Automatic Ultrasound Vessel Segmentation with Deep Spatiotemporal Context Learning

Autor:	Baichuan Jiang, Shyam Bharat, Mingxin Zheng, Alvin I. Chen
Rok vydání:	2021
Předmět:	Computer science business.industry Deep learning Ultrasound ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Lumen (anatomy) Pattern recognition Context (language use) Vessel segmentation Context learning Leverage (statistics) Segmentation Artificial intelligence business
Zdroj:	Simplifying Medical Ultrasound ISBN: 9783030875824 ASMUS@MICCAI
Popis:	Accurate, real-time segmentation of vessel structures in ultrasound image sequences can aid in the measurement of lumen diameters and assessment of vascular diseases. This, however, remains a challenging task, particularly for extremely small vessels that are difficult to visualize. We propose to leverage the rich spatiotemporal context available in ultrasound to improve segmentation of small-scale lower-extremity arterial vasculature. We describe efficient deep learning methods that incorporate temporal, spatial, and feature-aware contextual embeddings at multiple resolution scales while jointly utilizing information from B-mode and Color Doppler signals. Evaluating on femoral and tibial artery scans performed on healthy subjects by an expert ultrasonographer, and comparing to consensus expert ground-truth annotations of inner lumen boundaries, we demonstrate real-time segmentation using the context-aware models and show that they significantly outperform comparable baseline approaches.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::104c0f806a8ceba0a5d47d36b2a97d62 https://doi.org/10.1007/978-3-030-87583-1_1 Zobrazit plný text záznamu