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SKILL verified MIT Self-run

Bio Bioimage Segmentation

skill-onescience-ai-oneskills-bioimage-segmentation · by onescience-ai

生物显微图像分割与定量 skill。用于荧光、明场、相差、3D z-stack 或 time-lapse 图像的 Cellpose、scikit-image、OpenCV、napari 审阅、mask 生成、regionprops 和细胞追踪交接。

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Install

$ agentstack add skill-onescience-ai-oneskills-bioimage-segmentation

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • ✓ Prompt-injection patterns
  • ✓ Secret / credential exfiltration
  • ✓ Dangerous shell & filesystem operations
  • ✓ Untrusted network calls
  • ✓ Known-malicious package signatures

What it can access

  • ✓ Network access No
  • ✓ Filesystem access No
  • ✓ Shell / process execution No
  • ✓ Environment & secrets No
  • ✓ Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

✓ Security review passed
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Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

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About

生物图像分割与定量

使用边界

用于 microscopy image 到 mask、object table 和 QC overlay 的任务。若是病理 WSI tile pipeline，读取 ../digital-pathology-wsi/SKILL.md；若是 FCS event table，读取 ../flow-cytometry-analysis/SKILL.md。

可复用资源

  • onescience-coder/assets/bio_cell_imaging_templates/segmentation_plan.yaml：图像维度、通道、模型、阈值、QC 和输出路径模板。
  • references/segmentation_methods.md：Cellpose、watershed、OpenCV、3D stack、追踪和 QC 选择规则。
  • onescience-coder/assets/bio_cell_imaging_tools/label_mask_measurements.py：对整数 label mask CSV/TSV 和强度表做基础面积/强度汇总的轻量脚本。

推荐流程

  1. 明确图像：文件格式、维度、像素尺寸、通道含义、z/time、bit depth。
  2. 选择方法：rule-based threshold/watershed、Cellpose/nnU-Net、OpenCV contour、Fiji plugin。
  3. 生成 mask：保存整数 label mask，不要只保存彩色 overlay。
  4. QC：原图+边界 overlay、object size distribution、空 mask、merged/split errors、边缘对象。
  5. 量化：area、centroid、shape、mean/max intensity、多通道 marker、track id。
  6. 输出：mask、measurement table、QC figures、参数记录和人工审阅点。

交接物

bio_task_family: cell-imaging-cytometry
cell_task: bioimage-segmentation
image_inputs:
channel_map:
pixel_size:
segmentation_method:
parameters:
qc_review:
measurements:
expected_outputs:
execution_entry:

禁止事项

  • 不要只输出 PNG overlay 而不输出可计算的 label mask。
  • 不要在没有像素尺度时解释真实面积或距离。
  • 不要忽略 3D stack、time-lapse 和多通道图像的轴顺序。

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.

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