Single-sample image-fusion upsampling of fluorescence lifetime images
Fuente:
arXiv
Salvato in:
| Autori principali: | , , , , , , , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2024
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866916214978117632 |
|---|---|
| author | Kapitány, Valentin Fatima, Areeba Zickus, Vytautas Whitelaw, Jamie McGhee, Ewan Insall, Robert Machesky, Laura Faccio, Daniele |
| author_facet | Kapitány, Valentin Fatima, Areeba Zickus, Vytautas Whitelaw, Jamie McGhee, Ewan Insall, Robert Machesky, Laura Faccio, Daniele |
| contents | Fluorescence lifetime imaging microscopy (FLIM) provides detailed information about molecular interactions and biological processes. A major bottleneck for FLIM is image resolution at high acquisition speeds, due to the engineering and signal-processing limitations of time-resolved imaging technology. Here we present single-sample image-fusion upsampling (SiSIFUS), a data-fusion approach to computational FLIM super-resolution that combines measurements from a low-resolution time-resolved detector (that measures photon arrival time) and a high-resolution camera (that measures intensity only). To solve this otherwise ill-posed inverse retrieval problem, we introduce statistically informed priors that encode local and global dependencies between the two single-sample measurements. This bypasses the risk of out-of-distribution hallucination as in traditional data-driven approaches and delivers enhanced images compared for example to standard bilinear interpolation. The general approach laid out by SiSIFUS can be applied to other image super-resolution problems where two different datasets are available. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_13102 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Single-sample image-fusion upsampling of fluorescence lifetime images Kapitány, Valentin Fatima, Areeba Zickus, Vytautas Whitelaw, Jamie McGhee, Ewan Insall, Robert Machesky, Laura Faccio, Daniele Image and Video Processing Computer Vision and Pattern Recognition Biological Physics Optics I.4.3; I.4.8; I.5.1 Fluorescence lifetime imaging microscopy (FLIM) provides detailed information about molecular interactions and biological processes. A major bottleneck for FLIM is image resolution at high acquisition speeds, due to the engineering and signal-processing limitations of time-resolved imaging technology. Here we present single-sample image-fusion upsampling (SiSIFUS), a data-fusion approach to computational FLIM super-resolution that combines measurements from a low-resolution time-resolved detector (that measures photon arrival time) and a high-resolution camera (that measures intensity only). To solve this otherwise ill-posed inverse retrieval problem, we introduce statistically informed priors that encode local and global dependencies between the two single-sample measurements. This bypasses the risk of out-of-distribution hallucination as in traditional data-driven approaches and delivers enhanced images compared for example to standard bilinear interpolation. The general approach laid out by SiSIFUS can be applied to other image super-resolution problems where two different datasets are available. |
| title | Single-sample image-fusion upsampling of fluorescence lifetime images |
| topic | Image and Video Processing Computer Vision and Pattern Recognition Biological Physics Optics I.4.3; I.4.8; I.5.1 |
| url | https://arxiv.org/abs/2404.13102 |