Lecture Medical image processing - Chapter 1 (Phần 2)

The field of "Medical Image Processing" is pivotal in modern healthcare, offering indispensable tools for non-invasive diagnosis, treatment planning, and monitoring of various diseases. Understanding the foundational principles of "Image Acquisition" is paramount for appreciating the capabilities and limitations of different diagnostic techniques. This document provides an essential overview of how medical images are generated, highlighting the physical, mathematical, and computational underpinnings. It explores key "imaging modalities" from conventional radiography to advanced tomographic methods, emphasizing their unique characteristics and the fundamental concepts that govern their operation. This foundational knowledge is crucial for anyone involved in developing, interpreting, or utilizing medical imaging technologies.

Sinh viên, nghiên cứu sinh, kỹ sư y sinh, và chuyên gia y tế quan tâm đến nguyên lý và kỹ thuật xử lý ảnh y tế và các phương thức chẩn đoán hình ảnh.

This academic draft provides a comprehensive overview of "Medical Image Processing", primarily focusing on the principles and evolution of "Image Acquisition" techniques. The document elucidates how localization information regarding tissue properties and cellular composition is acquired through various physical, mathematical, and computational principles. It introduces a spectrum of "imaging modalities", including Conventional X-ray Radiography, Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Nuclear Medicine, Ultrasound, Biomagnetism, and Microscopic Imaging. A detailed discussion on "Conventional X-ray Radiography" outlines the interaction of X-rays with the body, their absorption, diffraction, and detection, while also addressing its inherent limitation due to image superimposition. Subsequently, the text transitions to "Computed Tomography (CT)", presenting it as a significant advancement that mitigates superimposition by employing scanning perpendicular to the body axis and leveraging sophisticated "image reconstruction" algorithms, such as Fourier, Radon, and back-projection transforms. Furthermore, the document highlights critical "Image Characteristics" that define image quality, including "spatial resolution", "contrast resolution", time resolution, and repetitive time, which are vital for system evaluation. The evolution of CT technology is also explored through its different generations, illustrating how these systems have progressed to enhance diagnostic capabilities. This exploration underscores the importance of these technologies in providing detailed anatomical and functional insights, thereby advancing clinical diagnostics and patient care.