Medical hyperspectral imaging: a review

Abstract

Hyperspectral imaging (HSI) is an emerging imaging modality for medical applications, especially in disease diagnosis and image-guided surgery. HSI acquires a three-dimensional dataset called hypercube, with two spatial dimensions and one spectral dimension. Spatially resolved spectral imaging obtained by HSI provides diagnostic information about the tissue physiology, morphology, and composition. This review paper presents an overview of the literature on medical hyperspectral imaging technology and its applications. The aim of the survey is threefold: an introduction for those new to the field, an overview for those working in the field, and a reference for those searching for literature on a specific application.

Figures

Fig. 1

Comparison between hypercube and RGB image. Hypercube is three-dimensional dataset of a two-dimensional image on each wavelength. The lower left is the reflectance curve (spectral signature) of a pixel in the image. RGB color image only has three image bands on red, green, and blue wavelengths respectively. The lower right is the intensity curve of a pixel in the RGB image.

Fig. 2

Schematic diagram of a pushbroom hyperspectral imaging system.

Fig. 3

A gray-scale image of a melanoma lesion showing the transmission spectra in the nuclear and interstitial areas.

Fig. 4

Spatial oxygen saturation maps. (a) Oxygen saturation map of 29-year-old healthy male. Vascular separation from the background is seen as well as reasonable saturation values for veins versus arteries. (b) Zero-order color image. (c) Oxygen saturation map of 58-year-old healthy male. (d) Zero-order color images.

Fig. 5

(a) Cross-section diagram of tissue sample for angular-domain spectroscopic imaging testing. (b) Color photographs of mouse tumor tissue sandwiched between two glass slides. The opening due to the black mask that was used for transmission imaging is marked by the yellow dashed line. The black line (left panel) indicates the location of bone embedded in the tissue. (c) Normalized spectra from regions of tumor and muscle tissue [as indicated in (b)]. (d) Correlation map of data cube based on reference spectral signature related to the muscle tissue. (e) Correlation map of data cube based on reference spectral signature related to the tumor tissue.

Fig. 6

(a) Photomicroscopic and corresponding medical hyperspectral imaging image from breast tumor in situ (4×3  cm) (upper left and upper middle panels). Resected tumor and surrounding tissue (5×7  mm) was stained with hematoxylin and eosin and evaluated by histopathology after resection. Microscopic histological images with further resolution are displayed (right panels). (b) Representative examples of normal tissue (grade 0), benign tumor (grade 1), intraductal carcinomas (grade 2), papillary and cribriform carcinoma (grade 3), and carcinoma with invasion (grade 4) are represented.

Fig. 7

(a) Photographic image of the biliary tissue structure. (b) Classification of the biliary tissue types based on hyperspectral imaging, superimposed with the fluorescence image of the encapsulate indocyanine green-loaded microballoons. The dual-mode image clearly identifies the biliary anatomy and its relative location with respect to the surrounding tissue components.

Fig. 8

The RGB image is shown on the left side. Using the method described, the segmented image can be viewed on the right side. Spleen is shown in red, peritoneum in pink, urinary bladder in blue, colon in green, and small intestine in yellow.