Automatic Differentiation for Inverse Problems in X-ray Imaging and Microscopy
Computational techniques allow breaking the limits of traditional imaging methods, such as time restrictions, resolution, and optics flaws. While simple computational methods can be enough for highly controlled microscope setups or just for previews, an increased level of complexity is instead requi...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-02-01
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| Series: | Life |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-1729/13/3/629 |
| _version_ | 1797610672199041024 |
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| author | Francesco Guzzi Alessandra Gianoncelli Fulvio Billè Sergio Carrato George Kourousias |
| author_facet | Francesco Guzzi Alessandra Gianoncelli Fulvio Billè Sergio Carrato George Kourousias |
| author_sort | Francesco Guzzi |
| collection | DOAJ |
| description | Computational techniques allow breaking the limits of traditional imaging methods, such as time restrictions, resolution, and optics flaws. While simple computational methods can be enough for highly controlled microscope setups or just for previews, an increased level of complexity is instead required for advanced setups, acquisition modalities or where uncertainty is high; the need for complex computational methods clashes with rapid design and execution. In all these cases, Automatic Differentiation, one of the subtopics of Artificial Intelligence, may offer a functional solution, but only if a GPU implementation is available. In this paper, we show how a framework built to solve just one optimisation problem can be employed for many different X-ray imaging inverse problems. |
| first_indexed | 2024-03-11T06:17:31Z |
| format | Article |
| id | doaj.art-b1994967512c47ebb492466a24a37b21 |
| institution | Directory Open Access Journal |
| issn | 2075-1729 |
| language | English |
| last_indexed | 2024-03-11T06:17:31Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Life |
| spelling | doaj.art-b1994967512c47ebb492466a24a37b212023-11-17T12:10:10ZengMDPI AGLife2075-17292023-02-0113362910.3390/life13030629Automatic Differentiation for Inverse Problems in X-ray Imaging and MicroscopyFrancesco Guzzi0Alessandra Gianoncelli1Fulvio Billè2Sergio Carrato3George Kourousias4Elettra—Sincrotrone Trieste, Strada Statale 14—km 163,500 in AREA Science Park, Basovizza, 34149 Trieste, ItalyElettra—Sincrotrone Trieste, Strada Statale 14—km 163,500 in AREA Science Park, Basovizza, 34149 Trieste, ItalyElettra—Sincrotrone Trieste, Strada Statale 14—km 163,500 in AREA Science Park, Basovizza, 34149 Trieste, ItalyDepartment of Engineering and Architecture (DIA), University of Trieste, 34127 Trieste, ItalyElettra—Sincrotrone Trieste, Strada Statale 14—km 163,500 in AREA Science Park, Basovizza, 34149 Trieste, ItalyComputational techniques allow breaking the limits of traditional imaging methods, such as time restrictions, resolution, and optics flaws. While simple computational methods can be enough for highly controlled microscope setups or just for previews, an increased level of complexity is instead required for advanced setups, acquisition modalities or where uncertainty is high; the need for complex computational methods clashes with rapid design and execution. In all these cases, Automatic Differentiation, one of the subtopics of Artificial Intelligence, may offer a functional solution, but only if a GPU implementation is available. In this paper, we show how a framework built to solve just one optimisation problem can be employed for many different X-ray imaging inverse problems.https://www.mdpi.com/2075-1729/13/3/629soft-X-ray microscopyautomatic differentiationcomputational imagingparameter refininginverse problems |
| spellingShingle | Francesco Guzzi Alessandra Gianoncelli Fulvio Billè Sergio Carrato George Kourousias Automatic Differentiation for Inverse Problems in X-ray Imaging and Microscopy Life soft-X-ray microscopy automatic differentiation computational imaging parameter refining inverse problems |
| title | Automatic Differentiation for Inverse Problems in X-ray Imaging and Microscopy |
| title_full | Automatic Differentiation for Inverse Problems in X-ray Imaging and Microscopy |
| title_fullStr | Automatic Differentiation for Inverse Problems in X-ray Imaging and Microscopy |
| title_full_unstemmed | Automatic Differentiation for Inverse Problems in X-ray Imaging and Microscopy |
| title_short | Automatic Differentiation for Inverse Problems in X-ray Imaging and Microscopy |
| title_sort | automatic differentiation for inverse problems in x ray imaging and microscopy |
| topic | soft-X-ray microscopy automatic differentiation computational imaging parameter refining inverse problems |
| url | https://www.mdpi.com/2075-1729/13/3/629 |
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