Radiologic Technologist Job at iMerit Technology in New York

We are seeking experienced, US-based Radiology Technicians to participate in a medical image segmentation annotation project. This project involves the precise segmentation of lesions identified in CT and MRI studies as part of a rigorous, multi-reader data labeling workflow designed to produce high-quality, adjudicated ground-truth masks for use in AI/ML model development. The project encompasses a total of 480 lesions — 240 CT and 240 MRI — each of which will be independently segmented by three (3) qualified radiology technicians. All completed segmentations will subsequently be reviewed, adjudicated, and if necessary corrected by a US Board-Certified (USBC) Radiologist. Annotation Workflow Step 1: Lesion Selection A US Board-Certified Radiologist will identify and select each lesion for segmentation across all CT and MRI cases. Technicians will work exclusively on pre-identified lesions; independent lesion discovery is not required. Step 2: Independent Segmentation (Technician Task) Each of the 480 lesions will be independently segmented by three (3) US-based Radiology Technicians. Technicians will:

• Review the imaging study containing the designated lesion.
• Perform a careful, slice-by-slice segmentation of the specified lesion boundary.
• Complete work independently, without reference to other technicians' annotations.
• Submit segmentation masks within the designated annotation platform and within agreed

turnaround timelines. Step 3: Consensus & Radiologist Adjudication Following the collection of three independent segmentation masks per lesion, a US Board Certified Radiologist will:

• Review the consensus mask derived from the three submissions.
• Assess segmentation accuracy and agreement.
• Make final adjustments to the segmentation where clinically necessary.

The adjudicated mask will serve as the final ground-truth annotation for the lesion.