Releases: Juaco2r/PathoImage-Toolkit
Release list
PathoImage Toolkit v2.0
PathoImage Toolkit is the evolution and rebranding of TiffCropper, expanding the original WSI crop, tile, and merge functionality into a broader desktop utility for digital pathology and microscopy image workflows.
This release represents a major evolution of the project, with expanded support for whole-slide images, multichannel microscopy data, OME-TIFF metadata, Leica LIF files, annotations, image visualization, and large-image processing.
Highlights
Whole-slide image workflows
- Whole Slide Image (WSI) visualization and preview
- Interactive ROI cropping
- Fixed-size tiling
- Row/column-based image division
- Tile reconstruction and image merging
- Image downsampling
- Improved handling of very large images and memory-intensive workflows
Microscopy and multichannel imaging
- Multichannel image support
- Channel visualization and preview controls
- Support for fluorescence and microscopy image workflows
- Leica LIF image splitting and conversion
OME-TIFF and metadata
- OME-TIFF support
- Preservation of spatial calibration and pixel-size metadata when available
- Improved handling of image metadata during crop, tile, merge, and downsampling operations
- Support for pyramidal TIFF workflows
Annotation workflows
- GeoJSON annotation loading and visualization
- Annotation editing and export
- Integration of annotations with image preview and ROI workflows
Image format support
PathoImage Toolkit supports multiple digital pathology and microscopy image formats, including:
- TIFF / pyramidal TIFF
- OME-TIFF
- SVS
- NDPI
- MRXS
- Leica LIF
- JPEG
- PNG
- Additional formats supported through the available image-reading backends
Project transition
Previous releases of this project were distributed as TiffCropper.
The original software focused primarily on WSI cropping, tiling, and reconstruction. As the application expanded to include microscopy, multichannel imaging, OME-TIFF processing, Leica LIF conversion, GeoJSON annotations, metadata preservation, and additional image-processing utilities, the project was renamed PathoImage Toolkit to better reflect its broader scope.
Previous release
TiffCropper v1.2
The historical TiffCropper release remains permanently archived on Zenodo under its original name and DOI.
Current release
PathoImage Toolkit v2.0
Starting with this release, the project is distributed and maintained as PathoImage Toolkit.
Repository
https://github.com/Juaco2r/PathoImage-Toolkit
License
MIT License
Author
José Rodriguez-Rojas
TiffCropper v1.3
Stable public release of TiffCropper, a standalone application for cropping, tiling, previewing, and reconstructing large digital pathology and microscopy images.
TiffCropper supports high-resolution ROI extraction, fixed-size tile generation, row/column image division, tile merging workflows, pyramid-aware previews, and basic IF threshold exploration.
Highlights
- Support for TIFF, pyramidal TIFF, OME-TIFF, SVS, NDPI, MRXS, JPEG, and PNG
- ROI cropping with exact pixel-coordinate control
- Interactive crop selection from image preview
- Full-image export and downsampling options
- Fixed-size tile generation with optional overlap
- Row/column-based image division
- Bulk tiling for multiple images
- Automatic and manual tile merging
- BigTIFF output for large crops, tiles, and merged images
- OME-TIFF export with physical pixel size preservation when available
- Correct physical pixel size scaling after downsampling
- Improved calibration preservation for OME-TIFF and IF crops
- Pyramid-aware preview for large images
- Safer handling of very large crop regions
- Improved RGB/Samples-axis TIFF handling during crop export
- Memory-safer merge and padding operations
- Optional lossless DEFLATE compression
- Batch tiling CSV logs
- New IF Cell / Tissue Threshold Explorer
- Fast IF threshold visualization using QuPath measurements CSV files
- Lightweight SQLite cache for large GeoJSON cell overlays
- Overlay toggle for quick comparison with the raw image
- More compact interface for Linux and smaller screens
- Help/About dialog with citation, DOI, supported formats, and usage notes
- Windows executable designed to run without a separate Python installation
IF Threshold Explorer
Version 1.3 introduces an experimental IF threshold exploration mode for fluorescence microscopy workflows.
The module can use:
- A multichannel IF image, such as OME-TIFF
- A cell GeoJSON file
- An optional QuPath measurements CSV file
When a QuPath CSV is provided, TiffCropper can use existing cell-level measurements such as:
Cell: FAP (C2): Mean
Cell: aSMA (C3): Mean
Cell: Cancer (C4): Mean
This allows fast visual testing of positivity thresholds without recalculating intensities from the image.
Crop and Preview Improvements
Version 1.3 improves crop preview and export behavior for very large images.
The preview system now attempts to use available pyramid or overview levels before falling back to full-resolution access. This improves responsiveness for large TIFF, pyramidal TIFF, and OME-TIFF images.
Crop export was also updated to better preserve calibration metadata and avoid unsafe memory allocation for very large regions.
Tiling and Merge
TiffCropper supports two tiling strategies:
- Fixed square tiles with optional overlap.
- Row/column division for structured rectangular tiling.
Merge mode can reconstruct tiled images using encoded filenames or manual grid assignment.
The merge operation is geometric and does not perform image registration or intelligent stitching.
Included in this Release
TiffCropper-Windows.zip→ Windows executable packageTiffCropper-Linux.tar.gz→ Linux artifact, when generated successfullyTiffCropper-macOS.zip→ macOS artifact, when generated successfully- Source code
README.mdLICENSECITATION.cffrequirements.txtTHIRD_PARTY_NOTICES.md, when included
No installation is required for the Windows executable.
Simply extract the package and run:
TiffCropper.exe
Notes
- Raw IF crops and tiles are saved without intensity normalization.
- Using a QuPath measurements CSV is recommended for faster IF threshold exploration.
- Existing crops generated with older versions may need to be regenerated if calibration metadata was not preserved correctly.
- The merge operation does not perform image registration.
TiffCropper v1.2
Stable public release of TiffCropper, a standalone application for cropping, tiling, and reconstructing large digital pathology and microscopy images.
TiffCropper supports high-resolution ROI extraction, fixed-size tile generation, row/column-based image division, and tile merging workflows for Whole Slide Images (WSI) and large microscopy files.
Highlights
- Support for TIFF, pyramidal TIFF, OME-TIFF, SVS, NDPI, MRXS, JPEG, and PNG
- ROI cropping with exact pixel-coordinate control
- Interactive crop rectangle selection from the image preview
- Full-image area selection for whole-slide export or downsampling
- Fixed-size square tile generation with optional overlap
- Row/column-based image division for structured tiling
- Bulk tiling of multiple images using the same parameters
- Automatic tile merging from encoded tile names
- Manual grid-based tile merging when filenames do not encode position
- OME-TIFF export with physical pixel size preservation when available
- Correct scaling of physical pixel size metadata after downsampling
- Calibration metadata reuse during merge when available
- Optional lossless DEFLATE compression
- BigTIFF output for large crops, tiles, and merged images
- Pyramid-aware preview for large images
- Robust OpenSlide fallback strategy for partially corrupted pyramid blocks
- Memory-safer external padding crop during merge
- Batch tiling CSV logs
- Help/About dialog with citation, DOI, supported formats, and usage notes
- Windows executable designed to run without a separate Python installation
Designed for Digital Pathology Workflows
TiffCropper enables precise pixel-level cropping, tiling, and reconstruction while preserving relevant calibration metadata when available.
The application can preserve or propagate:
- Resolution metadata, such as DPI
- Physical pixel size, such as µm per pixel
- OME-TIFF physical size metadata
- OpenSlide scanner metadata, embedded as OME MapAnnotations when exporting OME-TIFF
- Tile coordinate information in output filenames
When crops or tiles are downsampled, TiffCropper updates the physical pixel size accordingly. For example, if the original image has a pixel size of 0.25 µm/px and the output is saved with downsample 2, the resulting pixel size is written as 0.50 µm/px.
Tiling and Merge Improvements
TiffCropper v1.2 supports two tiling strategies.
Fixed square tiles
The image is divided into square tiles of a user-defined size. Optional overlap can be applied between neighboring tiles.
Padding is applied only to true border tiles. Internal tiles are extracted as direct crops to avoid introducing artificial black or white padding inside the image.
Divide image by rows/columns
The image can also be divided into a user-defined number of rows and columns. This mode may generate rectangular tiles and does not add artificial padding.
Tile names include row, column, division grid size, and original pixel coordinates to support traceability and reconstruction.
Merge mode
Merge mode can reconstruct tiled images using either automatic filename parsing or manual grid assignment.
The merge operation is geometric. It does not perform image registration or intelligent stitching. For best results, merge tiles generated from the same source image using the same tile size, overlap, and downsample settings.
Included in this Release
TiffCropper-Windows.zip→ Windows executable packageTiffCropper-Linux.tar.gz→ Linux artifactTiffCropper-macOS.zip→ macOS artifact, when generated successfully- Source code
README.mdLICENSECITATION.cffrequirements.txtTHIRD_PARTY_NOTICES.md, when included
No installation is required for the Windows executable.
Simply extract the package and run:
TiffCropper.exe
Tiff Cropper v1.0
TiffCropper v1.0
First stable public release of TiffCropper, a standalone Windows application for high-resolution ROI extraction from Whole Slide Images (WSI).
Highlights
- Support for TIFF, OME-TIFF, and NDPI
- OME-TIFF export with physical size preservation
- Optional lossless DEFLATE compression
- BigTIFF output for large regions
- Pyramid-aware interactive preview
- Robust fallback strategy for partially corrupted pyramid tiles
- Fully offline executable (no Python required)
🔬 Designed for Digital Pathology Workflows
TiffCropper enables precise pixel-level cropping while preserving:
- Resolution metadata (DPI)
- Physical pixel size (µm per pixel)
- NDPI scanner metadata (embedded as OME MapAnnotations when exporting OME-TIFF)
The application handles large multi-gigapixel WSIs efficiently using block-based reading and tiled output writing.
📦 Included in this Release
TiffCropper.zip→ Windows executable packageTiffCropper_Protocol_v1.0.pdf→ Full user and technical protocol
No installation required.
Simply extract and run TiffCropper.exe.
🖥 System Requirements
- Windows 10 / 11
- ≥ 4 GB RAM (≥ 16 GB recommended for large WSI)
📜 License
MIT License
© 2026 Jose Rodriguez-Rojas