Improving assessment of lesions in longitudinal CT scans: a bi-institutional reader study on an AI-assisted registration and volumetric segmentation workflow.
Alessa HeringMax WestphalAnnika GerkenHaidara AlmansourMichael MaurerBenjamin GeislerTemke KohlbrandtThomas EigentlerTeresa AmaralNikolas LessmannSergios GatidisHorst HahnKonstantin NikolaouAhmed OthmanJan MoltzFelix PeisenPublished in: International journal of computer assisted radiology and surgery (2024)
The findings of this study support the use of AI-assisted registration and volumetric segmentation for lymph node and soft tissue metastases in follow-up CT scans. The AI-assisted workflow achieved significant time savings, similar segmentation quality, and reduced inter-reader variability compared to manual segmentation.
Keyphrases
- deep learning
- computed tomography
- convolutional neural network
- lymph node
- artificial intelligence
- contrast enhanced
- dual energy
- soft tissue
- magnetic resonance imaging
- positron emission tomography
- radiation therapy
- machine learning
- magnetic resonance
- squamous cell carcinoma
- early stage
- pet ct
- sentinel lymph node
- rectal cancer
- locally advanced