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Related Concept Videos

Radiological Investigation I: X-ray and CT01:30

Radiological Investigation I: X-ray and CT

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 the...
Positron Emission Tomography01:29

Positron Emission Tomography

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.
One of the main requirements of a PET scan is a positron-emitting radioisotope, which is produced in a cyclotron and then attached to a substance used by the part of the body being...
X-ray Imaging01:24

X-ray Imaging

German physicist Wilhelm Röntgen (1845–1923) was experimenting with electrical current when he discovered that a mysterious and invisible "ray" would pass through his flesh but leave an outline of his bones on a screen coated with a metal compound. In 1895, Röntgen made the first durable record of the internal parts of a living human: an "X-ray" image (as it came to be called) of his wife’s hand. Scientists worldwide quickly began their own experiments with X-rays, and by 1900, X-ray was widely...
Radiological Investigation III: Pulmonary Angiogram and PET Scan01:13

Radiological Investigation III: Pulmonary Angiogram and PET Scan

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.
Pulmonary Angiogram
A Pulmonary Angiogram is an invasive procedure involving injecting a contrast medium through a catheter threaded into the pulmonary artery or the right side of the heart to visualize the pulmonary vasculature. Computed Tomography (CT) scans have mainly replaced this...
Computed Tomography01:10

Computed Tomography

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.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
Imaging Studies for Cardiovascular System III: X-Ray01:20

Imaging Studies for Cardiovascular System III: X-Ray

The most common cardiovascular diagnostic test is an X-ray. It produces images of the heart, blood vessels, and adjacent structures.
Definition and Purpose
An X-ray, or radiograph, is a non-invasive method that uses ionizing radiation to take images of internal structures. It is mainly used in cardiac imaging to examine the heart, lungs, and major blood vessels, aiming to identify abnormalities in the heart's size, shape, and position, such as heart failure, congenital defects, and vascular...

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Correction: Komatsu et al. Three-Dimensional Visualization and Detection of the Pulmonary Venous-Left Atrium Connection Using Artificial Intelligence in Fetal Cardiac Ultrasound Screening. <i>Bioengineering</i> 2026, <i>13</i>, 100.

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Related Experiment Video

Updated: May 28, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

LLaMA-XR: A Novel Framework for Radiology Report Generation Using LLaMA and QLoRA Fine Tuning.

Md Zihad Bin Jahangir1, Muhammad Ashad Kabir2, Sumaiya Akter3

  • 1Department of Computer Science and Engineering, Southeast University, Dhaka 1215, Bangladesh.

Bioengineering (Basel, Switzerland)
|May 27, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces LLaMA-XR, an AI system for automated radiology report generation from chest X-rays. LLaMA-XR significantly improves report accuracy and coherence, setting new performance benchmarks.

Keywords:
LLaMAchest X-rayfine-tuningradiologyreport generation

Related Experiment Videos

Last Updated: May 28, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

Area of Science:

  • Artificial Intelligence
  • Medical Imaging
  • Natural Language Processing

Background:

  • Automated radiology report generation aims to assist radiologists with chest radiograph interpretation.
  • Challenges include medical language complexity and correlating visual data with text.
  • Accurate and coherent report generation remains a significant hurdle in clinical practice.

Purpose of the Study:

  • To develop and evaluate LLaMA-XR, a novel framework for automated radiology report generation.
  • To leverage advanced AI models for improved accuracy and contextual relevance in radiology reports.

Main Methods:

  • LLaMA-XR integrates the Meta LLaMA 3.1 Large Language Model.
  • It utilizes DenseNet-121-based image embeddings for visual feature extraction.
  • Quantized Low-Rank Adaptation (QLoRA) fine-tuning optimizes model performance.

Main Results:

  • LLaMA-XR was evaluated on the IU X-ray dataset.
  • The framework demonstrated superior performance compared to existing state-of-the-art methods.
  • Achieved ROUGE-L score of 0.433 and METEOR score of 0.336, setting new benchmarks.

Conclusions:

  • LLaMA-XR shows significant potential as an effective AI system for automated radiology reporting.
  • The framework offers enhanced performance in generating descriptive and accurate reports.
  • This advancement could aid radiologists in their reporting tasks.