Multispectral Imaging Modalities Research Articles

High-Resolution Multi-Spectral Imaging With Diffractive Lenses and Learned Reconstruction

Spectral imaging is a fundamental diagnostic technique with widespread application. Conventional spectral imaging approaches have intrinsic limitations on spatial and spectral resolutions due to the physical components they rely on. To overcome these physical limitations, in this paper, we develop a novel multi-spectral imaging modality that enables higher spatial and spectral resolutions. In the developed computational imaging modality, we exploit a diffractive lens, such as a photon sieve, for both dispersing and focusing the optical field, and achieve measurement diversity by changing the focusing behavior of this lens. Because the focal length of a diffractive lens is wavelength-dependent, each measurement is a superposition of differently blurred spectral components. To reconstruct the individual spectral images from these superimposed and blurred measurements, model-based fast reconstruction algorithms are developed with deep and analytical priors using alternating minimization and unrolling. Finally, the effectiveness and performance of the developed technique is illustrated for an application in astrophysical imaging under various observation scenarios in the extreme ultraviolet (EUV) regime. The results demonstrate that the technique provides not only diffraction-limited high spatial resolution, as enabled by diffractive lenses, but also the capability of resolving close-by spectral sources that would not otherwise be possible with the existing techniques. This work enables high resolution multi-spectral imaging with low cost designs for a variety of applications and spectral regimes.

A Multimodal Biomicroscopic System based on High-frequency Acoustic Radiation Force Impulse and Multispectral Imaging Techniques for Tumor Characterization Ex vivo

We report a multimodal biomicroscopic system which offers high-frequency ultrasound B-mode, acoustic radiation force impulse (ARFI), and multispectral imaging for qualitative tumor characterization ex vivo. Examinations of resected tissues from diseased regions such as tumors are crucial procedures during surgical operations to treat cancer. Particularly, if tiny tumors remain at surgical sites after tumor resection, such tumors can result in unwanted outcomes, such as cancer recurrence or metastasis to other organs. To avoid this, accurate characterizations of tumors resected during surgery are necessary. To this end, we devised a multimodal biomicroscopic system including high-frequency ultrasound B-mode, ARFI, and multispectral imaging modalities to examine resected tumors with high levels of accuracy. This system was evaluated with tissue-mimicking phantoms with different mechanical properties. In addition, colorectal tumors excised from cancer patients were examined. The proposed system offers highly resolved anatomical, mechanical, chemical information pertaining to tumors, thus allowing the detection of tumor regions from the surface to deep inside tissues. These results therefore suggest that the multimodal biomicroscopic system has the potential to undertake qualitative characterizations of excised tumors ex vivo.

Fourier Spectral Filter Array for Optimal Multispectral Imaging.

Limitations to existing multispectral imaging modalities include speed, cost, range, spatial resolution, and application-specific system designs that lack versatility of the hyperspectral imaging modalities. In this paper, we propose a novel general-purpose single-shot passive multispectral imaging modality. Central to this design is a new type of spectral filter array (SFA) based not on the notion of spatially multiplexing narrowband filters, but instead aimed at enabling single-shot Fourier transform spectroscopy. We refer to this new SFA pattern as Fourier SFA, and we prove that this design solves the problem of optimally sampling the hyperspectral image data.