Singh Rahul Kumar, Nayak Nirlipta Priyadarshini, Behl Tapan, Arora Rashmi, Anwer Md Khalid, Gulati Monica, Bungau Simona Gabriela, Brisc Mihaela Cristina
Energy Cluster, University of Petroleum and Energy Studies, Dehradun 248007, Uttarakhand, India.
Amity School of Pharmaceutical Sciences, Amity University, Mohali 140306, Punjab, India.
Diagnostics (Basel). 2024 Jan 8;14(2):0. doi: 10.3390/diagnostics14020139.
To develop diagnostic imaging approaches, this paper emphasizes the transformational potential of merging geophysics with health sciences. Diagnostic imaging technology improvements have transformed the health sciences by enabling earlier and more precise disease identification, individualized therapy, and improved patient care. This review article examines the connection between geophysics and diagnostic imaging in the field of health sciences. Geophysics, which is typically used to explore Earth's subsurface, has provided new uses of its methodology in the medical field, providing innovative solutions to pressing medical problems. The article examines the different geophysical techniques like electrical imaging, seismic imaging, and geophysics and their corresponding imaging techniques used in health sciences like tomography, magnetic resonance imaging, ultrasound imaging, etc. The examination includes the description, similarities, differences, and challenges associated with these techniques and how modified geophysical techniques can be used in imaging methods in health sciences. Examining the progression of each method from geophysics to medical imaging and its contributions to illness diagnosis, treatment planning, and monitoring are highlighted. Also, the utilization of geophysical data analysis techniques like signal processing and inversion techniques in image processing in health sciences has been briefly explained, along with different mathematical and computational tools in geophysics and how they can be implemented for image processing in health sciences. The key findings include the development of machine learning and artificial intelligence in geophysics-driven medical imaging, demonstrating the revolutionary effects of data-driven methods on precision, speed, and predictive modeling.
为了开发诊断成像方法，本文强调了将地球物理学与健康科学相结合的变革潜力。诊断成像技术的进步通过实现更早、更精确的疾病识别、个性化治疗以及改善患者护理，改变了健康科学。这篇综述文章探讨了健康科学领域中地球物理学与诊断成像之间的联系。地球物理学通常用于勘探地球的地下结构，其方法在医学领域有了新的应用，为紧迫的医学问题提供了创新解决方案。文章研究了不同的地球物理技术，如电成像、地震成像等，以及它们在健康科学中对应的成像技术，如断层扫描、磁共振成像、超声成像等。研究内容包括这些技术的描述、异同点、挑战，以及改进后的地球物理技术如何应用于健康科学中的成像方法。重点介绍了从地球物理学到医学成像的每种方法的发展历程及其对疾病诊断、治疗规划和监测的贡献。此外，还简要解释了地球物理数据分析技术，如信号处理和反演技术在健康科学图像处理中的应用，以及地球物理学中的不同数学和计算工具，以及它们如何应用于健康科学的图像处理。主要发现包括地球物理学驱动的医学成像中机器学习和人工智能的发展，证明了数据驱动方法对精度、速度和预测建模的革命性影响。
