High-throughput mesoscopic optical imaging data processing and parsing using differential-guided filtered neural networks
Abstract High-throughput mesoscopic optical imaging technology has tremendously boosted the efficiency of procuring massive mesoscopic datasets from mouse brains. Constrained by the imaging field of view, the image strips obtained by such technologies typically require further processing, such as cr...
Saved in:
| Main Authors: | Hong Zhang, Zhikang Lu, Peicong Gong, Shilong Zhang, Xiaoquan Yang, Xiangning Li, Zhao Feng, Anan Li, Chi Xiao |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2024-12-01
|
| Series: | Brain Informatics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40708-024-00246-7 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Drop-in Replacement for LR(1) Table-Driven Parsing
by: Michael Oudshoorn
Published: (2021-12-01) -
Statistical Learning for Semantic Parsing: A Survey
by: Qile Zhu, et al.
Published: (2019-12-01) -
ACCURACY EVALUATION AND ERROR ANALYSIS OF DEPENDENCY PARSING FOR TEXTS IN UKRAINIAN
by: Костянтин Сироткін
Published: (2025-06-01) -
Parsing costs as predictors of reading difficulty: An evaluation using the Potsdam Sentence Corpus
by: Marisa Ferrara Boston, et al.
Published: (2008-09-01) -
Mesoscopic connectome enters the new age of single‐neuron projectome
by: Ning Li, et al.
Published: (2025-01-01)