Volume Segmentation and Analysis of Biological Materials Using SuRVoS (Super-region Volume Segmentation) Workbench

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9.7K Views

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11:38 min

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August 23rd, 2017

DOI :

10.3791/56162-v

August 23rd, 2017

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Michele C. Darrow¹, Imanol Luengo¹^,², Mark Basham¹, Matthew C. Spink¹, Sarah Irvine¹, Andrew P. French², Alun W. Ashton¹, Elizabeth M.H. Duke¹

¹Science Division, Harwell Science and Innovation Campus, Diamond Light Source, ²School of Computer Science, University of Nottingham

Podsumowanie

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Keywords Volume Segmentation

Biological Materials

SuRVoS

Super region Volume Segmentation

Workbench

Structural Biology

Phase Contrast X ray Tomography

Rozdziały w tym wideo

0:05

Title

0:53

Preparing the Workplace, Data Representation, and Generating Appropriate Super-regions

3:19

Introduction to Annotation

4:12

Segmentation Using Model Training

5:41

Segmentation Using Super-regions

6:42

Classifiction and Analysis of Data Objects Based on Inherent Characteristics

9:00

Results: Model Training, Super-region Segmentation, and Label Splitting Using the SuRVoS Workbench

10:55

Conclusion

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