Lu B, Dao PD, Liu J, He Y, Shang J. Recent advances of hyperspectral imaging technology and applications in agriculture. Remote Sens. 2020;12:2659. https://doi.org/10.3390/rs12162659.

Article  Google Scholar 

Khan MJ, Khan HS, Yousaf A, Khurshid K, Abbas A. Modern trends in hyperspectral image analysis: a review. IEEE Access. 2018;6:14118–29. https://doi.org/10.1109/access.2018.2812999.

Article  Google Scholar 

Goetz AFH. Three decades of hyperspectral remote sensing of the Earth: a personal view. Remote Sens Environ. 2009;113:S5–16. https://doi.org/10.1016/j.rse.2007.12.014.

Article  Google Scholar 

Lu G, Fei B. Medical hyperspectral imaging: a review. J Biomed Opt. 2014;19:10901. https://doi.org/10.1117/1.JBO.19.1.010901.

Article  CAS  PubMed  Google Scholar 

Nasrabadi NM. Hyperspectral target detection : an overview of current and future challenges. IEEE Signal Process Mag. 2014;31:34–44. https://doi.org/10.1109/MSP.2013.2278992.

Article  Google Scholar 

Sneha Kaul A. Hyperspectral imaging and target detection algorithms: a review. Multimed Tools Appl. 2022;81:44141–206. https://doi.org/10.1007/s11042-022-13235-x.

Article  Google Scholar 

Felli E, Cinelli L, Bannone E, et al. Hyperspectral imaging in major hepatectomies: preliminary results from the ex-machyna trial. Cancers (Basel). 2022;14:5591. https://doi.org/10.3390/cancers14225591.

Article  CAS  PubMed  Google Scholar 

Hennig S, Jansen-Winkeln B, Kohler H, et al. Novel intraoperative imaging of gastric tube perfusion during oncologic esophagectomy-a pilot study comparing hyperspectral imaging (HSI) and fluorescence imaging (FI) with indocyanine green (ICG). Cancers (Basel). 2021;14:97. https://doi.org/10.3390/cancers14010097.

Article  CAS  PubMed  Google Scholar 

Son GM, Ahn H-M, Lee IY, Lee SM, Park S-H, Baek K-R. Clinical effect and standardization of indocyanine green angiography in the laparoscopic colorectal surgery. J Minim Invasive Surg. 2021;24:113–22. https://doi.org/10.7602/jmis.2021.24.3.113.

Article  PubMed  PubMed Central  Google Scholar 

Tian C, Su W, Huang S, et al. Identification of gastric cancer types based on hyperspectral imaging technology. J Biophotonics. 2023;5:e202300276. https://doi.org/10.1002/jbio.202300276.

Article  Google Scholar 

Tian C, Hao D, Ma M, et al. Graded diagnosis of Helicobacter pylori infection using hyperspectral images of gastric juice. J Biophotonics. 2023;14:e202300254. https://doi.org/10.1002/jbio.202300254.

Article  Google Scholar 

Mitsui T, Mori A, Takamatsu T, et al. Evaluating the identification of the extent of gastric cancer by over-1000 nm near-infrared hyperspectral imaging using surgical specimens. J Biomed Opt. 2023;28:086001. https://doi.org/10.1117/1.JBO.28.8.086001.

Article  PubMed  PubMed Central  Google Scholar 

Liu S, Wang Q, Zhang G, Du J, Hu B, Zhang Z. Using hyperspectral imaging automatic classification of gastric cancer grading with a shallow residual network. Anal Methods. 2020;12:3844–53. https://doi.org/10.1039/d0ay01023e.

Article  CAS  PubMed  Google Scholar 

Liu N, Guo Y, Jiang H, Yi W. Gastric cancer diagnosis using hyperspectral imaging with principal component analysis and spectral angle mapper. J Biomed Opt. 2020;25:1–9. https://doi.org/10.1117/1.JBO.25.6.066005.

Article  PubMed  Google Scholar 

Li Y, Xie X, Yang X, et al. Diagnosis of early gastric cancer based on fluorescence hyperspectral imaging technology combined with partial-least-square discriminant analysis and support vector machine. J Biophotonics. 2019;12:e201800324. https://doi.org/10.1002/jbio.201800324.

Article  PubMed  Google Scholar 

Li Y, Deng L, Yang X, et al. Early diagnosis of gastric cancer based on deep learning combined with the spectral-spatial classification method. Biomed Opt Express. 2019;10:4999–5014. https://doi.org/10.1364/BOE.10.004999.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Ogihara H, Hamamoto Y, Fujita Y, Goto A, Nishikawa J, Sakaida I. Development of a gastric cancer diagnostic support system with a pattern recognition method using a hyperspectral camera. J Sensors. 2016;2016:1–6. https://doi.org/10.1155/2016/1803501.

Article  Google Scholar 

Kiyotoki S, Nishikawa J, Okamoto T, et al. New method for detection of gastric cancer by hyperspectral imaging: a pilot study. J Biomed Opt. 2013;18:26010. https://doi.org/10.1117/1.JBO.18.2.026010.

Article  CAS  PubMed  Google Scholar 

Akbari H, Uto K, Kosugi Y, Kojima K, Tanaka N. Cancer detection using infrared hyperspectral imaging. Cancer Sci. 2011;102:852–7. https://doi.org/10.1111/j.1349-7006.2011.01849.x.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Schwandner F, Hinz S, Witte M, Philipp M, Schafmayer C, Grambow E. Intraoperative assessment of gastric sleeve oxygenation using hyperspectral imaging in esophageal resection: a feasibility study. Visc Med. 2021;37:165–70. https://doi.org/10.1159/000509304.

Article  PubMed  Google Scholar 

Moulla Y, Buchloh DC, Kohler H, et al. Hyperspectral imaging (HSI)-a new tool to estimate the perfusion of upper abdominal organs during pancreatoduodenectomy. Cancers (Basel). 2021;13:2846. https://doi.org/10.3390/cancers13112846.

Article  CAS  PubMed  Google Scholar 

Collins T, Maktabi M, Barberio M, et al. Automatic recognition of colon and esophagogastric cancer with machine learning and hyperspectral imaging. Diagnostics (Basel). 2021;11:1810. https://doi.org/10.3390/diagnostics11101810.

Article  PubMed  Google Scholar 

Sato D, Takamatsu T, Umezawa M, et al. Distinction of surgically resected gastrointestinal stromal tumor by near-infrared hyperspectral imaging. Sci Rep. 2020;10:21852. https://doi.org/10.1038/s41598-020-79021-7.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Kohler H, Jansen-Winkeln B, Maktabi M, et al. Evaluation of hyperspectral imaging (HSI) for the measurement of ischemic conditioning effects of the gastric conduit during esophagectomy. Surg Endosc. 2019;33:3775–82. https://doi.org/10.1007/s00464-019-06675-4.

Article  PubMed  Google Scholar 

Jansen-Winkeln B, Maktabi M, Takoh JP, et al. Hyperspectral imaging of gastrointestinal anastomoses. Chirurg. 2018;89:717–25. https://doi.org/10.1007/s00104-018-0633-2.

Article  CAS  PubMed  Google Scholar 

Zimmermann A, Kohler H, Chalopin C, et al. The role of intraoperative hyperspectral imaging (HSI) in colon interposition after esophagectomy. BMC Surg. 2023;23:47. https://doi.org/10.1186/s12893-023-01946-3.

Article  PubMed  PubMed Central  Google Scholar 

Tkachenko M, Chalopin C, Jansen-Winkeln B, Neumuth T, Gockel I, Maktabi M. Impact of pre- and post-processing steps for supervised classification of colorectal cancer in hyperspectral images. Cancers (Basel). 2023;15:2157. https://doi.org/10.3390/cancers15072157.

Article  PubMed  Google Scholar 

Son GM, Nazir AM, Yun MS, et al. The safe values of quantitative perfusion parameters of ICG angiography based on tissue oxygenation of hyperspectral imaging for laparoscopic colorectal surgery: a prospective observational study. Biomedicines. 2023;11:2029. https://doi.org/10.3390/biomedicines11072029.

Article  PubMed  PubMed Central  Google Scholar 

Muniz FB, Baffa MFO, Garcia SB, Bachmann L, Felipe JC. Histopathological diagnosis of colon cancer using micro-FTIR hyperspectral imaging and deep learning. Comput Methods Programs Biomed. 2023;231:107388. https://doi.org/10.1016/j.cmpb.2023.107388.

Article  PubMed  Google Scholar 

Wagner T, Radunz S, Becker F, et al. Hyperspectral imaging detects perfusion and oxygenation differences between stapled and hand-sewn intestinal anastomoses. Innov Surg Sci. 2022;7:59–63. https://doi.org/10.1515/iss-2022-0007.

Article  PubMed  PubMed Central  Google Scholar 

Jansen-Winkeln B, Dvorak M, Kohler H, et al. Border line definition using hyperspectral imaging in colorectal resections. Cancers (Basel). 2022;14:1188. https://doi.org/10.3390/cancers14051188.

Article