電腦斷層掃描技術的創新和成長機會

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個工作天內

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簡介目錄

技術進步和相關人員的努力可以提高診斷準確性、降低輻射劑量並降低成本。

電腦斷層掃描 (CT) 是一種先進的成像技術，它結合了從多個角度獲取的 X光測量結果，並使用電腦演算法對其進行處理以產生截面影像或影像。橫斷面影像被進一步重建為器官和組織的 3D 表示，從而實現內部結構的精確可視化。

我們的分析表明，CT 技術已經取得了重大進步，其中包括雙能 CT，它透過使用兩個不同能量水平的 X光束來提供卓越的組織表徵。光子計數 CT (PCT) 使用先進的檢測器來偵測單一 X光光子，從而提高空間解析度、降低背景雜訊並降低輻射劑量。

將人工智慧和機器學習融入 CT 成像中，可增強影像重建、檢測異常並提供更準確的診斷。人工智慧驅動的迭代重建技術有助於實現更好的影像質量，同時降低訊號雜訊比和輻射暴露。

可攜式CT 設備和照護現場CT 設備的出現擴大了 CT 影像診斷的範圍，即使在緊急情況和偏遠地區也能即時進行診斷。 CT技術的進步也顯著改善了患者的預後。

在本報告中，我們將重點放在 PCT 和錐狀射束CT，旨在詳細分析 CT 診斷領域的這些技術進步、當前趨勢、研究進展和未來成長機會。

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