Related Experiment Video
Updated: May 18, 2026
12:08
From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
Published on: August 13, 2014
Digital images are data: and should be treated as such.
1Department of Cellular and Molecular Medicine, Southwest Environmental Health Sciences Center, Arizona Research Labs-Division of Biotechnology, Arizona Cancer Center, University of Arizona College of Medicine, Tuscon, AZ, USA. dcromey@email.arizona.edu
Methods in Molecular Biology (Clifton, N.J.)
|October 3, 2012
Summary
Scientific image manipulation is a growing concern, with 20-25% of papers containing non-compliant figures. Implementing clear image processing guidelines is crucial to maintain scientific integrity and public trust.
Area of Science:
- Scientific Integrity
- Image Analysis
- Research Ethics
Background:
- Growing concern in the scientific community regarding inappropriate image manipulation.
- Prevalence of non-compliant figures in published research, with 20-25% of papers containing at least one.
- Instances of fraudulent image manipulation reported in the scientific press, impacting trust and reputation.
Purpose of the Study:
- To address the issue of inappropriate image manipulation in scientific research.
- To provide guidance on proper digital image management and processing.
- To prevent unintentional misrepresentation and maintain the integrity of scientific data.
Main Methods:
- Review of existing literature and examples of image manipulation from related fields like photojournalism.
- Emphasis on understanding digital images as numerically sampled data.
- Proposal of image processing guidelines for scientists.
Main Results:
- Identification of a significant percentage of non-compliant figures in scientific publications.
- Highlighting the negative consequences of image manipulation on scientific record and public trust.
- Offering practical recommendations for managing and processing digital image data.
Conclusions:
- Inappropriate image manipulation poses a serious threat to scientific credibility.
- Scientists must treat digital image data with the same rigor as experimental protocols.
- Adherence to established image processing guidelines is essential for accurate scientific representation.
Related Concept Videos
01:18Imaging 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...
In optical microscopy, the specimen to be viewed is placed on a glass slide and clipped on the stage...
01:25Ethical Standards I
The American Nurses Association (ANA) created and implemented the first nationally accepted Code of Ethics for Nurses with Interpretive Statements. The Code of Ethics is a living document regularly updated by the ANA and establishes an ethical standard that is non-negotiable for nurses in all roles and settings.
The Code of Ethics provisions outline the nurse's duty to the patient, the healthcare team, the profession, and society. The Code's fundamental principles include advocacy,...
The Code of Ethics provisions outline the nurse's duty to the patient, the healthcare team, the profession, and society. The Code's fundamental principles include advocacy,...
01:26Phase Contrast and Differential Interference Contrast Microscopy
Phase-Contrast Microscopes
In-phase-contrast microscopes, interference between light directly passing through a cell and light refracted by cellular components is used to create high-contrast, high-resolution images without staining. It is the oldest and simplest type of microscope that creates an image by altering the wavelengths of light rays passing through the specimen. Altered wavelength paths are created using an annular stop in the condenser. The annular stop produces a hollow cone of...
In-phase-contrast microscopes, interference between light directly passing through a cell and light refracted by cellular components is used to create high-contrast, high-resolution images without staining. It is the oldest and simplest type of microscope that creates an image by altering the wavelengths of light rays passing through the specimen. Altered wavelength paths are created using an annular stop in the condenser. The annular stop produces a hollow cone of...
01:11How Data are Classified: Categorical Data
A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...
01:24X-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...
00:59How Data are Classified: Numerical Data
Data that are countable or measurable in specific units are called numerical or quantitative data. Quantitative data are always numbers. Quantitative data are the result of counting or measuring the attributes of a population. Amount of money, pulse rate, weight, number of people living in a town, and number of students who opt for statistics are examples of quantitative data.
Quantitative data may be either discrete or continuous. All quantitative data that take on only specific numerical...
Quantitative data may be either discrete or continuous. All quantitative data that take on only specific numerical...