The pulmonary (or respiratory) system is responsible for gas exchange between the external environment and the circulating blood supply in the body. The respiratory system contains a complex network of approximately 23 generations of branching arteries, veins, and airways that terminate in more than 280 billion capillaries and 300 million air sacs (alveoli). Rib cage and diaphragm muscles draw air into the lungs and then release air back to the atmosphere. The process of gas exchange is called ventilation, while the delivery of the blood supply to the lung capillary beds for gas exchange is termed perfusion. For effective gas exchange, there must be an approximate match between the regional ventilation and regional perfusion.
Disease processes (e.g., cancer, emphysema, fibrosis, bronchitis, pneumonia, asthma, cystic fibrosis, etc.) disrupt normal gas exchange by, for instance, altering the elastic properties of the lung tissue, blocking airways or blood vessels, changing the diffusing capacity of gas exchange surfaces, modifying muscle function of the rib cage or diaphragm, or altering the central nervous system processes that govern respiration. Most disease processes are associated with slowly developing anatomical, physiological, and mechanical changes that evolve over time as tissues change their underlying material and physiologic properties. Furthermore, many of the pathologic features of lung disease only manifest themselves in the dynamic state of the system (such as airway collapse during active expiration). Imaging modalities can be used to evaluate and track disease processes by quantifying anatomical, mechanical, and functional properties. The challenge for pulmonary imaging is to obtain the spatial and temporal image resolution to capture early pathologic processes; the challenges for pulmonary image processing are to objectively and accurately quantitate the pathologic processes at early stages. From an engineering perspective, pulmonary imaging can be extremely demanding due to the complex, time-varying anatomy and the need to follow events dynamically and across time gaps that may be minutes, days, months, or years. This leads to a wealth of interesting image-processing challenges.
This chapter is organized as follows. We first briefly discuss the major components of the pulmonary anatomy and the important clinical applications. In Section 16.2 we consider the major image processing and image analysis tasks in pulmonary medicine. For the most part, Section 16.2 introduces the interesting image processing problems, surveys possible solution approaches, and when possible, shows representative results. Much of the low-level image processing implementation detail has been covered previously in earlier chapters and is not repeated here. In Section 16.3 we discuss several important applications of pulmonary imaging.
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