@inproceedings{f8e519261f054a0bbd90fdea280801bb,
title = "Applying Attention Mechanism and Deep Neural Network for Medical Object Segmentation and Classification in X-Ray Fluoroscopy Images",
abstract = "We study how to apply attention mechanism and deep neural network for real-time segmentation and classification of balloon objects from X-ray fluoroscopy images during percutaneous balloon compression (PBC) surgical procedures. Fast and accurate identification of balloon shape and its relative location to the Meckel{\textquoteright}s cave can be of significant benefit to the success of the PBC procedure. In this work, we combine the most successful region-based convolutional neural network pipeline with attention mechanism to address these challenges. {\textcopyright} 2019, Springer Nature Singapore Pte Ltd.",
keywords = "Attention mechanism, Convolutional neural network, Deep learning, Percutaneous balloon compression",
author = "Yong Zhang and Jun Yan and Haitao Huang and Christopher Yencha",
year = "2019",
doi = "10.1007/978-981-15-1398-5\_7",
language = "English",
isbn = "9789811513978",
series = "Communications in Computer and Information Science",
publisher = "Springer Singapore",
pages = "101--110",
editor = "An Zeng and Dan Pan and Tianyong Hao and Daoqiang Zhang and Yiyu Shi and Xiaowei Song",
booktitle = "Human Brain and Artificial Intelligence - First International Workshop, HBAI 2019, held in Conjunction with IJCAI 2019",
address = "Singapore",
note = "1st International Workshop on Human Brain and Artificial Intelligence (HBAI 2019), held in conjunction with the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), IJCAI-HBAI 2019 ; Conference date: 12-08-2019",
}