SoreLogic
Wound imaging, LiDAR-supported 3D capture, tissue segmentation and longitudinal follow-up.
Segmentation Benchmarking source code
Review the public benchmark code, training workflow and evaluation protocol used in the SoreLogic research programme.
SoreLogic is the wound-imaging research case examined in detail on this portal. It covers standardized image capture, LiDAR-supported spatial measurement, image segmentation and longitudinal assessment. The work is presented for research and decision support, not autonomous diagnosis.
- 01
- Standardized image capture creates a comparable visual record across follow-up visits.
- 02
- LiDAR and depth information provide a three-dimensional context for area, perimeter, depth and volume research.
- 03
- The segmentation workflow separates the wound region from its surroundings and then studies tissue classes within the wound bed.
- 04
- Longitudinal views support side-by-side comparison and change tracking over time.
- 05
- Open-source benchmarking software and the restricted-access Amatis dataset remain legally and technically separate.
- 06
- Outputs are positioned as research and decision-support material rather than autonomous clinical conclusions.
Research areas
The research areas explain image acquisition, measurable spatial information, segmentation methods and the boundary between public software and restricted-access data.
Image acquisition and follow-up
A consistent capture workflow preserves visual history and makes observations from different dates easier to compare.
LiDAR-supported spatial capture
Depth-aware 3D capture adds geometric context to conventional images for measurement and reconstruction research.
Segmentation and tissue analysis
The research pipeline studies wound boundaries first and tissue regions second, with common metrics used to compare model behaviour.
Data and governance
Public source code can be reviewed openly; wound images and masks are handled as a distinct restricted-access research resource.
From capture to follow-up
Product views illustrate how spatial capture, image analysis and longitudinal comparison meet in the same workflow.
LiDAR-supported 3D capture
Segmentation and analysis
