Miniature MOEMS hyperspectral imager with versatile analysis tools

Trops, Roberts; Hakola, Anna Maria; Jääskeläinen, Severi; Näsilä, Antti; Annala, Leevi; Eskelinen, Matti A.; Saari, Heikki; Pölönen, Ilkka; Rissanen, Anna

doi:10.1117/12.2506366

Cited by 5 publications

(8 citation statements)

References 4 publications

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“…The imager is connected to a computer via Cube View software [ 24 ] (University of Jyväskylä, Spectral Imaging Laboratory [ 25 ]). The software is pre-set to capture 33 wavebands with wavelengths from visible to near infrared light (477–891 nm) [ 18 ].…”

Section: Methodsmentioning

confidence: 99%

Differentiating Malignant from Benign Pigmented or Non-Pigmented Skin Tumours—A Pilot Study on 3D Hyperspectral Imaging of Complex Skin Surfaces and Convolutional Neural Networks

Lindholm

Raita-Hakola

Annala

et al. 2022

JCM

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Several optical imaging techniques have been developed to ease the burden of skin cancer disease on our health care system. Hyperspectral images can be used to identify biological tissues by their diffuse reflected spectra. In this second part of a three-phase pilot study, we used a novel hand-held SICSURFIS Spectral Imager with an adaptable field of view and target-wise selectable wavelength channels to provide detailed spectral and spatial data for lesions on complex surfaces. The hyperspectral images (33 wavelengths, 477–891 nm) provided photometric data through individually controlled illumination modules, enabling convolutional networks to utilise spectral, spatial, and skin-surface models for the analyses. In total, 42 lesions were studied: 7 melanomas, 13 pigmented and 7 intradermal nevi, 10 basal cell carcinomas, and 5 squamous cell carcinomas. All lesions were excised for histological analyses. A pixel-wise analysis provided map-like images and classified pigmented lesions with a sensitivity of 87% and a specificity of 93%, and 79% and 91%, respectively, for non-pigmented lesions. A majority voting analysis, which provided the most probable lesion diagnosis, diagnosed 41 of 42 lesions correctly. This pilot study indicates that our non-invasive hyperspectral imaging system, which involves shape and depth data analysed by convolutional neural networks, is feasible for differentiating between malignant and benign pigmented and non-pigmented skin tumours, even on complex skin surfaces.

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Section: Methodsmentioning

confidence: 99%

Differentiating Malignant from Benign Pigmented or Non-Pigmented Skin Tumours—A Pilot Study on 3D Hyperspectral Imaging of Complex Skin Surfaces and Convolutional Neural Networks

Lindholm

Raita-Hakola

Annala

et al. 2022

JCM

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“…This can be accomplished using either piezo-actuators or electrostatic actuators. 183 According to Trops et al., 183 piezo-actuators FPI had larger optical apertures and higher SNR, and electrostatic actuators were mass-producible, have smaller optical apertures, and lower SNR. In terms of spectral ranges, piezo-actuated MEMS FPI have a wider tuning range compared with electrostatic actuated MEMS FPI.…”

Section: Technical Aspects Of Compact Spectral Camerasmentioning

confidence: 99%

Section: Technical Aspects Of Compact Spectral Camerasmentioning

confidence: 99%

“…178 In spectral imagers, this is most applicable to MEMS-enabled FPI imagers, where the air gap between the mirrors cannot be smaller than two-thirds of the initial unactuated air gap size to avoid pull-in phenomena. 159,183,188 For compact devices that are planned to be used in outdoor situations, mechanical housing is as important as every other component. Crocombe 8 discussed the importance of rigid and durable housing in portable spectrometers used in manufacturing.…”

Section: Mechanical Componentsmentioning

confidence: 99%

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Compact and ultracompact spectral imagers: technology and applications in biomedical imaging

Tran

Fei

2023

J. Biomed. Opt.

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. Significance Spectral imaging, which includes hyperspectral and multispectral imaging, can provide images in numerous wavelength bands within and beyond the visible light spectrum. Emerging technologies that enable compact, portable spectral imaging cameras can facilitate new applications in biomedical imaging. Aim With this review paper, researchers will (1) understand the technological trends of upcoming spectral cameras, (2) understand new specific applications that portable spectral imaging unlocked, and (3) evaluate proper spectral imaging systems for their specific applications. Approach We performed a comprehensive literature review in three databases (Scopus, PubMed, and Web of Science). We included only fully realized systems with definable dimensions. To best accommodate many different definitions of “compact,” we included a table of dimensions and weights for systems that met our definition. Results There is a wide variety of contributions from industry, academic, and hobbyist spaces. A variety of new engineering approaches, such as Fabry–Perot interferometers, spectrally resolved detector array (mosaic array), microelectro-mechanical systems, 3D printing, light-emitting diodes, and smartphones, were used in the construction of compact spectral imaging cameras. In bioimaging applications, these compact devices were used for in vivo and ex vivo diagnosis and surgical settings. Conclusions Compact and ultracompact spectral imagers are the future of spectral imaging systems. Researchers in the bioimaging fields are building systems that are low-cost, fast in acquisition time, and mobile enough to be handheld.

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“…The HS images were captured by dermatologists and nurses (users). The SICSURFIS HSI was combined with a specially designed hospital version of the CubeView software [25]. CubeView is a spectral imaging and analysis software developed by the spectral imaging laboratory of the University of Jyväskylä, Finland [26].…”

Section: Clinical Pre-test Instrumentationmentioning

confidence: 99%

FPI Based Hyperspectral Imager for the Complex Surfaces—Calibration, Illumination and Applications

Raita-Hakola

Annala

Lindholm

et al. 2022

Sensors

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Hyperspectral imaging (HSI) applications for biomedical imaging and dermatological applications have been recently under research interest. Medical HSI applications are non-invasive methods with high spatial and spectral resolution. HS imaging can be used to delineate malignant tumours, detect invasions, and classify lesion types. Typical challenges of these applications relate to complex skin surfaces, leaving some skin areas unreachable. In this study, we introduce a novel spectral imaging concept and conduct a clinical pre-test, the findings of which can be used to develop the concept towards a clinical application. The SICSURFIS spectral imager concept combines a piezo-actuated Fabry–Pérot interferometer (FPI) based hyperspectral imager, a specially designed LED module and several sizes of stray light protection cones for reaching and adapting to the complex skin surfaces. The imager is designed for the needs of photometric stereo imaging for providing the skin surface models (3D) for each captured wavelength. The captured HS images contained 33 selected wavelengths (ranging from 477 nm to 891 nm), which were captured simultaneously with accordingly selected LEDs and three specific angles of light. The pre-test results show that the data collected with the new SICSURFIS imager enable the use of the spectral and spatial domains with surface model information. The imager can reach complex skin surfaces. Healthy skin, basal cell carcinomas and intradermal nevi lesions were classified and delineated pixel-wise with promising results, but further studies are needed. The results were obtained with a convolutional neural network.

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Miniature MOEMS hyperspectral imager with versatile analysis tools

Cited by 5 publications

References 4 publications

Differentiating Malignant from Benign Pigmented or Non-Pigmented Skin Tumours—A Pilot Study on 3D Hyperspectral Imaging of Complex Skin Surfaces and Convolutional Neural Networks

Differentiating Malignant from Benign Pigmented or Non-Pigmented Skin Tumours—A Pilot Study on 3D Hyperspectral Imaging of Complex Skin Surfaces and Convolutional Neural Networks

Compact and ultracompact spectral imagers: technology and applications in biomedical imaging

FPI Based Hyperspectral Imager for the Complex Surfaces—Calibration, Illumination and Applications

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