Fluorescence Lifetime Endoscopy with a Nanosecond Time-Gated CAPS Camera with IRF-Free Deep Learning Method
Fluorescence imaging has been widely used in fields like (pre)clinical imaging and other domains. With advancements in imaging technology and new fluorescent labels, fluorescence lifetime imaging is gradually gaining recognition. Our research department is developing the <i>tau</i>CAM<...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-01-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/25/2/450 |
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| author | Pooria Iranian Thomas Lapauw Thomas Van den Dries Sevada Sahakian Joris Wuts Valéry Ann Jacobs Jef Vandemeulebroucke Maarten Kuijk Hans Ingelberts |
| author_facet | Pooria Iranian Thomas Lapauw Thomas Van den Dries Sevada Sahakian Joris Wuts Valéry Ann Jacobs Jef Vandemeulebroucke Maarten Kuijk Hans Ingelberts |
| author_sort | Pooria Iranian |
| collection | DOAJ |
| description | Fluorescence imaging has been widely used in fields like (pre)clinical imaging and other domains. With advancements in imaging technology and new fluorescent labels, fluorescence lifetime imaging is gradually gaining recognition. Our research department is developing the <i>tau</i>CAM<sup>TM</sup>, based on the Current-Assisted Photonic Sampler, to achieve real-time fluorescence lifetime imaging in the NIR (700–900 nm) region. Incorporating fluorescence lifetime into endoscopy could further improve the differentiation of malignant and benign cells based on their distinct lifetimes. In this work, the capabilities of an endoscopic lifetime imaging system are demonstrated using a rigid endoscope involving various phantoms and an IRF-free deep learning-based method with only 6-time points. The results show that this application’s fluorescence lifetime image has better lifetime uniformity and precision with 6-time points than the conventional methods. |
| format | Article |
| id | doaj-art-5ac2dfb54ee34a038d1230ac3f58c439 |
| institution | Kabale University |
| issn | 1424-8220 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-5ac2dfb54ee34a038d1230ac3f58c4392025-01-24T13:48:58ZengMDPI AGSensors1424-82202025-01-0125245010.3390/s25020450Fluorescence Lifetime Endoscopy with a Nanosecond Time-Gated CAPS Camera with IRF-Free Deep Learning MethodPooria Iranian0Thomas Lapauw1Thomas Van den Dries2Sevada Sahakian3Joris Wuts4Valéry Ann Jacobs5Jef Vandemeulebroucke6Maarten Kuijk7Hans Ingelberts8Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel, 1050 Brussels, BelgiumDepartment of Electronics and Informatics (ETRO), Vrije Universiteit Brussel, 1050 Brussels, BelgiumDepartment of Electronics and Informatics (ETRO), Vrije Universiteit Brussel, 1050 Brussels, BelgiumDepartment of Electronics and Informatics (ETRO), Vrije Universiteit Brussel, 1050 Brussels, BelgiumDepartment of Electronics and Informatics (ETRO), Vrije Universiteit Brussel, 1050 Brussels, BelgiumMOBI Rresearch Center, Vrije Universiteit Brussel, 1050 Brussels, BelgiumDepartment of Electronics and Informatics (ETRO), Vrije Universiteit Brussel, 1050 Brussels, BelgiumDepartment of Electronics and Informatics (ETRO), Vrije Universiteit Brussel, 1050 Brussels, BelgiumDepartment of Electronics and Informatics (ETRO), Vrije Universiteit Brussel, 1050 Brussels, BelgiumFluorescence imaging has been widely used in fields like (pre)clinical imaging and other domains. With advancements in imaging technology and new fluorescent labels, fluorescence lifetime imaging is gradually gaining recognition. Our research department is developing the <i>tau</i>CAM<sup>TM</sup>, based on the Current-Assisted Photonic Sampler, to achieve real-time fluorescence lifetime imaging in the NIR (700–900 nm) region. Incorporating fluorescence lifetime into endoscopy could further improve the differentiation of malignant and benign cells based on their distinct lifetimes. In this work, the capabilities of an endoscopic lifetime imaging system are demonstrated using a rigid endoscope involving various phantoms and an IRF-free deep learning-based method with only 6-time points. The results show that this application’s fluorescence lifetime image has better lifetime uniformity and precision with 6-time points than the conventional methods.https://www.mdpi.com/1424-8220/25/2/450endoscopyfluorescence imagingfluorescence lifetime imaginggated cameraCAPSconvolutional neural networks |
| spellingShingle | Pooria Iranian Thomas Lapauw Thomas Van den Dries Sevada Sahakian Joris Wuts Valéry Ann Jacobs Jef Vandemeulebroucke Maarten Kuijk Hans Ingelberts Fluorescence Lifetime Endoscopy with a Nanosecond Time-Gated CAPS Camera with IRF-Free Deep Learning Method Sensors endoscopy fluorescence imaging fluorescence lifetime imaging gated camera CAPS convolutional neural networks |
| title | Fluorescence Lifetime Endoscopy with a Nanosecond Time-Gated CAPS Camera with IRF-Free Deep Learning Method |
| title_full | Fluorescence Lifetime Endoscopy with a Nanosecond Time-Gated CAPS Camera with IRF-Free Deep Learning Method |
| title_fullStr | Fluorescence Lifetime Endoscopy with a Nanosecond Time-Gated CAPS Camera with IRF-Free Deep Learning Method |
| title_full_unstemmed | Fluorescence Lifetime Endoscopy with a Nanosecond Time-Gated CAPS Camera with IRF-Free Deep Learning Method |
| title_short | Fluorescence Lifetime Endoscopy with a Nanosecond Time-Gated CAPS Camera with IRF-Free Deep Learning Method |
| title_sort | fluorescence lifetime endoscopy with a nanosecond time gated caps camera with irf free deep learning method |
| topic | endoscopy fluorescence imaging fluorescence lifetime imaging gated camera CAPS convolutional neural networks |
| url | https://www.mdpi.com/1424-8220/25/2/450 |
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