Integrating Biomedical Image Processing and Informatics for Healthcare

In today’s fast-paced and ever-changing world of 21stcentury healthcare, the blend of technology, data, and medicine is reshaping how we think about diagnosis, treatment, and patient care. At the heart of this change is the smooth integration of biomedical imaging, informatics, and artificial intelligence (AI)—a combination that’s not just improving clinical decision- making but also pushing us toward a more predictive, personalized, and preventive approach to healthcare. This new book, Integrating Biomedical Imaging and Informatics for AI-Driven Healthcare, showcases the latest advancements across the key areas of artificial intelligence in healthcare, data acquisition and processing, and emerging technologies such as the digital twin.

The volume first offers a comprehensive yet detailed overview of how AI is being applied in healthcare, delving into the roles of machine learning, deep learning, and federated learning in helping machines with clinical diagnostics, pattern recognition, patient monitoring, and decision support systems. It covers topics on continuous patient monitoring, smart imaging, and algorithm-driven diagnostics to showcase how computational power is enhancing and supporting medical expertise.

The roles of data acquisition and processing in healthcare are considered as well, looking at the various innovations in gathering, processing, and analyzing intricate biomedical datasets. It explores topics from cardiotocography used for monitoring fetuses to the fascinating world of transfer learning for detecting pneumonia through chest X-rays. The chapters showcase real-world applications of image processing and advanced computing techniques. The book also takes a closer look at cutting-edge technologies like generative adversarial networks (GANs), offering readers a glimpse into how synthetic data generation and image enhancement are helping to fill the gaps in data availability and improve diagnostic accuracy.

Digital twins and emerging technologies in healthcare is also introduced along with the applications across various healthcare settings. By harnessing real-time data from wearables, IoT devices, and imaging systems, digital twins hold incredible promise for tailoring treatment plans, monitoring health in real-time, and enabling proactive healthcare interventions. The book also highlights complementary technologies like nanotechnology-driven blood flow simulations, AI-enhanced athletic performance training, and IoT-integrated hospital systems, showcasing a range of futuristic, holistic approaches to healthcare.

What ties together all the contributions in this volume is a common vision for patient-centered, data-driven healthcare. In a world thats increasingly influenced by digital ecosystems, healthcare needs to shift from being reactive to becoming proactive and continuous—where diagnostics, monitoring, and interventions are guided by solid data, smart algorithms, and systems that work well together. The technologies and methods discussed here showcase this transformation, where machines enhance human care, and virtual simulations shape real-world outcomes.