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Related Concept Videos

Clinical Trials01:16

Clinical Trials

Clinical trials are prospective experimental studies conducted on humans to determine the safety and efficacy of treatments, drugs, diet methods, and medical devices. Using statistics in clinical trials enables researchers to derive reasonable and accurate conclusions from the collected data, allowing them to make wise decisions in uncertain situations. In medical research, statistical methods are crucial for preventing errors and bias.
There are four phases in a clinical trial. A phase one...
Clinical Trials: Overview01:11

Clinical Trials: Overview

Clinical development focuses on how the drug will interact with the human body and encompasses four key phases of clinical trials, each serving a specific purpose in assessing the safety and effectiveness of new drugs. These phases overlap and build upon one another. Phase I involves a small group of healthy volunteers (typically 20-80 individuals) or, in cases where significant toxicity is expected, patients with the targeted disease, such as cancer or AIDS. The volunteers are tested for...
Nursing Clinical Information System01:27

Nursing Clinical Information System

Nursing Clinical Information System (NCIS)
A Nursing Clinical Information System (NCIS) is a specialized type of healthcare information system tailored to meet the unique needs of nursing practice. It incorporates the principles of nursing informatics to streamline information management and improve the quality of care delivery.
Critical attributes of NCIS include:
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...
Imaging Biological Samples with Optical Microscopy01:18

Imaging Biological Samples with Optical Microscopy

Optical microscopy uses optic principles to provide detailed images of samples. Antonie van Leeuwenhoek designed the first compound optical microscope in the 17th century to visualize blood cells, bacteria, and yeast cells. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes with enhanced magnification and resolution.
In optical microscopy, the specimen to be viewed is placed on a glass slide and clipped on the stage...
ER Retrieval Pathway01:45

ER Retrieval Pathway

In the secretory pathway, vesicles transport proteins from one cellular compartment to another in forward transport to deliver the protein to its correct location. Occasionally, misfolded proteins and incorrect proteins escape their original compartments, and a retrieval pathway is used to return the escaped proteins to their original compartment.
The ER uses many checkpoints to prevent the entry of incorrectly folded or a resident protein as cargo onto a transport vesicle. These mechanisms...

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Related Experiment Video

Updated: May 29, 2026

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
05:33

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

Prototypes for content-based image retrieval in clinical practice.

Adrien Depeursinge1, Benedikt Fischer, Henning Müller

  • 1Business Information Systems, University of Applied Sciences Western Switzerland (HES-SO), TechnoArk 3, 3960 Sierre, Switzerland.

The Open Medical Informatics Journal
|September 6, 2011
PubMed
Summary
This summary is machine-generated.

Content-based image retrieval (CBIR) shows promise for computer-aided diagnostics (CAD). While CBIR systems exist for clinical practice, further development in performance, usability, and workflow integration is needed for widespread adoption.

Keywords:
Content-based image retrievaldiagnosis aidmedical image retrievalprototypes.

Related Experiment Videos

Last Updated: May 29, 2026

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
05:33

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

Area of Science:

  • Medical Imaging Informatics
  • Computer-Aided Diagnostics
  • Content-Based Image Retrieval

Background:

  • Content-based image retrieval (CBIR) is a key technology for computer-aided diagnostics (CAD).
  • This review examines the current state and future challenges of CBIR in clinical practice.
  • Applicability was assessed through systems demonstrated at major international conferences (SPIE, CARS, SIIM, RSNA, ISBI) from 2009-2011.

Purpose of the Study:

  • To review the state-of-the-art and future challenges of CBIR for CAD in clinical practice.
  • To analyze and compare CBIR systems based on identified gaps.
  • To determine the current applicability of CBIR in clinical settings.

Main Methods:

  • Analysis of 70 software demonstrations from CADdemo@CARS and SPIE Medical Imaging workshops (2009-2011).
  • Identification and comparison of systems meeting specific criteria.
  • Categorization of application fields and addressed gaps (semantics, feature extraction, feature structure, evaluation).

Main Results:

  • Five CBIR systems met the criteria for clinical applicability.
  • Application domains include bone age assessment, bone fractures, interstitial lung diseases, and mammography.
  • Bridging semantic, feature extraction, feature structure, and evaluation gaps were common focuses.

Conclusions:

  • CBIR technology is available for specific clinical applications.
  • System development is shifting from content/feature gaps to performance and usability.
  • Widespread clinical adoption requires larger reference datasets and seamless workflow integration.