Automated scalable segmentation of neurons from multispectral images
Authors: Uygar Sümbül, Douglas Roossien, Dawen Cai, Fei Chen, Nicholas Barry, John P. Cunningham, Edward Boyden, Liam Paninski
NeurIPS 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | To quantify performance and gain insight, we generate simulated images, where the noise level and characteristics, the density of expression, and the number of fluorophore types are variable. We also present segmentations of real Brainbow images of the mouse hippocampus, which reveal many of the dendritic segments. |
| Researcher Affiliation | Academia | Uygar Sümbül Grossman Center for the Statistics of Mind and Dept. of Statistics, Columbia University Douglas Roossien Jr. University of Michigan Medical School Fei Chen MIT Media Lab and Mc Govern Institute Nicholas Barry MIT Media Lab and Mc Govern Institute Edward S. Boyden MIT Media Lab and Mc Govern Institute Dawen Cai University of Michigan Medical School John P. Cunningham Grossman Center for the Statistics of Mind and Dept. of Statistics, Columbia University Liam Paninski Grossman Center for the Statistics of Mind and Dept. of Statistics, Columbia University |
| Pseudocode | Yes | Algorithm 1 Brainbow image stack simulation |
| Open Source Code | No | The paper does not provide any links to its own open-source code or state that the code for their method is publicly available. |
| Open Datasets | Yes | To simulate Brainbow image stacks, we used volumetric single neuron reconstructions of mouse retinal ganglion cells in Algorithm 1. The dataset is obtained from previously published studies [28, 29]. |
| Dataset Splits | No | The paper does not explicitly specify training/validation/test splits for its models or algorithms. It describes evaluations on simulated and real image stacks, but not in terms of how data was partitioned for model training and validation. |
| Hardware Specification | No | The paper does not provide specific details about the hardware (e.g., GPU models, CPU types, memory) used to run the experiments or train the models. |
| Software Dependencies | No | The paper mentions using the "BM4D denoiser [12]" but does not specify version numbers for this or any other software dependencies crucial for replication. |
| Experiment Setup | No | The paper states: "Parameters used in the experiments are reported in Supp. Text." This indicates that the details are not in the main text of the paper. |