Biological image analysis using deep learning

Fabian Hauser

Biological image analysis using deep learning

Publikation: Konferenzbeitrag › Poster

Abstract

Showcase of 4 deep learning implementations used for biological image analysis:
1) Predicting fluorescent labels (DAPI) from phase contrast microscopy images
2) Dense nuclei counting in 2D and 3D
3) Object detection (alive, dead and aggregated cells) using YOLO-v8
4) Bacterial cell image segmentation

Originalsprache	Englisch
Publikationsstatus	Veröffentlicht - 7 Jän. 2023
Veranstaltung	11th TERMIS Winterschool: A Workshop Series on current hot Topics in Regenerative Medicine - Hotel zum jungen Römer, Radstadt, Österreich Dauer: 7 Jän. 2024 → 10 Jän. 2024 Konferenznummer: 11

Konferenz

Konferenz	11th TERMIS Winterschool
Land/Gebiet	Österreich
Ort	Radstadt
Zeitraum	07.01.2024 → 10.01.2024

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@conference{f51313be723b4018981304af97cdfa26,

title = "Biological image analysis using deep learning",

abstract = "Showcase of 4 deep learning implementations used for biological image analysis: 1) Predicting fluorescent labels (DAPI) from phase contrast microscopy images2) Dense nuclei counting in 2D and 3D3) Object detection (alive, dead and aggregated cells) using YOLO-v84) Bacterial cell image segmentation",

keywords = "deep learning, Cells, image analysis, Cell counting",

author = "Fabian Hauser",

year = "2023",

month = jan,

day = "7",

language = "English",

note = "11th TERMIS Winterschool : A Workshop Series on current hot Topics in Regenerative Medicine ; Conference date: 07-01-2024 Through 10-01-2024",

}

TY - CONF

T1 - Biological image analysis using deep learning

AU - Hauser, Fabian

N1 - Conference code: 11

PY - 2023/1/7

Y1 - 2023/1/7

N2 - Showcase of 4 deep learning implementations used for biological image analysis: 1) Predicting fluorescent labels (DAPI) from phase contrast microscopy images2) Dense nuclei counting in 2D and 3D3) Object detection (alive, dead and aggregated cells) using YOLO-v84) Bacterial cell image segmentation

AB - Showcase of 4 deep learning implementations used for biological image analysis: 1) Predicting fluorescent labels (DAPI) from phase contrast microscopy images2) Dense nuclei counting in 2D and 3D3) Object detection (alive, dead and aggregated cells) using YOLO-v84) Bacterial cell image segmentation

KW - deep learning

KW - Cells

KW - image analysis

KW - Cell counting

M3 - Poster

T2 - 11th TERMIS Winterschool

Y2 - 7 January 2024 through 10 January 2024

ER -

Biological image analysis using deep learning

Abstract

Konferenz

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