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Computed Tomography01:10

Computed Tomography

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Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
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DefinitionComputed Tomography (CT) of the genitourinary (GU) tract is a non-invasive imaging modality that utilizes X-rays and computer processing to generate detailed cross-sectional images of the urinary system, encompassing the kidneys, ureters, bladder, and adjacent structures such as the adrenal glands.PurposeCT scans of the GU tract serve several diagnostic and therapeutic purposes, including:Diagnosis of Urinary Tract Diseases: Detects kidney stones, tumors, cysts, and congenital...
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Radiological investigations are paramount in the diagnosis and management of various pulmonary diseases. Two essential investigations are the Pulmonary Angiogram and the Positron Emission Tomography (PET) Scan.
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Positron Emission Tomography01:29

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Positron emission tomography (PET) is a medical imaging technique involving radiopharmaceuticals — substances that emit short-lived radiation. Although the first PET scanner was introduced in 1961, it took 15 more years before radiopharmaceuticals were combined with the technique and revolutionized its potential.
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Radiological Investigation II: MRI and Ventilation Perfusion Scan01:30

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Description
Magnetic Resonance Imaging (MRI) and Ventilation Perfusion Scans are two radiological investigations that offer detailed diagnostic images of the body, particularly lung structures.
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MRI uses magnetic fields and radiofrequency signals to distinguish between normal and abnormal tissues. This technology provides a more detailed diagnostic image than CT scans, enabling it to characterize pulmonary nodules, stage bronchogenic carcinoma, and evaluate inflammatory activity in...
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Radiological Investigation I: X-ray and CT01:30

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Radiological investigations, including X-rays and computed tomography (CT) scans, are critical for diagnosing and evaluating various medical conditions. These imaging techniques provide valuable insights into the body's internal structures, aiding in the detection of abnormalities, assessment of disease progression, and development of treatment strategies. This article delves into two primary radiological investigations, chest X-rays and CT scans, outlining their purpose, procedures, and...
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Updated: Dec 17, 2025

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Four-Dimensional Cone-Beam Computed Tomography Image Compression Using Video Encoder for Radiotherapy.

Hui Yan1, Yexiong Li1, Jianrong Dai2

  • 1Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.

Journal of Digital Imaging
|June 26, 2020
PubMed
Summary
This summary is machine-generated.

Video coding algorithms like MPEG-4 can significantly compress four-dimensional cone-beam computed tomography (4D-CBCT) images, reducing data storage and transfer needs for radiotherapy applications. This method enhances efficiency by ordering and filtering images before compression.

Keywords:
4D-CBCTImage compressionVideo coding algorithm

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Area of Science:

  • Medical Imaging
  • Radiotherapy Physics
  • Image Compression

Background:

  • Four-dimensional cone-beam computed tomography (4D-CBCT) is crucial for patient positioning and target localization in radiotherapy.
  • The large data volume of 4D-CBCT necessitates efficient data transfer and storage solutions.

Purpose of the Study:

  • To investigate the feasibility of applying video coding algorithms for compressing 4D-CBCT image data.
  • To evaluate the effectiveness of different video coding techniques and pre-processing methods.

Main Methods:

  • 4D-CBCT images were ordered by breathing phase or slice location.
  • Median filtering was applied to enhance image quality and reduce noise/artifacts.
  • Three video coding algorithms (Motion JPEG 2000, Motion JPEG AVI, MPEG-4) were tested on a public database.

Main Results:

  • MPEG-4 achieved the highest average compression ratio (135), significantly outperforming Motion JPEG AVI (16) and Motion JPEG 2000 (7).
  • Slice location-based ordering yielded slightly better compression rates than breathing phase ordering.
  • Median filtering improved inter-frame similarity, leading to increased compression rates.

Conclusions:

  • Video coding algorithms, particularly MPEG-4, are highly effective for compressing 4D-CBCT data, offering substantial benefits for radiotherapy.
  • Pre-processing techniques like median filtering and strategic image ordering enhance compression efficiency.
  • These video coding approaches are also applicable to serial 3D imaging modalities.