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Implementation and evaluation of medical imaging techniques based on conformal geometric algebra

Franchini Silvia, Gentile Antonio, Vassallo Giorgio, Vitabile Salvatore

International Journal of Applied Mathematics and Computer Science

2020

Vol. 30, no. 3

415--433

Medical imaging tasks, such as segmentation, 3D modeling, and registration of medical images, involve complex geometric problems, usually solved by standard linear algebra and matrix calculations. In the last few decades, conformal geometric algebra (CGA) has emerged as a new approach to geometric computing that offers a simple and efficient representation of geometric objects and transformations. However, the practical use of CGA-based methods for big data image processing in medical imaging requires fast and efficient implementations of CGA operations to meet both real-time processing constraints and accuracy requirements. The purpose of this study is to present a novel implementation of CGA-based medical imaging techniques that makes them effective and practically usable. The paper exploits a new simplified formulation of CGA operators that allows significantly reduced execution times while maintaining the needed result precision. We have exploited this novel CGA formulation to re-design a suite of medical imaging automatic methods, including image segmentation, 3D reconstruction and registration. Experimental tests show that the re-formulated CGA-based methods lead to both higher precision results and reduced computation times, which makes them suitable for big data image processing applications. The segmentation algorithm provides the Dice index, sensitivity and specificity values of 98.14%, 98.05% and 97.73%, respectively, while the order of magnitude of the errors measured for the registration methods is 10-5.

Medical image registration in image guided surgery: Issues, challenges and research opportunities

Alam F., Rahman S. U., Ullah S., Gulati K.

Biocybernetics and Biomedical Engineering

2018

Vol. 38, no. 1

71--89

Multimodal images of a patient obtained at different time, pre-surgical planning, intra-procedural guidance and visualization, and post-procedural assessment are the core components of image-guided surgery (IGS). In IGS, the goal of registration is to integrate corresponding information in different images of the same organ into a common coordinate system. Registration is a fundamental task in IGS and its main purpose is to provide better visualization and navigation to the surgeons. In this paper, we describe the most popular types of medical image registration and evaluate their prominent state-of-the art issues and challenges in image-guided surgery. We have also presented the factors which affect the accuracy, reliability and efficiency of medical image registration methods. It is not possible to achieve highly successful IGS until all the issues and challenges in registration process are identified and subsequently solved.