Abstract
Diffuse optical tomography using deep learning is an emerging technology that has found impressive medical diagnostic applications. However, creating an optical imaging system that uses visible and near-infrared (NIR) light is not straightforward due to photon absorption and multi-scattering by tissues. The high distortion levels caused due to these effects make the image reconstruction incredibly challenging. To overcome these challenges, various techniques have been proposed in the past, with varying success. One of the most successful techniques is the application of deep learning algorithms in diffuse optical tomography. This article discusses the current state-of-the-art diffuse optical tomography systems and comprehensively reviews the deep learning algorithms used in image reconstruction. This article attempts to provide researchers with the necessary background and tools to implement deep learning methods to solve diffuse optical tomography.
Highlights
Diffuse optical tomography (DOT) using near-infrared (NIR) light is rapidly emerging as a viable way to image through mammalian tissues
Recent studies have suggested that data processing, image segmentation, and image reconstruction are faster, more reliable, and more accurate when deep learning algorithms are used instead of conventional inverse problems [6,8,9,10,11,12,13,14]
We review the recent developments in diffuse optical tomography, and we provide a tutorial on the use of deep learning algorithms in diffuse optical tomography
Summary
Diffuse optical tomography (DOT) using near-infrared (NIR) light is rapidly emerging as a viable way to image through mammalian tissues. Recent studies have suggested that data processing, image segmentation, and image reconstruction are faster, more reliable, and more accurate when deep learning algorithms are used instead of conventional inverse problems [6,8,9,10,11,12,13,14]. Research in this field is snowballing as developing a robust, inexpensive, and noninvasive system is necessary for high-resolution imaging of mammalian tissues to detect any abnormalities present in them [10,15,16,17,18,19].
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