Feature Detection and Computer-aided Diagnosis with Longitudinal Tracking of Benign Asbestos-Related Pleural Disease in CT images

CT 图像中良性石棉相关胸膜疾病的纵向跟踪特征检测和计算机辅助诊断

• 批准号: LP0991295
• 负责人: Prof Arcot Sowmya
• 金额: --
• 依托单位: The University of New South Wales
• 依托单位国家: 澳大利亚
• 项目类别: Linkage Projects
• 财政年份: 2010
• 资助国家: 澳大利亚
• 起止时间: 2010-03-31 至 2013-03-30
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/LP0991295
• 关键词: Feature; Detection; Computer; aided; Diagnosis

This project seeks to develop smart and novel feature extraction and knowledge acquisition techniques to assist radiologists in automated diagnosis and assessment of lung diseases. These outcomes will lead to improved delivery of health services in Australia, including in rural regions. They will lead to more accurate assessment of asbestos related pleural diseases for compensation and treatment and better followup, leading to earlier treatment and better quality of life for patients suffering from lung diseases. The project will also save costs due to automated assessment as well as the potential for fewer patient scans.

该项目旨在开发智能和新颖的特征提取和知识获取技术，以帮助放射科医生对肺部疾病进行自动诊断和评估。这些成果将改善澳大利亚的卫生服务，包括农村地区的卫生服务。它们将导致对与石棉有关的胸膜疾病进行更准确的评估，以进行补偿和治疗，并进行更好的跟进，从而使肺部疾病患者能够更早地接受治疗，并提高生活质量。该项目还将节省成本，因为自动评估以及减少患者扫描的可能性。