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Related Concept Videos

Ultrasound I: Abdominal Ultrasonography01:20

Ultrasound I: Abdominal Ultrasonography

220
Introduction:
Abdominal ultrasonography, commonly known as abdominal ultrasound, is a vital, non-invasive medical imaging technique widely used in healthcare.
Procedure:
This diagnostic tool allows the clinician to visually inspect internal structures within the abdomen, including vital organs such as the liver, gallbladder, pancreas, kidneys, and spleen.
The abdominal ultrasound process begins with applying a special gel to the patient's skin over the abdomen. This gel enhances the...
220
Ultrasonography01:17

Ultrasonography

4.5K
Ultrasonography is an imaging technique that uses high-frequency sound waves to visualize the body's internal structures. It is a non-invasive and safe procedure that does not involve the use of ionizing radiation, making it widely used in various medical fields. Ultrasonography is used to study heart function, blood flow in the neck or extremities, certain conditions such as gallbladder disease, and fetal growth and development.
During an ultrasonography procedure, a handheld device called...
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A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
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Artificial Intelligence for Breast US.

Juan C Villa-Camacho1, Masoud Baikpour1, Shinn-Huey S Chou1

  • 1Massachusetts General Hospital, Department of Radiology, Boston, MA, USA.

Journal of Breast Imaging
|February 28, 2024
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) enhances ultrasound (US) for breast cancer detection. AI tools improve diagnostic accuracy and workflow for radiologists using breast US.

Keywords:
artificial intelligencebreast cancer screeningcomputer-aided detectioncomputer-aided diagnosisultrasound

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Area of Science:

  • Radiology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Ultrasound (US) is a vital imaging tool for breast evaluations, particularly in low-resource settings for breast cancer detection.
  • US serves as a supplemental screening method for women with dense breasts, using handheld or automated approaches.
  • Recent advancements include AI systems designed to aid radiologists in identifying and diagnosing breast lesions on US.

Approach:

  • This review examines the foundational knowledge and evidence supporting AI applications in breast US.
  • It details strategies for integrating AI into clinical practice and its effects on radiologist workflow.
  • The article also explores prospective uses and future developments in AI for breast imaging.

Key Points:

  • AI is increasingly integrated into breast ultrasound (US) to assist radiologists.
  • Evidence supports AI's role in enhancing the detection and diagnosis of breast lesions.
  • Implementation strategies and workflow impacts are crucial considerations for AI adoption.

Conclusions:

  • AI holds significant promise for improving the efficacy and efficiency of breast US.
  • Future directions involve expanding AI's role in breast imaging and diagnostic capabilities.
  • Continued research and development are essential for optimizing AI tools in clinical practice.