| Full text | |
| Author(s): |
Stegmaier, Johannes
;
Spina, Thiago V.
;
Falcao, Alexandre X.
;
Bartschat, Andreas
;
Mikut, Ralf
;
Meyerowitz, Elliot
;
Cunha, Alexandre
;
IEEE
Total Authors: 8
|
| Document type: | Journal article |
| Source: | 2018 IEEE 15TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2018); v. N/A, p. 5-pg., 2018-01-01. |
| Abstract | |
Automated segmentation approaches are crucial to quantitatively analyze large-scale 3D microscopy images. Particularly in deep tissue regions, automatic methods still fail to provide error-free segmentations. To improve the segmentation quality throughout imaged samples, we present a new supervoxel-based 3D segmentation approach that outperforms current methods and reduces the manual correction effort. The algorithm consists of gentle preprocessing and a conservative super-voxel generation method followed by supervoxel agglomeration based on local signal properties and a postprocessing step to fix under-segmentation errors using a Convolutional Neural Network. We validate the functionality of the algorithm on manually labeled 3D confocal images of the plant Arabidopsis thaliana and compare the results to a state-of-the-art meristem segmentation algorithm. (AU) | |
| FAPESP's process: | 15/09446-7 - Medical Image Segmentation: How to integrate object appearance/shape models and interactive correction with minimum user intervention? |
| Grantee: | Thiago Vallin Spina |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
| FAPESP's process: | 16/11853-2 - SAMSAM: Segmentation for Analysis and Measurements in the Shoot Apical Meristem |
| Grantee: | Thiago Vallin Spina |
| Support Opportunities: | Scholarships abroad - Research Internship - Post-doctor |
| FAPESP's process: | 14/12236-1 - AnImaLS: Annotation of Images in Large Scale: what can machines and specialists learn from interaction? |
| Grantee: | Alexandre Xavier Falcão |
| Support Opportunities: | Research Projects - Thematic Grants |