CIMA histology images
This dataset provides user‑generated landmark annotations for CIMA histology images, containing 2D tissue micro‑sections stained with different methods. Challenges include extremely large image sizes, visual heterogeneity, and lack of salient objects. The dataset includes 108 image portions with manually placed landmarks for registration quality assessment.
Dataset description and usage context
Dataset Overview
Dataset Name
Dataset: histology landmarks
Dataset Content
The dataset contains 2D tissue micro‑section images stained by various methods. It is mainly used to assess registration quality and includes 108 images with manually placed landmarks.
Image Characteristics
- Image Size: Extremely large
- Visual Heterogeneity: Significant
- Lack of Salient Objects: Yes
Landmark Information
- Structure: Follows ImageJ standard structure and coordinate framework
- Origin: Upper‑left corner of the image plane [0, 0]
- Tools: Simple macros are provided for importing and exporting landmarks
- File Layout: Each image has a corresponding
.csvfile stored in the same directory
Dataset Structure
DATASET |- [set_name1] | |- scale-[number1]pc | | |- [image_name1].jpg | | |- [image_name1].csv | | |- [image_name2].jpg | | |- [image_name2].csv | | | ... | | |- [image_name].jpg | | - [image_name].csv | |- scale-[number2]pc | | ... | - scale-[number]pc | |- [image_name1].png | |- [image_name1].csv | | ... | |- [image_name].png | - [image_name].csv |- [set_name2] | ...
- [set_name]
Landmark Generation and Visualization
- Generation: Use
python handlers/run_generate_landmarks.pyscript - Visualization: Use
python handlers/run_visualise_landmarks.pyscript
Annotation Details
- Initial Annotations: Aggregated landmark sets placed by multiple users
- Additional Annotations: Aimed at improving precision by comparing landmarks across differently stained images
Annotation Structure
ANNOTATIONS |- [set_name1] | |- user-[initials1]_scale-[number2]pc | | |- [image_name1].csv | | |- [image_name2].csv | | | ... | | - [image_name].csv | |- user-[initials2]_scale-[number1]pc | | ... | |- user-[initials]_scale-[number]pc | | |- [image_name2].csv | | | ... | | - [image_name].csv |- [set_name2] | ...
- [set_name]
Validation Process
- Visual Check: Preliminary validation by comparing deformation of landmark pairs
- Error Analysis: Compute inter‑landmark error; pairs exceeding a threshold are flagged as suspicious
References
J. Borovec, A. Muñoz‑Barrutia, and J. Kybic, “Benchmarking of image registration methods for differently stained histological slides” in 2018 25th IEEE International Conference on Image Processing (ICIP), p. 3368‑3372, 2018. DOI: 10.1109/ICIP.2018.8451040
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