Prompt guided multi-organ segmentation of the total body

Motivation: Numerous studies have made significant strides in the field of medical image segmentation. However, most studies have focused on specific localized regions rather than addressing the challenge of unified segmentation across the entire human body. Goal(s): To improve the efficiency and accuracy of disease diagnosis and treatment, continuous advancements in multi-organ segmentation brings great advantages. Approach: In this paper, we present a prompt guided multi-organ segmentation model on total-body images, which can be adapted for CT, PET and MRI modalities. Results: Our extensive experiments demonstrate the superior performance of our model in accurately segmenting 21 organs. Impact: Our research leverages the power of prompts to tackle the challenge of multi-organ segmentation. It has potentially wide applications in the fields of CT, MRI and PET, enabling the simultaneous segmentation of multiple organs and images from diverse modalities.