Block-iterative Richardson-Lucy methods for image deblurring

Lee, Nam Yong

doi:10.1186/s13640-015-0069-2

“…In Ot2Rec, rather than developing an in-house solver, we have implemented a wrapper plugin for the Python library RedLionfish ( 53 ) for performing the 3-dimensional deconvolution between a reconstructed tomogram and a simulated PSF stack (similarly reconstructed as the experimental tomogram). To facilitate the deconvolution of larger stacks, which might cause GPU/CPU memory issues, we also implemented the 3D version of the so-called “block-iterative” algorithm, inspired by Lee ( 54 ) , which breaks the volume (tomogram) into chunks, on each of which a normal Richardson–Lucy deconvolution is performed independently. The separately deconvolved chunks are then stitched back together.…”

Section: Methodsmentioning

confidence: 99%

Ot2Rec: A semi-automatic, extensible, multi-software tomographic reconstruction workflow

Yee¹,

Ho²,

Tun³

et al. 2023

Biol. Imaging

0

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Electron cryo-tomography (cryo-ET) is an imaging technique for probing 3D structures with at the nanometre scale. This technique has been used extensively in the biomedical field to study the complex structures of proteins and other macromolecules. With the advancement in technology, microscopes are currently capable of producing images amounting to terabytes of data per day, posing great challenges for scientists as the speed of processing of the images cannot keep up with the ever-higher throughput of the microscopes. Therefore, automation is an essential and natural pathway on which image processing -from individual micrographs to full tomograms -is developing. In this paper, we present Ot2Rec, an open-source pipelining tool which aims to enable scientists to build their own processing workflows in a flexible and automatic manner. The basic building blocks of Ot2Rec are plugins which follow a unified API structure, making it simple for scientists to contribute to Ot2Rec by adding features which are not already available. In this paper, we also present three case studies of image processing using Ot2Rec, through which we demonstrate the speedup of using a semi-automatic workflow over a manual one, the possibility of writing and using custom (prototype) plugins, and the flexibility of Ot2Rec which enables the mix-and-match of plugins. We also demonstrate, in the supplementary information, a builtin reporting feature in Ot2Rec which aggregates the metadata from all process being run, and output them in the Jupyter Notebook and/or HTML formats for quick review of image processing quality. Ot2Rec can be found at https://github.com/rosalindfranklininstitute/ot2rec Impact StatementThe field of cryo electron tomography has grown substantially in recent years, bringing about new advances in hardware and software which enable visualisation of cell and tissue architecture and proteins found in their native context. These same advances have, in some ways, stratified the field into those with access and those without. On the software side, this has emphasised the need for open-source options that do not require high levels of computational literacy to access. Additionally, it has highlighted the need for ways to both mix-and-match software for easy prototyping and comparisons between parameters and methods. Ot2Rec addresses these needs through a simple, unified plugin structure allowing the addition of existing software or the development of new and does so in a way which democratises access.

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“…In Ot2Rec, rather than developing an in-house solver, we have implemented a wrapper plugin for the Python library RedLionfish (51) for performing the 3-dimensional deconvolution between a reconstructed tomogram and a simulated PSF stack (similarly reconstructed as the experimental tomogram). To facilitate the deconvolution of larger stacks, which might cause GPU/CPU memory issues, we also implemented the 3D version of the so-called “block-iterative” algorithm, inspired by Lee (52) , which breaks the volume (tomogram) into chunks, on each of which a normal Richardson-Lucy deconvolution is performed independently. The separately deconvolved chunks are then stitched back together.…”

Section: Methodsmentioning

confidence: 99%

“…To facilitate the deconvolution of larger stacks, which might cause GPU/CPU memory issues, we also implemented the 3D version of the so-called "block-iterative" algorithm, inspired by Lee (52) , which breaks the volume (tomogram) into chunks, on each of which a normal Richardson-Lucy deconvolution is performed independently. The separately deconvolved chunks are then stitched back together.…”

Section: Prototype Featuresmentioning

confidence: 99%

Ot2Rec: A Semi-Automatic, Extensible, Multi-Software Tomographic Reconstruction Workflow

Yee

¹

,

Ho

²

,

Tun

³

et al. 2022

Preprint

0

View full text Add to dashboard Cite

Electron cryo-tomography (cryo-ET) is an imaging technique for probing 3D structures with at the nanometre scale. This technique has been used extensively in the biomedical field to study the complex structures of proteins and other macromolecules. With the advancement in technology, microscopes are currently capable of producing images amounting to terabytes of data per day, posing great challenges for scientists as the speed of processing of the images cannot keep up with the ever-higher throughput of the microscopes. Therefore, automation is an essential and natural pathway on which image processing -- from individual micrographs to full tomograms -- is developing. In this paper, we present Ot2Rec, an open-source pipelining tool which aims to enable scientists to build their own processing workflows in a flexible and automatic manner. The basic building blocks of Ot2Rec are plugins which follow a unified API structure, making it simple for scientists to contribute to Ot2Rec by adding features which are not already available. In this paper, we also present three case studies of image processing using Ot2Rec, through which we demonstrate the speedup of using a semi-automatic workflow over a manual one, the possibility of writing and using custom (prototype) plugins, and the flexibility of Ot2Rec which enables the mix-and-match of plugins. We also demonstrate, in the supplementary information, a built-in reporting feature in Ot2Rec which aggregates the metadata from all process being run, and output them in the Jupyter Notebook and/or HTML formats for quick review of image processing quality. Ot2Rec can be found at https://github.com/rosalindfranklininstitute/ot2rec .

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“…The intended methods to be used in performing this task are directly dependent on the specifications of the imaging system. The camera system will need to possess an integration time (the time it takes to capture a frame) under 100µs, short enough to eliminate any motion blur that would occur from cells traveling through blood vessels [71]. There also needs to be a method implemented Camera specifications aside, there are several other features this system must possess.…”

Section: System Designmentioning

confidence: 99%

Imaging White Blood Cells using a Snapshot Hyper-Spectral Imaging System

Robison¹

0

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Block-iterative Richardson-Lucy methods for image deblurring

Cited by 7 publications

References 27 publications

Ot2Rec: A semi-automatic, extensible, multi-software tomographic reconstruction workflow

Ot2Rec: A semi-automatic, extensible, multi-software tomographic reconstruction workflow

Ot2Rec: A Semi-Automatic, Extensible, Multi-Software Tomographic Reconstruction Workflow

Imaging White Blood Cells using a Snapshot Hyper-Spectral Imaging System

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