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Computed Tomography Course
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Computed Tomography Course

4.4

Master the full scope of computed tomography — from X-ray physics and image reconstruction to advanced dual-energy techniques and AI-driven workflows. This course equips radiologic technologists and imaging professionals with the technical depth and clinical judgment needed to perform at the highest level. Build expertise that directly improves patient safety, image quality, and diagnostic outcomes.

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What you will learn:

This course covers the foundational physics of CT imaging, including X-ray attenuation, Hounsfield units, and scanner geometry. You will master image reconstruction algorithms, from filtered back-projection to deep learning methods, and learn to identify and correct common CT artefacts. Radiation dose quantification, contrast media management, and protocol design for the head, chest, abdomen, and cardiac regions are addressed in detail. Advanced topics include dual-energy CT, photon-counting detectors, CT perfusion, and 3D post-processing techniques. You will also explore quality assurance, radiation protection regulations, and emerging AI applications in CT workflow.

How you study practically Computed Tomography Course

How you practise Computed Tomography Course

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Course content

8 Chapters • 32 LessonsDuration between 4 and 360 hours (you decide)

Chapter 1See details

Foundations of CT Imaging

  • Lesson 1 • CT Scanner Components and Geometry

    Identifies gantry, detector array, and X-ray tube roles. Connects hardware configuration to image acquisition geometry and scan performance.

  • Lesson 2 • X-Ray Physics and Attenuation

    Covers photon interactions with matter and attenuation coefficients. Provides the physical basis for understanding how CT detectors capture transmitted radiation.

  • Lesson 3 • Hounsfield Units and Tissue Contrast

    Defines the CT number scale and its relationship to tissue density. Links attenuation values to clinical tissue differentiation across organ systems.

  • Lesson 4 • Data Acquisition and Sampling

    Explains projection data collection and angular sampling requirements. Establishes how raw data density affects spatial resolution and image quality.

Chapter 2See details

Image Reconstruction Techniques

  • Lesson 1 • Deep Learning Reconstruction

    Examines neural network-based reconstruction and denoising pipelines. Positions AI reconstruction within the broader evolution of image quality optimisation.

  • Lesson 2 • Iterative Reconstruction Methods

    Covers statistical and model-based iterative algorithms and their noise-reduction advantages. Connects iterative methods to dose reduction strategies in clinical practice.

  • Lesson 3 • Filtered Back-Projection Fundamentals

    Introduces the mathematical basis of FBP and convolution kernels. Demonstrates how kernel choice balances noise and spatial resolution in reconstructed images.

  • Lesson 4 • Reconstruction Parameters and Image Quality

    Analyses field of view, matrix size, and slice thickness effects on image quality. Guides parameter selection to meet diagnostic requirements for specific anatomical regions.

Chapter 3See details

CT Image Quality and Artefacts

  • Lesson 1 • Spatial and Contrast Resolution

    Defines modulation transfer function and low-contrast detectability metrics. Establishes quantitative benchmarks for evaluating scanner and protocol performance.

  • Lesson 2 • Artefact Reduction Strategies

    Applies hardware, software, and protocol-based corrections to minimise artefacts. Reinforces image quality concepts by linking artefact type to targeted correction method.

  • Lesson 3 • Common CT Artefacts

    Catalogues beam hardening, partial volume, motion, and metal artefacts with visual examples. Provides systematic identification skills applicable to all anatomical regions.

  • Lesson 4 • Noise Sources and Quantum Mottle

    Identifies electronic, quantum, and structured noise contributions to CT images. Connects noise magnitude to exposure parameters and reconstruction choices.

Chapter 4See details

Radiation Dose in CT

  • Lesson 1 • Automatic Exposure Control

    Explains angular and z-axis tube current modulation systems and their dose-saving mechanisms. Connects AEC configuration to patient size and anatomy-specific dose optimisation.

  • Lesson 2 • ALARA Principles and Dose Optimisation

    Applies as-low-as-reasonably-achievable principles to CT protocol design. Integrates dose tracking, diagnostic reference levels, and justification into clinical workflow.

  • Lesson 3 • Exposure Parameter Effects on Dose

    Analyses how kVp, mAs, pitch, and rotation time influence patient dose. Enables informed parameter adjustments that reduce dose without sacrificing diagnostic quality.

  • Lesson 4 • Dose Metrics and Measurement

    Defines CTDI, DLP, and effective dose and explains their clinical relevance. Establishes a common dosimetric vocabulary for protocol comparison and reporting.

Chapter 5See details

Contrast Media in CT

  • Lesson 1 • Contrast Reactions and Management

    Classifies acute and delayed contrast reactions by severity and guides clinical response. Prepares technologists to recognise and initiate treatment for adverse events.

  • Lesson 2 • Iodinated Contrast Agent Properties

    Compares ionic vs. nonionic, high vs. low osmolality contrast agents and their safety profiles. Provides the pharmacological basis for contrast selection decisions.

  • Lesson 3 • Injection Techniques and Timing

    Covers power injector settings, bolus tracking, and test bolus methods for optimal enhancement. Links injection rate and volume to vascular and parenchymal enhancement patterns.

  • Lesson 4 • Contrast Safety Screening and Precautions

    Applies risk stratification for renal impairment, allergy history, and metformin use. Integrates pre-procedure screening into departmental safety workflows.

Chapter 6See details

CT Protocol Design and Optimisation

  • Lesson 1 • Abdomen, Pelvis, and Musculoskeletal Protocols

    Designs multiphase abdominal, pelvic, and extremity CT protocols. Addresses contrast timing, bowel preparation, and bone algorithm selection.

  • Lesson 2 • Head and Neck CT Protocols

    Develops protocols for brain, sinuses, temporal bones, and neck vasculature. Addresses region-specific challenges including bone-brain interface and dental artefact.

  • Lesson 3 • Chest and Cardiac CT Protocols

    Covers pulmonary, mediastinal, and cardiac CT protocol requirements. Integrates ECG gating, low-dose lung screening, and high-resolution chest techniques.

  • Lesson 4 • Protocol Design Principles

    Establishes the framework for selecting scan parameters based on clinical indication. Links diagnostic task requirements to specific technical parameter choices.

Chapter 7See details

Advanced CT Acquisition Techniques

  • Lesson 1 • Dual-Energy CT Principles

    Explains the physics of dual-energy acquisition and material decomposition algorithms. Establishes the technical foundation for all spectral CT clinical applications.

  • Lesson 2 • Dual-Energy Clinical Applications

    Applies dual-energy post-processing to gout, pulmonary embolism, renal stones, and oncology. Connects material-specific images to improved diagnostic confidence over single-energy CT.

  • Lesson 3 • Photon-Counting CT Technology

    Introduces photon-counting detector architecture and its spectral and resolution advantages. Positions this emerging technology relative to conventional energy-integrating detectors.

  • Lesson 4 • CT Perfusion Imaging

    Covers dynamic contrast acquisition and perfusion map generation for brain and oncology. Links cerebral blood flow and volume maps to stroke triage decision-making.

Chapter 8See details

CT Post-Processing and 3D Visualization

  • Lesson 1 • Multiplanar and Curved Reformations

    Creates coronal, sagittal, and oblique reformations and curved planar reconstructions. Demonstrates how reformation planes improve anatomical display beyond axial images alone.

  • Lesson 2 • Volume Rendering and Surface Shading

    Applies transfer function design and lighting parameters to produce volume-rendered images. Connects 3D visualisation to clinical communication and preoperative planning workflows.

  • Lesson 3 • Quantitative CT Analysis

    Applies volumetric segmentation and density histogram analysis for lesion and organ quantification. Links quantitative outputs to treatment response assessment and longitudinal monitoring.

  • Lesson 4 • Maximum and Minimum Intensity Projections

    Generates MIP and MinIP projections for vascular, pulmonary, and airway evaluation. Explains projection thickness and orientation choices for specific diagnostic tasks.

Certification

Your valid completion certificate

This course is for you:

  • Radiologic technologist: seeking to deepen CT-specific technical knowledge and skills.

  • Radiology student: preparing to enter clinical practice with a CT specialisation.

  • MRI technologist: transitioning into CT scanning roles within a hospital setting.

  • Medical imaging educator: updating curriculum with current CT technology and practices.

  • Radiologist assistant: strengthening understanding of CT acquisition and post-processing workflows.

  • Healthcare professional: moving into imaging department management or quality assurance roles.

What our students say

Your lessons are perfect. I purchased the one-year package and finally have the opportunity to follow various topics of my interest without needing to change platforms... I thank you for everything you do, I've already recommended you to other people...
Giulio Carlo
Giulio CarloDigital Marketing Student
I like how the lessons are straight to the point and how I can change chapters and skip content I don't need.
Mariana Ferres
Mariana FerresPhotography Student
I like the content and the way videos are presented and transcribed, which speeds up the process!
Luciana Alvarenga
Luciana AlvarengaNail Design Student
The platform is fast, simple to use. The diversity of content and complementary videos help a lot with learning.
André Felipe
André FelipePrompt Engineering Student

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