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Computed Tomography01:10

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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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Introduction: MRI and CT scans are crucial advancements in medical imaging techniques, playing a vital role in diagnosing conditions related to the gastrointestinal (GI) system. Each scan serves distinct purposes, targets specific areas, and requires unique nursing duties.
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Patch-based models and algorithms for image processing: a review of the basic principles and methods, and their

Davood Karimi1, Rabab K Ward2

  • 1, 2366 Main Mall, Vancouver, BC, V6T 1Z4, Canada. karimi@ece.ubc.ca.

International Journal of Computer Assisted Radiology and Surgery
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Patch-based methods offer powerful image processing for computed tomography (CT). These techniques show great potential for improving CT image reconstruction and processing, despite not being fully realized yet.

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Area of Science:

  • Image Processing
  • Medical Imaging
  • Computed Tomography (CT)

Background:

  • Image models are crucial for advancements in digital image processing.
  • Patch-based models have become highly effective for natural images over the past decade.
  • Increased computational power and concerns about radiation drive innovation in CT imaging algorithms.

Purpose of the Study:

  • To explain the principles of patch-based image processing methods.
  • To review recent applications of patch-based methods in computed tomography (CT).

Main Methods:

  • Review of core concepts in patch-based image processing.
  • Explanation of state-of-the-art patch-based algorithms relevant to CT.
  • Survey of recent patch-based method applications in CT.

Main Results:

  • Patch-based methods have significantly advanced image processing, achieving state-of-the-art results.
  • Emerging studies demonstrate patch-based algorithms' effectiveness in CT tasks like denoising, restoration, and iterative reconstruction.
  • The full potential of patch-based methods in CT applications remains largely unexplored.

Conclusions:

  • Patch-based methods are poised to be central to CT image reconstruction and processing.
  • These methods hold significant promise for enhancing the current capabilities of CT technology.