电脑断层扫描技术的创新和成长机会

Computed Tomography Technology Innovations and Growth Opportunities

出版日期: 2024年07月23日 | 出版商:

Frost & Sullivan | 英文 58 Pages | 商品交期: 最快1-2个工作天内

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简介目录

技术进步和相关人员的努力可以提高诊断准确性、降低辐射剂量并降低成本。

电脑断层扫描 (CT) 是一种先进的成像技术，它结合了从多个角度获取的 X 射线测量结果，并使用电脑演算法对其进行处理以产生截面影像或影像。横断面影像被进一步重建为器官和组织的 3D 表示，从而实现内部结构的精确可视化。

我们的分析表明，CT 技术已经取得了重大进步，其中包括双能 CT，它透过使用两个不同能量水平的 X 射线束来提供卓越的组织表征。光子计数 CT (PCT) 使用先进的检测器来侦测单一 X 射线光子，从而提高空间解析度、降低背景杂讯并降低辐射剂量。

将人工智慧和机器学习融入 CT 成像中，可增强影像重建、检测异常并提供更准确的诊断。人工智慧驱动的迭代重建技术有助于实现更好的影像质量，同时降低讯号杂讯比和辐射暴露。

可携式CT 设备和照护现场CT 设备的出现扩大了 CT 影像诊断的范围，即使在紧急情况和偏远地区也能即时进行诊断。 CT技术的进步也显着改善了患者的预后。

在本报告中，我们将重点放在 PCT 和锥状射束CT，旨在详细分析 CT 诊断领域的这些技术进步、当前趋势、研究进展和未来成长机会。

Computed tomography (CT) is a sophisticated imaging technology that combines X-ray measurements obtained from multiple angles and processes them using computer algorithms to generate cross-sectional images or tomograms. The tomograms are further reconstructed into a 3D representation of organs or tissues, allowing precise visualization of the internal structures.

Frost & Sullivan's analysis shows that CT technology has experienced significant advancements, including dual-energy CT, which provides superior tissue characterization by using 2 X-ray beams with different energy levels. Photon counting CT (PCCT) uses advanced detectors to detect individual X-ray photons, resulting in improved spatial resolution, reduced background noise, and lower radiation doses.

Integrating artificial intelligence and machine learning into CT imaging enhances image reconstruction, detects anomalies, and provides more accurate diagnosis. AI-powered iterative reconstruction techniques help achieve better image quality while reducing the signal-to-noise ratio and radiation exposure.

The emergence of portable and point-of-care CT units has expanded the accessibility of CT imaging, enabling immediate diagnostic capabilities in emergency settings and remote locations. Fast-advancing CT technology has also significantly improved patient outcomes.

In this report, Frost & Sullivan aims to provide an in-depth analysis of these technological advancements, focusing on PCCT and cone beam CT, their current trends, research improvements, and future growth opportunities in the CT diagnostics space.

Strategic Imperatives

Why Is It Increasingly Difficult to Grow?
The Strategic Imperative 8™
The Impact of the Top 3 Strategic Imperatives on the Computed Tomography Industry
Growth Opportunities Fuel the Growth Pipeline Engine™
Research Methodology

Growth Opportunity Analysis

Scope of Analysis
Segmentation

Growth Generator

Growth Drivers
Growth Restraints

Technology Analysis

CT Technology Introduction and Attributes
CT System Components

PCCT Technology Analysis

Energy Integrating Detectors and PCDs: Technology Comparison

PCCT Technology Landscape

Siemens Healthineers, Germany
NeuroLogica Corp., United States
Primary Companies in the PCCT Landscape
Intellectual Property Trends, 2020-2024
Analysis of Intellectual Property Trends, 2020-2024

PCCT Stakeholders' Initiatives

Major Funding Supporting PCCT R&D, Global, 2020-2024
Strategic Collaborations, Research Partnerships, Mergers, and Acquisitions in the PCCT Landscape
PCCT: A Technology Road Map

CBCT Technology Analysis

CBCT: A Technology Overview

CBCT Technology Landscape

Koning Health, United States
Planmed Oy, Finland
Primary Companies in the CBCT Landscape
Intellectual Property Trends, 2020-2024
Analysis of Intellectual Property Trends, 2020-2024

CBCT Stakeholders' Initiatives

Major Funding Supporting CBCT R&D, Global, 2020-2024
Strategic Collaborations, Mergers, and Acquisitions in the CBCT Landscape
CBCT: A Technology Road Map

Growth Opportunity Universe in CT Technology Innovations

Growth Opportunity 1: Portable and Point-of-care Imaging
Growth Opportunity 2: Advanced Image Reconstruction for Enhancing CT Diagnostic Accuracy
Growth Opportunity 3: Hybrid Imaging Systems for Comprehensive Diagnostics