01. Intracranial pathology segmentation
Traumatic brain injury is one of the hardest segmentation problems in imaging. Lesions are often multifocal, heterogeneous and poorly defined. The NINDS recognises more than 20 distinct lesion types, and even specialists disagree on how to name them and where their boundaries lie. This complexity makes high-quality voxel-level ground truth scarce, and that scarcity is what holds automated tools back.
I've manually segmented hundreds of CT and MRI studies over more than 10 years, including for an AI system that later received CE marking and FDA clearance. In my academic research I build multi-expert consensus ground truth using STAPLE and study how segmentation methods can be made more reliable. Working on brain injury segmentation has shaped how I segment every other part of the body, with the same scientific rigour.
02. Visceral anatomy segmentation
Thoracic, abdominal and pelvic organs are usually easier to segment than TBI, but not automatic. Anatomy varies between individuals, boundary visibility depends on modality and contrast, and pathology adds further complexity.
I manually segment organs, vessels, muscles and other structures at the level of detail your question needs, from a single organ volume to a lesion mapped against nearby vessels in 3D. Results can be exported as 3D models for surgical planning, research or printing.