Detecting aggressive papillary thyroid carcinoma using hyperspectral imaging and radiomic features

Leitch, Ka'Toria; Halicek, Martin; Shahedi, Maysam; Little, James V.; Chen, Amy Y.; Fei, Baowei

doi:10.1117/12.2611842

Cited by 1 publication

(1 citation statement)

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“…Hyperspectral imaging (HSI) is an imaging modality that has been widely used in remote-sensing applications but is growing in popularity for use in medical applications. One important upcoming use for HSI is in the field of digital pathology, as the extra spectral information provided can be useful for a variety of analysis tasks, such as cancer detection [8][9][10][11][12] . To fully investigate a histological slide for cancer detection, whole-slide imaging is commonly employed to acquire the digital histologic image of the entire slide.…”

Section: Introductionmentioning

confidence: 99%

Extended depth of field imaging for mosaic hyperspectral images

Rathgeb

Tran

et al. 2023

Medical Imaging 2023: Digital and Computational Pathology

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Hyperspectral imaging (HSI) is an emerging modality for digital pathology. The purpose of this study is to develop an extended depth of field (EDOF) method for mosaic hyperspectral images acquired with a snapshot camera. EDOF is a technique for ensuring that an image is in focus at all points. A stack of mosaicked hyperspectral images of hematoxylin and eosin (H&E)-stained histologic slides were acquired at different positions along the z-axis and used to output a hyperspectral histologic image that was in-focus at every point. Three different methods were compared to achieve a fully focused image. We compared conventional patch-based methods to our proposed growth-based and band-based methods. The Brenner function was used to quantitatively measure the focus quality of each image measured. The results show that both of our proposed methods performed better qualitatively and quantitatively than the patch-based method, with the band-based method performing the best, as it leveraged dividing pixels into their proper wavelengths in addition to spatially, giving the algorithm better contrast to measure. In terms of speed, the band-based method was the fastest, followed by the patch-based method, with the growth-based method being the slowest. Our proposed extended depth of field hyperspectral imaging methods can have immediate applications in digital pathology, especially whole slide imaging, and other microscopic imaging.

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