OSCR

NeuroSeg-MF: robust neuron segmentation in two-photon Ca<sup>2+</sup> imaging using multi-feature fusion and detection-guided SAM.

Code ↔ Paper

11 matches between paragraphs of the paper and lines of its authors' code, computed by the harvester (lexical-v1). Click a colored paragraph or line to see its counterpart.

The 11 matches
  1. [1] § Materials and methods › Framework of NeuroSeg-MF › Multi-feature detection network ↔ ultralytics/nn/tasks.py, lines 1778–1920 · score 0.80 · basic block, GateFusion, A2C2f, RT DETR, AIFI, global
  2. [2] § Materials and methods › Framework of NeuroSeg-MF › Multi-feature detection network ↔ ultralytics/nn/modules/__init__.py, lines 37–71 · score 0.80 · RepConv, basic block, GateFusion, A2C2f, AIFI, decoder
  3. [3] § Materials and methods › Image preprocessing › Data augmentation ↔ ultralytics/data/augment.py, lines 2649–2750 · score 0.76 · horizontal flipping, Random erasing, jitter, augmentation, HSV, probability
  4. [4] § Materials and methods › Framework of NeuroSeg-MF › Multi-feature detection network ↔ ultralytics/nn/modules/__init__.py, lines 37–71 · score 0.74 · RepConv, BasicBlock, GateFusion, A2C2f, AIFI, decoder
  5. [5] § Materials and methods › Framework of NeuroSeg-MF › Detection-guided SAM for neuron segmentation ↔ tools/SAM_box_to_mask.py, lines 1–65 · score 0.74 · candidate masks generated, binary masks, box prompt, segmentation masks, overlays, bounding boxes
  6. [6] § Materials and methods › Framework of NeuroSeg-MF › Multi-feature detection network ↔ ultralytics/nn/tasks.py, lines 1778–1920 · score 0.74 · BasicBlock, GateFusion, A2C2f, RT DETR, AIFI, architecture
  7. [7] § Materials and methods › Framework of NeuroSeg-MF › Detection-guided SAM for neuron segmentation ↔ tools/SAM_box_to_mask.py, lines 1–65 · score 0.64 · generate candidate masks, box prompt, detection box, scores, predicted, neuron
  8. [8] § Materials and methods › Image preprocessing › Pseudo-depth map ↔ tools/generate_depth_twophoton.py, lines 61–145 · score 0.56 · bit grayscale, pseudo depth map
  9. [9] § Materials and methods › Evaluation metrics ↔ ultralytics/utils/coco_metrics.py, lines 282–404 · score 0.51 · IoU threshold, F1 score, recall, precision, metrics, predicted
  10. [10] § Materials and methods › Image preprocessing › Pseudo-depth map ↔ tools/generate_depth_twophoton.py, lines 61–145 · score 0.50 · pseudo depth map, smoothing, V2, filtering, clipping, resized
  11. [11] § Materials and methods › Image preprocessing › Correlation map ↔ tools/generate_corr.py, lines 404–483 · score 0.50 · local neighborhood, correlation map, frames, pixels

Paper

Loaded from Europe PMC by your browser, not stored by OSCR: doi.org · Europe PMC

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The authors' code

Python · 2,035 lines · 82 KB · no license · 2 matches

The registry keeps no copy of this file: its repository has no license, so its authors keep all their rights to it. Your browser shows it from its source, with JavaScript.

It can be read at the source: ultralytics/nn/tasks.py.

Overview

Authors: Zhehao Xu1, Weiyi Liu2, Shanshan Liang2, Hongbo Jia3,4, Xiaowei Chen2,5, Han Qin5, Xiang Liao1
ORCID iDs: Xiang Liao
  1. Center for Neurointelligence, School of Medicine, Chongqing University, Chongqing 400030, China
  2. Brain Research Center, State Key Laboratory of Trauma and Chemical Poisoning, Third Military Medical University, Chongqing 400038, China
  3. Jiangsu Key Laboratory for Advanced Theranostics and Medical Instrumentation, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, Jiangsu, China
  4. Leibniz Institute for Neurobiology, Magdeburg 39118, Germany
  5. LFC Laboratory (Chongqing Key Laboratory of Brain and Aerospace Intelligence) and Chongqing Institute for Brain and Intelligence, Guangyang Bay Laboratory, Chongqing 400064, China
Institutions: Chongqing University (China); Army Medical University (China); Chinese Academy of Sciences (China); Suzhou Institute of Biomedical Engineering and Technology (China); Leibniz Institute for Neurobiology (Germany)
Journal: Biomedical optics express, volume 17, issue 7, pages 3727-3746
Dates: received 31 March 2026; accepted 9 June 2026; published online 17 June 2026
Type: Research article · Language: English
License: none stated
Identifiers: DOI 10.1364/boe.600665 · PMID 42460356 · PMCID PMC13372336 · OpenAlex W7164500274
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: optical imaging (calcium, voltage, 2-photon) (modality), methods / tools (subfield)
Methods: Statistics, Machine learning, Connectivity, fMRI & imaging
Topic: Advanced Fluorescence Microscopy Techniques (Biophysics, Biochemistry, Genetics and Molecular Biology), according to OpenAlex
Funding: National Natural Science Foundation of China (32171096, 32127801)
Citations: cited by 1 paper (Europe PMC); 57 references in the paper

Abstract

The abstract is not reproduced here: the paper's license (none stated) does not allow it. Read it in the paper, at the publisher or on Europe PMC.

Repository

Its files are read in the Code ↔ Paper reader above, with 11 matches between paragraphs and lines of code.

XZH-James/NeuroSeg-MF

License: none: the authors keep all their rights
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: 4bfb1ef734acd2fa90b44960980d6233d71ed7cb, 16 June 2026
Languages: Python (100)
Size: 108 files, 100 scripts
Software Heritage: not archived
Found in: the references
Holds: README, environment (requirements.txt)
Not found: license file, CITATION.cff, tests, continuous integration, documentation
Tools: PyTorch (56 files), NumPy (39 files), OpenCV (20 files), Pillow (10 files), Matplotlib (5 files), pandas (4 files), SciPy (4 files), tifffile (2 files), seaborn (1 file), TensorFlow (1 file)
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
101 files, not copied: shown from their source

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At the source: github.com/XZH-James/NeuroSeg-MF

The paper's code and data availability statement is in the Data section.

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 100 scripts, each with its path and the digest of its content;
  • 11 matches between paragraphs of the paper and lines of the code (method lexical-v1);
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

No dataset and no data link were found in the paper.

Code and data availability statement

The paper has a code and data availability statement. Its license (none stated) does not allow reproducing it here; in short, from what the harvester recognized in it:

  • it says that the data are available on request

Read it in the paper: doi.org/10.1364/boe.600665.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 7 authors, 1 funder, 45 references.

Cite

This paper

Xu, Z., Liu, W., Liang, S., Jia, H., Chen, X., Qin, H., & Liao, X. (2026). NeuroSeg-MF: robust neuron segmentation in two-photon Ca<sup>2+</sup> imaging using multi-feature fusion and detection-guided SAM. Biomedical optics express, 17(7), 3727-3746. https://doi.org/10.1364/boe.600665

BibTeX

@article{xu2026neuroseg,
author = {Xu, Zhehao and Liu, Weiyi and Liang, Shanshan and Jia, Hongbo and Chen, Xiaowei and Qin, Han and Liao, Xiang},
title = {{NeuroSeg-MF: robust neuron segmentation in two-photon Ca\<sup\>2+\</sup\> imaging using multi-feature fusion and detection-guided SAM}},
journal = {Biomedical optics express},
year = {2026},
month = jun,
volume = {17},
number = {7},
pages = {3727--3746},
publisher = {Optica Publishing Group},
issn = {2156-7085},
doi = {10.1364/boe.600665},
url = {https://doi.org/10.1364/boe.600665},
pmid = {42460356},
pmcid = {PMC13372336}
}

RIS

TY - JOUR
AU - Xu, Zhehao
AU - Liu, Weiyi
AU - Liang, Shanshan
AU - Jia, Hongbo
AU - Chen, Xiaowei
AU - Qin, Han
AU - Liao, Xiang
TI - NeuroSeg-MF: robust neuron segmentation in two-photon Ca<sup>2+</sup> imaging using multi-feature fusion and detection-guided SAM
T2 - Biomedical optics express
J2 - Biomed Opt Express
PY - 2026
DA - 2026/06/17
VL - 17
IS - 7
SP - 3727
EP - 3746
SN - 2156-7085
PB - Optica Publishing Group
DO - 10.1364/boe.600665
UR - https://doi.org/10.1364/boe.600665
LA - en
ER -

CSL-JSON

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