDA). Imaging is expanding quickly and meets a wide range of clinical needs, including elevating critical imaging studies to the top of radiologist workloads.AI developers and ultrasound specialists must communicate interdisciplinary even though Obstetrics and and Gynecological Ultrasounds are two of the most often performed imaging studies.
For Instance,
In the field of artificial intelligence healthcare, in which sensitive data analysis is shared, patient privacy is of utmost importance. The maintenance of patient confidence in strong security measures for this data. Significant risks exist from unauthorized access or hacking, which could violate personal privacy and risk the confidentiality of health records.Another crucial component is data security, particularly when it comes to the transfer and storage of medical data using AI applications. Strong security measures are necessary to handle worries about possible hacking, illegal access, and data breaches. Such safety breaches can have severe repercussions for both people and healthcare organizations. As AI systems advance, informed agreement becomes a complicated problem. If patients are given more information regarding how their data will be used, they may become comfortable with the application of AI in their healthcare. The ever-evolving nature of artificial intelligence diagnoses and treatments makes obtaining informed consent more difficult, as patients might need help understanding the implications.
Additionally, the interpretability and accountability of specific AI algorithms are challenged by their "black box" nature. Accountability is a concern when decisions are difficult to understand, mainly when AI systems make mistakes or have unfavourable effects. Understanding and transparent AI systems are essential to gaining users' trust. This results in lower adoption rates as regulatory agencies and Healthcare organizations may adopt a more measured approach and carry out an in-depth analysis of the ethical consequences of AI Solutions.
2D, 3D, and 4D ultrasound imaging uses sound waves to produce real-time images of the body's internal structures. Artificial Intelligence (AI) in ultrasound imaging improves image analysis, which allows automated measurements for improved workflows and increases diagnostic accuracy. A two-dimensional depiction of the body slice, it is possible to create 3D images by gathering several neighbouring 2D images. A specialized probe is typically used to mechanically scan a standard 2D image transducer. However, the slow mechanical scanning makes creating 3D images of moving tissues challenging. 2D phased array transducers with 3D beam sweeping capabilities have recently been developed. These can create 3D pictures of hearts beating in real-time and can image more quickly. AI algorithms assist in image interpretation, enabling faster and more accurate diagnoses, which drives market growth.
The non-invasive method, extracorporeal shockwave lithotripsy (ESWL), breaks down uric acid stones using shockwaves. Artificial intelligence (AI) helps with Kidney stones detection, treatment planning, and monitoring, which enhances overall efficacy and patient outcomes. Doppler Ultrasound It evaluates the Doppler shift, the difference between the transmitted and received frequency, to determine how much blood is moving through vessels. Doppler sonography is helpful in the medical field. Doppler measurements can improve sonography, which uses the Doppler effect to determine whether structures, typically blood, are moving toward or away from the probe and their velocity. For example, the speed and direction of a jet of blood flow over a heart valve can be visualized by calculating the frequency shift of that sample volume. It is crucial in many areas, such as determining how portal hypertension causes reverse blood flow in the liver vessels. It is beneficial in cardiovascular studies (sonography of the heart and vasculature system enhances Doppler ultrasound by providing more accurate blood flow analysis, aiding in diagnosing vascular conditions.
Continuous advancements in AI algorithms enhance the overall performance of ultrasound systems, attracting investments and fuelling market expansion.
North America has dominated the industry with a market share of more than 29.75% in 2023. Critical drivers of regional market growth include a sizable number of competitors and an increase in cancer cases. Growing healthcare spending, improved knowledge of different diagnosis techniques, and advantageous reimbursement policies are expected to fuel regional market expansion. AI is being used in ultrasound imaging due to the region's concentration of top pharmaceutical and biotechnology companies and growing investments in the medical field's adoption of cutting-edge new technologies. Patients' need for ultrasound imaging has increased as a result of rising healthcare costs and the prevalence of numerous chronic diseases. North America currently holds a dominant position in the global AI ultrasound imaging market due to the availability of sophisticated healthcare facilities and easier access. The adoption of the newest software and medical devices, along with a rise in spending on research and development, is driving the growth of North American AI in the ultrasound imaging market.
Because of the availability of inexpensive production factors, Asia Pacific is one of the most prominent manufacturers of ultrasound imaging gadgets at low costs. Artificial Intelligence (AI) in ultrasound imaging systems is expanding due to the increasing incidence of different diseases and the growing need for precise diagnosis results. The need for an ultrasound for imaging in obstetrics and gynaecology applications has grown as a result of women's changing lifestyles and late marriages, which are contributing to an increase in pregnancy complications. Throughout the forecast period, the growing government investments in the construction of intelligent hospitals are anticipated to propel the growth of the Asia Pacific AI ultrasound imaging market.
Advancements in Innovation and technology are transforming the landscape of AI in Ultrasound Imaging due to the advancement that fosters increased competition. As the competition intensifies, organizations strive to adopt AI solutions to stay competitive, offering innovative solutions ranging from diagnostic tools to personalized medicine and data analytics. This development led to more precise diagnostics, improved imaging quality and enhanced patient care in the medical field. This trend is expected to shape the future of healthcare by revolutionizing patient outcomes and healthcare delivery.
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November 2024
November 2024
November 2024
November 2024
Deepa has certified the degree of Master’s in Pharmacy in the Pharmaceutical Quality Assurance department from Dr D.Y. Patil College of Pharmacy. Her research is focused on the healthcare industry. She is the author or co-author of four Review Articles, which include Solid dispersion a strategic method for poorly soluble drugs and solubility improvement techniques for poorly soluble drugs, Herbal Drugs Used In Treatment Of Cataracts, Nano sponges And Their Application in Cancer Prevention and Ayurvedic Remedies of Peptic ulcer. She has also published a Research Article on the Formulation and Evaluation of Mucoadhesive Tablets of Miconazole cocrystal which was published in GIS Science Journal Volume 9 Issue 8. Her passion for secondary research and desire to take on the challenge of solving unresolved issues is making her flourish is the in the research sector.
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