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Single-shot self-su...
Single-shot self-supervised object detection in microscopy
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- Midtvedt, Benjamin (author)
- Gothenburg University,Göteborgs universitet,Institutionen för fysik (GU),Department of Physics (GU)
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- Pineda, Jesus (author)
- Gothenburg University,Göteborgs universitet,Institutionen för fysik (GU),Department of Physics (GU)
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- Skärberg, Fredrik, 1992 (author)
- Gothenburg University,Göteborgs universitet,Institutionen för fysik (GU),Department of Physics (GU)
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- Olsén, Erik, 1994 (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Bachimanchi, Harshith (author)
- Gothenburg University,Göteborgs universitet,Institutionen för fysik (GU),Department of Physics (GU)
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- Vilhelmsson Wesén, Emelie, 1989 (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Esbjörner Winters, Elin, 1978 (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Selander, Erik, 1973 (author)
- Gothenburg University,Göteborgs universitet,Institutionen för marina vetenskaper,Department of marine sciences
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- Höök, Fredrik, 1966 (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Midtvedt, Daniel, 1988 (author)
- Gothenburg University,Göteborgs universitet,Institutionen för fysik (GU),Department of Physics (GU)
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- Volpe, Giovanni, 1979 (author)
- Gothenburg University,Göteborgs universitet,Institutionen för fysik (GU),Department of Physics (GU)
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Esbjörner, Elin K. (author)
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(creator_code:org_t)
- 2022-12-05
- 2022
- English.
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In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723 .- 2041-1723. ; 13:1
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Abstract
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- Object detection is a fundamental task in digital microscopy, where machine learning has made great strides in overcoming the limitations of classical approaches. The training of state-of-the-art machine-learning methods almost universally relies on vast amounts of labeled experimental data or the ability to numerically simulate realistic datasets. However, experimental data are often challenging to label and cannot be easily reproduced numerically. Here, we propose a deep-learning method, named LodeSTAR (Localization and detection from Symmetries, Translations And Rotations), that learns to detect microscopic objects with sub-pixel accuracy from a single unlabeled experimental image by exploiting the inherent roto-translational symmetries of this task. We demonstrate that LodeSTAR outperforms traditional methods in terms of accuracy, also when analyzing challenging experimental data containing densely packed cells or noisy backgrounds. Furthermore, by exploiting additional symmetries we show that LodeSTAR can measure other properties, e.g., vertical position and polarizability in holographic microscopy.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap -- Annan data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Other Computer and Information Science (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Robotteknik och automation (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Robotics (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)
- NATURVETENSKAP -- Fysik (hsv//swe)
- NATURAL SCIENCES -- Physical Sciences (hsv//eng)
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- art (subject category)
- ref (subject category)
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- By the author/editor
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Midtvedt, Benjam ...
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Pineda, Jesus
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Skärberg, Fredri ...
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Olsén, Erik, 199 ...
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Bachimanchi, Har ...
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Vilhelmsson Wesé ...
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Esbjörner Winter ...
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Selander, Erik, ...
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Höök, Fredrik, 1 ...
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Midtvedt, Daniel ...
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Volpe, Giovanni, ...
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Esbjörner, Elin ...
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- About the subject
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- NATURAL SCIENCES
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NATURAL SCIENCES
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and Computer and Inf ...
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and Other Computer a ...
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- ENGINEERING AND TECHNOLOGY
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ENGINEERING AND ...
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and Electrical Engin ...
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and Robotics
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- NATURAL SCIENCES
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NATURAL SCIENCES
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and Computer and Inf ...
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and Computer Vision ...
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- NATURAL SCIENCES
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NATURAL SCIENCES
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and Physical Science ...
- Articles in the publication
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Nature Communica ...
- By the university
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Chalmers University of Technology
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University of Gothenburg