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Related Concept Videos

Imaging Studies I: CT and MRI01:14

Imaging Studies I: CT and MRI

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.
Description of the Procedures
Computed Tomography (CT) scan:
Computed Tomography (CT) scans use X-ray technology to generate detailed images of bones, organs, and tissues. During the scan, the patient lies on a moving table...
Imaging Studies for Cardiovascular System IV: CMRI01:21

Imaging Studies for Cardiovascular System IV: CMRI

Cardiovascular magnetic resonance imaging, or CMRI, is a non-invasive diagnostic test that employs a magnetic field and radiofrequency waves to create precise images of the heart and arteries. It provides comprehensive information about cardiac anatomy, function, perfusion, and tissue characterization without ionizing radiation.IndicationsCMRI diagnoses various heart conditions, including tissue damage from heart attacks, ischemic heart disease, myocarditis, aortic issues (tears, aneurysms,...
Imaging Studies for Cardiovascular System V: CT01:28

Imaging Studies for Cardiovascular System V: CT

Cardiac computed tomography (CT) scanning is an advanced cardiac imaging technique that utilizes CT technology, with or without intravenous (IV) contrast, to produce accurate cross-sectional virtual slices of specific areas of the heart, coronary circulation, and major blood vessels such as the aorta, pulmonary veins, and arteries. The computer processes these slices to generate three-dimensional images. Multidetector CT (MDCT) is a rapid form of CT scanning that captures multiple slices...
Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

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...
Imaging Studies IV: Magnetic Resonance Imaging01:27

Imaging Studies IV: Magnetic Resonance Imaging

Introduction:Magnetic Resonance Imaging, or MRI, can include a specialized imaging technique of the urinary system known as Magnetic Resonance Urography (MRU). This radiation-free technique uses strong magnetic fields and radio waves to produce detailed images with the help of a computer. MRU is particularly effective for visualizing fluid-filled structures like the kidneys, ureters, and bladder.Applications of MRI in the Genitourinary SystemKidneys and Ureters: MRI detects tumors, cysts,...
Imaging Studies VII: Vascular Imaging01:19

Imaging Studies VII: Vascular Imaging

DefinitionRenal angiography, also known as renal arteriography, is an imaging technique used to obtain a comprehensive view of blood flow and the vascular structure of blood vessels in the kidneys and surrounding areas.PurposeRenal angiography detects blood vessel abnormalities in the kidneys, such as aneurysms, stenosis, thrombosis, vascular tumors, and renal artery stenosis. It evaluates kidney function and guides interventional treatments like angioplasty or stent placement.Pre-Procedure...

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A Systematic Review and Implementation Guidelines of Multimodal Foundation Models in Medical Imaging.

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  • 1Stanford University.

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Multimodal Foundation Models (FMs) using Self-Supervised Learning (SSL) advance AI in healthcare by reducing data needs. This review maps the field, identifying challenges and opportunities for responsible AI development.

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Area of Science:

  • Medical Artificial Intelligence
  • Machine Learning in Healthcare
  • Multimodal Data Analysis

Background:

  • Current AI in healthcare relies heavily on large labeled datasets and single data types, limiting progress.
  • Multimodal Foundation Models (FMs) utilizing Self-Supervised Learning (SSL) offer a promising approach for label-efficient, comprehensive patient modeling.

Purpose of the Study:

  • To systematically review multimodal FMs applied to medical imaging.
  • To establish unified terminology and assess the state-of-the-art in this rapidly evolving field.
  • To identify limitations and opportunities for future research and clinical translation.

Main Methods:

  • Systematic literature review of 1,144 publications from 2012-2024.
  • In-depth analysis of 48 selected studies on multimodal FMs in medical imaging.
  • Synthesis of findings to create a unified understanding and roadmap.

Main Results:

  • Identified a fragmented landscape of multimodal FM research.
  • Established a unified terminology for the field.
  • Assessed the current state-of-the-art, highlighting key limitations and underexplored areas.

Conclusions:

  • Multimodal FMs, especially with SSL, are crucial for overcoming data limitations in healthcare AI.
  • This review provides a roadmap for responsible development and clinical translation of advanced AI in medicine.
  • Actionable guidelines are offered for researchers, clinicians, developers, and policymakers.