TY - JOUR
T1 - In-vivo and ex-vivo tissue analysis through hyperspectral imaging techniques
T2 - Revealing the invisible features of cancer
AU - Halicek, Martin
AU - Fabelo, Himar
AU - Ortega, Samuel
AU - Callico, Gustavo M.
AU - Fei, Baowei
N1 - Funding Information:
This research was supported in part by the U.S. National Institutes of Health (NIH) grants (R21CA176684, R01CA156775, R01CA204254, and R01HL140325). In addition, this work has been supported in part by the Canary Islands Government through the ACIISI (Canarian Agency for Research, Innovation and the Information Society), ITHACA project “Hyperspectral Identification of Brain Tumors” under Grant Agreement ProID2017010164. Moreover, this work has been supported in part by the 2016 PhD Training Program for Research Staff of the University of Las Palmas de Gran Canaria. Finally, this work was completed while Samuel Ortega was beneficiary of a pre-doctoral grant given by the “Agencia Canaria de Investigacion, Innovacion y Sociedad de la Información (ACIISI)” of the “Conserjería de Economía, Industria, Comercio y Conocimiento” of the “Gobierno de Canarias”, which is part-financed by the European Social Fund (FSE) (POC 2014-2020, Eje 3 Tema Prioritario 74 (85%)).
Publisher Copyright:
© 2019 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2019/6
Y1 - 2019/6
N2 - In contrast to conventional optical imaging modalities, hyperspectral imaging (HSI) is able to capture much more information from a certain scene, both within and beyond the visual spectral range (from 400 to 700 nm). This imaging modality is based on the principle that each material provides different responses to light reflection, absorption, and scattering across the electromagnetic spectrum. Due to these properties, it is possible to differentiate and identify the different materials/substances presented in a certain scene by their spectral signature. Over the last two decades, HSI has demonstrated potential to become a powerful tool to study and identify several diseases in the medical field, being a non-contact, non-ionizing, and a label-free imaging modality. In this review, the use of HSI as an imaging tool for the analysis and detection of cancer is presented. The basic concepts related to this technology are detailed. The most relevant, state-of-the-art studies that can be found in the literature using HSI for cancer analysis are presented and summarized, both in-vivo and ex-vivo. Lastly, we discuss the current limitations of this technology in the field of cancer detection, together with some insights into possible future steps in the improvement of this technology.
AB - In contrast to conventional optical imaging modalities, hyperspectral imaging (HSI) is able to capture much more information from a certain scene, both within and beyond the visual spectral range (from 400 to 700 nm). This imaging modality is based on the principle that each material provides different responses to light reflection, absorption, and scattering across the electromagnetic spectrum. Due to these properties, it is possible to differentiate and identify the different materials/substances presented in a certain scene by their spectral signature. Over the last two decades, HSI has demonstrated potential to become a powerful tool to study and identify several diseases in the medical field, being a non-contact, non-ionizing, and a label-free imaging modality. In this review, the use of HSI as an imaging tool for the analysis and detection of cancer is presented. The basic concepts related to this technology are detailed. The most relevant, state-of-the-art studies that can be found in the literature using HSI for cancer analysis are presented and summarized, both in-vivo and ex-vivo. Lastly, we discuss the current limitations of this technology in the field of cancer detection, together with some insights into possible future steps in the improvement of this technology.
KW - Artificial intelligence
KW - Biomedical optical imaging
KW - Cancer
KW - Clinical diagnosis
KW - Hyperspectral imaging
KW - Machine learning
KW - Medical diagnostic imaging
UR - http://www.scopus.com/inward/record.url?scp=85069509747&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85069509747&partnerID=8YFLogxK
U2 - 10.3390/cancers11060756
DO - 10.3390/cancers11060756
M3 - Review article
C2 - 31151223
AN - SCOPUS:85069509747
SN - 2072-6694
VL - 11
JO - Cancers
JF - Cancers
IS - 6
M1 - 756
ER -