Application/API Based Artificial Intelligence Enhanced Analysis Of Pulmonary Emphysema Using Computed Tomography Imaging Of Thorax
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 发起方
- 入组人数
- 80
- 试验地点
- 1
- 主要终点
- To detect the presence of emphysema using AI-driven analysis of CT scans of thorax
研究概览
简要总结
The invention provides a novel, AI-powered solution for the automated detection and quantification of emphysema using CT thorax imaging. Emphysema, a major component of Chronic Obstructive Pulmonary Disease (COPD), is traditionally assessed through manual interpretation of CT scans, which is time-consuming, subjective, and prone to interobserver variability. This invention addresses these limitations by introducing an application/API module that integrates advanced AI algorithms with existing medical imaging systems.
The core of the invention is an AI-based mobile application and API interface designed to process CT thorax images, enabling precise analysis of lung parenchyma. The AI algorithms are trained on extensive datasets to detect subtle patterns of emphysema, classify subtypes, and provide quantitative metrics of disease severity and progression. Results are delivered in real time, ensuring prompt feedback for clinical decision-making.
The system is equipped with a user-friendly mobile interface that facilitates seamless uploading of CT images, real-time processing via cloud-based infrastructure, and intuitive presentation of results. It is scalable, adaptable to diverse healthcare settings, and supports integration with existing imaging workflows, enabling widespread adoption. Additionally, the invention provides opportunities for use in telemedicine, remote consultations, and longitudinal disease monitoring.
This invention offers a transformative approach to emphysema assessment, improving diagnostic accuracy, reproducibility, and efficiency. It aligns with the evolving needs of precision medicine in respiratory care and contributes to advancements in clinical practice, research, and patient outcomes.
研究设计
- 研究类型
- Observational
入排标准
- 年龄范围
- 15.00 Year(s) 至 90.00 Year(s)（—）
- 性别
- All
入选标准
- •1.Population Criteria: Individuals at varying stages of emphysema risk, including patients with existing CT scans and relevant data.
- •2.Medical History: Patients with complaints of new onset of breathlessness/documented respiratory conditions (including emphysema and related lung diseases) 3.CT Scan Data: High-quality CT scans showing clear lung structures.
- •4.Patients of both gender.
- •5.Patients who have provided informed consent to participate in the study.
排除标准
- •1.Patients who are pregnant.
- •2.Individuals with other chronic diseases, such as cancer, auto-immune disorders which might affect the study results, will not be included.
- •3.Patients with surgical history (especially involving the thorax) 4.Individuals with CT Scans of poor quality or artifacts that may compromise accurate assessment of lung parenchyma.
- •5.Patients who are unable to provide informed consent or participate in the study due to cognitive impairment, language barriers, or other reasons.
- •6.Patients who are not willing to be part of the study.
结局指标
主要结局
To detect the presence of emphysema using AI-driven analysis of CT scans of thorax
时间窗: 24 hours
次要结局
- To assess the accuracy and clinical utility of the AI model.(1 week.)
研究者
Michael Antony Vikram
Saveetha Medical College And Hospital, Saveetha Institute Of Medical And Technical Sciences