Recent Development of Medical Shape Analysis via Computational Quasi-conformal Geometry

Hei-Long Chan () and Lok-Ming Lui ()
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Hei-Long Chan: Chinese University of Hong Kong
Lok-Ming Lui: Chinese University of Hong Kong

Chapter 41 in Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging, 2023, pp 1413-1436 from Springer

Abstract: Abstract Medical analysis is closely related to mathematics in many aspects. Over the past decades, mathematicians have designed numerous mathematical models and algorithms to aid medical researches. However, the space for joint-forcing mathematics with the medical industry is very limited in early years due to immature implementation and technological support. Those models are mostly limited to simple applications of the probability and statistics theory. It is until recent years when computational geometry comes into appliance, and it opens up a huge room for the incorporation of mathematics with medical analysis. For instance, medical imaging, geometric modeling for medical surfaces, and machine learning for disease classification are crucial topics nowadays having heavy reliance on image processing and geometric analysis. There are many streams in applying the study of geometry. Among those, the application of the quasi-conformal Teichmüller theory has shown to be very successful in recent years. This article serves to conclude some most updated models having solid contributions to the medical science in different aspects.

Keywords: Shape analysis; Quasi-conformal geometry; Computational geometry; Medical imaging; Disease classification (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-98661-2_70

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DOI: 10.1007/978-3-030-98661-2_70

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