A Workflow to Visually Assess Interobserver Variability in Medical Image Segmentation.
IEEE Comput Graph Appl
; 44(1): 86-94, 2024.
Article
em En
| MEDLINE
| ID: mdl-38271155
ABSTRACT
We introduce a workflow for the visual assessment of interobserver variability in medical image segmentation. Image segmentation is a crucial step in the diagnosis, prognosis, and treatment of many diseases. Despite the advancements in autosegmentation, clinical practice widely relies on manual delineations performed by radiologists. Our work focuses on designing a solution for understanding the radiologists' thought processes during segmentation and for unveiling reasons that lead to interobserver variability. To this end, we propose a visual analysis tool connecting multiple radiologists' delineation processes with their outcomes, and we demonstrate its potential in a case study.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Algoritmos
Tipo de estudo:
Guideline
Limite:
Humans
Idioma:
En
Revista:
IEEE Comput Graph Appl
Ano de publicação:
2024
Tipo de documento:
Article