Automatic Detection of Pulmonary Embolism using Computational Intelligence

2007/06/03 by Simon John Scurrell, Simon Scurrell, Scurrell, Simon +4
Computer Science · Engineering · Environmental Science · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Fault Detection and Control Systems #Flow Measurement and Analysis #Hydrological Forecasting Using AI #cs.CV

paper · pdf · doi:10.48550/arxiv.0706.0300

5 pages

arxiv created 2007/06/03 · openalex publication_date 2007/06/03 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

This article describes the implementation of a system designed to automatically detect the presence of pulmonary embolism in lung scans. These images are firstly segmented, before alignment and feature extraction using PCA. The neural network was trained using the Hybrid Monte Carlo method, resulting in a committee of 250 neural networks and good results are obtained.

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