As per our research Report, the AI in Molecular Imaging Market is forecasted to be growing at a CAGR of 34.8% from 2024 to 2030.
Molecular Imaging (MI) is a field of biomedical research that is developing rapidly. It facilitates the visualization, characterization, and quantification of biological processes happening within living organisms, involving humans, at a cellular and subcellular level. MI images demonstrate how diseases function within the body. Analysing these biological processes within their natural environment is made possible by MI, which goes beyond the restrictions of traditional laboratory techniques that depend on biopsies or cell cultures. MI involves combining multiple imaging techniques with knowledge from various fields, including cell and molecular biology, chemistry, pharmacology, medical physics, biomathematics, and bioinformatics.
Adapting artificial intelligence (AI) in molecular imaging systems provides numerous advantages. Powerful AI algorithms can be used in molecular imaging systems, which can assist in offering clinically relevant and actionable information that is quantitative, accurate, reproducible, and aimed at outcomes, enabling doctors to make informed clinical decisions. These systems aid healthcare professionals in giving personalized treatment plans based on a patient's unique genetic and molecular profile. AI algorithms may update standardization by streamlining processes and lowering the need for manual intervention, leading to more automated and less dependent actions. In addition, these AI-powered systems provide high-quality images with lesser noise and artifacts by using the technology of deep learning. As a result of these benefits, the global AI in molecular imaging market is estimated to have the fastest CAGR during the forecast period.
The incidence of chronic illnesses, including cardiovascular diseases, neurological disorders, cancer, chronic respiratory diseases, diabetes, etc., is growing at a fast rate due to aging populations and unhealthy lifestyles. These illnesses are key public healthcare concerns worldwide. AI-based molecular imaging systems play a pivotal role in detecting these diseases at early stages with high accuracy. These systems can provide information that is unattainable with other imaging systems. The extent or severity of the disease, as well as whether it has spread elsewhere in the body, can be figured out by AI-based molecular imaging systems. Moreover, AI-based molecular imaging systems are non-invasive, painless, and safe. Therefore, this factor pushes the demand for AI-based molecular imaging systems.
As molecular imaging techniques continue to advance, they create considerable amounts of complex imaging data. AI algorithms make it happen to analyse complex imaging data with greater accuracy and efficiency. AI-based imaging solutions can analyse this complex imaging data more efficiently and precisely in contrast to other medical imaging techniques by providing faster and more accurate diagnosis and treatment planning. Additionally, AI algorithms can assist in identifying patterns and relationships in the data that might be tough or impossible to detect manually, leading to new insights and discoveries in disease mechanisms and treatment approaches. Hence, this factor also drives the demand for AI-based molecular imaging systems.
The global AI in molecular imaging market is facing challenges, primarily in terms of the high cost of integrating AI in molecular imaging systems and the hesitance among medical practitioners to deploy AI-based technologies. Healthcare options may face issues in the installation of AI-based molecular imaging solutions due to the high costs of hardware, software, and training. This factor may limit small and medium-sized healthcare facilities from integrating AI into molecular imaging systems. Furthermore, some healthcare practitioners appear reluctant to adopt new technologies. Since empathy and persuasion are human emotions, doctors and radiologists believe that technology cannot completely ignore the presence of a doctor. There is also an issue that patients may show an excessive preference for these technologies and may disregard necessary in-person treatments, posing a threat to long-term relationships between doctors and patients. Thus, these challenges affect the growth of global AI in the molecular imaging market.
Market strengthening strategies present lucrative opportunities in the global AI in the molecular imaging market. Given the growing demand for AI-powered molecular imaging solutions due to the rising incidence of chronic diseases and the growing technological updates in molecular imaging techniques, key companies specializing in developing AI-based molecular imaging solutions can stand to gain majorly from this opportunity by expanding their services in countries that lack sound healthcare infrastructure, to broaden their customer base and push their overall revenue.
Key Market Insights:
In 2023, the deep learning segment held the biggest share of around 58.6%, due to its wide-scale application in the radiology department object detection, image generation, image transformation, and image segmentation. The NLP segment is expected to grow at the quickest rate during the forecast period. The growth can be dedicated to the increased use of NLP in the fields of machine learning (ML) and artificial intelligence (AI).
In 2023, the software segment held the biggest market share. The growth can be dedicated to the rising demand for advanced technologies, such as artificial intelligence (AI), in molecular imaging systems, which can help healthcare professionals in providing fast and accurate detection of diseases. Software solutions are attractive to end users as they are easy to integrate into current molecular imaging systems, which makes it an affordable substitute in contrast to installing a newly AI-powered molecular imaging system.
Based on the application, the global AI in the molecular imaging market is fragmented into cardiology, neurology, oncology, and others. In 2023, the oncology segment held the dominant market share. The growth can be dedicated to the growing incidence of cancer, increasing awareness among patients toward cancer screening, and the rising number of global funding for cancer research activities. AI-based molecular imaging systems help in providing fast and accurate diagnosis of cancer and its cure planning. Patients' outcomes tend to update as a result of these systems' capacity to provide a more personalized and targeted approach to cancer treatment.
In 2023, the hospital segment held the biggest market share. The growth can be dedicated to increasing patient load owing to chronic diseases, such as cardiovascular diseases, cancer, neurological disorders, etc. Hospitals are well-devised with the necessary infrastructure and resources for conducting complex screening and diagnostic tests and treatment planning.
Deep Learning
Natural Language Processing
Others
Hardware
Software
Services
Cardiology
Neurology
Oncology
Others
Hospitals
Molecular Diagnostic Laboratories
Ambulatory Surgical Centres
Medical Clinics
North America
Europe
Asia-Pacific
South America
Middle East and Africa
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