Image Processing for Volume Electron Microscopy

Kornfeld, Joergen; Svara, Fabian; Wanner, Adrian

doi:10.1007/978-1-0716-0691-9_13

Cited by 5 publications

(5 citation statements)

References 47 publications

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“…It can be accessed anywhere (with an internet connection) and multiple annotators can simultaneously work on different parts of the volume. A comprehensive list comparing various features of all tools has been published elsewhere 108 …”

Section: Image Processing and Analysis In Volume Emmentioning

confidence: 99%

How innovations in methodology offer new prospects for volume electron microscopy

Kievits

Lane

Carroll

et al. 2022

Journal of Microscopy

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Detailed knowledge of biological structure has been key in understanding biology at several levels of organisation, from organs to cells and proteins. Volume electron microscopy (volume EM) provides high resolution 3D structural information about tissues on the nanometre scale. However, the throughput rate of conventional electron microscopes has limited the volume size and number of samples that can be imaged. Recent improvements in methodology are currently driving a revolution in volume EM, making possible the structural imaging of whole organs and small organisms. In turn, these recent developments in image acquisition have created or stressed bottlenecks in other parts of the pipeline, like sample preparation, image analysis and data management. While the progress in image analysis is stunning due to the advent of automatic segmentation and server-based annotation tools, several challenges remain. Here we discuss recent trends in volume EM, emerging methods for increasing throughput and implications for sample preparation, image analysis and data management.

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Section: Image Processing and Analysis In Volume Emmentioning

confidence: 99%

How innovations in methodology offer new prospects for volume electron microscopy

Kievits

Lane

Carroll

et al. 2022

Journal of Microscopy

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“…Munawar et al [51] used isotropic surround suppression and Hough transforms for target recognition from aerial images and performed rule-based verification of strategic targets detected from these images. Recently, edge detection techniques on multispectral aerial images to mine strategic bridge locations to provide aid in disaster relief missions have been applied [51][52][53]. Table 1 summarises the methodologies using edge detection for various flood management processes.…”

Section: Rqmentioning

confidence: 99%

An Integrated Approach for Post-Disaster Flood Management Via the Use of Cutting-Edge Technologies and UAVs: A Review

et al. 2021

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Rapid advances that improve flood management have facilitated the disaster response by providing first aid services, finding safe routes, maintaining communication and developing flood maps. Different technologies such as image processing, satellite imagery, synthetic imagery and integrated approaches have been extensively analysed in the literature for disaster operations. There is a need to review cutting-edge technologies for flood management. This paper presents a review of the latest advancements in the flood management domain based on image processing, artificial intelligence and integrated approaches with a focus on post-disaster. It answers the following research questions: (1) What are the latest developments in image processing for flood management in a post-disaster scenario? (2) What are the latest techniques for flood management based on artificial intelligence in a post-disaster scenario? (3) What are the existing gaps in the selected technologies for post-disaster? (4) How can the authorities improve the existing post-disaster management operation with cutting-edge technologies? A novel framework has been proposed to optimise flood management with the application of a holistic approach.

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“…Experiments involving dense reconstruction are often several TB in size and benefit from software which can handle annotations on extremely large image data (Kornfeld et al, 2020). To capture dendritic arborization while imaging at synaptic resolution, our datasets also ranged from 2-4 TB in size.…”

Section: The Precision Of Our Approach Allows Efficient Structure-funmentioning

confidence: 99%

Targeting Functionally Characterized Synaptic Architecture Using Inherent Fiducials and 3D Correlative Microscopy

et al. 2020

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Image Processing for Volume Electron Microscopy

Cited by 5 publications

References 47 publications

How innovations in methodology offer new prospects for volume electron microscopy

How innovations in methodology offer new prospects for volume electron microscopy

An Integrated Approach for Post-Disaster Flood Management Via the Use of Cutting-Edge Technologies and UAVs: A Review

Targeting Functionally Characterized Synaptic Architecture Using Inherent Fiducials and 3D Correlative Microscopy

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