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AI-Enhanced Ultrasound Image Segmentation by yuvanikaac is a document available to read on EtoBox.

The study presents a novel AI-assisted framework, MaskHybrid, utilizing a mamba-transformer architecture for the recognition and segmentation of anatomical structures in abdominal ultrasound images. It was developed using a dataset of 34,711 images and demonstrated a mean average precision score of 74.13%, significantly improving segmentation accuracy and inference efficiency compared to existing models. This advancement aims to enhance diagnostic interpretation and facilitate real-time analysis in clinical

Author

yuvanikaac

Language

EN