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Related Concept Videos

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 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 III: Gastrointestinal Motility Studies and Virtual Colonoscopy01:26

Imaging Studies III: Gastrointestinal Motility Studies and Virtual Colonoscopy

This lesson explores three gastrointestinal imaging techniques: radionuclide testing, colonic transit studies, and virtual colonoscopy.
Radionuclide Testing
Radionuclide testing is a sophisticated medical technique for assessing gastrointestinal motility. It focuses on gastric emptying and colonic transit time. Radioactive markers track the movement of food through the digestive system, providing insights into gastrointestinal disorders.
In gastric emptying studies, a meal's liquid and solid...
Endoscopic Procedures III: Video Capsule Endoscopy01:28

Endoscopic Procedures III: Video Capsule Endoscopy

Capsule endoscopy, or wireless or video capsule endoscopy, is a diagnostic procedure for examining the entire gastrointestinal tract. Patients swallow a capsule about the size of a vitamin tablet. The capsule is equipped with a transmitter, a battery, an LED light source, and a color video camera to capture images throughout the gastrointestinal tract. This procedure is particularly useful for diagnosing conditions such as Crohn's disease, ulcerative colitis, tumors, polyps, ulcers, unexplained...
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...
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...

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Related Experiment Video

Updated: May 22, 2026

Label-free, High-Resolution 3D Imaging and Machine Learning Analysis of Intestinal Organoids via Low-Coherence Holotomography
10:40

Label-free, High-Resolution 3D Imaging and Machine Learning Analysis of Intestinal Organoids via Low-Coherence Holotomography

Published on: August 12, 2025

Seeing is believing: video classification for computed tomographic colonography using multiple-instance learning.

Shijun Wang1, Matthew T McKenna, Tan B Nguyen

  • 1National Institutes of Health, Bethesda, MD 20892, USA.

IEEE Transactions on Medical Imaging
|May 4, 2012
PubMed
Summary
This summary is machine-generated.

This study introduces a new method for classifying colonic polyps using computed tomographic colonography (CTC) videos. The novel approach significantly improves the accuracy of computer-aided detection (CAD) for polyps.

Related Experiment Videos

Last Updated: May 22, 2026

Label-free, High-Resolution 3D Imaging and Machine Learning Analysis of Intestinal Organoids via Low-Coherence Holotomography
10:40

Label-free, High-Resolution 3D Imaging and Machine Learning Analysis of Intestinal Organoids via Low-Coherence Holotomography

Published on: August 12, 2025

Area of Science:

  • Medical imaging
  • Artificial intelligence
  • Computational pathology

Background:

  • Computed tomographic colonography (CTC) is a key tool for colorectal cancer screening.
  • Computer-aided detection (CAD) systems aim to improve the accuracy of polyp detection in CTC.
  • Radiologists interpret CTC data using 3-D fly-through, offering insights for algorithm development.

Purpose of the Study:

  • To develop and test a novel colonic polyp classification method for CTC CAD systems.
  • To leverage video sequences of detected marks for improved classification accuracy.
  • To address the challenges of classifying CAD marks with varying viewpoints.

Main Methods:

  • Developed a video-based classification algorithm inspired by radiologist interpretation.
  • Framed polyp classification as a multiple-instance learning (MIL) problem.
  • Introduced a novel MIL paradigm to handle class-imbalanced instances within bags, solved via semidefinite programming and L2-norm soft margin maximization.

Main Results:

  • The proposed method was tested on a CTC dataset from 50 patients across three medical centers.
  • Significantly superior performance was observed compared to traditional MIL methods.
  • The algorithm demonstrated effective classification of colonic polyps from video data.

Conclusions:

  • The novel video-based MIL approach offers a significant advancement for colonic polyp classification in CTC CAD.
  • This method enhances the interpretability and accuracy of automated polyp detection systems.
  • The findings suggest potential for improved colorectal cancer screening through advanced AI in medical imaging.